ENCYCLOPEDIA OF
OCEAN SCIENCES SECOND EDITION
Editor-in-chief
JOHN H. STEELE
Editors
STEVE A. THORPE KARL K. TUREKIAN
Boston • Heidelberg • London • New York • Oxford Paris • San Diego • San Francisco • Singapore • Sydney • Tokyo Academic Press is an imprint of Elsevier
(c) 2011 Elsevier Inc. All Rights Reserved.
ENCYCLOPEDIA OF
OCEAN SCIENCES SECOND EDITION
(c) 2011 Elsevier Inc. All Rights Reserved.
Subject Area Volumes from the Second Edition Climate & Oceans edited by Karl K. Turekian Elements of Physical Oceanography edited by Steve A. Thorpe Marine Biology edited by John H. Steele Marine Chemistry & Geochemistry edited by Karl K. Turekian Marine Ecological Processes edited by John H. Steele Marine Geology & Geophysics edited by Karl K. Turekian Marine Policy & Economics guest edited by Porter Hoagland, Marine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts Measurement Techniques, Sensors & Platforms edited by Steve A. Thorpe Ocean Currents edited by Steve A. Thorpe The Coastal Ocean edited by Karl K. Turekian The Upper Ocean edited by Steve A. Thorpe
(c) 2011 Elsevier Inc. All Rights Reserved.
ENCYCLOPEDIA OF
OCEAN SCIENCES SECOND EDITION Volume 6: T - Z Editor-in-chief
JOHN H. STEELE
Editors
STEVE A. THORPE KARL K. TUREKIAN
Boston • Heidelberg • London • New York • Oxford Paris • San Diego • San Francisco • Singapore • Sydney • Tokyo Academic Press is an imprint of Elsevier
(c) 2011 Elsevier Inc. All Rights Reserved.
Academic Press is an imprint of Elsevier 32 Jamestown Road, London NW1 7BY, UK 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA Copyright ^ 2009 Elsevier Ltd. All rights reserved
The following articles are US government works in the public domain and are not subject to copyright: Fish Predation and Mortality; International Organizations; Large Marine Ecosystems; Ocean Circulation: Meridional Overturning Circulation; Salt Marsh Vegetation; Satellite Passive-Microwave Measurements of Sea Ice; Satellite Oceanography, History and Introductory Concepts; Satellite Remote Sensing: Ocean Color; Science of Ocean Climate Models; Wind- and Buoyancy-Forced Upper Ocean. Fish Migration, Horizontal Crown Copyright 2001 Turbulence Sensors Canadian Crown Copyright 2001 No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher
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ISBN: 978-0-12-375044-0
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Editors
Editor-in-chief John H. Steele Marine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA
Editors Steve A. Thorpe National Oceanography Centre, University of Southampton Southampton, UK School of Ocean Sciences, University of Bangor, Menai Bridge, Anglesey, UK Karl K. Turekian Yale University, Department of Geology and Geophysics, New Haven, Connecticut, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
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Editorial Advisory Board John H. S. Blaxter Scottish Association for Marine Science Dunstaffnage Marine Laboratory Oban Argyll, UK Quentin Bone The Marine Biological Association of the United Kingdom Plymouth, UK Kenneth H. Brink Woods Hole Oceanographic Institution Woods Hole MA, USA Harry L. Bryden School of Ocean and Earth Science James Rennell Division University of Southampton Empress Dock Southampton, UK Robert Clark University of Newcastle upon Tyne Marine Sciences and Coastal Management Newcastle upon Tyne, UK J. Kirk Cochran State University of New York at Stony Brook Marine Sciences Research Center Stony Brook NY, USA Jeremy S. Collie Coastal Institute Graduate School of Oceanography University of Rhode Island South Ferry Road Narragansett RI, USA
Paul G. Falkowski Departments of Geological Sciences & Marine & Coastal Sciences Institute of Marine & Coastal Sciences School of Environmental & Biological Sciences Rutgers University New Brunswick NJ, USA Mike Fashamw Southampton Oceanography Centre University of Southampton Southampton UK John G. Field MArine REsearch (MA-RE) Institute University of Cape Town Rondebosch South Africa Michael Fogarty NOAA, National Marine Fisheries Service Woods Hole MA, USA Wilford D. Gardner Department of Oceanography Texas A&M University College Station TX, USA Ann Gargett Old Dominion University Center for Coastal Physical Oceanography Crittenton Hall Norfolk VA, USA
Peter J. Cook Australian Petroleum Cooperative Research Centre Canberra, Australia
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Robert A. Duce Departments of Oceanography and Atmospheric Sciences Texas A&M University College Station TX, USA
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deceased
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Editorial Advisory Board
Christopher Garrett University of Victoria Department of Physics Victoria British Columbia, Canada
Lindsay Lairdw Aberdeen University Zoology Department Aberdeen UK
W. John Gould Southampton Oceanography Centre University of Southampton Southampton UK
Peter S. Liss University of East Anglia School of Environmental Sciences Norwich, UK
John S. Grayw Institute of Marine Biology and Limnology University of Oslo Blindern Oslo, Norway
Ken Macdonald University of California Department of Geological Sciences Santa Barbara CA, USA
Gwyn Griffiths Southampton Oceanography Centre University of Southampton Southampton UK
Dennis McGillicuddy Woods Hole Oceanographic Institution Woods Hole MA, USA Alasdair McIntyre University of Aberdeen Department of Zoology Aberdeen UK
Stephen J. Hall World Fish Center Penang Malaysia Roger Harris Plymouth Marine Laboratory West Hoe Plymouth, UK Porter Hoagland Woods Hole Oceanographic Institution Woods Hole MA, USA George L. Hunt Jr. University of California, Irvine Department of Ecology and Evolutionary Biology Irvine CA, USA William J. Jenkins Woods Hole Oceanographic Institution Woods Hole MA, USA
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deceased
W. Kendall Melville Scripps Institution of Oceanography UC San Diego La Jolla CA, USA John Milliman College of William and Mary School of Marine Sciences Gloucester Point VA, USA James N. Moum College of Oceanic and Atmospheric Sciences Oregon State University Corvallis OR, USA Michael M. Mullinw Scripps Institution of Oceanography Marine Life Research Group University of California San Diego La Jolla CA, USA
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Editorial Advisory Board
Yoshiyuki Nozakiw University of Tokyo The Ocean Research Institute Nakano-ku Tokyo Japan
Ellen Thomas Yale University Department of Geology and Geophysics New Haven CT, USA
John Orcutt Scripps Institution of Oceanography Institute of Geophysics and Planetary Physics La Jolla CA, USA Richard F. Pittenger Woods Hole Oceanographic Institution Woods Hole MA, USA Gerold Siedler Universita¨t Kiel Institut fua¨r Meereskunde Kiel Germany
Peter L. Tyack Woods Hole Oceanographic Institution Woods Hole MA, USA Bruce A. Warren Woods Hole Oceanographic Institution Woods Hole MA, USA Wilford F. Weeks University of Alaska Fairbanks Department of Geology and Geophysics Fairbanks AK, USA
Robert C. Spindel University of Washington Applied Physics Laboratory Seattle WA, USA
Robert A. Weller Woods Hole Oceanographic Institution Woods Hole MA, USA
Colin P. Summerhayes Scientific Committee on Antarctic Research (SCAR) Scott Polar Institute Cambridge, UK
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Stewart Turner Australian National University Research School of Earth Sciences Canberra Australia
James A. Yoder Woods Hole Oceanographic Institution Woods Hole MA, USA
deceased
(c) 2011 Elsevier Inc. All Rights Reserved.
Preface to Second Print Edition The first edition of the Encyclopedia of Ocean Sciences, published in print form in 2001, has proven to be a valuable asset for the marine science community – and more generally. The continuing rapid increase in electronic access to academic material led us initially to publish the second edition electronically. We have now added this print version of the second edition because of a demonstrated need for such a product. The encyclopedia can now be accessed in print or electronic format according to the preferences and needs of individuals and institutions. In this edition there are 54 new articles, 67 revisions of previous articles, and a completely revised and improved index. We are grateful to the members of the Editorial Advisory Board, nearly all of whom have stayed with us during the lengthy process of going electronic. The transition from Academic Press to Elsevier occurred between the two editions. We thank Dr. Debbie Tranter of Elsevier for her efforts to see this edition through its final stages.
Preface to First Edition In 1942, a monumental volume was published on The Oceans by H. U. Sverdrup, M. W. Johnson, and R. H. Fleming. It was comprehensive and covered the knowledge at that time of the scientific study of the oceans. This seminal book helped to initiate the tremendous burgeoning of marine research that occurred during the following decades. The Encyclopedia of Ocean Sciences aims to embody the great growth of knowledge in a major new reference work. There have been remarkable new approaches to the study of the oceans that blur the distinctions between the physical, chemical, biological, and geological disciplines. New theories and technologies have expanded our knowledge of ocean processes. For example, plate tectonics has revolutionized our view not only of the geology and geophysics of the seafloor but also of ocean chemistry and biology. Satellite remote sensing provides a global vision as well as detailed understanding of the close coupling of ocean physics and biology at local and regional scales. Exploration, fishing, warfare, and the impact of storms have driven the past study of the seas, but we now have a great public awareness of and concern with broader social and economic issues affecting the oceans. For this reason, we have invited articles explicitly on marine policy and environmental topics, as well as encouraged authors to address these aspects of their particular subjects. We believe the encyclopedia should be of use to those involved with policy and management as well as to students and researchers. Over 400 scientists have contributed to this description of what we now know about the oceans. They are distinguished researchers who have generously shared their knowledge of this ever-growing body of science. We are extremely grateful to all these authors, whose ability to write concisely on complex subjects has generated a perspective on our science that we, as editors, believe will enhance the appreciation of the oceans, their uses, and the research ahead. It has been a major challenge for the members of the Editorial Advisory Board to cover such a heterogeneous subject. Their knowledge of the diverse areas of research has guaranteed comprehensive coverage of the ocean sciences. The Board contributed significantly by suggesting topics, persuading authors to contribute, and reviewing drafts. Many of them wrote Overviews that give broad descriptions of major parts of the ocean sciences. Clearly, it was the dedicated involvement of the Editorial Advisory Board that made this venture successful. Such a massive enterprise as a multivolume encyclopedia would not be possible without the long-term commitment of the staff of the Major Reference Works team at Academic Press. In particular, we are very grateful for the consistent support of our Senior Developmental Editor, Colin McNeil, who has worked so well with us throughout the whole process. Also, we are very pleased that new technology permits enhanced search and retrieval through the Internet. We believe this will make the encyclopedia much more accessible to individual researchers and students.
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Preface to Second Print Edition
In Memoriam During the creation of the Encyclopedia of Ocean Sciences and also in several cases prior to the publication of the electronic Second Edition, several Associate Editors or designated Associate Editors died. We specifically acknowledge their role in making this work an effective publication. They are Mike Fasham, John S. Gray, Lindsay Laird, Michael Mullin and Yoshiyuki Nozaki. J. H. Steele, S. A. Thorpe, and K. K. Turekian Editors
(c) 2011 Elsevier Inc. All Rights Reserved.
Guide to Use of the Encyclopedia
Introductory Points In devising the vision and structure for the Encyclopedia, the Editors have striven to unite and interrelate all current knowledge that can be designated ‘‘Ocean Sciences’’. To aid users of the Encyclopedia, this new reference work offers intuitive searching and extensive cross-linking of content. These features are explained in more detail below.
Structure of the Encyclopedia The material in the Encyclopedia is arranged as a series of articles in alphabetical order. To help you realize the full potential of the material in the Encyclopedia we have provided three features to help you find the topic of your choice.
1. Contents Lists Your first point of reference will probably be the contents list. The contents list appearing in each volume will provide you with the page number of the article. Alternatively you may choose to browse through a volume using the alphabetical order of the articles as your guide. To assist you in identifying your location within the Encyclopedia a running headline indicates the current article.
2. Cross References All of the articles in the encyclopedia have heen extensively cross referenced. The cross references, which appear at the end of each article, have heen provided at three levels: i. To indicate if a topic is discussed in greater detail elsewhere.
ACOUSTICS, ARCTIC See also: Acoustics in Marine Sediments. Acoustic Noise. Acoustics, Shallow Water. Arctic Ocean Circulation. Bioacoustics. Ice–ocean interaction. Nepheloid Layers. North Atlantic Oscillation (NAO). Ocean Circulation: Meridional Overturning Circulation. Platforms: Autonomous Underwater Vehicles. Satellite Passive-Microwave Measurements of Sea Ice. Sea Ice. Sea Ice: Overview. Seals. Seismic Structure. Tomography. Under-Ice Boundary Layer. Water Types and Water Masses.
ii. To draw the reader’s attention to parallel discussions in other articles. ACOUSTICS, ARCTIC See also: Acoustics in Marine Sediments. Acoustic Noise. Acoustics, Shallow Water. Arctic Ocean Circulation. Bioacoustics. Ice–ocean interaction. Nepheloid Layers. North Atlantic Oscillation (NAO). Ocean Circulation: Meridional Overturning Circulation. Platforms: Autonomous Underwater Vehicles. Satellite Passive-Microwave Measurements of Sea Ice. Sea Ice. Sea Ice: Overview. Seals. Seismic Structure. Tomography. Under-Ice Boundary Layer. Water Types and Water Masses.
(c) 2011 Elsevier Inc. All Rights Reserved.
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Guide to Use of the Encyclopedia
iii. To indicate material that broadens the discussion.
ACOUSTICS, ARCTIC See also: Acoustics in Marine Sediments. Acoustic Noise. Acoustics, Shallow Water. Arctic Ocean Circulation. Bioacoustics. Ice–ocean interaction. Nepheloid Layers. North Atlantic Oscillation (NAO). Ocean Circulation: Meridional Overturning Circulation. Platforms: Autonomous Underwater Vehicles. Satellite Passive-Microwave Measurements of Sea Ice. Sea Ice. Sea Ice: Overview. Seals. Seismic Structure. Tomography. Under-Ice Boundary Layer. Water Types and Water Masses.
3. Index The index will provide you with the volume and page number where the material is to be located, and the index entries differentiate between material that is a whole article, is part of an article or is data presented in a table or figure. On the opening page of the index detailed notes are provided.
4. Appendices In addition to the articles that form the main body of the encyclopedia, there are a number of appendices which provide bathymetric charts and lists of data used throughout the encyclopedia. The appendices are located in volume 6, before the index.
5. Contributors A full list of contributors appears at the beginning of volume 1.
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors Volume 1 E E Adams
N Caputi
Massachusetts Institute of Technology, Cambridge, MA, USA
Fisheries WA Research Division, North Beach, WA, Australia
T Akal
C A Carlson
NATO SACLANT Undersea Research Centre, La Spezia, Italy
University of California, Santa Barbara, CA, USA H Chamley
R Arimoto New Mexico State University, Carlsbad, NM, USA
Universite´ de Lille 1, Villeneuve d’Ascq, France R Chester
J L Bannister The Western Australian Museum, Perth, Western Australia
Liverpool University, Liverpool, Merseyside, UK V Christensen University of British Columbia, Vancouver, BC, Canada
E D Barton University of Wales, Bangor, UK
J W Dacey
N R Bates Bermuda Biological Station for Research, St George’s, Bermuda, USA
Woods Hole Oceanographic Institution, Woods Hole, MA, USA R A Duce
A Beckmann
Texas A&M University, College Station, TX, USA
Alfred-Wegener-Institut fu¨r Polar und Meeresforschung, Bremerhaven, Germany
H W Ducklow
P S Bell
The College of William and Mary, Gloucester Point, VA, USA
Proudman Oceanographic Laboratory, Liverpool, UK I Dyer G Birnbaum
Marblehead, MA, USA
Alfred-Wegener-Institut fu¨r Polar und Meeresforschung, Bremerhaven, Germany
D W Dyrssen Gothenburg University, Go¨teborg, Sweden
B O Blanton The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA E A Boyle Massachusetts Institute of Technology, Cambridge, MA, USA
S M Evans Newcastle University, Newcastle, UK I Everson Anglia Ruskin University, Cambridge, UK
P Boyle
J W Farrington
University of Aberdeen, Aberdeen, UK
Woods Hole Oceanographic Institution, MA, USA
D M Bush
M Fieux
State University of West Georgia, Carrollton, GA, USA
Universite´ Pierre et Marie Curie, Paris, France
K Caldeira
R A Fine
Stanford University, Stanford, CA, USA
University of Miami, Miami, FL, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contributors
K G Foote Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA L Franc¸ois University of Lie`ge, Lie`ge, Belgium M A M Friedrichs Old Dominion University, Norfolk, VA, USA T Gaston National Wildlife Research Centre, Quebec, Canada J Gemmrich University of Victoria, Victoria, BC, Canada Y Godde´ris University of Lie`ge, Lie`ge, Belgium D R Godschalk University of North Carolina, Chapel Hill, NC, USA A J Gooday Southampton Oceanography Centre, Southampton, UK A L Gordon Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA D A Hansell University of Miami, Miami FL, USA L W Harding Jr University of Maryland, College Park, MD, USA R Harris Plymouth Marine Laboratory, Plymouth, UK P J Herring Southampton Oceanography Centre, Southampton, UK B M Hickey University of Washington, Seattle, WA, USA M A Hixon Oregon State University, Corvallis, OR, USA E E Hofmann Old Dominion University, Norfolk, VA, USA S Honjo Woods Hole Oceanographic Institution, Woods Hole, MA, USA D J Howell Newcastle University, Newcastle, UK J M Huthnance CCMS Proudman Oceanographic Laboratory, Wirral, UK B Ja¨hne University of Heidelberg, Heidelberg, Germany F B Jensen SACLANT Undersea Research Centre, La Spezia, Italy A John Sir Alister Hardy Foundation for Ocean Science, Plymouth, UK
C D Jones University of Washington, Seattle, WA, USA P F Kingston Heriot-Watt University, Edinburgh, UK W Krauss Institut fu¨r Meereskunde an der Universita¨t Kiel, Kiel, Germany W A Kuperman Scripps Institution of Oceanography, University of California, San Diego, CA, USA D Lal Scripps Institute of Oceanography, University of California San Diego, La Jolla, CA, USA C S Law Plymouth Marine Laboratory, The Hoe, Plymouth, UK W J Lindberg University of Florida, Gainesville, FL, USA J R E Lutjeharms University of Cape Town, Rondebosch, South Africa P Malanotte-Rizzoli Massachusetts Institute of Technology, Cambridge, MA, USA W R Martin Woods Hole Oceanographic Institution, Woods Hole, MA, USA R P Matano Oregon State University, Corvallis, OR, USA J W McManus University of Miami, Miami, FL, USA G M McMurtry University of Hawaii at Manoa, Honolulu, HI, USA R Melville-Smith Fisheries WA Research Division, North Beach, WA, Australia P N Mikhalevsky Science Applications International Corporation, McLean, VA, USA W D Miller University of Maryland, College Park, MD, USA D Monahan University of New Hampshire, Durham, NH, USA J C Moore University of California at Santa Cruz, Santa Cruz, CA, USA A Morel Universite´ Pierre et Marie Curie, Villefranche-sur-Mer, France R Narayanaswamy The University of Manchester, Manchester, UK
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors W J Neal Grand Valley State University, Allendale, MI, USA D Pauly University of British Columbia, Vancouver, BC, Canada J W Penn Fisheries WA Research Division, North Beach, WA, Australia L C Peterson University of Miami, Miami, FL, USA S G Philander Princeton University, Princeton, NJ, USA N J Pilcher Universiti Malaysia Sarawak, Sarawak, Malaysia O H Pilkey Duke University, Durham, NC, USA
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D H Shull Western Washington University, Bellingham, WA, USA D K Steinberg College of William and Mary, Gloucester Pt, VA, USA L Stramma University of Kiel, Kiel, Germany R N Swift NASA Goddard Space Flight Center, Wallops Island, VA, USA T Takahashi Lamont Doherty Earth Observatory, Columbia University, Palisades, NY, USA P D Thorne Proudman Oceanographic Laboratory, Liverpool, UK
A R Piola Universidad de Buenos Aires, Buenos Aires, Argentina J M Prospero University of Miami, Miami, FL, USA S Rahmstorf Potsdam Institute for Climate Impact Research, Potsdam, Germany P C Reid SAHFOS, Plymouth, UK G Reverdin LEGOS, Toulouse Cedex, France S R Rintoul CSIRO Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, TAS, Australia J M Roberts Scottish Association for Marine Science, Oban, UK P A Rona Rutgers University, New Brunswick, NJ, USA T C Royer Old Dominion University, Norfolk, VA, USA B Rudels Finnish Institute of Marine Research, Helsinki, Finland
P L Tyack Woods Hole Oceanographic Institution, Woods Hole, USA T Tyrrell National Oceanography Centre, Southampton, UK F E Werner The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA E A Widder Harbor Branch Oceanographic Institution, Fort Pierce, FL, USA D J Wildish Fisheries and Oceans Canada, St. Andrews, NB, Canada A J Williams, III Woods Hole Oceanographic Institution, Woods Hole, MA, USA D K Woolf Southampton Oceanography Centre, Southampton, UK
W Seaman University of Florida, Gainesville, FL, USA
C W Wright NASA Goddard Space Flight Center, Wallops Island, VA, USA
F Sevilla, III, University of Santo Tomas, Manila,The Philippines
J D Wright Rutgers University, Piscataway, NJ, USA
L V Shannon University of Cape Town, Cape Town, South Africa
J R Young The Natural History Museum, London, UK
G I Shapiro University of Plymouth, Plymouth, UK
H J Zemmelink University of Groningen, Haren, The Netherlands
A D Short University of Sydney, Sydney, Australia
W Zenk Universita¨t Kiel, Kiel, Germany
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contributors
Volume 2 G P Arnold Centre for Environment, Fisheries & Aquaculture Science, Suffolk, UK
K Dyer University of Plymouth, Plymouth, UK
K M Bailey Alaska Fisheries Science Center, Seattle, WA, USA
M Elliott Institute of Estuarine and Coastal Studies, University of Hull, Hull, UK
J G Baldauf Texas A&M University, College Station, TX, USA
D M Farmer Institute of Ocean Sciences, Sidney, BC, Canada
J Bascompte CSIC, Seville, Spain
A V Fedorov Yale University, New Haven, CT, USA
A Belgrano Institute of Marine Research, Lysekil, Sweden
M J Fogarty Northeast Fisheries Science Center, National Marine Fisheries Service, Woods Hole, MA, USA
O A Bergstad Institute of Marine Research, Flødevigen His, Norway J H S Blaxter Scottish Association for Marine Science, Argyll, UK
R Fonteyne Agricultural Research Centre, Ghent, Oostende, Belgium
Q Bone The Marine Biological Association of the United Kingdom, Plymouth, UK
D J Fornari Woods Hole Oceanographic Institution, Woods Hole, USA
I Boyd University of St. Andrews, St. Andrews, UK
A E Gargett Old Dominion University, Norfolk, VA, USA
K M Brander DTU Aqua, Charlottenlund, Denmark and International Council for the Exploration of the Sea (ICES), Copenhagen, Denmark
C H Gibson University of California, San Diego, La Jolla, CA, USA
J N Brown Yale University, New Haven, CT, USA T K Chereskin University of California San Diego, La Jolla, CA, USA J S Collie Danish Institute for Fisheries Research, Charlottenlund, Denmark and University of Rhode Island, Narragansett, RI, USA G Cresswell CSIRO Marine Research, Tasmania, Australia
J D M Gordon Scottish Association for Marine Science, Argyll, UK J F Grassle Rutgers University, New Brunswick, New Jersey, USA S J Hall Flinders University, Adelaide, SA, Australia N Hanson University of St. Andrews, St. Andrews, UK P J B Hart University of Leicester, Leicester, UK
J Davenport University College Cork, Cork, Ireland
K R Helfrich Woods Hole Oceanographic Institution, Woods Hole, MA, USA
R H Douglas City University, London, UK
D M Higgs University of Windsor, Windsor, ON, Canada
S Draxler Karl-Franzens-Universita¨t Graz, Graz, Austria
N G Hogg Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J T Duffy-Anderson Alaska Fisheries Science Center, Seattle, WA, USA J A Dunne Santa Fe Institute, Santa Fe, NM, USA and Pacific Ecoinformatics and Computational Ecology Lab, Berkely, CA, USA
E D Houde University of Maryland, Solomons, MD, USA V N de Jonge Department of Marine Biology, Groningen University, Haren, The Netherlands
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors K Katsaros Atlantic Oceanographic and Meteorological Laboratory, NOAA, Miami, FL, USA J M Klymak University of Victoria, Victoria, BC, Canada M Kucera Eberhard Karls Universita¨t Tu¨bingen, Tu¨bingen, Germany R S Lampitt University of Southampton, Southampton, UK J R N Lazier Bedford Institute of Oceanography, NS, Canada J R Ledwell Woods Hole Oceanographic Institution, Woods Hole, MA, USA P F J Lermusiaux Harvard University, Cambridge, MA, USA M E Lippitsch Karl-Franzens-Universita¨t Graz, Graz, Austria
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T J Pitcher University of British Columbia, Vancouver, Canada A N Popper University of Maryland, College Park, MD, USA J F Price Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA R D Prien Southampton Oceanography Centre, Southampton, UK A-L Reysenbach Portland State University, Portland, OR, USA P L Richardson Woods Hole Oceanographic Institution, Woods Hole, MA, USA A R Robinson Harvard University, Cambridge, MA, USA M D J Sayer Dunstaffnage Marine Laboratory, Oban, Argyll, UK
B J McCay Rutgers University, New Brunswick, NJ, USA
R W Schmitt Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J D McCleave University of Maine, Orono, ME, USA
J Scott DERA Winfrith, Dorchester, Dorset, UK
D Minchin Marine Organism Investigations, Killaloe, Republic of Ireland
M P Sissenwine Northeast Fisheries Science Center, Woods Hole, MA, USA
C M Moore University of Essex, Colchester, UK K Moran University of Rhode Island, Narragansett, RI, USA G R Munro University of British Columbia, Vancouver, BC, Canada J D Nash Oregon State University, Corvallis, Oregon, OR, USA A C Naveira Garabato University of Southampton, Southampton, UK
T P Smith Northeast Fisheries Science Center, Woods Hole, MA, USA P V R Snelgrove Memorial University of Newfoundland, St John’s, NL, Canada M A Spall Woods Hole Oceanographic Institution, Woods Hole, MA, USA A Stigebrandt University of Gothenburg, Gothenburg, Sweden D A V Stow University of Southampton, Southampton, UK
J D Neilson Department of Fisheries and Oceans, New Brunswick, Canada
D J Suggett University of Essex, Colchester, UK
Y Nozakiw University of Tokyo, Tokyo, Japan
U R Sumaila University of British Columbia, Vancouver, BC, Canada
R I Perry Department of Fisheries and Oceans, British Columbia, Canada S G Philander Princeton University, Princeton, NJ, USA w
Deceased.
K S Tande Norwegian College of Fishery Science, Tromsø, Norway S A Thorpe National Oceanography Centre, Southampton, UK R S J Tol Economic and Social Research Institute, Dublin, Republic of Ireland
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contributors
K E Trenberth National Center for Atmospheric Research, Boulder, CO, USA J J Videler Groningen University, Haren, The Netherlands
R S Wells Chicago Zoological Society, Sarasota, FL, USA D C Wilson Institute for Fisheries Management and Coastal Community Development, Hirtshals, Denmark
Volume 3 S Ali Plymouth Marine Laboratory, Plymouth, UK
K H Coale Moss Landing Marine Laboratories, CA, USA
J T Andrews University of Colorado, Boulder, CO, USA
M F Coffins University of Texas at Austin, Austin, TX, USA
M A de Angelis Humboldt State University, Arcata, CA, USA
P J Corkeron James Cook University, Townsville, Australia
A J Arp Romberg Tiburon Center for Environment Studies, Tiburon, CA, USA
B C Coull University of South Carolina, Columbia, SC, USA
T Askew Harbor Branch Oceanographic Institute, Ft Pierce, FL, USA
R Cowen University of Miami, Miami, FL, USA
R D Ballard Institute for Exploration, Mystic, CT, USA
G Cresswell CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia
G Barnabe´ Universite´ de Montpellier II, France
D S Cronan Royal School of Mines, London, UK
R S K Barnes University of Cambridge, Cambridge, UK
J Csirke Food and Agriculture Organization of the United Nations, Rome, Italy
E D Barton University of Wales, Bangor, Menai Bridge, Anglesey, UK
G A Cutter Old Dominion University, Norfolk, VA, USA
D Bhattacharya University of Iowa, Iowa City, IA, USA
D J DeMaster North Carolina State University, Raleigh, NC, USA
F von Blanckenburg Universita¨t Bern, Bern, Switzerland
T D Dickey University of California, Santa Barbara, CA, USA
D R Bohnenstiehl North Carolina State University, Raleigh, NC, USA
D Diemand Coriolis, Shoreham, VT, USA
H L Bryden University of Southampton, Southampton, UK J Burger Rutgers University, Piscataway, NJ, USA S M Carbotte Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA G T Chandler University of South Carolina, Columbia, SC, USA M A Charette Woods Hole Oceanographic Institution, Woods Hole, MA, USA
C S M Doake British Antarctic Survey, Cambridge, UK C M Domingues CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia C J Donlon Space Applications Institute, Ispra, Italy F Doumenge Muse´e Oce´anographique de Monaco, Monaco R A Dunn University of Hawaii at Manoa, Honolulu, HI, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors R P Dziak Oregon State University/National Oceanic and Atmospheric Administration, Hatfield Marine Science Center, Newport, OR, USA O Eldholm University of Oslo, Oslo, Norway
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S K Hooker University of St. Andrews, St. Andrews, UK H Hotta Japan Marine Science & Technology Center, Japan G R Ierley University of California San Diego, La Jolla, CA, USA
A E Ellis Marine Laboratory, Aberdeen, Scotland, UK C R Engle University of Arkansas at Pine Bluff, Pine Bluff, AR, USA C C Eriksen University of Washington, Seattle, WA, USA V Ettwein University College London, London, UK S Farrow Carnegie Mellon University, Pittsburgh, PA, USA M Fieux Universite´ Pierre et Marie Curie, Paris Cedex, France N Forteath Inspection Head Wharf, TAS, Australia J D Gage Scottish Association for Marine Science, Oban, UK S M Garcia Food and Agriculture Organization of the United Nations, Rome, Italy
G Ito University of Hawaii at Manoa, Honolulu, HI, USA J Jacoby Woods Hole Oceanographic Institution, Woods Hole, MA, USA M J Kaiser Bangor University, Bangor, UK A E S Kemp University of Southampton, Southampton Oceanography Centre, Southampton, UK W M Kemp University of Maryland Center for Environmental Science, Cambridge, MD, USA V S Kennedy University of Maryland, Cambridge, MD, USA P F Kingston Heriot-Watt University, Edinburgh, UK G L Kooyman University of California San Diego, CA, USA
C Garrett University of Victoria, VIC, Canada
W Krijgsman University of Utrecht, Utrecht, The Netherlands
R N Gibson Scottish Association for Marine Science, Argyll, Scotland
J B Kristoffersen University of Bergen, Bergen, Norway
M Gochfeld Environmental and Community Medicine, Piscataway, NJ, USA
K Lambeck Australian National University, Canberra, ACT, Australia
H O Halvorson University of Massachusetts Boston, Boston, MA, USA
R S Lampitt University of Southampton, Southampton, UK
B U Haq Vendome Court, Bethesda, MD, USA
M Landry University of Hawaii at Manoa, Department of Oceanography, Honolulu, HI, USA
G R Harbison Woods Hole Oceanographic Institution, Woods Hole, MA, USA
C G Langereis University of Utrecht, Utrecht, The Netherlands A Lascaratos University of Athens, Athens, Greece
R M Haymon University of California, CA, USA
S Leibovich Cornell University, Ithaca, NY, USA
D L Hebert University of Rhode Island, RI, USA J E Heyning The Natural History Museum of Los Angeles County, Los Angeles, CA, USA P Hoagland Woods Hole Oceanographic Institution, Woods Hole, MA, USA
W G Leslie Harvard University, Cambridge, MA, USA C Llewellyn Plymouth Marine Laboratory, Plymouth, UK R A Lutz Rutgers University, New Brunswick, NJ, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
xx
Contributors
K C Macdonald Department of Geological Sciences and Marine Sciences Institute, University of California, Santa Barbara, CA, USA F T Mackenzie University of Hawaii, Honolulu, HI, USA L P Madin Woods Hole Oceanographic Institution, Woods Hole, MA, USA M Maslin University College London, London, UK G A Maul Florida Institute of Technology, Melbourne, FL, USA M McNutt MBARI, Moss Landing, CA, USA M G McPhee McPhee Research Company, Naches, WA, USA A D Mclntyre University of Aberdeen, Aberdeen, UK J Mienert University of Tromsø, Tromsø, Norway G E Millward University of Plymouth, Plymouth, UK H Momma Japan Marine Science & Technology Center, Japan J H Morison University of Washington, Seattle, WA, USA A E Mulligan Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J E Petersen Oberlin College, Oberlin, OH, USA M Phillips Network of Aquaculture Centres in Asia-Pacific (NACA), Bangkok, Thailand B Qiu University of Hawaii at Manoa, Hawaii, USA F Quezada Biotechnology Center of Excellence Corporation, Waltham, MA, USA N N Rabalais Louisiana Universities Marine Consortium, Chauvin, LA, USA R D Ray NASA Goddard Space Flight Center, Greenbelt, MD, USA M R Reeve National Science Foundation, Arlington VA, USA R R Reeves Okapi Wildlife Associates, QC, Canada A Reyes-Prieto University of Iowa, Iowa City, IA, USA P B Rhines University of Washington,Seattle, WA, USA A R Robinson Harvard University, Cambridge, MA, USA H T Rossby University of Rhode Island, Kingston, RI, USA H M Rozwadowski Georgia Institute of Technology, Atlanta, Georgia, USA
W Munk University of California San Diego, La Jolla, CA, USA
A G V Salvanes University of Bergen, Bergen, Norway
E J Murphy British Antarctic Survey, Marine Life Sciences Division, Cambridge, UK
R Schlitzer Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
P D Naidu National Institute of Oceanography, Dona Paula, India
M E Schumacher Woods Hole Oceanographic Institution, Woods Hole, MA, USA
N Niitsuma Shizuoka University, Shizuoka, Japan
M I Scranton State University of New York, Stony Brook, NY, USA
D B Olson University of Miami, Miami, FL, USA G-A Paffenho¨fer Skidaway Institute of Oceanography, Savannah, GA, USA C Paris University of Miami, Miami, FL, USA M R Perfit Department of Geological Sciences, University of Florida, Gainsville, FL, USA
K Sherman Narragansett Laboratory, Narragansett, RI, USA M D Spalding UNEP World Conservation Monitoring Centre and Cambridge Coastal Research Unit, Cambridge, UK J Sprintall University of California San Diego, La Jolla, CA, USA J H Steele Woods Hole Oceanographic Institution, MA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors C A Stein University of Illinois at Chicago, Chicago, IL, USA
S M Van Parijs Norwegian Polar Institute, Tromsø, Norway
C Stickley University College London, London, UK
L M Ver University of Hawaii, Honolulu, HI, USA
U R Sumaila University of British Columbia, Vancouver, BC, Canada
F J Vine University of East Anglia, Norwich, UK
S Takagawa Japan Marine Science & Technology Center, Japan
K L Von Damm University of New Hampshire, Durham, NH, USA
P K Taylor Southampton Oceanography Centre, Southampton, UK
R P Von Herzen Woods Hole Oceanographic Institution, Woods Hole, MA, USA
A Theocharis National Centre for Marine Research (NCMR), Hellinikon, Athens, Greece
xxi
D Wartzok Florida International University, Miami, FL, USA
P C Ticco Massachusetts Maritime Academy, Buzzards Bay, MA, USA R P Trask Woods Hole Oceanographic Institution, Woods Hole, MA, USA
W F Weeks Portland, OR, USA R A Weller Woods Hole Oceanographic Institution, Woods Hole, MA, USA
A W Trites University of British Columbia, British Columbia, Canada
J A Whitehead Woods Hole Oceanographic Institution, Woods Hole, MA, USA
A Turner University of Plymouth, Plymouth, UK
J C Wiltshire University of Hawaii, Manoa, Honolulu, HA, USA
P L Tyack Woods Hole Oceanographic Institution, Woods Hole, MA, USA
C Woodroffe University of Wollongong, Wollongong, NSW, Australia
G J C Underwood University of Essex, Colchester, UK
C Wunsch Massachusetts Institute of Technology, Cambridge, MA, USA
C L Van Dover The College of William and Mary, Williamsburg, VA, USA
H S Yoon University of Iowa, Iowa City, IA, USA
Volume 4 A Alldredge University of California, Santa Barbara, CA, USA D M Anderson Woods Hole Oceanographic Institution, Woods Hole, MA, USA O R Anderson Columbia University, Palisades, NY, USA
J M Bewers Bedford Institute of Oceanography, Dartmouth, NS, Canada N V Blough University of Maryland, College Park, MD, USA W Bonne
P G Baines CSIRO Atmospheric Research, Aspendale, VIC, Australia
Federal Public Service Health, Food Chain Safety and Environment, Brussels, Belgium
J M Baker Clock Cottage, Shrewsbury, UK
University of Cape Town, Cape Town, Republic of South Africa
J G Bellingham Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA
R D Brodeur
G M Branch
Northwest Fisheries Science Center, Newport, OR, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
xxii
Contributors
H Burchard Baltic Sea Research Institute Warnemu¨nde, Warnemu¨nde, Germany P H Burkill Plymouth Marine Laboratory, West Hoe, Plymouth, UK Francois Carlotti C.N.R.S./Universite´ Bordeaux 1, Arachon, France K L Casciotti Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J S Grayw University of Oslo, Oslo, Norway A G Grottoli University of Pennsylvania, Philadelphia, PA, USA N Gruber Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Switzerland K C Hamer University of Durham, Durham, UK D Hammond University of Southern California, Los Angeles, CA, USA
A Clarke British Antarctic Survey, Cambridge, UK
W W Hay Christian-Albrechts University, Kiel, Germany
M B Collins National Oceanography Centre, Southampton, UK
J W Heath Coastal Fisheries Institute, CCEER Louisiana State University, Baton Rouge, LA, USA
J J Cullen Department of Oceanography, Halifax, NS, Canada D H Cushing Lowestoft, Suffolk, UK
D Hedgecock University of Southern California, Los Angeles, CA, USA C Hemleben Tu¨bingen University, Tu¨bingen, Germany
K L Denman University of Victoria, Victoria, BC, Canada S C Doney Woods Hole Oceanographic Institution, Woods Hole, MA, USA
T D Herbert Brown University, Providence, RI, USA I Hewson University of California Santa Cruz, Santa Cruz, CA, USA
J F Dower University of British Columbia, Vancouver, BC, Canada
Richard Hey University of Hawaii at Manoa, Honolulu, HI, USA
K Dysthe University of Bergen, Bergen, Norway
P Hoagland Woods Hole Oceanographic Institution, Woods Hole, MA, USA
H N Edmonds University of Texas at Austin, Port Aransas, TX, USA
N Hoepffner Institute for Environment and Sustainability, Ispra, Italy
L Føyn Institute of Marine Research, Bergen, Norway
M Hood Intergovernmental Oceanographic Commission, Paris, France
J Fuhrman University of Southern California, Los Angeles, CA, USA
M J Howarth Proudman Oceanographic Laboratory, Wirral, UK
C P Gallienne Plymouth Marine Laboratory, West Hoe, Plymouth, UK
M Huber Purdue University, West Lafayette, IN, USA
E Garel CIACOMAR, Algarve University, Faro, Portugal
J W Hurrell National Center for Atmospheric Research, Boulder, CO, USA
D M Glover Woods Hole Oceanographic Institution, Woods Hole, MA, USA S L Goodbred Jr State University of New York, Stony Brook, NY, USA J D M Gordon Scottish Association for Marine Science, Oban, Argyll, UK
D R Jackett CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia R A Jahnke Skidaway Institute of Oceanography, Savannah, GA, USA w
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors
xxiii
A Jarre University of Cape Town, Cape Town, South Africa
A F Michaels University of Southern California, Los Angeles, CA, USA
J Joseph La Jolla, CA, USA
J D Milliman College of William and Mary, Gloucester, VA, USA
D M Karl University of Hawaii at Manoa, Honolulu, HI, USA
C D Mobley Sequoia Scientific, Inc., WA, USA
K L Karsh Princeton University, Princeton, NJ, USA
M M Mullinw Scripps Institution of Oceanography, La Jolla, CA, USA
J Karstensen Universita¨t Kiel (IFM-GEOMAR), Kiel, Germany
P Mu¨ller University of Hawaii, Honolulu, HI, USA
R M Key Princeton University, Princeton, NJ, USA
L A Murray The Centre for Environment, Fisheries and Aquaculture Sciences, Lowestoft, UK
P D Killworth Southampton Oceanography Centre, Southampton, UK B Klinger Center for Ocean-Land-Atmosphere Studies (COLA), Calverton, MD, USA H E Krogstad NTNU, Trondheim, Norway I Laing Centre for Environment Fisheries and Aquaculture Science, Weymouth, UK
T Nagai Tokyo University of Marine Science and Technology, Tokyo, Japan K H Nisancioglu Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway Y Nozakiw University of Tokyo, Tokyo, Japan
G F Lane-Serff University of Manchester, Manchester, UK
K J Orians The University of British Columbia, Vancouver, BC, Canada
A Longhurst Place de I’Eglise, Cajarc, France
C A Paulson Oregon State University, Corvallis, OR, USA
R Lukas University of Hawaii at Manoa, Hawaii, USA
W G Pearcy Oregon State University, Corvallis, OR, USA
M Lynch University of California Santa Barbara, Santa Barbara, CA, USA
W S Pegau Oregon State University, Corvallis, OR, USA
M Macleod World Wildlife Fund, Washington, DC, USA E Maran˜o´n University of Vigo, Vigo, Spain S Martin University of Washington, Seattle, WA, USA S M Masutani University of Hawaii at Manoa, Honolulu, HI, USA I N McCave University of Cambridge, Cambridge, UK T J McDougall CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia C L Merrin The University of British Columbia, Vancouver, BC, Canada
T Platt Dalhousie University, NS, Canada J J Polovina National Marine Fisheries Service, Honolulu, HI, USA D Quadfasel Niels Bohr Institute, Copenhagen, Denmark J A Raven Biological Sciences, University of Dundee, Dundee, UK G E Ravizza Woods Hole Oceanographic Institution, Woods Hole, MA, USA A J Richardson University of Queensland, St. Lucia, QLD, Australia M Rubega University of Connecticut, Storrs, CT, USA w
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
xxiv
Contributors
K C Ruttenberg Woods Hole Oceanographic Institution, Woods Hole, MA, USA
K K Turekian Yale University, New Haven, CT, USA T Tyrrell University of Southampton, Southampton, UK
A G V Salvanes University of Bergen, Bergen, Norway
O Ulloa Universidad de Concepcio´n, Concepcio´n, Chile
S Sathyendranath Dalhousie University, NS, Canada
C M G Vivian The Centre for Environment, Fisheries and Aquaculture Sciences, Lowestoft, UK
R Schiebel Tu¨bingen University, Tu¨bingen, Germany F B Schwing NOAA Fisheries Service, Pacific Grove, CA, USA
J J Walsh University of South Florida, St. Petersburg, FL, USA
M P Seki National Marine Fisheries Service, Honolulu, HI, USA
R M Warwick Plymouth Marine Laboratory, Plymouth, UK
L J Shannon Marine and Coastal Management, Cape Town, South Africa
N C Wells Southampton Oceanography Centre, Southampton, UK
K Shepherd Institute of Ocean Sciences, Sidney, BC, Canada
J A Whitehead Woods Hole Oceanographic Institution, Woods Hole, MA, USA
D Siegel-Causey Harvard University, Cambridge MA, USA D M Sigman Princeton University, Princeton, NJ, USA A Soloviev Nova Southeastern University, FL, USA J H Steele Woods Hole Oceanographic Institution, MA, USA P K Takahashi University of Hawaii at Manoa, Honolulu, HI, USA L D Talley Scripps Institution of Oceanography, La Jolla, CA, USA E Thomas Yale University, New Haven, CT, USA J R Toggweiler NOAA, Princeton, NJ, USA
M Wilkinson Heriot-Watt University, Edinburgh, UK R G Williams University of Liverpool, Oceanography Laboratories, Liverpool, UK C A Wilson III Department of Oceanography and Coastal Sciences, and Coastal Fisheries Institute, CCEER Louisiana State University, Baton Rouge, LA, USA H Yamazaki Tokyo University of Marine Science and Technology, Tokyo, Japan B deYoung Memorial University, St. John’s, NL, Canada G Zibordi Institute for Environment and Sustainability, Ispra, Italy
Volume 5 D G Ainley H.T. Harvey Associates, San Jose CA, USA W Alpers University of Hamburg, Hamburg, Germany J R Apelw Global Ocean Associates, Silver Spring, MD, USA w
Deceased.
A B Baggeroer Massachusetts Institute of Technology, Cambridge, MA, USA L T Balance NOAA-NMFS, La Jolla, CA, USA R Batiza Ocean Sciences, National Science Foundation, VA, USA W H Berger Scripps Institution of Oceanography, La Jolla, CA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors J L Bodkin US Geological Survey, AK, USA
I Everson British Antarctic Survey Cambridge, UK
I L Boyd Natural Environment Research Council, Cambridge, UK
I Fer University of Bergen, Bergen, Norway
A C Brown University of Cape Town, Cape Town, Republic of South Africa
M Fieux Universite´-Pierre et Marie Curie, Paris, France
xxv
J Burger Rutgers University, Piscataway, NJ, USA
R A Flather Proudman Oceanographic Laboratory, Bidston Hill, Prenton, UK
C J Camphuysen Netherlands Institute for Sea Research, Texel, The Netherlands
G S Giese Woods Hole Oceanographic Institution, Woods Hole, MA, USA
D C Chapman Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J M Gregory Hadley Centre, Berkshire, UK
R E Cheney Laboratory for Satellite Altimetry, Silver Spring, Maryland, USA T Chopin University of New Brunswick, Saint John, NB, Canada J A Church Antarctic CRC and CSIRO Marine Research, TAS, Australia J K Cochran State University of New York, Stony Brook, NY, USA P Collar Southampton Oceanography Centre, Southampton, UK R J Cuthbert University of Otago, Dunedin, New Zealand L S Davis University of Otago, Dunedin, New Zealand K L Denman University of Victoria, Victoria BC, Canada R P Dinsmore Woods Hole Oceanographic Institution, Woods Hole, MA, USA G J Divoky University of Alaska, Fairbanks, AK, USA
S M Griffies NOAA/GFDL, Princeton, NJ, USA G Griffiths Southampton Oceanography Centre, Southampton, UK A Harding University of California, San Diego, CA, USA W S Holbrook University of Wyoming, Laramie, WY, USA G L Hunt, Jr University of Washington, Seattle, WA, USA and University of California, Irvine, CA, USA P Hutchinson North Atlantic Salmon Conservation Organization, Edinburgh, UK K B Katsaros Atlantic Oceanographic and Meteorological Laboratory, NOAA, Miami, FL, USA H L Kite-Powell Woods Hole Oceanographic Institution, Woods Hole, MA, USA M A Kominz Western Michigan University, Kalamazoo, MI, USA
L M Dorman University of California, San Diego, La Jolla, CA, USA
R G Kope Northwest Fisheries Science Center, Seattle, WA, USA
J F Dower University of British Columbia, Vancouver, BC, Canada
G S E Lagerloef Earth and Space Research, Seattle, WA, USA
J B Edson Woods Hole Oceanographic Institution, Woods Hole, MA, USA
L M Lairdw Aberdeen University, Aberdeen, UK
T I Eglinton Woods Hole Oceanographic Institution, Woods Hole, MA, USA
M Leppa¨ranta University of Helsinki, Helsinki, Finland w
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
xxvi
Contributors
E J Lindstrom NASA Science Mission Directorate, Washington, DC, USA
C T Roman University of Rhode Island, Narragansett, RI, USA
A K Liu NASA Goddard Space Flight Center, Greenbelt, MD, USA
M Sawhney University of New Brunswick, Saint John, NB, Canada
C R McClain NASA Goddard Space Flight Center, Greenbelt, MD, USA
G Shanmugam The University of Texas at Arlington, Arlington, TX, USA
D J McGillicuddy Jr Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J Sharples Proudman Oceanographic Laboratory, Liverpool, UK
W K Melville Scripps Institution of Oceanography, La Jolla CA, USA
J H Simpson Bangor University, Bangor, UK R K Smedbol Dalhousie University, Halifax, NS, Canada
D Mills Atlantic Salmon Trust, UK
L B Spear H.T. Harvey Associates, San Jose, CA, USA
P J Minnett University of Miami, Miami, FL, USA W A Montevecchi Memorial University of Newfoundland, NL, Canada W S Moore University of South Carolina, Columbia, SC, USA S J Morreale Cornell University, Ithaca, NY, USA K W Nicholls British Antarctic Survey, Cambridge, UK T J O’Shea Midcontinent Ecological Science Center, Fort Collins, CO, USA T E Osterkamp University of Alaska, Alaska, AK, USA F V Paladino Indiana-Purdue University at Fort Wayne, Fort Wayne, IN, USA C L Parkinson NASA Goddard Space Flight Center, Greenbelt, MD, USA A Pearson Woods Hole Oceanographic Institution, Woods Hole, MA, USA J T Potemra SOEST/IPRC, University of Hawaii, Honolulu, HI, USA J A Powell Florida Marine Research Institute, St Petersburg, FL, USA T Qu SOEST/IPRC, University of Hawaii, Honolulu, HI, USA
R L Stephenson St. Andrews Biological Station, St. Andrews, NB, Canada J M Teal Woods Hole Oceanographic Institution, Rochester, MA, USA K K Turekian Yale University, New Haven, CT, USA P Wadhams University of Cambridge, Cambridge, UK W F Weeks Portland, OR, USA G Wefer Universita¨t Bremen, Bremen, Germany W S Wilson NOAA/NESDIS, Silver Spring, MD, USA M Windsor, North Atlantic Salmon Conservation Organization, Edinburgh, UK S Y Wu NASA Goddard Space Flight Center, Greenbelt, MD, USA L Yu Woods Hole Oceanographic Institution, Woods Hole, MA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors
xxvii
Volume 6 A V Babanin Swinburne University of Technology, Melbourne, VIC, Australia
S E Humphris Woods Hole Oceanographic Institution, Woods Hole, MA, USA
R T Barber Duke University Marine Laboratory, Beaufort, NC, USA
W J Jenkins University of Southampton, Southampton, UK
J Bartram World Health Organization, Geneva, Switzerland
D R B Kraemer The Johns Hopkins University, Baltimore, MD, USA
A Beckmann Alfred-Wegener-Institut fu¨r Polar- und Meeresforschung, Bremerhaven, Germany M C Benfield Louisiana State University, Baton Rouge, LA, USA P S Bogden Maine State Planning Office, Augusta, ME, USA J A T Bye The University of Melbourne, Melbourne, VIC, Australia M F Cronin NOAA Pacific Marine Environmental Laboratory, Seattle, WA, USA A R J David Bere Alston, Devon, UK W Deuser Woods Hole Oceanographic Institution, Woods Hole, MA, USA J Donat Old Dominion University, Norfolk, VA, USA C Dryden Old Dominion University, Norfolk, VA, USA A Dufour United States Environmental Protection Agency, OH, USA C A Edwards University of Connecticut, Groton, CT, USA W J Emery University of Colorado, Boulder, CO, USA E Fahrbach Alfred-Wegener-Institut fu¨r Polar- und Meeresforschung, Bremerhaven, Germany
S Krishnaswami Physical Research Laboratory, Ahmedabad, India E L Kunze University of Washington, Seattle, WA, USA T E L Langford University of Southampton, Southampton, UK J R Ledwell Woods Hole Oceanographic Institution, Woods Hole, MA, USA P L-F Liu Cornell University, Ithaca, NY, USA M M R van der Loeff Alfred-Wegener-Institut fu¨r Polar und Meereforschung Bremerhaven, Germany R Lueck University of Victoria, Victoria, BC, Canada J E Lupton Hatfield Marine Science Center, Newport, OR, USA L P Madin Woods Hole Oceanographic Institution, Woods Hole, MA, USA M E McCormick The Johns Hopkins University, Baltimore, MD, USA M G McPhee McPhee Research Company, Naches, WA, USA J H Middleton The University of New South Wales, Sydney, NSW, Australia P J Minnett University of Miami, Miami, FL, USA E C Monahan University of Connecticut at Avery Point, Groton, CT, USA
A M Gorlov Northeastern University, Boston, Massachusetts, USA
C Moore WET Labs Inc., Philomath, OR, USA
I Helmond CSIRO Marine Research, TAS, Australia
J H Morison University of Washington, Seattle, WA, USA
R A Holman Oregon State University, Corvallis, OR, USA
J N Moum Oregon State University, Corvallis, OR, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
xxviii
Contributors
N S Oakey Bedford Institute of Oceanography, Dartmouth, NS, Canada D T Pugh University of Southampton, Southampton, UK D L Rudnick University of California, San Diego, CA, USA H Salas CEPIS/HEP/Pan American Health Organization, Lima, Peru L K Shay University of Miami, Miami, FL, USA W D Smyth Oregon State University, Corvallis, OR, USA J Sprintall University of California San Diego, La Jolla, CA, USA
L St. Laurrent University of Victoria, Victoria, BC, Canada W G Sunda National Ocean Service, NOAA, Beaufort, NC, USA M Tomczak Flinders University of South Australia, Adelaide, SA, Australia A J Watson University of East Anglia, Norwich, UK P H Wiebe Woods Hole Oceanographic Institution, Woods Hole, MA, USA P F Worcester University of California at San Diego, La Jolla, CA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contents Volume 1 Abrupt Climate Change
S Rahmstorf
1
Absorbance Spectroscopy for Chemical Sensors Abyssal Currents
R Narayanaswamy, F Sevilla, III
W Zenk
Accretionary Prisms
15
J C Moore
31
Acoustic Measurement of Near-Bed Sediment Transport Processes Acoustic Noise
Acoustic Scintillation Thermography Acoustics In Marine Sediments
K G Foote
62
P A Rona, C D Jones
71
T Akal
75
P N Mikhalevsky
Acoustics, Deep Ocean
92
W A Kuperman
101
F B Jensen
112
Acoustics, Shallow Water R Chester
Agulhas Current
120
J R E Lutjeharms
Aircraft Remote Sensing
128
L W Harding Jr, W D Miller, R N Swift, C W Wright
Air–Sea Gas Exchange
38 52
Acoustic Scattering by Marine Organisms
Aeolian Inputs
P D Thorne, P S Bell
I Dyer
Acoustics, Arctic
7
B Ja¨hne
138 147
Air–Sea Transfer: Dimethyl Sulfide, COS, CS2, NH4, Non-Methane Hydrocarbons, Organo-Halogens J W Dacey, H J Zemmelink
157
Air–Sea Transfer: N2O, NO, CH4, CO
163
Alcidae
C S Law
T Gaston
171
Antarctic Circumpolar Current Antarctic Fishes
S R Rintoul
I Everson
191
Anthropogenic Trace Elements in the Ocean Antifouling Materials
E A Boyle
211
W Seaman, W J Lindberg
234
R A Duce
Atmospheric Transport and Deposition of Particulate Material to the Oceans R Arimoto Authigenic Deposits
226
S G Philander
Atmospheric Input of Pollutants
Baleen Whales
203
B Rudels
Atlantic Ocean Equatorial Currents
Bacterioplankton
195
D J Howell, S M Evans
Arctic Ocean Circulation Artificial Reefs
178
G M McMurtry H W Ducklow
J L Bannister
238 J M Prospero, 248 258 269 276
(c) 2011 Elsevier Inc. All Rights Reserved.
xxix
xxx
Contents
Baltic Sea Circulation Bathymetry
W Krauss
288
D Monahan
297
Beaches, Physical Processes Affecting Benguela Current
Benthic Foraminifera
316 D J Wildish
328
A J Gooday
Benthic Organisms Overview
336
P F Kingston
348
P L Tyack
357
Biogeochemical Data Assimilation
E E Hofmann, M A M Friedrichs
Biological Pump and Particle Fluxes Bioluminescence
Bioturbation
S Honjo
376
A Morel
385
D H Shull
Black Sea Circulation
395
G I Shapiro
Bottom Water Formation
401
A L Gordon
415
Brazil and Falklands (Malvinas) Currents
A R Piola, R P Matano
Breaking Waves and Near-Surface Turbulence
J Gemmrich
D K Woolf
Calcium Carbonates
L C Peterson
E D Barton
Carbon Dioxide (CO2) Cycle
467
T Takahashi
Cenozoic Climate – Oxygen Isotope Evidence Cenozoic Oceans – Carbon Cycle Models
J D Wright L Franc¸ois, Y Godde´ris
R A Fine W R Martin
J W Farrington
Coastal Zone Management
514
539 551 563
F E Werner, B O Blanton
Coastal Topography, Human Impact on Coastal Trapped Waves
502
531
H Chamley
Coastal Circulation Models
495
524
Chemical Processes in Estuarine Sediments
Coccolithophores
E E Adams, K Caldeira
P Boyle
Chlorinated Hydrocarbons
477 487
Carbon Sequestration via Direct Injection into the Ocean
Clay Mineralogy
455
C A Carlson, N R Bates, D A Hansell, D K Steinberg
CFCs in the Ocean
431
445
B M Hickey, T C Royer
Canary and Portugal Currents
Cephalopods
422
439
California and Alaska Currents
Carbon Cycle
364 371
P J Herring, E A Widder
Bio-Optical Models
Bubbles
305
L V Shannon
Benthic Boundary Layer Effects
Bioacoustics
A D Short
D M Bush, O H Pilkey, W J Neal
J M Huthnance D R Godschalk
T Tyrrell, J R Young
(c) 2011 Elsevier Inc. All Rights Reserved.
572 581 591 599 606
Contents
Cold-Water Coral Reefs Conservative Elements
J M Roberts
615
D W Dyrssen
626
Continuous Plankton Recorders Copepods
A John, P C Reid
R Harris
Coral Reefs
630 640
Coral Reef and Other Tropical Fisheries Coral Reef Fishes
xxxi
V Christensen, D Pauly
M A Hixon
655
J W McManus
660
Corals and Human Disturbance Cosmogenic Isotopes
N J Pilcher
671
D Lal
678
Coupled Sea Ice–Ocean Models Crustacean Fisheries
651
A Beckmann, G Birnbaum
688
J W Penn, N Caputi, R Melville-Smith
699
CTD (Conductivity, Temperature, Depth) Profiler Current Systems in the Atlantic Ocean Current Systems in the Indian Ocean
A J Williams, III
L Stramma M Fieux, G Reverdin
Current Systems in the Southern Ocean
A L Gordon
Current Systems in the Mediterranean Sea
P Malanotte-Rizzoli
708 718 728 735 744
Volume 2 Data Assimilation in Models Deep Convection
A R Robinson, P F J Lermusiaux
J R N Lazier
Deep Submergence, Science of
13 D J Fornari
22
K Moran
37
Deep-Sea Drilling Methodology Deep-Sea Drilling Results
1
J G Baldauf
45
Deep-Sea Fauna
P V R Snelgrove, J F Grassle
55
Deep-Sea Fishes
J D M Gordon
67
Deep-Sea Ridges, Microbiology
A-L Reysenbach
73
Deep-Sea Sediment Drifts
D A V Stow
80
Demersal Species Fisheries
K Brander
90
Determination of Past Sea Surface Temperatures Differential Diffusion
A E Gargett
Dispersion from Hydrothermal Vents Diversity of Marine Species Dolphins and Porpoises
R W Schmitt, J R Ledwell
K R Helfrich
P V R Snelgrove R S Wells
Double-Diffusive Convection
98 114
Dispersion and Diffusion in the Deep Ocean
Drifters and Floats
M Kucera
R W Schmitt
P L Richardson
(c) 2011 Elsevier Inc. All Rights Reserved.
122 130 139 149 162 171
xxxii
Contents
Dynamics of Exploited Marine Fish Populations East Australian Current
M J Fogarty
G Cresswell
179 187
Economics of Sea Level Rise
R S J Tol
197
Ecosystem Effects of Fishing
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201
Eels
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208
Effects of Climate Change on Marine Mammals Ekman Transport and Pumping
T K Chereskin, J F Price
El Nin˜o Southern Oscillation (ENSO)
Electrical Properties of Sea Water
Energetics of Ocean Mixing
228
S G Philander
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Elemental Distribution: Overview
Y Nozaki
255
A C Naveira Garabato
261
Eutrophication
271
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Estuarine Circulation
288
K Dyer
299
V N de Jonge, M Elliott
Evaporation and Humidity
Fiord Circulation
306
K Katsaros
Exotic Species, Introduction of Expendable Sensors
241 247
w
A V Fedorov, J N Brown
Estimates of Mixing
218 222
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El Nin˜o Southern Oscillation (ENSO) Models
Equatorial Waves
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324
D Minchin
332
J Scott
345
A Stigebrandt
353
Fiordic Ecosystems
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359
Fish Ecophysiology
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Fish Feeding and Foraging Fish Larvae
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Fish Locomotion
381
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Fish Reproduction
Fish Vision
392
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Fish Predation and Mortality
Fish Schooling
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411
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425
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445
Fish: Demersal Fish (Life Histories, Behavior, Adaptations) Fish: General Review
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458 467
Fish: Hearing, Lateral Lines (Mechanisms, Role in Behavior, Adaptations to Life Underwater) A N Popper, D M Higgs w
417
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Fisheries Overview
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Fishery Management, Human Dimension
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Florida Current, Gulf Stream, and Labrador Current Flow through Deep Ocean Passages Flows in Straits and Channels
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Fluorometry for Biological Sensing
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Food Webs
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596
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Volume 3 Gas Exchange in Estuaries
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General Circulation Models
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20
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Geophysical Heat Flow
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40 K Lambeck
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M McNutt
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Groundwater Flow to the Coastal Ocean Habitat Modification
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Global Marine Pollution
Gravity
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Glacial Crustal Rebound, Sea Levels, and Shorelines Gliders
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Geomagnetic Polarity Timescale
1
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Heat and Momentum Fluxes at the Sea Surface Heat Transport and Climate History of Ocean Sciences
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Holocene Climate Variability Hydrothermal Vent Biota
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Hydrothermal Vent Deposits
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Hydrothermal Vent Ecology
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Hydrothermal Vent Fauna, Physiology of
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159
Hydrothermal Vent Fluids, Chemistry of
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164
Hypoxia
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172
Icebergs
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Ice-Induced Gouging of the Seafloor Ice–Ocean Interaction
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191 198
Ice Shelf Stability
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209
Igneous Provinces
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218
Indian Ocean Equatorial Currents Indonesian Throughflow
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237
Inherent Optical Properties and Irradiance Internal Tidal Mixing Internal Tides
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258
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266
International Organizations Intertidal Fishes
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274
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Intra-Americas Sea
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Internal Waves
Intrusions
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280
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Inverse Modeling of Tracers and Nutrients
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300
Inverse Models
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312
IR Radiometers
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319
K H Coale
331
Iron Fertilization Island Wakes Krill
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343
E J Murphy
349
Kuroshio and Oyashio Currents
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Laboratory Studies of Turbulent Mixing Lagoons
358 J A Whitehead
R S K Barnes
Lagrangian Biological Models Land–Sea Global Transfers
377 D B Olson, C Paris, R Cowen F T Mackenzie, L M Ver
Langmuir Circulation and Instability Large Marine Ecosystems
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Leeuwin Current
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Long-Term Tracer Changes Macrobenthos Magnetics
444
F von Blanckenburg
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xxxv
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Manned Submersibles, Deep Water
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Manned Submersibles, Shallow Water
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505 513
Mariculture Diseases and Health
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Mariculture of Aquarium Fishes
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524
Mariculture of Mediterranean Species Mariculture Overview
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537
Mariculture, Economic and Social Impacts Marine Algal Genomics and Evolution Marine Biotechnology
532
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545
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552 560
Marine Chemical and Medicine Resources
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567
Marine Fishery Resources, Global State of
J Csirke, S M Garcia
576
Marine Mammal Diving Physiology
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Marine Mammal Evolution and Taxonomy
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Marine Mammal Migrations and Movement Patterns Marine Mammal Overview
582
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P L Tyack
Marine Mammal Trophic Levels and Interactions Marine Mammals and Ocean Noise
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Marine Policy Overview Marine Protected Areas Marine Silica Cycle
635 643
654 G-A Paffenho¨fer
656
P Hoagland, P C Ticco
664
P Hoagland, U R Sumaila, S Farrow D J DeMaster
R S Lampitt
Maritime Archaeology
622
651
J H Steele
Marine Plankton Communities
Mediterranean Sea Circulation
672 678 686
R D Ballard
Meddies and Sub-Surface Eddies
Meiobenthos
S K Hooker
A E S Kemp
Marine Mesocosms
615
628
R R Reeves
Marine Mammals: Sperm Whales and Beaked Whales
Marine Snow
P L Tyack
D Wartzok
Marine Mammals, History of Exploitation
596 605
Marine Mammal Social Organization and Communication
Marine Mats
589
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Mesocosms: Enclosed Experimental Ecosystems in Ocean Science Mesopelagic Fishes
J E Petersen, W M Kemp
A G V Salvanes, J B Kristoffersen
Mesoscale Eddies
748
P B Rhines
Metal Pollution
755
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Metalloids and Oxyanions
732
768
G A Cutter
776
Methane Hydrates and Climatic Effects
B U Haq
784
Methane Hydrate and Submarine Slides
J Mienert
790
Microbial Loops
M Landry
Microphytobenthos
799
G J C Underwood
807
Mid-Ocean Ridge Geochemistry and Petrology Mid-Ocean Ridge Seismic Structure Mid-Ocean Ridge Seismicity
M R Perfit
815
S M Carbotte
826
D R Bohnenstiehl, R P Dziak
Mid-Ocean Ridge Tectonics, Volcanism, and Geomorphology
837 K C Macdonald
Mid-Ocean Ridges: Mantle Convection and Formation of the Lithosphere Millennial-Scale Climate Variability
J T Andrews
Mineral Extraction, Authigenic Minerals Molluskan Fisheries Monsoons, History of Moorings
G Ito, R A Dunn
852 867 881
J C Wiltshire
890
V S Kennedy
899
N Niitsuma, P D Naidu
910
R P Trask, R A Weller
919
Volume 4 Nekton
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Nepheloid Layers
1
I N McCave
Network Analysis of Food Webs
8 J H Steele
Neutral Surfaces and the Equation of State Nitrogen Cycle
19 T J McDougall, D R Jackett
D M Karl, A F Michaels
Nitrogen Isotopes in the Ocean Noble Gases and the Cryosphere Non-Rotating Gravity Currents North Atlantic Oscillation (NAO) North Sea Circulation
25 32
D M Sigman, K L Karsh, K L Casciotti
40
M Hood
55
P G Baines
59
J W Hurrell
65
M J Howarth
73
Nuclear Fuel Reprocessing and Related Discharges
H N Edmonds
82
Ocean Biogeochemistry and Ecology, Modeling of
N Gruber, S C Doney
89
Ocean Carbon System, Modeling of Ocean Circulation
S C Doney, D M Glover
N C Wells
105 115
Ocean Circulation: Meridional Overturning Circulation
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Contents
Ocean Gyre Ecosystems
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Ocean Margin Sediments Ocean Ranching
132
S L Goodbred Jr
138
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146
R G Williams
156
Ocean Subduction
Ocean Thermal Energy Conversion (OTEC) Ocean Zoning
S M Masutani, P K Takahashi
M Macleod, M Lynch, P Hoagland
Offshore Sand and Gravel Mining Oil Pollution
Okhotsk Sea Circulation
E Garel, W Bonne, M B Collins
200
H Yamazaki, H Burchard, K Denman, T Nagai
Open Ocean Convection
A Soloviev, B Klinger
Open Ocean Fisheries for Deep-Water Species
Optical Particle Characterization
P H Burkill, C P Gallienne
265 272 274
R Lukas
287
E Thomas
295 W W Hay
Paleoceanography: Orbitally Tuned Timescales Paleoceanography: the Greenhouse World Particle Aggregation Dynamics Past Climate from Corals
T D Herbert
M Huber, E Thomas
A Alldredge
A G Grottoli
K L Denman, J F Dower
Pelagic Biogeography
A Longhurst
D H Cushing
Pelecaniformes
Peru–Chile Current System
C A Paulson, W S Pegau
J Karstensen, O Ulloa
319 330 338 348 356
379 385 393
K C Ruttenberg
Photochemical Processes
311
370
M Rubega
Phosphorus Cycle
303
364
D Siegel-Causey
Penetrating Shortwave Radiation
252 261
I Laing
Paleoceanography, Climate Models in
Phytobenthos
R A Jahnke
K K Turekian
Pacific Ocean Equatorial Currents
Phalaropes
243
G F Lane-Serff
Oysters – Shellfish Farming
Pelagic Fishes
234
K K Turekian
Oxygen Isotopes in the Ocean
Paleoceanography
226
J Joseph
Organic Carbon Cycling in Continental Margin Environments
Overflows and Cascades
208 218
J D M Gordon
Open Ocean Fisheries for Large Pelagic Species
Origin of the Oceans
182 191
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One-Dimensional Models
167 174
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Patch Dynamics
xxxvii
N V Blough
M Wilkinson
401 414 425
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Phytoplankton Blooms
D M Anderson
Phytoplankton Size Structure Plankton
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Plankton and Climate Plankton Viruses
432
E Maran˜o´n
445
w
453
A J Richardson
455
J Fuhrman, I Hewson
465
Platforms: Autonomous Underwater Vehicles Platforms: Benthic Flux Landers
J G Bellingham
R A Jahnke
485
Platinum Group Elements and their Isotopes in the Ocean
G E Ravizza
Plio-Pleistocene Glacial Cycles and Milankovitch Variability Polar Ecosystems
K H Nisancioglu
A Clarke
Pollution, Solids
494 504 514
C M G Vivian, L A Murray
Pollution: Approaches to Pollution Control Pollution: Effects on Marine Communities Polynyas
473
519
J S Grayw, J M Bewers R M Warwick
526 533
S Martin
540
Population Dynamics Models
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Population Genetics of Marine Organisms Pore Water Chemistry
546
D Hedgecock
556
D Hammond
Primary Production Distribution
563
S Sathyendranath, T Platt
572
Primary Production Methods
J J Cullen
578
Primary Production Processes
J A Raven
585
Procellariiformes
K C Hamer
590
Propagating Rifts and Microplates
Richard Hey
597
Protozoa, Planktonic Foraminifera
R Schiebel, C Hemleben
606
Protozoa, Radiolarians
O R Anderson
Radiative Transfer in the Ocean Radioactive Wastes Radiocarbon
C D Mobley
619
L Føyn
629
R M Key
637
Rare Earth Elements and their Isotopes in the Ocean Red Sea Circulation Redfield Ratio Refractory Metals
Y Nozaki
w
D Quadfasel
677
K J Orians, C L Merrin
Regime Shifts, Physical Forcing Regime Shifts: Methods of Analysis
653 666
T Tyrrell
Regime Shifts, Ecological Aspects
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613
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Regional and Shelf Sea Models
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Remote Sensing of Coastal Waters
Rigs and offshore Structures River Inputs
722
N Hoepffner, G Zibordi
Remotely Operated Vehicles (ROVs)
xxxix
732
K Shepherd
742
C A Wilson III, J W Heath
748
J D Milliman
754
Rocky Shores
G M Branch
762
Rogue Waves
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770
Rossby Waves
P D Killworth
Rotating Gravity Currents
781
J A Whitehead
790
Volume 5 Salmon Fisheries, Atlantic
P Hutchinson, M Windsor
Salmon Fisheries, Pacific Salmonid Farming Salmonids
1
R G Kope
L M Laird
12
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23
D Mills
29
Salt Marsh Vegetation
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Salt Marshes and Mud Flats Sandy Beaches, Biology of Satellite Altimetry
39
J M Teal
43
A C Brown
49
R E Cheney
58
Satellite Oceanography, History, and Introductory Concepts J R Apel w
W S Wilson, E J Lindstrom, 65
Satellite Passive-Microwave Measurements of Sea Ice
C L Parkinson
80
Satellite Remote Sensing of Sea Surface Temperatures
P J Minnett
91
Satellite Remote Sensing SAR
A K Liu, S Y Wu
Satellite Remote Sensing: Ocean Color
C R McClain
Satellite Remote Sensing: Salinity Measurements Science of Ocean Climate Models Sea Ice
103
G S E Lagerloef
S M Griffies
P Wadhams
114 127 133 141
Sea Ice Dynamics
M Leppa¨ranta
159
Sea Ice: Overview
W F Weeks
170
Sea Level Change
J A Church, J M Gregory
179
Sea Level Variations Over Geologic Time Sea Otters
w
M A Kominz
J L Bodkin
185 194
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Sea Surface Exchanges of Momentum, Heat, and Fresh Water Determined by Satellite Remote Sensing L Yu
202
Sea Turtles
212
F V Paladino, S J Morreale
Seabird Conservation
J Burger
Seabird Foraging Ecology Seabird Migration
220
L T Balance, D G Ainley, G L Hunt Jr
L B Spear
227 236
Seabird Population Dynamics
G L Hunt Jr
247
Seabird Reproductive Ecology
L S Davis, R J Cuthbert
251
Seabird Responses to Climate Change Seabirds and Fisheries Interactions
David G Ainley, G J Divoky C J Camphuysen
Seabirds as Indicators of Ocean Pollution Seabirds: An Overview Seals
265
W A Montevecchi
274
G L Hunt, Jr
279
I L Boyd
285
Seamounts and Off-Ridge Volcanism Seas of Southeast Asia
R Batiza
292
J T Potemra, T Qu
Seaweeds and their Mariculture Sediment Chronologies
305
T Chopin, M Sawhney
317
J K Cochran
327
Sedimentary Record, Reconstruction of Productivity from the Seiches
Seismic Structure
I Fer, W S Holbrook
L M Dorman
367
K B Katsaros
375
Sensors for Micrometeorological and Flux Measurements Shelf Sea and Shelf Slope Fronts
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J Sharples, J H Simpson
H L Kite-Powell
Single Point Current Meters
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P Collar, G Griffiths
436
Slides, Slumps, Debris Flows, and Turbidity Currents Small Pelagic Species Fisheries Small-Scale Patchiness, Models of
419 428
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R L Stephenson, R K Smedbol D J McGillicuddy Jr
Small-Scale Physical Processes and Plankton Biology
J F Dower, K L Denman
M Fieux
447 468 474 488 494
A B Baggeroer
Southern Ocean Fisheries
391
409
Single Compound Radiocarbon Measurements
Sonar Systems
382
401
R P Dinsmore
Somali Current
351 361
Sensors for Mean Meteorology
Shipping and Ports
333 344
A Harding
Seismology Sensors
Sirenians
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D C Chapman, G S Giese
Seismic Reflection Methods for Study of the Water Column
Ships
257
504
I Everson
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Contents
Sphenisciformes
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520
Stable Carbon Isotope Variations in the Ocean Storm Surges
K K Turekian
529
R A Flather
530
Sub Ice-Shelf Circulation and Processes Submarine Groundwater Discharge Sub-Sea Permafrost Surface Films
xli
K W Nicholls
541
W S Moore
551
T E Osterkamp
559
W Alpers
570
Surface Gravity and Capillary Waves
W K Melville
573
Volume 6 Temporal Variability of Particle Flux Thermal Discharges and Pollution
W Deuser
1
T E L Langford
10
Three-Dimensional (3D) Turbulence Tidal Energy Tides
W D Smyth, J N Moum
A M Gorlov
26
D T Pugh
Tomography
32
P F Worcester
Topographic Eddies Towed Vehicles
40
J H Middleton
57
I Helmond
Trace Element Nutrients
65
W G Sunda
Tracer Release Experiments
75
A J Watson, J R Ledwell
Tracers of Ocean Productivity
Transmissometry and Nephelometry Tritium–Helium Dating
87
W J Jenkins
93
Transition Metals and Heavy Metal Speciation
Tsunami
18
J Donat, C Dryden
100
C Moore
109
W J Jenkins
119
P L-F Liu
127
Turbulence in the Benthic Boundary Layer Turbulence Sensors
R Lueck, L St. Laurrent, J N Moum
N S Oakey
Under-Ice Boundary Layer
148
M G McPhee, J H Morison
Upper Ocean Heat and Freshwater Budgets Upper Ocean Mean Horizontal Structure Upper Ocean Mixing Processes
155
P J Minnett
163
M Tomczak
175
J N Moum, W D Smyth
185
Upper Ocean Structure: Responses to Strong Atmospheric Forcing Events Upper Ocean Time and Space Variability Upper Ocean Vertical Structure Upwelling Ecosystems
141
L K Shay
192
D L Rudnick
211
J Sprintall, M F Cronin
217
R T Barber
Uranium-Thorium Decay Series in the Oceans: Overview
225 M M R van der Loeff
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Uranium-Thorium Series Isotopes in Ocean Profiles Vehicles for Deep Sea Exploration
S E Humphris
Viral and Bacterial Contamination of Beaches Volcanic Helium
J Bartram, H Salas, A Dufour
285
Water Types and Water Masses
W J Emery
291
M E McCormick, D R B Kraemer
Waves on Beaches
267 277
E L Kunze
Wave Generation by Wind
244 255
J E Lupton
Vortical Modes
Wave Energy
S Krishnaswami
300
J A T Bye, A V Babanin
304
R A Holman
310
Weddell Sea Circulation
E Fahrbach, A Beckmann
318
Wet Chemical Analyzers
A R J David
326
Whitecaps and Foam
E C Monahan
Wind- and Buoyancy-Forced Upper Ocean Wind Driven Circulation
331 M F Cronin, J Sprintall
P S Bogden, C A Edwards
Zooplankton Sampling with Nets and Trawls
337 346
P H Wiebe, M C Benfield
355
Appendix 1. SI Units and Some Equivalences
373
Appendix 2. Useful Values
376
Appendix 3. Periodic Table of the Elements
377
Appendix 4. The Geologic Time Scale
378
Appendix 5. Properties of Seawater
379
Appendix 6. The Beaufort Wind Scale and Seastate
384
Appendix 7. Estimated Mean Oceanic Concentrations of the Elements
386
Appendix 8. Abbreviations
389
Appendix 9. Taxonomic Outline Of Marine Organisms
L P Madin
401
Appendix 10. Bathymetric Charts of the Oceans
412
Index
421
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TEMPORAL VARIABILITY OF PARTICLE FLUX W. Deuser, Woods Hole Oceanographic Institution, Woods Hole, MA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2925–2933, & 2001, Elsevier Ltd.
Ridge off Namibia, the Bransfield Strait, the Weddell Sea, the Arabian Sea, and the Bay of Bengal. No doubt, other parts of the ocean will be sampled in the future and, most likely, temporal variations in particle flux will be found.
Reality of ‘Temporal’ Flux Variations
Introduction Until the late 1960s the deep ocean was considered the least variable environment above the solid surface of the earth. It is always cold and dark, and no expressions of the diurnal or annual cycles shaping the subaerial environment were expected to penetrate the ocean beyond a depth of a few hundred meters. It was also believed that the fine particles constituting the bulk of deep-sea sediments took years to reach the seafloor. Then, in the 1970s and early 1980s, several lines of evidence contradicting this view emerged: what appeared to be annual varves were detected in the sediments of the Black Sea at a depth of more than 2000 m, and annual reproduction cycles and growth bands were reported for a few deep-benthic organisms. A plausible explanation for such periodicity in the deep sea was lacking, however, until time-series measurements by deep-ocean sediment traps at a depth of 3200 m in the Sargasso Sea revealed seasonal changes in the flux of particulate organic matter and, indeed, of all types of sedimenting particles. The variability of the deep flux could be attributed to changes in primary productivity in the euphotic zone about 1 month earlier. This finding demonstrated how unexpectedly rapid the transport of particles to the deep sea is and provided evidence for a seasonally variable food supply for deep-benthic organisms. Such variable food supply fosters uneven growth rates and cyclic reproduction.
Variations in the amount of sinking material per unit time recorded by stationary sediment traps in reality are convolutions of three components: (1) true temporal variations in the sinking flux, (2) spatial variations in the distribution of sinking particles moving past the trap site, and (3) variations in the retention efficiency of the traps caused by changes in trap tilt and ambient current speed. To some extent, the magnitudes of the second and third components can be reduced by the use of free-floating, neutrally buoyant traps, but the difficulties of deploying them at the desired depths and of tracking and recovering them have as yet prevented their widespread use. Further complications in interpreting apparent temporal flux variations recorded by stationary traps are introduced by the different sinking speeds of particles, typically ranging from 50 to 4500 m d 1. Rapidly sinking particles intercepted by traps carry signatures of conditions in overlying waters in a more recent time interval than do slowly sinking ones. This effect leads to both a mixing and ‘smearing’ of the real temporal variations of different particle classes prevailing during their departure intervals at or near the surface (Figure 1). In addition, apparentchanges in flux measured during successive sampling intervals of a given length (e. g. 15 d) in reality represent variations in near-surface conditions over significantly longer intervals (Figure 2). Nevertheless, some new and important insights into the inner workings of the ocean have been gained through the use of sediment traps.
Ubiquity of Temporal Flux Variations Time-series measurements of the sinking particle flux in many parts of the oceans and marginal seas have consistently revealed significant temporal variations. A partial listing includes the north-eastern, eastern, and central North Pacific, the Panama Basin, the Gulf of California, the Equatorial Pacific, the Greenland and Norwegian Seas, the north-eastern North Atlantic, Bay of Biscaye, Mediterranean, Sargasso Sea, the Atlantic off West Africa, the Caribbean Sea,the eastern Equatorial Atlantic, the Walvis
Causes of Flux Variability A variety of processes lead to variability in the flux of particulate matter to the seafloor. Variations in primary productivity in surface waters owing to seasonal (and shorter-term) changes in mixed-layer depth and attendant replenishment of nutrients in the euphotic zone are the primary cause of flux variations to the deep oceans of the temperate and subtropical latitudes. Intense storms, such as hurricanes, can also create localized flux pulses along their
(c) 2011 Elsevier Inc. All Rights Reserved.
1
2
TEMPORAL VARIABILITY OF PARTICLE FLUX
Overlapping departure intervals (76.5 d)
0
500
1500
50 m _1
d
Depth (m)
1000
2000 200 m
3200-m trap
_1
d
2500 1500-m trap 3000
500-m trap Collection interval (15 d)
3500
_ 80
_ 60
_ 20
_ 40
0
20
40
Time from cup opening (d)
Figure 1 Schematic illustration of the different time intervals of surface departure of particles with different sinking speeds sampled simultaneously by a deep-ocean sediment trap. (Reprinted from Deep-Sea Research I, 44, Siegel and Deuser, Trajectories of sinking particles in the Sargasso Sea: modeling of statistical funnels above deep-ocean sediment traps. pp. 1519–1541, copyright (1997) with permission from Elsevier Science.)
tracks. Dust storms, as emanating from the western Sahara and reaching far across the Atlantic, for example, create pulses of lithogenic flux components in their wake. Iron, a growth-limiting micronutrient associated with the dust particles, can stimulate a primary production spike, especially of diatoms which, in turn, may boost the sinking flux of opaline silica and zooplankton fecal material and skeletal remains. The seasonal monsoons affecting the northern Indian Ocean have been shown to influence the primary production and flux of particles to the deep Arabian Sea and Bay of Bengal. Seasonal changes in flow of tropical rivers cause fluctuations in the supply of nutrients to their plumes and can cause seemingly erratic fluctuations in productivity and particle export as far as hundreds to thousands of kilometers from the river mouths. The annual cycle of waxing and waning ice cover on high-latitude oceans influences the amount of sinking material. Variations in upwelling intensity on seasonal
to multiannual timescales result in concomitant variations in sinking flux.
Timescales of Flux Variability Knowledge of timescales of flux variabilityis limited by the sampling schemes designed to intercept the sinking flux of particles. While in all likelihood particle fluxes vary on timescales as shortas minutes or less, the practicality of sampling measurable amounts in the deep ocean has placed a lower limit of daily sampling intervals on attempts to determine variability. Also, inasmuch as appropriate technology became available only in the late 1970s and only a few sites have been sampled for even a single decade, detection of true decadal variability thus far is restricted to decade-length trends only. There is no way of knowing whether such trends are parts of continuing unidirectional changes or parts of
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TEMPORAL VARIABILITY OF PARTICLE FLUX
3
Figure 2 Schematic of the overlapping, but widely different, time intervals which were sampled simultaneously by an array of three sediment traps at different depths on the same mooring. (Reprinted from Deep-Sea Research I, 44, Siegel and Deuser, Trajectories of sinking particles in the Sargasso Sea: modeling of statistical funnels above deep-ocean sediment traps, pp. 1519–1541, copyright (1997) with permission from Elsevier Science.)
Figure 3 Example of daily mass flux differences at three depths in the Sargasso Sea. Note that the three traps sampled particles which departed the upper ocean at different times (compare with Figure 2).
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4
TEMPORAL VARIABILITY OF PARTICLE FLUX Flux accumulation curves
Accumulated flux (% of total)
100
80
60
50% of total annual flux
40
20
0 0
50
100
150
200
250
300
350
Accumulated time (d)
Western Indian Ocean North-eastern Pacific North-eastern Atlantic Equatorial Pacific Figure 4 Yearly cumulative flux curves for four oceanic provinces. (Reprinted from Deep-Sea Research I, 44, from Lampitt and Antia, Particle flux in deep seas: regional characteristics and temporal variability, pp. 1377–1403, copyright (1997) with permission from Elsevier Science.)
long-term cycles. It is fair to say, however, that flux variability has been found wherever and whenever attempts were made to detect it. At least at one site in the Sargasso Sea it has been documented on timescales from diurnal to decadal. Evidence for even longer-term variability of sediment flux, on timescales of centuries and beyond, is found in the sedimentary record of agreat many geological periods. Diurnal
Diurnal flux variability is the rule in the upper ocean due to such causes as patchiness in the distribution of particle-producing organisms, eddies, day-to-day differences in solar heating, and wind speed. For technical and logistical reasons, there is less documentation of diurnal flux variability in the deep ocean. An example of this flux at three depths on the same mooring in the Sargasso Sea is shown in Figure 3. Even at a depth of 1500 m daily fluxes varied by a factor of two.
Monthly
There are hints of a lunar cycle (29.5 d). in some sediment trap records. Some organisms, such as planktonic foraminifera, have lunar reproduction cycles which ought to find an expression in the sinking flux of their skeletal parts. The difficulty in demonstrating lunar cyclicity in the flux intercepted by sediment traps lies in devising sampling schemes which avoid aliasing of the lunar period. With the widely employed monthly or semimonthly sampling frequency of traps this is not possible. Seasonal
The most widely detected temporal variation in the sinking flux is seasonal, i. e. an annual cycle. The practical reason for this is that the cycle of seasons fits best into the sampling schemes suitable to remote locations and into the funding schemes of agencies supporting oceanographic research. The fundamental
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TEMPORAL VARIABILITY OF PARTICLE FLUX
5
Figure 5 Average annual flux variation over a period of 18 years (1978–95) at 3200 m in the Sargasso Sea. The standard deviations around the semimonthly averages in the left panel give an indication of the interannual variability. The small panel at lower left indicates the number of years for which measurements were made at begining and middle of each month.
reason is that all parts of the ocean, including those at tropical latitudes, are subject to seasonal changes. Insolation, sea surface temperature, wind speed and direction, precipitation, and in some parts ice cover and surface currents, as well as human activities, all undergo seasonal changes. All of these factors have some bearing on biological productivity and/or detrital input into the surface ocean. Amplitudes of the annual cycle differ widely in different parts of the ocean. In the high latitudes, where the ocean is ice-free for only a short time, half of the annual particle flux may be delivered to deep water in a month or less. Annual cumulative flux curves for four different open-ocean regimes, calculated for a standard depth of 2000 m, are shown in Figure 4. In general, the lower the latitude, the less pronounced the annual cycle, but areas such as the Arabian Sea, which is strongly affected by the seasonal monsoons, deviate from this pattern.
The longest series of consistent measurements of the particle flux to the deep ocean is for a depth of 3200 m in the Sargasso Sea. The average annual cycle and its standard deviation over a period of 18 years for that site are shown in Figure 5. The cycle is quasisinusoidal, but there are several features worthy of note, as follows. (1) On average, even at the time of lowest flux, i. e. in the fall, the flux is still about half that at the time of maximum flux. (2) The greatest variance (a measure of interannual variability) occurs at the time of maximum flux, i. e. in the spring, followed by a secondary maximum in midsummer. Conversely, the lowest variance occurs at the time of lowest flux. (3) The transition from the autumnal flux minimum to the vernal flux maximum is not sudden, as might be expected based on a rather sudden spring bloom, but gradual. The reason for this is that there are actually a number of mixing events triggering minor blooms which increase in
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TEMPORAL VARIABILITY OF PARTICLE FLUX Bimonthly flux anomalies at 3200 m
103
Flux anomalies (18 y)
102
Power density
7
101
100
Average annual flux cycle
_1
10
_2
10
_1
100
10
101
Frequency (1 per year) Figure 7 Power spectrum of the anomalies shown in Figure 6 (solid line) compared with that of the average annual flux cycle (dotted line). There are no significant peaks for periods longer than 1 year.
4.5 years, with the latter not being significant. This demonstrates clearly that patterns of multiannual variability can be detected only in sampling records of duration far exceeding those presently available.
column which, in turn, led to decreases in mixed-layer depth, nutrient supply to the euphotic zone, and primary production. Thus it appears that here, too, climatic change, whether of cyclic or unidirectional nature, affects the flux of particles to the deep ocean.
Decadal
True decadal variability is detectable only in time-series of several decades’ length, but trends may become apparent in shorter series. An example is a significant 14-year negative trend in the opal/calcium carbonate ratio in the sinking material in the Sargasso Sea (Figure 8). It appears that changes in the species assemblage of the silica-producing biota were responsible for the trend. But, while the trend parallels a significant trend of increasing wind speed in the Bermuda area, a causal connection between the two is not obvious. A 7-year trend of decreasing flux of particulate organic carbon was detected in the deep eastern North Pacific. In that case the trend was attributed to a longterm increase in the temperature of the upper water
Episodic
There is increasing evidence that episodic or ‘unusual’ events, i. e. events that fall outside the norm of commonly observed variability, can have significant and enduring effects on ecosystems and the sedimentary record. The question of what constitutes an unusual event, however, is not trivial. The evidence suggests that the frequency of such occurrences decreases, rather than increases, with increasing length of a series of observations or measurements. In other words, the lack of a long-term perspective causes the observer to attribute a deviation from the short-term norm to an unusual event although the longer-term norm may well encompass deviations of this magnitude. Even more difficult is the assignment of likely
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8
TEMPORAL VARIABILITY OF PARTICLE FLUX Sargasso Sea, 3200 m
0.55
0.5 _
Slope of fit: _0.0105/yr 1 (significant at 99% confidence level)
n = 82
Opal/CaCO3 flux ratio
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1 1978
1980
1982
1984
1986
1988
1990
1992
Start of year Figure 8 The 14-year record of variations in the ratio of opaline silica to calcium carbonate in material sinking to the deep Sargasso Sea. The over all trend of a decrease in the ratio (dotted line) is probably due to changes in the species assemblage of opal-producing biota which,in turn, could be related to a subtle climatic trend over that period. (Reprinted from Deep-Sea Research I, 42, Deuser, Jickells,King and Commeau, Decadal and annual changes in biogenic opal and carbonate fluxes to the deep Sargasso Sea, pp. 1923– 1932, copyright (1995) with permission from Elsevier Science.)
causes to such events. There is a general lack of simultaneous, continuous monitoring of meteorological and oceanographic variables to identify chains of events which might trigger episodic peaks in the sinking flux. Even closely spaced snapshot measurements of those variables stand a good chance of missing the brief conditions initiating the chain. An example is the record of an event of very high coccolith flux in the Panama Basin. The flux during one of six bimonthly collection periods exceeded by orders of magnitude the flux observed during the other five. Most likely, the defining event was much shorter than 2 months, suggesting an even more pronounced transient. However, the lack of appropriate concurrent measurement series precluded the assignment of a likely cause to the event. It is hoped that with increasing recognition of the value of timeseries measurements and with the trend towards
developing instrumentation capable of long-term automated monitoring of meteorological and hydrographic variables it will become easier both to detect and identify the causes of unpredictable episodic events.
Conclusions Except near hydrothermal vents, the sinking flux of particles – whose formation ultimately depends on photosynthesis– provides the fuel for all life forms in the deep ocean. It is becoming increasingly clear that this ‘rain’ varies on all timescales up to decadal and beyond. The deep ocean is thus not in a steady state and its life forms are quite closely coupled to both gradual changes and sudden events near the surface.
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TEMPORAL VARIABILITY OF PARTICLE FLUX
See also Primary Production Distribution. Primary Production Methods. Primary Production Processes. River Inputs. Upper Ocean Mixing Processes. Upper Ocean Time and Space Variability.
Further Reading Berger WH and Wefer G (1990) Export production: seasonality and intermittency, and paleoceanographic implications. Palaeogeography, Palaeoclimatology and Palaeoecology 89: 245--254. Deuser WG and Ross EH (1980) Seasonal change in the flux of organic carbon to the deep Sargasso Sea. Nature 283: 364--365. Deuser WG (1996) Temporal variability of particle flux in the deep Sargasso Sea. In: Ittekkot V, Schafer P, Honjo
9
S, and Depetris PJ (eds.) Particle Flux in the Ocean. London: Wiley and Sons. Honjo S (1982) Seasonality and interaction of biogenic and lithogenic particulate flux at the Panama Basin. Science 218: 883--890. Lampitt RS and Antia AN (1997) Particle flux in deep seas: regional characteristics and temporal variability. DeepSea Research I 44: 1377--1403. Siegel DA and Deuser WG (1997) Trajectories of sinking particles in the Sargasso Sea: modeling of statistical funnels above deep-ocean sediment traps. Deep-Sea Research I 44: 1519--1541. Smith KL jr and Kaufmann RS (1999) Long-term discrepancy between food supply and demand in the deep eastern North Pacific. Science 284: 1174--1177. Weatherhead PJ (1986) How unusual are unusual events? American Naturalist 128: 150--154.
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THERMAL DISCHARGES AND POLLUTION T. E. L. Langford, University of Southampton, Southampton, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2933–2940, & 2001, Elsevier Ltd.
Sources of Thermal Discharges The largest single source of heat to most water bodies, including the sea, is the sun. Natural thermal springs also occur in many parts of the world, almost all as fresh water, some of which discharge to the sea. In the deep oceans hydrothermal vents discharge mineral-rich hot water at temperatures greatly exceeding any natural temperatures either at depth or at the surface. To add to these natural sources of heat, industrial processes have discharged heated effluents into coastal waters in many parts of the world for at least 150 years. By far the largest volumes of these heated effluents reaching the sea in the past 60 years have originated from the electricity generation industry (power industry). Indeed more than 80% of the volume of heated effluents to the sea originate from the power industry compared with 3– 5% from the petroleum industries and up to 7% (in the USA) from chemical and steel industries. The process known as ‘thermal’ power generation, in which a fuel such as oil or coal or the process of nuclear fission is used to heat water to steam to drive turbines, requires large volumes of cooling water to remove the waste heat produced in the process. Where power stations are sited on or near the coast all of this waste heat, representing some 60–65% of that used in the process, is discharged to the sea. The heat is then dissipated through dilution, conduction, or convection. In a few, atypical coastal situations, where the receiving water does not have the capacity to dissipate the heat, artificial means of cooling the effluent such as ponds or cooling-towers are used. Here the effluent is cooled prior to discharge and much of the heat dissipated to the air. The waste heat is related to the theoretical thermal efficiency of the Rankine cycle, which is the modification of the Carnot thermodynamic cycle on which the process is based. This has a maximum theoretical efficiency of about 60% but because of environmental temperatures and material properties the practical efficiency is around 40%. Given this level of efficiency and the normal operating conditions of a modern coal- or oil-fired power station, namely
10
steam at 5501C and a pressure of 10.3 106 kg cm2 with corresponding heat rates of 2200 kg cal kWh1 of electricity, some 1400 kg cal kWh1 of heat is discharged to the environment, usually in cooling water at coastal sites. This assumes a natural water temperature of 101C. Nuclear power stations usually reject about 50% more heat per unit of electricity generated because they operate at lower temperatures and pressures. Since the 1920s efficiencies have increased from about 20% to 38–40% today with a corresponding reduction by up to 50% of the rate of heat loss. The massive expansion of the industry since the 1920s has, however, increased the total amounts of heat discharged to the sea. Thus for each conventional modern power station of 2000 MW capacity some 63 m3 s1 of cooling water is required to remove the heat. Modern developments such as the combined cycle gas turbine (CCGT) power stations with increased thermal efficiencies have reduced water requirements and heat loss further so that a 500 MW power station may require about 9–10 m3 s1 to remove the heat, a reduction of over 30% on conventional thermal stations.
Water Temperatures Natural sea surface temperatures vary widely both spatially and temporally throughout the world with overall ranges recorded from 21C to 301C in open oceans and 21C to 431C in coastal waters. Diurnal fluctuations at the sea surface are rarely more than 11C though records of up to 1.91C have been made in shallow seas. The highest temperatures have been recorded in sheltered tropical embayments where there is little exchange with open waters. Most thermal effluents are discharged into coastal waters and these are therefore most exposed to both physical and biological effects. In deeper waters vertical thermal stratification can often exceed 101C and a natural maximum difference of over 231C between surface and bottom has been recorded in some tropical waters. The temperatures of thermal discharges from power stations are typically 8–121C higher than the natural ambient water temperature though at some sites, particularly nuclear power stations, temperature rises can exceed 151C (Figure 1). Maximum discharge temperatures in some tropical coastal waters have reached 421C though 35–381C is more typical. There are seasonal and diurnal fluctuations
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THERMAL DISCHARGES AND POLLUTION Tidal currents
20
Number of power units
18
11
Wind
Slackwater plume
16 14
Flood
12
Ebb
10 8 6
Coastline
(A)
4
Tidal currents
2 8 10
14
18
26
22
30
34
38
Wind
Slackwater plume
42
∆T, °F 5
7
9
11 13
15
17 19
Flood
21 23 25
∆T, °C
Ebb Coastline
Figure 1 Frequency distribution of designed temperature rises for thermal discharges in US power station cooling water systems. (Reproduced with permission from Langford, 1990.)
at many sites related to the natural seasonal temperature cycles and to the operating cycles of the power station.
(B) Figure 2 Movements of thermal plumes in tidal waters. (A) Offshore outfall; (B) onshore outfall. (Reproduced with permission from Langford, 1990.)
400
Thermal Plumes and Mixing Zones
40
Area within isotherm (ha)
Once discharged into the sea a typical thermal effluent will spread and form a three-dimensional layer with the temperature decreasing with distance from the outfall. The behavior and size of the plume will depend on the design and siting of the outfall, the tidal currents, the degree of exposure and the volume and temperature of the effluent itself. Very few effluents are discharged more than 1 km from the shore. Effects on the shore are, however, maximized by shoreline discharge (Figure 2). The concept of the mixing zone, usually in three components, near field, mid-field and far-field, related to the distance from the outfall, has mainly been used in determining legislative limits on the effluents. Most ecological studies have dealt with near and mid-field effects. The boundary of the mixing zone is, for most ecological limits, set where the water is at 0.51C above natural ambients though this tends to be an arbitrary limit and not based on ecological data. Mixing zones for coastal discharges can be highly variable in both temperature and area of effect (Figure 3). In addition to heat effects, thermal discharges also contain chemicals, mainly those used for the control of marine fouling in pipework and culverts. Chlorine compounds are the most common and because of its
Theoretical upper limit
4
0.4
0.1
7 1 2 3 4 5 0 6 Surface isotherm temperature minus intake temperature (°C) Figure 3 Relationship between surface-temperature elevation and surface area affected for nine different surveys at Moro Bay Power Plant, California. (Reproduced with permission from Langford, 1990.)
strong biocidal properties, the effects of chlorine are of primary concern in many coastal discharges, irrespective of the temperature. Measured chlorine
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THERMAL DISCHARGES AND POLLUTION
residuals immediately after application vary between 0.5 and 10 mg l1 throughout the world but most are within the 0.5–1.0 mg l1 range. Because of the complex chemical reactions in sea water free chlorine residuals in discharges are usually a factor of 10 lower than the initial dosing rate. Even so, concentrations of chlorine compounds can exceed lethal limits for organisms at some sites.
environment. These effects can be defined briefly as follows.
Biological Effects of Temperature
•
The biological effects of temperature on marine and coastal organisms have been reviewed by a number of authors. Most animals and plants can survive ranges of temperature which are essentially genetically determined. The ultimate lethal temperature varies within poikilothermic groups but there is a trend of tolerance which is inversely related to the structural complexity of the organism (Table 1). Thus groups of microorganisms tend to contain species which have much higher tolerances than invertebrates, fish, or vascular plants. Because the life processes and survival of many organisms is so dependent on water temperature many species have developed physiological or behavioral strategies for optimizing temperature exposure and for survival in extremes of heat or cold. Examples are to be found among intertidal species and in polar fish. The effects of temperature on organisms can be classified mainly from experimental data as lethal, controlling, direct, and indirect and all are relevant to the effects of thermal discharges in the marine
Table 1 Upper temperature limits for aquatic organisms. Data from studies of geothermal watersa Group
Temperature (1C)
Animals Fish and other aquatic vertebrates Insects Ostracods (crustaceans) Protozoa
38 45–50 49–50 50
Plants Vascular plants Mosses Eukaryotic algae Fungi
45 50 56 60
Prokaryotic microorganisms Blue–green algae Photosynthetic bacteria Nonphotosynthetic bacteria a
70–73 70–73 499
Reproduced with permission from Langford (1990).
•
•
•
Lethal: high or low temperatures which will kill an organism within a finite time, usually less than its normal life span. The lethal temperature for any one organism depends on many factors within genetic limits. These include acclimatization, rate of change of temperature, physiological state (health) of the organism and any adaptive mechanisms. Controlling: temperatures below lethal temperatures which affect life processes, i.e., growth, oxygen consumption, digestive rates, or reproduction. There is a general trend for most organisms to show increases in metabolic activity with increasing temperature up to a threshold after which it declines sharply. Direct: temperatures causing behavioral responses such as avoidance or selection, movements, or migrations. Such effects have been amply demonstrated in experiments but for some work in situ the effects are not always clear. Indirect: where temperatures do not act directly but through another agent, for example poisons or oxygen levels or through effects on prey or predators. Temperature acts synergistically with toxic substances which can be important to its effects on chlorine toxicity in situ in thermal plumes. Where temperature immobilizes or kills prey animals they can become much more vulnerable to predation.
Biological Effects of Thermal Discharges The translation of data obtained from experimental studies to field sites is often not simple. The complexity of the natural environment can mask or exacerbate effects so that they bear little relation to experimental conditions and this has occurred in many studies of thermal discharges in situ. Further, factors other than that being studied may be responsible for the observed effects. Examples relevant to thermal discharges are discussed later in this article. Entrainment
The biological effects of any thermal discharge on marine organisms begin before the effluent is discharged. Cooling water abstracted from the sea usually contains many planktonic organisms notably bacteria, algae, small crustacea, and fish larvae. Within the power station cooling system these
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THERMAL DISCHARGES AND POLLUTION
organisms experience a sudden increase in temperature (10–201C, depending on the station) as they pass through the cooling condensers. They will also experience changes in pressure (1–2 atm) and be dosed with chlorine (0.5–5 mg l1) during this entrainment, with the effect that many organisms may be killed before they are discharged to the receiving water. Estimates for power stations in various countries have shown that if the ultimate temperatures are less than 231C the photosynthesis of entrained planktonic marine algae may increase, but at 27–281C a decrease of 20% was recorded. At 29–341C the rates decreased by 61–84% at one US power station. Only at temperatures exceeding 401C has total mortality been recorded. Concentrations of chlorine (total residual) of 1.0 mg l1 have been found to depress carbon fixation in entrained algae by over 90% irrespective of temperature (Figure 4). Diatoms were less affected than other groups and the effects in open coastal waters were less marked than in estuarine waters. Unless the dose was high enough to cause complete mortality many algae showed evidence of recovery.
1.2
Carbon fixation (discharge / intake)
1.0
0.8
0.6
13
The mean mortality rates for marine zooplankton entrained through cooling-water systems were shown to be less than 30% except in unusual cases where extreme temperatures and high chlorine doses caused 100% mortality. High mortalities can also occur where the entrained organisms are exposed to high temperatures in cooling ponds after discharge from the cooling system. In general, zooplankton do not suffer percentage mortalities as high as those of phytoplankton under typical cooling-water conditions. After passing through the cooling system at a US power station the dead or dying zooplankton were observed being eaten by large numbers of fish gathered at the outfall and hence passed into the food chain. There are few published observations of marine macro-invertebrates entrained in cooling-water systems though at a site in the UK, field experiments showed that specimens of the prawn Palaemonetes varians were killed by mechanical damage as they passed through a cooling system. Larval fish are probably most vulnerable to the effects of entrainment, mostly killed by the combination of mechanical, chemical, and temperature effects. Mortalities of ichthyoplankton have varied from 27 to 100% at sites in the US and UK. Many of these were, however, on estuaries or tidal reaches of rivers. At a coastal site in California the mortality rate increased from 10 to 100% as temperatures rose from 31 to 381C. Some 13% mortalities occurred with no heat, mainly as a result of pressure and abrasion in the system. The significance of 20% larval mortalities to the natural populations of flounders (Platichthyes americanus) calculated for a site on Long Island Sound indicated that the annual mortality was estimated at a factor of 0.01 which might cause a reduction of 9% of the adult population over 35 years provided the fish showed no compensatory reproductive or survival mechanism, or no immigration occurred.
0.4
Effects of Discharges in Receiving Waters 0.2
Algae
At some US power stations the metabolism of phytoplankton was found to be inhibited by chlorine as far as 200 m from the outfall. Also, intermittent 0 0.2 0.4 0.6 0.8 1.0 1.2 0 1.4 1.6 chlorination caused reductions of 80–90% of the _1 Residual chlorine concentration (mg l ) photosynthetic activity some 50 m from the outfall at a site on the Californian coast. From an assessment Figure 4 The effect of cooling water chlorination on carbon of the total entrainment and discharge effects, howfixation in marine phytoplankton. #, San Onofre; þ , Morgantown; , Hudson River; , Fawley; &, Dunkerque. ever, it was reported that where dilution was 300 (Reproduced with permission from Langford, 1990.) times per second the effect of even a 100% kill of
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14
THERMAL DISCHARGES AND POLLUTION
phytoplankton would not be detectable in the receiving water. In Southampton Water in the UK, mortality rates of 60% were estimated as causing about 1.2–3% reduction in the productivity of the tidal exchange volume where a power station used 6% of this for cooling. The main problem with most assessments is that replication of samples was typically low and estimates suggest that 88 samples would be needed from control and affected areas to detect a difference of 5% in productivity at a site, 22 samples for a 10% change and at least six for a 20% change. Such replication is rarely recorded in site studies. Temperatures of 35–361C killed shore algae at a coastal site in Florida, particularly Halimeda sp. and Penicillus spp. but factors other than temperature, most likely chlorine and scour, removed macro-algae at another tropical site. Blue–green algae were found where temperatures reached 401C intermittently and Enteromorpha sp. occurred where temperatures of 391C were recorded. In more temperate waters the algae Ascophyllum and Fucus were eliminated where temperatures reached 27–301C at an outfall but no data on chlorination were shown. Replacing the shoreline outfall with an offshore diffuser outfall (which increased dilution and cooling rates) allowed algae to recolonize and recover at a coastal power station in Maine (US). On the Californian coast one of the potentially most vulnerable algal systems, the kelps Macrocystis, were predicted to be badly affected by power station effluents, but data suggest that at one site only about 0.7 ha was affected near the outfall. The seagrass systems (Thalassia spp.) of the Florida coastal bays appeared to be affected markedly by the effluents from the Turkey Point power stations and a long series of studies indicated that within the þ 3 to þ 41C isotherm in the plume, seagrass cover declined by 50% over an area of 10–12 ha. However, the results from two sets of studies were unequivocal as to the effects of temperature. The data are outlined briefly in the following summary. First, the effluent was chlorinated. Second it contained high levels of copper and iron. Third, the main bare patch denuded of seagrass, according to some observations, may have been caused by the digging of the effluent canal. Although one set of data concluded that the threshold temperature for adverse effects on seagrass was þ 1.51C (summer 33–351C) a second series of observations noted that Thalassia persisted apparently unharmed in areas affected by the thermal discharge, though temperatures rarely exceed 351C. From an objective analysis, it would appear that the effects were caused mainly by a combination of thermal and chemical stresses.
Zooplankton and Microcrustacea
In Southampton Water in the UK, the barnacle Elminius modestus formed large colonies in culverts at the Marchwood power station and discharged large numbers of nauplii into the effluent stream increasing total zooplankton densities. Similar increases occurred where fouling mussels (Mytilus sp.) released veliger larvae into effluent streams. Data from 10 US coastal power stations were inconclusive about the effects of thermal discharges on zooplankton in receiving waters with some showing increases and others the reverse. Changes in community composition in some areas receiving thermal discharges were a result of the transport of species from littoral zones to offshore outfalls or vice versa. At Tampa Bay in Florida no living specimens of the benthic ostracod Haplocytheridea setipunctata were found when the temperature in the thermal plume exceeded 351C. Similarly the benthic ostracod Sarsiella zostericola was absent from the area of a power effluent channel in the UK experiencing the highest temperature range. Macro-invertebrates
As with other organisms there is no general pattern of change in invertebrate communities associated with thermal discharges to the sea which can be solely related to temperature. Some of the earliest studies in enclosed temperate saline waters in the UK showed that no species was consistently absent from areas affected by thermal plumes and the studies at Bradwell power station on the east coast showed no evidence of a decline in species richness over some 20 years though changes in methodology could have obscured changes in the fauna. No changes in bottom fauna were recorded at other sites affected by thermal plumes in both Europe and the US. The polychaete Heteromastus filiformis was found to be common to many of the thermal plume zones in several countries. In these temperate waters temperatures rarely exceeded 33–351C. In contrast, in tropical coastal waters data suggest that species of invertebrates are excluded by thermal plumes. For example in Florida, surveys showed that some 60 ha of the area affected by the Turkey Point thermal plume showed reduced diversity and abundance of benthos in summer, but there was marked recovery in winter. The 60 ha represented 0.0023% of the total bay area. A rise of 4–51C resulted in a dramatic reduction in the benthic community. Similarly, at Tampa Bay, 35 of the 104 indigenous invertebrate species were excluded from the thermal plume area. Removal of the vegetation was considered to be the primary cause of the loss of benthic
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THERMAL DISCHARGES AND POLLUTION
invertebrates. In an extreme tropical case few species of macro-invertebrates survived in a thermal effluent where temperatures reached 401C, 10 species occurred at the 371C isotherm and the number at the control site was 87. Scour may have caused the absence of species from some areas nearer the outfall (Figure 5). The effluent was chlorinated but no data on chlorine concentrations were published. Corals suffered severe mortalities at the Kahe power station in Hawaii but the bleaching of the colonies suggested that again chlorine was the primary cause of deaths, despite temperatures of up to 351C. It has been suggested that temperature increases of as little as 1– 21C could cause damage to tropical ecosystems but detailed scrutiny of the data indicate that it would be difficult to come to that conclusion from field data, especially where chlorination was used for antifouling. The changes in the invertebrate faunas of rocky shores in thermal effluents have been less well studied. Minimal changes were found on breakwaters in the paths of thermal plumes at two Californian sites. Any measurable effects were within 200–300 m of the outfalls. In contrast in southern France a chlorinated thermal discharge reduced the numbers of
100 C
90
C
80 2 3
Number of species
70
2 4
3 4
60 50
5
40
1
1
6
30
7
20
5
6
10 0
7 24
26
28
30
32
34
36
38
40
Temperature (°C) (from field measurements) Figure 5 Numbers of invertebrate species recorded at various temperatures, taken from two separate surveys ( , October; , winter) at Guyanilla Bay. C, control sampling; 1–7, effluent sampling sites. (Reproduced with permission from Langford, 1990.)
15
species on rocks near the outfall though 11 species of Hydroida were found in the path of the effluent. In most of the studies, chlorine would appear to be the primary cause of reductions in species and abundance though where temperatures exceeded 371C both factors were significant. There is some evidence that species showed advanced reproduction and growth in the thermal plumes areas of some power stations where neither temperature nor chlorine were sufficient to cause mortality. Also behavioral effects were demonstrated for invertebrates at a Texas coastal power station. Here, blue crabs (Callinectes sapidus) and shrimps (Penaeus aztecus and P. setiferus) avoided the highest temperatures (exceeding 381C) in the discharge canal but recolonized as temperatures fell below 351C. At another site in tropical waters, crabs (Pachygrapsus transversus) avoided the highest temperatures (and possibly chlorine) by climbing out of the water on to mangrove roots. Fish
There are few records of marine fish mortalities caused by temperature in thermal discharges except where fish are trapped in effluent canals. For example mortalities of Gulf menhaden (Brevoortia petronus), sea catfish (Arius felis) occurred in the canal of a Texas power station when temperatures reached 391C. Also a rapid rise of 151C killed menhaden (Alosa sp.) in the effluent canal of the Northport power station in the US. Avoidance behavior prevents mortalities where fish can move freely. The apparent attraction of many fish species to thermal discharges, widely reported, was originally associated with behavioral thermoregulation and the selection of preferred temperatures. Perhaps the best recorded example is the European seabass (Dicentrarchus labrax) found associated with cooling-water outfalls in Europe. Temperature selection is, however, not now believed to be the cause of the aggregations. Careful analysis and observations indicate clearly that the main cause of aggregation is the large amounts of food organisms discharged either dead or alive in the discharge. Millions of shrimps and small fish can be passed through into effluents and are readily consumed by the aggregated fish. Further where fish have gathered, usually in cooler weather, they remain active in the warmer water and are readily caught by anglers unlike the individuals outside the plume. This also gives the impression that there are more fish in the warmer water. Active tracking of fish has shown mainly short-term association with outfalls though some species have been
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16
THERMAL DISCHARGES AND POLLUTION 360 320 (C)
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Kingsnorth × and SD (measured) (heated canal) Irish Sea (median) Kingsnorth (back-calculated) Fawley (measured) Severn (measured) Morocco (measured)
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Age, at December (observed) Figure 6 Growth of bass (Dicentrarchus labrax) in a thermal discharge canal in comparison to other locations. Note that back calculated lengths are smaller because they probably relate to cold water growth. (Reproduced with permission from Langford, 1990.)
shown as entering water at temperatures above their lethal maximum for very short periods to collect food. There is clear evidence, however, that fish avoid adversely high temperatures for most of the time and will return to a discharge area once the temperatures cool. Avoidance behavior is also apparent at high chlorine concentrations. Where water temperatures and chemical conditions allow consistent residence, fish in thermal discharge canals show increased growth (Figure 6). At the Kingsnorth power station in the UK seabass (D. labrax) grew at twice the rate as in cold water, particularly in the first year. Fish showed varying residence times and sequential colonization of the canal at various ages. Winter growth occurred and the scales of older fish with long-term association with the discharge showed no evidence of annual winter growth checks. The fish were able to move into and out of the canal freely.
Occurrence of Exotic Species Exotic or introduced marine invertebrate species have been recorded from thermal discharges in various parts of the world. Some of the earliest were from the enclosed docks heated by power station effluents near Swansea and Shoreham in the UK. The exotic barnacle Balanus amphitrite var. denticulata
and the woodborer Limnoria tripunctata replaced the indigenous species in the heated areas but declined in abundance when the effluent ceased. The polyzoan Bugula neritina originally a favored immigrant species in the heated water disappeared completely as the waters cooled. In New Jersey (USA) subtropical species of Teredo bred in a heated effluent and both the ascidian Styela clavata and the copepod Acartia tonsa have both been regarded as immigrant species favored by heated effluents. However many immigrant species have survived in temperate waters without being associated with heated waters. In UK waters, only the crab Brachynotus sexdentatus and the barnacle B. amphitrite may be regarded as the only species truly associated with thermal discharges despite records of various other species. The decline of the American hard shell clam fishery (Mercenaria mercenaria) introduced to Southampton Water in the UK was reportedly caused by the closure of the Marchwood power station combined with overfishing. Recruitment of young clams and their early growth were maximized in the heated water and reproduction was advanced but all declined as the thermal discharge ceased.
Aquaculture in Marine Thermal Discharges The use of marine thermal discharges from power stations for aquaculture has not been highly successful in most parts of the world. Although it is clear that some species will grow faster in warmer water, the presence and unpredictability of chlorination has been a major obstacle. It is not generally economically viable to allow a large power station to become fouled such that efficiency declines merely to allow fish to grow. In Japan some farming ventures are regarded as profitable at power stations but in Europe and the USA such schemes are rarely profitable. At the Hunterston power station in Scotland plaice (Pleuronectes platessa) and halibut (Hippoglossus hippoglossus) grew almost twice as fast in warm water as in natural ambient but the costs of pump maintenance and capital equipment caused the system to be uneconomic irrespective of chlorination problems. Optimization of temperature is also a problem especially where temperatures fluctuate diurnally or where they exceed optimal growth temperatures. The general conclusion is that commercial uses of heated effluents in marine systems are not yet proven and are unlikely to become large-scale global ventures.
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THERMAL DISCHARGES AND POLLUTION
Thermal Discharges and Future Developments The closure of many older, less-efficient power stations, has led to an increase in the efficiency of the use of water and a decline in the discharge of heat to the sea per unit of electricity generated. However, the increasing industrialization of the developing countries, China, Malaysia, India and the African countries is leading to the construction of new, large power stations in areas not previously developed. The widespread use of CCGT stations can reduce the localized problems of heat loss and water use further as well as reducing emissions of carbon dioxide and sulphur dioxide to the air but the overall increase in power demand and generation will lead to an increase in the total aerial and aquatic emissions in some regions. In some tropical countries the delicate coastal ecosystems will be vulnerable not only to heat and higher temperature but much more importantly to the biocides used for antifouling. There is as yet no practical alternative that is as economic as chlorine though different methods have been tried with varying success in some parts of the world. There is little doubt that the same problems will be recognized in the areas of new development but as in the past after they have occurred.
17
that are more tolerant or less exposed. Constraints should therefore be tailored to each specific site and ecosystem. Irrespective of temperature it is also very clear that chlorination or other biocidal treatment has been responsible for many of the adverse ecological effects originally associated with temperature. The solution to fouling control and the reduction of chlorination of other antifouling chemicals is therefore probably more important than reducing heat loss and discharge temperatures particularly where vulnerable marine ecosystems are at risk.
See also Deep-Sea Ridges, Microbiology. Demersal Species Fisheries. Dispersion from Hydrothermal Vents. Fish Ecophysiology. Geophysical Heat Flow. Heat and Momentum Fluxes at the Sea Surface. Hydrothermal Vent Biota. Hydrothermal Vent Deposits. Hydrothermal Vent Ecology. Hydrothermal Vent Fluids, Chemistry of. Mesopelagic Fishes. Ocean Thermal Energy Conversion (OTEC). Pelagic Fishes. Satellite Remote Sensing of Sea Surface Temperatures. Upper Ocean Heat and Freshwater Budgets. Upper Ocean Mixing Processes. Wind- and BuoyancyForced Upper Ocean.
Conclusions It is clear that the problems of the discharge of heated effluents are essentially local and depend on many factors. Although temperatures of over 371C are lethal to many species which cannot avoid exposure, there are species which can tolerate such temperatures for short periods. Indeed it can be concluded for open coastal waters that discharge temperatures may exceed the lethal limits of mobile species at least for short periods. This, of course, would not apply if vulnerable sessile species were involved, though again some provisos may be acceptable. For example, an effluent which stratified at the surface in deep water would be unlikely to affect the benthos. On the other hand an effluent which impinges on the shore may need strict controls to protect the benthic community. From all the data it is clear that blanket temperature criteria intended to cover all situations would not protect the most vulnerable ecosystems and may be too harsh for those
Further Reading Barnett PRO and Hardy BLS (1984) Thermal deformations. In: Kinne O (ed.) Marine Ecology, vol. V. Ocean Management, part 4, Pollution and Protection of the Seas, Pesticides, Domestic Wastes and Thermal Deformations, pp. 1769–1926. New York: Wiley. Jenner HA, Whitehouse JW, Taylor CJL and Khalanski M (1998) Cooling Water Management in European Power Stations: Biology and Control of Fouling. Hydroecologie Appliquee. Electricite´ de France. Kinne O (1970) Marine Ecology, vol. 1, Environmental Factors, part 1. New York: Wiley-Interscience. Langford TE (1983) Electricity Generation and the Ecology of Natural Waters. Liverpool: Liverpool University Press. Langford TE (1990) Ecological Effects of Thermal Discharges. London: Elsevier Applied Science. Newell RC (1970) The Biology of Intertidal Animals. London: Logos Press.
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THREE-DIMENSIONAL (3D) TURBULENCE
Introduction
Figure 2 illustrates the main physical mechanisms that drive turbulence at the smallest scales. The description is presented in terms of strain and vorticity, quantities that represent the tendency of the flow at any point to deform and to rotate fluid parcels, respectively. A major and recent insight is that vorticity and strain are not distributed randomly in turbulent flow, but rather are concentrated into coherent regions, each of which is dominated by one type of motion or the other. The first mechanism we consider is vortex rollup due toshear instability. This process
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The Mechanics of Turbulence
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This article describes fluid turbulence withapplication to the Earth’s oceans. We begin with the simple, classical picture of stationary, homogeneous, isotropic turbulence. We then discuss departures from this idealized state that occur in small-scale geophysical flows. The discussion closes with a tour of some of the many physical regimes in which ocean turbulence has been observed. Turbulent flow has been a source of fascination for centuries. The term ‘turbulence’ appears to have been used first in reference to fluid flows by da Vinci, who studied the phenomenon extensively. Today, turbulence is frequently characterized as the last great unsolved problem of classical physics. It plays a central role in both engineering and geophysical fluid flows. Its study led to the discovery of the first strange attractor by Lorenz in 1963, and thus to the modern science of chaotic dynamics. In the past few decades, tremendous insight into the physics of turbulence has been gained through theoretical and laboratory study, geophysical observations, improved experimental techniques, and computer simulations. Turbulence results from the nonlinear nature of advection, which enables interaction between motions on different spatial scales. Consequently, an initial disturbance with a given characteristic length scale tends to spread to progressively larger and smaller scales. This expansion of the spectral range is limited at large scales by boundaries and/or body forces, and at small scales by viscosity. If the range of scales becomes sufficiently large, the flow takes a highly complex form whose details defy prediction. The roles played by turbulence in the atmosphere and oceans can be classified into two categories: momentum transport and scalar mixing. In transporting momentum, turbulent motions behave in a manner roughly analogous to molecular viscosity, reducing differences in velocity between different regions of a flow. For example, winds transfer momentum to the Earth via strong turbulence in the planetary boundary layer (a kilometer-thick layer adjacent to the ground) and are thus decelerated.
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This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2947–2955, & 2001, Elsevier Ltd.
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Scalar mixing refers to the homogenization of fluid properties such as temperature by random molecular motions. Molecular mixing rates are proportional to spatial gradients, which are greatly amplified due to the stretching and kneading (i.e. stirring) of fluid parcels by turbulence. This process is illustrated in Figure 1, which shows the evolution of an initially circular region of dyed fluid in a numerical simulation. Under the action of molecular mixing (or diffusion) alone, an annular region of intermediate shade gradually expands as the dyed fluid mixes with the surrounding fluid. If the flow is turbulent, the result is dramatically different. The circle is distended into a highly complex shape, and the region of mixed fluid expands rapidly.
Di ffu
W. D. Smyth and J. N. Moum Oregon State University, Corvallis, OR, USA
Figure 1 A comparison of mixing enhanced by turbulence with mixing due to molecular processes alone, as revealed by a numerical solution of the equations of motion. The initial state includes a circular region of dyed fluid in a white background. Two possible evolutions are shown: one in which the fluid is motionless (save for random molecular motions), and one in which the fluid is in a state of fully developed, two-dimensional turbulence. The mixed region (yellow–blue) expands much more rapidly in the turbulent case.
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THREE-DIMENSIONAL (3D) TURBULENCE
Figure 2 Schematic illustration of line vortices and strained regions in turbulent flow. Fluid parcels in the vortex interiors rotate with only weak deformation. In contrast, fluid parcels moving between the vortices are rapidly elongated in the direction of the purple arrows and compressed in the direction of the green arrows.
results in a vorticity concentration of dimension close to unity, i.e. a line vortex. Line vortices are reinforced by the process of vortex stretching. When a vortex is stretched by the surrounding flow, its rotation rate increases to conserve angular momentum. Opposing these processes is molecular viscosity, which both dissipates vorticity and fluxes it away from strongly rotational regions. Turbulence may thus be visualized as a loosely tangled ‘spaghetti’ of line vortices, which continuously advect each other in complex ways (Figure 3). At any given time, some vortices are being created via rollup, some are growing due to vortex stretching, and some are decaying due to viscosity. Many, however, are in a state of approximate equilibrium among these processes, so that they appear as long-lived, coherent features of the flow. Mixing is not accomplished within the vortices themselves; in fact, these regions are relatively stable, like the eye of a hurricane. Instead, mixing occurs mainly in regions of intense strain that exist between any two nearby vortices that rotate in the same sense (Figure 2). It is in these regions that fluid parcels are deformed to produce amplified gradients and consequent rapid mixing.
Stationary, Homogeneous, Isotropic Turbulence Although the essential structures of turbulence are not complex (Figure 2), they combine in a bewildering range of sizes and orientations that defies analysis (Figure 3). Because of this, turbulence is most usefully understood in statistical terms. Although the statistical approach precludes detailed
19
Figure 3 Computer simulation of turbulence as it is believed to occur in the ocean thermocline. The colored meshes indicate surfaces of constant vorticity.
prediction of flow evolution, it does give access to the rates of mixing and property transport, which are of primary importance in most applications. Statistical analyses focus on the various moments of the flowfield, defined with respect to some averaging operation. The average may betaken over space and/or time, or it may be an ensemble average taken overmany flows begun with similar initial conditions. Analyses are often simplified using three standard assumptions. The flow statistics are assumed to be
• • •
stationary (invariant with respect to translations intime), homogeneous (invariant with respect to translations inspace), and/or isotropic (invariant with respect to rotations).
Much of our present understanding pertains to this highly idealized case. Our description will focus on the power spectra that describe spatial variability of kinetic energy and scalar variance. The spectra provide insight into the physical processes that govern motion and mixing at different spatial scales. Velocity Fields
Big whorls have little whorls That feed on their velocity And little whorls have lesser whorls And so on to viscosity L.F. Richardson (1922) Suppose that turbulence is generated by a steady, homogeneous, isotropic stirring force whose spatial
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20
THREE-DIMENSIONAL (3D) TURBULENCE
variability is described by the Fourier wavenumber kF . Suppose further that the turbulence is allowed to evolve until equilibrium is reached between forcing and viscous dissipation, i.e., the turbulence is statistically stationary. Figure 4 shows typical wavenumber spectra of kinetic energy, EðkÞ, and kinetic energy dissipation, DðkÞ, for such a flow. EðkÞdk is the kinetic energy contained in motions whose wavenumber magnitudes lie in an interval of width dk surrounding k. DðkÞdk ¼ nk2 EðkÞdk is the rate at which that kinetic energy is dissipated by molecular viscosity (n) in that wavenumber band. R NThe net rate of energy dissipation is given by e ¼ 0 dk, and is equal (in the equilibrium state) to the rate at which energy is supplied by the stirring force. Nonlinear interactions induce a spectral flux, or cascade, of energy. The energy cascade is directed primarily (though not entirely) toward smaller scales, i.e., large-scale motions interact to create smaller-scale motions. The resulting small eddies involve sharp velocity gradients, and are therefore susceptible to viscous dissipation. Thus, although kinetic energy resides mostly in large-scale motions, it is dissipated primarily by small-scale motions. (Note that the logarithmic axes used in Figure 4 tend to de-emphasize the peaks in the energy and dissipation rate spectra.) Turbulence can be envisioned as a ‘pipeline’ conducting kinetic energy through wavenumber space: in at the large scales, down the spectrum, and out again at the small scales, all at a rate e. The cascade concept was first suggested early Energy
/
Inertial
E (k)
/
Dissipation
Energy, dissipation rate
D (k)
kF
kK Wavenumber
Figure 4 Theoretical wavenumber spectra of kinetic energy and kinetic energy dissipation for stationary, homogeneous, isotropic turbulence forced at wavenumber kF . Approximate locations of the energy containing, inertial, and dissipation subranges are indicated, along with the Kolmogorov wavenumber kk . Axes are logarithmic. Numerical values depend on Re and are omitted here for clarity.
in the twentieth century by L.F. Richardson, who immortalized his idea in the verse quoted at the beginning of this section. The energy spectrum is often divided conceptually into three sections. The energy-containing subrange encompasses the largest scales of motion, whereas the dissipation subrange includes the smallest scales. If the range of scales is large enough, there may exist an intermediate range in which the form of the spectrum is independent of both large-scale forcing and small-scale viscous effects. This intermediate range is called the inertial subrange. The existence of the inertial subrange depends on the value of the Reynolds number: Re ¼ ul=n, where u and l are scales of velocity and length characterizing the energy-containing range. The spectral distance between the energy-containing subrange and the dissipation 3=4 subrange, kF =kK , is proportional to Re . A true inertial subrange exists only in the limit of large Re . In the 1940s, the Russian statistician A.N. Kolmogorov hypothesized that, in the limit Re -N, the distribution of eddy sizes in the inertial and dissipation ranges should depend on only two parameters (besides wavenumber): the dissipation rate e and the viscosity n, i.e., E ¼ Eðk; e; nÞ. Dimensional reasoning then implies that E ¼ e1=4 n5=4 f ðk=kK Þ, where kK ¼ ðe=n3 Þ1=4 is the Kolmogorov wavenumber and f is some universal function. Thus, with the assumptions of stationarity, homogeneity, isotropy, and infinite Reynolds number, all types of turbulence, from flow over a wing to convection in the interior of the sun, appear as manifestations of a single process whose form depends only on the viscosity of the fluid and the rate at which energy is transferred through the ‘pipeline’. This tremendous simplification is generally regarded as the beginning of the modern era of turbulence theory. Kolmogorov went on to suggest that the spectrum in the inertial range should be simpler still by virtue of being independent of viscosity. In that case E ¼ Eðk; eÞ, and the function can be predicted from dimensional reasoning alone up to the universal constant CK , namely, E ¼ CK e2=3 k5=3 . This powerlaw spectral form indicates that motions in the inertial subrange are self-similar, i.e., their geometry is invariant under coordinate dilations. Early efforts to identify the inertial subrange in laboratory flows were inconclusive because the Reynolds number could not be made large enough. (In a typical, laboratory-scale water channel, uB0:1ms1 , lB0:1m, and nB106 m2 s1 , giving Re B104 . In a typical wind tunnel, uB1ms1 , B1m, and nB106 m2 s1 , so that Re B105 .) The inertial subrange spectrum was first verified in 1962 using measurements in a strongly turbulent tidal channel
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THREE-DIMENSIONAL (3D) TURBULENCE
Passive Scalars and Mixing
Now let us suppose that the fluid possesses some scalar property y, such as temperature or the concentration of some chemical species, and that the scalar is dynamically passive, i.e., its presence does not affect the flow. (In the case of temperature, this is true only for sufficiently small-scale fluctuations; see Buoyancy Effects later in this article for details.) Suppose also that there is a source of large-scale variations in y, e.g., an ambient temperature gradient in the ocean. Isosurfaces of y will be folded and kneaded by the turbulence so that their surface area tends to increase. As a result, typical gradients of y will also increase, and will become susceptible to erosion by molecular diffusion. Scalar variance is destroyed at a rate w, which is equal (in equilibrium) to the rate at which variance is produced by the large eddies. Thus, the turbulent mixing of the scalar proceeds in a manner similar to the energy cascade discussed above. However, there is an important difference in the two phenomena. Unlike energy, scalar variance is driven to small scales by a combination of two processes. First, scalar gradients are compressed by the strain fields between the turbulent eddies. Second, the eddies themselves are continually redistributed toward smaller scales. (The latter process is just the energy cascade described in the previous section.) Figure 5 shows the equilibrium scalar variance spectrum for the case of heat mixing in water. Most of the variance is contained in the large scales, which are separated from the small scales by an inertialconvective subrange (so-called because temperature variance is convected by motions in the inertial subrange of the energy spectrum). Here, the spectrum depends only on e and w; its form is Ey ¼ bwe1=3 k5=3 , where b is a universal constant. The shape of the spectrum at small scales is very different from that of the energy spectrum, owing to the fact that, in sea water, the molecular diffusivity, k, of heat is smaller than the kinematic viscosity. The ratio of viscosity to thermal diffusivity is termed the Prandtl number (i.e. Pr ¼ n=k) and has a value near 7 for sea water. In the viscous-convective subrange, the downscale cascade of temperature variance is slowed because the eddies driving the cascade are weakened by viscosity. In other words, the first of the two
Variance-
containing Scalar variance, dissipation rate
near Vancouver Island, where typical turbulent velocity scales uB1ms1 and length scales lB100 m combine with the kinematic viscosity of seawater nB106 m2 s1 to produce a Reynolds number Re B108 . From this experiment and others like it, the value of CK has been determined to be near 1.6.
/
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Viscousdiffusive
E θ (k) Dθ (k)
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Figure 5 Theoretical wavenumber spectra of scalar variance and dissipation for stationary, homogeneous, isotropic turbulence forced at wavenumber kF . Approximate locations of the variancecontaining, inertial-convective, viscous-convective, and viscousdiffusive subranges are indicated, along with the Kolmogorov wavenumber kK and the Batchelor wavenumber kB . Axes are logarithmic. Numerical values depend on Re and are omitted here for clarity.
processes listed above as driving the scalar variance cascade is no longer active. There is no corresponding weakening of temperature gradients, because molecular diffusivity is not active on these scales. As a result, there is a tendency for variance to ‘accumulate’ in this region of the spectrum and the spectral slope is reduced from 5=3 to 1. However, the variance in this range is ultimately driven into the viscous-diffusive subrange, where it is finally dissipated by molecular diffusion. A measure of the wavenumber at which scalar variance is dissipated is the Batchelor wavenumber, kB ¼ ðe=nk2 Þ1=4 . When Pr > 1, as for sea water, the Batchelor wavenumber is larger than the Kolmogorov wavenumber, i.e., temperature fluctuations can exist at smaller scales than velocity fluctuations. In summary, the energy and temperature spectra exhibit many similarities. Energy (temperature variance) is input at large scales, cascaded down the spectrum by inertial (convective) processes, and finally dissipated by molecular viscosity (diffusion). The main difference between the two spectra is the viscous-convective range of the temperature spectrum, in which molecular smoothing acts on the velocity field but not on the temperature field. This difference is even more pronounced if the scalar field represents salinity rather than temperature, for salinity is diffused even more weakly than heat. The ratio of the molecular diffusivities of heat and salt is of order 102, so that the smallest scales of salinity fluctuation in sea water are ten times smaller than those of temperature fluctuations.
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THREE-DIMENSIONAL (3D) TURBULENCE
Turbulence in Geophysical Flows The assumptions of homogeneity, stationarityand isotropy as employed by Kolmogorov have permitted tremendous advances inour understanding of turbulence. In addition, approximations based on theseassumptions are used routinely in all areas of turbulence research. However, wemust ultimately confront the fact that physical flows rarely conform to our simplifying assumptions. In geophysical turbulence, symmetries are upset by acomplex interplay of effects. Here, we focus on three important classes of phenomena that modify small-scale turbulence in the ocean: shear, stratification, and boundary proximity. Shear Effects
Geophysical turbulence often occurs in the presence of a current which varies on scales much larger than the energy-containing scales of the turbulence, and evolves much more slowly than the turbulence. Examples include atmospheric jet streams and largescale ocean currents such as the Gulf Stream and the Equatorial Undercurrent. In such cases, it makes sense to think of the background current as an entity separate from the turbulent component of the flow. Shear upsets homogeneity and isotropy by deforming turbulent eddies. By virtue of the resulting anisotropy, turbulent eddies exchange energy with the background shear through the mechanism of Reynolds stresses. Reynolds stresses represent correlations between velocity components parallel to and perpendicular to the background flow, correlations that would vanish if the turbulence were isotropic. Physically, they represent transport of momentum by the turbulence. If the transport is directed counter to the shear, kinetic energy is transferred from the background flow to the turbulence. This energy transfer is one of the most common generation mechanisms for geophysical turbulence. In sheared turbulence, the background shear acts primarily on the largest eddies. Motions on p scales ffiffiffiffiffiffiffiffiffi much smaller than the Corrsin scale, LC ¼ e=S3 (where S ¼ dU=dz, the vertical gradient of the ambient horizontal current) are largely unaffected. Buoyancy Effects
Most geophysical flows are affected to some degree by buoyancy forces, which arise due to spatial variations in density. Buoyancy breaks the symmetry of the flow by favoring the direction in which the gravitational force acts. Buoyancy effects can either force or damp turbulence. Forcing occurs in the case of unstable density stratification, i.e., when heavy
fluid overlies light fluid. This happens in the atmosphere on warm days, when the air is heated from below. The resulting turbulence is often made visible by cumulus clouds. In the ocean, surface cooling (at night) has a similar effect. Unstable stratification in the ocean can also result from evaporation, which increases surface salinity and hence surface density. In each of these cases, unstable stratification results in convective turbulence, which can be extremely vigorous. Convective turbulence usually restores the fluid to a stable state soon after the destabilizing flux ceases (e.g., when the sun rises over the ocean). Buoyancy effects tend to damp turbulence in the case of stable stratification, i.e., when light fluid overlies heavier fluid. In stable stratification, a fluid parcel displaced from equilibrium oscillates pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi vertically with frequency N ¼ gr1 dr=dz, the buoyancy or Brunt–Vaisala frequency (g represents acceleration due to gravity and rðzÞ is the ambient mass density). A result of stable stratification that can dramatically alter the physics of turbulence is the presence of internal gravity waves (IGW). These are similar to the more familiar interfacial waves that occur at the surfaces of oceans and lakes, but continuous density variation adds the possibility of vertical propagation. Visible manifestations of IGW include banded clouds in the atmosphere and slicks on the ocean surface. IGW carry momentum, but no scalar flux and no vorticity. In strongly stable stratification, motions may be visualized approximately as two-dimensional turbulence (Figure 1) flowing on nearly horizontal surfaces that undulate with the passage of IGW. The quasitwo-dimensional mode of motion carries all of the vorticity of the flow (since IGW carry none), and is therefore called the vortical mode. In moderately stable stratification, three-dimensional turbulence is possible, but its structure is modified by the buoyancy force, particularly at large scales. Besides producing anisotropy, the suppression of vertical motion damps the transfer of energy from any background shear, thus reducing the intensity of turbulence. On scales smaller than the Ozmipffiffiffiffiffiffiffiffiffiffimuch ffi dov scale, L0 ¼ e=N 3 , buoyancy has only a minor effect. (In Passive scalars and mixing above, we used temperature as an example of a dynamically passive quantity. This approximation is valid only on scales smaller than the Ozmidov scale.) The relative importance of stratification and shear depends on the magnitudes of S and N. If SbN, shear dominates and turbulence is amplified. On the other hand, if S5N, the buoyancy forces dominate and turbulence is suppressed. The relationship between IGW and turbulence in stratified flow is exceedingly complex. At scales in
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THREE-DIMENSIONAL (3D) TURBULENCE
excess of a few meters (Figure 6), ocean current fluctuations behave like IGW, displaying the characteristic spectral slope k1 . At scales smaller than the Ozmidov scale (typically a few tens of centimeters), fluctuations differ little from the classical picture of homogeneous, isotropic turbulence. The intermediate regime is a murky mix of nonlinear IGW and anisotropic turbulence that is not well understood at present. The breaking of IGW is thought to be the major source of turbulence in the ocean interior. Breaking occurs when a superposition of IGW generates locally strong shear and/or weak stratification. IGW propagating obliquely in a background shear may break on encountering a critical level, a depth at which the background flow speed equals the horizontal component of the wave’s phase velocity. (Many dramatic phenomena occur where wave speed matches flow speed; other examples include the hydraulic jump and the sonic boom.) Just as waves may generate turbulence, turbulent motions in stratified flow may radiate energy in the form of waves. In stably stratified turbulence, the distinction between stirring and mixing of scalar properties becomes crucial. Stirring refers to the advection and deformation of fluid parcels by turbulent motion, whereas mixing involves actual changes in the scalar properties of fluid parcels. Mixing can only be accomplished by molecular diffusion, though it is accelerated greatly in turbulent flow due to stirring (cf. Figure 1 and the accompanying discussion). In stable
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stratification, changes in the density field due to stirring are reversible, i.e., they can be undone by gravity. In contrast, mixing is irreversible, and thus leads to a permanent change in the properties of the fluid. For example, consider a blob of water that has been warmed at the ocean surface, then carried downward by turbulent motions. If the blob is mixed with the surrounding water, its heat will remain in the ocean interior, whereas if the blob is only stirred, it will eventually bob back up to the surface and return its heat to the atmosphere. Boundary Effects
It is becoming increasingly clear that most turbulent mixing in the ocean takes place near boundaries, either the solid boundary at the ocean bottom, or the moving boundary at the surface. All boundaries tend to suppress motions perpendicular to themselves, thus upsetting both the homogeneity and the isotropy of the turbulence. Solid boundaries also suppress motion in the tangential directions. Therefore, since the velocity must change from zero at the boundary to some nonzero value in the interior, a shear is set up, leading to the formation of a turbulent boundary layer. Turbulent boundary layers are analogous to viscous boundary layers, and are sites of intense, shear-driven mixing (Figure 7). In turbulent boundary layers, the characteristic size of the largest eddies is proportional to the distance from the boundary. Near the ocean surface, the flexible nature of the boundaries leads to a multitude of interesting phenomena, notably surface gravity waves and Langmuir cells. These phenomena contribute significantly to upper-ocean mixing and thus to air–sea fluxes of momentum, heat and various chemical species. Boundaries also include obstacles to the flow, such as islands and seamounts, which create turbulence. If flow over an obstacle is stably stratified, buoyancyaccelerated bottom flow and a downstream hydraulic jump may drive turbulence (Figure 7). Ocean turbulence is often influenced by combinations of shear, stratification, and boundary effects. In the example shown in Figure 7, all three effects combine to create an intensely turbulent flow that diverges dramatically from the classical picture of stationary, homogeneous, isotropic turbulence.
Length Scales of Ocean Turbulence
Vertical wavenumber
Figure 6 Energy spectrum (cf. Figure 4) extended to larger scales to include internal gravity waves (IGW) plus anisotropic stratified turbulence. Labels represent approximate length scales from ocean observations.
Examples of turbulent flow regimes that havebeen observed in the ocean can be considered in terms of typical values of e and N that pertain to each (Figure 8). This provides the information to estimate
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24
THREE-DIMENSIONAL (3D) TURBULENCE
Depth
20 m
40 m
1 km
2 km
Distance _7
_9
_5 _1
log10 (W kg )
m
0
=
1
10
O
=
L
O
L
Strait of Gibraltar hydraulic jump
10
–4
(m– 2 s – 3 )
both largest and smallest scales present in the flow. The largest scale is approximated by the Ozmidov scale, which varies from a few centimeters in the ocean’s thermocline to several hundred meters in weakly stratified and/or highly energetic flows. The smallest scale, the Kolmogorov scale LK ¼ k1 K , is typically 1 cm or less. Turbulence in the upper ocean mixed layer may be driven by wind and/or by convection due to surface cooling. In the convectively mixed layer, N is effectively zero within the turbulent region, and the maximum length scale is determined by the depth of the mixed layer. In both cases the free surface limits length scale growth. Turbulence in the upper equatorial thermocline is enhanced by the presence of shear associated with the strong equatorial zonal current system. Stratification tends to be considerably stronger in the upper thermocline than in the main thermocline. Despite weak stratification, turbulence in the main thermocline tends to be relatively weak due to isolation from strong forcing. Turbulence in this region is generated primarily by IGW interactions. Tidal channels are sites of extremely intense turbulence, forced by interactions between strong tidal currents and three-dimensional topography. Length scales are limited by the geometry of the channel. Turbulent length scales in the bottom boundary layer are limited below by the solid boundary and above by stratification. Intense turbulence is also found in hydraulically controlled flows, such as have been
m
Figure 7 Flow over Stonewall bank, on the continental shelf off the Oregon coast. Colors show the kinetic energy dissipation rate, with red indicating strong turbulence. White contours are isopycnals, showing the effect of density variations in driving the downslope flow. Three distinct turbulence regimes are visible: (1) turbulence driven by shear at the top of the rapidly moving lower layer, (2) a turbulent bottom boundary layer and (3) a hydraulic jump.
Tidal channel
10
Internal hydraulic flow on the Continental Shelf
–6
10
–8
Wind-mixed layers Convectively Upper equatorial mixed layers thermocline Bottom boundary layer Main thermocline
10
–4
–3
10
N (s )
10– 2
LK = 1 mm
LK = 5 mm
10–1
–1
Figure 8 Regimes of ocean turbulence located with respect to stratification and energy dissipation. Dotted lines indicate Ozmidov and Kolmogorov length scales.
found in the Strait of Gibraltar, and also over topography on the continental shelf (cf. Figure 7). In these flows the stratification represents a potential energy supply that drives strongly sheared downslope currents, the kinetic energy of which is in turn converted into turbulence and mixing. All of these turbulence regimes are subjects of ongoing observational and theoretical research, aimed at generalizing Kolmogorov’s view of turbulence to encompass the complexity of real geophysical flows.
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THREE-DIMENSIONAL (3D) TURBULENCE
25
See also
Further Reading
Atlantic Ocean Equatorial Currents. Brazil and Falklands (Malvinas) Currents. Breaking Waves and Near-Surface Turbulence. Heat and Momentum Fluxes at the Sea Surface. Heat Transport and Climate. Indian Ocean Equatorial Currents. Internal Waves. Island Wakes. Langmuir Circulation and Instability. Mesoscale Eddies. Open Ocean Convection. Turbulence in the Benthic Boundary Layer. Upper Ocean Mixing Processes. Vortical Modes.
Frisch U (1995) Turbulence. Cambridge: Cambridge University Press. Hunt JCR, Phillips OM, and Williams D (1991) Turbulence and Stochastic Processes; Kolmogoroff ’s Ideas 50 Years On. London: The Royal Society. Kundu PK (1990) Fluid Mechanics. London: Academic Press.
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TIDAL ENERGY A. M. Gorlov, Northeastern University, Boston, Massachusetts, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2955–2960, & 2001, Elsevier Ltd.
Introduction Gravitational forces between the moon, the sun and the earth cause the rhythmic rising and lowering of ocean waters around the world that results in Tide Waves. The moon exerts more than twice as great a force on the tides as the sun due to its much closer position to the earth. As a result, the tide closely follows the moon during its rotation around the earth, creating diurnal tide and ebb cycles at any particular ocean surface. The amplitude or height of the tide wave is very small in the open ocean where it measures several centimeters in the center of the wave distributed over hundreds of kilometers. However, the tide can increase dramatically when it reaches continental shelves, bringing huge masses of water into narrow bays and river estuaries along a coastline. For instance, the tides in the Bay of Fundy in Canada are the greatest in the world, with amplitude between 16 and 17 meters near shore. High tides close to these figures can be observed at many other sites worldwide, such as the Bristol Channel in England, the Kimberly coast of Australia, and the Okhotsk Sea of Russia. Table 1 contains ranges of amplitude for some locations with large tides. On most coasts tidal fluctuation consists of two floods and two ebbs, with a semidiurnal period of about 12 hours and 25 minutes. However, there are some coasts where tides are twice as long (diurnal tides) or are mixed, with a diurnal inequality, but are still diurnal or semidiurnal in period. The magnitude of tides changes during each lunar month. The
highest tides, called spring tides, occur when the moon, earth and sun are positioned close to a straight line (moon syzygy). The lowest tides, called neap tides, occur when the earth, moon and sun are at right angles to each other (moon quadrature). Isaac Newton formulated the phenomenon first as follows: ‘The ocean must flow twice and ebb twice, each day, and the highest water occurs at the third hour after the approach of the luminaries to the meridian of the place’. The first tide tables with accurate prediction of tidal amplitudes were published by the British Admiralty in 1833. However, information about tide fluctuations was available long before that time from a fourteenth century British atlas, for example. Rising and receding tides along a shoreline area can be explained in the following way. A low height tide wave of hundreds of kilometers in diameter runs on the ocean surface under the moon, following its rotation around the earth, until the wave hits a continental shore. The water mass moved by the moon’s gravitational pull fills narrow bays and river estuaries where it has no way to escape and spread over the ocean. This leads to interference of waves and accumulation of water inside these bays and estuaries, resulting in dramatic rises of the water level (tide cycle). The tide starts receding as the moon continues its travel further over the land, away from the ocean, reducing its gravitational influence on the ocean waters (ebb cycle). The above explanation is rather schematic since only the moon’s gravitation has been taken into account as the major factor influencing tide fluctuations. Other factors, which affect the tide range are the sun’s pull, the centrifugal force resulting from the earth’s rotation and, in some cases, local resonance of the gulfs, bays or estuaries.
Energy of Tides Table 1
Highest tides (tide ranges) of the global ocean
Country
Site
Tide range (m)
Canada England France France Argentina Russia Russia
Bay of Fundy Severn Estuary Port of Ganville La Rance Puerto Rio Gallegos Bay of Mezen (White Sea) Penzhinskaya Guba (Sea of Okhotsk)
16.2 14.5 14.7 13.5 13.3 10.0 13.4
26
The energy of the tide wave contains two components, namely, potential and kinetic. The potential energy is the work done in lifting the mass of water above the ocean surface. This energy can be calculated as: ð E ¼ grA zdz ¼ 0:5grAh2 ; where E is the energy, g is acceleration of gravity, r is the seawater density, which equals its mass per unit
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TIDAL ENERGY
volume, A is the sea area under consideration, z is a vertical coordinate of the ocean surface and h is the tide amplitude. Taking an average (gr) ¼ 10.15 kN m3 for seawater, one can obtain for a tide cycle per square meter of ocean surface: E ¼ 1:4h2 ; watt-hour or E ¼ 5:04h2 ; kilojoule The kinetic energy T of the water mass m is its capacity to do work by virtue of its velocity V. It is defined by T ¼ 0.5 m V2. The total tide energy equals the sum of its potential and kinetic energy components. Knowledge of the potential energy of the tide is important for designing conventional tidal power plants using water dams for creating artificial upstream water heads. Such power plants exploit the potential energy of vertical rise and fall of the water. In contrast, the kinetic energy of the tide has to be known in order to design floating or other types of tidal power plants which harness energy from tidal currents or horizontal water flows induced by tides. They do not involve installation of water dams.
Extracting Tidal Energy: Traditional Approach People used the phenomenon of tides and tidal currents long before the Christian era. The earliest navigators, for example, needed to know periodical tide fluctuations as well as where and when they could use or would be confronted with a strong tidal current. There are remnants of small tidal hydromechanical installations built in the Middle Ages around the world for water pumping, watermills and other applications. Some of these devices were exploited until recent times. For example, large tidal waterwheels were used for pumping sewage in Hamburg, Germany up to the nineteenth century. The city of London used huge tidal wheels, installed under London Bridge in 1580, for 250 years to supply fresh water to the city. However, the serious study and design of industrial-size tidal power plants for exploiting tidal energy only began in the twentieth century with the rapid growth of the electric industry. Electrification of all aspects of modern civilization has led to the development of various converters for transferring natural potential energy sources into electric power. Along with fossil fuel power systems and nuclear reactors, which create huge new environmental pollution problems, clean renewable energy sources have attracted scientists
27
and engineers to exploit these resources for the production of electric power. Tidal energy, in particular, is one of the best available renewable energy sources. In contrast to other clean sources, such as wind, solar, geothermal etc., tidal energy can be predicted for centuries ahead from the point of view of time and magnitude. However, this energy source, like wind and solar energy is distributed over large areas, which presents a difficult problem for collecting it. Besides that, complex conventional tidal power installations, which include massive dams in the open ocean, can hardly compete economically with fossil fuel (thermal) power plants, which use cheap oil or coal, presently available in abundance. These thermal power plants are currently the principal component of world electric energy production. Nevertheless, the reserves of oil and coal are limited and rapidly dwindling. Besides, oil and coal cause enormous atmospheric pollution both from emission of green house gases and from their impurities such as sulfur in the fuel. Nuclear power plants produce accumulating nuclear wastes that degrade very slowly, creating hazardous problems for future generations. Tidal energy is clean and not depleting. These features make it an important energy source for global power production in the near future. To achieve this goal, the tidal energy industry has to develop a new generation of efficient, low cost and environmentally friendly apparatus for power extraction from free or ultra-low head water flow. Four large-scale tidal power plants currently exist. All of them were constructed after World War II. They are the La Rance Plant (France, 1967), the Kislaya Guba Plant (Russia, 1968), the Annapolis Plant (Canada, 1984), and the Jiangxia Plant (China, 1985). The main characteristics of these tidal power plants are given in Table 2. The La Rance plant is shown in Figure 1. All existing tidal power plants use the same design that is accepted for construction of conventional river hydropower stations. The three principal structural and mechanical elements of this designare: a water dam across the flow, which creates an artificial water basin and builds up a water head for operation of hydraulic turbines; a number of turbines coupled with electric generators installed at the lowest point of the dam; and hydraulic gates in the dam to control the water flow in and out of the water basin behind the dam. Sluice locks are also used for navigation when necessary. The turbines convert the potential energy of the water mass accumulated on either side of the dam into electric energy during the tide. The tidal power plant can be designed for operation either by double or single action. Double action means that the turbines work in both water
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28
TIDAL ENERGY Table 2
Extant large tidal power plants
Country
Site
Installed power (MW)
Basin area (km2)
Mean tide (m)
France Russia Canada China
La Rance Kislaya Guba Annapolis Jiangxia
240 0.4 18 3.9
22 1.1 15 1.4
8.55 2.3 6.4 5.08
flows, i.e. during the tide when the water flows through the turbines, filling the basin, and then, during the ebb, when the water flows back into the ocean draining the basin. In single-action systems, the turbines work only during the ebb cycle. In this case, the water gates are kept open during the tide, allowing the water to fill the basin. Then the gates close, developing the water head, and turbines start
operating in the water flow from the basin back into the ocean during the ebb. Advantages of the double-action method are that it closely models the natural phenomenon of the tide, has least effect on the environment and, in some cases, has higher power efficiency. However, this method requires more complicated and expensive reversible turbines and electrical equipment. The
Figure 1 Aerial view of the La Rance Tidal Power Plant (Source: Electricite´de France).
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TIDAL ENERGY
single action method is simpler, and requires less expensive turbines. The negative aspects of the single action method are its greater potential for harm to the environment by developing a higher water head and causing accumulation of sediments in the basin. Nevertheless, both methods have been used in practice. For example, the La Rance and the Kislaya Guba tidal power plants operate under the double-action scheme, whereas the Annapolis plant uses a single-action method. One of the principal parameters of a conventional hydropower plant is its power output P (energy per unit time) as a function of the water flow rate Q (volume per time) through the turbines and the water head h (difference between upstream and downstream water levels). Instantaneous power P can be defined by the expression: P ¼ 9.81 Qh, kW, where Q is in m3s1, h is in meters and 9.81 is the product (rg) for fresh water, which has mass density r ¼ 1000 kg m3 and g ¼ 9.81 m s2. The (rg) component has to be corrected for applications in salt water due to its different density (see above). The average annual power production of a conventional tidal power plant with dams can be calculated by taking into account some other geophysical and hydraulic factors, such as the effective basin area, tidal fluctuations, etc. Tables 2 and 3 contain some characteristics of existing tidal power plants as well as prospects for further development of traditional power systems in various countries using dams and artificial water basins described above.
Extracting Tidal Energy: Non-traditional Approach As mentioned earlier, all existing tidal power plants have been built using the conventional design
Table 3
29
developed for river power stations with water dams as their principal component. This traditional river scheme has a poor ecological reputation because the dams block fish migration, destroying their population, and damage the environment by flooding and swamping adjacent lands. Flooding is not an issue for tidal power stations because the water level in the basin cannot be higher than the natural tide. However, blocking migration of fish and other ocean inhabitants by dams may represent a serious environmental problem. In addition, even the highest average global tides, such as in the Bay of Fundy, are small compared with the water heads used in conventional river power plants where they are measured in tens or even hundreds of meters. The relatively low water head in tidal power plants creates a difficult technical problem for designers. The fact is that the very efficient, mostly propeller-type hydraulic turbines developed for high river dams are inefficient, complicated and very expensive for lowhead tidal power application. These environmental and economic factors have forced scientists and engineers to look for a new approach to exploitation of tidal energy that does not require massive ocean dams and the creation of high water heads. The key component of such an approach is using new unconventional turbines, which can efficiently extract the kinetic energy from a free unconstrained tidal current without any dams. One such turbine, the Helical Turbine, is shown in Figure 2. This cross-flow turbine was developed in 1994. The turbine consists of one or more long helical blades that run along a cylindrical surface like a screwthread, having a so-called airfoil or ‘airplane wing’ profile. The blades provide a reaction thrust that can rotate the turbine faster than the water flow itself. The turbine shaft (axis of rotation) must be perpendicular to the water current, and the turbine can be positioned either horizontally or
Some potential sites for tidal power installations (traditional approach)
Country
Site
Potential power (MW)
Basin area (km2)
USA USA Russia Russia UK UK Argentina Korea Australia Australia
Passamaquoddy Cook Inlet Mezen Tugur Severn Mersey San Jose Carolim Bay Secure Walcott
400 Up to 18 000 15 000 6790 6000 700 7000 480 570 1750
300 3100 2640 1080 490 60 780 90 130 260
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Mean tide (m) 5.5 4.35 5.66 5.38 8.3 8.4 6.0 4.7 8.4 8.4
30
TIDAL ENERGY
a cross-flow area A is Pw ¼ 0.5rAV3. The turbine efficiency Z, also called power coefficient, is the ratio of the turbine power output Pt to the power of either the water head for traditional design or unconstrained water current Pw , i.e. Z ¼ Pt /Pw. The maximum power of the Uldolmok tidal project shown in Figure 3 is about 90 MW calculated using the above approach for V ¼ 12 knots, A ¼ 2100 m2 and Z ¼ 0.35. Along with the floating power farm projects with helical turbines described, there are proposals to use large-diameter propellers installed on the ocean floor to harness kinetic energy of tides as well as other ocean currents. These propellers are, in general, similar to the well known turbines used for wind farms.
Helical Turbine
Waterproof chamber for generator and data collectors
Ports
Figure 2 Double-helix turbine with electric generator for underwater installation.
vertically. Due to its axial symmetry, the turbine always develops unidirectional rotation, even in reversible tidal currents. This is a very important advantage, which simplifies design and allows exploitation of the double-action tidal power plants. A pictorial view of a floating tidal power plant with a number of vertically aligned triple-helix turbines is shown in Figure 3. This project has been proposed for the Uldolmok Strait in Korea, where a very strong reversible tidal current with flows up to12 knots (about 6 m s1) changes direction four times a day. The following expression can be used for calculating the combined turbine power of a floating tidal plant (power extracted by all turbines from a free, unconstrained tidal current): Pt ¼ 0.5ZrAV3, where Pt is the turbine power in kilowatts, Z is the turbine efficiency (Z ¼ 0.35 in most tests of the triple-helix turbine in free flow), r is the mass water density, A is the total effective frontal area of the turbines in m2 (cross-section of the flow where the turbines are installed) and V is the tidal current velocity in m s1. Note, that the power of a free water current through
Utilizing Electric Energy from Tidal Power Plants A serious issue that must be addressed is how and where to use the electric power generated by extracting energy from the tides. Tides are cyclical by their nature, and the corresponding power output of a tidal power plant does not always coincide with the peak of human activity. In countries with a welldeveloped power industry, tidal power plants can be a part of the general power distribution system. However, power from a tidal plant would then have to be transmitted a long distance because locations of high tides are usually far away from industrial and urban centers. An attractive future option is to utilize the tidal power in situ for year-round production of hydrogen fuel by electrolysis of the water. The hydrogen, liquefied or stored by another method, can be transported anywhere to be used either as a fuel instead of oil or gasoline or in various fuel cell energy systems. Fuel cells convert hydrogen energy directly into electricity without combustion or moving parts, which is then used, for instance, in electric cars. Many scientists and engineers consider such a development as a future new industrial revolution. However, in order to realize this idea worldwide, clean hydrogen fuel would need to be also available everywhere. At present most hydrogen is produced from natural gases and fossil fuels, which emit greenhouse gases into the atmosphere and harm the global ecosystem. From this point of view, production of hydrogen by water electrolysis using tidal energy is one of the best ways to develop clean hydrogen fuel by a clean method. Thus, tidal energy can be used in the future to help develop a new era of clean industries, for example, to clean up the automotive industry, as well as other energy-consuming areas of human activity.
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TIDAL ENERGY
31
Electric generators sit above the water
Figure 3 Artist rendition of the floating tidal power plant with vertical triple-helix turbines for Uldolmok Strait (Korean Peninsula).
Conclusion Tides play a very important role in the formation of global climate as well as the ecosystems for ocean habitants. At the same time, tides are a substantial potential source of clean renewable energy for future human generations. Depleting oil reserves, the emission of greenhouse gases by burning coal, oil and other fossil fuels, as well as the accumulation of nuclear waste from nuclear reactors will inevitably force people to replace most of our traditional energy sources with renewable energy in the future. Tidal energy is one of the best candidates for this approaching revolution. Development of new, efficient, low-cost and environmentally friendly hydraulic energy converters suited to free-flow waters, such as triple-helix turbines, can make tidal energy available worldwide. This type of machine, moreover, can be used not only for multi-megawatt tidalpower farms but also for mini-power stations with turbines generating a few kilowatts. Such power stations can
provide clean energy to small communities or even individual households located near continental shorelines, straits or on remote islands with strong tidal currents.
See also Flows in Straits and Channels. Tides.
Further Reading Bernshtein LB (ed.) (1996) Tidal Power Plants. Seoul: Korea Ocean Research and Development Institute (KORDI). Gorlov AM (1998) Turbines with a twist. In: Kitzinger U and Frankel EG (eds.) Macro-Engineering and the Earth: World Projects for the Year 2000 and Beyond, pp. 1--36. Chichester: Horwood Publishing. Charlier RH (1982) Tidal Energy. New York: Van Nostrand Reinhold.
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TIDES D. T. Pugh, University of Southampton, Southampton, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2961–2968, & 2001, Elsevier Ltd.
Introduction Even the most casual coastal visitor is familiar with marine tides. Slightly more critical observers have noted from early history, relationships between the movements of the moon and sun, and with the phases of the moon. Several plausible and implausible explanations for the links were advanced by ancient civilizations. Apart from basic curiosity, interest in tides was also driven by the seafarer’s need for safe and effective navigation, and by the practical interest of all those who worked along the shore. Our understanding of the physical processes which relate the astronomy with the complicated patterns observed in the regular tidal water movements is now well advanced, and accurate tidal predictions are routine. Numerical models of the ocean responses to gravitational tidal forces allow computations of levels both on- and offshore, and satellite altimetry leads to detailed maps of ocean tides that confirm these. The budgets and flux of tidal energy from the earth–moon dynamics through to final dissipation in a wide range of detailed marine processes has been an active area of research in recent years. For the future, there are difficult challenges in understanding the importance of these processes for many complicated coastal and open ocean phenomena.
The two main tidal features of any sea-level record are the range (measured as the height between successive high and low levels) and the period (the time between one high (or low) level and the next high (or low) level).Spring tides are semidiurnal tides of increased range, which occur approximately twice a month near the time when the moon is either new or full. Neap tides are the semidiurnal tides of small range which occur between spring tides near the time of the first and last lunar quarter. The tidal responses of the ocean to the forcing of the moon and the sun are very complicated and tides vary greatly from one site to another. Tidal currents, often called tidal streams, have similar variations from place to place. Semidiurnal, mixed, and diurnal currents occur; they usually have the same characteristics as the local tidal changes in sea level, but this is not always so. For example, the currents in the Singapore Strait are often diurnal in character, but the elevations are semidiurnal. It is important to make a distinction between the popular use of the word ‘tide’ to signify any change of sea level, and the more specific use of the word to mean only regular, periodic variations. We define tides as periodic movements which are directly related in amplitude and phase to some periodic geophysical force. The dominant geophysical forcing function is the variation of the gravitational field on the surface of the earth, caused by the regular movements of the Moon–Earth and Earth–Sun systems. Movements due to these gravitational forces are termed gravitational tides. This is to distinguish them from the smaller movements due to regular meteorological forces which are called eithermeteorological or more usually radiational tides.
Gravitational Potential Tidal Patterns Modern tidal theory began when Newton(1642– 1727) applied his formulation of the Law of Gravitational Attraction: that two bodies attract each other with a force which is proportional to the product of their masses and inversely proportional to the square of the distance between them. He was able to show why there are two tides for each lunar transit. He also showed why the half-monthly springto-neap cycle occurred, why once-daily tides are a maximum when the Moon is furthest from the plane of the equator, and why equinoctial tides are larger than those at the solstices.
32
The essential elements of a physical understanding of tide dynamics are contained in Newton’s Laws of Motion and in the principle of Conservation of Mass. For tidal analysis the basics are Newton’s Laws of Motion and the Law of Gravitational Attraction. The Law of Gravitational Attraction states that for two particles of masses m1 and m2, separated by a distance r the mutual attraction is: F¼G
m1 m2 r2
G is the universal gravitational constant.
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½1
TIDES
33
Use is made of the concept of the gravitational potential of a body; gravitational potential is the work which must be done against the force of attraction to remove a particle of unit mass to an infinite distance from the body. The potential at P on the Earth’s surface (Figure 1) due to the moon is:
The terms in Pn(cos f) are the Legendre Polynomials:
Gm Op ¼ MP
P3 ¼ 12 5cos3 f 3cos f
½2
This definition of gravitational potential, involving a negative sign, is the one normally adopted in physics, but there is an alternative convention often used in geodesy, which treats the potential in the above equation as positive. The advantage of the geodetic convention is that an increase in potential on the surface of the earth will result in an increase of the level of the free water surface. Potential has units of L2T2. The advantage of working with gravitational potential is that it is a scalar property, which allows simpler mathematical manipulation; in particular, the vector, gravitational force on a particle of unit mass is given by grad (Op). Applying the cosine law to DOPM in Figure 1 MP2 ¼ a2 þ r2 2ar cos f
½3
P1 ¼ cos f
½7
P2 ¼ 12 3cos2 f 1
½8
The tidal forces represented by the terms in this potential are calculated from their spatial gradients grad (Pn). The first term in the equation is constant (except for variations in r) and so produces no force. The second term produces a uniform force parallel to OM because differentiating with respect to (a cos f) yields a gradient of potential which provides the force necessary to produce the acceleration in the earth’s orbit towards the center of mass of the Moon–Earth system. The third term is the major tide-producing term. For most purposes the fourth term may be neglected, as may all higher terms. The effective tide-generating potential is therefore written as: OP ¼ 12 Gm
Hence we have:
½10
qOp ¼ 2gDl cos2 f 13 qa
½11
horizontally in the direction of increasing f.
1=2 Gm a a2 1 2 cosf þ 2 Op ¼ r r r
½5 qOp ¼ gDl sin2f adf
½12
3 ml a 3 Dl ¼ 2 me Rl
½13
which may be expanded: For the Moon:
Gm a a2 OP ¼ 1 þ P1 ðcosfÞ þ 2 P2 ðcosfÞ r r r 2 a þ 2 P3 ðcosfÞ þ y r
½6
P
O
a2 3cos2 f 1 3 r
½4 vertically upwards :
M
½9
The force on the unit mass at P may be resolved into two components as functions of f:
2 1=2
a a ‘MP ¼ r 1 2 cosf þ 2 r r
a
r Moon
Earth
Figure 1 The general position of the point P on the Earth’s surface, defined by the angle f.
m1 is the lunar mass and me is the Earth mass. R1, the lunar distance, replaces r. The resulting forces are shown in Figure 2. To generalize in three dimensions, the lunar angle f must be expressed in suitable astronomical variables. These are chosen to be declination of the Moon north or south of the equator, the north–south latitude of P, fp, and the hour angle of the moon, which is the difference in longitude between the meridian of P and the meridian of the sublunar point V on the Earth’s surface.
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34
TIDES
mass, distance, and declination substituted for lunar parameters. The ratio of the two tidal amplitudes is: ms R l 3 m1 Rs
(A)
(B)
Figure 2 The tide-producing forces at the Earth’s surface, due to the Moon. (A) The vertical forces, showing an outward pull at the equator and a smaller downward pull at the poles. (B) The horizontal forces, which are directed away from the poles towards the equator, with a maximum value at 451 latitude.
The Equilibrium Tide An equilibrium tide can be computed from eqn [10] by replacing cos2f by the full astronomical expression in terms of d1, fp and the hour angle C1. The equilibrium tide is defined as the elevation of the sea surface that would be in equilibrium with the tidal forces if the Earth were covered with water and the response is instantaneous. It serves as an important reference system for tidal analysis. It has three coefficients which characterize the three main species of tides: (1) the long period species; (2) the diurnal species at a frequency of one cycle per day (cos C); and (3) the semidiurnal species at two cycles per day(cos 2C). The equilibrium tide due to the sun is expressed in a form analogous to the lunar tide, but with solar
For the semidiurnal lunar tide at the equator when the lunar declination is zero, the equilibrium tidal amplitude is 0.27 m. For the sun it is 0.13 m. The solar amplitudes are smaller by a factor of 0.46 thanthose of the lunar tide, but the essential details are the same. The maximum diurnal tidal ranges occur when the lunar declination is greatest. The ranges become very small when the declination is zero. This is because the effect of declination is to produce an asymmetry between the two high- and the two low-water levels observed as a point P rotates on the earth within the two tidal bulges. The fortnightly spring/neap modulation of semidiurnal tidal amplitudes is due to the various combinations of the separate lunar and solar semidiurnal tides. At times of spring tides the lunar and solar forces combine together, but at neap tides the lunar and solar forces are out of phase and tend to cancel. In practice, the observed spring tides lag the maximum of the tidal forces, usually by one or two days due to the inertia of the oceans and energy losses. This delay is traditionally called the age of the tide. The observed ocean tides are normally much larger than the equilibrium tide because of the dynamic response of the ocean to the tidal forces. But the observed tides do have their energy at the samefrequencies (or periods) as the equilibrium tide. This forms the basis of tidal analysis.
Tidal Analysis Tidal analysis of data collected by observations of sea levels and currents has two purposes. First, a goodanalysis provides the basis for predicting tides at future times, a valuable aid for shipping and other operations. Secondly, the results of analyses can be mapped and interpreted scientifically in terms of the hydrodynamics of the seas and their responses to tidal forcing. In tidal analysis the aim is to produce significant time-stable tidal parameters which describe the tidal regime at the place of observation. These parameters are often termed tidal constants on the assumption that the responses of the oceans and seas to tidal forces do not change with time. A good tidal analysis seeks to represent the data by afew significant stable numbers which mean something physically. In general, the longer the period of data included in the analysis, the greater the number of
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TIDES
constants which can be independently determined. If possible, an analysis should give some idea of the confidence which should be attributed to each tidal constant determined. The close relationship between the movement of the moon and sun, and the observed tides, make the lunar and solar coordinates a natural starting point for any analysis scheme. Three basic methods of tidal analysis have been developed. The first, which is now generally of only historical interest, the non-harmonic method, relates high and low water times and heights directly to the phases of the moon and other astronomical parameters. The second method which is generally used for predictions and for scientific work, harmonic analysis, treats the observed tides as the sum of a finite number of harmonic constituents with angular speeds determined from the astronomical arguments. The third method developsthe concept, widely used in electronic engineering, of a frequency-dependent response of a system to a driving mechanism. For tides, the driving mechanism is the equilibrium potential. The latter twomethods are special applications of the general formalisms of time series analysis. Analyses of changing sea levels (scalar quantities) are obviously easier than those of currents (vectors), which can be analysed by resolving into two components. Harmonic Analysis
The basis of harmonic analysis is the assumption that the tidal variations can be represented by a finite number N of harmonic terms of the form: Hn cosðsn t gn Þ where Hn is the amplitude, gn is the phase lag on the equilibrium tide at Greenwich and sn is the angular speed. The angular speeds sn are determined by an expansion of the equilibrium tide into harmonic terms. The speeds of these terms are found to have the general form: on ¼ ia o1 þ ib o2 þ ic o3 þ ðo4 ; o5 ; o6 termsÞ
½14
where the values of o1 to o6 are the angular speeds related to astronomical parameters and the coefficients, ia to ic are small integers (normally 0, 1 or 2) (Table 1). The phase lags gn are defined relative to the phase of the corresponding term in the harmonic expansion of the equilibrium tide. Full harmonic analysis of the equilibrium tide shows the grouping of tidal terms into species (1;
35
Table 1 The basic astronomical periods which modulate the tidal forces
Mean solar day (msd) Mean lunar day Sidereal month Tropical year Moon’s perigee Regression of Moon’s nodes Perihelion
Period
Symbol
1.0000 msd 1.0351 msd 27.3217 msd 365.24222 msd 8.85 years 18.61 years 20 942 years
o0 o1 o2 o3 o4 o5 o6
diurnal, semidiurnal y), groups (o2; monthly) and constituents (o3; annual). Response Analysis
The basic ideas involved in response analysis are common to many activities. A system, sometimes called a ‘black box’, is subjected to an external stimulus or input. The output from a system depends on the input and the system response to that input. The response of the system may be evaluated by comparing the input and output functions at various forcing frequencies. These ideas are common in many different contexts, including mechanical engineering, financial modeling and electronics. In tidal analysis the input is the equilibrium tidal potential. The tidal variations measured at a particular site may be considered as the output from the system. The system is the ocean, and we seek to describe its response to gravitational forces. This ‘response’ treatment has the conceptual advantage of clearly separating the astronomy (the input) from the oceanography (the black box). The basic response analysis assumes a linear system, but weak nonlinear interactions can be allowed for with extra terms.
Tidal Dynamics The equilibrium tide consists of two symmetrical tidal bulges directly opposite the moon or sun. Semidiurnal tidal ranges would reach their maximum value of about 0.5 m at equatorial latitudes. The individual high water bulges would track around the earth, moving from east to west in steady progression. These theoretical characteristics are clearly not those of the observed tides. The observed tides in the main oceans have much larger mean ranges, of about 1 m, but there are considerable variations. Times of tidal high water vary in a geographical pattern which bears norelationship to the simple ideas of a double bulge. The tides spread from the oceans onto the surrounding
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36
TIDES
continental shelves, where even larger ranges areobserved. In some shelf seas the spring tidal range may exceed 10 m: the Bay of Fundy, the Bristol Channel and the Argentine Shelf are well-known examples. Laplace (1749–1827) advanced the basic mathematical solutions for tidal waves on a rotating earth. More generally, the reasons for these complicated ocean responses to tidal forcing may be summarized as follows. 1. Movements of water on the surface of the earth must obey the physical laws represented by the hydrodynamic equations of continuity and momentum balance; this means that they must propagate as long waves. Any propagation of a wave, east to west around the earth, is impeded by the north–south continental boundaries. 2. Long waves travel at a speed that is related to the water depth; oceans are too shallow for this to match the tracking of the moon. 3. The various ocean basins have their individual natural modes of oscillation which influence their response to the tide-generating forces. There are many resonant frequencies. However, the whole global ocean system seems to be near to resonance at semidiurnal tidal frequencies, as the observed semidiurnal tides are generally much bigger than the diurnal tides. 4. Water movements are affected by the rotation of the earth. The tendency for water movement to maintain a uniform direction in absolute spacemeans that it performs a curved path in the rotating frame of reference within which our observations are made. 5. The solid earth responds elastically to the imposed gravitational tidal forces, and to the ocean tidal loading. The redistribution of water mass during the tidal cycle affects the gravitational field. Long-Wave Characteristic, No Rotation
Provided that wave amplitudes are small compared with the depth, and that the depth is small compared with the wavelength, then the speed for the wave propagation is: c ¼ ðgDÞ1=2
Standing Waves and Resonance
Two progressive waves traveling in opposite directions result in a wave motion, called a standing wave. This can happen where a wave is perfectly reflected at a barrier. Systems which are forced by oscillations close to their natural period have large amplitude responses. The responses of oceans and many seas are close to semidiurnal resonance. In nature, the forced resonant oscillations cannot grow indefinitely because friction limits the response. Because of energy losses, tidal waves are not perfectly reflected at the head of a basin, which means that the reflected wave is smaller than the ingoing wave. It is easy to show that this is equivalent to a progressive wave superimposed on a standing wave with the progressive wave carrying energy to the head of the basin. Standing waves cannot transmit energy because they consist of two progressive waves of equal amplitude traveling in opposite directions. Long Waves on a Rotating Earth
A long progressive wave traveling in a channel on a rotating Earth behaves differently from a wave traveling along a nonrotating channel. The geostrophic forces that affect the motion in a rotating system, cause a deflection of the currents towards the right of the direction of motion in the Northern Hemisphere. The build-up of water on the right of the channel gives rise to a pressure gradient across the channel, which in turn develops until at equilibrium it balances the geostrophic force. The resulting Kelvin wave is described mathematically:
½15
where g is gravitational acceleration, and D is the water depth. The currents u are related to the instantaneous level z by: u ¼ zðg=DÞ1=2
on the value of g and the water depth; any disturbance which consists of a number of separate harmonic constituents will not change its shape as it propagates – this is nondispersive propagation. Waves at tidal periods are long waves, even in the deep ocean, and so their propagation is nondispersive. In the real ocean, tides cannot propagate endlessly as progressive waves. They undergo reflection at sudden changes of depth and at the coastal boundaries.
½16
Long waves have the special property that the speed c is independent of the frequency, and depends only
zðyÞ ¼ Ho exp
g 1=2 fy zðyÞ ½17 ; u ð yÞ ¼ c D
where z(y) is the amplitude at a distance y from the right-hand boundary (in the Northern Hemisphere) and Ho is the amplitude of the wave at the boundary. The effect of the rotation appears only in the factor exp ( fy/c), which gives a decay of wave amplitude away from the boundary with a length scale of
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TIDES
c/f ¼ [(gD)1/2/f], which depends on the latitude and the water depth. This scale is called the Rossby radius of deformation. At a distance y ¼ c/f from the boundary the amplitude has fallen to 0.37 Ho. At 451N in water of 4000 m depth the Rossby radius is 1900 km, but in water 50 m deep this is reduced to 215 km. Kelvin waves are not the only solution to the hydrodynamic equations on a rotating Earth: a more general form, called Poincare´ waves, gives amplitudes which vary sinusoidally rather than exponentially in the direction transverse to the direction of wave propagation. The case of a standing-wave oscillation on a rotating Earth is of special interest in tidal studies. Away from the reflecting boundary, tidal waves can be represented by two Kelvin waves traveling in opposite directions. The wave rotates about a nodal point, which is called an amphidrome (Figure 3). The cotidal lines all radiate outwards from the amphidrome and the co-amplitude lines form a set of nearly concentric circles around the center at the amphidrome, at which the amplitude is zero. The amplitude is greatest around the boundaries of the basin.
Ocean Tides Dynamically there are two essentially different types of tidal regime; in the wide and relatively deep ocean
37
basins the observed tides are generated directly by the external gravitational forces; in the shelf seas the tides are driven by co-oscillation with the oceanic tides. The ocean response to the gravitational forcing may be described in terms of a forced linear oscillator, with weak energy dissipation. A global chart of the principal lunar semidiurnal tidal constituent M2 shows a complicated pattern of amphidromic systems. As a general rule these conform to the expected behavior for Kelvin wave propagation, with anticlockwise rotation in the Northern Hemisphere, and clockwise rotation in the Southern Hemisphere. For example, in the Atlantic Ocean the mostfully developed semidiurnal amphidrome is located near 501N, 391W. The tidal waves appear to travel around the position in a form which approximates to a Kelvin wave, from Portugal along the edge of the north-west European continental shelf towards Iceland, and thence west and south past Greenland to Newfoundland. There is a considerable leakage of energy to the surrounding continental shelves and to the Arctic Ocean, so the wave reflected in a southerly direction, is weaker than the wave traveling northwards along the European coast. The patterns of tidal waves on the continental shelf are scaled down as the wave speeds are reduced. In the very shallow water depths (typically less than 20 m) there are strong tidal currents and substantial
Y λ/
2
4
3
2
1
12
11
λ/
9
10
4 8
Open boundary
7
6 0.4
0.4 0.8
1.2
1.2 8
9
5
0.8
10
11
0
1
2
Reflecting (closed) boundary
Reflected Kelvin wave
1.6 3
4
X
Ingoing Kelvin wave Figure 3 Cotidal and co-amplitude lines for a Kelvin wave reflected without energy loss in a rectangular channel. The incoming wave travels fromleft to right. Continuous lines are cotidal lines at intervals of 1/12 of a full cycle. Broken lines are lines of equal amplitude. Progression of the wave crests in the Northern Hemisphere is anticlockwise for both the amphidromic systems shown. In practice the reflected wave is weaker and so the amphidromes are moved towards the upper wall in the diagram.
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38
TIDES
energy losses due to bottom friction. Tidal waves are strongly influenced by linear Kelvin wave dynamics and by basin resonances. Energy is propagated to the shallow regions where it is dissipated.
Energy Fluxes and Budgets The energy lost through tidal friction gradually slows down the rate of rotation of the earth, increasing the length of the day by one second in 41 000 years. Angular momentum of the earth–moon system is conserved by the moon moving away from the earth at 3.7 mm per year. The total rate of tidal energy dissipation due to the M2 tide can be calculated rather exactly from the astronomic observations at 2.50 7 0.05 TW, of which 0.1 TW is dissipated in the solid Earth. The total lunar dissipation is 3.0 TW, and the total due to both sun and moon is 4.0 TW. For comparison the geothermal heat loss is 30 TW, and the 1995 total installed global electric capacity was 2.9 TW. Solar radiation input isfive orders of magnitude greater. Most of the 2.4 TW of M2 energy lost in the ocean is due to the work against bottom friction which opposes tidal currents. Because the friction increases approximately as the square of current speed, and the energy loses as the cube, tidal energy loses are concentrated in a few shelf areas of strong tidal currents. Notable among these are the north-west European Shelf, the Patagonian Shelf, the Yellow Sea, the Timor and Arafura Seas, Hudson Bay, Baffin Bay, and the Amazon Shelf. It now appears that up to 25% (1 TW) of the tidal energy may be dissipated by internal tidal waves in the deep ocean, where the dissipation processes contribute to vertical mixing and the breakdown of stratification. Again, energy losses may be concentrated in a few areas, for example where the rough topography of midocean ridges and islandarcs create favorable conditions. One of the main areas of tidal research is increasingly concentrated on gaining a better understanding of the many nonlinear ocean processes that are driven by this cascading tidal energy. Some examples, outlined below, are considered in more detail elsewhere in this Encyclopedia.
•
•
Generation of tidal fronts in shelf seas, where the buoyancy forces due to tidal mixing compete with the buoyancy fluxes due to surface heating; the ratio of the water depth divided by the cube of the tidal currentis a good indicator of the balance between the two factors, and fronts form along lines where this ratio reaches a critical value. River discharges to shallow seas near the mouth of rivers. The local input of freshwater
• •
•
•
•
•
buoyancy may be comparable to the buoyancy input fromsummer surface warming. These regions are called ROFIs (regions of freshwater influence). Spring–neap variations in the energy of tidal mixing strongly influence the circulation in these regions. The mixing and dispersion of pollutants often driven by the turbulence generated by tides. Maximum turbulent energy occurs some hours after the time of maximum tidal currents. Sediment processes of erosion and deposition are often controlled by varying tidal currents, particularly over a spring–neap cycle. The phase delay in suspended sediment concentration after maximum currents may be related to the phase lag in the turbulent energy, which has importantconsequences for sediment deposition and distribution. Residual circulation is partly driven by nonlinear responses to tidal currents in shallow water. Tidal flows also induce residual circulation around sandbanks because of the depth variations. In the Northern Hemisphere this circulation is observed to be in a clockwise sense. Near headlands and islands which impede tidal currents, residual eddies can cause marked asymmetry between the time and strength of the tidal ebb and flow currents. Tidal currents influence biological breeding patterns, migration, and recruitment. Some types of fish have adapted to changing tidal currents to assist in their migration: they lie dormant on the seabed when the currents are not favorable. Tidal mixing in shallow seas promotes productivity by returning nutrients to surface waters where light is available. Tidal fronts are known to be areas of high productivity. The most obvious example of tidal influence on biological processes is the zonation of species found at different levels along rocky shorelines. Evolution of sedimentary shores due to the dynamic equilibrium between waves, tides and other processes along sedimentary coasts which resultsin a wide range of features such as lagoons, sandbars, channels, and islands. These are very complicated processes which are still difficult to understandand model. Tidal amphidrome movements. The tidal amphidromes as shown in Figure 4 only fall along the center line of the channel if the incoming tidal Kelvin wave is perfectly reflected. In reality, the reflected wave is weaker, and the amphidromes are displaced towards the side of the sea along which the outgoing tidal wave travels. Proportionately more energy is removed at spring tides than at neap tides, so the amphidromes can
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_ 270°
_ 240°
_ 210°
_ 180°
_ 150°
_ 120°
_ 90°
_ 60°
_ 30°
_ 0°
_ 300° _ 330° LEGOS _ Toulouse
_ 270°
_ 240°
_ 210°
_ 180°
_ 150°
_ 120°
_ 90°
_ 60°
_ 30°
_ 0°
10
20
30
60° 0.0
5
40
50
60
70
80
90
100
_ 90
°
_ 90°
_ 60
°
_ 60°
_ 30°
_ 30°
_0
_ 0°
°
30°
30°
60°
90°
_ 300°
_ 330°
39
90°
TIDES
150
Figure 4 Map of the principal lunar semidiurnal tide produced by computer. Ocean tides observed by satellite and in situ now agree very closely with computer modeled tides. The dark areas show regions of high tida lamplitude. Note the convergence of cophase lines at amphidromes. In the Northern Hemisphere the tides normally progress in an anticlockwise sense around the amphidrome; in the Southern Hemisphere the progression is usually clockwise.
move by several tens of kilometers during thespring–neap cycle. Nonlinear processes on the basic M2 tide generate a series of higher harmonics, M4, M6y, with corresponding terms such as MS4 for spring–neap interactions. A better understanding of the significance of the amplitudes and phases of these terms in the analyses of shallow-water tides and tidal phenomena will be an important tool in advancing our overall knowledge of the influence of tides on a wide range of ocean processes.
See also Beaches, Physical Processes Affecting. Coastal Trapped Waves. Dispersion in Shallow Seas. Estuarine Circulation. Fish Migration, Horizontal. Geomorphology. Internal Tidal Mixing. Internal Waves. Intertidal Fishes. Lagoons. River Inputs. Salt Marshes and Mud Flats. Satellite Altimetry. Sea Level Change. Shelf Sea and Shelf Slope Fronts. Tidal Energy. Upper Ocean Vertical Structure. Waves on Beaches.
Further Reading Cartwright DE (1999) Tides – a Scientific History. Cambridge: Cambridge University Press. Garrett C and Maas LRM (1993) Tides and their effects. Oceanus 36(1): 27--37. Parker BB (ed.) (1991) Tidal Hydrodynamics. New York: John Wiley. Prandle D (1997) Tidal characteristics of suspended sediment concentrations. Journal of Hydraulic Engineering 123: 341--350. Pugh DT (1987) Tides, Surges and Mean Sea Level. Chichester: John Wiley. Ray RD and Woodworth PL (eds.) (1997) Special issue on tidal science in honour of David E Cartwright. Progress in Oceanography 40. Simpson JH (1998) Tidal processes in shelf seas. In: Brink KH and Robinson AR (eds.) The Sea, Vol. 10. New York: John Wiley. Wilhelm H, Zurn W, and Wenzel HG (eds.) (1997) TidalPhenomena: Lecture Notes in Earth Sciences 66. Berlin: Springer-Verlag.
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TOMOGRAPHY P. F. Worcester, University of California at San Diego, La Jolla, CA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2969–2986, & 2001, Elsevier Ltd.
Introduction Ocean acoustic tomography is a method for acoustic remote sensing of the ocean interior that takes advantage of the facts that the propagation of sound through the ocean is sensitive to quantities of oceanographic interest, such as temperature and water velocity, and that the ocean is nearly transparent to low-frequency sound so that signals can be transmitted over long distances. The procedure is (i) to transmit acoustic signals through the ocean, (ii) to make precise measurements of the properties of the received signals, e.g., travel times, and (iii) to use inverse methods to infer the state of the ocean traversed by the sound field from the measured properties. The characteristics of the ocean between the sources and receivers are determined, rather than the characteristics of the ocean at the instruments as is the case for conventional thermometers and current meters. Ocean acoustic tomography has a number of attractive attributes. It makes possible the rapid and repeated measurement of ocean properties over large areas, taking advantage of the speed with which sound travels in water (B1500 m s1). It permits the monitoring of regions in which it is difficult to install instruments to make direct measurements, such as the Gulf Stream or the Strait of Gibraltar, using sources and receivers on the periphery of the region. Acoustic measurements are inherently spatially integrating, suppressing the small-scale variability that can contaminate point measurements and providing direct measurements of horizontal and vertical averages over large ranges. Finally, the amount of data grows as the product (S R) of the number of acoustic sources S and receivers R, rather than linearly as the sum of the number of instruments (S þ R) as is the case for point measurements. Ocean acoustic tomography was originally introduced by Munk and Wunsch in 1979 to address the difficult problem of observing the evolving ocean mesoscale. Mesoscale variability has spatial scales of order 100 km and timescales of order one month. The short timescales mean that ships move too slowly for ship-based measurements to be practical.
40
The short spatial scales mean that moored sensors must be too closely spaced to be practical. Munk and Wunsch proposed that the travel times of acoustic signals propagating between a relatively small number of sources and receivers could be used to map the evolving temperature field in the intervening ocean. Their work led directly to the first 3D ocean acoustic tomography experiment, conducted in 1981. In spite of the marginal acoustic sources that were available at the time, the experiment showed that it was possible to use acoustic methods to map the evolving mesoscale field in a 300 km by 300 km region (Figure 1). It was quickly realized, however, that the integral measures provided by acoustic methods are powerful tools for addressing certain types of problems, including the measurement of integral quantities such as heat content, mass transport, and circulation. Acoustic measurements of the integrated water velocity around a closed contour, for example, provide the circulation, which is directly related to the arealaverage vorticity in the interior by Stokes’ theorem. Vorticity is difficult to measure in other ways. The suppression of small-scale variability in the spatially integrating acoustic measurements also makes them well suited to measure large-scale phenomena, such as the barotropic and baroclinic tides. Finally, the integral measurements provided by the acoustic data can be used to test the skill of dynamic models and to provide strong model constraints. Acoustic scattering due to small-scale oceanic variability (e.g., internal waves) causes the properties of the received acoustic signals to fluctuate. Although these fluctuations limit the precision with which the signal characteristics can be measured and with which oceanic parameters such as temperature and water velocity can be inferred, it was soon realized that measurements of the statistics of the fluctuations can be used to infer the statistical properties of the small-scale oceanic variability, such as internal-wave energy level, as a function of space and time. Summarizing, tomographic methods can be used to map the evolving ocean, to provide integral measures of its properties, and to characterize the statistical behavior of small-scale oceanic variability.
Ocean Acoustics: The Forward Problem The ‘forward’ problem in ocean acoustics is to compute the properties of the received signal given the sound-speed C(x, y, z) and current v(x, y, z) fields
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41
TOMOGRAPHY
R
300 km
S
R
S
R
300 km
88
-6
-10 -8 -4
-1
-4
0 -2
0
-5
103 -1
-1
-3
-3
-7
-1
-1 -3
-5
-5
-5
-1
112
-1
-3
-3
-2
109
-6
100
-6
-3
-2
-2
-2
-4
-5
-3
0
-6
-8
-12
-8
97
-7
106
-2
-3
-5
-8
-4
-5
94
91
-4
-7
-5
-6
-8 -10
-9
-4
-4
85 -6
-5
-5
-2
-4
82
-7
R
S
79
76 -2
-2
R
S
66 _ 85
CTD I
115
CTD II 120 _ 139
118
1
-2 -2
-6
-4
-6
-4
-2
-4
-6
-2
-6
-4
-2 -3
-4
-4
-7
1
-5
-5
-4
-4
-1
-3
Figure 1 The 1981 tomography experiment. The first panel shows the geometry, with four source (S) and five receiver (R) moorings on the periphery of a 300 km by 300 km region in the north-west Atlantic Ocean. Subsequent panels show the sound-speed perturbations at 700 m depth derived from the acoustic data at 3-day intervals, with regions of high uncertainty shaded. The initial and final panels are derived from two ship-borne conductivity-temperature-depth (CTD) surveys, each of which required about 20 days to complete. The label on each panel is the year day in 1981. The contour interval is 1 m s1 (0.21C). Adapted from Cornuelle B, Wunsch C, Behringer D, et al. (1985) Tomographic maps of the ocean mesoscale. Part I: Pure acoustics. Journal of Physical Oceanography 15: 133–152.
between the source and receiver. Acoustic remote sensing of the ocean interior requires first a full understanding of the forward problem, i.e., of methods for finding solutions to the wave equation. A variety of approaches are available to do this, including geometric optics, normal mode, and parabolic equation methods. The appropriate method depends in part on the character of the sound-speed and current fields (e.g., range-independent or rangedependent) and in part on the choice of the observables in the received signal to use in the inverse problem. The approach most commonly used in ocean acoustic tomography has been to transmit broadband signals designed to measure the impulse response of the ocean channel and to interpret the peaks in the impulse response in terms of geometric rays. Ray travel times are robust observables in the presence of internal-wave-induced scattering because of Fermat’s principle, which states that ray travel times are not sensitive to first-order changes in the ray path. Other observables are possible, however. The peaks in the impulse response are in some cases more appropriately interpreted in terms of normalmode arrivals, for example, and the observables are then modal group delays. Another possibility is to perform full-field inversions that use the time series
of intensity and phase for the entire received signal as observables. Unfortunately, neither normal modes nor the intensities and phases of the received signal are robust in the presence of internal-wave-induced scattering, and so tend to be useful only at short ranges and/or low frequencies where internal-waveinduced scattering is less important. A number of other possible observables have been proposed as well. In what follows the use of ray travel times as observables will be emphasized, in part because they have been the observable most commonly used to date and in part because they are robust to internalwave-induced scattering. Ocean Sound Channel
The speed with which sound travels in the ocean increases with increasing temperature, salinity, and pressure. As a result, over much of the temperate world ocean there is a subsurface minimum in sound speed at depths of roughly 1000 m. Sound speed increases toward the surface above the minimum because of increasing temperature and toward the bottom below the minimum because of increasing pressure. Salinity does not play a major role because its effect on sound speed is normally less than that of either temperature or pressure. The depth of the
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42
TOMOGRAPHY
sound-speed minimum is called the sound channel axis. The axis shoals towards high latitudes where the surface waters are colder, actually reaching the surface during winter at sufficiently high latitudes. The sound speed gradients above and below the sound channel axis refract acoustic rays toward the axis in accord with Snell’s law. Near-horizontal rays propagating outward from an omnidirectional source on the axis will therefore tend to be trapped, cycling first above and then below the axis (Figure 2). Such rays are referred to as refracted–refracted (RR) rays. Steeper rays will interact with the surface and/or seafloor. Rays can reflect from the sea surface with relatively low loss. Rays that are refracted at depth and reflected from the sea surface are referred to as refracted-surface-reflected (RSR) rays. Both RR and RSR rays can propagate to long distances and are
commonly used in ocean acoustic tomography. Rays that interact with the seafloor tend to be strongly scattered, however. Rays with multiple bottom interactions therefore tend not to propagate to long ranges. A receiver at a specified range from an omnidirectional acoustic source will detect a discrete set of ray arrivals (Figure 2), corresponding to the rays that are at the depth of the receiver at the appropriate range. These rays are called eigenrays and are designated 7p, where 7 indicates an upward/downward launch direction and p is the total number of ray turning points (including reflections). The ray geometry controls the vertical sampling properties of tomographic measurements. One can obtain significant vertical resolution even for the case of source and receiver both on the sound channel axis, because the eigenrays in general have a range of turning depths.
_1
0
C (km s ) 1.50 1.55
Depth (km)
1 2
W
+20
N
3 +11
4 5
0
(A)
100
Range (km)
200
300 +20
+11
Measured
203
(B)
_11 +10 _ 10 +12 _12 +13 _13 +11 +14 _14 +15 _15 +16 _16 +17 _17 +18 _18 +19 _19 +20
+11
+10 _ 10
_9
+9
_7 _7 +8 _8 +8 _8 +9
Predicted
τ (s)
204
Figure 2 (A) Sound-speed profile in the western North Atlantic and the corresponding ray paths for source and receiver near the depth of the sound channel axis and about 300 km apart. The geometry is that of a reciprocal acoustic transmission experiment conducted in 1983 with transceivers designated W(est) and N(orth). (B) Measured and predicted acoustic amplitudes as a function of time for the 1983 experiment. The arrivals are labeled with their ray identifier. The earliest arrivals are from steep ray paths that cycle through nearly the entire water column. The latest arrivals are from flat ray paths that remain near the sound-channel axis. The differences between the measured and predicted arrival times are the data used in tomographic inversions. Adapted from Howe BM, Worcester PF and Spindel RC (1987) Ocean acoustic tomography: mesoscale velocity. Journal of Geophysical Research 92: 3785–3805.
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TOMOGRAPHY
43
DC=C and jvj=C gives
Ray Travel Time
To first order in jvj=C, the travel time ti of ray i is ti ¼
ð
ds CðrÞ þ vðrÞ r0
½1
Gi
where Gi is the ray path for ray i along which distance s is measured and r0 is the tangent to the ray at position r. The sign of v . r0 depends on the direction of propagation, and the travel times and ray paths in opposite directions differ because of the effects of currents. (Sound travels faster with a current than against a current.) The eigenrays Gi are obtained using a numerical eigenray code.
þ Dtþ i ¼ ti t i ð Þ ¼ ð ½DCðrÞ þ vðrÞ r0 ðÞ ds C2 ðr;Þ
½7
GiðÞ Dt i ¼ ti t i ð Þ ¼ ð ½DCðrÞ vðrÞ r0 ðÞ ds C2 ðr;Þ
½8
GiðÞ
where GiðÞ ; r0 ðÞ are the ray path and tangent vector for the reference state. The superscript plus (minus) refers to propagation in the þ ðÞ direction. The reference travel time is ð ds ½9 ti ðÞ ¼ Cðr;Þ GiðÞ
The Inverse Problem The ‘inverse’ problem is to compute the sound-speed CðrÞ and current vðrÞ fields given the measured travel times. In fact, a great deal is normally known about CðrÞ in the ocean from climatological or other data. The interesting problem is therefore to compute the perturbations from an assumed reference state, using the measured perturbations from the travel times computed for the reference state.
The sum of the travel time perturbations ð 1 ds Dsi ¼ Dtþ DCðrÞ þ Dt ¼ i i 2 C2 ðr;Þ
½10
GiðÞ
depends only on the sound-speed perturbation DCðrÞ. The difference ð 1 ds Ddi ¼ Dtþ vðrÞ r0 ðÞ ½11 þ Dt ¼ i i 2 C2 ðr;Þ
Data
Gi ð Þ
Travel times are in general a nonlinear function of the sound-speed and current fields, because the ray path Gi depends on CðrÞ and vðrÞ. Linearize by setting CðrÞ ¼ Cðr;Þ þ DCðrÞ
½2
vðrÞ ¼ vðr;Þ þ DvðrÞ
½3
where Cðr; Þ; vðr; Þ are the known reference states. The argument ðÞ denotes the dependence of the variables only on the reference state, independent of the measurements. Normally, jDCðrÞj5Cðr;Þ
½4
jDvðrÞj5vðr;Þ
½5
In general, however, jDvðrÞj > jvðr;Þj
½6
because the fluctuations in current at a fixed location in the ocean are typically large compared to the timemean current. Setting vðr; Þ 0; DvðrÞ vðrÞ, forming perturbation travel times, and linearizing to first order in
depends only on the water velocity v . r0 along the ray path. Forming sum and difference travel times separates the effects of DC and v. This separation is crucial for measuring v, because jvj is usually much smaller than DC. It is not crucial for measuring DC, however, and one-way, rather than sum, travel time perturbations are often used for this purpose. The data used in the inverse problem can therefore either be the one-way travel time perturbations, e.g., Dtþ i , or the sum and difference travel time perturbations, Dsi and Ddi . The use of one-way travel time measurements to estimate DC is sometimes given the special name of acoustic thermometry, reflecting the fact that sound-speed perturbations depend mostly on temperature. Reference States and Perturbation Models
The perturbation field DC and therefore the data depend on the choice of reference state, Cðr; Þ. Although there is some freedom in the choice, reference states that include the range and time dependence of the sound-speed field available from ocean climatologies, for example, usually yield reference ray paths that are acceptably close to the true ones. Accurate prior estimates of the ray paths help ensure that the sampling properties of the rays are included properly
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44
TOMOGRAPHY
in the inverse procedure and that the nonlinearities associated with ray-path mismatches are minimized. The continuous perturbation fields DC and v are parametrized with a finite number of discrete parameters using a model. Because the tomographic inverse problem is always underdetermined, it is important to use perturbation models that are oceanographically meaningful and that provide an efficient representation of ocean variability. Separable models using a linear combination of basis functions describing the horizontal (x, y) and vertical (z) structures, DCðx; y; zÞ ¼
X
aklm Xk ðxÞYl ðyÞFm ðzÞ
½12
k;l;m
have frequently been used for simplicity, although more general models are of course possible. The coefficients aklm are the model parameters to be determined, and the Xk, Yl, Fm are the basis functions. Inverse Methods: Vertical Slice
The inverse problem is most simply described for the case of a single acoustic source–receiver pair. Neglecting currents and assuming that the sound-speed perturbation is a function of depth only, Dti ¼
ð
DCðzÞ ds þ dti ; C2 ðr;Þ
i ¼ 1; y; M
½13
Gi ðÞ
where there are M rays. (Note that although the sound-speed perturbation has been assumed to be independent of range, the reference state can be a more general function of position.) The quantity dti has been introduced to represent the noise contribution that is inevitably present. The noise term arises not only from observational errors but also from modeling errors associated with the representation of DC using a finite number of parameters and from nonlinearity errors associated with the use of the ray paths for the reference state rather than the true ray paths. (In the absence of currents the problem can be restated somewhat more simply in terms of sound slowness, S ¼ C1, if desired.) Substituting DCðzÞ ¼
X
am Fm ðzÞ
½14
m
gives Dti ¼
X
am
m
ð
Fm ðzÞ ds þ dti ; C2 ðr;Þ
¼
X m
Eim am þ dti ;
i ¼ 1; y; M
y ¼ Exþn
½17
where y ¼ ½Dti ; x ¼½am ;
E ¼fEim g; n ¼ ½dti
½18
The inverse problem consists (i) of finding a particular solution xˆ and (ii) of determining the uncertainty and resolution of the particular solution. Writing the estimate xˆ as a weighted linear sum of the observations, xˆ ¼ By ¼ BðEx þ nÞ
½19
For zero-mean noise, /nS ¼ 0, the expected value is /xˆ S ¼ BE/xS
½20
The matrix BE is called the resolution matrix. It gives the particular solution as a weighted average of the true solution x, with weights given by the row vectors of BE. If the resolution matrix is the identity matrix I, then the particular solution is the true solution. If the row vectors of BE are peaked on the diagonal with low values elsewhere, the particular solution is a smoothed version of the true solution. The solution uncertainty is described by the covariance matrix D T E ½21 P ¼ xˆ x xˆ x where superscript T denotes transpose. There is an immense literature on inverse methods, and a variety of approaches are available to construct the inverse operator B, including least squares, singular-value decomposition (SVD), and Gauss–Markov estimation. To provide an example of one approach that has been widely used, the Gauss– Markov estimate is discussed briefly here. (The Gauss–Markov estimate is sometimes known as the ‘stochastic inverse’ or as ‘objective mapping’.) The Gauss–Markov estimate is derived by minimizing the expected uncertainty between the true value xj and the estimate xˆj , i.e., by individually minimizing the diagonal elements of the uncertainty covariance matrix P. The result is the Gauss–Markov theorem, B ¼ Uxy U1 xy
½22
½15
Uxy xyT ; Uyy yyT
½23
½16
are the model–data and data–data covariance matrices, respectively. These covariances can be rewritten
where
Gi ð Þ
i ¼ 1; y; M
The elements Eim depend only on prior information. This equation can be written in compact matrix notation as
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TOMOGRAPHY
using y ¼ Ex þ n. The model–data covariance matrix becomes
Uxy ¼ xxT E
T
¼ Uxy ET
½24
where it has been assumed that the model x and noise n are uncorrelated. The data–data covariance matrix becomes D E Uyy ¼ ðEx þ nÞðEx þ nÞT ¼ EFxx ET þ Unn
½25
Finally, the inverse estimate, xˆ ¼ By, can be written in the familiar form 1 xˆ ¼ By ¼ Uxx ET EFxx ET þ Unn y
½26
The Gauss–Markov estimator requires that the perturbation model discussed above include the a priori specification of the statistics of the model parameters, i.e., of the covariance matrix Uxx . The solution uncertainty P includes contributions due to data error and due to a lack of resolution. In most realistic cases the lack of resolution dominates the solution uncertainty estimate. A key, and unfamiliar, feature of the acoustic methods is that the solution uncertainty matrix is not diagonal, i.e., the uncertainties in the model parameters are correlated in a way that depends on the ray sampling properties. These correlated uncertainties often cancel in the computation of integral properties of the solution, such as the vertically averaged heat content. Once a solution and its uncertainty have been found, the solution must be evaluated for consistency with the various assumptions made in its construction before it can be accepted. The statistics of the residuals yˆ yÞ, where yˆ ¼ E xˆ , need to be examined for consistency with the assumed noise statistics Unn , for example. Further, ray trajectories should be recomputed for the field CðrÞ ¼ Cðr;Þ þ DCðrÞ
½27
and the resulting ray travel times compared with the original data to test for consistency. Significant differences imply that the reference state is inadequate or the model is inadequately formulated. When nonlinearities are important, iterative or other methods are needed to find a solution consistent with the original data. The linear inverse methods used in ocean acoustic tomography are well known and widely used in a variety of fields. The crucial problem in the application to tomography is the construction of the model used to describe oceanic variability, including the choice of parametrization and the specification of the (co)variances of the model parameters and noise.
45
Sampling Properties of Acoustic Rays
Vertical slice: range-independent The vertical sampling properties of acoustic rays are most easily understood for the range-independent case, in which sound speed is a function of depth z only. In that case, eqn [13] can be converted to an integral over depth z˜ þðÞ ð
Dti ¼
z˜ ðÞ
þ dti ;
dz qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi DCðzÞ ˜ 2 C2 ðz; Þ 1 Cðz; Þ=C i ¼ 1; y; M
½28
˜ where y is the ray using Snell’s law, CðzÞ=cosðyÞ ¼ C, ˜ is the sound angle relative to the horizontal and C speed at the ray turning points z˜7. The function 1 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 C2 ðz; Þ 1 Cðz; Þ=C˜
½29
gives the weighting with which DCðzÞ contributes to Dti . There are (integrable) singularities in the weighting function at both the upper and lower ˜ The ray turning point depths, where ( z˜7; Þ ¼ C: travel times are therefore most sensitive to soundspeed perturbations at the ray turning points (Figure 3). The value of the weighting function is the same for depths z7 above and below the sound-channel axis at which Cðzþ ; Þ ¼ Cðz ; Þ
½30
There is a fundamental up–down ambiguity for acoustic measurements in mid-latitudes. It is in principle impossible to distinguish from the acoustic data alone whether the observed travel-time perturbations are due to sound-speed perturbations located above or below the sound channel axis. This ambiguity has to be resolved from a priori information or from other data. This up–down ambiguity is not present in polar regions when the temperature profile is close to adiabatic, so that sound speed is a minimum at the surface and increases monotonically with depth (pressure). Vertical slice: range-dependent A ray trapped in the sound channel, cycling between upper and lower turning points at regular intervals, samples the ocean periodically in space, so that its travel time is sensitive to some spatial frequencies but is unaffected by others. The key to understanding the horizontal sampling properties of acoustic travel times is to consider the wavenumber domain, rather than physical space, using a truncated Fourier series
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46
TOMOGRAPHY
The travel-time perturbations are then
0
Dti ¼
0.1
XX k
( akm
m
ð
ds C2 ðr;Þ
Gi ð Þ
) 2pi exp ðkxÞ Fm ðzÞ þ dti L
~+ Upper turning depth z (km)
0.2
0.3
0.4
0.5
0.6
0
1
2
3 ∆ (ms)
4
5
Figure 3 Travel-time perturbations computed at about 1000 km range in the North-east Pacific for a sound-speed perturbation with an amplitude of 1 m s1 at 100 m depth, linearly decreasing to zero at 90 m and 110 m. The travel-time perturbations are zero for rays with upper turning depths below 110 m, because they do not sample the perturbed region. The perturbations are sharply peaked for rays with upper turning depths between 90 m and 110 m. Rays that have upper turning depths above 90 m have nonzero perturbations because they traverse the perturbed region, but the perturbations are relatively small because the ray weighting function falls off rapidly with distance from the turning point. Adapted from Cornuelle BD, Worcester PF, Hildebrand JA, et al. (1993) Ocean acoustic tomography at 1000-km range using wavefronts measured with a large-aperture vertical array. Journal of Geophysical Research 98: 16365–16377.
in x as the model for the sound-speed perturbations,
DCðx; zÞ ¼
XX k
m
where the integrals depend only on prior information. The problem has again reduced to the form y ¼ Ex þ n, with the solution vector x containing an ordered set of the complex Fourier coefficients akm. The sensitivity of the travel-time inverse to various wavenumbers can be quantified by plotting the diagonal of the resolution matrix BE defined in eqn [20]. For the specific case of two moorings separated by 600 km, with a source and five widely-separated receivers on each mooring, the resolution matrix shows the sensitivity of tomographic measurements to the features that match the ray periodicity (i.e., have the same wavelength as the ray double loops) (Figure 4). Further, because the ray paths are somewhat distorted sinusoids in midlatitudes, the resolution matrix displays sensitivity to harmonics of the basic ray double loop length. Finally, as expected, the measurements are sensitive to the mean. There are obvious spectral gaps for wavenumbers between the mean and first harmonics of the ray paths, and again between the first and second harmonics. The harmonics extend over bands of wavenumbers because the eigenrays connecting the source and receiver have a range of double-loop lengths. Horizontal slice The sampling issues present when the goal is to map the evolving ocean using integral data are most easily understood by considering the two-dimensional horizontal slice problem. In this case sound speed is assumed to be constant in the vertical, so that ray paths travel in straight lines in the horizontal plane containing the sources and receivers. Neglecting currents, Dti ¼
2pi akm exp ðkxÞ Fm ðzÞ; L
k ¼ 0; 71; y; 7N
½32
ð
DCðx; yÞ ds þ dti ; C2 ðx; y; Þ
Gi ð Þ
i ¼ 1; y; M ½31
The Fourier series is periodic over a domain of length L and is truncated at harmonic N. The domain is normally chosen sufficiently large (say twice the size of the source–receiver range) to avoid artifacts within the area of interest that might be caused by the periodicity.
½33
where there is one ray path per source–receiver pair and there are a total of M ray paths connecting the sources and receivers. As was the case for the range-dependent vertical slice problem, the key to understanding the horizontal sampling properties of acoustic travel times is to consider the wavenumber domain, rather than physical space, using a truncated Fourier series in x and y
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TOMOGRAPHY 1.0
Resolution
0.8 0.6 0.4 0.2 0.0 0
10
20 30 40 k (cycles / 600 km)
50
60
Figure 4 Diagonal elements of the resolution matrix (‘transfer function’) for tomographic measurements over a 600-km path in a range-dependent ocean. The plot is for the lowest baroclinic mode. Adapted from Cornuelle BD and Howe BM (1987) High spatial resolution in vertical slice ocean acoustic tomography. Journal of Geophysical Research 92: 11680–11692.
as the model for the sound-speed perturbations, XX 2pi DCðx; yÞ ¼ akl exp ðkx þ lyÞ ; L k l k; l ¼ 0; 71; y; 7N
½34
where the integrals depend only on prior information. The problem has again reduced to the form y ¼ Ex þ n, with the solution vector x containing an ordered set of the complex Fourier coefficients akl. To explore the horizontal sampling properties of integral data, consider a simple scenario in which two ships start in the left and right bottom corners of a 1000-km square and steam northward in parallel, transmitting from west to east through an isotropic mesoscale field constructed to have a 1/e decay scale of 120 km (Figure 5). Inversion of the resulting travel-time data leads to an estimate that consists only of east–west contours, as all the ray paths measure only zonal averages. To interpret this result in wavenumber space, note that for
ka0
determined for the assumptions made in this simple scenario. Similarly, for north–south transmissions between two ships traveling from east to west, only the parameters ak0 are determined. Combining east– west and north–south transmissions determines both a0l and ak0, but nonetheless fails to give useful maps because the majority of the wavenumbers are still undetermined. Adding scans at 451 determines wavenumbers for which k ¼ l, giving improved, but still imperfect, maps. The conclusion is that generating accurate maps from integral data requires sampling geometries with ray paths at many different angles to provide adequate resolution in wavenumber space. This requirement must be independently satisfied in any region with dimensions comparable to the ocean correlation scale. These results are a direct consequence of the projection-slice theorem. Time-dependent Inverse Methods
The Fourier series is doubly periodic over the square domain of size L and is truncated at harmonic N. The travel-time perturbations are then ( ð XX ds akl Dti ¼ 2 ð x; y; Þ C k l GiðÞ ) 2pi exp ðkx þ lyÞ þ dti ½35 L
ðL dxDCðx; yÞ ¼ 0
47
½36
0
East–west transmissions therefore give information only on the parameters a0l, which are nearly perfectly
The discussion of inverse methods to this point has implicitly assumed that data from a single instant in time are used to estimate the state of the ocean at that instant. Observations from different times can be combined to generate improved estimates of the evolving ocean, however, using a time-dependent ocean model to connect the oceanic states at those times. One seeks to minimize the misfit between the estimate xˆ (t) and the true state x(t) over some finite time span, instead of at a single instant. The practice of combining data with time-evolving ocean circulation models, referred to as ‘assimilation’ or ‘state estimation’, simultaneously tests and constrains the models. A variety of approaches are available to solve this problem, including, for example, Kalman filtering and the use of adjoint methods. Although the problem of combining integral tomographic data with time-evolving models does not differ in any fundamental way from the problem of using other data types, tomographic data do differ from most other oceanographic data because their sampling and information content tend to be localized in spectral space rather than in physical space, as discussed above. It is therefore important to use methods that directly assimilate the tomographic measurements and preserve the integral information they contain. Approximate data assimilation methods optimized for measurements localized in physical space are generally inappropriate because they do not preserve the nonlocal tomographic information.
Selected Tomographic Results Tomographic methods have been used to study a wide range of ocean processes, at diverse locations. Measurements have been made at scales ranging
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48
TOMOGRAPHY
Figure 5 The top center panel is the ‘true ocean,’ constructed assuming a horizontally homogeneous and isotropic wavenumber spectrum, to be mapped using tomographic data. (A) W-E transmissions between two northward-traveling ships (left panel). Inversion of the travel time perturbations produces east–west contours in DC (middle) with only a faint relation to the ‘true ocean.’ Expected predicted variances in wavenumber space (right) are 0% (no skill) except for (k,l) ¼ (0,1),(0,2),y,(0,7), which account for s2 ¼ 16% of the a priori DC variance. (B) S-N transmissions between two eastward traveling ships. (C) Combined W-E and S-N transmissions, accounting for 32% of the DC variance. (D) Combined W-E, S-N, SW-NE, and SE-NW transmissions, accounting for 67% of the variance and giving some resemblance to the true ocean. Distances are shown in magameters (Mm) and wavenumbers are shown in cycles per megameter (cpMm). Adapted from Cornuelle BD, Munk WH and Worcester PF (1989) Ocean acoustic tomography from ships. Journal of Geophysical Research 94: 6232–6250.
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TOMOGRAPHY
from a few tens of kilometers (e.g., to measure the transport through the Strait of Gibraltar) to thousands of kilometers (e.g., to measure the heat content in the north-east Pacific Ocean). This review concludes by presenting results from a few selected experiments to provide some indication of the breadth of possible applications and to illustrate the strengths and weaknesses of tomographic measurements. Oceanic Convection
Oceanic convection to great depths occurs at only a few locations in the world (see Deep Convection). Nonetheless, it is believed to be the process by which the properties of the surface ocean and deep ocean are connected, with important consequences for the global thermohaline circulation and climate. The deep convective process is temporally intermittent and spatially compact, consisting of convective plumes with scales of about 1 km clustered in chimneys with scales of tens of kilometers. Observing the evolution of the deep convective process and quantifying the amount of deep water formed presents a difficult sampling problem. Tomographic measurements have been key components in programs to study deep convection in the Greenland Sea (1988–1989) and the Mediterranean
49
Sea (1991–1992), as well as in an ongoing program in the Labrador Sea (1996 to present). In all of these regions the tomographic data provide the spatial coverage and temporal resolution necessary for observing the convective process. In the Greenland Sea, for example, six acoustic transceivers were deployed from summer 1988 to summer 1989 in an array approximately 210 km in diameter (Figure 6), as part of the intensive field phase of the International Greenland Sea Project. The acoustic data were combined with moored thermistor data and hydrographic data to estimate the evolution of the three-dimensional temperature field T(x, y, z) in the Greenland Sea during winter. (During the convective period, the hydrographic data were found to be contaminated by small-scale variability and were not useful for determining the chimney and gyre-scale structure.) A convective chimney reaching depths of about 1500 m was observed to the south west of the gyre center during March 1989. The chimney had a spatial scale of about 50 km and a timescale of about 10 days (Figure 7). The location of the chimney seemed to be sensitively linked to the distribution of the relatively warm, salty Arctic Intermediate Water found at intermediate depths. Potential temperature profiles
Figure 6 (A) Geometry of the tomographic transceiver array deployed in the Greenland Sea during 1988–1989. Mooring 2 failed about one month after deployment. A deep convective chimney was observed near the center of the array during March 1989 (shaded region). (B) Time-depth evolution of potential temperature averaged over the chimney region. Contour interval is 0.21C. Typical rms uncertainty (1C) as a function of depth is shown to the right. Total heat flux (from the British Meteorological Office) and daily averaged ice cover (derived from satellite SSM/I measurements) are shown above. Adapated from Morawitz WML, Cornuelle BD and Worcester PF (1996) A case study in three-dimensional inverse methods: combining hydrographic, acoustic, and moored thermistor data in the Greenland Sea. Journal of Atmospheric and Oceanic Techniques 13: 659–679.
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50
TOMOGRAPHY
Depth (km)
0
1
° 76
2
6°
°
5°
75
4°
Wes t lo
ngitu
3° de
2°
° 74
r th
No
de
itu
lat
Figure 7 Mixed layer depth in the central Greenland Sea on 19 March 1989, as defined by the minimum depth of the 1.21C isotherm. The ocean is colder than 1.21C above this depth as a result of surface cooling and is warmer below. The main chimney reaches a maximum depth of about 1500 m in an area about 50 km in diameter centered on 74.751N, 3.51W, south west of the gyre center. A secondary chimney with a maximum depth of about 1000 m is evident to the north east of the gyre center, separated from the primary chimney by a ridge of warmer water. Contours of mixed layer depth are shown below. Adapted from Morawitz WML, Sutton PJ, Worcester PF et al. (1996) Threedimensional observations of a deep convective chimney in the Greenland Sea during winter 1988/1989. Journal of Physical Oceanography 26: 2316–2343.
extracted from the three-dimensional inverse estimates were averaged over the chimney region to show the time-evolution of the chimney (Figure 6). A one-dimensional vertical heat balance adequately described changes in total heat content in the chimney region from autumn 1988 until the time of chimney break-up, when horizontal advection became important and warmer waters moved into the region. The average annual deep-water production rate in the Greenland Sea for 1988–1989 was estimated from the average temperature change over the region occupied by the tomographic array to be about 0.1 106m3 s1.
with baroclinic (internal) tidal displacements and of barotropic tidal currents, respectively. The availability of global sea-surface elevation data from satellite altimeter measurements has made possible the development of improved global tidal models. Tomographic measurements of tidal currents made in both the central North Pacific and western North Atlantic Oceans have shown that the harmonic constants for current derived from a recent global tidal model (TPXO.2) are accurate to a fraction of a millimeter per second in amplitude and a few degrees in phase in open ocean regions (Figure 8). Small, spatially coherent differences between the modeled and measured harmonic constants are found in the western North Atlantic near complicated topography that is unresolved in the model. These differences are almost certainly due to errors in the TPXO.2 currents. The integrating nature of the tomographic measurements suppresses short-scale internal waves and internal tides, providing tidal current measurements that are substantially more accurate than those derived from current-meter data. Tomographic measurements of sound-speed fluctuations at tidal frequencies from the same experiments revealed large-scale internal tides that are phase-locked to the barotropic tides. Prior to these measurements it had commonly been assumed that midocean internal tides are not phase-locked to the barotropic tides (except for locally forced internal tides) and have correlation length scales of order only 100–200 km. The measurements in the North Pacific were consistent with a large-scale, phaselocked internal tide that had been generated at the Hawaiian Ridge and then propagated to the tomographic array over 2000 km to the north (Figure 9). These observations were subsequently confirmed from satellite altimeter data. The measurements in the western North Atlantic revealed a diurnal internal wave resonantly trapped between the shelf just north of Puerto Rico and the turning latitude for the diurnal K1 internal tide, 1100 km distant at 30.01N (Figure 10). In both cases the peak-to-peak temperature variations associated with the maximum displacement of the first baroclinic modes were only about 0.041C. Once again, the acoustic observations of the baroclinic tide average in range and depth, suppressing internal-wave noise and providing enhanced estimates of the deterministic part of the internal-tide signal compared to measurements made at a point, such as by moored thermistors.
Barotropic and Baroclinic Tides
Sum and difference travel times from long-range reciprocal transmissions provide precise measurements of the sound-speed (temperature) changes associated
Heat Content
Acoustic methods have been used to measure the heat content of the ocean and its variability on basin
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TOMOGRAPHY
51
50° N 40°
30°
20°
10°
0°
80° W
70°
50°
60°
20°
30°
40°
10°
0°
2.5 400
Model (deg)
Model (cm/s)
2 1.5 1 0.5
300 200 100 0
Zonal
0
Zonal
2.5 400
Model (deg)
Model (cm/s)
2 1.5 1 0.5 0
300 200 100 0 Meridional
Meridional 0
1 1.5 2 0.5 Measured (cm / s)
2.5
0
200 Measured (deg)
400
Figure 8 (Bottom) Comparison of the M2 current harmonic constants (amplitude and phase) in the North Atlantic Ocean derived from reciprocal acoustic transmissions (filled circles) and from current meter data (dots) with those predicted by a global tidal model derived from satellite altimeter measurements (TPXO.2). (Top) The acoustic data are from the pentagonal tomographic transceiver array deployed in the western North Atlantic between Puerto Rico and Bermuda during 1991–1992. The current-meter mooring locations are indicated by crosses. Adapted from Dushaw BD, Egbert GD, Worcester PF et al. (1997) A TOPEX/POSEIDON global tidal model (TPXO.2) and barotropic tidal currents determined from long-range acoustic transmissions. Progress in Oceanography 40: 337–367.
scales, taking advantage of the integrating nature of acoustic transmissions to rapidly and repeatedly make range- and depth-averaged temperature measurements at ranges out to about 5000 km. In the Mediterranean Sea, for example, a network of seven tomographic instruments was deployed for nine months during 1994 in the
THETIS-2 experiment, including cross-basin transmissions from Europe to Africa (Figure 11). Although it is normally difficult to obtain heat content measurements comparable to those provided by the acoustic data, in this case one of the transmission paths was intentionally aligned with the route of a commercial ship, from which expendable
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52
TOMOGRAPHY
160 km
40° N
RTE87
30° Midway
20°
Hawaii
10 cm 10° km
180°
170° W
500
61
23
112
74
36
125
87
49
11
100
0 160°
150°
Figure 9 Schematic diagram showing the phase-locked internal tide generated at the Hawaiian Ridge and the triangular tomographic array deployed north of Hawaii during 1987 used to detect it. The dashed lines represent the crests of a wave with 160 km wavelength. Each leg of the tomographic array functions as a linear array with maximum sensitivity to an incident plane wave propagating perpendicular to the leg (i.e., with wave crests aligned parallel to the leg). The beam pattern (in dB) of the 750-km northern leg for a model-1 incident wave with a wavelength of 160 km is indicated. The satellite altimeter data that subsequently confirmed the tomographic observations are also shown. High-pass filtered M2 surface elevations (cm) are plotted along ten ascending TOPEX/ POSEIDON ground tracks. Adapted from Dushaw BD, Cornuelle BD, Worcester PF, Howe BM and Luther DS (1995) Barotropic and baroclinic tides in the central North Pacific Ocean determined from long-range reciprocal acoustic transmissions. Journal of Physical Oceanography 25: 631–647; Ray RD and Mitchum GT (1996) Surface manifestation of internal tides generated near Hawaii. Geophysical Research Letters 23: 2101–2104.
bathythermograph (XBT) measurements were made at two-week intervals. The acoustic average of potential temperature between 0 and 2000 m depth over the 600-km path and the corresponding XBT average between 0 and 800 m depth agreed within the expected uncertainty of 0.031C (Figure 11). Further, the evolution of the three-dimensional heat content of the western Mediterranean estimated from the acoustic data was found to be consistent with the integral of the surface heat flux provided by European Centre for Medium-range Weather Forcasts (ECMWF), after correction for the heat flux through the Straits of Gibraltar and Sicily (Figure 11). The acoustic data were subsequently combined with satellite altimeter data and an ocean general circulation model to generate a consistent description of the basin-scale temperature and flow fields in the western Mediterranean and their evolution over time. Acoustic and altimetric data are complementary for this purpose, with the acoustic
data providing information on the ocean interior with moderate vertical resolution and the altimetric data providing detailed horizontal coverage of the ocean surface. Similar measurements have been made in the Arctic Ocean in the Transarctic Acoustic Propagation (TAP) experiment during 1994 and in the Arctic Climate Observations using Underwater Sound (ACOUS) project beginning in 1999. During the TAP experiment, ultralow-frequency (19.6 Hz) acoustic transmissions propagated across the entire Arctic basin from a source located north of Svalbard to a receiving array located in the Beaufort Sea at a range of about 2630 km. Modal travel time measurements yielded the surprising result that the Atlantic Intermediate Water layer was about 0.41C warmer than expected from historical data. This result was subsequently confirmed by direct measurements made from icebreakers and submarines. Acoustic data collected on a similar path during
(c) 2011 Elsevier Inc. All Rights Reserved.
TOMOGRAPHY
53
USA 1000
80°
4000
e
tud
4000 o
6o
,4
69, 71 o
85
53, 70 o
2000 m
51
,3 14 o 62 o
101, 2
2
o
48
o
94, 252
6 46, 53
282
o
o
86
o
20
26
44,
9,
,3
76,
4
30
o
6
,2
76
o
53,
22°
1
o
49, 89
5
24°
30° N
25° 20°
K1
26°
ati
(A)
5500
5500
60°
gl
ch
65°
1
2
5500
Bermuda
nin
ren .T
Puerto Rico
6
3
P.R
70°
N
5
4
t ur
75°
K1
W
28°
2000
Cuba
1 6,
110 o
3
3
Caicos Is. Silver Bk.
20° 4000 m
Hispaniola
2000 m
18° (B)
Puerto Rico 72° W
70°
68°
66°
64°
_1
1
Figure 10 (A) Schematic diagram showing the predicted displacement of the lowest internal mode for the resonant diurnal (K1) internal tide north of Puerto Rico and the six-element tomographic array deployed during 1991–1992 used to observe it. The tomographic array is about 670 km in diameter. (B) The predicted displacement of the diurnal (K1) internal tide and the measured harmonic constants (amplitude and phase) for each acoustic path. Adapted from Dushaw BD and Worcester PF (1998) Resonant diurnal internal tides in the North Atlantic. Geophysical Research Letters 25: 2189–2192.
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54
TOMOGRAPHY 44° N
42°
40°
38°
36°
(A)
2°W
0
2°E
4°
6°
8°
10°
12°
Potential temperature anomaly (°C)
0.15 0.10 0.05 0 _ 0.05 _ 0.10
(B)
Inversion CTD sections XBT sections
1 Feb
1 Apr
1 Jun
1 Aug
1 Oct
Potential temperature anomaly (°C)
0.15 0.10 0.05 0 _ 0.05 3-D average tomography ECMWF with straits corr. Climatology
_ 0.10 _ 0.15
(C)
April 1999 as part of the ACOUS project indicated further warming of about 0.51C, which was again confirmed by direct measurements made from submarines. Acoustic methods can provide the longterm, continuous observations in ice-covered regions that are difficult to obtain using other approaches. Finally, measurements of basin-scale heat content in the Northeast Pacific were made intermittently from 1983 through 1989 using transmissions from an acoustic source located near Kaneohe, Hawaii, and more recently from 1996 through 1999 during the Acoustic Thermometry of Ocean Climate (ATOC) project using sources located off central California and north of Kauai, Hawaii. Data from the ATOC project have shown that ray travel times may be used for acoustic thermometry at least out to ranges of about 5000 km. The estimated uncertainty in rangeand depth-averaged temperature estimates made from the acoustic data at these ranges is only about 0.01 1C. Comparisons between sea-surface height measurements made with a satellite altimeter and sea-surface height estimates derived using the range-averaged temperatures computed from the acoustic data indicate that thermal expansion alone is inadequate to account for all of the observed changes in sea level (Figure 12). Analysis of the results obtained when the acoustic and altimetric data were used to constrain an ocean general circulation model indicates that the differences result largely from a barotropic redistribution of mass, with variable salt anomalies a contributing, but smaller, factor.
1 Feb
1 Apr
1 Jun 1 Aug 1994
1 Oct
1 Dec
Figure 11 (A) Geometry of the THETIS-2 experiment in the western Mediterranean Sea, showing the instrument locations and acoustic transmission paths. The transmission path from source H to receiver W3 (heavy solid) coincided with an XBT section occupied every two weeks. (B) Range- and depthaveraged potential temperature (relative to 13.1111C) over 0– 2000 m depth and over the 600 km path from source H to receiver W3 derived from the acoustic data, from CTD data, and from XBT data. The shaded band indicates the uncertainty in the temperature estimates derived from the acoustic data. (C) Evolution of the three-dimensional average heat content for the western Mediterranean during 1994 derived from the acoustic data, from the ECMWF surface heat fluxes corrected for heat transport through the Straits of Gibraltar and Sicily, and from climatology. Adapted from Send U, Krahmann G, Mauuary D et al. (1997) Acoustic observations of heat content across the Mediterranean Sea. Nature 385: 615–617.
Appendix: Conversion from Sound Speed to Temperature Tomgraphic methods fundamentally provide information on the oceanic sound-speed and water-velocity fields. For most oceanographic purposes, however, temperature T and salinity Sa are of more interest than sound speed. Although sound speed C is a function of both T and Sa (as well as pressure), temperature perturbations are normally by far the most important contributor to sound-speed perturbations. A simple nine-term equation for sound speed due to Mackenzie is CðT; Sa; DÞ ¼ 1448:96 þ 4:591T 5:304 102 T 2 þ 2:374 104 T 3 þ 1:340ðSa 35Þ þ 1:630 102 D þ 1:675 107 D2 1:025 102 T ðSa 35Þ 7:139 1013 TD3
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½37
55
cm (rms)
TOMOGRAPHY
34
l
32 30 28 26 24 22
k n o v1
20 18 16 14 12 10 8 6
v2
4 2 (A)
5
l
0
Sea surface height (cm)
_5 k
5 0 _5
5
o
0 _5 (B)
Jan 93
Jan 97
Jan 95
Figure 12 (A) The ATOC acoustic array is superimposed on a map of the root-mean-square (rms) sea level anomaly from altimetric measurements. Transmission paths from sources off central California and north of Kauai to a variety of receivers are shown. (B) The range-averaged sea-surface height anomaly along several of the acoustic sections from satellite altimeter data (solid black), inferred from the acoustic data (solid red), computed from climatological temperature fluctuations (dashed), and derived from an ocean general circulation model (solid blue). Uncertainties are indicated for the acoustic estimates. Adapted from ATOC Consortium (1998) Ocean climate change: comparison of acoustic tomography, satellite altimetry, and modeling. Science 281: 1327–1332.
where C is in ms1, T is in degrees Celsius, Sa is in parts per thousand (ppt), and D is the depth (positive down) in meters. Differentiating,
@C ¼ 4:59 0:106T þ 7:12 104 T 2 @T 1:03 102 ðSa 35Þ
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½38
56
TOMOGRAPHY 0.45
where TðÞ is the reference temperature profile corresponding to the reference sound-speed profile CðÞ and DT ¼ T TðÞ. The fractional change in sound speed is then
0.40
DC=C ¼ aDT ð1 þ mb=aÞ
∂T / ∂C (°C / m s−1)
0.35
In midlatitudes a typical value for m might be 0.1(ppt)(1C)1, giving mb=a E 0:03. Thus the soundspeed perturbation DC depends to first order only on the temperature perturbation DT. The sound-speed perturbation profile DCðzÞ derived from the acoustic data can be easily converted to the corresponding temperature perturbation profile
0.30
0.25
DT ðzÞ ¼ 0.20
0.15
½44
ðCðÞþDC
@T dC; @C
½45
CðÞ
5
10
15 T (°C)
where the integral allows for the dependence of @T=@C on temperature.
20
Figure 13 The derivative @T =@C as a function of temperature. Adapted from Dushaw BD, Worcester PF, Cornuelle BD and Howe BM (1993) Variability of heat content in the central North-Pacific in summer 1987 determined from long-range acoustic transmissions. Journal of Physical Oceanography 23: 2650–2666.
See also Acoustics, Arctic. Acoustics in Marine Sediments. Deep Convection. Internal Tides. Inverse Models. Tides.
Further Reading
@C ¼ 1:34 1:03 102 T @Sa
½39
where a slight depth dependence has been dropped. The derivative @T=@C ¼ 1=ð@C=@TÞ varies significantly with temperature (Figure 13). To first order, the fractional change in sound speed is then DC=C ¼ aDT þ bDSa
½40
a¼
1 @C E 2:4 103 ðo CÞ1 C @T
½41
b¼
1 @C E 0:8 103 ðpptÞ1 C @Sa
½42
where
at 101C. For a locally linear temperature–salinity relation, Sa ¼ SaðT ðÞÞ þ mDT
Khil’ko AI, Caruthers JW, and Sidorovskaia NA (1998) Ocean Acoustic Tomography: A Review with Emphasis on the Russian Approach. Nizhny Novgorod: Institute of Applied Physics, Russian Academy of Sciences. Munk W, Worcester P, and Wunsch C (1995) Ocean Acoustic Tomography, Cambridge: Cambridge University Press. (The review given here draws heavily from, and uses the same notation as, this monograph, which provides a comprehensive account of the elements of oceanography, acoustics, signal processing, and inverse methods necessary to understand the application of tomographic methods to studying the ocean.) Munk Wand Wunsch C (1979) Ocean acoustic tomography: a scheme for large scale monitoring. Deep-Sea Research 26: 123--161. Worcester PF (1977) Reciprocal acoustic transmission in a mid-ocean environment. Journal of the Acoustical Society of America 62: 895--905.
½43
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TOPOGRAPHIC EDDIES J. H. Middleton, The University of New South Wales, Sydney, NSW, Australia Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2986–2993, & 2001, Elsevier Ltd.
Introduction Topographic eddies in the ocean may have a range of scales, and arise from flow separation caused by an abrupt change in topography. This abrupt change may be of large scale, such as a major headland, in which case the topographic eddy is essentially a horizontal eddy of scale many tens of kilometers in a shallow coastal ocean. Eddies also occur at much smaller scales when ocean currents flow around small reefs, or over a rocky seabed. In this case the topographic eddies are perhaps only meters or centimeters in scale. A rule of thumb is that topographic eddies are generated at the same length scales as the generating topography. Perhaps the earliest recorded evidence of a topographic eddy in the ocean comes from Greek mythology, where there is mention of a whirlpool occurring beyond the straits of Messina, between Sicily and Italy. Jason and the Argonauts in their vessel the Argo had to find the path between the Cliff known as Scylla, and the whirlpool having the monster Charybdis. The whirlpool still exists and occurs as the tides flood and ebb through the narrow straits. Another well-known tidal whirlpool, intensified at times by contrary winds and often responsible for the destruction of small craft, occurs off the Lofoten Islands of Norway. The Norwegian word maelstrom is associated with the whirlpool. More recently, the fishing and marine lore of the Palau District of Micronesia, and the knowledge of ocean currents held apparently for hundreds, if not thousands, of years has been investigated. In fact, it was found ‘The islanders had discovered stable vortex pairs and used them in their fishing and navigation long before they were known to science.’ A sketch, drawn from the fishermen’s description, is shown in Figure 1. The flow appears to comprise a stable vortex pair in the lee of the island, with identifiable zones of rougher water which would result from the conflicting directions of currents and waves, and calmer waters directly upstream from the island. A most interesting feature is the description of concentrations of tuna and flying fish, which clearly
have a preference for congregating in certain zones, perhaps because there they find food more prevalent. This diagram underscores a fundamental importance of topographic eddies; they serve not only as a feature of the circulation, but also to provide preferential environments for the marine biota. Although such whirlpools, eddies, and wakes had been well known for centuries by seafarers, in the early 1900s pilots and aerodynamicists ‘rediscovered’ eddies. The additional feature that they discovered was that eddies and wakes draw their energy from the mean flow, and provide a ‘form drag’ on the incident flow, tending to slow it down. In the ocean, topographic eddies (or recirculating flows) comprise horizontal eddies generated by coastal currents flowing past coastal headlands, coral reefs, islands, or over undersea hills or ridges. They are important as they profoundly affect not only the
HAPITSETSE (very rough)
Daily tuna migration route ARM (rough)
(calm)
Flying fish concentrated along here
Launch canoes here Current fastest here
ISLAND REEF
SURIYOUT (calm) good fishing Prevailing current Figure 1 Island Wake of Tobi in Micronesia, showing flow patterns and concentrations of tuna and flying fish. (Reproduced from Johannes, 1981.) , Tuna concentrations; J, Flying fish concentrations.
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57
58
TOPOGRAPHIC EDDIES
horizontal distribution of nutrients, pollutants, bottom sediments and biota through direct horizontal transport, but also the vertical distribution through the associated three-dimensional flow field. In addition, a cascade of turbulent energy to smaller scales provides a continued source of smaller-scale turbulence, which itself acts to further diffuse and transport such matters. Topographic eddies may also be produced by smaller-scale reefs (submerged wholly or partly) with scales typical of the width and height of the reef, in which case the turbulent eddies are fully three-dimensional in nature. These eddies are also unstable and break down into turbulence of progressively smaller scale, stirring the ocean, and creating strong spatial gradients, which enhance mixing and diffusion of passive materials. Perhaps it is appropriate now to discuss the terms turbulence and diffusion. Turbulence refers to a state of flow which is chaotic and random in its detail, such that any instantaneous state of flow will not ever be reproduced at any later time. However, there may be underlying physics which imply that measurements of properties made at any point will, after much averaging over time, produce an average which is predictable and reproducible. Diffusion refers to the stirring and mixing of waters as they flow in a turbulent manner. Diffusion tends to smear out or dilute unusually large concentrations of some property, such as a pollutant. The stronger the turbulence, the more rapid the diffusion.
Larger Scale Topographic Eddies Many coastal headlands protrude several kilometers into coastal currents, where the ocean depth is often less than 100 m or so. The coastal currents may be tidally induced, changing over a period of 12 h or so, or may be relatively steady, changing perhaps only once every 7–10 days as a result of local synoptic scale atmospheric systems (see Wind Driven Circulation), or as a result of coastal trapped waves. Any resulting eddies are somewhat two-dimensional, with horizontal size many times that of vertical size, and occur downstream of the headland. The generation of such recirculating flows or eddies has traditionally been considered to occur as follows. Flow separation occurring as a coastal current passes a headland is a result of the inability of the pressure field to allow the flow to follow the coastal contours, resulting in an adverse pressure gradient at the boundary. The separated flow has a very strong shear layer (with high vorticity), and a large-scale eddy may form, and either remain
attached to the headland, or be carried downstream. In some cases, a string of eddies (known as a vortex street) may be generated. Figure 2 shows a characteristic flow pattern behind Bass Point (near Sydney), with an overall larger-scale wake pattern, superimposed on which there are a number of smaller eddies. There are several dimensionless numbers which represent various balances between physical processes, and hence terms in the equations of motion, which have been proposed in an attempt to simplify the physical balances which exist. For example, classical laboratory studies of the breakdown to turbulence have utilized the Reynolds number Re ¼ UL=v where U is the scale for the incident flow, L is the horizontal scale of the obstacle (reef or headland), and n is the kinematic viscosity of the fluid. For example, Reynolds numbers between 4 and 40 for two-dimensional flows around a circular cylinder indicate a trapped and steady recirculating eddy-pair. For Re > 40 the trapped eddy-pair maintains its presence, but the downstream wake begins to become unstable. At Reynolds numbers larger than Re ¼ 80, the eddy-pairs are swept downstream as a von Karman vortex street. Reports of such studies invariably cite the need to have no ‘environmental noise’ in the system to ensure reproducibility of the wake at low Re , that is, a perfectly smooth incident flow upstream. Field observations show some features which are at first sight similar to the laboratory observations, however, characterization of wakes and eddies based on the Reynolds numbers (and/or other simple dimensionless parameters) have often produced conflicting results. For field observations, relevant dimensional quantities include the incident current speed U, the distance the headland protrudes into the free stream L, the Coriolis parameter f and the water depth D. Vertical density stratification plays a role in deeper water, and the effects of the winddriven surface layer and the frictional bottom boundary layer play a role in shallower water. Quantities arising from the flow itself are the horizontal eddy diffusivity nx and vertical eddy diffusivity nz associated with horizontal and vertical turbulent diffusion, respectively. Values of nx are usually several orders of magnitude greater than values of nz for most oceanic flows, indicating that horizontal diffusion dominates over vertical. The assumption that turbulent Reynolds stresses are proportional to the mean velocity gradient allows an eddy-diffusivity approximation for the mean components of a turbulent flow. Reynolds numbers
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TOPOGRAPHIC EDDIES
59
Figure 2 Attached eddies and vortex street in the wake of Bass Point as simulated by a computer model. (Reproduced from Denniss et al., 1995.) The domain width is 6.67 km, and the maximum current vector, as indicated by the longest arrow, is 0.42 m s1.
for oceanic flows are then evaluated using the horizontal eddy diffusivity nx rather than the molecular viscosity. As an example, for flows around Bass Point Sydney, Re ¼ UL=nx B1000 using the overall headland width, and Re ¼ 5–10 for smaller-scale eddies produced by reefs at the tip of the headland, where LB100 m and nx B15 m2 s1. Thus there are at least two different scales of topographic eddies in the recirculation processes depicted in Figure 2. Other relevant dimensionless parameters include the Rossby number Ro ¼ U=fL which gives a ratio of advective acceleration (nonlinear) terms to Coriolis terms in the momentum equations. The Coriolis parameter f denotes the local rate of the earth’s rotation about the vertical axis. Low Ro flows (Ro 51) have the background rotation of the earth controlling the dynamics, with relatively slow flows, and a tendency to stable flow patterns. High Ro flows (Ro B1) have a stronger tendency to produce eddies, as the non-linear terms which characterize energetic flows tend to dominate. Most larger-scale flows in the ocean have Ro 51, indicating the rotation of the earth is a dominating effect, whereas for the Bass Point example described above,
Ro B1, indicating that the advective acceleration terms may be strong enough to produce eddies. Derived parameters include the bottom boundary layer or Ekman layer thickness d, which scales as dBð vz =f Þ1=2 This height is a measure of the vertical extent above the bottom where the flow is affected by transfer of vertical stresses. This results in a deceleration of current from the free stream value U in the flow above to zero at the sea bed. In this bottom boundary layer, currents will change in direction, turning to the left (right) in the Northern (Southern) Hemisphere as the seabed is approached from above. If the bottom depth Dbd, then the boundary layer provides a frictional decay on the overall flow. If, however, DBd, then the bottom turbulent layer dominates the entire water column, and somewhat different dynamics follow. The vertical Ekman number giving the ratio of vertical momentum diffusion terms to the Coriolis term is E ¼ vz =fHd Thus E may be interpreted as a ratio indicating relative importance of bottom frictional effects and those
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60
TOPOGRAPHIC EDDIES
due to the Earth’s rotation. High E values are indicative of flows in which bottom friction dominates the flow (very shallow flows or flows with high vertical eddy viscosity), whereas E51 is indicative of deeper flows, or flows where bottom friction is less effective. The importance of an island wake parameter P (or its square root) defined by P ¼ UD2 =vz L is discussed by several authors as being the relevant parameter (see Island Wakes) to describe a wake some distance downstream; it is essentially a Reynolds number based on vertical eddy diffusivity rather than horizontal. A survey of data from a range of island wakes indicates that for P51 the current simply flows around the headland with no recirculating eddies, for PB1 the wake is steady and stable, and for Pb1 eddy shedding is observed. For very shallow water flows where bottom stress is dominant, a summary of data show that a ratio of Rossby to Ekman numbers defined by Ro =Ek ¼ UDd=vz L is perhaps a better parameter than P with eddy shedding for large numbers (Ro =Ek > 500), steady eddy formation for Ro =Ek B100 and fully attached eddies for Ro =Ek o10. In shallow waters where DBd, these parameters (P and Ro =Ek ) are essentially the same. The use of dimensionless numbers to characterize flows is based on the assumptions that the essential processes are characterized by simple dynamical balances which will hold essentially throughout the domain of interest. However, for unsteady, nonlinear flows the balances are dependent on both location and time. Thus the Reynolds and Rossby numbers above are a measure of the flow balance in the upstream region. Reynolds numbers higher than some critical value imply that the resultant downstream flow is unsteady and chaotic, and is fundamentally different from the steady flow which occurs at lower Reynolds numbers. By contrast, the island wake parameters P and the Ro =Ek represent physical balances of the wake downstream of the headland. The bottom boundary layer thickness and Ekman numbers are properties of the vertical profile of the flow at any location. A major feature, recognized in the early laboratory experiments was that flow stability at low Reynolds numbers was dependent on the absence of smallscale, rapidly changing background variability (referred to here as stochastic noise) occurring in the incident or upstream flow. However, it has been
demonstrated theoretically that transition of the larger-scale flow to an unsteady chaotic system can be linked to the system’s amplification of background stochastic noise. In the case of recirculating headland eddies, such stochastic noise might be due to variations in wind stress, wave activity (internal and surface), and nonlinear small-scale high-frequency turbulence caused by flow over or around bottom topography such as submerged or semisubmerged reefs. Support for these ideas is provided by analyses of data from Bass Point. It is hypothesized that the turbulence generated by the smaller-scale reefs at the tip of Bass Point creates a turbulent horizontal shear layer. This pushes the flow separation point downstream, inhibiting the formation of a larger-scale attached eddy except under strong incident current conditions. Thus the smaller-scale turbulence at the tip of the Point has a substantial effect on the largerscale wake flow. The small-scale turbulence is characterized in strength by a horizontal eddy diffusivity nx , and since nx is absent from the above wake parameters, the wake parameters cannot be definitive in terms of flow description. Thus it can be concluded that simulations or predictions of flow behavior based on dimensionless numbers alone, traditional stability analyses, or direct (nonlinear) numerical simulation may fail without exact knowledge of the background environmental stochastic noise. The above description of flows is essentially applicable to cases of steady upstream inflows, however, in many coastal regions the tidal flood and ebb creates an alongshore current which floods and ebbs in opposite directions alongshore. In this case, there may be transient eddies generated at each half tidal cycle at every headland. The schematic diagram given here in Figure 3 illustrates the point. Eddies are generated on each cycle, and sit either side of the headland, with a residual flow always directed offshore at the tip of the point (Figure 3A); depth variability offshore ensures that rotational motions are generated by differential bottom friction (Figure 3B). A simple headland eddy is shown in Figure 3C, and a vortex street in Figure 3D. The dynamics that allow generation of topographic eddies do not necessarily control their subsequent motion, the turbulent energy cascades or their ultimate dissipation. For topographic eddies in coastal waters, the presence of bottom boundary layers renders the flow partly three-dimensional, and so energy cascades to smaller and smaller scales as eddies break up. Vertical eddy viscosity in the bottom boundary layer, caused by friction at the seabed, also extracts energy from the system, creating a form drag on coastal currents.
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TOPOGRAPHIC EDDIES
ebb
flood
flow downstream with Fr o1, are also known to occur in strongly flowing rivers. Flows which are density stratified are characterized by the flow speed U and the buoyancy frequency N, where N is defined by
(A)
N2 ¼
residual shallow
61
gdr rdz
In flows of depth D, the dimensionless number which reflects the ratio of current speed to wave speed is
deep
Fr ¼ U=ND
(B)
(C)
(D) Figure 3 The possible mechanisms for the generation of headland eddies in a tidally cyclic flow (A), a steady flow where the depth increases offshore (B), and cases where a steady flow induces a simple attached eddy (C) or a train of separated eddies (D). (Reproduced from (Robinson 1975.)
Topographic Eddies Due to Bottom Topography in Stratified Flows A dimensionless number which directly gives the ratio of current velocity U to the velocity of gravity waves in a current of depth D is known as the Froude number and is defined by Fr ¼ U=ðgDÞ1=2 The Froude number is the definitive number which divides a physical process where a disturbance may propagate upstream (called subcritical and denoted by Fr o1), or a disturbance is swept downstream (called supercritical and denoted by Fr > 1). Flows over shallow sills, or coral reefs, in areas of strong tidal flow (e.g., north-western Australia) may sometimes be so rapid as to be supercritical. Hydraulic jumps, caused by a flow transition from rapid smooth flow upstream with Fr > 1 to slow turbulent
Flows over and around obstacles depend not only on this internal Froude number, but also on the height H of the obstacle, its horizontal size and the steepness of the topography. Internal hydraulic jumps are also known to exist in the ocean where very strong tidal currents flow over steep topography, such as the Mediterranean outflow, or off the British Columbia coast (Figure 4). The subsequent turbulence is confined downstream causing a high level of mixing and turbidity, while upstream waters remain relatively placid and clear. Since such hydraulic jumps usually occur in irregularly shaped channels, they are often also the source of small topographic eddies. Consideration of stratified flow around obstacles having an infinite value Ro (zero Coriolis parameter) provides many examples of the generation of topographic edies. These include hydraulic jumps, exchange flows, waves and recirculating flows over two and three-dimensional obstacles in finite depth and infinitely deep stratified flows. In water much deeper than the obstacle height H, the relevant height scale is H, and the relevant dimensionless parameter is NH=U, an inverse Froude number based on the obstacle height. An interesting case study is depicted in Figure 5, for stratified flow with parameter NH/U ¼ 5. In this case the stratification is sufficiently strong to confine recirculation patterns to within about two obstacle heights of the seabed, with flow going both over and around the obstacle, and generating a pair of steady attached eddies. The dynamics are extremely complex, and consist of nodes where the flow separates, and stagnation points where the flow has zero current. The flows described have zero background rotation (i.e., f ¼ 0), and thus cannot describe a range of eddy-like flows, trapped above an obstacle in a current flow in a rotating reference frame and known as Taylor columns. For stratified flows over typical ocean seamounts in which the earth’s rotation plays a
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62
TOPOGRAPHIC EDDIES 0
20
Capping surface layer
15
19
20
21
Depth (m)
22.5
24 23
Subcritical flow
23.5 24.2
40
15
16 22
Entraining interface
Weakly stratified layer
24
60 Internal hydraulic jump
24.2
80
100 _ 800 E
24.4
_ 600
_ 400
_ 200
0 Distance (m)
200
400 W
Figure 4 Schematic diagram of an internal hydraulic jump, in which the upstream flow (at left) is slow (with Fr o1=mn) accelerates rapidly down a steep slope (with Fr > 1=mn), and flows into a turbulent hydraulic jump (with Fr o1=mn) (Reproduced from Farmer and Armi, 1999.) The downstream turbulence cannot propagate up the steep slope as the stratification N is not sufficiently large for the internal wave speed ND to exceed U, and so the turbulent flow is confined downstream of the topographic slope.
in the form Bu ¼ ðNH=fLÞ2 ¼ ðRo =Fr Þ2 is known as the Burger number. Bu is also the ratio of Rossby number to Froude number squared. The Burger number is thus an indication of the balance of effects of stratification and earth’s rotation, adjusted for the vertical aspect ratio of the seamount. High values of Bu tend to keep topographic disturbances more confined vertically, whereas low values permit taller Taylor columns, in which the effects of the obstacle extend higher in the water column. A full description of Taylor columns above seamounts in stratified flows is beyond the scope of this article.
(A)
Turbulence Due to Small-scale Bottom Topography and Reefs
(B) Figure 5 Topographic eddy in stratified flow over a threedimensional obstacle with NH/U ¼ 5 (reproduced from Baines, 1995), showing the side view through a cross-section along the line of symmetry (A), and the plan view showing the horizontal current components at a depth below the top of the obstacle (B). Also shown in (B) is the zone in which upwelling occurs at that same level (hatched).
role, the relevant scale of vertical disturbance above the seamount is fL=N, where L is the horizontal scale of the seamount. The ratio of the vertical scale of the obstacle H to this scale height is thus NH=fL, which
For topography whose roughness scales are much smaller than the depth, and timescales are short, then the Ro number is high and Coriolis effects are negligible. Flow around such topography then has properties typical of those found in laboratory experiments, allowing for even smaller-scale turbulence to act as a stochastic noise at the inflow region. A number of topographic eddies may then be formed at different times and/or places, sometimes creating a wholly turbulent flow field over a limited region of the coastal ocean.
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TOPOGRAPHIC EDDIES
Such turbulence may be caused by strongly flowing tidal currents over a rough seabed or over and through coral reefs, for example, where the roughness scales may be as small as a few centimeters. These flows may scour the seabed, raising sediments off the seafloor and transporting them elsewhere. Such turbulence can also act to thoroughly mix the water column in areas where strong tidal currents flow over significant bottom topography. This occurs, for example, over submerged coral reefs at 80 m of water depth offshore from Hydrographers Passage in the Great Barrier Reef where phytoplankton multiply rapidly as a consequence of the combination of nutrient supply and light. Turbulence on these scales is still subject to the energy cascade phenomenon, whereby eddies continually break down to smaller and smaller eddies until fluid viscosity damps out the motions.
Biological Implications of Topographic Eddies As depicted in Figure 1, there is clearly a relationship between the wake of Tobi Island and the fish concentrations, as described by the local fishermen. However, there are also some much more subtle responses. These are related to the vertical circulation which is necessarily part of a horizontally circulating eddy. The physics is relatively straightforward. In a horizontal eddy, the eddy can only maintain its structure if the eddy center has low pressure, which exists by virtue of a reduced sea level in the eddy center. Throughout the main part of the water column (away from the seabed) the horizontal pressure gradient balances the centripetal force. However, in coastal waters the pressure gradient has an effect right down through the bottom boundary layer to the seabed. In this bottom boundary layer, the centripetal force is reduced because the velocity is reduced, and so the pressure gradient drives a flow
Figure 6 Topographic eddy in the coastal ocean showing inflow in the bottom boundary layer, upwelling in the eddy center, and outflow at the surface.
63
toward the center along the seabed. This flow then upwells in the eddy center (Figure 6), and outflows on the surface. The upwelling brings with it fine sediments, nutrients, plankton, and perhaps larval fish. The combination of nutrients, plankton and greater light can enhance plankton growth. Thus eddies in shallow waters are intrinsically places of enhanced plankton growth, and perhaps enhanced concentrations of other elements of the marine food chain. In deeper waters, where the ocean is stratified, the lower pressure at the eddy center also results in a general uplift of deeper nutrient-rich waters, creating the same effect as in shallower waters. Observations in the wake of Cato Reef off eastern Australia showed higher concentrations of nutrients, phytoplankton, and larval fish of better condition, and the principal effects of this increased productivity were attributed to the uplift in the wake. Referring back finally to Figure 1, the diagram can now be interpreted. The arms along which the flying fish and tuna concentrate are zones in which upwelled nutrient-rich waters, now outflowing from the eddy centers, meet the nutrient poor free-stream currents. This is likely to be a zone where plankton in the free stream now have an opportunity to grow, and the larger fish are perhaps benefiting from the enhanced primary productivity.
See also Coastal Trapped Waves. Island Wakes. Mediterranean Sea Circulation. Mesoscale Eddies. Small-Scale Physical Processes and Plankton Biology. Three-Dimensional (3D) Turbulence. Wind Driven Circulation.
Further Reading Baines PG (1995) Topographic Effects in Stratified Flows. Cambridge: Cambridge University Press. Batchelor GK (1967) An Introduction to Fluid Dynamics. Cambridge: Cambridge University Press. Boyer DL and Davies PA (2000) Laboratory studies in rotating and stratified flows. Annual Reviews of Fluid Mechanics 32: 165--202. Coutis PF and Middleton JH (1999) Flow topography interaction in the vicinity of an isolated deep ocean island. Deep-Sea Research 46: 1633--1652. Denniss T and Middleton JH (1994) Effects of viscosity and bottom friction on recirculating flows. Journal of Geophysical Research 99: 10183--10192. Denniss T, Middleton JH, and Manasseh R (1995) Recirculation in the lee of complicated headlands; a case study of Bass Point. Journal of Geophysical Research 100: 16087--16101.
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Farmer D and Armi L (1999) Stratified flow over topography; the role of small-scale entrainment and mixing in flow establishment. Proceedings of the Royal Society of London A455: 3221--3258. Farrell BF and Ioannou PJ (1996) Generalized stability theory. Part I: Autonomous operators. Journal of the Atmospheric Sciences 53: 2025--2040. Huppert HE (1975) Some remarks on the initiation of internal Taylor columns. Journal of Fluid Mechanics 67: 397--412. Johannes RE (1981) Words of the Lagoon: Fishing and Marine Lore of the Palau District of Micronesia. San Diego: University of California Press. Kundu PK (1990) Fluid Mechanics. London: Academic Press. Middleton JH, Griffin DA, and Moore AM (1993) Ocean circulation and turbulence in the coastal zone. Continental Shelf Research13143--13168.
Pattiaratchi C, James A, and Collins M (1986) Island wakes; a comparison between remotely sensed data and laboratory experiments. Journal of Geophysical Research 92: 783--794. Rissik D, Taggart C, and Suthers IM (1997) Enhanced particle abundance in the lee of an isolated reef in the south Coral Sea; the role of flow disturbance. Journal of Plankton Research 19: 1347--1368. Robinson IS (1975) Tidally induced residual flows. In: Johns B (ed.) Physical Oceanography of Coastal and Shelf Seas. Amsterdam: Elsevier. Tennekes H and Lumley JL (1972) A First Course in Turbulence. Cambridge, MA: MIT Press. Tomczak M (1988) Island wakes in deep and shallow water. Journal of Geophysical Research 93: 5153--5154.
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TOWED VEHICLES I. Helmond, CSIRO Marine Research, TAS, Australia Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 2994–3003, & 2001, Elsevier Ltd.
Introduction As a platform for marine instruments the towed vehicle (often termed a ‘towfish’ or ‘towed body’) combines the advantages of a ship-mounted instrument that gathers surface data while under way, and an instrument lowered from a stationary ship to gather data at depth. This article discusses the types of vehicles, the significance of the hydrodynamic drag of the tow cable and methods to reduce it. It also outlines the basic hydrodynamics of towed vehicles and presents the results of a model of the vehicle/cable system, indicating depths and cable tensions for a typical system.
•
Types of Towed Vehicles A towed vehicle system has three main components: the vehicle, the tow cable and a winch. The vehicles fall into two broad categories: those with active depth control and those without. Vehicles With Active Depth Control
Depth-controlled towed vehicles (or ‘undulators’) can move vertically in the water column while being towed horizontally by the ship. The main advantage they have over the lowered instrument is that they can quickly and conveniently measure vertical profiles of ocean properties with high horizontal spatial resolution. The main disadvantage is that it is difficult to reach depths greater than 1000 m while being towed at useful speeds; most available systems are limited to 500 m at best. The reason for the depth limitation is that the hydrodynamic drag of the tow cable must be overcome by a downward force on the vehicle, produced either by weight or a downward hydrodynamic force from hydrofoils or wings. However the cable’s strength limits the allowable size of these forces. The following are the common types of depthcontrolled vehicles.
•
A vehicle with controllable wings towed with an electromechanical cable that connects it to a
•
controlling computer on board the vessel. The electromechanical cable allows the data to be transmitted to the ship and displayed and processed in real time. This can be an advantage when following a feature such as an ocean front; the ship’s course can be adjusted to optimize the data collection. It also has the advantage of enabling fast, real-time response, an important consideration for bottom avoidance when operating in shallow water. As with most towed vehicles, cable drag dominates performance, so cable fairing is commonly used to reduce drag. Examples of this type of towed vehicle are the Batfish (Guildline Instruments, Canada), SeaSoar (Chelsea Instruments, UK) and the Scanfish (MacArtney A/S, Denmark). A vehicle with controllable wings that is totally self-contained. It is preprogrammed for maximum and minimum depths and records the data internally. As such a vehicle can be towed on a simple wire rope, it is convenient to use on ships not equipped for research. The lack of real-time control and data can be a disadvantage. An example of this type is the Aquashuttle (Chelsea Instruments, UK). A passive vehicle, often with fixed wings, where changes in depth are made by winching the tow cable in and out. This necessitates a high-speed, computer-controlled winch to produce the depth variation, but the vehicle can be simple. A recent development of this type is the Moving Vessel Profiler (Brooke Ocean Technology Ltd, Canada). This system has a winch that spools out the cable fast enough to allow the vehicle to free fall while the ship is under way, and then retrieves it after it has reached its maximum depth, which may be as deep as 800 m. Because the profiler free-falls on a slack cable, the usual cable drag constraints are not as relevant. This allows good depths to be achieved without the complication of cable fairing.
Vehicles Without Active Depth Control
The vehicle without active depth control produces the depressing force by means of its weight, fixed wings or both. It maintains a constant depth for a given tow-cable length and tow speed. The vehicle can be towed with either an electromechanical cable to provide real-time data to the ship (as used for underwater survey instruments such as the side-scan sonar) or with a wire rope (as often used for plankton recorders).
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TOWED VEHICLES
Tow cables are either wire rope or double-armored electromechanical cables. In the latter, two layers of armor provide mechanical strength, and because the layers are wound in opposite directions they are approximately torque balanced, i.e., the cable has little tendency to rotate when loaded. The electrical conductors handle data and power and optical fibers are used for high data rates. Except for systems with short cables used for shallow operations the tow cable is usually the dominant part of a towed vehicle system. Even a modest cable of 8 mm diameter and 500 m length has a mass of about 150 kg and a longitudinal cross-sectional area of 4 m2. This large cross-sectional area means that the cable drag dominates the performance of the system. Drag Caused by Flow Normal to the Cable
The normal drag on a moving body in a fluid is given by DN ¼ CDN 12ru2N A For a cable, the cross-sectional area A is the product of the cable’s diameter (d) and length (l) (see list of symbols at end of article). This drag is the sum of drag due to the shape of the body (the form or pressure drag) and drag due to surface friction (additionally a shape that produces lift also generates induced drag). The value of the drag coefficient CDN depends on the Reynolds number Re (the ratio of inertial to viscous forces), which is defined as Re ¼ ud=v. For a long smooth cylinder with normal flow at Reynolds numbers less than about 3 105 the flow is laminar and CDN E 1:2. At higher Reynolds numbers, the flow becomes turbulent and CDN drops to about 0.35. This change in drag coefficient is due to the large area of separated flow in the wake of the cylinder in laminar flow decreasing when the flow becomes turbulent. For most cables used for towed vehicles, the value of the Reynolds number is less than 105. To exceed this value a 10 mm-diameter cable moving through water requires a normal velocity greater than 10 m s1. For cables with a rough surface, such as the usual stranded cable, CDN E 1:5 when 103oReo105 (Figure 1). There is a mechanism that increases the drag coefficient of a cable above the value of a rigid cylinder. This is vortex-induced oscillation, commonly referred to as ‘strumming’. Vortices shed from the region of flow separation alter the local pressure distribution and the cable experiences a time-varying force at the frequency of the vortex shedding. This frequency, f , is a function of the normal flow velocity uN and the
Drag coefficient (CD)
Tow Cable Drag
10 5 2 1 0.5 0.2 0.1 0.05 0.02 0.01 0.005 0.002 0.001
CDN
Cable Smooth cylinder
CDT
1
10
2
3
4
10 10 10 Reynolds number (Re)
5
10
6
10
Figure 1 Normal and tangential drag coefficients for a typical cable.
cable diameter d. The Strouhal number Sn is defined as Sn ¼ fd=uN , and Sn E 0:2 over the range of Reynolds numbers 102 oRe o105 . If this frequency is close to a natural frequency of the cable, an amplified oscillation occurs. A tow cable has many natural frequencies and there are many modes excited by vortex shedding; the result is a continuous oscillation of the cable. These vortex-induced oscillations, which can have an amplitude of up to three cable diameters, increase cable fatigue and drag. The increase in drag can be as much as 200%, resulting in drag coefficients as high as 3. Values around 2 are common. The values of the drag coefficient for towed cables cited in the literature differ widely because each case has its own set of conditions: cable curvature, tension, Reynolds number and surface roughness vary from case to case. A good starting point for estimating the normal cable drag is CDN E 1:5 for cables that are not strumming and CDN E 2 for strumming cables. For the towed vehicle to be able to dive, the normal cable drag force must be overcome by downward or depressing forces: the cable weight, the towed vehicle weight and the hydrodynamic forces produced by the vehicle. The normal drag does not contribute directly to cable tension but by influencing the angle of the cable in the water it determines the component of cable weight that contributes to tension. Drag Caused by Flow Tangential to the Cable
The tangential drag on a long cylinder is due to surface friction. It is given by: DT ¼ CDT 12ru2T pA For tow cables with Reynolds numbers greater than about 103, a typical value for the tangential
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TOWED VEHICLES
drag coefficient (CDT) E 0.005 (Figure 1). With a towed vehicle system, the tangential drag contributes significantly to cable tension but has little influence on the depth achieved.
Reduction of Cable Drag Normal cable drag can be reduced by an attachment that gives the cable a streamlined or ‘fair’ shape. Alternatively the attachment can be designed to split the wake, so that the shed vortices cannot become correlated over a significant length of cable and strumming is prevented. These attachments are usually called ‘fairing’. Rigid Airfoil-shaped Fairing
‘Wrap-round’ fairing is the most effective method of reducing normal drag. An example is shown in Figure 2. A good airfoil shape can have a normal drag coefficient of 0.05, but the practicalities of having a rigid moulded plastic shape that can wrap around a cable, be passed over sheaves and spooled onto a winch often results in a drag coefficient of about 0.2. The greater drag is primarily due to the circular nose of the fairing (to accommodate the cable) and gaps between fairing sections. Because of the large surface area of the fairing, the tangential drag coefficient (based on cable surface area) is about 0.05. This means that, although the normal drag coefficient of a faired cable is only a tenth of a bare cable, the tangential drag coefficient is about ten times greater. A consequence of this is large cable tensions. For a typical system with 500 m of faired cable, at least 50% of the cable tension can be due to the fairing.
Cable
Another consequence of the high tangential drag is that this loading must be transferred from the fairing sections to the cable. Every 2–3 m, a ‘stop ring’ is swaged or clamped to the cable to take the load. If this force accumulates over too great a length the fairing sections will not rotate freely, and in the extreme they can break under the high compressive load. Another form of rigid fairing is the ‘clip-on’ fairing (see Figure 2). Unlike the ‘wrap-round’ type this does not totally enclose the cable, but is essentially an after-body attached to the cable with clips. Because of the gap between the cable and the fairing the drag coefficient is higher. Typical values are CDN E 0.4. A problem that can occur with rigid fairing is the phenomenon of ‘tow-off’. If the fairing sections are not free to align accurately with the flow, they can generate a considerable lift force, which can cause the cable to tow off to the side and decrease the depth it achieves. Although the rigid airfoil fairing is the most effective method of decreasing drag, it comes at a high cost. Not only is it expensive but it also requires special winches and handling gear. However, if a system is set up well it gives reliable performance. Flexible Ribbon and ‘Hair’ Fairing
Ribbon fairing is made of a flexible material in the form of trailing ribbons (Figure 2). Fibers or ‘hairs’ attached to the cable are also effective. These fairing devices do not usually produce a fair shape, but achieve their effect by splitting the wake. Their main effect is, therefore, to reduce strumming and reduce the normal drag coefficient to the bare cable value of
Fixed to cable
Fairing
Stop ring
Stop ring
(A)
(B)
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(C)
Figure 2 (A) ‘Wrap-round’ fairing; (B) ‘clip-on’ fairing; (C) ‘ribbon’ fairing; (D) ‘hair’ fairing.
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(D)
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TOWED VEHICLES
about 1.5. In some cases ribbon fairing can streamline the cable, reducing the normal drag coefficient to about 0.7 (due to the reduction of form drag). Hair fairing reduces strumming but can increase the normal drag coefficient so that CDN E2. These devices increase the surface area over a bare cable so the tangential drag is increased, resulting in greater cable tensions. Flexible fairing does not need special handling gear and can be wound onto a regular winch. However, the fairing deteriorates rather quickly requiring regular repair and replacement.
L
Chord line Angle of attack
D
AC M
u
Mean camber line
Figure 4 Forces and moment on an airfoil.
M ¼ CM 12ru2 Sc
Basic Aerodynamics of the Towed Vehicle Vehicles that Generate Lift
Most towed vehicles use wings (hydrofoils) to generate the force required to pull the tow cable down. Figure 3 shows an example of a winged vehicle. As shown in Figure 4, a wing moving through a fluid experiences a force perpendicular to the direction of flow (the lift), a force directly opposing the motion (the drag), and a moment tending to rotate the wing (the pitching moment). The pitching moment is usually referenced about a point termed the aerodynamic center, chosen so that the moment coefficient is constant with angle of attack. The lift force is given by: L ¼ CL 12ru2 S The drag force is given by: D ¼ CD 12ru2 S
The lift coefficient CL is proportional to the angle of attack. The theoretical relationship for a thin, symmetrical airfoil gives the slope of the curve of lift coefficient against angle of attack dCL =da ¼ a0 ¼ 2p=radian ¼ 0:11=degree The theoretical aerodynamic center is at the quarter chord point ðc=4Þ and CM ¼ 0. If the angle of attack is increased beyond a certain value the flow separates from the low-pressure side of the wing rapidly causing the lift to decrease and the drag to increase. This is termed ‘stall’ (Figure 5). An asymmetrical or cambered airfoil, where the camber line (the line drawn halfway between the upper and lower surfaces) deviates from the chord line (Figure 4), has the same theoretical slope of the lift curve, 2p, but has a nonzero value of the lift coefficient when a ¼ 0. The aerodynamic center is also at the quarter chord point but CMa0 (Figure 6).
The pitching moment is given by:
Lift coefficient (CL)
1.0 _ 0.1
0.5
_ 0.5
CM
_ 1.0
_ 0.1
Moment coefficient (C M)
CL
1.5
_ 1.5 _ 15 _ 10 _ 5
5
10
15
Angle of attack
Figure 3 CSIRO (Australia) modified SeaSoar with a Sea-Bird Electronics Inc. conductivity, temperature and depth (CTD) instrument.
Figure 5 Typical section characteristics for symmetrical airfoil type NACA0012.
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TOWED VEHICLES
Lift coefficient (CL)
1.0 0.5
_ 0.5
CM
_ 1.0
_ 0.1 _ 0.2
Moment coefficient (C M)
CL
1.5
_ 0.3
_ 1.5 _ 15 _ 10 _ 5
5
10
15
Angle of attack
Figure 6 Typical section characteristics for asymmetrical airfoil type NACA4412.
These properties describe airfoil sections that are two-dimensional. In a real wing, the span is finite and there is spanwise flow. The effect of this is a ‘leakage’ around the wing tips from the high-pressure side to the low-pressure side. This generates wing-tip vortices, which in turn produce a downward flow around the wing – the downwash. The angle of this local flow relative to the wing subtracts from the angle of attack so that the wing actually experiences a smaller effective angle of attack. Since the lift vector is normal to the local relative flow it becomes inclined behind the vertical and so has a rearward component – the induced drag. This drag can be the dominant drag on a towed vehicle. The induced drag coefficient is given by: CDi ¼ C2L =ðpARÞ The reduction in the effective angle of attack of a wing with finite span also reduces the slope of the lift curve, a. dCL =da ¼ a ¼ a0 =ð1 þ a0 =pARÞ The reduced slope of the lift curve means that the wing has a higher angle of attack at stall. To achieve the necessary mechanical strength, the aspect ratio of wings used on towed vehicles is usually very low. This results in high induced drag and low values of the lift curve slope. It will be shown later that the higher induced drag is not significant. The lower sensitivity to changes in the angle of attack (and the higher angle at stall) can be an advantage: it makes the vehicle more tolerant of flight
69
perturbations such as those experienced when towing in rough seas. The delta wing (a wing with a triangular planform) is a popular form for vehicles without active depth control. Flow over a delta wing is dominated by large leading-edge vortices and cross-flow that enable the wing to operate at large angles of attack without stalling. A delta wing has a typical lift curve slope of about 0.05/degree (about half that of a conventional wing), but can operate with an angle of attack up to 301 before stalling. Delta wings make robust depressors and are often given large dihedral angles to increase roll stability. The dihedral is the angle of inclination of the wings in relation to the lateral axis. To control the depth of a towed vehicle, the magnitude and direction of the wing’s lift force are usually varied by:
•
the use of control surfaces (flaps) on the trailing edge;
• •
an independent control surface, usually at the tail; rotating the entire wing about its aerodynamic center to vary its angle of attack.
The first two methods cause the whole vehicle to adopt an angle of attack and so the body of the vehicle also generates lift. Some towed vehicles, such as the Aquashuttle (Chelsea Instruments, UK), operate without wings, generating all the lift from the body. Others, such as the Scanfish (MacArtney A/S, Denmark) and the V-Fin (Endeco Inc, USA), are effectively flying wings. The third method, used by the Batfish (Guildline Instruments, Canada) and SeaSoar (Chelsea Instruments, UK), maintains the body aligned with the flow, which is an advantage for some types of sensors that need to be aligned to the flow. Both these vehicles use a highly cambered wing section (NACA6412) that has a large moment coefficient ðCM E 0:13Þ. Thus a large torque is needed to rotate the wing. If a small operating torque is required the wings are typically controlled by an electric servomotor. If large forces are needed a hydraulic system is used. A symmetrical wing section pivoted at the quarter chord point requires only a small torque, but the control system needs to be robust enough to survive rough handling on the ship’s deck. To gain the maximum benefit of any lift force, the vehicle must fly so that the force is directed near to vertical, that is it should fly without a significant roll angle. A towed vehicle often needs to be able to direct its lift force both down and up, to maximize its depth range. A consequence of this is that dihedral, a
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TOWED VEHICLES T
1
D
AC
servomotor systems. The other basic requirement is for pitch and yaw stability. This is achieved by ensuring that the tow point is ahead of the aerodynamic center (AC) of the vehicle (Figure 7). The position of the vehicle’s aerodynamic center is controlled by providing a suitably sized tailfin.
Center of gravity
Vehicles That do not Generate Lift
W
L
Figure 7 Basic forces on a towed vehicle.
common method of providing roll stability, cannot be used. What would be stable for lift in one direction would be unstable in the other. By having the tow cable attachment point above the center of gravity of the vehicle, the vehicle’s weight contributes to roll stability (Figure 7). But to stabilize the large lift forces needed for good depth performance, additional aerodynamic control by means of ailerons or similar devices is needed. These can be simple systems driven directly with gravity by using a heavy pendulum device or more sophisticated electric
These passive towed vehicles use their weight to produce the required downward force. The drag of the cable is overcome by the combined weight of cable and vehicle. Depth is controlled by varying the cable length. The depth is also very dependent on the tow speed. This is because the cable drag is proportional to the square of the tow speed and the depressing force is fixed by the cable and vehicle weight. This contrasts with the vehicle that generates lift; its depth is less speed-dependent because both lift and drag vary with speed in the same manner. A heavy passive vehicle can have good pitch and roll stability if the position of the tow point, center of mass, center of gravity and the aerodynamic center are carefully chosen. The lack of flow separation over lifting surfaces also makes them acoustically quiet. This stability and quietness make them useful vehicles for underwater acoustic work (Figure 8).
Figure 8 The CSIRO (Australia) multifrequency towed vehicle used for fish stock measurements. Note the ribbon-faired cable.
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TOWED VEHICLES
71
shown in Figure 7 the angle of the cable at the vehicle, f1 is determined by the weight ðWÞ, lift ðLÞ and drag ðDÞ of the vehicle.
0
DN
tan f1 ¼ ðW þ LÞ=D D u DT w Figure 9 Forces on the tow cable.
Performance of the Vehicle/Cable System When a cable is towed through water, it assumes an equilibrium angle where the drag force (D) is balanced by the cable weight (w). If the cable properties are uniform, this angle is constant along the cable length By referring to Figure 9
Effects of Wave-induced Ship Motion on the Towed Vehicle
tan f0 ¼ w=D Or expressed in terms of the normal drag coefficient cos f0 ¼ 17 1 þ 4B2
The cable profile starts at an angle of f1 at the vehicle and gradually approaches f0 up the cable. The vehicle drag is the sum of the form drag, the friction drag and the induced drag. With vehicles that generate lift the induced drag is the main component. Even with a poorly streamlined vehicle it dominates, providing perhaps 75% of the drag. The rather poor performance of the typical low aspect ratio wing used on towed vehicles gives the vehicle a lift to drag ratio of about 3. This makes the cable angle f1 E 701. Further improvement in the lift to drag ratio does not gain much in cable angle or depth. Table 1 compares the equilibrium depths for bare and faired cables; Table 2 compares the performance of bare and faired cable when towing a vehicle with controllable wings. These data were produced by a computer model of the vehicle/cable system.
1=2
=2B
where B ¼ ru2 dCDN =ð2wÞ The equilibrium depth is ðl sin f0 Þ. When a vehicle is attached to the end of the cable it perturbs this equilibrium depth by the extent that its weight and lift force either drag the cable deeper when diving, or lift the cable when climbing. This defines the depth range of the vehicle/cable system (Figure 10). As
Equilibrium depth
A problem with towing in rough seas is that the wave-induced motion of the towing vessel is propagated down the tow cable to the vehicle. Motion normal to the cable is rapidly damped, but there is surprisingly little attenuation of the tangential motion of the cable. The amplitude of the perturbation of the vehicle is approximately the same as the cable at the ship. This causes changes in the vehicle’s pitch angle and depth which can be very significant for towed acoustic systems and vehicles such as camera units operating very close to the seafloor.
0
Depth range
1
Figure 10 Towed cable profile.
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Table 1 Comparison of equilibrium depths for 500 m of 8.2 mm diameter cable with a weight of 2.5 N m1 towed at 4 m s1 for faired and bare cable
Faired CDN ¼ 0.2 Bare CDN ¼ 2.0
Equilibrium depth (m)
Tension (kN)
f0 (degrees)
142 61
3.6 0.7
17 7
The following methods are used to minimize the effects of ship motion.
• • •
•
•
The vehicle can be tuned to minimize the pitching effect by carefully adjusting the position of the vehicle’s aerodynamic center and center of mass in relation to the tow point. A constant-tension winch reduces the cable displacement at the ship by spooling cable in and out as the ship surges. A device called an accumulator produces an effect similar to the constant-tension winch. The cable runs over a pair of sheaves that are mounted on a sprung or pneumatic arrangement that allows them to take up and pay out cable as needed. In the ‘two-body system’ the instrumented vehicle is passive and near-neutrally buoyant. It is towed behind the depressor or depth-controlled vehicle on a cable that is approximately horizontal. This geometry decouples ship’s motion from the second vehicle. A system that has a cable angle close to horizontal at the ship is insensitive to ship pitch and heave as these displacements are almost normal to the cable. A system that uses a long cable, a cable without fairing or a high tow speed has this characteristic.
Flight Control Tow speeds vary from as low as 1 ms1 for seafloor survey instruments to 10 ms1 for high-speed systems. The fast systems are limited to shallow depths.
Speeds of 3–5 ms1 are common for oceanographic surveys and depths of up to 1000 m can be achieved. Depth-controlled vehicles operate with vertical velocities up to about 1 m s1. Depth-controlled vehicles are commonly operated in an undulating mode with maximum and minimum depths set to specific values to give a triangular flight path. The depth is measured by the water pressure at the vehicle and the wings or control surfaces are adjusted to make the vehicle follow the defined path by a servo system. The servo-loop parameters are usually controlled by the shipboard computer; however the actual servo-loop system may reside in the towed vehicle or combine ship- and vehicle-based components. The control algorithm needs to be carefully tuned to achieve smooth flight.
Sensors Some of the earliest towed vehicles were used to collect plankton (in fact a trawl net is a form of towed vehicle). These plankton collectors are often separate nets and depressors but can also be single units. An early system, the Hardy Continuous Plankton Recorder, dates from the 1930s. Several commercially available vehicles are a development of this type, for example the Aquashuttle (Chelsea Instruments, UK) and the U-Tow (Valeport Ltd, UK). Depth-controlled vehicles are commonly equipped with a conductivity, temperature and depth (CTD) instrument. They are also suitable platforms for
Table 2 Comparison of depths, cable tensions and cable angles (f2 cable angle at ship, f1 cable angle at vehicle) for the same cable as Table 1 towing a typical vehicle with the following characteristics: weight in water, 1500 N; cross–sectional area, 0.2 m2; wing area, 0.5 m2; wing aspect ratio, 1; tow speed, 4 m s1. Positive lift coefficients indicate lift force upwards
Faired CDN ¼ 0.2 Bare CDN ¼ 2.0
Wing CL
Depth (m)
Tension (kN)
f2 (degrees)
f1 (degrees)
1.0 þ 0.5 1.0 þ 0.5 þ 1.0
360 0 140 31 0
11.2 4.3 6.5 1.6 3.2
36 7 8 7 6
72 36 72 36 55
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TOWED VEHICLES
Depth (m)
many other types of sensors, such as fluorometers, radiometers, nutrient analysers and transmissometers. In the case of a CTD it is recommended that the sensors be duplicated. When a CTD is lowered from a stationary ship in the usual manner the calibration of the conductivity sensor is checked by collecting water samples for laboratory analysis. This option is not usually available on a towed instrument so a check of sensor stability can be obtained by using dual sensors. The conductivity cells
100
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can also be blocked by marine organisms especially when towing near the surface. Dual cells allow recognition of this problem. Figure 11 shows the data from a CTD section across an ocean front demonstrating the high spatial resolution realized with a towed system. Passive towed vehicles are often used for acoustic survey work. Examples are side-scan sonars, towed multibeam systems for seafloor mapping, and vehicles for estimating fish stocks. The towed vehicle
12
14 13
11
12
11
200
10
300
Salinity
Depth (m)
35.5 100
35.6
34.8
35.0
35.1
35.4 35.0
200
34.8 34.9
34.8
35.5 300
Density (sigma-t)
Depth (m)
26.55
26.60
100 26.50
26.55
26.70
26.70 26.75
200
26.80 300 0
50
100
150 200 Distance (km)
250
300
Figure 11 An example of a conductivity, temperature and depth (CTD) section across the Sub-Tropical Front south of Australia using a SeaSoar towed vehicle equipped with a Seabird CTD instrument. (From Tomczak M and Pender L (1999) Density compensation in the Sub-Tropical Front in the Indian Ocean South of Australia.http://www.es.flinders.edu.au/ Bmattom/STF/ fr1098.html.
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TOWED VEHICLES
D DN DT L M Re S Sn T W a a0 Figure 12 A faired cable winch and SeaSoar towed vehicle. This winch holds 5000 m of cable, 400 m faired and 4600 m of bare cable. A combination of faired and bare cable can be a costeffective method of achieving greater depths.
offers advantages over hull-mounted transducers by deploying the acoustic transducer away from the high noise environment and bubble layer near the ship and closer to the object of interest. A well-designed system can also be a more stable platform for the acoustic transducers than a ship in rough seas.
The Winch Towed-vehicle systems using electromechanical cables usually require a special, purpose-built winch with accurate spooling gear and slip-rings to make the electrical connection to the rotating drum. Cable lengths can vary from 100 m to 5000 m. If a cable with rigid fairing is used special blocks and fairing guiding devices are needed to handle the cable. The faired cable has a large bending radius and can only be wound onto the winch drum in a single layer. As illustrated in Figure 12, this type of winch is quite large. If the towed vehicle system uses wire rope for the tow cable, then the winch can be a standard type.
b c cg d f l u uN uT w a f f0 f1 f2 m n r
Drag force Normal drag force Tangential drag force Lift force Pitching moment Reynolds number ¼ ud/v Wing planform area Strouhal number ¼ fd/u Cable tension Tow vehicle weight Slope of the lift curve for a wing ¼ dCL/da Slope of the lift curve for an airfoil section ¼ dCL/da Wing span Chord length Center of gravity Cable diameter Frequency Cable length Velocity Normal velocity Tangential velocity Cable weight per unit length Angle of attack Angle of the cable to the horizontal Cable equilibrium angle Cable angle at the towed vehicle Cable angle at the ship Dynamic viscosity (E1 10 3 kg m 1 s for water) Kinematic viscosity ¼ m/r (E1 10 6m2s 1 for water) Density (E1000 kg m 3 for water)
See also Acoustic Scattering by Marine Organisms. Platforms: Autonomous Underwater Vehicles. Ships. Sonar Systems.
Symbols used A AC AR CDi CDN CDT CL CM
Area Aerodynamic center Wing aspect ratio ¼ b2/S Induced drag coefficient Normal drag coefficient Tangential drag coefficient Lift coefficient Moment coefficient
Further Reading Abbott IH and von Doenhoff AE (1959) Theory of Wing Sections. New York: Dover Publications. Anderson JD (1991) Fundamentals of Aerodynamics, 2nd edn. New York: McGraw-Hill. Wingham PJ (1983) Comparative steady state deep towing performance of bare and faired cable systems. Ocean Engineering 10(1): 1--32.
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TRACE ELEMENT NUTRIENTS W. G. Sunda, National Ocean Service, NOAA, Beaufort, NC, USA Published by Elsevier Ltd.
Introduction Life in the sea is dependent on fixation of carbon and nitrogen by unicellular algae, ranging in size from o1 to over 100 mm in diameter. These so-called phytoplankton consist of eukaryotic algae, which photosyntheticly fix carbon into organic matter, and photosynthetic bacteria (cyanobacteria) that carry out both carbon and dinitrogen (N2) fixation. Until recently, phytoplankton productivity in the ocean was thought to be primarily limited by available fixed nitrogen (nitrate, nitrite, ammonia, and various organic nitrogen compounds) and to a lesser extent phosphorus (orthophosphate and organic phosphorus compounds). However, in the past 20 years, enrichment experiments in bottles and in mesoscale patches of surface water have shown that iron regulates the productivity and species composition of planktonic communities in major regions of the world ocean, including the Southern Ocean, the equatorial and subarctic Pacific, and some coastal upwelling systems. In addition, it now appears that
iron limits N2 fixation by cyanobacteria in large regions of the subtropical and tropical ocean, and thus may control oceanic inventories of biologically available fixed nitrogen. Several other micronutrient metals (zinc, cobalt, manganese, and copper) have also been shown to stimulate phytoplankton growth in ocean waters, but their effect is usually much less than that of iron. However, these metals may play an important role in regulating the composition of phytoplankton communities because of large differences in trace metal requirements among species. In this article interactions between trace element nutrients (iron, zinc, cobalt, manganese, copper, nickel, cadmium, molybdenum, and selenium) and phytoplankton in seawater are discussed. In these interactions, not only do the trace nutrients affect the growth and species composition of phytoplankton communities, but the phytoplankton and other biota (e.g., heterotrophic bacteria and zooplankton) have a profound influence on the distributions, chemistry, and biological availability of these elements (Figure 1). There are many aspects to consider, including (1) the sources, sinks, and cycling of trace element nutrients in the ocean; (2) the distribution of these elements in time and space, and their chemical speciation (or forms); (3) the interactions of these elements with phytoplankton at different levels of biological organization (molecular, cellular, population, community,
Marine plankton - Growth rates - Biomass - Species composition Trace element chemistry - Concentrations - Speciation - Redox cycling
Figure 1 Conceptual diagram of the mutual interactions between trace element nutrients (Fe, Mn, Zn, Co, Cu, Cd, and Se) and phytoplankton in the sea. In these interactions, the chemistry of trace element nutrients, in terms of their concentrations, chemical speciation, and redox cycling, regulates the productivity and species composition of marine phytoplankton communities. These communities in turn regulate the chemistry and cycling of trace element nutrients through cellular uptake and assimilation, vertical transport of biogenic particles (intact cells and fecal pellets), grazer and bacterially mediated regeneration processes, production of organic chelators, and biological mediation of trace element redox transformations.
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ecosystem); and (4) the role of planktonic communities in regulating the chemistry and cycling of these nutrient elements in seawater.
Distribution in Seawater Knowledge of the distributions of trace element nutrients is essential to understanding the influence of these micronutrients on the productivity and species diversity of marine planktonic communities. Concentrations of filterable iron and zinc (that portion passing through a 0.2- or 0.4-mm-pore filter) typically are extremely low (only 0.02 to 0.1 nM) in surface waters of the open ocean. Cadmium, a nutrient analog for zinc, can reach values as low as 0.002 nM (Table 1). Concentrations of these and other trace element nutrients often increase by orders of magnitude in transects from the open ocean to coastal and estuarine waters due to inputs from continental sources, such as rivers, groundwater, eolian dust, and coastal sediments. Filterable iron can reach micromolar concentrations in estuaries and can approach 10–20 mM in rivers, 5 or 6 orders of magnitude higher than surface ocean values. This filterable iron occurs largely as colloidal particles (o0.4-mm diameter) consisting of iron oxides in association with organic matter. These are rapidly lost from estuarine and coastal waters via salt-induced coagulation and particulate settling. Because of this efficient removal, very little of the iron in rivers reaches the open sea, and most of the iron in ocean waters is derived from the deposition of mineral dust blown on the wind from arid regions of the continents. These eolian inputs change seasonally with variations in prevailing winds and are highest in
Table 1
Micronutrient elements and their abundance in ocean water and phytoplankton
Micronutrient element
Iron Manganese Zinc Cobalt Cadmium Copper Nickel Molybdenum Selenium
a
waters downwind of arid regions such as North Africa and Central Asia. Areas far removed from these eolian sources, such as the South Pacific and the Southern Ocean, receive little atmospheric iron deposition and are among the most iron-limited regions of the oceans. Because of the large gradients in trace metal concentrations between the open ocean and coastal waters, oceanic phytoplankton species have evolved the ability to grow at much lower available concentrations of iron, zinc, and manganese. In doing so they have been forced to rearrange their metabolic architecture (e.g., in the case of iron-rich protein complexes involved in photosynthesis) or to switch from scarce elements to more abundant ones in some critical metalloenzymes (e.g., Ni and Mn replacement of Fe in the antioxidant enzyme superoxide dismutase). Concentrations of many trace element nutrients (zinc, cadmium, iron, copper, nickel, and selenium) increase with depth in the ocean, similar to increases observed for major nutrients (nitrate, phosphate, and silicic acid) (Figures 2–4). In the central North Pacific, filterable concentrations of zinc and cadmium increase by 80-fold and 400-fold, respectively, between the surface and 1000-m depth. The similarity between vertical distributions of these trace elements and major nutrients indicates that both sets of nutrients are subject to similar biological uptake and regeneration processes. In these processes, both major and trace element nutrients are efficiently removed from surface waters through uptake by phytoplankton. Much of these assimilated nutrients are recycled within the euphotic zone by the coupled processes of zooplankton grazing and excretion, viral lysis of cells, and bacterial degradation of organic
Major input source
Wind-born dust Rivers Wind-born dust Rivers Rivers Rivers Rivers Rivers Rivers
Major dissolved chemical species
Organic chelates Mn2þ Organic chelates Organic chelates Organic chelates Organic chelates Ni2þ MoO4 2 Organic selenides, SeO4 2
Dissolved concentrationa (nM) Surface water
Deep water (Z0.8 km)
0.02–0.5 0.1–5 0.05–0.2 0.007–0.03 0.002–0.3 0.5–1.4 2–3 100–110 0.5–1.0
0.4–1 0.08–0.5 2–10 0.01–0.05 0.3–1.0 1.5–5 5–11 100–110 1.5–2.3
Dissolved is defined operationally as that passing through a 0.2- or 0.4-mm-pore filter.
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Element:carbon ratio in phytoplankton (mmol:mol)
3–40 2–30 1–40 0.1–3 0.2–8 2–6 2–17 0.05–0.8 1–2
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Nitrate (µmol kg −1)
(a) 0
0
10
20
30
40
(b) 50
0
0
Phosphate (µmol kg −1) 1
2
3
(c) 4
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Silicic acid ( µmol kg −1) 50
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Zinc (nmol kg−1) 2
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Cadmium (nmol kg−1)
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Depth (m)
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Atlantic
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Nickel (nmol kg−1) 2
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(g) 12
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Copper (nmol kg−1) 1
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Manganese (nmol kg−1)
(h) 5
0.0 0.5 1.0 1.5 2.0 2.5 3.0 0
0
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1000
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Figure 2 Depth profiles for major nutrients (nitrate (Pacific only), phosphate, and silicic acid) and filterable concentrations (that passing a 0.4-mm filter) of trace nutrient elements (zinc, cadmium, nickel, copper, and manganese) in the central North Pacific (diamonds, 32.71 N, 145.01 W, Sep. 1977) and North Atlantic (squares, 34.11 N, 66.11 W, Jul. 1979). Manganese concentrations in the Pacific were analyzed in acidified, unfiltered seawater samples. The units mol kg1 are defined as moles per kilogram of seawater. Data from Bruland KW and Franks RP (1983) Mn, Ni, Cu, Zn and Cd in the western North Atlantic. In: Wong CS, Boyle E, Bruland KW, Burton JD, and Goldberg ED (eds.) Trace Metals in Sea Water, pp. 395–414. New York: Plenum.
(a) 0
0
Nitrate (µmol kg −1) 10 20 30 40
(b) 50
0
0
Iron (nmol kg−1) 0.2 0.4 0.6
(c) 0.8
0
0
2
Zinc (nmol kg−1) 4 6 8 10
(d) 12
0
1000
1000
1000
2000
2000
2000
2000
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3000
Cobalt (pmol kg−1) 20 40
60
Depth (m)
1000
0
Figure 3 Depth profiles for nitrate and filterable concentrations of trace element nutrients (iron, zinc, and cobalt) in the subarctic North Pacific Ocean (ocean station Papa, 50.01 N, 145.01 W, Aug. 1987). Data from Martin JH, Gordon RM, Fitzwater S, and Broenkow WW (1989) VERTEX: Phytoplankton/iron studies in the Gulf of Alaska. Deep-Sea Research 36: 649–680.
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0.0 0
0.5
Selenium (nmol kg−1) 1.0 1.5
2.0
2.5 Selenate Selenite
200
Organic Se Total Se
Depth (m)
400
600
800
1000 Figure 4 Depth profiles for concentrations of total selenium and different chemical forms of selenium (selenate, selenite, and organic selenium compounds) in filtered seawater samples from the eastern tropical North Pacific Ocean (181 N, 1081 W; Oct.–Nov. 1981). Data are from Cutter GA and Bruland KW (1984) The marine biogeochemistry of selenium: A reevaluation. Limnology and Oceanography 29: 1179–1192.
materials. However, a portion of the assimilated nutrients is continuously lost from the euphotic zone by vertical settling of intact algal cells or zooplankton fecal pellets. The macro- and micronutrients contained within these settling biogenic particles are then returned to solution at depth in the ocean via bacterial degradation processes. Ultimately the uptake, settling, and regeneration processes deplete nutrients within the euphotic zone to low levels while concentrations at depth are increased. This process also transfers CO2 to the deep sea and is often refered to as the biological CO2 pump. The cycle is completed when the nutrient and CO2 reservoirs at depth are returned to the surface via vertical advection (upwelling) and mixing processes. The deep-water concentrations of both major nutrient elements (N, P, and Si) and many micronutrients (Zn, Cd, Ni, and Cu) are much higher in deep waters of the Pacific than the Atlantic (Figure 2) because of large-scale ocean circulation patterns, in which deep waters are formed via subduction at high latitudes in the North Atlantic and are returned to the surface via upwelling in the northern regions of the North Pacific and Indian Oceans. Because of these patterns, the deep North Pacific contains waters that have resided at the bottom for much
longer (B1000 years) than the deep Atlantic waters and thus have had a much longer time to accumulate major nutrient and micronutrient elements from biological regeneration processes. Several trace element nutrients (molybdenum, manganese, and cobalt) provide exceptions to the general trend of increasing concentrations with depth. Molybdenum occurs almost exclusively as soluble, nonreactive molybdate ions MoO4 2 , which occur at a high concentration (B105 nM) relative to their biological demand (Table 1). Consequently, there is minimal biological removal of molybdenum from surface seawater and its concentration varies in proportion to salinity. By contrast, concentrations of manganese (Figure 2(h)) and cobalt (Figure 3(d)) are typically maximum near the surface and depleted at depth owing to deep-water scavenging processes.
Chemical Speciation Trace element nutrients exist as a variety of chemical species in the sea, which strongly influences their chemical behavior and biological availability. All but Se and Mo occur as cationic metal ions that are complexed (bound) to varying degrees by inorganic
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TRACE ELEMENT NUTRIENTS
and organic ligands (complexing agents) or are adsorbed onto or bound within particles. Many trace element nutrients (iron, copper, manganese, cobalt, and selenium) cycle between different oxidation states, which have quite different kinetic labilities (reaction rates), solubilities, binding strengths with organic ligands, and biological availabilities. Nickel, zinc, and cadmium exist in normal oxygenated seawater as highly soluble divalent cations that are complexed to varying degrees by inorganic ligands (Cl, OH, and CO3 2 ) and organic chelators. Nickel is bound to only a small extent (0–30%) by organic ligands. By contrast, B99% of the zinc ions and 70% of the cadmium are heavily complexed by unidentified strong organic ligands present at low concentrations in surface waters of the North Pacific. The strong chelation of zinc reduces the concentration of dissolved inorganic zinc to B1 pM in surface seawater, sufficiently low to limit the growth of many algal species. Manganese undergoes redox transformations, but is minimally bound to organic ligands. The stable redox species of manganese in oxygenated seawater, Mn(IV) and Mn(III) oxides, are insoluble, although Mn(III) can exist in some instances as soluble organic chelates. Mn(III) and Mn(IV) can be reduced chemically, photochemically, or biologically to dissolved Mn(II), which is fully soluble in seawater and is not appreciably bound by organic ligands. Although Mn(II) is unstable with respect to oxidation by molecular oxygen, the chemical kinetics of this reaction are exceedingly slow in seawater. However, Mn(II) oxidation is greatly accelerated by bacterial enzymes that catalyze Mn(II) oxidation to Mn(IV) oxides. The bacterial formation of Mn oxides, and subsequent removal via coagulation and settling of oxide particles, results in short residence times (20–40 years in the North Pacific) and low concentrations for manganese in deep-ocean waters (Figure 2(h)). Oxidation is absent or greatly diminished in the ocean’s surface mixed layer due to photo-inhibition of the Mn-oxidizing bacteria. The absence of bacterially mediated oxidation of Mn(II) and minimal organic chelation often results in high concentrations of Mn2þ ions in surface seawater (Table 1; Figure 2(h)), enhancing the supply of Mn to phytoplankton. Iron is the most biologically important trace metal nutrient, and its chemical behavior is perhaps the most complex. Its stable oxidation state in oxygencontaining waters is Fe(III), which forms sparingly soluble iron hydroxide and oxide precipitates. This oxide formation and the tendency of ferric ions to adsorb onto particle surfaces results in the scavenging of iron from seawater via particulate aggregation and settling processes. This removal results in
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short residence times for iron in deep-ocean waters (B50–100 years) and low concentrations (0.4– 0.8 nM) despite the high crustal abundance of iron (it is the fourth most abundant element by weight). Most (499%) of the dissolved ferric iron in seawater is bound to organic ligands which minimizes iron adsorption and precipitation, and thus reduces the removal of iron from seawater by particulate scavenging processes. Some of these organic ligands may be strong ferric chelators (siderophores) produced by bacteria to solubilize iron and facilitate intracellular iron uptake. Ferric iron can be reduced in seawater to highly soluble Fe(II) (ferrous iron) by a number of processes including photo-reduction of organic chelates in surface waters, biological reduction of iron at cell surfaces, and reduction by chemical reducing agents. Because ferrous iron binds much more weakly to organic chelators than ferric iron, the photo-reduction or biological reduction of iron in ferric chelates often results in the dissociation of iron from the chelates, which increases iron availability for biological uptake (see below). The released ferrous ions are unstable in oxygenated seawater, and are reoxidized to soluble ferric hydrolysis species, and recomplexed by organic ligands on timescales of minutes. Thus iron undergoes a dynamic redox cycling in surface seawater, which can greatly enhance its biological availability to phytoplankton. Other micronutrient metals such as copper and cobalt also exist in multiple oxidation states and are heavily complexed by organic chelators. Copper can exist in seawater as thermodynamically stable copper(II), or as copper(I). Most (499%) of the copper in near-surface seawater is heavily chelated by strong organic ligands present at low concentrations (2– 3 nM in ocean waters). This chelation decreases free cupric (copper II) ion concentrations to very low levels (0.1–1 pM). Copper(II) can be reduced to Cu(I) by photochemical and biological processes or by reaction with chemical reducing agents, such as sulfurcontaining organic ligands. The resultant Cu(I) can be reoxidized by reaction with molecular oxygen, but the effect of this redox cycling on the biological availability of copper is currently unknown. The chemistry of cobalt is also highly complex. Cobalt exists in seawater as soluble cobalt(II) or as cobalt(III), which forms insoluble oxides at the pH of seawater. The formation of these oxides appears to be microbially mediated and is largely responsible for the removal of cobalt from deep-ocean waters and for the resultant low deep-ocean concentrations (Figure 3(d)). Much of the dissolved cobalt in seawater is strongly bound to organic ligands, and recent evidence suggests that this cobalt exists as
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kinetically inert cobalt(III) chelates. There is also evidence that these cobalt(III)-binding ligands are produced by marine cyanobacteria and that these ligands may facilitate microbial uptake of cobalt. Selenium is a metalloid, which occurs immediately below sulfur in the periodic table. Consequently, its chemical behavior often mimics that of sulfur. Selenium exists in subsurface seawater primarily as soluble oxyanions selenate (SeO4 2 ; þ 6 oxidation state) and selenite (SeO3 2 ; þ 4 oxidation state). Phytoplankton preferentially take up selenite which depletes its concentration in surface seawater (Figure 4). Selenate is then taken up and depleted following the removal of selenite. The selenate and selenite ions taken up by phytoplankton are metabolically reduced to the selenide ( 2 oxidation state) and used to synthesize selenomethionine and selenocysteine, chemical analogs of the sulfur-containing amino acids methionine and cysteine. In surface waters a majority of the selenium occurs as biologically regenerated organic selenide compounds of unknown chemical structure (Figure 4).
Biological Uptake All trace elements are taken up intracellularly by specialized transport proteins (enzymes) on the outer membrane of plankton cells. Consequently, uptake rates generally follow Michaelis–Menten enzyme kinetics: Uptake rate ¼ Vmax S=ðKs þ SÞ Vmax is the maximum uptake rate, S is the concentration of the pool of chemical species that react with receptor sites on the transport protein, and Ks is concentration of the substrate pool at which half of the transport protein is bound, and the uptake rate is half of Vmax. Virtually all of these proteins act as pumps and require energy for intracellular uptake. Each transport system reacts with a single chemical species or group of related chemical species and thus chemical speciation is extremely important in regulating cellular uptake. Uptake systems range from simple to highly complex depending on the chemical speciation of the nutrient element and its biological demand (requirement) relative to its external availability. Uptake systems appear to be simplest for dissolved Mn(II), which is taken up in phytoplankton by a single high-affinity transport system that is under negative feedback regulation. In this negative feedback, as the concentration of dissolved Mn(II) decreases, the Vmax of the transport system is increased
to maintain relatively constant Mn uptake rates and intracellular concentrations. Uptake systems for zinc, cadmium, cobalt(II), and copper(II) are somewhat more complex. The phytoplankton species examined to date have at least two separate zinc transport systems: a low-affinity system whose Vmax is relatively constant, and an inducible high-affinity system. The low-affinity system has high Vmax and high Ks values and transports zinc at high zinc ion concentrations. The high-affinity system is responsible for zinc uptake at low zinc ion concentrations, and has low Ks, and variable Vmax values that are under negative feedback regulation. At sufficiently low concentrations of dissolved inorganic zinc species (B10 pM), the cellular uptake approaches limiting rates for the diffusion of labile inorganic zinc species to the cell surface. The existence of high- and low-affinity transport systems results in sigmoidal relationships between zinc uptake rates (and cellular Zn:C ratios) and concentrations of dissolved inorganic zinc species as seen in Figure 5 for an oceanic diatom. Cobalt and sometimes cadmium can metabolically substitute for zinc in many metalloenzymes. To facilitate this substitution, the uptake of these divalent metals is increased by over 100-fold in diatoms with decreasing dissolved inorganic zinc concentrations and resulting decreases in cellular zinc uptake rates (Figure 5). Uptake of Cd by this inducible transport system is repressed at high intracellular zinc levels, and under these conditions, cadmium leaks into the cell through the cell’s Mn(II) transport system. Thus cellular uptake of cadmium in the ocean is regulated by complex interactions among dissolved inorganic concentrations of Cd, Zn, and Mn. Likewise, since cobalt uptake is repressed at high zinc ion concentrations, biological depletion of cobalt often does not occur until after zinc is depleted, as observed in the subarctic Pacific (Figure 6). The binding and subsequent intracellular uptake of the above divalent metals (Zn2þ, Mn2þ, Cd2þ, Co2þ, and Cu2þ) by the various intracellular uptake systems are regulated by the concentration of dissolved inorganic metal species (free aquated ions and inorganic complexes with chloride ions, hydroxide ions, etc.). Organic complexation of these metals reduces their uptake by decreasing the concentration of dissolved inorganic metal species. This effect can be substantial in cases such as zinc, where up to 99% or more of the metal is bound to organic ligands in surface seawater. Since iron is the most limiting of the trace element nutrients and its chemistry the most complex, it is perhaps not surprising that the transport systems for iron are the most varied and complex. Iron is highly
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Cellular metal uptake rate (µmol (mol C)−1d−1)
10
1
0.1
0.01
Zinc Cobalt Cadmium
0.001 −13.0
−12.0
−11.0
−10.0
−9.0
log [Zn′] Figure 5 Cellular uptake rates for zinc, cobalt, and cadmium (normalized per mol of cell carbon) for the oceanic diatom Thalassiosira oceanica plotted as a function of the log10 of the molar concentration of dissolved inorganic zinc species (Zn0 , aquated zinc ions plus inorganic zinc complexes). Dissolved inorganic cobalt and cadmium species in the seawater medium were held constant at concentrations of 1.5 and 2.7 pM (1012 M), respectively. Uptake rates for cadmium and cobalt increase by at least 2 orders of magnitude when Zn0 concentrations decrease below 1010 M. The large increase in uptake rates reflects the induction of high-affinity cellular transport systems for Cd and Co in response to declining intracellular Zn concentrations. Data are from Sunda WG and Huntsman SA (2000) Effect of Zn, Mn, and Fe on Cd accumulation in phytoplankton: Implications for oceanic Cd cycling. Limnology and Oceanography 45: 1501–1516.
bound as ferric oxides and organic chelates and prokaryotic and eukaryotic plankton cells have evolved different strategies to access these bound forms of iron. Prokaryotic cells (cyanobacteria and heterotrophic bacteria) have evolved high-affinity uptake systems that are induced under iron deficiency. These systems involve the biosynthesis and extracellular release of a variety of high-affinity iron chelators (siderophores) that strongly bind iron(III) in the surrounding seawater. The siderophore chelates are then actively taken up into the cells by transport proteins on the outer cell membrane. The siderophore chelates have different chemical structures, and different outer membrane siderophore transport proteins are needed to take up structurally distinct siderophores or groups of siderophores with similar chemical structures. Bacteria often take up not only
their own siderophores, but those produced by other bacteria, resulting in complex ecological interactions among bacteria. Eukaryotic phytoplankton do not appear to produce siderophores and there is little evidence for direct cellular uptake of ferric siderophore chelates. Instead there is mounting evidence for the utilization of a high-affinity transport system that accesses ferric complexes via their reduction at the cell surface and subsequent dissociation of the resulting ferrous-ligand complexes. The released ferrous ions bind to iron(II) receptors on iron transport proteins located on the outer cell membrane, which transport the iron into the cell. This intracellular transport involves the reoxidation of bound iron(II) to iron(III) by a copper protein, and thus copper is required for cellular iron uptake. The availability of iron to this transport
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Zinc (nmol kg−1)
(a)
TRACE ELEMENT NUTRIENTS
10
Metabolic Requirements and their Relation to Other Limiting Resources
8
Trace element micronutrients are essential for the growth and metabolism of all marine algae and bacteria. They play critical roles in photosynthesis, respiration, and the assimilation and transformation of essential macronutrients (nitrogen, phosphorus, and silicic acid). Thus trace metal requirements can be influenced by the availability of light, CO2, and major nutrients and the cycles of major nutrient elements are influenced by trace element nutrients. Of the micronutrient metals, iron is needed in the greatest amount and is the metal that most frequently limits algal growth. Iron serves essential metabolic functions in photosynthetic electron transport, respiration, nitrate assimilation, N2 fixation, and detoxification of reactive oxygen species (e.g., superoxide radicals and hydrogen peroxide). Because of its heavy involvement in photosynthetic electron transport, cellular iron requirements increase with decreasing light intensity and photoperiod. Such effects can lead to iron–light co-limitation in low-light environments such as regions where the depth of the surface wind mixed layer greatly exceeds the depth of light penetration (as often occurs in the Southern Ocean and at high latitudes during the winter) or in the deep chlorophyll maximum at the bottom of the euphotic zone (the sunlit layer) in thermally stratified surface waters. Iron also occurs in the enzymes (nitrate and nitrite reductases) involved in the reduction of nitrate to ammonium in phytoplankton and the enzyme complex (nitrogenase) that fixes nitrogen (reduces dinitrogen molecules to ammonia) in cyanobacteria. Both processes require cellular energy (in the form of ATP molecules) and reductant molecules (NADPH), and iron is also needed in high amounts for the photosynthetic production of the needed ATP and NADPH. Algal cells growing on nitrate need B50% more iron to support a given growth rate than cells growing on ammonium. Consequently, iron can be especially limiting in oceanic upwelling systems (such as the equatorial and subarctic Pacific) where waters containing high nitrate concentrations, but low iron, are advected to the surface (see Figures 3(a) and 3(b)). Even higher amounts of iron (up to 5 times as much) are needed for diazotrophic growth (growth on N2) than for equivalent growth on ammonium due to high energetic (ATP) cost for nitrogen fixation and the large amount of iron in the nitrogenase enzyme complex. As a result, iron appears to limit N2 fixation in large regions of the ocean and is thought to control oceanic inventories of fixed nitrogen. As a consequence, nitrogen is the primary limiting major nutrient in most ocean waters, while in lakes, where
6 4 Zinc, T-5
2
Zinc, T-6 0
0
1
2
3
(b) 50
Cobalt (pmol kg−1)
40 30 20 Cobalt, T-5
10
Cobalt, T-6 0
0
1 2 Phosphate (µmol kg−1)
3
Figure 6 Plots of filterable zinc and cobalt concentrations vs. phosphate at two stations in the subarctic Pacific (Station T-5, 39.61 N, 140.81 W and Station T-6, 45.01 N, 142.91 W, Aug. 1987). The decrease in zinc with decreasing phosphate is caused by the simultaneous removal of both metals via cellular uptake and assimilation by phytoplankton. Cobalt becomes depleted by phytoplankton uptake only after zinc concentrations drop to very low levels (o0.2 nmol kg1). This pattern is consistent with metabolic replacement of cobalt for zinc, as observed in phytoplankton cultures (see Figure 5). Data plots after Sunda WG and Huntsman SA (1995) Cobalt and zinc interreplacement in marine phytoplankton: Biological and geochemical implications. Limnology and Oceanography 40: 1404–1417.
system is dependent on the reduction potential of the ferric complexes; consequently, readily reducible ferric species such as dissolved inorganic ferric hydroxide complexes are accessed much more readily by this system than are strongly bound ferric siderophore chelates. Thus, iron uptake by this system is highly dependent on the chemical speciation of iron in seawater. Photo-reductive dissociation of ferric chelates increases iron availability to this system, since the released ferrous ions can directly react with the membrane transport protein and the reoxidized ferric hydrolysis species are readily reduced and taken up.
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TRACE ELEMENT NUTRIENTS
iron concentrations are much higher, phosphate is the primary limiting nutrient. Due to iron limitation of C fixation and N2 fixation in major regions of the ocean, iron plays a significant role in regulating carbon and nitrogen cycles in the ocean. It thus helps regulate the biological CO2 pump discussed earlier, which through transport of carbon to the deep ocean, controls the ocean/atmosphere CO2 balance and CO2-linked greenhouse warming. There is evidence that climatically driven variations in the input of iron-rich continental dust to the ocean has played an important role in regulating glacial–interglacial climate cycles. Manganese occurs in the water-splitting complex of photosystem II, and thus is essential for photosynthesis. Consequently, like iron, it is needed in higher amounts for growth at low light. Manganese also occurs in superoxide dismutase, an antioxidant enzyme that removes toxic superoxide radicals, produced as byproducts of photosynthesis. Because it has fewer metabolic functions, its cellular growth requirement is less than that of iron. Manganese may limit algal growth in certain low-Mn environments such as the subarctic Pacific and Southern Ocean, where manganese additions have been observed to stimulate algal growth in bottle incubation experiments. Zinc serves a variety of metabolic functions and has a cellular requirement similar to that for manganese. It occurs in carbonic anhydrase (CA), an enzyme critical to intracellular CO2 transport and fixation. Higher amounts of this enzyme are needed at low CO2 concentrations, leading to potential colimitation by zinc and CO2 in the ocean. However, the B35% increase in CO2 in the atmosphere and surface ocean waters from the burning of fossil fuels makes Zn–CO2 co-limitation less likely in the modern ocean than in preindustrial times. Zinc also occurs in zinc finger proteins, involved in DNA transcription, and in alkaline phosphatase, needed to acquire phosphorus from organic phosphate esters, which dominate phosphate pools in low-phosphate ocean waters. Consequently, Zn and P may co-limit algal growth in regions where both nutrients occur at low concentrations such as the central gyre of the North Atlantic. Cobalt, and sometimes cadmium, can substitute for zinc in many zinc enzymes such as CA, leading to complex interactions among the three metals in marine algae (Figure 5). The presence of cadmium in CA appears to explain its nutrient-like distribution in ocean waters (Figure 2(e)), and the identification of a unique Cd-CA enzyme in marine diatoms means that it functions as a micronutrient in these organisms. Cobalt also occurs in vitamin B12, an essential
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vitamin required for growth of many eukaryotic algal species. This vitamin is synthesized only by bacteria, resulting in potential interactions between B12-producing bacteria and B12-requiring eukaryotic algae in the ocean. A specific requirement for cobalt not involving B12 is seen in marine cyanobacteria and bloom-forming prymnesiophytes (including Emiliania huxleyi), but the biochemical basis for this is not known. Both zinc and cobalt additions have been shown to stimulate phytoplankton growth in bottle incubation experiments in the subarctic Pacific and in some coastal upwelling regimes along the eastern margin of the Pacific, but the effects were modest relative to those for added iron. However, zinc addition had a large effect on algal species composition, and preferentially stimulated the growth of coccolithophores, an algal group largely responsible for calcium carbonate formation in the ocean. Biogenic CaCO3 formation helps regulate the alkalinity (acid–base balance) of ocean water, which in turn affects oceanic CO2 concentrations, and air– sea flux of this important greenhouse gas. By influencing the growth of coccolithophores, zinc could indirectly affect atmospheric CO2 levels and global climate. Copper occurs in cytochrome oxidase, a key protein in respiratory electron transport, and in plastocyanin, which substitutes for the iron protein cytochrome c6 in photosynthetic electron transport in oceanic phytoplankton. It is also an essential component of the high-affinity iron transport system of many eukaryotic algae. Because copper is needed for iron uptake and can metabolically substitute for iron, co-limitations can occur for Cu and Fe, as observed in some diatoms. Nickel and molybdenum, like iron, play important roles in nitrogen assimilation. Nickel occurs in the enzyme urease, and thus is required by phytoplankton grown on urea as a nitrogen source. It also occurs in Ni-superoxide dismutase found in many marine cyanobacteria, which, like the Mn and Fe forms of the enzyme, removes harmful superoxide radicals from cells. Little is currently known about the potential for nickel limitation in the ocean. Molybdenum occurs with iron in the enzymes nitrate reductase and nitrite reductase and in nitrogenase, and consequently is utilized in nitrate assimilation and N2 fixation. Along with the Fe–Mo enzyme, there are two other isoforms of nitrogenase, a primitive less-efficient form containing only iron in its active center, and another which contains iron and vanadium. Thus molybdenum is not absolutely essential for dinitrogen fixation, although the predominance of the more efficient Fe–Mo isoform in the modern ocean helps to minimize iron limitation of
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nitrogen fixation. Because of its high concentration in seawater (c. 105 nM), Mo does not appear to limit algal growth or N2 fixation in the ocean. The metalloid selenium is also essential for the growth of many marine phytoplankton. It occurs in glutathione peroxidase, an enzyme that degrades hydrogen peroxide, and thus is important in antioxidant protection. However, it is likely that selenium has other as-yet-unidentified metabolic functions. The potential for selenium limitation in the ocean is currently unknown.
Biological Feedback on Seawater Chemistry Trace elements not only influence the productivity and species composition of planktonic communities, but the plankton have a profound effect on the chemistry and cycling of these elements on a variety of temporal and spatial scales (Figure 1). The most obvious example is the effect of algal uptake, particulate settling, and regeneration cycles on the vertical distribution and interocean transfer of trace element nutrients (Fe, Zn, Cd, Ni, Cu, and Se; Figures 2–4). In addition, bacteria largely mediate the removal of dissolved manganese and cobalt from subsurface seawater via the formation of Mn(IV) and Co(III) oxides. There is evidence that the organic ligands that strongly bind iron, copper, zinc, and cobalt are produced either directly or indirectly by the biota. In the North Pacific, the organic ligands that strongly bind copper occur at highest levels at the depth of maximum productivity, and decrease below the euphotic zone. Ligands having the same copper-binding strength are produced by Synechococcus, an abundant group of oceanic cyanobacteria. There is evidence that these organisms produce the chelators to detoxify copper by decreasing free cupric ion concentrations. The organic ligands that strongly bind iron(III), cobalt, and zinc also have a beneficial effect. The iron ligands tightly bind ferric ions in soluble chelates and thereby minimize the abiotic removal of iron from seawater via the formation of insoluble ferric oxides or ferric ion adsorption onto particulate surfaces. Without such chelating ligands, iron concentrations would likely be much lower, and the productivity of the ocean would be greatly reduced. The Co(III)-binding ligands serve a similar function in limiting the formation of insoluble Co(III) oxides, a major mechanism for removal of cobalt from seawater. Recent culture experiments and seawater incubation experiments suggest that these ligands are produced by the cyanobacterial genus Synechococcus,
whose growth may be limited by cobalt in some regions of the ocean. Zinc chelators also serve a beneficial function, not only by minimizing abiotic scavenging of zinc in surface waters, but also by preventing the extremely efficient uptake systems of eukaryotic phytoplankton from completely depleting this essential micronutrient element from surface ocean waters. Thus trace element nutrients and marine plankton comprise an interactive system in the ocean in which each exerts a controlling influence on the composition and dynamics of the other (Figure 1). On longer geological timescales, the feedback interactions between the biota and trace metal chemistry and availability have been profound. Currently, the air we breathe and virtually the entire ocean, with the exception of a few isolated anoxic basins (e.g., the Black Sea), contain free dioxygen molecules (O2), generated over billions of years from its release as a byproduct of oxygenic photosynthesis. The presence of free O2 sets the redox state of modern ocean toward oxidizing conditions, which as noted previously, limits the solubility of essential transition metals (Fe, Co, and Mn) whose stable oxidation states under these conditions are insoluble Co(III) and Mn(IV) oxides or sparingly soluble Fe(III) oxides. However, prior to the advent of oxygenic photosynthesis c. 3 billion years ago, the chemistry of the ocean was far different from that which exists today. There was no free oxygen and the entire ocean and Earth’s surface was much more reducing. Under these conditions, the stable redox state of Fe, Mn, and Co was soluble Fe(II), Mn(II), and Co(II), and that of copper was Cu(I). Furthermore, the stable redox form of sulfur was sulfide ( 2 oxidation state), rather sulfate (þ 6 oxidation state), which occurs in present-day seawater at a relatively high concentration (28 mM). The presence of moderate to high levels of sulfide greatly restricted the availability of zinc, copper, molybdenum, and cadmium, which form insoluble sulfide precipitates; but it had a much lesser impact on other metals (Mn2þ, Fe2þ, Co2þ, and Ni2þ) whose sulfides are much more soluble. Thus, early life in the ocean evolved in an environment of high availability of Fe, Mn, Co, and Ni and low availabilities of Zn, Mo, Cu, and Cd, contrasting the situation in the modern ocean. Given the utility of Fe as a redox catalyst and its relative abundance in the Earth’s crust and ancient ocean, it is perhaps not surprising that this metal was utilized in the evolution of the major redox catylysts of life. It occurs in high amounts in the redox centers of nitrogenase responsible for dinitrogen fixation and in the various proteins and protein complexes involved in oxygenic photosynthesis (photosystem I, photosystem II,
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TRACE ELEMENT NUTRIENTS
cytochorme b6/f complex, ferredoxin, and cytochrome c). In addition, the abundant soluble manganese in the early ocean was utilized in the wateroxidizing centers of photosystem II. The combined action of these iron- and manganese-containing biological redox catalysts provided for efficient fixation of N2 and CO2 needed for production of proteins and other biological compounds. The concomitant release of O2 from photosynthesis and sequestration of organic carbon in marine sediments and sedimentary rocks, slowly (over 1–2 billion years) oxidized ferrous iron to ferric oxides and sulfide species to soluble sulfate, ultimately resulting in the buildup of free O2 first in the surface ocean and atmosphere, and gradually in the ocean as a whole. The precipitation of ferric oxides from the sea has resulted in the chronic Fe limitation of carbon fixation and N2 fixation that we currently observe in the ocean. However, this negative effect is more than balanced by the usefulness of molecular oxygen in highly efficient oxygen-dependent respiration utilized by all present-day aerobic microbes, plants, and animals. Furthermore, the release of zinc, copper, molybdenum, and cadmium from insoluble sulfides allowed for the subsequent evolution of numerous new enzymes utilizing these metals, which appear to have evolved following the appearance of free O2. Thus, evolution has involved a continuous feedback between biological systems and the surrounding chemical environment, with biological trace metal catalysts playing a central mediating role in this process.
Glossary ATP Adenosine triphosphate; a high-energy compound produced in photosynthesis and respiration which is used as the main energy currency of cells. Chemical speciation The different chemical forms of trace elements. Chelate A strong complex between an organic ligand and a metal. Chelation The reaction of a metal with an organic ligand to form a chelate. Chelator An organic ligand that forms stable complexes with metal ions. Cytochrome b6/f complex An iron-rich protein complex involved proton pumping and ATP synthesis in photosynthesis. Fe(II), Fe(III) Iron with oxidation states of þ 2 and þ 3, respectively, also referred to as ferrous and ferric iron. Ferredoxin A soluble iron–sulfur protein involved in photosynthetic electron transport.
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Ferric hydrolysis species Inorganic complexes of iron(III) with one to four hydroxide ions: FeOH2 þ , FeðOHÞþ 2 , Fe(OH)3, and FeðOHÞ4 . Metalloenzyme An enzyme containing a metal as an essential functional component. Mn(II), Mn(III), Mn(IV) Manganese with oxidation states of þ 2, þ 3, and þ 4, respectively. NADPH The reduced form of nicotinamide adenine dinucleotide phosphate, which is produced in photosynthesis and serves as the primary reductant molecule in plant cells. Nitrogenase An iron-containing enzyme complex responsible for nitrogen fixation. Photosystem I and photosystem II The two photochemical reaction centers in photosynthesis. Redox Chemical reduction and oxidation. Siderophore A high-affinity organic ligand produced by bacteria to complex iron and facilitate its intracellular uptake. Superoxide radical A free radical of chemical structure (dO 2 ) formed from the single electron reduction of molecular oxygen.
See also Carbon Cycle. Iron Fertilization. Nitrogen Cycle. Primary Production Processes. Transition Metals and Heavy Metal Speciation.
Further Reading Anbar AD and Knoll AH (2002) Proterozoic ocean chemistry and evolution: A bioinorganic bridge? Science 297: 1137--1142. Barbeau K, Rue EL, Trick CG, Bruland KW, and Butler A (2003) Photochemical reactivity of siderophores produced by marine heterotrophic bacteria and cyanobacteria based on characteristic Fe(III) binding groups. Limnology and Oceanography 48: 1069--1078. Boyle E, Edmond JM, and Sholkovitz ER (1977) The mechanism of iron removal in estuaries. Geochimica Cosmochimica Acta 41: 1313--1324. Brand LE, Sunda WG, and Guillard RRL (1983) Limitation of marine phytoplankton reproductive rates by zinc, manganese and iron. Limnology and Oceanography 28: 1182--1198. Bruland KW (1989) Complexation of zinc by natural organic ligands in the central North Pacific. Limnology and Oceanography 34: 269--285. Bruland KW (1992) Complexation of cadmium by natural organic ligands in the central North Pacific. Limnology and Oceanography 37: 1008--1017. Bruland KW and Franks RP (1983) Mn, Ni, Cu, Zn and Cd in the western North Atlantic. In: Wong CS, Boyle E, Bruland KW, Burton JD, and Goldberg ED (eds.)
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Trace Metals in Sea Water, pp. 395--414. New York: Plenum. Coale KH (1991) Effects of iron, manganese, copper, and zinc enrichments on productivity and biomass in the subarctic Pacific. Limnology and Oceanography 36: 1851--1864. Coale KH, Johnson KS, Chavez FP, et al. (2004) Southern Ocean iron enrichment experiment, carbon cycling in high- and low-Si waters. Science 304: 408--414. Crawford DW, Lipsen MS, Purdie DA, et al. (2003) Influence of zinc and iron enrichments on phytoplankton growth in the northeastern subarctic Pacific. Limnology and Oceanography 48: 1583--1600. Cutter GA and Bruland KW (1984) The marine biogeochemistry of selenium: A reevaluation. Limnology and Oceanography 29: 1179--1192. da Silva JJRF and Williams RJP (1991) The Biological Chemistry of the Elements. Oxford, UK: Clarendon. Donat JR and Bruland KW (1995) Trace elements in the oceans. In: Salbu B and Steinnes E (eds.) Trace Elements in Natural Waters, pp. 247--281. Boca Raton, FL: CRC Press. Duce RA and Tindale NW (1991) Atmospheric transport of iron and its deposition in the ocean. Limnology and Oceanography 36: 1715--1726. Falkowski PG (1997) Evolution of the nitrogen cycle and its influence on the biological sequestration of CO2 in the ocean. Nature 387: 272--275. Ho T, Quigg A, Findel ZV, et al. (2003) The elemental composition of some marine phytoplankton. Journal of Phycology 39: 1145--1159. Hutchins DA, Hare CE, and Weaver RS (2002) Phytoplankton iron limitation in the Humboldt Current and Peru Upwelling. Limnology and Oceanography 47: 997--1011. Ito Y and Butler A (2005) Structure of synechobactins, new siderophores of the marine cyanobacterium Synechococcus sp. PCC 7002. Limnology and Oceanography 50: 1918--1923. Johnson KS, Gordon RM, and Coale KH (1997) What controls dissolved iron concentrations in the world ocean? Marine Chemistry 57: 137--161. Kustka AB, San˜udo-Wilhelmy S, Carpenter EJ, et al. (2003) Iron requirements for dinitrogen and ammonium supported growth in cultures of Trichodesmium (IMS 101): Comparison with nitrogen fixation rates and
iron:carbon ratios of field populations. Limnology and Oceanography 48: 1869--1884. Maldonado MT and Price NM (1996) Influence of N substrate on Fe requirements of marine centric diatoms. Marine Ecology Progress Series 141: 161--172. Martin JH, Gordon RM, Fitzwater S, and Broenkow WW (1989) VERTEX: Phytoplankton/iron studies in the Gulf of Alaska. Deep-Sea Research 36: 649--680. Morel FMM and Price NM (2003) Biogeochemical cycles of trace metals in the oceans. Science 300: 944--947. Morel FMM, Reinfelder JR, Roberts SB, et al. (1994) Zinc and carbon co-limitation of marine phytoplankton. Nature 369: 740--742. Rue EL and Bruland KW (1995) Complexation of iron(III) by natural organic ligands in the central North Pacific as determined by a new competitive ligand equilibration/adsorptive cathodic stripping voltammetric method. Marine Chemistry 50: 117--138. Saito MA, Moffett JW, and Ditullio GR (2004) Cobalt and nickel in the Peru Upwelling region: A major flux of labile cobalt utilized as a micronutrient. Global Biogeochemical Cycles 18: GB4030. Saito MA, Sigman DM, and Morel FMM (2003) The bioinorganic chemistry of the ancient ocean: The coevolution of cyanobacterial metal requirements and biogeochemical cycles at the Archean–Proterozoic boundary? Inorganica Chimica Acta 356: 308--318. Shaked Y, Kustka AB, and Morel FMM (2005) A general kinetic model for iron aquisition by eucaryotic phytoplankton. Limnology and Oceanography 50: 872--882. Strzepek RF and Harrison PJ (2004) Photosynthetic architecture differs in coastal and oceanic diatoms. Nature 431: 689--692. Sunda WG and Huntsman SA (1995) Cobalt and zinc interreplacement in marine phytoplankton: Biological and geochemical implications. Limnology and Oceanography 40: 1404--1417. Sunda WG and Huntsman SA (1997) Interrelated influence of iron, light and cell size on marine phytoplankton growth. Nature 390: 389--392. Sunda WG and Huntsman SA (2000) Effect of Zn, Mn, and Fe on Cd accumulation in phytoplankton: Implications for oceanic Cd cycling. Limnology and Oceanography 45: 1501--1516. Turner DR and Hunter KA (eds.) (2001) The Biogeochemistry of Iron in Seawater. New York: Wiley.
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TRACER RELEASE EXPERIMENTS A. J. Watson, University of East Anglia, Norwich, UK J. R. Ledwell, Woods Hole Oceanographic Institution, Woods Hole, MA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3004–3009, & 2001, Elsevier Ltd.
atmosphere. The signatory nations are thus committed to controlling the rate of its production. However, for any realistic future emission scenario, SF6 will remain insignificant (o1%) as a contributor to the anthropogenic greenhouse effect for the foreseeable future.
Mixing Experiments in the Deep Ocean
Introduction Since the mid 1980s, analytical and engineering techniques have been developed to enable the compound sulfur hexafluoride (SF6) to be used as a tracer for oceanographic experiments. SF6 is a stable and inert substance with an exceptionally low level of detection, and its use enables large bodies of water to be unambiguously marked, allowing the investigator to keep track of a particular parcel of water. Three kinds of experiment have thus far made use of this technique: (1) measurement of mixing and transport integrated over large regions; (2) estimates of gas transfer velocities at the surface of the sea; (3) open ocean iron enrichment experiments. This article briefly describes the techniques used, and the major results from each of these types of process study.
The Tracer Sulfur hexafluoride is an inert perfluorine, routinely detectable in sea water at B0.01 fmol kg1 by electron-capture gas chromatography (1 fmol ¼ 1015 mol). At room temperature and pressure SF6 is a gas, but it forms a dense (r ¼ 1880 kg m3) liquid at pressures exceeding 20 bar. It is extremely stable in the environment and, other than being an asphyxiant, the pure compound has no known toxic effects. It is produced commercially largely (B80%) for use as a gaseous insulator in high-voltage installations. Much of this industrial production eventually finds its way into the atmosphere. The atmospheric mixing ratio was about 4 1012 in 1999, and is growing at about 7% per year. Its solubility is very low, so that the surface concentrations in equilibrium with the atmospheric concentration are on the order of 1 fmol kg1. The combination of very low detection limit, nontoxicity, low marine background concentration, ease of analysis and inertness make SF6 a nearly ideal tracer. SF6 is included in the Kyoto Protocol because, molecule-for-molecule, it is a powerful greenhouse gas with a long (41000 years) lifetime in the
To measure diapycnal mixing (i.e. mixing acrossdensity surfaces) by tracer release, the tracer is released, as near as possible, onto a single, well-defined density surface, and its subsequent spread onto neighboring surfaces is monitored. If the mixing occurs in accordance with Fick’s law, the square of the mean width of the concentration distribution increases linearly with time, the rate of increase being a direct measure of the diffusivity. The advantage of this strategy compared to the documentation of temperature or velocity microstructure, is that it gives an unambiguous measurement integrated over a substantial time and space scale. In practice, in the open ocean these scales are of order months or years, and hundreds or thousands of kilometers – hence also the method’s main disadvantage, which is that it must be done on a large scale. At the time of writing, five experiments of this kind have been initiated in the open ocean. The first two, relatively small-scale releases, were made in the ocean-floor basins off the coast of Southern California and the remaining three in the thermocline of the North Atlantic, the deep Brazil Basin and the central Greenland Sea. Below we describe the release method used in most of these experiments, and the results of the North Atlantic experiment in more detail. Mixing rates from all five experiments are then compared. Release Method
Sulfur hexafluoride is very insoluble; for small-scale experiments it can be dissolved by presaturating drums or tanks of water with the gas. However, the practical limit for the amount which can be injected in this way is a few moles, sufficient for tracer experiments on the 10–100 km scale only. For large open ocean releases, we designed an injection package which releases liquid SF6 into water by pumping it through fine orifices at high pressure, so that it breaks into an emulsion of fine droplets on contact
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with the sea. These droplets are sufficiently small that they dissolve before they have settled an appreciable distance. The apparatus is designed to allow the accurate delivery of SF6 at rates of up to 3 kg h1 onto a given ‘target’ density surface at any depth greater than 200 m in the ocean, when towed behind a ship on a conducting cable. In use, the injector was controlled by a computer in the laboratory of the ship. The output of the CTD was used to calculate in real time the density of the water at the package, and compare it to the ‘target’ density. The computer issued commands to the automated winch to haul in wire if the density was higher than the target, or pay out if it was significantly lower. During the North Atlantic Tracer Release Experiment (NATRE) this system was able to deliver tracer with an overall RMS accuracy of 72 m from the target surface. With such an injection system, it is practical to initiate experiments using several hundred kilograms of tracer, sufficient to enable investigations at the ocean-basin scale.
150
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Height above target density surface (m)
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The tracer results from NATRE have been reported in detail. Major findings were that the diapycnal diffusivity was 0.12 cm2 s1 for the first 6 months, and then 0.17 cm2 s1 for the subsequent 24 months. The mean vertical profile for each survey was nearly Gaussian, and as a set they illustrate an approximate solution of the diffusion equation in one dimension (Figure 1). The result that the diapycnal diffusivity in the pycnocline is of order 0.1 cm2 s1 confirms estimates based on internal wave dynamics and on measurements of turbulent dissipation rates. Some analyses of the penetration of transient tracers into the deep pycnocline also have implied diffusivities on the order of 0.1 cm2 s1. Values of diffusivity of 1 cm2 s1 were inferred by Munk’s classic ‘abyssal recipes’ analysis, but this was for depths between 1000 and 4000 m and included boundary processes as well as interior processes. It is now clear that 1 cm2 s1 is an overestimate for the interior pycnocline. The lateral dispersion of the tracer revealed surprisingly efficient mechanisms of stirring at scales from 0.1 to 30 km. The lateral diffusivity setting the width of tracer streaks at 6 months was found to be about 2 m2 s1. The mechanism is not well understood, but may be due to shear dispersion by vortices generated during the adjustment to diapycnal mixing events. The experiment did confirm the predictions of C. Garrett, that a tracer patch remains streaky only for a year or so, after which time the exponential growth of the area actually tainted by the
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NATRE: Overview of Results
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Figure 1 Mean vertical profiles from NATRE at 0, 5, 6, 12 and 30 months after the initial survey. The SF6 concentration has been averaged on isopycnal surfaces, approximately, and plotted versus height above the target isopycnal surface using the mean relation between depth and density for the 12-month survey. The profiles are normalized to have equal areas. The initial profile (y .) is allowed to run off the graph so that the others are clear.
tracer streaks catches up with a power-law growth of the overall area occupied by the tracer patch. It is important in a tracer study of mixing in the ocean to measure the hydrodynamic forcing, and also to measure hydrodynamic parameters that are believed to be useful for estimating diffusivities, so that existing theories can be tested. Several groups were involved in profiling fine structure and microstructure during NATRE. Dissipation of turbulent kinetic energy and temperature variance measured by profiling instruments gave estimates of diapycnal diffusivity which agreed closely with the tracer results. Measurements of the fine structure have helped reveal the roles of shear and double diffusive gradients in driving the mixing. Dependency of Diapycnal Mixing and Buoyancy Frequency from Tracer Release Experiments
Figure 2 shows diapycnal diffusivities as a function of buoyancy period for the deep ocean tracer release experiments so far published. Except for the recent
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TRACER RELEASE EXPERIMENTS 4.5
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Diapycnal mixing rate (cm s )
Gas exchange is dependent on environmental conditions that affect the near-surface turbulence in the 4.0 sea and which are not easily reproduced in laboratory facilities, such as wind speed, sea state, and the 3.5 chemical state of the air–sea interface. In laboratory wind-wave facilities for example, a strong depend3.0 Brazil Basin ence on wind speed is observed, but the functional form depends on the experimental set-up. As a con2.5 sequence, though substantial theoretical understanding has been gained from experiments in 2.0 laboratory facilities, there has also been a need to assemble a body of gas transfer measurements made 1.5 at sea. Santa Cruz The first aqueous use of SF6 as a tracer was the Basin 1.0 measurement of gas exchange in lakes by R. WanGreenland Sea ninkhof, in 1985. Lake experiments are compara0.5 tively easy to set up and perform, and give absolute Santa Monica estimates of gas exchange. The basis of the technique Basin NATRE 0 is to keep track of the total amount of gas in the lake. 0 0.5 2.0 2.5 3.0 1.0 1.5 The results of the first experiment gave unambiguous 1/ N (hours) evidence in a field situation, for a strong dependence of gas exchange on wind speed, and the data form Figure 2 Vertical mixing coefficients for five tracer release experiments in the open ocean, plotted as a function of 1/N where the calibration for the ‘Liss–Merlivat’ formulation of N is the buoyancy frequency. For discussion see text. gas exchange. However, the gas exchange rates found in that experiment, when scaled and applied to Brazil Basin experiment, the data indicate correlation carbon dioxide, are lower by about a factor of two between the two, as would be expected if the forcing than might be expected from an analysis of the glowere in some sense held constant. However, the reader bal 14C budget of the ocean. This uncertainty in should beware of such relationships, as the Brazil marine gas exchange rates remains unresolved up to Basin result shows. There is evidence from internal the present. In recent years, many investigators who wave phenomenology and energy dissipation meas- need to parameterize gas exchange as a function of urements that the diffusitivity in the interior of the wind speed, have bracketed the uncertainty by apocean, when driven only by the background internal plying both the Liss–Merlivat relation (scaled to wave field, is independent of the buoyancy period with agree with the lake SF6 experiment), and a relation a value of approximately 0.05 cm2 s1. The only one due to Wanninkhof that is scaled to agree with global of our experiments that has been conducted in the 14C values. interior of the ocean, well away from boundaries, was NATRE, and that was probably influenced by salt The Dual Tracer Technique fingering. The measurements shown in Figure 2 are those made before the tracer-containing water had This long-standing uncertainty in marine gas extime to contact the boundaries; mixing increased change rates provided a good reason to adapt the dramatically in the California basin experiments once lake SF6 technique to the measurement of gas exsuch contact occurred. Nevertheless, the energy input change at sea. However, whereas in a lake it was easy for all but the NATRE site may have been enhanced to determine the total amount of tracer present and by the proximity of the boundaries. If this is the reason the area over which it is spread, in the open ocean the why most of these experiments show elevated values, tracer release is unenclosed and dilutes into a conit is evident that in many situations of interest, the stantly larger volume of water. A means must be diffusivity, and presumably the energy flux through found to account for this dilution. Theoretically, this the internal wave field, must be enhanced even at could be accomplished by releasing a nonvolatile conservative tracer with the gaseous one, and then considerable distance from boundaries. use the change in ratio between the two to define gas exchange rates. In practice, no such ideal conservaGas Exchange Experiments tive nonvolatile tracer is available, so instead SF6 and The rate of air–sea gas transfer is a parameter which 3He were released, two volatile tracers having very is needed in a wide range of biogeochemical studies. different molecular diffusivities. When the water
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TRACER RELEASE EXPERIMENTS
column is well mixed and of constant depth H, the ratio r ¼ c2 =c1 of the concentrations of the tracers (in excess of any concentration in equilibrium with the atmosphere) evolves according to the equation:
where k1 and k2 are the gas transfer velocities appropriate to each tracer. This suggested that in the right environment, that is a shallow sea, well-mixed and with a constant depth, measurement of the tracer ratio could be used to define the difference between the two gas transfer rates. If another relation between the gas transfer rates could be defined, the ‘dual tracer’ technique would enable absolute values for k1 and k2 to be derived. For this second relation, dual tracer experimenters have used a power law dependence of gas transfer velocities on Schmidt number (the ratio of kinematic viscosity of water to the diffusivity of the gas): k1 ¼ k2
North Sea Georges Bank 60
_1
1 dr 1 ¼ ðk2 k1 Þ r dt H
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Gas transfer velocity (cm h , Sc = 600)
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n Sc1 Sc2
For most conditions in which bubbles and spray are not affecting gas exchange, n ¼ 0:5. This result is derived from models and supported by measurements, in the laboratory and on lakes. At very low wind speeds when the sea is glassy smooth, this relation does not hold and n ¼ 0:67 is the theoretical result, but this condition is very rarely met at sea. In rough seas where substantial bubble-mediated gas transfer may occur, the theory is more complex and different assumptions have been made to derive absolute values under these conditions. Recent theoretical work suggests that the square-root assumption is reasonably accurate even in the presence of bubble-mediated transfer, though care is needed in scaling the results obtained using these insoluble tracers to more soluble gases such as carbon dioxide. In one experiment, a third tracer, bacterial spores specially treated to be suitable for this purpose, were used as a nonvolatile tracer, and these results also support the use of the square-root law. Figure 3 shows a compilation of results from dualtracer experiments at sea. The dual-tracer results confirm the strong dependence of gas exchange on wind speed. They generally lie between the Liss– Merlivat and Wanninkhof parameterizations. In the light of recent results, concerning the effect of ubiquitous natural organic films, we can hypothesize that the trends in these data are due to the decreasing effect of organics as one moves away from coastally influenced sites out into the open ocean. The
(1) (2)
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Wind speed at 10 m (m s ) Figure 3 Compilation of dual tracer gas exchange measurements. The North Sea results include some previously published data for which revised wind speeds have been estimated using the procedures detailed by P. D. Nightingale. Data from (1) Wanninkhof (1992) and (2) Liss and Merlivat (1986).
Wanninkhof parameterization, being tuned to global C exchange rate, is most affected by the open ocean and the Liss–Merlivat formulation, originally calibrated from the result of lake experiments, the most affected by organics. The two data sets lie in between these. Georges Bank might be expected to be less coastally influenced than the North Sea, and the trend in the results is consistent with that expectation. 14
Small-scale Surface Patch Experiments for Biogeochemical Studies A practical problem in carrying out open-sea dualtracer gas exchange experiments was the difficulty of keeping track of the released tracer patch. To overcome this, in the late 1980s instrumentation was built which took advantage of the uniquely fast gas chromatographic analysis for SF6. Gas chromatography is normally a slow, batch process, but for SF6 using a molecular sieve column, the actual separation takes only 30 seconds and the entire analysis can be completed in three minutes. Thus it was possible to build an instrument which continually measured the concentration of SF6 in a supply of water, and use this to ‘chase’ the tracer patch from a ship. This opened the possibility of using the tracer
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TRACER RELEASE EXPERIMENTS
In-situ Iron Enrichment Experiments
The first use of the tracer technique to guide biogeochemical studies was in the IRONEX experiments in the equatorial Pacific. At about the time the tracer-release technique had been developed for gasexchange experiments, the idea was suggested of testing the ‘Iron hypothesis’ of phytoplankton limitation by releasing a large amount of iron in the surface waters of, for example, the equatorial Pacific. A difficulty was that if the experiment was too small, then the iron-enriched patch would be easily lost, whereas if it were large enough to be easily found (probablyB100 km in scale) then it would be logistically difficult and expensive. The use of the tracer release to guide a 10-km scale experiment was an obvious next step, and the design for such a study was published in 1991. The first two unenclosed iron-enrichment studies were carried out in 1993 and 1995 in the Equatorial Pacific. In both, nanomolar concentrations of iron were induced in the surface layer by release of iron sulfate, the patches being labeled by SF6 addition. The SF6(o1 mol in total) was added in a constant ratio to the initial addition of iron, the tracer component was then used as a guide to keep track of the affected patch of ocean. Sampling could be reliably categorized as ‘in’ or ‘out’ the patch, even after all the measurable iron had disappeared from solution. In the second study, the main experiment included reseeding the patch with iron, but not tracer, twice after the initial release. Important secondary aims of the tracer component of the experiments have been the study of mixing rates both horizontally in the mixed layer, and vertically across the thermocline. Figure 4 shows a summary of the results for the effect of the iron releases on surface water fugacity of carbon dioxide (fCO2) from Ironex I and II. fCO2 is plotted against SF6 measured in the water on paired samples, for various times following the initiation of the experiment. Such a plot shows whether the fCO2 (or any other variable of interest) develops a
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to guide experiments to investigate the biology or chemistry of an accurately marked patch of surface water, over a period of days to weeks. Such ‘lagrangian’ experiments have frequently been performed in the past using drogued drifting buoys to mark movement of water. However, an early observation from the trial tracer experiments made in the English Channel was that such buoys do not normally stay co-located with a patch of water marked by a tracer release. Surface buoys are subject to windage and tend to slip downwind of the marked water.
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Figure 4 Linear regressions of sea surface values of fugacity of CO2 (fCO2) with SF6 concentration, for specified periods after the start of the Ironex I (lower) and Ironex II (upper). Representative data points are shown, for the ‘day 4–5’ period during Ironex I (J), and the ‘day 6–8’ period during the Ironex II (}). The hashed region around the two regression lines which correspond to these data shows the confidence limit (3-s) on the slope of the line. (Data from Cooper et al., 1996; Law et al., 1998; Watson et al., 1994.)
relationship with the tracer concentration over time. It is a useful summary of the effects observed even if the evolution of the patch shape is complex and not readily mapped in space. Data at low and background SF6 show the ‘control’ condition, outside the patch, while data at high SF6 show the evolution of the center of the marked water. Figure 4 shows the contrasting results of the experiments. Ironex II produced an intense bloom of diatoms which fixed substantial carbon, resulting in a drawdown of carbon dioxide in the surface water which at its peak amounted to 70–80 matm below the starting ‘outside patch’ condition. The drawdown continued to build up beyond the first week of the experiment, and a substantial signal was left in the water even after the bloom began to fade. By contrast, during Ironex I (shown on the same fCO2 scale) the effect on the carbon concentration of the surface water was small, only 10–20% of that seen on the Ironex II, and it was already fading by the end of the first week. As measured by carbon uptake, the response of the two experiments in the first 3–4 days
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is similar. The divergence between the two time histories after that time is probably attributable to the fact that there were further additions of iron to the patch water on days 3 and 7 of Ironex II, but only the single initial iron enrichment during Ironex I, after which the disappearance of the added Fe, presumably by sedimentation, occurred very quickly. The simplest possible interpretation of the Ironex results is therefore that iron supply, when increased in the equatorial Pacific, allows diatoms to bloom and the chemistry of the water to change, providing that the iron concentration is elevated for several days at least.
routine. Three experiments at the 1000-km scale have so far been initiated, to measure ocean mixing on these scales. There have been more than twenty smaller scale experiments, of increasing sophistication, since they were first begun in 1986. For topics to which they are suited, such as iron limitation, biogeochemical budgets, gas exchange and diapycnal mixing rates, these experiments have enabled something of the precision of the land-based laboratory investigation to be brought to bear in at-sea oceanography.
See also Conclusion Several further applications of the tracer technique are presently under way. Two ‘large scale’ experiments in the open ocean are being actively monitored, in the Greenland Sea and the Brazil Basin. Numerous useful subsurface experiments can be imagined. However, because of the conflict between such subsurface release experiments and the use of SF6 as a transient tracer, there is a need to establish a forum by which the wider oceanographic community can have input into the planning of prospective release experiments. Small-scale releases in surface waters should not normally compromise the transient tracer signal. One obvious application now under way is that of iron fertilization experiments to examine the extent to which ‘high nutrient low chlorophyll’ regions other than the equatorial Pacific are limited by iron availability. The recent Southern Ocean Iron Enrichment Experiment (SOIREE) has shown unequivocal evidence that iron supply does affect the biology of that region. This experiment was carried out during sometimes stormy weather, confirming that the patch-tracking technique works well in the open ocean under storm conditions. To summarize, experiments using SF6 tracer in the open ocean are now reduced to practice, if not
Air–Sea Gas Exchange. Long-Term Changes. Tracers of Ocean Productivity.
Tracer
Further Reading Cooper DJ, Watson AJ, and Nightingale PD (1996) Large decrease in ocean-surface CO2 fugacity in response to in-situ iron fertilization. Nature 383: 511--513. Law CS, Watson AJ, Liddicoat MI, and Stanton T (1998) Sulphur hexaflouride as a tracer of biogeochemical and physical processes in an open-ocean iron fertilisation experiment. Deep-Sea Research II 45: 977--994. Ledwell JR, Montgomery ET, Polzin KL, et al. (2000) Evidence for enhanced mixing over rough topography in the abyssal ocean. Nature 403: 179--182. Ledwell JR, Watson AJ, and Law CS (1998) Mixing of a tracer in the pycnocline. Journal of Geophysical Research 103: 21499--21529. Watson AJ, Law CS, Van Scoy K, et al. (1994) Minimal effect of iron fertilization on sea-surface carbon dioxide concentrations. Nature 371: 143--145. Watson AJ, Messias M-J, Fogelqvist E, et al. (1999) Mixing and convection in the Greenland sea from a tracer release. Nature 401: 902--904. Watson AJ, Upstill-Goddard RC, and Liss PS (1991) Air– sea gas exchange in rough and stormy seas measured by a dual-tracer technique. Nature 349: 145--147.
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TRACERS OF OCEAN PRODUCTIVITY W. J. Jenkins, University of Southampton, Southampton, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3020 –3026, & 2001, Elsevier Ltd.
Introduction Primary production is the process whereby inorganic carbon is fixed in the sunlit (euphotic) zone of the upper ocean, and forms the base of the marine food pyramid. It occurs when marine phytoplankton use sunlight energy and dissolved nutrients to convert inorganic carbon to organic material, thereby releasing oxygen. The total amount of carbon fixed during photosynthesis is called gross production, whereas the amount of carbon fixed in excess of internal metabolic costs is referred to as net production. It is understood that a significant fraction of the carbon fixed in this manner is rapidly recycled by a combination of grazing by zooplankton and in situ bacterial oxidation of organic material. New production is that portion of net production that is supported by the introduction of new nutrients into the euphotic zone. Traditionally, this has been regarded as production fueled by nitrate as opposed to more reduced forms of nitrogen, such as ammonia and urea. Some portion of the fixed carbon sinks out of the euphotic zone in particulate form, or is subducted or advected away as dissolved organic material from the surface layers by physical processes. This flux is regarded collectively as export production. The ratio of new (export) to net production, referred to as the f-ratio (e-ratio) can vary between 0 and 1, and is believed to be low in oligotrophic (‘blue water’), low productivity regions, and higher in eutrophic, high productivity regions. Finally, net community production is the total productivity in excess of net community metabolic cost. On sufficiently long space- and time-scales, it can be argued that new, net community, and export production should be equivalent in magnitude. Net production has been measured ‘directly’ by radiocarbon incubation experiments, whereby water samples are ‘spiked’ with radiocarbon-labeled bicarbonate, and the net rate of transfer of the radioisotope into organic matter phases determined by comparison of light versus dark incubations. Global maps of net productivity have been constructed on the basis of such measurements, and current
estimates indicate a global fixation rate of order 50 GT C a1 (1 GT ¼ 1015 g). Rates of export, new, and net community production are more difficult to determine directly, yet are of equal importance as determinants of biogeochemically important fluxes on annual through centennial timescales. Geochemical tracer techniques have been used to make such estimates, and offer significant advantages in that they are fundamentally nonperturbative, and integrate over relatively large space-scales and long time-scales. Conversely, such determinations must be viewed from the perspective that they are indirect measures of biogeochemical processes, and have characteristic implicit space- and time-scales, as well as boundary conditions, and sometimes ambiguities and model dependence. Further, the specific tracer or physical system used to obtain production estimates determines the type of productivity measured. Thus any treatment of geochemical tracer estimates must include a discussion of these attributes.
Measuring Oceanic Productivity with Tracers Just a few approaches will be discussed here. Other techniques have been used with some success, particularly with relation to particle interceptor traps, but this section will concentrate on basic mass budgeting approaches using water column distributions or seasonal cycling of tracers. There are three basic, yet fundamentally independent approaches that can be used. 1. Aphotic zone oxygen consumption rates that, when vertically integrated, provide a net water column oxygen demand that can then be related stoichiometrically to a carbon export flux. 2. Seasonal timescale euphotic zone mass budgets, particularly of oxygen, carbon, and carbon isotopes, which lead to estimates of net community production. 3. Tracer flux-gauge measurements of physical mechanisms of nutrient supply to the surface ocean, which place lower bounds on rates of new production. These techniques, summarized in Figure 1, yield estimates of subtly different facets of biological production. On annual timescales, however, these different modes of production should be very close to equivalent, and hence the results of these various
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Figure 1 A schematic of the upper ocean, showing material fluxes and various tracer constraints on primary production.
measurement approaches should be comparable. As shown below, their quantitative agreement coupled with their essential independence lends an inductive support to the validity of their results.
Aphotic Zone Oxygen Consumption Rates In the surface ocean air–sea gas exchange controls the composition of dissolved gases and phytoplankton release oxygen. Below, in the aphotic (nonsunlit) zone, oxygen is generally undersaturated, because bacterially mediated oxidation of sinking organic material consumes oxygen. Credible estimates of aphotic zone oxygen consumption rates have been made since the 1950s. However, the earliest quantitative linkage to primary production was in 1982. The principle behind it is dating water masses and dividing the age of the water mass into the observed oxygen deficit. Another approach involves correlating water mass age along streamlines with oxygen concentration (older water has less oxygen). This dating can be achieved by a technique such as tritium-3He dating, which uses the ingrowth of the stable, inert noble gas isotope 3He from the decay of the radioactive heavy isotope of hydrogen (tritium), according to: 3
12:45y
H - 3He
If surface waters are in good gas exchange contact with the atmosphere, then very little 3He will accumulate due to tritium decay. Once isolated from the surface, this 3He can accumulate. From the measurement of both isotopes in a fluid parcel, a tritium-3He age can be computed according to: 3 He t ¼ l ln 1 þ 3 ½ H 1
where l is the decay probability for tritium, and t is the tritium-3He age (usually given in years). Under typical Northern Hemispheric conditions with current technology, times ranging from a few months to a few decades can be determined. Although a conceptually simple approach, under normal circumstances mixing must be accounted for because it can affect the apparent tritium-3He age in a nonlinear fashion. Furthermore, in regions of horizontal oxygen gradients, lateral mixing may significantly affect apparent oxygen consumption rates. For example, following a fluid parcel as it moves down a streamline, mixing of oxygen out of the parcel due to large-scale gradients will masquerade as an augmentation of oxygen consumption rates. These issues can be accounted for by determining the three-dimensional distributions of these properties, and applying the appropriate conservation equations. With additional constraints provided by geostrophic velocity calculations, these effects can be separated and absolute oxygen
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_1
Oxygen utilization rate (µmol kg y ) 0
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Figure 2 Aphotic zone oxygen consumption rates as a function of depth for two locales in the subtropical North Atlantic. These consumption rates are based on tritium-3He dating and other tracer techniques.
consumption rates can be computed as a function of depth. Figure 2 shows profiles of oxygen consumption rates as functions of depth for two locales in the subtropical North Atlantic. Integration of these curves as a function of depth gives net water column oxygen demands of 6.571.0 mol m2 a1 for the Sargasso Sea and 4.770.5 mol m2 a1 in the eastern subtropical North Atlantic. Using the molar ratio of oxygen consumed to carbon oxidized for organic material (170 : 117), the flux of carbon from the euphotic zone above required to support such an oxygen demand can be calculated for the two regions (4.570.7 and 3.270.4 mol C m2 a1). The character of these estimates bears some consideration. Firstly, according to the definitions of primary production types described earlier, this represents a determination of export productivity. Secondly, the determinations represent an average over timescales ranging from several years to a decade or more. This is the range of ages of the water masses for which the oxygen utilization rate has been determined. Thirdly, the corresponding space-scales are of order 1000 km, for this is the region over which the age gradients were determined. Fourthly, although the calculation was done assuming that the required carbon flux was particulate material, it cannot distinguish between the destruction of a particulate rain of carbon and the in situ degradation of dissolved organic material advected along with the
water mass from a different locale. These characteristics must be borne in mind when comparing this with other estimates.
Seasonal Euphotic Zone Mass Budgets There have been three basically independent approaches to estimating net community production based on observation of the seasonal cycles of oxygen and carbon in the upper ocean. Photosynthesis in the euphotic zone results in the removal of inorganic carbon from the water column, and releases oxygen (Figure 3). Recycling of organic material via respiration and oxidation consumes oxygen and produces CO2 in essentially the same ratios. It is only that carbon fixation that occurs in excess of these processes, i.e., processes that result in an export of organic material from the euphotic zone, or a net biomass increase, that leaves behind an oxygen or total CO2 (SCO2) signature. Estimates of productivity based on euphotic zone oxygen or carbon budgets are consequently estimates of net community production. Such productivity estimates are characterized by seasonal to annual timescales, and spacescales of order of a few hundred kilometers. In subtropical waters, excess oxygen appears within the euphotic zone just after the onset of
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Total CO2 (µmol kg ) 0
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Figure 3 Euphotic zone seasonal cycles of total inorganic carbon (A) and oxygen (B) near Bermuda. Note the build-up of oxygen anomaly and reduction of total CO2 in the euphotic zone during the summer months due to photosynthetic activity.
stratification, and continues to build up throughout summer months. Use of the seasonal accumulation of photosynthetic oxygen in the upper ocean to estimate primary production is complicated by the fact that it tends to be lost to the atmosphere by gas exchange at the surface. Furthermore, temperature changes due to seasonal heating and cooling will change the solubility of the gas, further driving fluxes of oxygen across the air–sea interface. In addition, bubble trapping by surface waves can create small supersaturations. While such processes conspire to complicate the resultant picture, it is possible to use observations of noble gases (which do not undergo biological and chemical processing) and upper ocean physical models to interpret the seasonal cycle of
oxygen. These calculations have been successfully carried out at a variety of locations, including the subtropical North Atlantic and the North Pacific. In the Sargasso Sea, estimates of oxygen productivity range from 4.3 to 4.7 mol m2 a1. Using the molar ratio of oxygen released to carbon fixed in photosynthesis of 1.4 : 1, the carbon fixation rate is estimated to be 3.270.4 mol m2 a1. There is also a net seasonal decrease in SCO2 attributable to photosynthesis at these locations. Such decreases are simpler to use in productivity estimates, principally because air–sea interaction has a much weaker influence on SCO2. On the other hand, precise measurements are required because the photosynthetically driven changes are much smaller
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TRACERS OF OCEAN PRODUCTIVITY
compared with the background SCO2 levels. Because of these differences, estimates based on SCO2 seasonal cycles offer an independent measure of euphotic zone mass budgets. Finally, differences in the carbon isotopic ratio between organic and inorganic carbon, as well as atmospheric CO2, allow the construction of yet a third mass budget for the euphotic zone. There is a clear carbon isotope signature that can be modeled
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as a function of primary production, air–sea exchange, and mixing with deeper waters.
Tracer Flux-gauge Determinations The third tracer constraint that may be used to determine primary production involves the use of ‘tracer flux gauges’ to estimate the flux of nutrients to
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Figure 4 An approximately 6 year history of surface water 3He isotope ratio anomalies (A) and computed flux to the atmosphere near Bermuda (B).
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10
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the euphotic zone. This approach relies on the premise that the physical mechanisms that serve to transport nutrients to the euphotic zone from the nutrient-rich waters below also carry other tracers in fixed proportion. If the rate at which these other tracers are transported can be determined, and the nutrient to tracer ratio at the ‘source’ is known, then the corresponding nutrient flux may be inferred; that is: FNutrient ¼
Nutrient Tracer
FTracer Source
Inasmuch as there may be alternate, biologically mediated pathways (such as zooplankton migration), such a calculation would serve as an underestimate to the total nutrient flux. Measurements of the rare, inert isotope 3He in the mixed layer of the Sargasso Sea near Bermuda reveal a persistent excess of this isotope over solubility equilibrium with the atmosphere (Figure 4). The existence of this excess implies a flux of this isotope to the atmosphere, which can be calculated using the estimated gas exchange rate. Although 3He is produced in the water by the in situ decay of tritium, it can be shown that only about 10% of the observed flux can be explained by tritium decay within the euphotic zone. The greater portion of this 3He flux arises from the upward ‘exhalation’ of old tritium-
produced 3He from the waters below. That is, the 3 He flux observed leaving the surface ocean is largely the loss of this isotope from the main thermocline. The ocean–atmosphere flux of 3He shows a pronounced seasonal variation, with the greatest fluxes in the winter months. The winter maximum is due to high rates of gas exchange (more vigorous winter winds lead to higher gas exchange rates) and deeper winter convection. This is the time history of the 3He flux out of the upper ocean. The time history of the 3 He flux to the upper ocean may be different. However, the annual mean fluxes must be the same, since the winter mixed layer penetrates below the bottom of the euphotic zone. The annual average 3 He flux from the ocean surface near Bermuda is 1.8470.25%-m d1. To estimate the flux of 3He entering the euphotic zone from below, this flux must be corrected for the in situ production of 3He by the decay of tritium within the euphotic zone, which produces a 3He flux of 0.2070.02%-m d1. The resultant flux is thus 1.6470.25%-m d1. Insofar as there is a strong correlation between the concentrations of this isotope and nutrients within the waters below the euphotic zone (older waters are richer in both 3He and nutrients), the ratio of 3He to nutrient can be employed to compute nutrient flux. Figure 5 is a composite plot of 3He versus nitrate in the upper 600 m over a 3 year period. The slope of the relationship is 0.8770.05 mmol kg1%1.
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TRACERS OF OCEAN PRODUCTIVITY
Applying the flux equation presented above, a nitrate flux of 0.5670.16 mol m2 a1 is computed. Using the average biological C : N ratio of 6.6, this leads to a carbon fixation rate of 3.77 1.0 mol m2 a1. The estimate thus obtained is a local, annual-scale measure of new production. A similar calculation can be made by observing the long-term (decade timescale) trends in thermocline 3 He inventories. The long-term evolution of 3He inventory in the thermocline must respond to the opposing processes of production by tritium decay and ‘exhalation’ upward to the euphotic zone. Knowing the former gives the latter. Using nutrient-3He ratios, a gyre-scale, decadal average estimate of the nutrient flux to the euphotic zone can be obtained. A detailed analysis of the long-term trends of tritium and 3He in the upper 1000 m of the Sargasso Sea, coupled with the observed nitrate : 3He ratios, yields an estimate of 0.7070.20 mol m2 a1. This leads to a somewhat higher carbon fixation rate of 4.671.3 mol m2 a1. This estimate differs from the surface layer flux calculation in that it is a much longer-term average, since it depends on the very long-term evolution of isotopes in the thermocline. Moreover, it represents a very large-scale gyre-scale determination, rather than a local measure: horizons within the thermocline probably connect to regions of higher productivity further north.
Comparing Tracer-derived Estimates Although the various techniques described here are based on differing assumptions, and measure different types of production, they should be mutually consistent on annual or greater timescales. Table 1 is a comparison between the various estimates near Bermuda in the Sargasso Sea. A weighted average of these determinations gives a productivity of 3.670.5 mol (C) m2 a1 for the Sargasso Sea near Bermuda. The determinations are within uncertainties of each
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Table 1 Comparison of tracer-derived estimates near Bermuda in the Sargasso Sea Type of determination
Type of production
Aphotic zone oxygen consumption rates Euphotic zone cycling
Export Tritium-3He dating production
4.5 7 0.7
Net Oxygen cycling community Carbon isotopes New Mixed layer 3He production Thermocline budgets
3.2 7 0.4
Tracer flux-gauge
Technique used
Carbon flux (mol m 2a 1)
3.8 7 1.3 3.7 7 1.0 4.6 7 1.3
other, although they utilize different tracer systems, are reliant on different assumptions, and are virtually independent of each other. This agreement provides some confidence as to their accuracy.
See also Air–Sea Transfer: N2O, NO, CH4, CO. Carbon Cycle. Primary Production Distribution. Primary Production Processes. Tritium–Helium Dating.
Further Reading Falkowski PG and Woodhead AD (1992) Primary Productivity and Biogeochemical Cycles in the Sea. New York: Plenum Press. Jenkins WJ (1995) Tracer based inferences of new and export primary productivity in the oceans. IUGG, Quadrennial Report 1263–1269. Williams PJ and le B (1993) On the definition of plankton production terms. ICES Marine Science Symposium 197: 9--19.
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TRANSITION METALS AND HEAVY METAL SPECIATION J. Donat and C. Dryden, Old Dominion University, Norfolk, VA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3027–3035, & 2001, Elsevier Ltd.
Introduction The transition metals and heavy metals (those with atomic weights greater than 20) enter the ocean via river runoff, wind-blown dust, diffusion from sediments, hydrothermal inputs resulting from reactions of sea water with newly formed ocean crust at midocean seafloor spreading centers, and from anthropogenic activities. Some of these metals (e.g., manganese, iron, cobalt, nickel, copper and zinc) are extremely important micronutrients needed by phytoplankton for various metabolic functions. Several trace metals that are nonconservative with short oceanic residence time (e.g., manganese and aluminum, though the latter is not a heavy metal) are valuable as tracers for circulation and mixing in the ocean. Micronutrient metals, as well as metals like mercury, lead, and silver, which have no biochemical role, can be toxic very low concentrations. Until recently, marine chemists and chemical oceanographers, using sample collection and analytical techniques of the time, could not accurately measure the naturally low concentrations of these metals in unpolluted sea water because of sample contamination problems and lack of instrumental sensitivity. Development of modern techniques for collection, storage, and analysis of uncontaminated samples, plus the development of highly sensitive analytical techniques and instrumentation, have only recently enabled marine trace metal chemists to determine accurate concentrations of these elements in sea water, furthering our understanding of their distributions and chemical behavior in the oceans. These procedural, analytical, and instrumental advancements led to the discoveries that the concentrations of many of these metals were orders of magnitude lower than previously believed, and that the depth distributions (‘vertical profiles’) of transition and heavy metal concentrations result from biological, physical, and geochemical processes in the oceans.
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We now have a basic understanding of the concentrations and distributions of nearly all the naturally occurring elements in sea water. However, it has become increasingly clear that this information alone is insufficient for providing a complete understanding of the biological and geochemical interactions of these metals in the sea. Metals in sea water can exist in different physical forms (dissolved, colloidal, particulate) and chemical forms (ions, inorganic complexes, organic complexes, organometallic compounds) and in different oxidation states (collectively termed ‘species’) within a given chemical form. Knowing the distribution of a metal’s total concentration among these various forms (‘speciation’) is critically important because the different forms can have very different biological and geochemical behaviors, and thus different fates and transport. Before considering the speciation of the transition and heavy metals, we first present a brief overview of the concentrations and distributions of these elements.
Overview: Transition Metal and Heavy Metal Concentrations and Distributions Concentrations of the transition metals and heavy metals vary both horizontally and vertically through the world’s oceans. Table 1 lists the ranges in the oceanic concentrations of the transition metals and heavy metals. For a representation of the North Pacific depth profiles of the elements in the periodic table, including the transition metals and heavy metals (see Elemental Distribution: Overview). The relative rates of supply and removal of the elements determine their horizontal and vertical distributions. These elements are supplied to the oceans primarily by riverine input, atmospheric precipitation, hydrothermal venting, and anthropogenic activities, and they are removed by adsorption onto sinking particles (‘scavenging’) or by incorporation into sinking biologically produced material by active uptake by phytoplankton. On the basis of their vertical profiles, these elements can be classified into one of the following categories: (1) conservative type, (2) scavenged type, (3) nutrient (recycled) type, and (4) mixed type. Figure 1 shows the shapes of the vertical profiles for the conservative, scavenged, and nutrient (recycled) categories and lists the elements that display them.
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TRANSITION METALS AND HEAVY METAL SPECIATION
Table 1 Element
Sc Ti V Cr Mn Fe Co Ni Cu Zn Ga Ge Y Zr Nb Mo Rh Pd Ag Cd In Sn Te La Hf Ta W Re Os Ir Pt Au Hg Tl Pb Bi a
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Oceanic concentrations of transition metals and heavy metals Concentration unitsa
pmol l1 pmol l1 nmol l1 nmol l1 nmol l1 nmol l1 pmol l1 nmol l1 nmol l1 nmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 nmol l1 fmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 pmol l1 fmol l1 fmol l1 pmol l1 fmol l1 pmol l1 pmol l1 pmol l1 pmol l1
North Pacific
North Atlantic
Surface
Deep
Surface
Deep
8 4–8 32 3 0.5–3 0.02–0.5 4–50 2 0.5–1.3 0.1–0.2 12 5 66–187 12–95 2.8 93 370 0.18 1–5 1–10 0.09–1.8 4 1.2 20 0.2–0.4 0.09 41 28–82
18 200–300 36 5 0.08–0.5 0.5–1 10–20 11–12 4.5 8.2 30 100 306–383 275–325 3.9 105 900 0.66 23 1000 0.07–0.09
14 30–60 23 3.5 1–3 1–3 18–300 2 1.0–1.3 0.1–0.2 25–30 1
20 200
0.5 0.4 50–150 0.5–10 60–80 14–50 0.2
1 50–70 1–2 0.3 51 20 0.8 0.3–1.2 2–10 80 3–6 0.02
4.5 0.25–0.5 0.25–0.5 20–30 6 2 1.6 20
100
0.69–4.6 1–10 2.7 10–20 1–1.5 12–15 0.4
32–43 15 0.2–0.4 50–150 1–7 60–70 100–150 0.25
2.7–6.9 350 0.9 8 0.4–1 80–84
17 0.2–0.4 1 60 20
1 nmol l1 ¼ 109 mol l1; 1 pmol l1 ¼ 1012 mol l1; 1 fmol l1 ¼ 1015 mol l1.
Conservative Type
Owing to their low reactivity, conservative type transition metals and heavy metals (V, Mo, W, Re, and Tl) are present in sea water at relatively high concentrations that are in constant proportion to salinity. Conservative metals have long mean oceanic residence times (44105 y), their distributions are considerably homogeneous throughout the ocean due to the ocean’s 1000-year circulation, and their concentrations are controlled by physical processes (e.g., advection and turbulent mixing). Scavenged Type
Scavenged type transition metals and heavy metals (Mn, Co, Ga, In, Te, Pb, Bi, Ce) typically have strong
interactions with particles, short mean oceanic residence times (102 103 y), and low concentrations. Their removal from sea water is dominated by adsorption onto the surfaces of particles and transport to the sediment via interactions with large, rapidly settling particles. Their depth profiles typically show enrichment in surface waters owing to sources from rivers and atmospheric dust, and rapid depletion to low concentrations at depth. Nutrient (Recycled) Type
Metals having nutrient type distributions (Fe, Ni, Zn, Ge, Se, Y, Ag, Cd, Ba, La) are characterized by surface water depletion and enrichment at depth. Surface depletion is caused by biological uptake, and
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TRANSITION METALS AND HEAVY METAL SPECIATION
Type
Profile
Conservative (C)
Increasing depth
Increasing [X]
V, Mo, W, Re, T1
Scavenged (S)
Increasing depth
Increasing [X]
Mn, Co, Ga, In, Te, Hg, Pb, Bi, Ce
Nutrient (or recycled) (R)
Increasing depth
Increasing [X]
Fe, Ni, Zn, Ge, Se, Y, Ag, Cd, Ba, La
enabled oceanographers to make large numbers of measurements of the concentration of a few transition metals across some ocean basins to construct two- and three-dimensional horizontal profiles, instead of just presenting an element’s vertical profile. For example, two-dimensional ocean basin-scale distribution maps have been produced for aluminum and iron. These two-dimensional distribution maps can help identify the input and distribution mechanisms of an element and can be useful as tracers of water mass movements. Although such detailed information has been obtained for a few transition metals and heavy metals, initial measurements of the oceanic concentrations and distributions need to be made for elements such as Ti, Ga, Ru, Pd, Ir, Pt, Au, Re Te, Zr, and Hf in many ocean basins before simple vertical and horizontal profiles can be constructed. Using newly developed analytical techniques, researchers have begun to obtain initial data on these metals. For example, the first concentration data on iridium in sea water (North Pacific) have been reported. Iridium concentrations ranged from 0.5 1015 mol l1 in North Pacific surface waters and increased with depth to a maximum of 0.8 1015 mol l1 near the bottom.
Speciation Introduction
Figure 1 Oceanic profile classifications.
enrichment at depth is due to regeneration of the elements from particles back into solution by bacterial oxidation of the biological particulate matter. Deep waters of the North Pacific and Indian Ocean typically have higher concentrations of these elements than North Atlantic deep waters owing to biogeochemical cycles and ocean circulation. Mixed Type
Some transition metals and heavy metals, such as Cu, Fe, Ga, Zr, Ti, La and other rare earths, have distributions that are influenced by both recycling and scavenging processes. For example, copper displays the characteristic surface depletion and deep-sea enrichment of the recycled element type; however, its concentration increases only gradually (almost linearly) with depth, indicating the effects of scavenging.
Modern Advances Development of new analytical techniques, especially those that can be used at sea aboard ship, have
Knowing the oceanic concentrations and distributions is only part of the picture in understanding the biological and geochemical interactions of transition metals and heavy metals. Dissolved metals can exist in different oxidation states and chemical forms (‘species’). These forms include free solvated ions, organometallic compounds, organic complexes (e.g., metals bound to proteins or humic substances), and inorganic complexes (e.g., metals bound to Cl, 2 OH, CO2 3 , SO4 , etc.). Knowledge of the concentrations of these various species of a transition metal or a heavy metal, in conjunction with its distribution and concentration, is critical to understanding how the various chemical species interact biologically and geochemically. For example, the nutrient availability and toxicity of several transition metals have been found to be proportional to the concentrations of their free metal ions and not their total concentrations. Complexation of a metal by an organic ligand will decrease the concentration of the free ion form of the metal, thereby decreasing its toxicity or bioavailability. Organic complexation may also decrease or increase adsorption of metals onto metal oxide particles. These examples illustrate
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TRANSITION METALS AND HEAVY METAL SPECIATION
the importance of speciation information for fully understanding a metal’s oceanic biogeochemical cycle. Inorganic Speciation
Inorganic forms of the transition metals and heavy metals in sea water include hydrated metal ions, complexes with inorganic ligands, and species with different oxidation states. Transition metals and heavy metals with different oxidation states can exist in sea water when the potential required to change valence states falls within the range of the sea water’s oxidizing/reducing potentials. Examples of transition metals and heavy metals having multiple oxidation states in sea water include Fe(II)/Fe(III), Mn(II)/ Mn(IV), Cr(III)/Cr(VI), and Cu(I)/Cu(II). In oxygenated sea water, the thermodynamically stable form is usually the higher of the two oxidation states. However, species whose existence is thermodynamically unfavorable (i.e., usually the lower oxidation states) can be produced biochemically (e.g., by photosynthesis) and/or chemically (e.g., by photochemistry), as a result of the input of solar energy. Calculational estimates of the inorganic speciation of many of the transition metals and heavy metals in sea water have been given in two landmark papers by Turner et al. and Byrne et al. (see Further Reading). The extent to which a metal is complexed by inorganic ligands is expressed by the inorganic sidereaction coefficient, a. This, in turn, is calculated from eqn[1] where b is the overall conditional stability constant for the inorganic complex MXi of the transition or heavy metal M with the inorganic ligand Xi, and X½0i is the concentration of uncomplexed Xi. a¼1þ
X
bMXi X0i
½1
i
The inorganic side-reaction coefficient, a, is also equal to the ratio of the sum of the concentrations of all inorganic species of the metal Mð½M0 Þ to the concentration of its free hydrated cation M ½Mnþ (eqn [2]). a¼
½ M0 Mnþ
½2
For zinc and the first transition series metals manganese, iron, cobalt, and nickel, the free hydrated divalent cation form dominates the dissolved inorganic speciation. The trivalent metal cations Al3þ, Ga3þ, Tl3þ, Fe3þ, and Bi3þ are strongly hydrolyzed (i.e., they form strong complexes with
Table 2
Influence of pH and temperature on the a of Al3þ
pH
Temperature (1C)
a
7.6 7.6 8.2
5 25 5
105.76 107.23 109.39
Source: Byrne et al. (1988).
OH). With respect to complexation by OH, the inorganic side-reaction coefficients of the strongly hydrolyzed metals range from 105.76 for Al3þ to 1020.4 for Tl3þ, and their inorganic speciation is strongly influenced by pH and temperature. For example, at a pH of 7.6, a for Al3þ increases 300-fold as the temperature is increased from 5 to 251C; and at a temperature of 51C, a for Al3þ increases 4000fold as the pH increases from 7.6 to 8.2 (Table 2). Other important inorganic species are the chloride and carbonate complexes. Chloride complexes are important in the inorganic speciation of Agþ, Cd2þ, and Hg2þ. Unlike the strongly hydrolyzed metals, chloride dominated metals are only moderately affected by temperature and pH. Of this group, Hg2þ is complexed by chloride to the greatest extent. The side reaction coefficient of Hg2þ with respect to chloride is 1015.10 at 51C. Carbonate complexes dominate the inorganic speciation of the lanthanides and some actinides (e.g., U(VI) and La(III)). These carbonate complexes are considerably influenced by temperature and pH, although less than the strongly hydrolyzed metal cations. Organic Speciation
Organic forms of the transition metals and heavy metals in sea water include complexes with organic ligands (e.g., metals bound to proteins or humic substances) and organometallic compounds in which the metal is covalently bound to carbon (e.g., methyl forms of As, Ge, Hg, Sb, Se, Sn, and Te; ethyl-Pb forms; butyl-Sn forms). A most interesting discovery is that 90% of the germanium in open-ocean sea water exists in methylated forms so stable to degradation that they have been called the ‘Teflon of the sea.’ Methyl forms of metals are generally highly toxic because these compounds are soluble in cell walls and accumulate in cells. This accumulation is one example of how a nonessential metal can become biologically available. The organically complexed fraction of certain transition metals and heavy metals in sea water has been reliably estimated only relatively recently, and attempts have been made to characterize the nature of these complexes. Early studies of metal
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TRANSITION METALS AND HEAVY METAL SPECIATION
Table 3
Techniques used to determine the speciation of copper in natural waters
Technique
Limitations/considerations
Referencesa
Fixed-potential amperometry (FPA)
Applicable to high [Cl] solutions only and low organic ligand concentrations (r1000 mol l1) Limited sensitivity and chloride interferences
Waite and Morel (1983); Hering et al. (1987)
Copper ion-selective electrode (ISE) Biological assays Solid-phase extraction (SPE) Competitive equilibration with MnO2 Differential pulse anodic stripping voltammetry (DPASV) Competitive ligand equilibration/ adsorptive cathodic stripping voltammetry (CLE/CSV)
a
Assumes only free metal ion activity causes biological inhibition May underestimate the extent of organically complexed copper in oceanic surface waters Assumes only Cu2þ adsorbs to MnO2 Assumes only inorganic copper is detected and that natural copper complexes dissociate too slowly to be detected Assumes that samples at equilibrium during measurement and that natural copper complexes are not detected (i.e., not electroactive)
Belli and Zirino (1993); Zirino et al., 1998 Sunda and Ferguson (1983); Hering et al. (1987) Mills and Quinn (1981); Hanson and Quinn (1983); Donat et al. (1986) van den Berg (1982) Coale and Bruland (1988); Donat et al. (1994) van den Berg (1985); Donat and Bruland (1990)
See Further Reading list.
complexation showed little agreement between values for ligand concentrations, conditional stability constants, and the extent to which copper was organically complexed, which ranged from 0 to 100%. Organic speciation work on copper, zinc, and iron shows that the organically complexed fraction dominates the dissolved speciation of these metals in oceanic surface waters and is critically important in controlling the free metal ion concentrations of these metals. Although the chemical nature and complete chemical characteristics of the complexing ligands remains unknown, preliminary investigations have shown that the ligands are generally hydrophillic and of low molecular weight. Methods for determining the speciation of transition metals and heavy metals in natural waters include fixed-potential amperometry (FPA), ionselective electrodes (ISE), biological assays, solidphase extraction (SPE), competitive equilibration with MnO2(s), differential pulse anodic stripping voltammetry (DPASV), and competitive ligand equilibration with adsorptive cathodic stripping voltammetric detection (CLE/CSV). Table 3 lists the methods utilized for copper speciation with pertinent limitations and considerations. These techniques involve physical isolation or detection of one of the metal’s species, or of a metal species not originally present in the sample but created for the speciation determination by introduction of a competing ligand. The speciation methods must operate under some general constraints: (1) samples must be at equilibrium, and (2) the technique must detect only the species intended.
Copper The fraction of organically complexed copper in sea water has been determined throughout many of the world’s oceans including the Pacific, Atlantic, and Indian. The percentage of organic copper found in these oceans ranges from 89% to 99.9%. In the surface waters of the North Pacific (i.e., the upper 200 m), more than 99.7% of total dissolved Cu(II) is organically complexed (Figure 2A). The organic complexation is dominated by two coppercomplexing ligands (or classes of ligands), L1 and L2. The stronger L1 ligand class has an average concentration of B1.8 nmol l1 in the upper 100 m and from the surface down to 200 m and its concentration exceeds that of dissolved copper (Figure 2B). The great strength of the L1 class and its excess concentration relative to dissolved copper causes the inorganic copper fraction to account for less than 0.3% of total dissolved copper, and causes the free hydrated Cu2þ to account for only about 0.012% of total dissolved copper. A comparison of Figure 2C with Figure 2B shows that while dissolved copper ranges only from 0.3 to 1.5 nmol l1 (a factor of 5), the Cu2þ concentration ranges from 1013 to 1010 (a thousand-fold)! Measurements made in the Sargasso Sea revealed concentrations of the stronger L1 copper-complexing ligand class to be equal to or less than the dissolved copper concentration, causing the weaker L2 ligand class to dominate organic copper speciation, with a concomitant increase in the inorganic copper fraction and free Cu2þ concentration. Some evidence exists that the ligand concentrations and extent of organic complexation can vary seasonally.
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TRANSITION METALS AND HEAVY METAL SPECIATION % Organically complexed copper 0
0
20
40
60
80
100
100
Depth (m)
200 300 400 500 (A)
600 _
0
Copper and L1 (nmol l 1) 1 2
0
3
100
Depth (m)
200 300 400 500
(B)
600
0
_13
log [Cu _12
2+
_
(nmol l 1)] _11
_10
100
Depth (m)
200 300 400 500
(C)
600
Figure 2 North Pacific surface waters dissolved Cu(II) speciation: (A) depth profile of L1, the stronger coppercomplexing organic ligand; (B) dissolved Cu(II) depth profile; (C) depth profile of free Cu2þ ion as logarithmic concentration values.
Zinc The fraction of organically complexed zinc found in North Pacific waters averages 98.7% (Figure 3A). As with copper, organic complexation of zinc is dominated by a relatively zinc-specific organic ligand (or ligand class) in surface waters shallower than 200 m (Figure 3B). In this upper 200 m, the zinc-
105
complexing ligand averages 1.2 nmol l1 and exceeds the concentration of dissolved zinc at depths above 300 m (Figure 3B). The high degree of organic complexation of zinc in the upper 300 m is caused by the excess in ligand relative to that of dissolved zinc and the strength of its zinc complexes. Organic complexation of zinc reduces the concentration of inorganic zinc species to 2 1012 mol l1. Concentrations of free Zn2þ vary with depth from B1011.8 mol l1, at depths less than 200 m, increasing to B108.6 mol l1 at a depth of 600 m. Iron Fe3þ forms complexes with natural organic ligands (like humic substances) that help keep this very insoluble cation in solution at elevated levels in estuarine and coastal waters. In the North Pacific and in the North Sea, researchers have determined that more than 99% of dissolved Fe(II) is bound with an extremely strong ligand class whose concentration ranges from 1 to 5 nmol l1 and is in excess of the ambient dissolved iron concentration. These ligands have conditional stability constants consistent with low molecular weight organic substances called siderophores, which are produced by bacteria to specifically obtain iron. The availability of iron to aquatic primary producers has become the focus of many research projects since experiments have shown that in certain areas of the world’s oceans iron availability is very low and may regulate productivity and perhaps influence atmospheric levels of carbon dioxide. Other metals Organic complexation of other dissolved transition metals and heavy metals (i.e., Cd, Pb, Co, Ni, and Fe) has been investigated only much more recently and the information on these metals is not as defined or as extensive as for copper, iron and zinc. Recent measurements of dissolved cadmium in the North Pacific revealed that 70% was bound by cadmium-specific organic ligands found only at depths less than 175 m. Inorganic cadmium concentrations varied from 0.7 1012 mol l1 in surface waters to 800 1012 mol l1 at 600 m. The free Cd2þ concentration ranged from 20 1015 mol l1 in the surface, where organic complexation dominates the speciation, to 22 1012 mol l1 at 600 m where chloro complexes appear to dominate the inorganic speciation. In the North Pacific, measurements of dissolved lead in the surface waters revealed that 50% was organically complexed by one class of strong organic ligands found to have concentrations between 0.2 and 0.5 nmol l1. The free Pb2þ surface water concentration as a result of inorganic and organic complexation was B0.4 1012 mol l1.
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TRANSITION METALS AND HEAVY METAL SPECIATION % Organically complexed zinc 0
0
20
40
60
80
100
4
5
100
Depth (m)
200 300 400 500 600 (A) _
Zinc and L (nmol l 1) 0
0
1
2
3
Organic complexation of dissolved cobalt and nickel in the open ocean has not been reported; however, organically complexed cobalt and nickel in estuarine and coastal samples have been found. The fraction of organic complexation is highly variable from estuary to coastal ocean. About 50% of the dissolved cobalt in coastal sea water was found to be organically complexed. In UK coastal waters and south San Francisco Bay, 30–50% of the nickel was bound in extremely strong organic complexes. The information presented in this section demonstrates the importance of organic complexation of several transition metals and heavy metals. These organic ligands exist at low concentrations and form very strong complexes (i.e., they have high conditional stability constants). Although the actual chemical structures of these complexing organic ligands are still unknown, new analytical techniques may soon uncover their structure.
100
How Speciation Relates to Biology
Depth (m)
200 300 400 500 600 (B) _
0
_12
log [Zn2+ (nmol l 1)] _11 _10
_9
100
Depth (m)
200 300 400 500 600 (C) Figure 3 North Pacific zinc speciation: (A) depth profile of zinccomplexing organic ligand presented as percentage of organically complexed zinc; (B) dissovled zinc depth profile; (C) Zn2þ ion depth profile as logarithmic concentration values.
Early researchers suggested that some organic compounds present in sea water in trace quantities may influence the primary production of marine communities by reducing toxic free metal concentrations (especially Cu2þ) to nontoxic levels. Data show that maximum levels of organically complexed copper occur in the surface euphotic zone at depths near the productivity maximum, and decrease dramatically below the vernal mixed layer in the North Pacific. The speciation of dissolved zinc is dominated by organic complexes and it may suggest a biological influence, as discussed for copper. Yet, the reasons for organic zinc speciation are not completely understood and only speculations exist. Laboratory evidence exists for production of a strong copper-binding ligand by four marine phytoplankton (three species of eukaryotes and one prokaryote). The ligand that was produced has identical copper-complexing strength (i.e., similar conditional stability constants) to that of the stronger ligand observed in surface waters of the North Pacific and Sargasso Sea. The production of this L1-like ligand may demonstrate a detoxification mechanism used by phytoplankton to lower the free Cu2þ concentration. Laboratory studies of the sensitivity of phytoplankton to varying Cu2þ concentrations revealed the following trend: cyanobacteria were the most sensitive; diatoms were the least sensitive; and coccolithophores and dinoflagellates showed intermediate sensitivity. Using this laboratory work, researchers are theorizing how cyanobacteria might produce strong L1 ligands to lower the free Cu2þ
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TRANSITION METALS AND HEAVY METAL SPECIATION
concentration in oceanic surface waters to levels at which their growth would not be impacted (o1012 mol l1). During an upwelling event, cyanobacterial production of the L1 ligand might not exceed the newly upwelled Cu2þ, therefore cyanobacteria abundance would decline. Actual field evidence is supporting the speculation that species composition and seasonal species successions of phytoplankton are influenced by Cu2þ concentrations, especially in high-nutrient–low-chlorophyll areas. Growth limitation experiments, like those for copper, have also been performed for iron, zinc, and manganese. These experiments showed that sufficiently low free ion activities of these nutrient metals could result in species shifts in phytoplankton communities. Iron is perhaps the most important nutrient transition metal to phytoplankton and its speciation is extremely complex and is not known with any reliability. Forms of iron that are speculated to have biological importance are organic Fe(III) complexes, Fe(III) oxides, and Fe(III)–siderophore complexes. Unlike Cu2þ which acts as a toxin, increased free Zn2þ concentrations in upwelled water could enhance reproduction of phytoplankton communities. Manganese in sea water, which shows no evidence of any organic complexation, appears to be maintained by photochemical reduction processes and photoinhibition of microbial oxidation of Mn2þ. Low manganese concentrations could potentially limit oceanic productivity if not supplied in sufficient quantities by atmosphere or horizontal mixing. Therefore, the distributions of Zn2þ, Mn2þ, and dissolved iron have important consequences for species composition and species succession of a phytoplankton community. Oceanic concentrations of dissolved cadmium may be outside the range causing cadmium toxicity. However, in estuarine and riverine areas, anthropogenic sources could supply excessive cadmium inputs, leading to cadmium toxicity in aquatic phytoplankton. On the other hand, some researchers have shown that cadmium can promote growth of zinc-limited oceanic phytoplankton by substituting for zinc in certain macromolecules, thereby causing growth at lower than expected free Zn2þ concentrations. It has been speculated that this biochemical substitution of cadmium for zinc by phytoplankton could account for the nutrient-type oceanic distribution of cadmium.
Summary Major advances in procedural, analytical, and instrumental techniques have advanced our knowledge
107
of the concentrations, distributions, and speciation of the transition metals and heavy metals in the oceans, and therefore our understanding of their biogeochemical cycling. For most of the transition metals and heavy metals we have a first-order understanding of their oceanic distributions, and now with more data and better sea-going analytical techniques, basin-wide cross-sections of the distributions of some metals (e.g., aluminum, manganese, and iron) are becoming available. These basin-wide distributions allow more interpretation of sources and fates of these metals. Mediation by light and microorganisms dominates the biogeochemical cycling of certain metals such as copper, iron, and manganese. Organic complexation has come into the forefront of metal speciation research. Not only has the evidence for the existence of organic complexation been overwhelming, but organic ligands dominate the speciation of copper, zinc, and iron in oceanic surface waters. Organic complexation of certain metals in the oceans has important biological implications (i.e., controlling availability of metals as nutrients and toxicants) for phytoplankton.
See also Bacterioplankton. Carbon Cycle. Metal Pollution. Tracers of Ocean Productivity.
Further Reading Belli SL and Zirino A (1993) Behavior and calibration of the copper(II) ion-selective electrode in high chloride media and marine waters. Analytical Chemistry 65: 2583--2589. Brand LE, Sunda WG, and Guillard RRL (1986) Reduction of marine phytoplankton reproduction rates by copper and cadmium. Journal of Experimental Marine Biology and Ecology 96: 225--250. Broecker WS and Peng TH (1982) Tracers in the Sea. New York: Eldigio Press. Bruland KW (1983) Trace elements in sea-water. In: Riley JP and Chester R (eds.) Chemical Oceanography, vol. 8, pp. 157–220. London: Academic Press. Bruland KW, Donat JR, and Hutchings DA (1991) Interactive influences of bioactive trace metals on biological production in oceanic waters. Limnology and Oceanography 36: 1555--1577. Bruno J (1990) The influence of dissolved carbon dioxide on trace metal speciation in seawater. Marine Chemistry 30: 231--240. Burton JD and Statham PJ (1988) Trace metals as tracers in the ocean. Philosophical Transactions of the Royal Society of London Series A 325: 127--145.
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TRANSITION METALS AND HEAVY METAL SPECIATION
Byrne RH, Kump LR, and Cantrell KJ (1988) The influence of temperature and pH on trace metal speciation in seawater. Marine Chemistry 25: 163--181. Coale KH and Bruland KW (1990) Spatial and temporal variability in copper complexation in the North Pacific. Deep-Sea Research 37: 317--336. Donat JR and Bruland KW (1990) A comparison of two voltammetric techniques for determining zinc speciation in Northeast Pacific Ocean waters. Marine Chemistry 28: 301--323. Donat JR and Bruland KW (1995) Trace elements in the oceans. In: Steinnes E and Salbu B (eds.) Trace Elements in Natural Waters, pp. 247--281. Boca Raton, FL: CRC Press. Donat JR, Lao KA, and Bruland KW (1994) Speciation of dissolved copper and nickel in South San Francisco Bay: a multi-method approach. Analytica Chimica Acta 284: 547--571. Donat JR, Statham PJ, and Bruland KW (1986) An evaluation of a C-18 solid phase extraction technique for isolating metal–organic complexes from central North Pacific Ocean waters. Marine Chemistry 18: 85--99. Hanson AKJ and Quinn JG (1983) The distribution of organically complexed copper and nickel in the midAtlantic Bight. Canadian Journal of Fisheries and Aquatic Sciences 20: 151--161. Hering JG, Sunda WG, Ferguson RL, and Morel FMM (1987) A field comparison of two methods for the determination of copper complexation: bacterial bioassay and fixed-potential amperometry. Marine Chemistry 20: 299--312. Li YH (1991) Distribution patterns of the elements in the ocean. Geochimica et Cosmochimica Acta 55: 3223--3240. Millero FJ (1992) Stability constants for the formation of rare earth inorganic complexes as a function of ionic strength. Geochimica et Cosmochimica Acta 56: 3123--3132. Mills GL and Quinn JG (1981) Isolation of dissolved organic matter and copper–organic complexes from estuarine waters using reverse-phase liquid chromatography. Marine Chemistry 10: 93--102.
Nozaki Y (1997) A fresh look at element distribution in the North Pacific. Eos, Transactions of the AGU 78: 221. Quinby-Hunt MS and Turekian KK (1983) Distribution of elements in sea water. Eos, Transactions of the AGU 64: 130--131. Rainbow PS and Furness RW (eds.) (1990) Heavy Metals in the Marine Environment. Boca Raton, FL: CRC Press. Sunda WG and Ferguson RL (1983) Sensitivity of natural bacterial communities to additions of copper and to cupric ion activity: a bioassay of copper complexation in seawater. In: Trace Metals in Sea Water, NATO Conference Series 4, Marine Science, Vol. 9, pp. 871– 890. New York: Plenum Press. Turner DR, Whitfield M, and Dickson AG (1981) The equilibrium speciation of dissolved components in freshwater and seawater at 251C and 1 atm pressure. Geochimica et Cosmochimica Acta 45: 855--881. van den Berg CMG (1982) Determination of copper complexation with natural organic ligands in seawater by equilibration with MnO2. II. Experimental procedures and application to surface seawater. Marine Chemistry 11: 323--342. van den Berg CMG (1985) Determination of the zinc complexing capacity in seawater by cathodic stripping voltammetry of zinc–APDC complex ions. Marine Chemistry 16: 121--130. Waite TD and Morel FMM (1983) Characterization of complexing agents in natural waters by copper(II)/ copper(I) amperometry. Analytical Chemistry 55: 1268--1274. Wong CS, Boyle E, Bruland KW, Burton JD, and Goldberg ED (eds.) (1983) Trace Metals in Seawater. New York: Plenum Press. Whitfield M and Turner DR (1987) The role of particles in regulating the composition of seawater. In: Stumm W (ed.) Aquatic Surface Chemistry, pp. 457--493. New York: Wiley. Zirino A, DeMarco DJ, VanderWeele DA, and Belli SL (1998) Direct measurement of copper(II) (aq) in seawater at pH 8 with the jalpaite ion-selective electrode. Marine Chemistry 61: 173--184.
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TRANSMISSOMETRY AND NEPHELOMETRY C. Moore, WET Labs Inc., Philomath, OR, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3035 –3045, & 2001, Elsevier Ltd.
Introduction Transmissometry and nephelometry are two of the most common optical metrics used in research and monitoring of the Earth’s oceans, lakes, and streams. Both of these measurements relate to what we perceive as the clarity of the water, and both provide vital information in numerous studies of natural processes and human activities’ impact upon water bodies. Applications involving these measurements range from monitoring drinking water suitability to understanding how carbon is transferred into and transported within ocean waters. Transmissometry refers to measurements made by transmissometers or beam attenuation meters. These sensors infer the total light lost from a beam of light passing through the water. These losses are caused by two primary mechanisms. Suspended particles and the molecules of the water itself scatter the light away from its original path; the water, and dissolved and particulate matter contained within, absorb the light and convert it into heat, photosynthetic activity, fluorescence, and other forms of energy. Larger concentrations of scattering and absorbing substances therefore result in greater losses in signal. Nephelometry refers to measurements made by optical scattering sensors, often referred to as turbidity sensors or nephelometers. These sensors project a beam of light into the water and measure the radiant flux of light scattered into the direction of a receiver. Since the receiver signal increases with greater numbers of particles, the device infers the concentration of suspended particles in the water. Scattering sensors are used more commonly in environmental monitoring applications, especially in highly turbid waters with large concentrations of particles; transmissometers see more use in general scientific studies. However, the uses for which they are employed broadly overlap. Nevertheless, transmissometers perform quite different measurements from those of scattering sensors and the quantities they measure are independent of one another and typically offer no direct comparison. In fact, while the data products they provide may covary, the relationship between the values most certainly will
differ depending upon the composition of the materials in the water. Using a transmissometer one can derive an attenuation coefficient that mathematically describes the ability of the water to transmit light. This coefficient is a fundamental optical characteristic and an absolute quantity for a given medium. The scattering sensor, on the other hand, collects a very small portion of the scattered light and is usually calibrated to some secondary standard. The units of measurement are themselves relative to that standard. Other differences also prove crucial in defining these measurements. Limitations imposed by the instruments themselves, application-specific requirements, sensor sizes, and cost all play roles in determining the possible suitability of one measurement versus another. Thus, in order to best fit these two methods to potential applications, it is necessary to understand the measurements, the design of the sensors performing them, and the products that the sensors provide.
Measurements and Fundamental Values In the realm of water sciences, transparency and turbidity are two of the most commonly used terms in describing optical clarity. These are general terms and typically not tied to absolute physical quantities other than through the use of secondary standards. However, the set of underlying optical processes that describe the impact of water-based media upon light propagating through them are well defined, if not completely understood. In the study of the transmission of light energy through water, the inherent optical properties (IOPs) refer to the set of intrinsic optical characteristics of the water and components contained therein. The IOPs define how light propagates through the water. In comparison to apparent optical properties (AOPs), the other general class of in-water optical measurements, the IOPs are not affected by changes in the radiance distribution from sunlight or other sources. The IOPs include coefficients for the attenuation, absorption, and scattering of light as well as the volume scattering function. The coefficients of attenuation (c), absorption (a), and scattering (b) determine radiance losses of a ray of light propagating through the water. Light is either lost to absorption by the water and material
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109
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TRANSMISSOMETRY AND NEPHELOMETRY 3
contained within or it is scattered by the same. The attenuation coefficient accounts for losses attributed to both the absorption and the scattering and is equal to the sum of these coefficients eqn [1].
Dissolved organic matter Particulate absorption Particulate scattering
½1
Total attenuation
_
One determines the beam attenuation coefficient by comparing the radiant flux of a collimated beam of light at source (Fs) with the radiant flux of the beam at a receiver detector (Fd), a finite distance (r) away. This ratio is known as the beam transmittance (T), given by eqn[2] or equivalently by eqn[3].
Total non-water attenuation
2
Attenuation (m 1 )
c¼aþb
Water
Wavelength of most common transmissometers
1
Fd =Fs ¼ T ¼ ecr
½2
c ¼ lnðT Þ=r
½3
Here r is the path length between the source and the receiver. This coefficient is the value ultimately determined by a transmissometer. The attenuation coefficient is expressed in units of inverse meters (m1). Thus, when one refers to water with an attenuation coefficient of 1 m1, the implication is that within a 1 m path the available light within a collimated beam is reduced to 1/e or approximately 37% of its original energy. Within the visible light spectrum the scattering and absorption losses from the water itself remain effectively constant, and thus variability found in field measurements results from non-water particulate and dissolved matter. The extent of absorption-based losses compared to scattering-based losses depend both on the materials being measured and on the spectral configuration of the meters. Both the scattering and absorbing properties of water-based components are prone to variation with the wavelength of light at which measurements are conducted. Variations in the absorption depend heavily upon the amount of colored dissolved organic matter (CDOM) and chlorophyll content. CDOM absorbs very strongly in the blue wavelengths; chlorophyll absorbs heavily in the blue and in addition has a pronounced absorption peak in the deep red portion of the spectrum (676 nm). Absorption by these materials provides the appearance of color to the water. Visually, CDOM laden waters tend to appear brown, and chlorophyll-rich waters appear green. A deep blue cast to the water indicates very low levels of both of these substances. The spectral dependency of the scattering signals is largely due to the size of the particles from which the light is scattered (Figure 1). In addition to the optical loss coefficients, the volume scattering function (VSF) forms another important component of the IOPs in describing the fate
0 400
450
500
550 600 Wavelength (nm)
650
700
Figure 1 Relative contributions of water and non-water scattering and absorbing components are seen in formulation of the attenuation coefficient within ‘typical’ waters.
of light in water. The VSF describes optical scattering as a function of the angle, y, away from the direction of propagation of the incident beam of light. The VSF coefficient, bðyÞ, defines the radiant energy lost into a given angular region of the light scattering and is expressed in terms of inverse meters per steradian. The VSF integrated over the entire spherical volume into which light is scattered provides b, the total scattering coefficient (eqn [4]). ðp
b ¼ 1p bðyÞsinðyÞdy
½4
0
The actual shape of the VSF depends upon the particle field being measured. Specific properties that define this shape include the particle size and shape and the index of refraction. Particle size is probably the single most pronounced factor in defining the VSF in that it dictates the regime of light interaction with the particles themselves. Very small particles that fall within the wavelength of the light impinging upon the particles are subject to molecular or Rayleigh scattering. This interaction is relatively weak, and creates a VSF that is relatively constant with angle. While Rayleigh scatterers are by far the most prevalent in most waters, most of the scattering signal seen by sensors is attributed to particles ranging
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TRANSMISSOMETRY AND NEPHELOMETRY
from 1 mm to >50 mm. The scattering behavior of these particles is typically modeled using Mie theory. Mie theory uses Maxwell’s equations to predict perturbations of an incident planar wave by spherical particles in its path. In general, larger particles will create a greater degree of near-forward scattering. Most scattering sensors are not considered tools for determination of in-water optical properties, but all scattering sensors including turbidity sensors measure the VSF within a given angular region, typically somewhere in the region of 90–1601 with respect to the incident direction of the light. It is perhaps ironic that while these sensors are among the most ubiquitous of in-water optical tools, the VSF is one of the least-characterized of all the IOPs. This is because no single angle measurement can account for the shape of the entire function. This in turn points to a major source of error in all turbidity-based measurements. Different materials dictate different VSFs and a single angle measurement will vary with concentration from one type of material to the next. In actual fact a diverse amalgam of organic and inorganic particulates reside within most waters. This ultimately tends to homogenize the VSFs such that the variability in the VSF of the composite is less than the variability of individual components (Figure 2). Most scattering measurements are based upon some standard such as formazin, diatomaceous earth, or more recently spherical styrene bead suspensions. These standards are used because they tend to be reproducible and easy to mix into various concentrations for calibrations. Units of quantity are expressed in form of turbidity units such as NTU (nephelometric turbidity units). Because of the _3
10
Normalized VSF
disparate VSFs of these standards and natural waters, total attenuation (or particle concentration) cannot be obtained from turbidity measurements without intercalibrating with transmissometers (or by filtering and weighing) in natural waters.
Sensors Transmissometers
A basic transmissometer consists of a collimated light source projected through an in-water beam path and then refocused upon a receiver detector. Typically single-wavelength transmissometers employ a light-emitting diode coupled with an optical bandpass filter as the source. Source light is often split so that a portion of the beam impinges upon a reference or compensation detector that is either used in numerical processing of the data or integrated into a source stabilization feedback circuit. The source output is often modulated and the lamp and receiver detector samples are in phase with the source modulation. This greatly reduces ambient light detection by the receiver from the sun or other unwanted sources. Path lengths are fixed with distances typically ranging from 5 cm to 25 cm depending upon the waters in which the sensors are used (Figure 3). The receiver detector converts radiant flux into current and its output is thus proportional to the radiant energy passed through the water. Electronics subsequent to the detector amplify and rectify the signal for digitization or direct output as a DC voltage level. This signal is known as the instrument transmittance (Ti) (eqn [5]).
Open Ocean
1
San Diego Harbor
10
111
California Coast
_4
23
4 5 6
8
11 10
9
12 13
14
This is a common scattering angle for many nephelometers
10
10
_5
7 _6
10
_7
0
50
100 Angle (deg)
150
200
Figure 2 Normalized VSF data for three representative ocean water types. Note that at 901, the most common nephelometer scattering angle, significant differences exist for the respective coefficients. Data collected by Theodore Petzold and Seibert Duntley of Scripps Institute of Oceanography.
15
Figure 3 Cutaway view showing the primary optical components found in a modern transmissometer. A transmitter assembly and receiver assembly are mounted and aligned within a rigid frame. The transmitter assembly consists of (1) a source lamp; (2) a pinhole aperture; (3) a collimating lens; (4) field aperture; (5) an interference filter; (6) a beam splitter; (7) a reference detector; and (8) a pressure window. The beam (9) then passes through a fixed-path volume of water and enters the receiver assembly. The receiver consists of (10) a pressure window, (11) field aperture, (12) a refocus lens, (13) a pinhole aperture, and (14) the receiver detector. Signals from the detector are then fed to the electronics for processing and output (15).
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Ti ¼ S T
½5
S represents the instrument transmittance scaling constant. This constant is a combined term that includes signal amplification, losses through windows and lenses, and other sensor gain factors. From eqn[5] and assuming a 25 cm pathlength, we obtain eqn[6] or equivalently eqn[7]. Ti =S ¼ ecð0:25Þ
½6
c ¼ 4ln Ti Q
½7
The constant Q ¼ 4 ln S is a general scaling term that is removed, or compensated for, during the calibration process. An ideal transmissometer would reject all but the parallel incident light into its receiver. This implies that there is no error associated with near-forward scattered light getting into the receiver. However, limitations in real-world optics make this a near impossibility. Transmissometers thus provide a value for a system attenuation coefficient that has a finite scattering error and is defined primarily by the acceptance angle of the receiver optics. These values range from around 0.51 to 11 in water for most commercial instruments. Because that VSF for inwater particles is highly peaked at these angles, this can result in underestimation of the attenuation coefficient and can also lead to sensor-to-sensor discrepancies in measurement. It thus becomes important to know this angle in treating data carefully. While it is possible to build sensors with narrower acceptance angles than 0.51, scattering in the very near-forward direction becomes dominated by turbulent fluctuations in the density of the water itself. This turbulence-induced scattering is irrelevant to particulate studies and, depending upon the distances and receiver sizes involved, to most signal transmission applications. The conceptual framework for the transmissometer measurement involves starting with a full signal and monitoring small negative deviations from it. The sensitivity of the instrument thus depends upon its ability to resolve these changes. In many oceanic and other clear water investigations, signal changes as small as 0.001 m1 become significant. In a 25 cm instrument this implies a requirement for transmittance resolution on the order of 0.025%. At the other end of the environmental spectrum, many inland waterways and some harbor areas would render a 25 cm path instrument ineffective due to loss of all signal. Therefore, range and resolution become the two critical factors in determining a
transmissometer’s effectiveness in a given application. While it is easy to imagine using arbitrarily long path lengths to obtain increased sensitivity, the instrument path begins to impose other limitations upon its utility. Size and mechanical stability both reduce utility of the longer path instruments. On the other hand, shorter paths impose more demands than just high levels of precision in measurement. Cleaning of optical surfaces also becomes a major issue in maintaining sensor reproducibility and accuracy. Again using the 25 cm path length instrument as an example, maintaining signal reproducibility of 0.01 m1 over time requires a cleaning technique that gives results that repeat within 0.25% transmittance. For a 10 cm path length instrument, repeatability would need to be within 0.10% transmittance. Likewise, internal correction mechanisms such as compensation of temperature-related drift impose stringent requirements upon the sensor’s electronics as well as the subsequent characterization process. Long-term drift and general mechanical stability also must be tightly constrained for the instrument to provide accurate results over time. The requirements prove challenging in light of the forty degree (centigrade) temperature swings and the 6000 meter depth excursions to which the instruments potentially get exposed. While the calculation of the attenuation coefficient from raw transmittance is independent of the crosssectional area of the beam, the beam size does play an important role in the transmissometer’s ability to measure. Accurate transmittance measurements rely upon the water and the materials it contains acting as a homogenous medium. This model starts to break down in two important cases: when the number concentration of particulates becomes significantly low compared to the total volume of the illuminated sample area; and when the particle sizes become significantly large in comparison to the cross-sectional area of the beam. Taken in the extreme, one can easily imagine a very narrow beam providing a binary response at the receiver depending upon whether a particle occludes its path. Practically speaking, most transmissometers need to show minimal spiking for particle sizes up to 100 mm diameter. Particles more than a few micrometers in diameter are ‘seen’ by the receiver at about two times their actual size as a result of diffraction. This means for a beam of 5 mm nominal width that a single 100 mm particle could reduce signal at the receiver by approximately 0.08% or on the order of 0.0032 m1 in a 25 cm path (or 0.008 m1 in 10 cm path). This proves acceptable for most operational conditions. On the other hand, a 1 mm particle could create an 8% deviation in sensor output, creating a noticeable
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TRANSMISSOMETRY AND NEPHELOMETRY
spike. Fortunately, 1 mm particles are extremely rare except in active erosion zones. There are presently two primary methods used in calibrating transmissometers. The first uses fundamental principles of beam optics and knowledge of the index of refraction difference between air and water to directly estimate the sensor output. Electrooptical linearity in response to signal changes is assumed or verified. The sensor’s gain level is set near full scale for transmission in air and the sensor is checked to ensure that if the source output is completely blocked it provides a real zero output. Accounting for the differences in reflection and transmission of the air–glass interfaces compared to the water–glass interfaces, one can then assume that, upon immersion, any further deviations in signal are due to the attenuation of the water and materials contained therein. This measurement is then verified by immersion in clean water and subsequent comparison to clean water values. Error terms in this method usually include deviations of the modeled optics from the real world. These errors include lensinduced focusing aberrations, alignment issues, spectral content of the source, and any dust or film on any of the optical components. The primary advantages of this method are that the calibration process relies only upon the air value measured by the meter, and that the attenuation due to the water is included in the water-based measurements. The second method involves blanking the meter directly with clean water. More akin to calibration approaches used in spectrophotometry, this method involves immersion of the instrument into optically clean water, measuring the value, and setting that value as full-scale transmittance or, conversely, 0.000 m1 attenuation (clean water values for the attenuation can then be added back in accordance with published values). The chief disadvantage of this method lies in the difficulty of creating and verifying optically clean water. While various levels of filtering can remove most of the particulates from the water, filters can also introduce bubbles. These bubbles are seen as particles by the sensor. Assuming that one achieves filtration without introducing any bubbles, bubble creation is still a concern in that any partial pressure imbalances between the gases contained within the water and the surrounding environment will result in subsequent bubble formation. Added to that is the possibility that the containers and the sensors themselves may also act as sources of particulate contamination. The chief advantage of this method is that it accommodates for small deviations in the real instrument with respect to the ideal. The overriding issue with calibration of transmissometers is the same as in the discussion of the
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need for and difficulty of proper cleaning. In order to calibrate an instrument to operate accurately in cleaner waters, the calibrations must achieve accuracy to within 0.25% of full-scale measurement. Ultimately, reproducibility of results becomes the best check for calibration. That said, this level of accuracy is really only required in conditions where particle concentrations are approaching minimal levels. Relative changes of transmittance will still be precisely reflected in the instrument’s measurements.
Scattering Sensors A simple scattering sensor consists of a source element projecting a beam of light in the water and a receiver detector positioned at a fixed angle with respect to the source. The source beam is sometimes stabilized by inclusion of a second receiver that receives a portion of the light coming directly out of the lamp. This signal is then fed back into the lamp driver circuitry to compensate for fluctuations in the source with time and temperature. The source beam has a defined primary projection angle and a distribution of light about that angle. Conversely, the receiver is placed at a specific angle and maintains a defined field of view about that angle. These factors combine to form the distribution of angular response for the scattered light (Figure 4). As with transmissometers, it is necessary to reject ambient light from the sun and other non-sensor sources during measurement. With scattering sensors this is achieved both through the use of synchronously modulated light and detector amplification and also through the use of direct optical rejection. Direct optical rejection is employed at the source through the use of relatively narrow spectral band sources that emit light in the infrared away from the waterpenetrating wavelengths of sunlight. Accordingly the receiver incorporates narrowband optical filters that
Figure 4 Typical scatter sensors and transmissometers.
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reject wavelengths away from the primary emission bands of the source. Specific angular configurations used in modern scattering sensors vary widely. Some sensors are designed to operate within a highly constrained, narrowband, angular relationship, and some are designed to collect as much scattered light as possible and thus encompass a very wide angular range. In general two truths hold for all the designs: they will all provide a roughly linear response that is proportional to the particle concentration (at least in low to moderate concentrations); and different optical configurations will demonstrate different absolute response curves with respect to each other even when calibrated with the same standard (Figure 5). A scattering sensor works by the simple principle that when particles are present they will scatter light and the receiver will collect some of that light. Using Beer’s law, which states that increasing concentrations will result in a linear increase in output signal, the sensor’s output varies from a zero value in clean water to a full-scale value at the upper end of its range. While it is convenient to assume a linear response with concentration, this is not strictly true. Light reaching the volume of interaction and the light scattered back into the detector is subject to secondary losses due to attenuation. As the concentration of scattering components in the water increases, so does the attenuation. This produces a nonlinearity in the output signal. In sensors with large interaction volumes and a wide angular response, this becomes a particularly messy analytical problem in that the light is subject to a large range of effective path lengths in propagation from the source and back to the receiver. In the extreme case, sensors exist that position a near-isotropic source next to a
Figure 5 One of many possible optical configurations for a scattering sensor. A source assembly consisting of a LED lamp, reference detector, lens, and right angle prism projects light into the water. The receiver is placed to receive light at 901 with respect to projected source beam.
wide-angle detector such that they both project out, perpendicular to the same plane. In these sensors the effective volume of interaction is strictly a function the attenuation coefficient in that it is infinite other than for induced losses of light. As with transmissometers, the volume of interaction also affects a scattering sensor’s sensitivity and the effect of larger particles upon the signal. Small volumes show less sensitivity and measure larger particles as signal spikes. The combined issues of long-path attenuation coupling and volumetric sensitivity point to the preference of designs incorporating larger beams with greater interaction volumes for measurements of cleaner waters and narrower beams with interaction volumes close to the sensor surface for use in highly turbid waters. The response of a given scattering sensor is very highly dependent upon its specific optical configuration. Angle of interaction, angular distribution, wavelength at which the source emits, and the relative path distance from the source and back to the receiver are all factors in how a sensor will behave. As mentioned earlier, it should be expected that two different designs will provide two different responses. In studies in which researchers require only relative responses with space or time, this is not a major issue. A twofold change in a given concentration of particles will generate an associated response in the instrument output. However, many studies require some form of reproducible results. It is not enough that two sensors are calibrated to the same medium. They must also respond in the same way to any other medium that they might mutually measure. Standards such as ISO 7027 have been published. These standards impose constraints on the angle of interaction between the source and the receiver (901), the angular distribution of the source, and its wavelength of operation, as well as other design parameters. The goal is to ensure that all sensors built within the constraints imposed by the standard will provide similar results in similar waters. This is a very important step toward achieving consistent results amenable to intercomparison. Straightforward in concept, sensor calibration employing a standard suspension, provides several pitfalls in practice. First and foremost, no calibration can be achieved to better accuracy than the standard solutions themselves. Secondly, it is critical to ensure that the container in which the calibration takes place is not a cause of secondary reflections of light that can get back to the receiver. Care must also be taken to ensure that the suspension is not settling or flocculating during the measurement. Finally, one variation of this technique is to use arbitrary
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TRANSMISSOMETRY AND NEPHELOMETRY
concentration of the calibration media and calibrate against another ‘standard’ precalibrated sensor. Great care should be applied when using this method. Standard sensors often already incorporate compensation schemes for linearizing the data. These schemes in turn are developed for use with a specific type of suspension. This can create dramatic and surprising results when using another suspension. While scattering sensors are predominantly used to determine relative concentrations of particulates, another very important set of applications involve characterization of the volume scattering function itself. One of the important goals in observational oceanography involves the use of remotely sensed data from satellites and other airborne platforms to rapidly characterize large areas of surface and near surface waters. Of particular interest are the emerging methodologies associated with using ocean color data captured from airborne and space-borne platforms to provide information about the biology and chemistry of waters. In the United States, NASA projects such as the Coastal Zone Color Scanner and the more recent SeaWiFs satellite program stimulated this interest, and in the case of SeaWiFs continue to contribute a growing body of information. The light that these platforms receive is a function of the sea surface state and the resultant reflections and the water-leaving radiance. This radiance in turn is defined by the absorption and scattering characteristics of the water. Scattering in the region of 90– 1801 is specifically important because it represents incoming light from the sun that is scattered back into the atmosphere. To quantify this, a class of sensors called optical backscattering sensors have been developed and calibrated specifically for this purpose. In many respects these sensors are very similar to other scattering sensors in that they use the same basic optical configurations and respond similarly to variations in the particle field. The major differences involve design constraints upon the wavelengths of the source emitters and the angles of interaction. Equally importantly, the calibration of these sensors involves tying the sensor response directly to the volume scattering function. Calibration of scattering sensors for radiometric measurements involves detailed knowledge of the sensor optics geometry and some known scattering agent. The prevalent method for single-angle measurements incorporates a sheet of highly reflective diffuse material and maps the sensor response as a function of the distance between the target and the sensor. This information is then applied to derive the angular weighting function of the interaction volume. Finally, this weighting function is applied to a typical ocean water VSF. More recently, researchers
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have begun to apply a calibration technique that incorporates known concentrations of scattering agents with well-defined VSFs. These two techniques address different elements of a sensor calibration and may well find optimum effectiveness when used in conjunction with one another (Figure 5).
Applications Domains of Use
The use of transmissometers and nephelometers falls broadly into two categories. We want to study the water’s optical properties and how they might relate to ongoing processes occurring in the water, and we want to determine how much foreign matter is in it. While, ultimately, both thrusts of study lead to measurement of the same media within a given body of water, the products that the instruments provide differ, and the requirements surrounding the given areas of study tend to drive the development of the different technologies. The factors ultimately determining the appropriateness of one sensor versus another do not always pertain to the data products provided. Size, cost, ease of deployment, ease of maintenance, and researcher’s experiences all contribute to decisions on which type of sensor is the best to use. Optical oceanographic research motivated much of the development of modern transmissometers. This arena also stimulated development of scattering sensors that are specifically designed and calibrated for providing coefficients related to the VSF. Much of this work in the United States revolves around Naval research needs, and primary development of sensors now available commercially was in large part funded through Naval research dollars. Naval applications include mine hunting, underwater tactical assessment for diving operations, and sea truthing for laser communications and imaging research. The US National Aeronautics and Space Administration (NASA) has also played a major role in developing underwater tools for optical characterization. These tools help calibrate the airborne sensors. Similarly, numerous other governments foster the development and use of these tools through their respective Naval, space and other scientific agencies. While not engaged in the study of ocean optical properties per se, many other ocean scientists working under aegis of funds supplied by these agencies use transmissometers and optical backscattering sensors in ongoing efforts to understand physical, biological, and chemical distributions and processes in the water. Scattering sensors remain the dominant optical tools used by environmental researchers. These
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sensors’ size and cost make them widely affordable and easily used, and the newer sensors incorporate fouling-retardant features such as shutters and biocidal exposed surfaces. As such they are becoming increasingly subscribed to as the sensor of choice in compliance-driven monitoring applications developed by various governmental agencies throughout the world. Naturally, the more attractive size and costs of scattering sensors also make them favorable choices in many larger-scale applications. It is likely that remote sensing will to some degree change preferences for sensors among fresh water researchers over the next ten years. Presently there is relatively little airborne color data available for fresh water bodies, and thus many limnology researchers have not yet been compelled to measure optical properties of lakes directly. With the next generation color airborne sensors and new governmental mandates driving more effective broader-scale sampling strategies, the need and desire for transmissometer measurements and scattering measurements for VSF determination will undoubtedly grow. How Sensors are Deployed
One major constraint in an underwater sampling is how to use the instrumentation effectively in the environment for which it is intended. Researchers often want to measure the water in places they cannot easily get to, or over timescales that make personal attendance of equipment an unappealing proposition. To these considerations must be added the requirement that the data gathered must truly reflect changes at the time and space scales of the governing processes within the water column, and the constraint imposed by doing this sampling at a reasonable cost. The sampling challenge becomes formidable. As a result, the development of effective sampling platforms has become as challenging and competitive a discipline of research as instrumentation design itself. Transmissometers and scattering sensors are typically integrated into multiparameter sampling packages for acquiring and storing data (CTDs, data sondes, loggers). The packages are then deployed from boats or other platforms and lowered through the water column, travel on or are towed by a vessel, or are placed on buoys or mooring lines in order to log measurements over an extended period. Many variations of these basic methods exist but virtually all entail these basic concepts. A new class of autonomous deployment platforms will serve to revolutionize underwater sampling. These range from miniature programmable underwater vehicles, to freely drifting ocean profilers that
can continuously move through the water column, and to rapidly deployable profiling moorings. Many flavors of these various platforms are now emerging. Some will find important niches for acquisition of data over space and time. Some Current Applications
There are many different applications engaging the use of transmissometers and scattering sensors. Table 1 represents only a sampling across numerous disciplines. Extending Capabilities
As mankind’s need to understand and monitor the Earth’s waters has increased, they have driven the development of more rugged, more reliable, smaller, and cost-effective technologies for transmissometry and nephelometry as measurement techniques. These resultant technologies have not only carved greater roles for optical measurement methods but have also proved seminal in the development of entirely new sensors. Recently, a new generation of IOP tools has been made available to the oceanographic community. They include sensors for the determination of the in-water absorption coefficient, multiangle scattering sensors, and a set of IOP tools with spectral capabilities. Transmissometers and simple scattering sensors have laid the foundation for the optical techniques and data methods of these new devices. In turn, these new sensors promise to significantly enhance the role of IOP measurements in modern observing platforms. One of the more significant recent breakthroughs in optical measurement techniques lies in the development of the absorption meter. This sensor uses a measurement method and optical geometry similar to a transmissometer except that it encompasses the sensor’s beam path with a reflective tube and incorporates a large-area detector at the receiver end of the path. The reflective tube and large-area detector combine to collect the bulk of the light scattered from the source beam. Thus the light not detected is primarily due to absorption by the water and its constituents. The wide-band spectral nature of sunlight coupled with the selective filtering capabilities of water and the absorption characteristics of phytoplankton and dissolved organic material make spectral optical characterization of the water highly desirable. Likewise, the spectral information from the scattering of particles provides more direct correlation with remote color data as well as a more complete description of the type of particles scattering. New tools encompassing spectral attenuation, absorption,
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TRANSMISSOMETRY AND NEPHELOMETRY
Table 1
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Applications of transmissometry and nephelometry
Application
Description
Monitoring terrestrial runoff and impact of industrial inflows on water quality
Scattering sensors stationed in rivers and streams allow researchers to determine impacts of inflows upon water quality. Inflows might be created by logging, agriculture, mining, land development, controlled and uncontrolled outflows from water treatment plants, natural runoff and other events that introduce new matter into the monitored bodies. Compliance monitoring United States’ compliance monitoring of fresh water bodies is soon likely to include turbidity as a required parameter for ongoing measurement. Determining biological distribution in the water Both transmissometers and scattering sensors are deployed in viewing the biological variability in space and time through the water column. Radiative transfer studies – optical closure In verifying the optical relationships between the inherent and apparent optical properties, researchers seek to test the relationships through direct measure and comparison of values from the disparate instrument types. Scientists also seek to reconcile measurements of the inherent properties among themselves in validation of IOP theory. Remote sensing validation Satellite and other airborne remote imaging systems require in-water transmissometry, scattering, and absorption measurements to calibrate these sensors to water-borne optical properties. Studying the benthic layer processes In understanding the processes effecting the settling and re-suspension of particles near the bottom of the water column both scattering sensors and transmissometers can provide relative indications of particle flux. Frazil ice formation Transmissometers have been shown to ‘see’ signal fluctuations associated with the formation of frazil or supercooled ice. These studies are imperative in understanding how polar ice sheets are formed. Diver visibility Navies require better tactical assessment of waters for determining operational risk for divers and other visibility-related operations. Small-scale structure in the water column In coastal regimes many physical and ecological processes take place on smaller time and space scales than previously thought. The speed of acquisition and sensitivity of modern scattering sensors and transmissometers allow accurate particulate mapping within the water column, which in turn serves as a tracer for these processes. Tracking particulate organic carbon Data from transmissometers has been shown to accurately reflect total particulate organic carbon within the water column. Understanding in-water carbon transport processes is, in turn, vital to understanding carbon flux between the water and atmosphere through the uptake and output of CO2. Tracking bloom cycles Transmissometers on moorings located both in open ocean and in coastal areas track seasonal bloom cycles as well as event-driven changes from major storms or other potential system disturbances. Monitoring activity around thermal vents and Scattering sensors on moorings and underwater vehicles track plumes from underwater volcanoes underwater vents and eruptions.
and scattering are now commercially available. These tools are playing increasingly important roles in various applications. Despite the plethora of scattering sensor data available, very little information exists concerning the range of variability of the VSF, and how it relates to different water masses and the processes within them. One of the chief constraints in fully characterizing the VSF is that it requires a multiangle scattering measurement encompassing in excess of 4 orders of magnitude of scattered light intensity. After some seminal work performed by researchers at the Scripps Institute of Oceanography during the late 1960s and early 1970s, very little has since been done to add to this body of data. In fact, VSF functions measured then remain de facto calibration
standards for instruments being built today. In recent years researchers in Europe and the United States have refocused attention upon this issue. As a result, a new set of multiangle scattering sensors is now coming into commercial availability. Other development efforts and new instrumentation incorporate scattering and transmittance measurements in unique ways to obtain specific underwater chemical and biological components. One example of these includes an underwater transmissometer that uses polarized light to determine concentrations of particulate inorganic carbon. These instruments promise to fill a vital niche in understanding the fate of carbon in the seas. Another example in development are underwater flow cytometers. While the prevalence of IOP measurements
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look at bulk phase phenomena, new instruments are now available as ship-board and dock mounted units that couple scattering and fluorescence measurements of individual cells and organisms to provide identifying signatures. Patterned after laboratory flow-cytometers, the in water devices will offer break-through capability in typing specific organisms in their natural environment. One of the most exciting aspects of the recent advancements in IOP-related technologies lies in the opportunities offered by their combined use. One marked example lies in the characterization of particle aggregations in the water. While the attenuation or scattering at one wavelength will provide data about relative concentrations of particles within the water column, spectral data from these sensors combined with absorption measurements can move us a long way toward characterizing the aggregation into various biological and inorganic components.
deflected. While these sensors play an increasing role in observing in water processes, they also provide a technological foundation for a new generation of sensors that extend IOP capabilities. These new sensors hold the ability to determine absorption coefficients, to determine coefficients as a function of wavelength, and to characterize the volume scattering function at more than one angle. These improvements not only allow more complete characterization of natural waters but also provide a tangible means of relating remotely sensed data from air and space to in-water processes.
See also Optical Particle Characterization. Radiative Transfer in the Ocean. Turbulence Sensors.
Further Reading
Summary Transmissometry and nephelometry provide increasingly valuable information relating to the lighttransmitting characteristics of water as well as an idea of the relative concentration of suspended material within lakes and oceans. While sometimes viewed as near-synonymous techniques, these methods use different measurement methods, provide different products, and have different strengths and weaknesses in considering the applications to which they are applied. Applications vary widely and across numerous disciplines, but tend to be divided into two major classes: those that attempt to characterize the fundamental optical properties of the water; and those that seek the relative concentrations of foreign particulate matter in the water. In general, nephelometry is the preferred technique in environmental and fresh water applications and transmissometry is more common in oceanographic research. Although transmissometry and nephelometry differ as measurement techniques, in their application domains, and in subsequent calibration and handling, all of these sensors are capable of providing outputs in terms of absolute coefficients that describe the fate of light passing through water. These coefficients of light transfer are collectively known as the inherent optical properties or IOPs. Their values are related through the volume scattering function that describes scattering as a function of angle into which light is
Bogucki DJ, Domaradzki JA, Stramski D, and Zaneveld JRV (1998) Comparison of near-forward light scattering on oceanic turbulence and particles. Applied Optics 37: 4669--4677. Bricaud A, Morel A, and Prieur L (1981) Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains. Limnology and Oceanography 26: 43--53. Greenberg AE, Clescerl LS, and Eaton AD (eds.) (1992) Standard Methods for the Examination of Water and Wastewater 18th edn. Washington, DC: American Public Health Association, AWWA, WEF. Jerlov NG (1976) Marine Optics. Amsterdam: Elsevier. Kirk JTO (1994) Light and Photosynthesis in Aquatic Ecosystems. Cambridge: Cambridge University Press. Mobley CD (1994) Light and Water: Radiative Transfer in Natural Waters. New York: Academic Press. Pegau WS, Paulson CA, and Zaneveld JRV (1996) Optical measurements of frazil concentration. Cold Regions Science and Technology 24: 341--353. Petzold TJ (1972) Volume Scattering Functions for Selected Ocean Waters. Reference Publication 72–28. La Jolla, CA: Scripps Institute of Oceanography. Tyler JE, Austin RW, and Petzold TJ (1974) Beam transmissometers for oceanographic measurements. In: Gibbs RJ (ed.) Suspended Solids in Water. New York: Plenum Press. Zaneveld JRV, Bartz R, and Kitchen JC (1990) A reflectivetube absorption meter. Ocean Optics X, Proceeding of the Society for Photo-Optical Instrumentation and Engineering 1302: 124--136.
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TRITIUM–HELIUM DATING W. J. Jenkins, University of Southampton, Southampton, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3048–3056, & 2001, Elsevier Ltd.
Introduction: Tritium in the Oceans Tritium (3H) is the heaviest isotope of hydrogen. Its nucleus consists of one proton (making it hydrogen) and two neutrons. Inasmuch as it is chemically hydrogen, tritium exists within the global environment primarily as part of the water molecule. Thus it is a potentially useful tracer of the hydrologic cycle, and an ideal tracer of water motions within the ocean. Tritium is radioactive, decaying with a halflife of 12.45 years to the stable, inert daughter isotope 3He. Because of its geologically short half-life, there is very little natural tritium in the environment. Small quantities are created by cosmic ray spallation (i.e. the smashing of atomic nuclei into small fragments by high-energy cosmic rays) in the upper atmosphere. The balance between production and radioactive decay leads to a global natural tritium inventory of approximately 4 kg. This natural inventory was dwarfed by the production of tritium by the atmospheric testing of nuclear fusion weapons during the 1950s and early 1960s. During this period, several hundred kilograms of tritium were released, largely late in the test series, and primarily in the Northern Hemisphere. The
detonations generally injected the tritium into the stratosphere, where it was quickly oxidized to form water vapor. Over a period of a few years, the tritiated water vapor was transferred, largely at mid-latitudes, to the troposphere, where it was rapidly ‘rained out’ to the earth’s surface. The delivery of bomb tritium to the earth’s surface was monitored by a number of WMO/IAEA (World Meteorological Organization (UN)/International Atomic Energy Authority) precipitation sampling stations. The pattern and timing of this delivery has been shown to consist of two primary components: a dominant northern, spike-like component, and a weaker southern component. Due to the geographic nature of the coupling between the stratosphere and the troposphere, tritium concentrations were elevated in both components toward higher latitudes, and weaker near the equator (Figure 1). Tritium levels in precipitation over land also tended to increase with altitude. The northern component reflects the more immediate injection of bomb tritium into the northern hemispheric hydrologic system because virtually all of the major detonations occurred in the Northern Hemisphere. Prior to the bomb tests, the concentration of natural tritium in rainfall was of the order of 5–10 tritium units (1 TU ¼ 1 tritium atom per 1018 normal hydrogen atoms). During the mid-1960s, tritium concentrations of more than several thousand TU were recorded in higher latitude, mid-continental locales such as Chicago, USA or Ottawa, Canada. The southern component, on the other hand, is much weaker in amplitude and more smeared out in time
Northern Factor
Southern Factor
_ 50 0 50 100 150 200 250 300 350 400 500
_ 200 0
5
10 15 20 25 30 35 40
Figure 1 Spatial pattern of the two dominant principal components of bomb tritium in precipitation. These were derived from a statistical analysis of the time variation of bomb tritium in precipitation by S. Doney.
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6 Northern Factor
Annual tritium flux
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1975 Year
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Vapor exchange Precipitation Runoff Southern inflow Arctic flow
2 1.5 1 0.5
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0 1950
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Figure 2 Time history of the two dominant principal components of tritium in precipitation. Note that the northern component (red curve) is more spike-like and the southern component (blue curve) is more ‘smeared out’ in time.
Figure 3 The various modes of tritium deposition to the North Atlantic over time. Note that during the peak of bomb-testing, vapor deposition was dominant, but that after the early 1970s, the influx of fresh water from the Arctic plays a prominent role.
since it results primarily from the cross-equatorial leakage of northern hemispheric tritium with few local sources (Figure 2). Providing the production of bomb tritium is well known, the patterns and time variations of tritium concentrations in rain, environmental, and ocean waters provide useful insights into the hydrologic cycle and ocean circulation. Unfortunately, direct observation of environmental tritium levels was limited because the development of analytical techniques lagged events. Efforts are ongoing to reconstruct tritium records in precipitation by analysis of this isotope in tree rings. This has been made possible by the relatively recent development and improvement of high-sensitivity techniques of tritium measurement by 3He regrowth. The deposition of tritium to the oceans occurs both by direct precipitation and by vapor exchange. Vapor exchange is a two-way process, and in general dominates over the direct precipitation. There are relatively few direct measures of tritium concentration in atmospheric water vapor, but studies indicate that it is closely related to levels in precipitation. This linkage has been exploited in order to construct tritium depositional histories for ocean basins from tritium in precipitation records. Another pathway whereby tritium enters the ocean is through continental runoff and river flow. Tritium deposited to the continents ultimately flows to the oceans via lakes, rivers and groundwater flow, but is retained within the continental hydrosphere for time-scales of many years, thereby introducing a delayed input to the oceans. Further, when computing the time-evolving tritium inventory within an ocean basin, it is necessary to consider inflow and outflow across the basin’s boundaries. The relative importance of the various inputs to the ocean varied with time. An analysis of the tritium
budget for the North Atlantic Ocean, for example, shows that water vapor exchange (the magenta curve in Figure 3) and direct precipitation (the cyan curve in Figure 3) were the dominant inputs of tritium during the mid-1960s when the tritium ‘spike’ occurred. By the 1970s, however, the major input became the inflow of low salinity water from the Arctic (the dark blue curve in Figure 3). A substantial inventory of bomb tritium had been delivered to and held up within the Arctic fresh-water system, to be released more gradually to the subpolar oceans, and subsequently to the North Atlantic. This input can be seen in the distribution of tritium in surface waters as observed during the early 1980s (Figure 4). Figure 4 shows the intrusion of tritiumlabeled waters along the east coast of Greenland and the Labrador Sea (red areas). This is superimposed on a general southward-decreasing trend. In response to the deposition of tritium, North Atlantic surface water concentrations rose rapidly, reaching values approaching 18 TU, or about 40 times greater than natural, prebomb, surface ocean levels. After peaking in 1964, surface water concentrations decreased, in part due to radioactive decay of this isotope, but also due to the dilution of surface waters with older, lower tritium waters from below, and lower concentration Southern Hemisphere waters. Consequently, the surface water decrease observed is significantly faster than the radioactive decay timescale. The penetration of tritium into the oceans provides us with a direct visualization of the large-scale ventilation of the oceans. As a time-dependent dye, it stains water that has been in contact with the surface since the bomb tests in the 1960s. The time evolution of this picture highlights those processes that occur on decade time-scales that are important for climate change. Figure 5 is a north–south section taken
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through the western North Atlantic in the early 1980s. The section shows how far the dye has penetrated along the pathway of the planetary-scale overturning circulation (‘the global conveyor’) and is
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Surface tritium (TU)
an important quantitative measure of the rate of this overturning on decade timescales. The boundary between high- and low-tritium waters at depths of 4–5 km corresponds to the transition region between the subtropical and subpolar 80W gyres. In the subpolar gyre, deep convection injected 0 40W tritium into deep and intermediate waters. In the subtropical gyre, subsurface penetration occurs from 60N the north, primarily along deep western boundary N 60 currents. Otherwise, bomb tritium is restricted to the upper 1 km, tracing the bowl-like structure of the main thermocline, which it penetrates by subduction 40N 40N of fluid by a combination of wind stress convergence (a process called ‘Ekman pumping’, i.e. convergence of surface waters due to wind forcing effectively 20N 20N pushes water downward) and southward penetration under lighter, warmer waters. A time series of tritium in the Sargasso Sea near 80W 0 Bermuda shows the penetration of this bomb tritium 60W 20W 40W into the subtropical North Atlantic (Figure 6). To TU (A) compensate for predictable radioactive decay, the 20 0 6 2 4 concentration of tritium has been decay-corrected to one point in time (arbitrarily chosen here to be 1981, 16 the approximate mid-point of the series). Two relatively sudden increases in tritium concentrations 12 occur in the deep waters. The first appears at a depth of about 1500 m in the late 1970s, whereas the 8 deeper one arrives in the late 1980s. These increases signal the arrival of waters that had been ‘ventilated’ 4 or exposed to the surface since the bomb tests. The delayed arrival provides a measure of the transit time 0 of properties southward from the outcropping re1990 1960 1970 1950 1980 gions, important knowledge for ocean climate (B) Year models. Figure 4 North Atlantic surface water tritium concentrations: The time series, however, is dominated in the (A) geographical distribution in the early 1980s; (B) variation with upper waters by the downward penetration of bomb time in the subtropics.
TU
0 1
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Depth (km)
2 3 3 2 4 1
5 6
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Latitude Figure 5 A North Atlantic tritium meridional section taken in the early 1980s.
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0 3.5 3 2.5 1.5 2
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Figure 6 A Bermuda time series of (A) tritium and (B) 3He. The tritium concentrations have been decay-corrected (that is, corrected for the effects of radioactive decay) to a fixed point in time (1981). This allows the effects of dilution and fluid motions to be seen.
tritium into the main thermocline. The tritium ‘spike’ first appears as a surface-intensified maximum at the beginning of the record, but then subsequently descends into the thermocline at a rate of about 20 m y1. As it descends, its intensity decreases due to dilution (the series has been corrected for radioactive decay). The rate at which this maximum descends into the thermocline is vital information for climate modeling; i.e., this information is important for predicting how the ocean will respond to changes on decade timescales.
Tritium–3He Dating in the Ocean !The penetration of tritium into the oceans, and its subsequent evolution, provides us with valuable information on ocean ventilation and large-scale circulation on multiyear and multidecade timescales.
However, it is possible to use this tracer in combination with its stable, inert daughter 3He to extend its utility to much shorter timescales, and provide a powerful measure of circulation and ventilation, as well as the rates of biological and chemical processing in the oceans. The manner in which this is accomplished can be seen in the following thought experiment. Imagine a parcel of water at the sea surface (Figure 7). Tritium within this fluid parcel is decaying, producing its daughter product 3He. (Half of the tritium decays to 3He in 12.45 years, while in 24.9 years, one-quarter would be left, and in 37.4 years, only one-eighth would remain, etc.) However, because it is at the sea surface, this 3He will be lost to the atmosphere via gas exchange. Thus no excess or ‘tritiugenic’ 3He would accumulate. However, should this water parcel sink below the surface and lose contact with the atmosphere, tritiugenic 3He would
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Figure 7 The tritium–helium dating concept.
_ 100
Age (y)
_ 150
_ 150
35
_ 200
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itud
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h
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_ 200
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Above 7 6 −7 5−6 4−5 3−4 2−3 1− 2 Below 1
_ 20
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_ 25 20
_ 30 _ 35
de
gitu
n Lo
Figure 8 The distribution of tritium–helium age on a constant density surface (26.4 kg m3) in the subtropical North Atlantic.
accumulate at a predictable rate. By measuring both the tritium concentration and the accumulated 3He in the fluid parcel, the time that has elapsed since the fluid was last in contact with the surface can be determined according to the equation: He t ¼ 17:96ln 1 þ 3 ½ H
3
where t is the tritium–3He age in years, and [3He] and [3H] are the concentrations of 3He and tritium in the water, respectively. For typical surface water concentrations of a few tritium units, elapsed times as short as a month or two can be detected, and the upper limit to the dating technique is of the order of 10–20 years (see discussion below). This range of timescales is ideal for studying shallow-ocean circulation, ventilation, and biogeochemical processing.
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Figure 9 Two deep Pacific zonal sections of 3He. Data are presented as isotope ratio anomaly (%), relative to atmospheric helium. Samples were processed during the WOCE Pacific hydrographic expeditions from 1989 to 1994.
In the subtropics, where wind-stress is convergent, water tends to be forced downward from the surface ocean into the thermocline. This downwelling is an important process for ventilation of the thermocline, and for driving the shallow gyre circulation. Figure 8 shows the measured tritium–helium age as measured on a constant density surface (1024 kg m3) in the eastern subtropical North Atlantic in the early 1990s. Water is youngest in the north-east, where the horizon rises toward the ocean surface. In fact, this horizon intercepts the base of the wintertime mixing layer, and the tritium–helium age of the water is less than one year, indicating that it was in active contact with the previous winter’s surface mixed layer. The age of the water increases monotonically as the layer deepens to the southwest, consistent with a south-
westward flow associated with the large-scale circulation of the gyre. The next logical step would be to use the observed age-gradients to compute fluid velocities. Before applying this technique quantitatively, however, there are two significant concerns that need to be considered. The first is the possible release of volcanic helium from submarine hydrothermal activity. This injection occurs at active volcanic centers, predominantly along midocean ridges, and to a lesser extent at near-axial seamounts. This helium is a mixture of primordial helium inherited during the earth’s formation from the presolar nebula and radiogenic helium produced by the decay of longlived radioactive U and Th isotopes in the deep earth. The injection of this helium is visible on a very large
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scale in the deep Pacific Ocean, where plumes of this helium extend across the basin (Figure 9). These plumes provide compelling evidence of ocean–crust interaction, terrestrial degassing, and trace deep ocean circulation (see Volcanic Helium). As this helium tends to be enriched in 3He compared to atmospheric helium, it may be confused with tritiugenic 3He. Such injections tend to occur in deeper waters, away from the surface where one would tend to use tritium–3He dating. Moreover, calculations indicate that despite the impressive signature in abyssal waters, the actual flux of volcanic 3 He is smaller than the tritiugenic production rate due to bomb tests. Clearly, however, caution should be exercised in areas where the two signals can interfere. The shallow North Atlantic, in particular, is well suited to tritium–3He dating, partly because water masses tend to be younger there, and partly because seafloor spreading rates (and hence the rate of injection of volcanic 3He into the deep water) are low. (One would expect, on average, that volcanic activity would be related to seafloor spreading rates.) A second concern arises from the behavior of the tritium–3He age in response to mixing. Returning to the model concept discussed earlier, it must be recognized that water does not circulate in discrete ‘parcels’ but is subjected to mixing. In general, this manifests itself in a ‘nonlinear’ response in the tritium–3He age. For example, consider two fluid parcels that undergo mixing in equal proportions (Figure 10). We consider, for simplicity, the case where the two are mixed in equal proportions, but the arguments apply equally well for an arbitrary mixture. In general, the tritium–3He age of the mixture would be calculated from its tritium and 3He concentrations, and will be different from the average of the component ages. That is, the age of the mixture is not equivalent to the mixture of the ages. The results for three example cases are shown in Table 1. In the first case, the average age of the two water masses should be slightly more than 22 years, but the tritium concentration of the mixture is dominated by water mass A, which is the younger water mass. In the second case, the mixture is significantly older than ‘average age’, again because it is dominated by the higher tritium component. Only when the two components are of equal tritium concentration (case 3) does the mixture age more closely match the average of the components. Even here, there is a deviation due to the logarithmic nature of the age dependence. Consideration of the scenarios presented in Table 1 reveals that when water masses mix, the tritium–3He age of the resultant mixture is weighted in favor of the water mass component with the
Water Mass A Tritium = TA Helium-3 = HA Age = 17.95 log(1 +
Water Mass B Tritium = TB Helium-3 = HB HA ) TA
Age = 17.95 log(1 +
HB ) TB
Water Mass C Tritium = TC = (TA + TB)/2 Helium-3 = HC = (HA + HB)/2 Age = 17.95 log(1 +
HC ) TC
Figure 10 The effect of mixing on the tritium–helium age.
Table 1 Examples of water mass mixing effects on the tritium– helium age
Case 1
Case 2
Case 3
Watermass A Watermass B 50 : 50 Mixture Watermass A Watermass B 50 : 50 Mixture Watermass A Watermass B 50 : 50 Mixture
[3H]
[3He]
Age (y)
10 1 5.5 10 1 5.5 10 10 5
1 10 5.5 100 0.1 50.05 10 1 5.5
1.71 43.04 12.45 43.04 1.71 41.51 17.95 1.71 13.32
greater tritium concentration. The implication of this is that a small admixture of a young, relatively tritium-rich water mass will depress the tritium–3He age disproportionately. Therefore, there will be a tendency for the tritium–3He age to be an underestimate of the true age in the presence of mixing. Although it seems a serious concern, consideration of real-world oceanographic situations indicates that this is not a significant problem for timescales of less than a decade. The effects of mixing on the tritium–3He age have been quantified by the development of an advection– diffusion equation for the age. This is accomplished by combining the definition of the tritium–3He age (t) with the advection–diffusion equations for tritium and 3He. 3 3 r He H @t ! þ 2 :rt þ u rt ¼ rðkrtÞ þ 1 k ½3 He ½3 H @t
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where k is the turbulent diffusivity and u is the fluid velocity. The equation appears similar to that of an ideal age tracer (A), governed by ! u rA ¼ rðkrAÞ þ 1 except for the presence of the unsteady (time derivative) term and the last term on the right. The unsteady term arises from the fact that the parent distributions are changing with time, and the age distribution is adjusting accordingly. The last term appears more as a pseudovelocity that is a direct manifestation of the nonlinear mixing behavior exemplified in the two-water-mass thought experiment described earlier. Although the equation appears complex, the key point is that all the terms are observable. That is, given field observations of the tracers, the terms can be computed to within a value of k. The effects on the shallowest surfaces are small. Analysis of actual distributions within the shallow North Atlantic, for example, shows that deviations from ‘ideal’ behavior are negligibly small. Moreover, combining the age distributions with other tracers, for example salinity, and with geostrophic constraints, permits the determination of absolute velocities within the main thermocline to a resolution of order 0.1 cm s1.
See also Elemental Distribution: Overview. Ekman Transport and Pumping. Ocean Subduction. Ocean Circulation: Meridional Overturning Circulation. Water Types and Water Masses.
Further Reading Clarke WB, Jenkins WJ, and Top Z (1976) Determination of tritium by mass spectrometric measurement of 3He. International Journal of Applied Radioisotopes 27: 515. Doney SC, Glover DM, and Jenkins WJ (1992) A model function of the global bomb tritium distribution in precipitation, 1960–1986. Journal of Geophysical Research 97: 5481--5492. ¨ stlund HG (1993) A tritium Doney SC, Jenkins WJ, and O budget for the North Atlantic. Journal of Geophysical Research 98(C10): 18069--18081. Jenkins WJ (1978) Helium isotopes from the solid earth. Oceanus 21: 13. Jenkins WJ (1992) Tracers in oceanography. Oceanus 35: 47--56. Jenkins WJ (1998) Studying subtropical thermocline ventilation and circulation using tritium and 3He. Journal of Geophysical Research 103: 15817--15831. Jenkins WJ and Smethie WM (1996) Transient tracers track ocean climate signals. Oceanus 39: 29--32.
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TSUNAMI P. L.-F. Liu, Cornell University, Ithaca, NY, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction Tsunami is a Japanese word that is made of two characters: tsu and nami. The character tsu means harbor, while the character nami means wave. Therefore, the original word tsunami describes large wave oscillations inside a harbor during a ‘tsunami’ event. In the past, tsunami is often referred to as ‘tidal wave’, which is a misnomer. Tides, featuring the rising and falling of water level in the ocean in a daily, monthly, and yearly cycle, are caused by gravitational influences of the moon, sun, and planets. Tsunamis are not generated by this kind of gravitational forces and are unrelated to the tides, although the tidal level does influence a tsunami striking a coastal area. The phenomenon we call a tsunami is a series of water waves of extremely long wavelength and long period, generated in an ocean by a geophysical disturbance that displaces the water within a short period of time. Waves are formed as the displaced water mass, which acts under the influence of gravity, attempts to regain its equilibrium. Tsunamis are primarily associated with submarine earthquakes in oceanic and coastal regions. However, landslides, volcanic eruptions, and even impacts of objects from outer space (such as meteorites, asteroids, and comets) can also trigger tsunamis. Tsunamis are usually characterized as shallowwater waves or long waves, which are different from wind-generated waves, the waves many of us have observed on a beach. Wind waves of 5–20-s period (T ¼ time interval between two successive wave crests or troughs) have wavelengths (l ¼ T2(g/2p) distance between two successive wave crests or troughs) of c. 40–620 m. On the other hand, a tsunami can have a wave period in the range of 10 min to 1 h and a wavelength in excess of 200 km in a deep ocean basin. A wave is characterized as a shallowwater wave when the water depth is less than 5% of the wavelength. The forward and backward water motion under the shallow-water wave is felted throughout the entire water column. The shallow water wave is also sensitive to the change of water depth. For instance, the speed (celerity) of a shallowwater wave is equal to the square root of the product
of the gravitational acceleration (9.81 m s 2) and the water depth. Since the average water depth in the Pacific Ocean is 5 km, a tsunami can travel at a speed of about 800 km h 1 (500 mi h 1), which is almost the same as the speed of a jet airplane. A tsunami can move from the West Coast of South America to the East Coast of Japan in less than 1 day. The initial amplitude of a tsunami in the vicinity of a source region is usually quite small, typically only a meter or less, in comparison with the wavelength. In general, as the tsunami propagates into the open ocean, the amplitude of tsunami will decrease for the wave energy is spread over a much larger area. In the open ocean, it is very difficult to detect a tsunami from aboard a ship because the water level will rise only slightly over a period of 10 min to hours. Since the rate at which a wave loses its energy is inversely proportional to its wavelength, a tsunami will lose little energy as it propagates. Hence in the open ocean, a tsunami will travel at high speeds and over great transoceanic distances with little energy loss. As a tsunami propagates into shallower waters near the coast, it undergoes a rapid transformation. Because the energy loss remains insignificant, the total energy flux of the tsunami, which is proportional to the product of the square of the wave amplitude and the speed of the tsunami, remains constant. Therefore, the speed of the tsunami decreases as it enters shallower water and the height of the tsunami grows. Because of this ‘shoaling’ effect, a tsunami that was imperceptible in the open ocean may grow to be several meters or more in height. When a tsunami finally reaches the shore, it may appear as a rapid rising or falling water, a series of breaking waves, or even a bore. Reefs, bays, entrances to rivers, undersea features, including vegetations, and the slope of the beach all play a role modifying the tsunami as it approaches the shore. Tsunamis rarely become great, towering breaking waves. Sometimes the tsunami may break far offshore. Or it may form into a bore, which is a steplike wave with a steep breaking front, as the tsunami moves into a shallow bay or river. Figure 1 shows the incoming 1946 tsunami at Hilo, Hawaii. The water level on shore can rise by several meters. In extreme cases, water level can rise to more than 20 m for tsunamis of distant origin and over 30 m for tsunami close to the earthquake’s epicenter. The first wave may not always be the largest in the series of waves. In some cases, the water level will fall significantly first, exposing the bottom of a bay
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Figure 1 1946 tsunami at Hilo, Hawaii (Pacific Tsunami Museum). Wave height may be judged from the height of the trees.
or a beach, and then a large positive wave follows. The destructive pattern of a tsunami is also difficult to predict. One coastal area may see no damaging wave activity, while in a neighboring area destructive waves can be large and violent. The flooding of an area can extend inland by 500 m or more, covering large expanses of land with water and debris. Tsunamis may reach a maximum vertical height onshore above sea level, called a runup height, of 30 m. Since scientists still cannot predict accurately when earthquakes, landslides, or volcano eruptions will occur, they cannot determine exactly when a tsunami will be generated. But, with the aid of historical records of tsunamis and numerical models, scientists can get an idea as to where they are most likely to be generated. Past tsunami height measurements and computer modeling can also help to forecast future tsunami impact and flooding limits at specific coastal areas.
Historical and Recent Tsunamis Tsunamis have been observed and recorded since ancient times, especially in Japan and the Mediterranean areas. The earliest recorded tsunami occurred in 2000 BC off the coast of Syria. The oldest reference of tsunami record can be traced back to the sixteenth century in the United States. During the last century, more than 100 tsunamis have been observed in the United States alone. Among them, the 1946 Alaskan tsunami, the 1960 Chilean tsunami, and the 1964 Alaskan tsunami were the three most destructive tsunamis in the US history. The 1946 Aleutian earthquake (Mw ¼ 7.3) generated catastrophic tsunamis that attacked the Hawaiian Islands after traveling about 5 h and killed 159 people.
(The magnitude of an earthquake is defined by the seismic moment, M0 (dyn cm), which is determined from the seismic data recorded worldwide. Converting the seismic moment into a logarithmic scale, we define Mw ¼ (1/1.5)log10M0 10.7.) The reported property damage reached $26 million. The 1960 Chilean tsunami waves struck the Hawaiian Islands after 14 h, traveling across the Pacific Ocean from the Chilean coast. They caused devastating damage not only along the Chilean coast (more than 1000 people were killed and the total property damage from the combined effects of the earthquake and tsunami was estimated as $417 million) but also at Hilo, Hawaii, where 61 deaths and $23.5 million in property damage occurred (see Figure 2). The 1964 Alaskan tsunami triggered by the Prince William Sound earthquake (Mw ¼ 8.4), which was recorded as one of the largest earthquakes in the North American continent, caused the most destructive damage in Alaska’s history. The tsunami killed 106 people and the total damage amounted to $84 million in Alaska. Within less than a year between September 1992 and July 1993, three large undersea earthquakes strike the Pacific Ocean area, causing devastating tsunamis. On 2 September 1992, an earthquake of magnitude 7.0 occurred c. 100 km off the Nicaraguan coast. The maximum runup height was recorded as 10 m and 168 people died in this event. A few months later, another strong earthquake (Mw ¼ 7.5) attacked the Flores Island and surrounding area in Indonesia on 12 December 1992. It was reported that more than 1000 people were killed in the town of Maumere alone and two-thirds of the population of Babi Island were swept away by the tsunami. The maximum runup was estimated as 26 m. The final toll of this Flores earthquake stood at 1712 deaths and more than 2000 injures. Exactly
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Figure 2 The tsunami of 1960 killed 61 people in Hilo, destroyed 537 buildings, and damages totaled over $23 million.
7 months later, on 12 July 1993, the third strong earthquake (Mw ¼ 7.8) occurred near the Hokkaido Island in Japan (Hokkaido Tsunami Survey Group 1993). Within 3–5 min, a large tsunami engulfed the Okushiri coastline and the central west of Hokkaido, impinging extensive property damages, especially on the southern tip of Okushiri Island in the town of Aonae. The runup heights on the Okushiri Island were thoroughly surveyed and they varied between 15 and 30 m over a 20-km stretch of the southern part of the island, with several 10-m spots on the northern part of the island. It was also reported that although the runup heights on the west coast of Hokkaido are not large (less than 10 m), damage was extensive in several towns. The epicenters of these three earthquakes were all located near residential coastal areas. Therefore, the damage caused by subsequent tsunamis was unusually large. On 17 July 1998, an earthquake occurred in the Sandaun Province of northwestern Papua New Guinea, about 65 km northwest of the port city of Aitape. The earthquake magnitude was estimated as Mw ¼ 7.0. About 20 min after the first shock, Warapo and Arop villages were completely destroyed by tsunamis. The death toll was at over 2000 and many of them drowned in the Sissano Lagoon behind the Arop villages. The surveyed maximum runup height was 15 m, which is much higher than the predicted value based on the seismic information. It has been suggested that the Papua New Guinea tsunami could be caused by a submarine landslide. The most devastating tsunamis in recent history occurred in the Indian Ocean on 26 December 2004.
An earthquake of Mw ¼ 9.0 occurred off the west coast of northern Sumatra. Large tsunamis were generated, severely damaging coastal communities in countries around the Indian Ocean, including Indonesia, Thailand, Sri Lanka, and India. The estimated tsunami death toll ranged from 156 000 to 178 000 across 11 nations, with additional 26 500–142 000 missing, most of them presumed dead.
Tsunami Generation Mechanisms Tsunamigentic Earthquakes
Most tsunamis are the results of submarine earthquakes. The majority of earthquakes can be explained in terms of plate tectonics. The basic concept is that the outermost part the Earth consists of several large and fairly stable slabs of solid and relatively rigid rock, called plates (see Figure 3). These plates are constantly moving (very slowly), and rub against one another along the plate boundaries, which are also called faults. Consequently, stress and strain build up along these faults, and eventually they become too great to bear and the plates move abruptly so as to release the stress and strain, creating an earthquake. Most of tsunamigentic earthquakes occur in subduction zones around the Pacific Ocean rim, where the dense crust of the ocean floor dives beneath the edge of the lighter continental crust and sinks down into Earth’s mantle. These subduction zones include the west coasts of North and South America, the coasts of East Asia (especially Japan), and many Pacific island chains (Figure 3). There are
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different types of faults along subduction margins. The interplate fault usually accommodates a large relative motion between two tectonic plates and the overlying plate is typically pushed upward. This upward push is impulsive; it occurs very quickly, in a
Ridge axis divergent boundary
few seconds. The ocean water surface responds immediately to the upward movement of the seafloor and the ocean surface profile usually mimics the seafloor displacement (see Figure 4). The interplate fault in a subduction zone has been responsible for
Subduction zone Convergent boundary
Transform
Zone of extension with continents
Uncertain plate boundary
Figure 3 Major tectonic plates that make up the Earth’s crust.
(a)
(b)
Stuck S ubdu cting
(c)
Earthquake starts tsunami
Overriding plate
Slow distortion
p late
(d)
Tsunami waves spread
Stuck area ruptures, releasing energy in an earthquake Figure 4 Sketches of the tsunami generation mechanism caused by a submarine earthquake. An oceanic plate subducts under an overriding plate (a). The overriding plate deforms due to the relative motion and the friction between two tectonic plates (b). The stuck area ruptures, releasing energy in an earthquake (c). Tsunami waves are generated due to the vertical seafloor displacement (d).
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TSUNAMI
most of the largest tsunamis in the twentieth century. For example, the 1952 Kamchatka, 1957 Aleutian, 1960 Chile, 1964 Alaska, and 2004 Sumatra earthquakes all generated damaging tsunamis not only in the region near the earthquake epicenter, but also on faraway shores. For most of the interplate fault ruptures, the resulting seafloor displacement can be estimated based on the dislocation theory. Using the linear elastic theory, analytical solutions can be derived from the mean dislocation field on the fault. Several parameters defining the geometry and strength of the fault rupture need to be specified. First of all, the mean fault slip, D, is calculated from the seismic moment M0 as follows: M0 ¼ mDS
estimation, the fault plane can be approximated as a rectangle with length L and width W. The aspect ratio L/W could vary from 2 to 8. To find the static displacement of the seafloor, we need to assign the focal depth d, measuring the depth of the upper rim of the fault plane, the dip angle d, and the slip angle l of the dislocation on the fault plane measured from the horizontal axis (see Figure 5). For an oblique slip on a dipping fault, the slip vector can be decomposed into dip-slip and strike-slip components. In general, the magnitude of the vertical displacement is less for the strike-slip component than for the dip-slip component. The closed form expressions for vertical seafloor displacement caused by a slip along a rectangular fault are given by Mansinha and Smylie. For more realistic fault models, nonuniform stressstrength fields (i.e., faults with various kinds of barriers, asperities, etc.) are expected, so that the actual seafloor displacement may be very complicated compared with the smooth seafloor displacement computed from the mean dislocation field on the fault. As an example, the vertical seafloor displacement caused by the 1964 Alaska earthquake is sketched in Figure 6. Although several numerical models have considered geometrically complex faults, complex slip distributions, and elastic layers of variable thickness, they are not yet disseminated in
½1
din
al)
where S is the rupture area and m is the rigidity of the Earth at the source, which has a range of 6–7 1011 dyn cm 2 for interplate earthquakes. The seismic moment, M0, is determined from the seismic data recorded worldwide and is usually reported as the Harvard Centroid-Moment-Tensor (CMT) solution within a few minutes of the first earthquake tremor. The rupture area is usually estimated from the aftershock data. However, for a rough
(la
titu
X
rth no To
Y
O
lt au
e
lin
Overriding block
F
Tectonic motion
Foot block
Z
Symbols
X
Fa
Foot block
W
W Width of fault plane
Slip direct ion
O
Y
L Length of fault plane
ine
l ult
131
Strike angle Dip angle
Slip angle L
X OY parrallel to the horizontal Earth surface; OZ pointing upward; is the azimuth of OX measuring clockwise from the latitudinal Figure 5 A sketch of fault plane parameters.
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NW
19.5 m
0
5.2 m
Horizontal SW displacements
SE
3.5+ m?
m
11.3 m
12 8
5.0 m
Vertical displacements
4
3.5 m
0 −2
Volcanic arc
Patton Bay Fault
Anchorage North American Plate
Aleutian
Middleton Island
400
300
km 0
Megathrust
200
50
Pacific Plate and mantle
H/V = 1 475
Aleutian Trench
100
0 km
100
Figure 6 A sketch of 1964 Alaska earthquake generated vertical seafloor displacement (G. Plafker, 2006).
tsunami research. One of the reasons is that our knowledge in source parameters, inhomogeneity, and nonuniform slip distribution is too incomplete to justify using such a complex model. Certain earthquakes referred to as tsunami earthquakes have slow faulting motion and very long rupture duration (more than several minutes). These earthquakes occur along the shallow part of the interplate thrust or de´collement near the trench (the wedge portion of the thin crust above the interface of the continental crust and the ocean plate). The wedge portion consisting of thick deformable sediments with low rigidity, and the steepening of rupture surface in shallow depth all favor the large displacement of the crust and possibility of generating a large tsunami. Because of the extreme heterogeneity, accurate modeling is difficult, resulting in large uncertainty in estimated seafloor displacement. Landslides and Other Generation Mechanisms
There are occasions when the secondary effects of earthquakes, such as landslide and submarine slump, may be responsible for the generation of tsunamis. These tsunamis are sometimes disastrous and have gained increasing attentions in recent years. Landslides are generated when slopes or sediment deposits become too steep and they fail to remain in equilibrium and motionless. Once the unstable conditions are present, slope failure can be triggered by storm, earthquakes, rains, or merely continued
deposition of materials on the slope. Alternative mechanisms of sediment instability range between soft sediment deformations in turbidities, to rotational slumps in cohesive sediments. Certain environments are particularly susceptible to the production of landslides. River delta and steep underwater slopes above submarine canyons are likely sites for landslide-generated tsunamis. At the time of the 1964 Alaska earthquake, numerous locally landslide-generated tsunamis with devastating effects were observed. On 29 November 1975, a landslide was triggered by a 7.2 magnitude earthquake along the southeast coast of Hawaii. A 60-km stretch of Kilauea’s south coast subsided 3.5 m and moved seaward 8 m. This landslide generated a local tsunami with a maximum runup height of 16 m at Keauhou. Historically, there have been several tsunamis whose magnitudes were simply too large to be attributed to the coseismic seafloor movement and landslides have been suggested as an alternative cause. The 1946 Aleutian tsunami and the 1998 Papua New Guinea tsunami are two significant examples. In terms of tsunami generation mechanisms, two significant differences exist between submarine landslide and coseismic seafloor deformation. First, the duration of a landslide is much longer and is in the order of magnitude of several minutes or longer. Hence the time history of the seafloor movement will affect the characteristics of the generated wave and needs to be included in the model. Second, the
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TSUNAMI
effective size of the landslide region is usually much smaller than the coseismic seafloor deformation zone. Consequently, the typical wavelength of the tsunamis generated by a submarine landslide is also shorter, that is, c. 1–10 km. Therefore, in some cases, the shallow-water (long-wave) assumption might not be valid for landslide-generated tsunamis. Although they are rare, the violent geological activities associated with volcanic eruptions can also generate tsunamis. There are three types of tsunamigeneration mechanism associated with a volcanic eruption. First, the pyroclastic flows, which are mixtures of gas, rocks, and lava, can move rapidly off an island and into an ocean, their impact displacing seawater and producing a tsunami. The second mechanism is the submarine volcanic explosion, which occurs when cool seawater encounters hot volcanic magma. The third mechanism is due to the collapse of a submarine volcanic caldera. The collapse may happen when the magma beneath a volcano is withdrawn back deeper into the Earth, and the sudden subsidence of the volcanic edifice displaces water and produces a tsunami. Furthermore, the large masses of rock that accumulate on the sides of volcanoes may suddenly slide down the slope into the sea, producing tsunamis. For example, in 1792, a large mass of the mountain slided into Ariake Bay in Shimabara on Kyushu Island, Japan, and generated tsunamis that reached a height of 10 m in some places, killing a large number of people. In the following sections, our discussions will focus on submarine earthquake-generated tsunamis and their coastal effects.
Modeling of Tsunami Generation, Propagation, and Coastal Inundation To mitigate tsunami hazards, the highest priority is to identify the high-tsunami-risk zone and to educate the citizen, living in and near the risk zone, about the proper behaviors in the event of an earthquake and tsunami attack. For a distant tsunami, a reliable warning system, which predicts the arrival time as well as the inundation area accurately, can save many lives. On the other hand, in the event of a nearfield tsunami, the emergency evacuation plan must be activated as soon as the earth shaking is felt. This is only possible, if a predetermined evacuation/ inundation map is available. These maps should be produced based on the historical tsunami events and the estimated ‘worst scenarios’ or the ‘design tsunamis’. To produce realistic and reliable inundation maps, it is essential to use a numerical model that calculates accurately tsunami propagation from
133
a source region to the coastal areas of concern and the subsequent tsunami runup and inundation. Numerical simulations of tsunami have made great progress in the last 50 years. This progress is made possible by the advancement of seismology and by the development of the high-speed computer. Several tsunami models are being used in the National Tsunami Hazard Mitigation Program, sponsored by the National Oceanic and Atmospheric Administration (NOAA), in partnership with the US Geological Survey (USGS), the Federal Emergency Management Agency (FEMA), to produce tsunami inundation and evacuation maps for the states of Alaska, California, Hawaii, Oregon, and Washington. Tsunami Generation and Propagation in an Open Ocean
The rupture speed of fault plane during earthquake is usually much faster than that of the tsunami. For instance, the fault line of the 2004 Sumatra earthquake was estimated as 1200-km long and the rupture process lasted for about 10 min. Therefore, the rupture speed was c. 2–3 km s 1, which is considered as a relatively slow rupture speed and is still about 1 order of magnitude faster than the speed of tsunami (0.17 km s 1 in a typical water depth of 3 km). Since the compressibility of water is negligible, the initial free surface response to the seafloor deformation due to fault plane rupture is instantaneous. In other words, in terms of the tsunami propagation timescale, the initial free surface profile can be approximated as having the same shape as the seafloor deformation at the end of rupture, which can be obtained by the methods described in the previous section. As illustrated in Figure 6, the typical cross-sectional free surface profile, perpendicular to the fault line, has an N shape with a depression on the landward side and an elevation on the ocean side. If the fault plane is elongated, that is, L4 4W, the free surface profile is almost uniform in the longitudinal (fault line) direction and the generated tsunamis will propagate primarily in the direction perpendicular to the fault line. The wavelength is generally characterized by the width of the fault plane, W. The measure of tsunami wave dispersion is represented by the depth-to-wavelength ratio, that is, m2 ¼ h/l, while the nonlinearity is characterized by the amplitude-to-depth ratio, that is, e ¼ A/h. A tsunami generated in an open ocean or on a continental shelf could have an initial wavelength of several tens to hundreds of kilometers. The initial tsunami wave height may be on the order of magnitude of several meters. For example, the 2004 Indian Ocean tsunami
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had a typical wavelength of 200 km in the Indian Ocean basin with an amplitude of 1 m. The water depth varies from several hundreds of meters on the continental shelf to several kilometers in the open ocean. It is quite obvious that during the early stage of tsunami propagation both the nonlinear and frequency dispersion effects are small and can be ignored. This is particularly true for the 2004 Indian tsunami. The bottom frictional force and Coriolis force have even smaller effects and can be also neglected in the generation area. Therefore, the linear shallow water (LSW) equations are adequate equations describing the initial stage of tsunami generation and propagation. As a tsunami propagates over an open ocean, wave energy is spread out into a larger area. In general, the tsunami wave height decreases and the nonlinearity remains weak. However, the importance of the frequency dispersion begins to accumulate as the tsunami travels a long distance. Theoretically, one can estimate that the frequency dispersion becomes important when a tsunami propagates for a long time: sffiffiffi h l 3 ½2 t4 4td ¼ g h or over a long distance: x4 4xd ¼ td
pffiffiffiffiffiffi l3 gh ¼ 2 h
½3
In the case of the 2004 Indian Ocean tsunami, tdE700 h and xdE5 105 km. In other words, the frequency dispersion effect will only become important when tsunamis have gone around the Earth several times. Obviously, for a tsunami with much shorter wavelength, for example, lE20 km, this distance becomes relatively short, that is, xdE5 102 km, and can be reached quite easily. Therefore, in modeling transoceanic tsunami propagation, frequency dispersion might need to be considered if the initial wavelength is short. However, nonlinearity is seldom a factor in the deep ocean and only becomes significant when the tsunami enters coastal region. The LSW equations can be written in terms of a spherical coordinate system as: @z 1 @P @ @h þ þ ðcosjQÞ ¼ ½4 @t Rcosj @c @j @t @P gh @z þ ¼0 @t Rcosj @c
½5
@Q gh @z þ ¼0 @t R @j
½6
where (c,j) denote the longitude and latitude of the Earth, R is the Earth’s radius, z is free surface elevation, P and Q the volume fluxes (P ¼ hu and Q ¼ hv, with u and v being the depth-averaged velocities in longitude and latitude direction, respectively), and h the water depth. Equation [4] represents the depth-integrated continuity equation, and the time rate of change of water depth has been included. When the fault plane rupture is approximated as an instantaneous process and the initial free surface profile is prescribed, the water depth remains timeinvariant during tsunami propagation and the righthand side becomes zero in eqn [4]. The 2004 Indian Ocean tsunami provided an opportunity to verify the validity of LSW equations for modeling tsunami propagation in an open ocean. For the first time in history, satellite altimetry measurements of sea surface elevation captured the Indian Ocean tsunami. About 2 h after the earthquake occurred, two NASA/French Space Agency joint mission satellites, Jason-1 and TOPEX/Poseidon, passed over the Indian Ocean from southwest to northeast ( Jason-1 passed the equator at 02:55:24UTC on 26 December 2004 and TOPEX/ Poseidon passed the equator at 03:01:57UTC on 26 December 2004) (see Figure 7). These two altimetry satellites measured sea surface elevation with accuracy better than 4.2 cm. Using the numerical model COMCOT (Cornell Multi-grid Coupled Tsunami Model), numerical simulations of tsunami propagation over the Indian Ocean with various fault plane models, including a transient seafloor movement model, have been carried out. The LSW equation model predicts accurately the arrival time of the leading wave and is insensitive of the fault plane models used. However, to predict the trailing waves, the spatial variation of seafloor deformation needs to be taken into consideration. In Figure 8, comparisons between LSW results with an optimized fault plane model and Jason-1/TOPEX measurements are shown. The excellent agreement between the numerical results and satellite data provides a direct evidence for the validity of the LSW modeling of tsunami propagation in deep ocean.
Coastal Effects – Inundation and Tsunami Forces
Nonlinearity and bottom friction become significant as a tsunami enters the coastal zone, especially during the runup phase. The nonlinear shallow water (NLSW) equations can be used to model certain aspects of coastal effects of a tsunami attack. Using the same notations as those in eqns [4]–[6], the NLSW
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20
15
0.8
10
0.4 0
0.2
TOP
−10
EX
−0.2 −0.4
−1
0
−5
Jason
Latitude (deg)
0.6 5
−0.6
−15
−0.8 70
75
80
85 90 Longitude (deg)
95
100
105
Figure 7 Satellite tracks for TOPEX and Jason-1. The colors indicate the numerically simulated free surface elevation in meter at 2 h after the earthquake struck.
equations in the Cartesian coordinates are @z @P @Q þ þ ¼0 @t @x @y
½7
@P @ P2 @ PQ @z þ þ þ gH þ tx H ¼ 0 @t @x H @y H @x
½8
@Q @ PQ @ Q2 @z þ gH þ ty H ¼ 0 þ þ @t @x H @y H @y
½9
The bottom frictional stresses are expressed as tx ¼
gn2 PðP2 þ Q2 Þ1=2 H 10=3
½10
ty ¼
gn2 QðP2 þ Q2 Þ1=2 H 10=3
½11
where n is the Manning’s relative roughness coefficient. For flows over a sandy beach, the typical value for the Manning’s n is 0.02. Using a modified leapfrog finite difference scheme in a nested grid system, COMCOT is capable of solving both LSW and NLSW equations simultaneously in different regions. For the nested grid system, the inner (finer) grid adopts a smaller grid size and time step compared to its adjacent outer (larger) grid. At the beginning of a time step, along the interface of two different grids, the volume flux, P and Q, which is product of water depth and depthaveraged velocity, is interpolated from the outer (larger) grids into its inner (finer) grids. And at the end of this time step, the calculated water surface elevations, z, at the inner finer grids are averaged to update those values of the larger grids overlapping the finer grids, which are used to compute the volume fluxes at next time step in the outer grids. With this procedure, COMCOT can capture near-shore
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TSUNAMI
Water surface elevation (m)
(a)
(b)
1
Jason-1 Model
0.8 0.6 0.4 0.2 0 −0.2 −0.4 −0.6 −0.8 −1
−5
0
5 10 Latitude (deg)
Water surface elevation (m)
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Model TOPEX
0.8 0.6 0.4 0.2 0 −0.2 −0.4 −0.6 −0.8 −1
15
Model vs. TOPEX
1
−5
0
5 10 Latitude (deg)
15
Figure 8 Comparisons between optimized fault model results and Jason-1 measurements (a)/TOPEX measurements (b).
(a)
Grids with dx = 36.7 m
(b)
5.6
5.6
5.5
Latitude (deg)
Ulee Lheue BANDA ACEH
5.55
Lampuuk Lhoknga
5.45
5.55 5.5 5.45
Leupung
5.4
5.4
Inundated area Dry land Ocean
95.15
95.2
95.25
95.3
95.35
95.4
95.15
95.2
95.25 95.3 Longitude (deg)
95.35
95.4
Figure 9 Calculated inundation areas (a) and overlaid with QUICKBIRD image (b) in Banda Aceh, Indonesia.
features of a tsunami with a higher spatial and temporal resolution and at the same time can still keep a high computational efficiency. To estimate the inundation area caused by a tsunami, COMCOT adopts a simple moving boundary scheme. The shoreline is defined as the interface between a wet grid and its adjacent dry grids. Along the shoreline, the volume flux is assigned to be zero. Once the water surface elevation at the wet grid is higher than the land elevation in its adjacent dry grid, the shoreline is moved by one grid toward the dry grid and the volume flux is no longer zero and need to be calculated by the governing equations. COMCOT, coupled up to three levels of grids, has been used to calculate the runup and inundation areas at Trincomalee Bay (Sri Lanka) and Banda Aceh (Indonesia). Some of the numerical results for Banda Aceh are shown here.
The calculated inundation area in Banda Aceh is shown in Figure 9. The flooded area is marked in blue, the dry land region is rendered in green, and the white area is ocean region. The calculated inundation area is also overlaid with a satellite image taken by QUICKBIRD in Figure 9(b). In the overlaid image, the thick red line indicates the inundation line based on the numerical simulation. In the satellite image, the dark green color (vegetation) indicates areas not affected by the tsunami and the area shaded by semitransparent red color shows flooded regions by this tsunami. Obviously, the calculated inundation area matches reasonably well with the satellite image in the neighborhood of Lhoknga and the western part of Banda Aceh. However, in the region of eastern Banda Aceh, the simulations significantly underestimate the inundation area. However, in general, the agreement
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5.52
5.5
5.5
5.48
5.48
Survey by Tsuji et al.
Survey by Shibayama et al.
Latitude (deg)
Latitude (deg)
Lampuuk
5.46 5.44 5.42
5.36 40
5.42
30 20 10 Tsunami heights (m)
5.38
0
5.36 95.2
10 5 0 95.24
95.26
95.28
95.3 95.32 Longitude (deg)
95.34
95.36
95.38
95.36
95.38
5.62
5.4 Survey by Tsuji et al. Survey by Shibayama et al. Numerical result Nearest numerical result
Survey by Tsuji et al. Survey by Shibayama et al. Numerical result Nearest numerical result
Lhoknga
5.44
Leupung
5.4 5.38
5.46
15
Flooded area Dry land Ocean
95.22 95.24 95.26 95.28 Longitude (deg)
Latitude (deg)
5.52
is measured more than 30 m, the numerical results match very well with the field measurements. However, beyond Lhoknga to the north, the numerical results, in general, are only half of the measurements, except in middle regions between Lhoknga and Lampuuk.
Tsunami heights (m)
between the numerical simulation and the satellite observation is surprisingly good. In Figure 10, the tsunami wave heights in Banda Aceh are also compared with the field measurements by two Japan survey teams. On the coast between Lhoknga and Leupung, where the maximum height
5.6 5.58
Survey by Tsuji et al.
Survey by Shibayama et al.
Flooded area
Dry land Ocean
5.56
Ulee Lheue
5.54 95.24
BANDA ACEH
95.26
95.28
95.32 95.3 Longitude (deg)
95.34
Figure 10 Tsunami heights on eastern and northern coast of Banda Aceh, Indonesia. The field survey measurements are from Tsuji et al. (2005) and Shibayama et al. (2005).
120.0° E 135.0° E
150.0° E 165.0° E
180.0° E
165.0° W 150.0° W 135.0° W 120.0° W 105.0° W 90.0° W
75.0° W
60.0° W
45.0° W
60.0° N
45.0° N
30.0° N
15.0° N
15.0° S
30.0° S
45.0° S
Figure 11 The locations of the existing and planned Deep-Ocean Assessment and Reporting of Tsunamis (DART) system in the Pacific Ocean (NOAA magazine, 17 Apr. 2006).
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Tsunami Hazard Mitigation The ultimate goal of the tsunami hazard mitigation effort is to minimize casualties and property damages. This goal can be met, only if an effective tsunami early warning system is established and a proper coastal management policy is practiced. Tsunami Early Warning System
The great historical tsunamis, such as the 1960 Chilean tsunami and the 1964 tsunami generated near Prince William Sound in Alaska, prompted the US government to develop an early warning system in the Pacific Ocean. The Japanese government has
Bidirectional communication and control
Iridium satellite
also developed a tsunami early warning system for the entire coastal community around Japan. The essential information needed for an effective early warning system is the accurate prediction of arrival time and wave height of a forecasted tsunami at a specific location. Obviously, the accuracy of these predictions relies on the information of the initial water surface displacement near the source region, which is primarily determined by the seismic data. In many historical events, including the 2004 Indian Ocean tsunami, evidences have shown that accurate seismic data could not be verified until those events were over. To delineate the source region problem, in the United States, several federal agencies and states
DART II System Optional met sensors
Iridium and GPS antennas Electronic systems and batteries
Tsunami warning center
Optional sensor mast
Wind Barometric pressure Sea surface temperature and conductivity Air temperature/ relative humidity
Lifting handle 2.0 m
Surface buoy 2.5-m diameter 4000-kg displacement Swivel Acoustic transducers (two each) Tsunameter
25-mm chain (3.5m)
Signal flag
Glass ball flotation
1.8 m
Bidirectional acoustic telemetry
13-mm polyester
~75 m
25-mm nylon 22-mm nylon
19-mm nylon Acoustic transducer Acoustic release CPU Batteries Sensor Anchor 325 kg
13-mm chain (5 m) Anchor 3100 kg
Figure 12 A sketch of the second-generation DART (II) system.
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1000 − 6000 m
TSUNAMI
Newport, Oregon Highway 101 This map is intended for emergency planning purposes only
Yaquina Bay
139
These models can simulate a ‘design tsunami’ approaching a coastline, and they can predict which areas are most at risk to being flooded. The tsunami inundation maps are an integral part of the overall strategy to reduce future loss of life and property. Emergency managers and local governments of the threatened communities use these and similar maps to guide evacuation planning. As an example, the tsunami inundation map (Figure 13) for the coastal city of Newport (Oregon) was created using the results from a numerical simulation using a design tsunami. The areas shown in orange are locations that were flooded in the numerical simulation
Acknowledgment Highway 101
The work reported here has been supported by National Science Foundation with grants to Cornell University.
Figure 13 Tsunami inundation map for the coastal city of Newport, Oregon.
have joined together to create a warning system that involves the use of deep-ocean tsunami sensors to detect the presence of a tsunami. These deep-ocean sensors have been deployed at different locations in the Pacific Ocean before the 2004 Indian Ocean tsunami. After the 2004 Indian Ocean tsunami, several additional sensors have been installed and many more are being planned (see Figure 11). The sensor system includes a pressure gauge that records and transmits the surface wave signals instantaneously to the surface buoy, which sends the information to a warning center via Iridium satellite (Figure 12). In the event of a tsunami, the information obtained by the pressure gauge array can be used as input data for modeling the propagation and evolution of a tsunami. Although there have been no large Pacific-wide tsunamis since the inception of the warning system, warnings have been issued for smaller tsunamis, a few of which were hardly noticeable. This tends to give citizens a lazy attitude toward a tsunami warning, which would be fatal if the wave was large. Therefore, it is very important to keep people in a danger areas educated of tsunami hazards. Coastal Inundation Map
Using numerical modeling, hazards in areas vulnerable to tsunamis can be assessed, without the area ever having experienced a devastating tsunami.
See also Glacial Crustal Rebound, Sea Levels, and Shorelines. Heat and Momentum Fluxes at the Sea Surface. Land–Sea Global Transfers. Sea Level Variations Over Geologic Time. Seismology Sensors. Sensors for Mean Meteorology. Sensors for Micrometeorological and Flux Measurements. Turbulence Sensors. Wave Generation by Wind. Waves on Beaches.
Further Reading Geist EL (1998) Local tsunami and earthquake source parameters. Advances in Geophysics 39: 117--209. Hokkaido Tsunami Survey Group (1993) Tsunami devastates Japanese coastal region. EOS Transactions of the American Geophysical Union 74: 417--432. Kajiura K (1981) Tsunami energy in relation to parameters of the earthquake fault model. Bulletin of the Earthquake Research Institute, University of Tokyo 56: 415--440. Kajiura K and Shuto N (1990) Tsunamis. In: Le Me´haute´ B and Hanes DM (eds.) The Sea: Ocean Engineering Science, pp. 395--420. New York: Wiley. Kanamori H (1972) Mechanism of tsunami earthquakes. Physics and Earth Planetary Interactions 6: 346--359. Kawata Y, Benson BC, Borrero J, et al. (1999) Tsunami in Papua New Guinea was as intense as first thought. EOS Transactions of the American Geophysical Union 80: 101, 104--105. Keating BH and Mcguire WJ (2000) Island edifice failures and associated hazards. Special Issue: Landslides and Tsunamis. Pure and Applied Geophysics 157: 899--955.
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TSUNAMI
Liu PL-F, Lynett P, Fernando H, et al. (2005) Observations by the International Tsunami Survey Team in Sri Lanka. Science 308: 1595. Lynett PJ, Borrero J, Liu PL-F, and Synolakis CE (2003) Field survey and numerical simulations: A review of the 1998 Papua New Guinea tsunami. Pure and Applied Geophysics 160: 2119--2146. Mansinha L and Smylie DE (1971) The displacement fields of inclined faults. Bulletin of Seismological Society of America 61: 1433--1440. Satake K, Bourgeois J, Abe K, et al. (1993) Tsunami field survey of the 1992 Nicaragua earthquake. EOS Transactions of the American Geophysical Union 74: 156--157. Shibayama T, Okayasu A, Sasaki J, et al. (2005) The December 26, 2004 Sumatra Earthquake Tsunami, Tsunami Field Survey in Banda Aceh of Indonesia. http://www.drs.dpri.kyoto-u.ac.jp/sumatra/indonesia-ynu/ indonesia_survey_ynu_e.html (accessed Feb. 2008). Synolakis CE, Bardet J-P, Borrero JC, et al. (2002) The slump origin of the 1998 Papua New Guinea tsunami.
Proceedings of Royal Society of London, Series A 458: 763--789. Tsuji Y, Matsutomi H, Tanioka Y, et al. (2005) Distribution of the Tsunami Heights of the 2004 Sumatra Tsunami in Banda Aceh measured by the Tsunami Survey Team. http://www.eri.u-tokyo.ac.jp/namegaya/sumatera/ surveylog/eindex.htm (accessed Feb. 2008). von Huene R, Bourgois J, Miller J, and Pautot G (1989) A large tsunamigetic landslide and debris flow along the Peru trench. Journal of Geophysical Research 94: 1703--1714. Wang X and Liu PL-F (2006) An analysis of 2004 Sumatra earthquake fault plane mechanisms and Indian Ocean tsunami. Journal of Hydraulics Research 44(2): 147--154. Yeh HH, Imamura F, Synolakis CE, Tsuji Y, Liu PL-F, and Shi S (1993) The Flores Island tsunamis. EOS Transactions of the American Geophysical Union 74: 369--373.
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TURBULENCE IN THE BENTHIC BOUNDARY LAYER
& 2008 Elsevier Ltd. All rights reserved.
Introduction Fluids do not slip at solid boundaries. The fluid velocity changes from 0 to a speed that matches the ‘far field’ in a transition, or boundary layer, where friction and shear (the rate of change of velocity with distance from the boundary) are strong. The thickness of the ocean bottom (benthic) boundary layer is determined by the bottom stress and the rate of rotation of the Earth. The benthic boundary layer is usually thin (O(10 m)) compared to typical ocean depths of B4000 m. However, in coastal regions which are shallow, and where currents and thus friction are relatively strong compared to the deep ocean, the benthic boundary layer may span most of the water column. The boundary layer can be separated into several layers within which some forces are much stronger than others. Neglect of the weaker forces leads to scaling and parametrization of the flow within each layer. The benthic boundary layer is usually considered to consist of (1) an outer or Ekman layer in which rotation and turbulent friction (Reynolds stress) are important; (2) a very thin (O(10 3 m)) viscous layer right next to the boundary where molecular friction is important; and (3) a transitional layer between these, usually called the logarithmic layer, in which turbulent friction is important (Figure 1). The pressure gradient is an important force in all the three layers. Because the velocity profile within the logarithmic layer must match smoothly with both the Ekman layer above and the viscous layer below, it will be considered last. This discussion is framed in the context of a neutrally-stratified ocean remote from the free surface. Additional constraints due to stratification and proximity to the free surface are noted later.
The Ekman Layer Most of the open ocean is essentially frictionless and in geostrophic balance, being well described by a
balance between the Coriolis force which pushes the flow to the right (in the Northern Hemisphere) and the pressure gradient which keeps it from veering (Figure 2(a)).This picture changes as we approach the bottom. Friction acts against the flow and decreases the velocity U. However, the pressure gradient remains and is not completely balanced by the Coriolis force fU. The current backs leftward so that friction, which is directed against the current, establishes a balance of forces in the horizontal plane (Figure 2(b)). Progressively closer to the bottom, the increasing friction slows the flow and brings it to a complete halt right at the bottom while also further backing the flow direction. A vertical profile of the two components of the horizontal velocity might look like those depicted in Figure 3. The equations of motion and their boundary conditions are 1 @P 1 @tx 1 @P 1 @ty ; fU ¼ þ þ fV ¼ r @x r @z r @y r @z U ¼ Ug ; V ¼ Vg ; tx ¼ ty ¼ 0 as z-N U ¼ V ¼ 0 at z ¼ 0
H =u* /f
½1
Ekman height
Z
R. Lueck and L. St. Laurrent, University of Victoria, Victoria, BC, Canada J. N. Moum, Oregon State University, Corvallis, OR, USA
»0.03H Log layer
Linear viscous layer
»0.001m U Figure 1 A conceptual sketch of the three sublayers forming the bottom boundary layer. The pressure-gradient, friction, and Coriolis forces are in balance in the Ekman layer while only friction and pressure-gradient forces are significant in the logarithmic and viscous layers. In the logarithmic layer, friction stems predominantly from the Reynolds stress of turbulence, whereas in the viscous layer it comes mainly from molecular effects.
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141
142 (a)
TURBULENCE IN THE BENTHIC BOUNDARY LAYER No friction
(b)
−∂P/∂y
Friction −∂P/∂y
U
U
y
the bottom, that is fUg ¼
1 @P ; r @y
fVg ¼
1 @P r @x
½2
and if the density is homogeneous within the boundary layer, the pressure gradient is independent of height within this layer. Substituting [2] into [1] gives the so-called Ekman equation for the boundary layer, namely
fU fU
f ðV Vg Þ ¼
x Figure 2 Plan view of the balance of forces in the geostrophic flow far above the bottom (a) and in the Ekman layer (b). The current, U, is directed to the right in the positive x-direction. Far above the bottom, the pressure gradient in the y-direction is balanced by Coriolis force in the opposite direction and this force is always directed to the right of the current (in the Northern Hemisphere). Within the Ekman layer, friction, t, acts against the current. A balance of forces in ‘both’ the x- and y-directions is only possible if the current backs anticlockwise when viewed from above.
1 @tx 1 @ty ; f ðU Ug Þ ¼ r @z r @z
½3
It is convenient to assume that the bottom stress has no y-component so that the bottom stress t0 ¼ tx ð0Þ is directed entirely in the x-direction, that is, ty ð0Þ ¼ 0. Solving [3] for the velocity profile requires the relationship between stress and velocity, which is a major focus of boundary layer research. Fortunately, the height above the bottom over which friction is important can be determined using only dimensional analysis. For example, the x-component of velocity must be some function, F, of the parameters and variables in [3] and its boundary condition, tx ð0Þ ¼ t0 , so that U ¼ Fðr; t0 ; f ; zÞ
½4
Height
All the four variables in [4] cannot be independent. For example, r and t0 must always appear as a ratio because they are the only ones with the dimension of mass. The root of this ratio, u V U
has dimensions of velocity velocity’. It represents a velocity fluctuations in the other independent variable
Current
Figure 3 A conceptual velocity profile that may result from the effect of friction as depicted in Figure 2. A positive current component, V, is directed to the left of the geostrophic current.
where we have assumed that the vertical velocity, W, is zero (flat bottom), taken the bottom at z ¼ 0, assumed that both components of the stress ðtx ; ty Þ vanish far above the bottom, and assigned the x- and y-components of the geostrophic velocity to Ug and Vg ; respectively. The flow is geostrophic far above
H
rffiffiffiffiffi t0 r
½5
and is called the ‘friction scale for the turbulent boundary layer. The only is
rffiffiffiffiffi 1 t0 u ¼ f f r
½6
and this is the only dimensional group that can be used to nondimensionalize z, the height above the bottom. Thus, the velocity profile must be U Ug =u ¼ Fu ðz=HÞ ðV Vg Þ=u ¼ Fv ðz=HÞ
½7
where Fu and Fv are universal functions. Equation [7] is usually called the ‘velocity defect law’. The order of
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TURBULENCE IN THE BENTHIC BOUNDARY LAYER
magnitude of the height H of the boundary layer, that is, the scale over which friction is important, is usually called the Ekman height. The actual height to which friction is important is within a factor of order unity of H. The Ekman height can also be considered the transition height; for z{H, friction dominates over the Coriolis force while above this level, the reverse holds. An important effect of rotation is that the thickness of the BBL does not grow in the downstream direction (for uniform bottom conditions) whereas the boundary layer over a nonrotating and flat surface grows downstream. Numerical values for the Ekman height can be derived from a traditional formulation of the bottom stress in terms of a drag coefficient, such as t0 ¼ rCD Ug2
½8
where the drag coefficient, CD, must depend on the bottom characteristics, such as roughness. Typical values are CDE0.002. Using a geostrophic flow of UgE0.1 m s 1 commonly found in the open ocean and f ¼ 1 10 4 s 1 gives a friction velocity of u ¼ 4:5 103 m s1 and an Ekman height of H ¼ 45 m which is 100 times smaller than the average ocean depth. The friction layer is thus thin compared to the ocean depth, as assumed. Ekman solved [3] almost a century ago for the special case of a stress proportional to the shear. That is, tx ¼ rKV
@U ; @z
ty ¼ rKV
@V @z
½9
where KV is the eddy viscosity. The mathematically elegant spiral predicted by [3] and [9] is presented in standard textbooks on fluid mechanics. However, the predicted profile is not directly observed due to a number of complicating factors, such as complex boundary geometries, temporal variability in stress acting in the boundary layer, nonconstant eddy viscosity, and nonlinear dynamics. Despite these difficulties, very nice Ekman spirals have been documented when data of sufficient quantity and quality have been carefully analyzed. Trowbridge and Lentz provide an excellent contemporary example of bottom boundary layer observations and analysis (see Further Reading). They show that Ekman balance dynamics are recovered with adequate time averaging. They also show how the traditional Ekman equations presented above must be modified to include important buoyancy effects occurring in a stratified boundary layer. An additional review of interest, focused more on the Ekman spiral extending from the ocean surface boundary layer, is given by Rudnick.
143
Viscous Sublayer Very near to a smooth bottom, z{H, a layer forms in which momentum is transferred only by molecular diffusion. In general, the stress tx ¼ r
dU ru0 w0 dz
½10
is the sum of the shear stress due to molecular friction (first term on the right-hand side of [10]) and the Reynolds stress ru0 w0 ; where ¼ m=r is the kinematic molecular viscosity (E1 10 6 m2 s 1). The covariance u0 w0 of horizontal, u0; and vertical, w0; velocity fluctuations leads to a transfer of momentum from the fluid toward the wall. Very near the wall, vertical velocity fluctuations are strongly suppressed (no normal-flow boundary condition) and the Reynolds stress is negligible compared to molecular friction. The Ekman height, H, is not an appropriate parameter for nondimensionalizing the height above the bottom in the thin viscous layer. Rather, the viscous scale is used: d ¼ =u
½11
Using [3] the nondimensionalized momentum balance is @ tx =u2 d V Vg ¼ Hu @ ðz=dÞ @ ty =u2 d U Ug ¼ Hu @ ðz=dÞ
½12
To estimate the magnitude of the terms on the righthand side of [12], we note the following. From [8], the ratio of the geostrophic speed to friction velocity 1=2 is related to the drag coefficient by Ug =u ¼ CD ; and this equals approximately 25. The velocity is at most comparable to the geostrophic velocity, so the factor ðU Ug Þ=u is no more than about 25. Even for very weak flows, the terms in [12] are smaller than O(10 3). Thus, the vertical divergence of the stress is zero and the stress itself is constant. When the stress stems entirely from molecular friction, the only possible velocity profile is a linear one that has a shear which is commensurate with the bottom stress, that is, U zu ¼ zþ ¼ u
½13
Laboratory observations of flow over smooth surfaces show that [13] holds to about z þ E5 and this innermost region is called the ‘viscous sublayer’. A
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144
TURBULENCE IN THE BENTHIC BOUNDARY LAYER
typical dimensional thickness for the viscous sublayer is 5=u E0:001 m. Thus, this layer never extends more than a few millimeters above the bottom. Most of the ocean bottom is not ‘smooth’ compared to this scale.
The Wall Layer Further above the bottom but still well within the extent of the Ekman layer, for =u {z{H ¼ u =f, neither the Ekman height, H, nor the molecular viscosity, n, can be relevant parameters controlling the velocity profile. The only parameter that can nondimensionalize the vertical height is either the thickness of the viscous sublayer or the characteristic height of bottom roughness features, z0. Equation [12] is still the appropriate nondimensional momentum balance if we substitute z0 for d. The lefthand side of [12] is no longer as small as for the viscous sublayer but it is still small compared to unity, and the stress can be taken as constant. Thus, the wall layer and the viscous sublayer are usually called the constant-stress layer. The stress [10], however, is now entirely due to the Reynolds stress. Because the bottom stress has no component in the y-direction, there is also no bottom velocity in this direction. The only parameters that control the velocity profile are the bottom stress and the roughness height. On purely dimensional grounds, we have near the wall: V=u ¼ 0 U=u ¼ g2 ðz=z0 Þ
½14
where g2 is a yet to be determined universal function. Equation [14] is the ‘law of the wall’ for rough bottoms. The law of the wall must be matched to the velocity-defect law [7] and this is usually done by matching the shear rather than the velocity itself. The result is that Vg ¼ Fv ð0Þ ¼ A u U 1 z ¼ ln u k z0 Ug 1 H C ¼ ln u k z0
½15
where k ¼ 0.4 is von Karman’s constant and atmospheric observations indicate that AE12 and CE4. These equations are valid for z/z0c1 and z/H{1 ‘simultaneously’. Thus, the velocity increases logarithmically with increasing height and this profile
ultimately turns into an ‘Ekman’-like spiral that matches the geostrophic flow at z ¼ O(H). A thin viscous sublayer may underlie this profile if the bottom is very smooth, in which case z0 is chosen to match the profile given by [13] for the same bottom stress. It is frequently convenient to express the stress in terms of an eddy viscosity and the shear such as in [9]. However, a constant stress and a logarithmic velocity profile make the eddy viscosity proportional to height, namely K ¼ u kz
½16
Thus, a constant eddy diffusivity is not a good model for the wall layer and may well be inappropriate in much of the Ekman layer. The Reynolds stress in the presence of a shear leads to the production of turbulent kinetic energy (TKE) within the wall layer. It is thought that almost all of the TKE is dissipated locally and that the rate of dissipation is given by e ¼ u0 w0
@U u3 ¼ kz @z
½17
Thus, profiles of the rate of dissipation of kinetic energy provide an alternate measure of the bottom stress to that which can be derived from the velocity profile.
Observations Values of the bottom stress are required for two major purposes: as a boundary condition for flows above the bottom and for the prediction of sediment motions. The near-bottom velocity profile [15] provides a convenient method for estimating the bottom stress through a fitting of U against the logarithm of z. This profile method is the one most frequently used to estimate the bottom stress. Point current meters have been placed within a few meters of the bottom and, under the assumption that they are within the logarithmic region, the bottom stress was estimated from as few as a pair of current meters. Some bottom velocity ‘profile’ measurements were accompanied by concurrent measurements of the turbulent fluctuations of along-flow and vertical velocity components. The covariance of these fluctuations, ru0 w0 ; is an unambiguous measure of the Reynolds stress and, when this stress is extrapolated to the bottom, it usually agrees closely with the stress (ru2 ) inferred from the slope of the logarithmic velocity profile. (Readers are referred to the article by Trowbridge and Lentz in ‘Further Reading’, an excellent source of citations to past observational studies.)
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TURBULENCE IN THE BENTHIC BOUNDARY LAYER
Taking profiles of velocity within the BBL is very difficult. Consequently, there is very little observational evidence on the form of the velocity profile. One of the best deep-ocean velocity profiles was taken in the North Atlantic Western Boundary Current over the Blake Outer Ridge and reached to within 5 m of the bottom (Figure 4). The potential density was homogeneous within 250 m of the bottom and so the pressure gradient was independent of height as assumed in [3]. The current in the upper parts of the homogeneous layer was 0.22 m s 1 and directed along the isobaths (approximately southward). The along-slope current had a very slight maximum at 40 m, decreased sharply below 15 m, and dropped to 0.18 m s 1 at 5 m. The full decay to zero current at the bottom was not resolved for instrumental reasons. The cross-slope current was negligible further than 50 m above the bottom. It increased to 0.025 m s 1 at 5 m and was consistently directed to the left of the along-slope current (approximately eastward). The veering of the velocity vector with height above the bottom was like that depicted in Figures 2 and 3 and reached a maximum of 81 at the lowest observation located at 5 m. Simultaneous measurements of the rate of dissipation of TKE indicate that the turbulence was negligible for heights greater than 50 m above the bottom. The dissipation rate decreased monotonically with increasing height up to 50 m. Above this height, it was small and fairly uniform. Thus, the frictional layer was 50-m thick and 5 times thinner than the homogeneous layer. It is common to find different heights for the homogeneous (‘mixed’) and the turbulent (‘mixing’) layers. The height of the Ekman
layer, H, predicted by [6] was 120 m and the actual height to which friction was important was close to the expected value of kH ¼ 50 m, where k ¼ 0.41 is the von Karman constant. The height of the logarithmic layer [15] has not been extensively surveyed and based on the scaling arguments it must be small compared to the Ekman height. Measurements in a tidal channel indicate that profiles depart from a logarithmic form at about 3–4% of the Ekman height. The height of the constant stress layer cannot be greater than the logarithmic profile height. For horizontally homogeneous bottom roughness, such as flat sand and fine gravel, the roughness height, z0, is c. 30 times smaller than the actual roughness. The notion is that the velocity profile reaches zero somewhere below the highest bottom features. Thus, there must be considerable local variations of the velocity profile for heights less than zE30z0 and [15] represents a horizontally averaged velocity profile. The constancy of z0 is not well established for any particular site nor does it increase consistently with increasing bottom roughness. Cheng et al. found a systematic decrease in z0 with increasing speed above 0.2 m s1 and attributed this to the onset of sediment motions and its smoothing effect upon the bottom. The bottom roughness is seldom horizontally homogeneous and the major contribution to roughness comes from bedforms (e.g., ripples and sand waves) and other features with horizontal scales far greater than the largest pieces of bottom material. Thus, bottom profiles well above zE30z0 should show horizontal variations (Figure 5). For example, a
U
60
z (m)
145
U
V
40
20
0
0
0.1
0.2 −1
(ms )
Figure 4 A sketch of the along- , U, and across-isobath, V, flow over the Blake Outer Ridge in the North Atlantic Western Boundary Current as reported by Stahr and Sanford (1999). Dashed lines within 5 m of the bottom are hypothetical extensions.
Figure 5 Conceptual sketch of spatial variations in the vertical profile of velocity over bedforms with long horizontal scales, such as sand waves. The vertical and dashed lines give a zero-velocity reference. The flow accelerates and stream-lines compress on the ‘upwind’ side of crests and the flow decelerates and its streamlines dilate on the lee side. This causes a pressure drop in the flow direction. If slopes are steep, flow separation and back flow may occur in the troughs and over the leesides as depicted for the right profile.
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146
TURBULENCE IN THE BENTHIC BOUNDARY LAYER
wavy bottom may appear locally to have a roughness scale commensurate with the bottom material (such as sand) but at a height comparable to the amplitude of sand waves, the bottom turns ‘rough’ as the turbulent eddies respond to the larger horizontal-scale structures on the bottom and not just the local features. Additional drag will be exerted on the flow by the pressure differences across sand waves (or other obstacles) due to stream-line asymmetry and outright flow separation when the slope on the lee side of objects is very steep. This is usually labeled ‘form drag’ due to its similarity to the drag on bluff bodies. This feature was first observed by Chriss and Caldwell in 1982 in profiles taken over the continental shelf off Oregon. They found two logarithmic layers with differing slopes (Figure 6a). The lower layer extended to 0.1 m, and its logarithmic slope implies a friction velocity of u ¼ 0:004 m s1 : This layer appears to be associated with skin friction over a fairly smooth surface. The upper layer reached to at least 0.2 m and its much greater slope is indicative of stress due to form drag. Form drag can also result when boundary layer turbulence is produced by wave-like variations in the seabed. Sanford and Lien
report on measurements from a tidal channel, where sand ripples of 0.3-m amplitude and 16-m wavelength were present and oriented span-wise to the flow direction. They find a double logarithmic velocity profile (Figure 6b) similar to that observed by Chriss and Caldwell in 1982. The slope of the velocity–log z relation increased by a factor of 2 near z ¼ 4 m, even though the seabed amplitude variations were much smaller than this height. The effect of long horizontal-scale features on the flow over the bottom is still being investigated. An alternate method of estimating the bottom stress is provided by the dissipation profile technique. Profiles of the rate of dissipation have verified the inverse height dependence predicted by [17] for heights of up to 10 m. However, when the estimates of bottom stress derived from dissipation profiles are compared to the stress estimated from a fit of the velocity profile to a logarithmic form, the dissipation-based estimates are typically 3 times smaller. Momentum budgets for bottom streams such as the Mediterranean outflow are consistent with the drag determined from the velocity profile but not with the drag inferred from dissipation profiles. There is still Tidal channel
Oregon shelf s −1
20 m
m
5
1
3
2
2
u * = 0.0 24 m s−
3
z (m)
5
43
7
u * =0 .0
7
m s −1
10
u = * 0.00 4
z (cm)
u * =
0.
01
10
s −1
15
1
1 (a)
0.08
0.1 U (m s −1)
0.12 (b)
0.5
0.6 U (m s −1)
0.7
Figure 6 A sketch of velocity profiles plotted against the logarithm of height above the bottom based on data reported by Chriss and Caldwell (1982) and Sanford and Lien (1999). Approximately 10 data points were available for each regression (a) whereas data from about 100 different depths were used for (b). Both profiles imply a jump by a factor of 2 in friction velocity and an increase by a factor of 4 in stress for the upper logarithmic layer compared to the lower layer. The grey-shaded line is the law-of-the-wall scaling modified by proximity to the free surface.
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TURBULENCE IN THE BENTHIC BOUNDARY LAYER
no satisfactory explanation for such discrepancies. Recent observations on the Oregon shelf include those of Nash and Moum, who document the hydraulic production of bottom boundary layer turbulence at a topographic bump in the presence of a coastal jet. Their measurements appear to be dominated by a form drag stress-layer, with u C0:00520:01 m s1 estimated using the dissipation rate method. They find that the resulting form drag can be of sufficient magnitude to break the geostrophic balance of flow near the bump. Nash and Moum also document that the boundary layer properties can change significantly due variations in forcing and stratification over both short (O(1 day)) and long (O(1 year)) timescales.
Modifications due to Stratification and Proximity of the Free Surface In the absence of stratification and a close upper boundary, turbulence length scales increase linearly from z ¼ 0. However, turbulence scales are attenuated by stratification and by boundaries. Most commonly, unstratified near-bottom layers are capped by stratified layers. In these cases, the length scales of the turbulence cannot increase unbounded and are attenuated throughout the boundary layer (Perlin et al., 2005). In shallow tidal channels (such as is shown in Figure 6b), a similar effect ensues. This offers an alternate explanation to the two logarithmic layer model, in which a single velocity scale (u ) describe the full velocity profile (shown in grey in Figure 6b).
See also Benthic Boundary Layer Effects. Ekman Transport and Pumping. Fluid Dynamics, Introduction, and Laboratory Experiments. Grabs for Shelf Benthic Sampling. Non-Rotating Gravity Currents. Overflows and Cascades. Rotating Gravity Currents. Sub-sea Permafrost. Turbulence Sensors. UnderIce Boundary Layer.
147
Further Reading Cheng RT, Ling C-H, and Gartner JW (1999) Estimates of bottom roughness length and bottom shear stress in South San Francisco Bay, California. Journal of Geophysical Research 104: 7715--7728. Chriss TM and Caldwell DR (1982) Evidence for the influence of form drag on bottom boundary layer flow. Journal of Geophysical Research 87: 4148--4154. Dewey RK and Crawford WR (1988) Bottom stress estimates from vertical dissipation rate profiles on the continental shelf. Journal of Physical Oceanography 18: 1167--1177. Johnson GC, Lueck RG, and Sanford TB (1995) Stress on the Mediterranean outflow plume. Part 2: Turbulent dissipation and shear measurements. Journal of Physical Oceanography 24: 2072--2083. Lueck RG and Huang D (1999) Dissipation measurement with a moored instrument in a swift tidal channel. Journal of Atmospheric and Oceanic Technology 16: 1499--1505. Nash JD and Moum JN (2001) Internal hydraulic flows on the continental shelf: High drag states over a small bank. Journal of Geophysical Research 106: 4593--4612. Perlin A, Moum JN, Klymak JM, Levine MD, Boyd T, and Kosro PM (2005) A modified law-of-the-wall applied to oceanic bottom boundary layers. J. Geophysics Research 110: doi:10.1029/2004JC002310. Rudnick D (2003) Observations of momentum transfer in the upper ocean: Did Ekman get it right? In: Muller P and Garrett C (eds.) Proceedings of the ‘Aha Huliko’a Hawaiian Winter Workshop, pp. 163--170. Honolulu, HI: University of Hawaii. Sanford TB and Lien R-C (1999) Turbulent properties in a homogeneous tidal bottom boundary layer. Journal of Geophysical Research 104: 1245--1257. Stahr FR and Sanford TB (1999) Transport and bottom boundary layer observations of the North Atlantic deep western boundary current at the Blake outer ridge. Deep-Sea Research 46: 205--243. Trowbridge JH and Lentz SJ (1998) Dynamics of the bottom boundary layer on the North California Shelf. Journal of Physical Oceanography 28: 2075--2093.
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TURBULENCE SENSORS N. S. Oakey, Bedford Institute of Oceanography, Dartmouth, NS, Canada Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3063–3069, & 2001, Elsevier Ltd.
Introduction This article describes sensors and techniques used to measure turbulent kinetic energy dissipation in the ocean. Dissipation may be thought of simply as the rate at which turbulent mechanical energy is converted into heat by viscous friction at small scales. This is a complicated indirect measurement requiring mathematical models to allow us to envisage and understand turbulent fields. It will require using this theory to understand how sensors might be developed using basic principles of physics to measure properties of a turbulent field to centimeter scales. Instruments must be used to carry these sensors into the ocean so that the researcher can measure its turbulent characteristics in space and time. It is also this sensor–instrument combination that converts the sensor output into a quantity, normally a voltage varying in time, that is used by the experimenter to calculate turbulent intensity. Thus, both the characteristics of sensors and the way in which the sensor– instrument combination samples the environment must be understood and will be discussed below.
Understanding Turbulence in the Ocean There is no universally accepted definition of turbulence. Suppose that one stirs a bowl of clear water and injects some colored dye into it. One sees that filaments of dye become stretched, twisted and contorted into smaller and smaller eddies and eventually the bowl becomes a uniform color. This experiment leads to one definition of turbulence. It includes the concept that eddies in the water are distributed randomly everywhere in space and time, that energy is transferred from larger to smaller eddies, and that over time the mean separation of the dyed particles increases. In contrast, the ocean is typically stratified through a density that is determined by the temperature and salt in the water as well as the pressure. In this environment, a vertical shear in the velocity in the water column can be large enough to overcome the stability. Energy from the mean flow is converted
148
into large-scale eddies determined by flow boundary conditions that characterize turbulent kinetic energy at its maximum scales. Further vortex stretching creates smaller and smaller eddies resulting in a turbulent cascade of energy (velocity fluctuations) to smaller scales until viscous forces begin to dominate where the energy is eventually dissipated as heat. This article focuses on sensors to measure this dissipation process directly by measuring the effect of viscosity on the turbulent cascade. The irregular and aperiodic velocity fluctuations in space and time characteristic of turbulence, accompanied by energy transfer between scales and associated fluid mixing, may be described mathematically through nonlinear terms in the Navier–Stokes equation. Nevertheless, it is difficult to solve numerically in oceanographic applications. At the dissipation scales, typically a few meters and smaller, we normally assume that the turbulent field is homogenous and that it has definable statistical averages in all parts of the field. We further assume that direction is unimportant (isotropy) and statistical distributions depend only on separation distances between points. With the turbulence controlled only by internal parameters, we assume the nature of the nonlinear cascade of energy from large to small scales generates a universal velocity spectrum. An example of this spectrum is shown schematically in Figure 1A. At low wavenumbers, k, no energy is taken out by viscous dissipation, so the energy flux, e, across each wave number, or down the cascade, is constant. Through dimensional arguments, the three-dimensional turbulent energy spectrum, EðkÞ in this region (called the inertial subrange) as a function of wavenumber k is given by EðkÞ ¼ ae2=3 k5=3
½1
where a is a constant determined experimentally to be approximately 1.5. In practice the three-dimensional spectrum given in eqn [1] cannot easily be measured and one must use the one-dimensional analogy where k is replaced by a component ki . At higher wavenumbers or smaller scales the velocity gradient spectrum (obtained by multiplying the spectrum in eqn [1] by the square of the wave number k2 ) shows more clearly where dissipation occurs. Figure 1B shows the spectra of velocity shear for velocity fluctuations for one component of k for values of e most typically found in the ocean. In this case, the spectra of fluctuations transverse to the
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TURBULENCE SENSORS
149
The factor 2p gives a length scale from the radian wave number. This is an important scale for the design of instruments and sensors because it defines the smallest diameter eddies that must be measured. The dissipation e is given by integrating the spectrum shown in Figure 1B.
e ¼ 15v
N ð
k21 E1 ðk1 Þdk1
0
¼ 7:5v
N ð
k21 E2 ðk1 Þdk1
½3
0
E1 ðk1 Þ is the one-dimensional wavenumber spectrum of longitudinal velocity, and E2 ðk1 Þ is the onedimensional spectrum of transverse velocity and one assumes isotropy to estimate the factors 15 and 7.5, respectively. In practice, the upper integration limit may be replaced with the viscous cutoff scale. For the transverse turbulent velocity u, the shear variance in the z direction, ðdu=dzÞ2 is equivalent to the integral of equation [3] and e is given by 15 du 2 e¼ v 2 dz
Figure 1 (A) The universal, velocity spectra for dissipation rates that typically occur in the ocean. Power density in velocity is plotted as a function of wavenumber. The shape of the spectrum remains the same but, as the energy in the turbulent field increases, the spectrum moves to higher wavenumbers and to higher intensities. (B) The equivalent universal, velocity shear spectra. (A) and (B) both show the inertial subrange and dissipation region, but in (B), the dissipation portion is more strongly emphasized.
measurement direction are shown but the picture for along-axis fluctuations would look almost identical. At the highest wavenumbers (smallest scales), viscous dissipation reduces the energy per unit wavenumber to zero. At small scale, it is assumed that turbulent motion is determined only by kinematic viscosity, v( ¼ 1.3 106 m2 s1 at 101C), and the rate, e, at which energy passed down from larger eddies, must be dissipated. By dimensional arguments the length scale at which viscous forces equal inertial forces, and viscosity dissipates the turbulent energy as heat, is given by viscous cutoff scale 1=4 ½2 Lv ¼ 2p v3 =e
½4
These assumptions are important to the way in which sensors are designed. A common way to observe turbulent fields is by making measurements of velocity and other mixing quantities along a trajectory through a turbulent field assuming that it is frozen in space and time. Measurement along a line, recorded as a time-series (Figure 2), is interpreted as spatial variability by assuming stationarity and using the known sensor velocity to convert into distance. Standard Fourier transform techniques allow one to generate spectra similar to those in Figure 1 from which dissipation, e, may be estimated. If there is a temperature gradient in the water column when turbulence is generated, the velocity field strains the temperature field, creating strongly interleaved temperature filaments over the vertical range of the overturn. The temperature microstructure intensity depends not only on the mean gradient but also on the energy in the turbulent field, in particular dissipation, e. Temperature fluctuations recorded as a time-series (Figure 2) can be represented by spectra similar to those shown in Figure 1. As with the velocity fluctuations, there is a subrange where diffusive and viscous effects are unimportant where temperature fluctuations are transferred towards higher wave numbers. Temperature spectra persist to length scales smaller than the viscous cutoff scale. In this range, not only kinematic viscosity, v, and dissipation, e, are important but also, thermal diffusion, kT (E1.4 107 ms s1). The cutoff
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layers on continental shelves. (To put these numbers into a simple perspective, energy dissipated in the ocean may range from the almost insignificant rate of 100 W km3 to the very large rate of 100 MW km3.) Present sensors and instruments are capable of measuring over this range of dissipation. Regions of higher dissipation such as river outflows and tidal channels are not normally measurable with sensors and instruments described here.
10
uz
Depth (m)
20
Tz
30
Measuring Dissipation in the Ocean
40
50
60
70
8
10
12 14 16 Temperature (°C)
18
20
Figure 2 A representative vertical profile of temperature is shown from the surface to bottom obtained with a vertical falling instrument. In panels at the right are shown expanded portions of the velocity shear (uz ) and the gradients in temperature (Tz ). The panels represent small sections of the vertical record that are treated as time-series to calculate spectra similar to those in Figure 1. The upper panel of Uz at mid-depth is a region of low dissipation and the one below represents higher dissipation.
wavelength for temperature fluctuations is given by 1=4 LT ¼ 2p vk2T =e
½5
Under restricted circumstances, the temperature gradients or temperature microstructure can be measured in the ocean to this scale. Under these circumstances one can determine LT and hence estimate dissipation e. The sensors used most commonly in oceanography to measure dissipation make use of the above ideas. Velocity fluctuations may be used to determine dissipation e directly using eqns [3] or [4]. Measuring temperature fluctuations allows dissipation to be calculated indirectly from eqn [5]. The units used to express dissipation in the ocean are W kg1 (watts of mechanical energy converted into heat per kilogram of sea water). Typical values range from 1010 W kg1 in the deep ocean to 104 W kg1 in active boundary
The most common technique of estimating dissipation in the ocean involves measuring small-scale velocity and temperature fluctuations. This may be accomplished by dropping a profiler vertically, towing one horizontally or setting it at a fixed position and measuring the fluctuations in velocity and temperature as the water moves past the sensors. This allows a time-series of turbulent velocity fluctuations to be recorded. A typical platform used to measure dissipation in the ocean is a vertical profiler that falls typically at a speed of 0.5–1.0 ms1. There have been many such instruments built and each one typically carries a number of sensors to measure some components of the turbulent velocity as well as temperature microstructure. A sample time-series for a vertical profiler is shown in Figure 2. Assuming that the turbulent field is isotropic, homogeneous and stationary one can use the mean flow velocity to determine the wavenumber scale and calculate the one-dimensional turbulence spectrum, E1 ðk1 Þ or E2 ðk1 Þ, as defined above and from this determine the dissipation, e, using eqns [3] and [4]. As the turbulent dissipation gets larger, the wavenumber at cut-off gets larger. Alternatively, Lv and LT become smaller as shown in Figure 3(A). As one tries to measure higher dissipation one must have a sensor with better spatial resolution and higher frequency response. We convert from wavenumber, k (cycles m1), to frequency using the relationship f ¼ kV (Hz) where V (m s1) is the flow speed past the sensor. The cutoff frequencies corresponding to Lv and LT are given by fci ¼ V=Li. In practice, one does not have to measure the microstructure variance to the cutoff frequency because of the universal characteristic of the dissipation curves. A usual compromise is to consider that if 90% of the dissipation curve is measured then a satisfactory measure of dissipation can be achieved. This is summarized in Figure 3A which shows the sampling frequency that must be achieved to resolve a particular dissipation. (It must be remembered that to resolve the energy at any frequency one must sample at least twice that frequency.)
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LT and LV (cm)
TURBULENCE SENSORS
Sampling freq. (Hz)
(A)
(B)
10 5
LV LT
0 _ 10 10
_8
10
_6
_4
10
10
2000
LT
1000
LV 0 _ 10 10
_8
_6
10 10 _ Dissipation (W kg 1)
_4
10
Figure 3 (A) The decrease in the cutoff scale with increasing dissipation for viscous dissipation, Lv (eqn [2]) and thermal dissipation, LT (eqn [5]). (B) The sampling frequency that is required for a particular e for viscous dissipation, Lv and for thermal cutoff, LT. The upper and lower boundaries of the shaded bands correspond to measurement at flow speeds of 1.0 and 0.5 m s1, respectively.
Turbulence Dissipation Sensors Airfoil Probes
One of the most commonly used turbulence sensors to measure turbulent velocity fluctuations is called an airfoil probe. This sensor is an axially symmetrical airfoil made of flexible rubber surrounding a sensitive piezoelectric crystal. The sensitive tip of the probe approximates a parabola of revolution, several millimeters in diameter and about 1 cm long. The crystal generates a voltage proportional to the magnitude of a force applied perpendicular to its axis. The crystal is rigid in one transverse direction so responds to a cross force only in one direction. Thus, two sensors are required to measure the two transverse components of turbulent velocity fluctuations. The sensor is placed on the leading end of an instrument that is moving relative to the water at a mean speed V. In a mean flow along the axis of the shear probe, no lift will be generated and no force applied to the crystal. If there is an off-axis turbulent velocity, a lift will be generated which will apply a force to the piezoelectric crystal through the flexible rubber tip. Thus, the sensor will provide a voltage that is linearly proportional to the turbulent velocity. The effective resolution of the sensor is of order 1 cm, the smallest scale of turbulence that can be effectively measured by this sensor. From Figure 3, it can be seen that for values above 105 W kg1 this type of sensor will begin to underestimate dissipation. Normally the signal from the sensor is
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differentiated to emphasize the high frequency part of the turbulence spectrum. This gives the velocity shear, and analysis of this signal allows direct generation of spectra similar to the theoretical ones shown in Figure 1B. For this reason, airfoil probes are often called shear probes. These sensors measure the component of turbulence perpendicular to the drop direction of the instrument. As such, it is eqn [4]. Which is most relevant to calculating dissipation, e. Figure 3B, shows that to measure dissipation to 105 W kg1 in a flow speed of 1 m s1 (along the axis of the sensor) the output must be sampled to at least as rapidly as 200 Hz. Of the many instruments that use this sensor to measure dissipation, the most common are vertical profilers. Those used near the surface are often called tethered free-fall profilers because they have a light, loose line attached to the instrument for quick recovery and redeployment. The line is usually a data link to the ship where data are recorded on computers for analysis. Because of the intermittent nature of turbulence, it is important to have many profiles (or independent samples) in measuring dissipation to be able to obtain a statistically robust average value. For deeper measurements of dissipation, free-fall profilers are used that have no tether line. They are deployed to a predetermined depth in the ocean where their buoyancy is changed to allow them to return to the surface. These instruments record internally and can be inherently quieter than tethered free-fall instruments but are slower to recover and redeploy. In practice, both types of profilers can measure dissipation as low as 1010 W kg1. In shallow regions of high dissipation such as the bottom boundary layer of tidally generated flow over banks, in bottom river channels or in active regions such as the Mediterranean outflow tethered free-fall instruments have been most successful. Where the dissipation exceeds 105 W kg1, these profilers and the shear probe sensor give limited results. The airfoil probe has also been used successfully to obtain dissipation measurements horizontally. It has been used as a sensor on a towed fish pulled horizontally at speeds of order 1 m s1. The results look similar to those in Figure 2 where the depth axis is replaced by a horizontal axis and similar techniques to those described above are used to extract dissipation. Because of towline vibration, a towed instrument is generally noisier than a free-fall profiler. If the vibration noise of the platform is transferred to the airfoil sensor, it will generate velocity signals relative to the sensor indistinguishable from turbulence in the water with the sensor not vibrating. Generally, a measurable dissipation lower limit for these instruments of 109 W kg1 would be
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considered good. These shear probes have also been mounted on submarines for horizontal measurements. Nevertheless, this platform has had only limited use because of vehicle noise and expensive operating costs. More recently, unmanned submarines called autonomous underwater vehicles have been used as suitable platforms for turbulent kinetic energy measurements. They are expected to have similar noise characteristics to towed instruments. Another interesting way of obtaining horizontal measurements is to place shear probes on a moored instrument. The turbulence in the water is measured as it flows past the sensor at a speed V m s1. In this case, the water velocity must typically be faster than 0.1 m s1 for the measurements to be within the sensor capabilities and mooring vibrations generate similar problems to towed instruments. Thin Film Sensors
One of the original sensors used to measure turbulence and dissipation is called a hot film sensor. In these sensors, a platinum or nickel film is deposited on the surface near the conical tip of a glass rod of order 1 mm diameter and covered with a thin film of quartz to insulate it from the water. The film is heated to several degrees centigrade above the ambient temperature and special electronics are used to maintain a constant thin film temperature. Water flowing across the probe cools the platinum. Fluctuations in the current, required to keep the sensor at a constant temperature, are a measure of the turbulent velocity fluctuations along the axis of the sensor. This sensor measures the E1 ðk1 Þ component of the turbulent field as opposed to the E2 ðk1 Þ component measured by the shear probe. Therefore, the first part of the eqn [3] is relevant to estimating dissipation. The primary advantage of this sensor over the shear probe is that it has much smaller spatial resolution and a much higher frequency response. As one can see from Figure 3, this allows one to measure to higher dissipation rates. The disadvantages of this probe are that the electronics to run it are much more complicated than for shear probes and the sensors are more difficult to fabricate and quite expensive. They also require a lot of power to heat since they are very low in resistance (of order 5–10 O). Because the quartz insulation must be extremely thin to provide good heat transfer, thin films are also very fragile and easily damaged by impact with particles in the water. These probes do not provide an output voltage that is linear with turbulent velocity fluctuations. They also tend to be noisy and subject to fouling. They are seldom used today in ocean measurements.
Pitot Tubes
Another recently developed sensor used to measure dissipation makes use of a Pitot tube. If a Pitot tube is placed in water flowing at a speed W along its axis, the pressure generated by the flow is proportional to W 2 . This technique has been applied to turbulence measurements by carefully designing an axisymmetric port a few millimeters in diameter on the tip of a sensor of order 1 cm in diameter. By connecting the port to a very sensitive differential pressure sensor, fluctuations in pressure along the axis of the probe can be measured. Using suitable electronic circuits, a signal is produced that is linearly proportional to along-axis fluctuations in turbulent velocity. In this sense, it is similar to the heated-film sensor and different from the shear probe which measures fluctuations perpendicular to the mean flow. This sensor has been used in conjunction with a pair of shear probes to simultaneously measure all three components of turbulent velocity fluctuations. Temperature Microstructure Sensors
As outlined above, if there is turbulent mixing occurring in a region where there is a temperature gradient, the turbulent velocity will cause the temperature to be mixed. If, for example, warmer fluid overlays colder fluid, turbulence will move parcels of warm fluid down and cold fluid up. A temperature sensor that traverses a patch of fluid such as this will measure fluctuations in temperature as shown in Figure 2. The spectrum of these fluctuations can be used to determine the dissipation using eqn [5]. Because the molecular diffusivity of heat for water is much smaller than the molecular viscosity, the scale at which temperature fluctuations cease is about a factor of three smaller than the scale at which velocity fluctuations cease. This is shown clearly in Figure 3A that compares LT and Lv . These facts place a severe restriction on the speed and size of a temperature sensor compared to a shear probe, or alternatively limits the speed that an instrument may fall. For the same fall speed, a temperature sensor must be sampled at a much higher rate than a shear probe. The simplest temperature sensor with the precision and noise level to measure temperature microstructure in the ocean is the thermistor. The smallest thermistors that are used in sea water are a fraction of millimeter in diameter and have a frequency response of order 10 ms. At a flow speed of 1 m s1, one is able to delimit the spectrum of temperature for dissipations up to about 107 W kg1. Some success has been obtained by using very slow moving profilers that fall or rise at about 0.1 m s1. An alternative to the thermistor is a thin film
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thermometer. It is similar to the hot film velocity sensor described above and is constructed identically. Used as a thermometer, the change in the resistance of this sensor is a measure of change of temperature. Thin film sensors are faster than thermistors, typically with a time-constant of 2 ms which means that for any sensor velocity the temperature fluctuations may be measured to a higher wave number. These sensors are nevertheless at least an order of magnitude noisier than thermistors, which means that they are suitable for measuring microstructure only in regions where there are strong mean gradients. Using thermometry to measure dissipation is subject to large errors because, as indicated in eqn [5], dissipation is proportional to (LT Þ4 , and this requires accuracy in determining LT that is seldom achieved. Some success has been made using sensors that measure conductivity as a proxy for temperature. These sensors make use of the fact that the conductivity of sea water is determined by both salt and temperature and in most cases, the temperature causes most of the fluctuations. The techniques used are similar to those described above for temperature. Some of the sensors are smaller and faster than thermistors and less noisy than thin film thermometers. They are still limited to the same constraints as thermometers in that they must fully resolve the spectrum in order to estimate LT and utilize eqn [5].
allow water velocity fluctuations to be inferred. This configuration of sensors is generally mounted as a fixed array on a platform on the bottom and has been used to measure turbulent mixing in many places on continental shelves. This technique has the advantage over profiling dissipation sensors of measuring three components of velocity fluctuations over long periods of time at a single place. Dissipation is estimated from the k5=3 wavenumber range.
Acoustic Current Meters
E(k) E1(k1)
Acoustic techniques have also been used to measure water velocity in the ocean and indirectly to infer dissipation rates. One such technique utilizes an acoustic Doppler current meter optimized to measure vertical velocity fluctuations in the water column. In these instruments, a sound pulse is transmitted into the water and the sound scattered back to a sound receiver. The back-scattered pulse contains information about the water velocity because of the Doppler shift in the sound frequency. This technique is unable to measure to dissipation scales but instead, measures vertical velocities in the k5=3 wavenumber range defined by eqn [1]. By suitably defining a turbulent timescale, dissipation is estimated from the intensity in the fluctuations in the vertical velocity. This technique is very useful in studying turbulence in regions of intense mixing such as tidally driven flows. In another technique, an array of small acoustic transmitters and receivers is configured such that the transit time of a pulse of sound can be measured over a short distance of around 10–20 cm. Velocity fluctuations in the water change the transit time and
Conclusions The measurement of mixing rates in the ocean is important to our understanding of the distributions of temperature, salinity, and nutrients in the ocean. We need to understand this to include them correctly in climate and biological ocean models. The way in which energy is converted from sources at large scale and dissipated at small scales has required the development of a variety of ocean sensors. Some of these are described briefly above. It is hoped that enough of the key words and ideas have been put forward for the reader to understand some of the principles involved in turbulence measurement and at least some of the sensors and techniques used.
Symbols used a
E2(k1)
e f KT Lv LT u v V W z
An experimentally determined spectral constant Energy spectral density One-dimensional energy wavenumber spectrum – fluctuations along the axis of measurement One-dimensional energy wavenumber spectrum – fluctuations perpendicular to the axis of measurement Dissipation of turbulent kinetic energy measurement or sampling frequency molecular diffusivity of heat viscous cutoff scale temperature cutoff scale horizontal velocity fluctuation kinematic viscosity flow velocity along axis of sensor drop velocity distance coordinate (normally vertical)
See also Dispersion and Diffusion in the Deep Ocean. Fossil Turbulence. Internal Tidal Mixing. Intrusions. Island Wakes. Langmuir Circulation and Instability. Meddies and Sub-Surface Eddies. Mesoscale
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Eddies. Three-Dimensional (3D) Turbulence. Topographic Eddies Under-Ice Boundary Layer.
Further Reading Bradshaw P (1971) An Introduction to Turbulence and Its Measurement. Oxford, New York, Toronto, Sydney, Paris, Braunschweig: Pergamon Press. Dobson F, Hasse L, and Davis R (1980) Air–Sea Interaction Instruments and Methods. New York and London: Plenum Press. Frost W and Moulden TH (1977) Handbook of Turbulence, vol. 1: Fundamentals and Applications. New York: Plenum Press
Hinze JO (1959) Turbulence. New York, Toronto, London: McGraw-Hill. Journal of Atmospheric and Oceanic Technology (1999) 16(11), Special Issue on Microstructure Sensors. Neumann G and Pierson WJ (1966) Principles of Physical Oceanography. Englewood Cliffs, NJ: Prentice Hall. Patterson GK and Zakin JL (1973) Turbulence in liquids. Proceedings of the Third Symposium, 414pp., Department of Chemical Engineering, University of MissouriRolla. Summerhayes CP and Thorpe SA (1996) Oceanography, pp. 280--299. New York: John Wiley.
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UNDER-ICE BOUNDARY LAYER M. G. McPhee, McPhee Research Company, Naches, WA, USA J. H. Morison, University of Washington, Seattle, WA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3071–3078, & 2001, Elsevier Ltd.
Introduction Sea ice is in almost constant motion in response to wind, ocean currents, and forces transmitted within the ice cover itself, thus there is nearly always a zone of sheared flow between the ice and underlying, undisturbed ocean where turbulence transports momentum, heat, salt, and other contaminants vertically. The zone in which these turbulent fluxes occur, which can span from a few to hundreds of meters, is the under-ice boundary layer (UBL). This article describes general characteristics of the UBL, with emphasis on the physics of vertical turbulent transfer, specifically turbulent mixing length and eddy diffusivity. Extensive measurements of turbulence in the UBL, not available elsewhere, have not only made these ideas concrete, but have also provided quantitative guidance on how external forcing controls the efficiency of vertical exchange. Here we stress features that the UBL has in common with ocean boundary layers everywhere. The article on ice–ocean interaction emphasizes unique aspects of the interaction between sea ice and the ocean (see Ice–ocean interaction). While largely responsible for the relative paucity of oceanographic data from polar regions, sea ice also serves as an exceptionally stable platform, often moving with the maximum velocity in the water column. In effect, it provides a rotating geophysical laboratory with unique opportunities for directly measuring turbulent fluxes of momentum, heat, and salt at multiple levels in the oceanic boundary layer – measurements that are extremely difficult in the open ocean. Examples of important oceanographic boundary-layer processes first observed from sea ice include: (1) the Ekman spiral of velocity with depth; (2) Reynolds stress through the entire boundary layer, and its associated spiral with depth; (3) direct measurements of turbulent heat flux and salinity flux; (4) direct measurements of eddy viscosity and diffusivity in the ocean boundary layer; (5) the impact of surface buoyancy, both negative and positive,
on boundary layer turbulence, and (6) internal wave drag (‘dead water’) as an important factor in the surface momentum and energy budgets. The UBL differs from temperate open ocean boundary layers by the absence of strong diurnal forcing and of high frequency, wind-driven surface waves. It thus lacks the near surface zone of intense turbulence and dissipation associated with wave breaking, and organized Langmuir circulation due to the nonlinear interaction between waves and currents (e.g., the interaction of Stokes drift with near surface vorticity) (see Langmuir Circulation and Instability). On the other hand, quasi-organized roll structures associated with sheared convective cells have been observed under freezing ice, and are apparently a ubiquitous feature of freezing leads and polynyas. Large inertial-period oscillations in UBL horizontal velocity are observed routinely, especially in summer when the ice pack is relaxed. The annual cycle of buoyancy flux from freezing and melting mimics in some respects the diurnal cycle of heating and cooling, as well as the annual evolution of temperate ocean boundary layers. The range of surface forcing, with observations of surface stress ranging up to 1 Pa, and buoyancy flux magnitudes as high as 106W kg1, is comparable to that encountered in open oceans. All these factors suggest that similarities between the UBL and the open ocean boundary layer far outweigh the differences.
History and Basic Concepts Rotational Physics and the Ekman Layer
From 1893 to 1896, the Norwegian research vessel Fram drifted with the Arctic pack ice north of Eurasia in one of the most productive oceanographic cruises ever conducted. Among other important discoveries was the observation by Fridtjof Nansen, the great scientist–explorer–statesman, that the drift was consistently to the right of the surface wind. Nansen surmised that this effect arose from the differential acceleration in a rotating reference frame (the earth) on the sheared turbulent flow beneath the ice, and interested the young Swedish scientist, V.W. Ekman, in the problem. Ekman discovered an elegantly simple solution to the coupled differential equations describing the steady-state boundary layer, which exhibited attenuated circular rotation with depth (spirals) in both velocity and stress (momentum flux). The solution includes a constant phase difference between velocity and stress, resulting in a
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451 clockwise deflection of surface velocity with respect to surface stress in the Northern Hemisphere, roughly comparable to the 20–401 deflection Nansen observed. In his classic 1905 paper, Ekman extended his findings with remarkable insight to predict inertial oscillations, large circular currents superimposed on the mean current, and even derived credible estimates of eddy viscosity in the ocean from surfacedrift-to-wind-speed ratios. Ekman postulated the eddy viscosity should vary as the square of the surface wind speed, with kinematic values of order 0.04 m2 s1 for typical wind speeds of 10 m s1. After nearly a century, it is tempting to dismiss Ekman’s solution as not adequately accounting for vertical variation of eddy viscosity in the boundary layer. Surface (ice) velocity, for example, is strongly influenced by a zone of intense shear near the ice– ocean interface where eddy viscosity varies linearly with distance from the ice. For typical under-ice conditions, this approximately halves the angle between interfacial stress and velocity and significantly increases the ratio of surface speed to surface stress. The Ekman approach also ignores potentially important effects from density gradients in the water column, or from buoyancy flux at the interface. Nevertheless, measurements from the UBL show that with slight modification, Ekman theory does indeed provide a very useful first-order description of turbulent stress in the UBL. Turbulent stress is not much affected by either variation in eddy viscosity in the near surface layer (across which the stress magnitude varies by only about 10%), or by horizontal gradients in density of the boundary layer (‘thermal wind’). Both can have large impact on the mean velocity profile. The Ekman solution for turbulent stress is derived as follows. Using modern notation, the equations of motion in a noninertial reference frame rotating with the earth include an apparent acceleration resulting in the Coriolis force, with horizontal vector component rfk V, where r is density, V is the horizontal velocity vector, k is the vertical unit vector, and f is the Coriolis parameter (positive in the Northern Hemisphere). Ekman postulated that eddy viscosity, K, which behaves similarly to molecular viscosity but is several orders of magnitude larger, relates stress to velocity shear: tˆ ¼ KqV=qz where tˆ is a traction vector combining the horizontal components of stress in the water. Expressing horizontal vectors as complex numbers, e.g., V ¼ u þ iv, the steady-state, horizontally homogeneous equation for horizontal velocity in an otherwise quiescent ocean forced by stress at the surface is then given by: q2 V if V ¼ K 2 qz
½1
Implicit in eqn [1] is that k does not vary with depth, so differentiation of eqn [1] with respect to z and substituting tˆ =K for qV=qz yields a second-order differential equation for tˆ subject to boundary conditions that tˆt vanish at depth and that it match the applied interfacial stress, tˆ 0 at z ¼ 0. The solution is simply: 4
tˆ ðzÞ ¼ tˆ 0 e
dz
½2
where dˆ ¼ ðf=7f7Þðif=KÞ1=2 is a complex extinction coefficient that both attenuates and rotates stress with increasing depth, clockwise in the Northern Hemisphere, counterclockwise in the Southern Hemisphere. The practical differences between Ekman spirals in velocity and stress are illustrated by measurements of mean velocity and Reynolds stress during a period of rapid ice drift at Ice Station Weddell near 651S, 501W (Figure 1). The mean current in a reference frame drifting with the ice velocity (i.e., the negative of the dashed vector labeled ‘Bot’ in Figure 1A) shows the characteristic leftward turning with depth, but 24 20 16 N 8
Bot
4 _1
0.1 m s
(A)
24
16 20
8 4
0 _4
(B)
_2
10 m2 s
Figure 1 (A) Plan view of mean velocity averaged over a period of steady drift at Ice Station Weddell (1992). Numbers indicate meters from the ice–ocean interface. The vector labeled ‘Bot’ is the apparent velocity of the seafloor in the drifting reference frame. (B) Horizontal Reynolds stress. The dotted stress hodograph is from a similarity model, with boundary stress (dashed vector) inferred from the model solution that matches observed stress at 4 m. (Reproduced from McPhee MG and Martinson DG (1994) Science 263: 218–221.)
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UNDER-ICE BOUNDARY LAYER
also includes a region of strong shear between 4 m and the ice–ocean interface, as well as an apparent eastward geostrophic current of several centimeters per second. The last may include its own vertical shear unrelated to UBL dynamics. None of these complicating factors has much impact on the Reynolds stress (Figure 1B), which shows (in a general sense) the depth attenuation and rotation predicted by a simple complex exponential (2) with vertically invariant eddy viscosity. The latter derives from a similarity based value for K, proportional to 7tˆ 0 =f 7, with a magnitude of about 0.02 m2 s1. Since the interfacial stress is approximately proportional to wind speed squared, this is indeed similar to Ekman’s development,1 with the magnitude implied by the observations within a factor of about two of Ekman’s prediction. Although the profile of Figure 1(B) is especially ‘clean,’ numerous other examples of spirals in Reynolds stress profiles exist from under-ice measurements, most consistent with the neutral scaling implied by Kp7tˆ 0 =f 7. Thus despite its simplicity, the Ekman approach provides a remarkably accurate account of momentum flux in the UBL for many commonly encountered situations. It is a relatively minor step to adjust the surface velocity to account for the variable K surface layer. Done properly, this leads to a Rossby similarity drag formulation. Buoyancy Flux and the Seasonal Cycle
The other major factor by which the under-ice boundary layer interacts with the ice cover and atmosphere is the annual cycle of mixed layer temperature, salinity, and depth. During summer, the mixed layer warms, freshens, and shoals, to be followed during and after freezeup, by cooling (to freezing), salination, and deepening. Although this cycle emulates in many ways the annual cycle of temperate mixed layers, a major distinction is that buoyancy is controlled mainly by salinity rather than temperature (the thermal expansion coefficient decreases rapidly as T approaches freezing, whereas the saline contraction coefficient remains relatively constant), thus freezing or melting at the ice–ocean interface is the main source of buoyancy flux for the UBL. In the perennial pack of the Arctic, heat absorbed in the upper ocean through summer leads, melt ponds, and thin ice contributes to bottom melting and is an important part of both the ice mass balance
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and the total summer buoyancy increase for the UBL. Away from the continental shelves and ice margins, heat exchange with the deep ocean tends to be small, limited by the cold halocline that separates water of Atlantic origin from the surface. In the eastern Arctic, the marginal ice zone of Fram Strait, and in the vast seasonal sea ice zone surrounding the Antarctic continent, the UBL interacts directly with warmer deep ocean, and oceanic heat mixed into the boundary layer from below often controls the ice mass balance, and exerts major influence on overall ocean stability. Buoyancy plays a major role in these exchange processes and is not adequately represented by treating eddy viscosity as dependent solely on surface stress. Most of the UBL research in recent years has been devoted to understanding how buoyancy influences turbulent fluxes.
Turbulence in the Under-ice Boundary Layer Reynolds Flux
When ice is in motion relative to the underlying water, there is a net flux of momentum in the underlying boundary layer, most of which is carried by turbulent fluctuations arising from relatively small, chaotic instabilities in the flow, motions which will also induce fluxes of scalar properties (e.g., T, S) if a mean gradient in the property exists. The turbulent transport process is best demonstrated by considering the advective part of the material derivative. Consider, for example, the simplest form of the heat equation: horizontally homogeneous, with no internal sources or sinks of heat. In a Eulerian reference frame, this reduces to a simple balance between the material derivative of temperature and the vertical gradient of the molecular heat diffusion dT qT q qT ¼ þ u rT ¼ vT dt qt qz qz
½3
where vT is the molecular thermal diffusivity. Turbulent flux of temperature variations arises from the advective term, u DT. If velocity and temperature are expressed as the sum of mean and turbulent (fluctuating) parts: u ¼ U¯ þ u0 and T ¼ T¯ þ T 0 , and the flow is incompressible and horizontally homogeneous with no mean vertical velocity,
1 Ekman suggested that the ‘depth of frictional influence’ D ¼ pO(2K/f) varied as wind speed divided by Osin F, where F is latitude. This implies no f dependence for k. At high latitudes, this has minor impact.
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u rT ¼
q /w0 T 0 S qz
½4
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Normally this term completely dominates the molecular flux and eqn [3] is approximated by qT q ¼ /w0 T 0 S qt qz
½5
In a strict sense, the angle brackets represent an ensemble Reynolds average over many independent realizations of the flow, but for practical applications it is assumed that the large-scale, ‘mean’ properties of the flow and its turbulent fluctuations respond in different and separable wavenumber bands (so that the local time derivative in eqn [5] has meaning), and that a suitable average in time is representative of the Reynolds flux. A similar analysis of du/dt leads to the divergence of the Reynolds stress tensor formed from the velocity covariance matrix of the three fluctuating velocity components. Under the same simplifications as above, the advective term in the mean horizontal velocity equation becomes q ð/u0 w0 S þ i/v0 w0 SÞ qz where the horizontal vector quantity t ¼ /u0 w0 S þ i/v0 w0 S is traditionally called Reynolds stress. A second important turbulence property associated with the Reynolds stress tensor is its trace q2 ¼ /u0 u0 S þ /v0 v0 S þ /w0 w0 S
½6
which is twice the turbulent kinetic energy (TKE) per unit mass. The connection between turbulence and eddy viscosity becomes apparent when the horizontal velocity equation is written with the simplifying (but often reasonable) assumptions of horizontal homogeneity, no mean vertical velocity, and negligible impact of molecular viscosity: qV q þ if V ¼ ð/u0 w0 S þ i/v0 w0 SÞ qt qz q qV ¼ ut l qz qz
½7
The last term in eqn [7] represents the mixing-length hypothesis, essentially a scaling argument that Reynolds stress is uniquely related to the mean velocity shear by the product of velocity and length scales characterizing the largest, energy-containing eddies in the flow. Eddy viscosity is K ¼ utl. The steady version of eqn [7] differs from eqn [1] in that K may depend on z and remains within the scope of the outer derivative.
Scales of Turbulence
A reasonable choice for the turbulence velocity scale (ut) is the friction speed u* ¼ O7tˆ 7. In exceptional cases where destabilizing buoyancy flux (/w0 b0 S ¼ (g/r)/r0 w0 S) from rapid freezing is the main source of turbulence, a more appropriate choice is the convective scale velocity w* ¼ ðlj/w0 b0 S0 jÞ1=3 where l is the length scale of the dominant eddies. An alternative scale is q given by eqn [6]; however, observations in the UBL show the ratio q/u * to be relatively constant (B 3) in shear-dominated flows; the distinction may therefore be academic until a clear connection between q and w* is demonstrated. Mixing length is the distance over which the ‘energy-containing’ eddies are effective at diffusing momentum. Several observational studies in the UBL have shown a robust relationship between a length scale lpeak inversely proportional to the wavenumber at the maximum of the weighted spectrum of vertical velocity, and l inferred by other methods. Since the spectrum of vertical velocity is relatively easy to measure, lpeak provides a useful proxy for estimating l simultaneously at several levels in the UBL. A diagram of governing turbulence scales in the UBL is presented in Figure 2, developed by combining simple boundary-layer similarity theory with numerous observations from drifting sea ice ranging from the marginal ice zone of the Greenland Sea, to the central Arctic ocean under thick ice and at the edges of freezing leads, and in the Weddell Sea. Figure 2(A) shows neutral stratification in the bulk of the UBL, when surface buoyancy flux (melt rate) is too small to have appreciable impact on turbulence. This is a common condition for perennial pack ice, which grows or melts slowly most of the year. Working from the interface down, mixing length increases approximately linearly with depth through the surface layer, until it reaches a limiting value proportional to the planetary length scale lmax ¼ L* u*0 =f , where L* B0:03. Usually, the surface layer extends 5 m or less. From there the mixing length holds relatively constant through the extent of the Ekman (or outer) part of the UBL, to the depth of the pycnocline (typically 35–50 m in the western Arctic; 75–150 m in the Weddell Sea). If the neutral layer is very deep, stress decreases more or less exponentially, following approximately the Ekman solution (see the discussion of Figure 3B below); however, if the pycnocline is shallow, a finite stress will exist at zp (indicated in Figure 2 by u*p ) instigating upward mixing of pycnocline water with associated buoyancy flux, /w0 b0 Sp. Mixing length in the highly stratified fluid just below the mixed-layer–pycnocline interface is estimated from the turbulent kinetic
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UNDER-ICE BOUNDARY LAYER Melt season _ stabilizing buoyancy
Neutral stability
159
Freezeup _ destabilizing buoyancy
Ice
Surface layer
s1 = |z|
〈w ′b ′〉0 ≈ 0
〈w ′b ′〉0 > 0
〈w ′b ′〉0 < 0
2
max = ∗ Λ∗u∗0 /|f |
Ekman layer
max → zpyc max =Λ∗u∗0 /|f | → RcLp
u∗p
z = zpyc Pycnocline
→RcLp
〈w ′b ′〉p
ρ
(A)
(B)
(C)
Figure 2 Schematic diagram of mixing length distributions in the UBL under conditions of (A) dynamically negligible surface buoyancy flux (neutral stratification in the well mixed layer), (B) upward buoyancy flux from summer melting, with formation of a seasonal pycnocline and a negative density gradient in the ‘well mixed’ layer, and (C) downward buoyancy flux from rapid freezing, with positive density gradient to the pycnocline. u * , Friction velocity; /w0 b0 S, buoyancy flux; k, Ka´rma´n’s constant, 0.4; L * , similarity constant, 0.028; Rc, critical flux Richardson number, 0.2; f, Coriolis parameter; L ¼ u 3 =ðk/w 0 b 0 SÞ, Obukhov length; Z * ¼ (1 þ L * u * / * kRc|f|L))1/2, stability parameter.
energy equation, which is dominated by three terms: production of TKE by shear ðPS ¼ tˆ qU=qzÞ, production by buoyancy (Pb ¼ /w0 b0 S), and dissipation by molecular forces (e). Relating stress and shear by the mixing-length hypothesis, the balance of TKE production with dissipation is u3 =l /w0 b0 S ¼ e
½8
*
The negative ratio of buoyancy production to shear production is the flux Richardson number: Pb =PS ¼
l/w0 b0 S l ¼ 3 u kL
½9
*
where L ¼ u3 =ðk/w0 b0 SÞ is known as the Obukhov * length. Studies of turbulence in stratified flows have shown that the ratio eqn [9] does not exceed a limiting value (the critical flux Richardson number, Rc) of about 0.2. This establishes a limit for mixing length in stratified flow: lrRckL, and it is assumed that in the pycnocline this limit is approached, where
L is based on pycnocline fluxes of momentum and buoyancy. Estimates of mixing length in a near neutral UBL from the Ice Station Weddell data (Figure 1) are illustrated in Figure 3(A). Points marked lpeak were taken from the inverse of the wavenumber at the peak in the vertical velocity spectra (averaged over all 1-h flow realizations), as described above. Values marked le were obtained using eqn [8] assuming negligible buoyancy flux, with measured values for u * and e (obtained from spectral levels in the inertial subrange). They show clearly that the ‘wall layer’ scaling, l ¼ k|z| does not hold for depths greater than about 4 m. Rapid melting reduces the extent of the surface layer and the maximum mixing length (Figure 2B). The stability factor Z* ¼ ð1 þ L* u* =ðkRc jf jLÞÞ1=2 derives from similarity theory and ensures that the mixing length varies smoothly from the neutral limit ðlmax -L* u*0 =jf jÞ to the stable limit (lmax-kRcL0) for increasing stability. A consequence of reduced scales during melting is formation of a seasonal
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UNDER-ICE BOUNDARY LAYER
0
0
1
2
m
_
3
4
5
4
m2 s 2 (× 10 ) 0.4 0.8 1.2
0
_
1.6
0
m2 s 1 0.02 0.01
Kfit
az
= oe
⎥ z⎥
0.03
_5
Klocal
_ 10
m
peak
_ 15
Ksim
_ 20 _ 25
_ 30 Turbulent length scale (A)
Turbulent stress magnitude (C)
(B)
Eddy viscosity
Figure 3 (A) Mixing length determined from the TKE equation (le) and from the inverse of the wavenumber at the peak in the weighted w spectrum (lpeak). Error bars indicate twice the standard deviation from the spectra calculated from 1-h segments of data. (B) Average Reynolds stress magnitude, with a least-squares fitted exponential decay with depth. Fit coefficients are t0 ¼ 1.44 104 m2 s2 and a ¼ 0.051 m1. (C) Eddy viscosity estimated by three methods as described in the text. (Reproduced from McPhee MG and Martinson DG (1994) Science 263, 218–221.)
pycnocline, above a ‘trapped’ layer with properties indicative of the mixed layer that existed before the freshwater influx. Rapid ice growth produces negative buoyancy via enhanced salinity at the interface, increasing TKE by the buoyancy production term in eqn [8]. The result is that mixing length and eddy viscosity increase in the UBL, sometimes dramatically. During the 1992 Lead Experiment, turbulent flux and dissipation measured from the edge of a freezing lead in a forced convective regime showed that, compared with the neutral UBL, there was a tenfold increase in mixing length (based on w spectral peaks) and in eddy heat and salt diffusivity (based on measured fluxes and gradients). The Obukhov length was 12 m, about 40% of the mixed layer extent, indicating relatively mild convection, yet the turbulence was greatly altered, apparently by the generation of quasi-organized roll structures in the lead, reminiscent of Langmuir circulations (a thin ice cover precluded any surface waves at the time of the measurements). Mixing length inferred from the lead measurements increased away from the surface following Monin– Obukhov similarity (adapted from atmospheric boundary layer studies), reaching a maximum value roughly comparable to the pycnocline depth scaled by von Ka´rma´n’s constant.
The density profiles in Figure 2(B) and (C) are drawn schematically with slight gradients in the socalled mixed layer. This is at odds with conceptual models of the upper ocean which treat the boundary layer as completely mixed, but is consistent with measurements in the UBL. Wherever scalar fluxes of temperature and salinity are measurable, vertical gradients (albeit small) of mean temperature and salinity are found in the fully turbulent UBL, including statically unstable profiles as in Figure 2(C).
Effective Eddy Viscosity and Diffusivity
Figure 3(C) illustrates different methods for estimating bulk eddy viscosity in the UBL. The distribution labeled Ksim is from the similarity model used to construct the stress profile of Figure 1(B) by matching observed stress at 4 m. The vertical distribution labeled Klocal is the product lpeaku * at each level (Figure 3A and B). Its vertical average value is 0.019 m2 s1. Finally, the dashed line labeled Kfit in Figure 3(B) is from the least-squares fitted extinction coefficient ðRefdˆ gÞ for the Ekman stress solution eqn [2]. The last method is sensitive to small stress values at depth: if the bottommost cluster is ignored, Kfit ¼ 0.020 m2 s1.
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UNDER-ICE BOUNDARY LAYER
The mixing length hypothesis holds for scalar properties of the UBL as well as momentum, so that it is reasonable to express, e.g., kinematic heat flux as /w0 T 0 S ¼ u* lT
qT qT ¼ KH qz qz
½10
In flows where turbulence is fully developed with large eddies and a broad inertial subrange, scalar eddy diffusivity and eddy viscosity are comparable (Reynold’s analogy). In stratified flows with internal wave activity and relatively low turbulence levels, momentum may be transferred by pressure forces that have no analog in scalar conservation equations, hence scalar mixing length may be considerably less than l. By measuring turbulent heat flux and the mean thermal gradient, it is possible to derive an independent estimate of eddy diffusivity in the UBL from eqn [10]. An example of this method is shown in Figure 4, where heat flux measurements averaged over five instrument clusters are compared with the negative thermal gradient. The data are from the same Ice Station Weddell storm as the other turbulence measurements of Figures 1 and 3. The mean thermal diffusivity, KH ¼ 0.018 m2 s1, is similar to the eddy viscosity (Figure 3C). Close correspondence between eddy viscosity and heat diffusivity was also found during the 1989 CEAREX drift north of Fram Strait, and during the 1992 LEADEX project. In the forced convective regime of the latter, salinity flux 270
20
135
µK m
_1
10
Wm
_2
15
5 0 _5
0
87.0
87.5
88.0
88.5
89.0
Day of 1992
Figure 4 Time series of turbulent heat flux, rcp /w 0 T 0 S(W m2, circles) and temperature gradient qT=qz(mK m1 curve). The overbar indicates a vertical average over five turbulence clusters from 4 to 24 m. Error bars are twice the sample standard deviation. The temperature gradient was calculated by linear regression, after the calibration of each thermometer was adjusted by a constant amount so that the gradient was zero at time 86.95 when heat flux was zero (heavy arrow). (Reproduced from McPhee MG and Martinson DG (1994) Science 263: 218– 221.)
161
was measured for the first time, with comparably large values for eddy salt diffusivity as for eddy viscosity and heat diffusivity (but with low statistical significance for the regression of /w0 S0 S against qS/ qz).
Outstanding Problems Mixing in the Pycnocline
Understanding of turbulent mixing in highly stratified fluid just below the interface between the wellmixed layer and pycnocline is rudimentary. Many conceptual models assume, for example, that fluid ‘entrained’ at the interface immediately assumes the properties of the well-mixed layer (i.e., is mixed completely), so that the interface sharpens during storms as it deepens following the mean density gradient. Instead, measurements during severe storms in the Weddell Sea show upward turbulent diffusion of the denser fluid with a ‘feathering’ of the interface. Depending on how it is defined, the pycnocline depth may thus decrease significantly during extreme mixing events. Where the bulk stability of the mixed layer is low and there is large horizontal variability in pycnocline depth (as in the Weddell Sea), advection of horizontal density gradients may have large impact on mixing, both by changing turbulence scales and by conditioning the water column for equation-of-state related effects like cabbeling and thermobaric instability. Even with the advantage of the stable ice platform, observations in the upper pycnocline are hampered by the small turbulence scales, by the difficulty of separating turbulence from high frequency internal wave velocities, and by rapid migration of the interface in response to internal waves or horizontal advection. Convection in the Presence of Sea Ice
The cold, saline water that fills most of the abyssal world ocean originates from deep convection at high latitudes. Sea ice formation is a (geophysically) very efficient distillation process and may play a critical role in deep convection in areas like the Greenland, Labrador, and Weddell Seas where the bulk stability of the water column is low. By the same token, melting sea ice is a strong surface stabilizing influence that can rapidly shut down surface driven convection as soon as warm water reaches the well mixed layer from below. Understanding the physics of turbulent transfer in highly convective regimes is a difficult problem both from theoretical and observational standpoints, complicated not only by uncertainty about how
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large-scale eddies interact with the stably stratified pycnocline fluid, but also by the possibility of frazil ice, small crystals that form within the water column. Depending on where it nucleates, frazil can represent a distributed internal source of buoyancy and heat in the UBL. Zones of intense freezing tend to be highly heterogeneous, concentrated in lead systems or near the ice margins, and require specialized equipment for studying horizontal structure. Measuring difficulties increase greatly in the presence of frazil ice or supercooled water, because any intrusive instruments present attractive nucleation sites. In addition to questions of UBL turbulence and surface buoyancy flux, factors related to nonlinearities in the equation of state for sea water may have profound influence on deep convection triggered initially by ice growth and UBL convection. Recent studies have shown, for example, that certain regions of the Weddell Sea are susceptible to thermobaric instability, arising from nonlinearity of the thermal expansion coefficient with increasing pressure. The importance of thermobaric instability for an ice-covered ocean is that once triggered, the potential energy released and converted in to turbulence as the water column overturns thermobarically, may be sufficient to override the surface buoyancy flux that would result from rapid melting as warm water reaches the surface.
PS q Rc S T u u*
Z* k L* l lT v vT t F
turbulence scale velocity horizontal velocity vector convective turbulence scale velocity turbulent buoyancy flux, (g/r)/w0 r0 S kinematic turbulent heat flux turbulent salinity flux complex attenuation coefficient dissipation rate of turbulent kinetic energy stability factor, (1 þ L * u * /(kRc|f|L)) 1/2 von K`rmK`n’s constant (0.4) similarity constant (B 0.03) turbulent mixing length scale turbulent scalar mixing length scale kinematic molecular viscosity, units m2 s1 molecular scalar (thermal) diffusivity, units m2 s 1 Reynolds stress: /u0 w0 S þ i/v0 w0 S latitude
See also Arctic Ocean Circulation. Bottom Water Formation. Deep Convection. Ice–ocean interaction. Internal Tides. Langmuir Circulation and Instability. Windand Buoyancy-Forced Upper Ocean.
Further Reading
Symbols used f g K KH i L Pb
ut V w* /w0 b0 S /w0 T0 S /w0 S0 S dˆ e
Coriolis parameter acceleration of gravity eddy viscosity scalar eddy diffusivity imaginary number Obukhov length, u3 =ðk/w0 b0 SÞ * production rate of turbulent kinetic energy by buoyancy, /w0 b0 S production rate of turbulent kinetic energy by shear, u3* /l turbulent kinetic energy scale velocity critical flux Richardson number (B 0.2) salinity temperature three-dimensional velocity vector (u, v, w components) friction velocity, square root of kinematic stress
Ekman VW (1905) On the influence of the earth’s rotation on ocean currents. Ark. Mat. Astr. Fys 2: 1--52. Gill AE (1982) Atmosphere–Ocean Dynamics. New York: Academic Press. Johannessen OM, Muench RD, and Overland JE (eds.) (1994) The Polar Oceans and Their Role in Shaping the Global Environment: The Nansen Centennial Volume. Washington DC: American Geophysical Society. McPhee MG (1994) On the turbulent mixing length in the oceanic boundary layer. Journal of Physical Oceanography 24: 2014--2031. Pritchard RS (ed.) (1980) Sea Ice Processes and Models. Seattle, WA: University of Washington Press. Smith WO (ed.) (1990) Polar Oceanography. San Diego, CA: Academic Press. Untersteiner N (ed.) (1986) The Geophysics of Sea Ice. New York: Plenum Press.
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UPPER OCEAN HEAT AND FRESHWATER BUDGETS P. J. Minnett, University of Miami, Miami, FL, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction Most of the solar energy reaching the surface of the Earth is absorbed by the upper ocean. Some of this is released locally, often within the course of the following night, but some heat is retained for longer periods and is moved around the planet by the oceanic surface currents. Subsequent heat release to the atmosphere helps determine the patterns of weather and climate around the globe. While maps of sea surface temperature measured from satellites are now commonplace, it is the underlying reservoir of heat stored in the upper ocean that has the impact on the atmospheric circulation and weather, not only over the oceans but also over the continents downstream. Because the specific heat of water is much greater than that for air, the thermal capacity of a layer of the ocean about 3-m thick is the same as that of the entire atmosphere above. The upper ocean heat content, however, is not so accessible to measurements by satellite-borne instruments and is therefore less well described, and its properties less well understood. The density of seawater is determined in a nonlinear fashion by temperature and salinity and, to a much lesser degree, by pressure. Warmer, fresher seawater is less dense than cooler, saltier water. The viscosity of seawater is very low and so the fluid is very sensitive to flow generation by density differences. However, as a result of the rotation of the Earth, oceanic flow is not simply a redistribution of mass so that the surfaces of constant density coincide with surfaces of constant gravitational force; deviations are supported by balancing the horizontal pressure forces, caused by the variable distribution of density, with the Coriolis force (geostrophy). Vertical exchanges between the upper ocean and the deeper layers are inhibited by layers of density gradients, called pycnoclines, some of which are permanent features of the ocean, and others, generally close to the surface, are transient, existing for a day or less. Upper ocean salinity, through its contribution to controlling the ocean density, is therefore an important variable in determining the density distribution of
the upper ocean and the availability of oceanic heat to drive atmospheric processes. The range of sea surface temperatures, and, by extension, the mixed layer temperature, extends from 1.8 1C, the freezing point of seawater, to above 30 1C in the equatorial regions, especially in the western Pacific Ocean and eastern Indian Ocean. In particularly favorable situations, surface temperatures in excess of 35 1C may be found, such as in the southern Red Sea. The lowest upper ocean salinities are found in the vicinity of large river outflows and are close to zero. For most of the open ocean, upper ocean salinities lie in the range of 34–37. (Ocean salinity is measured as a dimensionless ratio with a multiplier of 10 3. A salinity of 35 means that 1 kg of seawater contains 35 g of dissolved salts.) Unlike elevated surface temperatures that result in a lowering of the surface density and a stable near-surface water column, increasing surface salinities by evaporation lead to increasing density and an unstable situation where the denser surface waters sink.
Governing Processes The upper ocean heat and salt (or freshwater) distributions are determined by the fluxes of heat and moisture through the ocean surface, the horizontal divergence of heat and salinity by advection, and by fluxes through the pycnocline at the base of the upper ocean ‘mixed layer’. This can be expressed for heat content per unit area, H, by DH ¼ Qsurf þ Qhoriz þ Qbase Dt where Qsurf represents the heat fluxes through the ocean surface, Qhoriz the divergence of advective heat flux in the column extending from the surface to the depth of the mixed layer, and Qbase is the vertical heat flux through the pycnocline at the base of the mixed layer, often presumed to be small in comparison with the surface exchanges. The surface heat flux has three components: the radiative fluxes, the turbulent fluxes, and the heat transport by precipitation. The radiative fluxes are the sum of the shortwave contribution from the sun, and the net infrared flux, which is in turn the difference between the incident atmospheric emission and the emission from
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UPPER OCEAN HEAT AND FRESHWATER BUDGETS
the sea surface. The turbulent fluxes comprise those of sensible and latent heat. A similar expression can be used for the upper ocean freshwater budget, where the fluxes are simply those of water. The surface exchanges are the difference between the mass fluxes due to precipitation and evaporation, and the horizontal advective fluxes can be best framed in terms of the divergence of salinity. The depth of the mixed layer is often not easy to determine and there are several approaches used in the literature, including the depth at which the temperature is cooler than the surface temperature, and values of 0.1, 0.2, or 0.5 K are commonly used. Another is based on an increase in density, and a value of 0.125 kg m 3 is often used. These are both proxies for the parameter that is really desired, which is the depth to which turbulent mixing occurs, thereby connecting the atmosphere to the heat stored in the upper ocean. In situations of low wind speed and high insolation, a significant shallow pycnocline can develop through temperature stratification, and this decouples the ‘mixed’ layer beneath from the atmosphere above. Nevertheless, in most discussions of the surface heat and salt budget, these diurnal effects are discounted and the depth of integration is to the top of the seasonal pycnocline, or in the absence of the seasonal pycnocline, to the depth of the top of the permanent pycnocline. Surface Heat Exchanges
The heat input at the surface is primarily through the absorption of insolation. Of course this heating occurs only during daytime and is very variable in the course of a day because of the changing solar zenith angle, and by modulation of the atmospheric transparency by clouds, aerosols, and variations in water vapor. At a given location, there is also a seasonal modulation. In the Tropics, with the sun overhead on a very clear day, the instantaneous insolation can exceed 1000 W m 2. The global average of insolation is about 170 W m 2. The reflectivity of the sea surface in the visible part of the spectrum is low and depends on the solar zenith angle and the surface roughness, and thereby on surface wind speed. For a calm surface with the sun high in the sky, the integrated reflectance, the surface albedo, is about 0.02, with an increase to B0.06 for a solar zenith angle of 601. Having passed through the sea surface the solar irradiance, Ll, is absorbed along the propagation path, z, according to Beer’s law: dLl =dz ¼ kl Ll where the absorption coefficient, kl, is dependent on the wavelength of the light (red being absorbed more
quickly than blue) and on the concentration of suspended and dissolved material in the surface layer, such as phytoplankton. When the wind is low, the nearsurface density stratification that results from the absorption of heat causes the temperature increase to be confined to the near-surface layers, causing the growth of a diurnal thermocline. This is usually eroded by heat loss back to the atmosphere during the following night. If the wind speed during the day is sufficiently high, greater than a few meters per second, the subsurface turbulence spreads the heat throughout the mixed layer. There are a few locations where the insolation is high, the water is very clear, and the mixed layer depth sufficiently shallow that a small fraction of the solar radiation penetrates the entire mixed layer and is absorbed in the underlying pycnocline. Although the absorption and emission of thermal infrared radiation are confined to the ocean surface skin layer of a millimeter or less, the net infrared budget is a component of the surface heat flux that indirectly contributes to the upper ocean heat budget. The infrared budget is the difference between the emission, given by esT4, where e is the broadband infrared surface emissivity, s is Stefan–Boltzmann constant, and T is the absolute temperature of the sea surface. For T ¼ 20 1C, the surface emission is B410 W m 2. The incident infrared radiation is the emission from greenhouse gases (such as CO2 and H2O), aerosols, and clouds, and as such is very variable. For a dry, cloud-free polar atmosphere, the incident atmospheric radiation can be o200 W m 2, whereas for a cloudy tropical atmosphere, 400 W m 2 can be exceeded. The net infrared flux at the surface is generally in the range of 0–100 W m 2, with an average of about 50 W m 2. The turbulent heat fluxes at the ocean surface are so called because the vertical transport is accomplished by turbulence in the lower atmosphere. They can be considered as having two components: the sensible heat flux that results from a temperature difference between the sea surface and the overlying atmospheric boundary layer, and the latent heat flux that results from evaporation at the sea surface. The sensible heat flux depends on the air–sea temperature difference and the latent heat flux on the atmospheric humidity near the sea surface. Both have a strong wind speed dependence. Since the ocean is usually warmer than the atmosphere in contact with the sea surface, and since the atmosphere is rarely saturated at the surface, both components usually lead to heat being lost by the ocean. The global average of latent heat loss is about 90 W m 2 but sensible heat loss is only about 10 W m 2. Extreme events, such as cold air outbreaks from the eastern coasts of continents
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UPPER OCEAN HEAT AND FRESHWATER BUDGETS
over warm western boundary currents, can lead to much higher turbulent heat fluxes, even exceeding 1 kW m 2. The final component of the surface heat budget is the sensible heat flux associated with precipitation. Rain is nearly always cooler than the sea surface and so precipitation causes a reduction of heat content in the upper ocean. Typical values of this heat loss are about 2–3 W m 2 in the Tropics, but in cases of intense rainfall values of up to 200 W m 2 can be attained. Surface Freshwater Exchanges
Over most of the world’s ocean, the flux of fresh water through the ocean surface is the difference between evaporation and precipitation. The loss of fresh water at the sea surface through evaporation is linked to the latent heat flux through the latent heat of evaporation. Clearly, precipitation exhibits very large spatial and temporal variability, especially in the Tropics where torrential downpours associated with individual cumulonimbus clouds can be very localized and short-lived. Estimates of annual, globally averaged rainfall over the oceans is about 1 m of fresh water per year, but there are very large regional variations with higher values in areas of heavy persistent rain, such as the Intertropical Convergence Zone (ITCZ) which migrates latitudinally with the seasons. Over much of the mid-latitude oceans, drizzle is the most frequent type of precipitation according to ship weather reports. The global distribution of evaporation exceeds that of oceanic precipitation, with the difference being made up by the freshwater influx from rivers and melting glaciers. Advective Fluxes
The determination of the amount of heat and fresh water moved around the upper oceans is not straightforward as the currents are not steady, exhibiting much temporal and spatial variation. The upper ocean currents are driven both by the surface wind stress, including the large-scale wind patterns such as the trade winds and westerlies, and by the large-scale density differences that give rise to the thermohaline circulation that links all oceans at all depths. The strong western boundary surface currents, such as the Gulf Stream, carry much heat poleward, but have large meanders and shed eddies into the center of the ocean basins. Indeed, the ocean appears to be filled with eddies. Thus the measurements of current speed and direction, and temperature and salinity taken at one place at one time could be quite different when repeated at a later date.
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Measurements Much of what we know about the upper ocean heat and salt distribution has been gained from analysis of measurements from ships. Large databases of shipboard measurements have been compiled to produce a ‘climatological’ description of upper ocean heat and salt content. In some ocean areas, such as along major shipping lanes, the sampling density of the temperature measurements is sufficient to provide descriptions of seasonal signals, and the length of measurements sufficiently long to indicate long-term climate fluctuations and trends, but these interpretations are somewhat contentious. In other ocean areas, the data are barely adequate to confidently provide an estimate of the mean state of the upper ocean. Temperature is a much simpler measurement than salinity and so there is far more information on the distribution of upper ocean heat than of salt. Historically temperatures were measured by mercury-in-glass thermometers which recorded temperatures at individual depths. Water samples could also be taken for subsequent chemical analysis for salinity. The introduction of continuously recording thermometers, such as platinum resistance thermometers and later thermistors, resulted in measurements of temperature profiles, and the use of expendable bathythermographs (XBTs) meant that temperature profiles could be taken from moving ships or aircraft. The continuous measurement of salinity was a harder problem to solve and is now accomplished by calculating salinity from measurements of the ocean electrical conductivity. The standard instruments for the combined measurements of temperature and conductivity are referred to as CTDs (conductivity–temperature–depth) and are usually deployed on a cable from a stationary research ship, although some have been installed in towed vehicles for measurements behind a moving ship in the fashion of a yo-yo. In recent years, CTDs have been mounted in autonomous underwater vehicles (AUVs) that record profiles along inclined saw-tooth paths through the upper ocean (say to 600 m) and which periodically break surface to transmit data by satellite telemetry. Similarly, autonomous measurements from deep-water (to 2000 m) floats are transmitted via satellite when they surface. In the ARGO project, begun in 2000, over 3000 floats have been deployed throughout the global ocean. The floats remain at depth for about 10 days, drifting with the currents, and then make CTD measurements as they come to surface where their positions are fixed by the Global Positioning System (GPS), and the profile data transmitted to shore. Where time series of profiles are required at a particular location, internally recording
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CTDs can be programmed to run up and down wires moored to the seafloor. These have been used effectively in the Arctic Ocean, but the instruments have to be recovered to retrieve the data as the presence of ice prevents the use of a surface float for data telemetry. Additional sensors, such as transmissometers to measure turbidity, often augment the CTD measurements. Further information is supplied by a network of moored buoys that now span the tropical Pacific and Atlantic Oceans and which support sensors at fixed depths. The spatial distribution of upper ocean temperatures can be derived from satellite measurements of the sea surface temperatures which can now be made with global accuracies of 0.4 K or better using infrared and microwave radiometers. Such data sets now extend back a couple of decades. In 2009 and 2010, two new low-frequency microwave radiometers capable of measuring open ocean salinity are planned for launch (Aquarius is a NASA instrument, and SMOS – Soil Moisture, Ocean Salinity – is an ESA mission). To convert these satellite measurements of surface temperature and surface salinity into upper ocean heat and salt contents requires knowledge of the mixed layer depth, and while this is not directly accessible from satellite measurements, it can be inferred from measurements of ocean surface topography, derived from satellite altimetry, through the use of a simple upper ocean model. Such upper ocean heat content estimates are now being routinely derived and used in an experimental mode to assist in hurricane forecasting and research. Several lines across ocean basins have been sampled from a fleet of research ships in the framework of the World Ocean Circulation Experiment (WOCE) which took place between 1990 and 2002. Many of these sections are currently being reoccupied in the Repeat Hydrography Program to determine changes on decadal scales.
Distributions Heat
The quantitative specification of the upper ocean heat content remains rather uncertain, not so much because of our ability to measure the sea surface temperature (Figure 1), which is generally a good estimate of the mixed layer temperature, especially at night, but in determining the depth of the mixed layer. If the objective is to estimate the heat potentially available to the atmosphere, then the depth of the mixed layer based on density stratification in the pycnocline is more appropriate than the depth based on a temperature gradient in the thermocline,
although this is often used because of the availability of more data. On an annual basis, this can lead to significant differences in the estimates of the depth of the oceanic layer that can supply heat to the atmosphere (Figure 2). The difference between the tops of the thermocline and pycnocline results from density stratification caused by vertical salinity gradients (a halocline). In the low-latitude oceans, this is sometimes called a ‘barrier layer’ and can be as thick as the overlying isothermal layer, that is, halving the thickness of the upper ocean layer in contact with the atmosphere compared to that which would be estimated using temperature profiles alone. The barrier layers are probably caused by the subduction of more saline waters underneath water freshened by rainfall or river runoff. At high latitudes, the nonlinear relationship between seawater density and temperature and salinity means that density is nearly independent of temperature. The depth of the surface layer is therefore determined by the vertical salinity profile. During ice formation, brine is released from the freezing water and this destabilizes the surface layer, causing convective mixing. During ice melt, the release of fresh water stabilizes the upper ocean. In the Arctic Ocean, the depth of the mixed layer is determined by the depth of the halocline. The annual means of course do not reveal the details of the seasonal cycle in heat content, which in turn reflect the seasonal patterns of the surface fluxes and advective transports. Figure 3 shows the global distributions of the surface fluxes for January and July. The patterns in the insolation (short-wave heat flux) reflect the changes in the solar zenith angle, and the seasonal changes in cloud cover and properties. The seasonal patterns of the surface winds are apparent in the turbulent fluxes. The seasonal changes in the sea surface temperatures and upper ocean heat content are the summations of small daily residuals of local heating and cooling. Under clear skies and low winds, the absorption of insolation in the upper ocean leads to a stabilization of the surface layer through the formation of a near-surface thermocline. While the surface heat budget remains positive (i.e., the insolation exceeds heat loss through turbulent heat loss and the net infrared radiation), the diurnal thermocline grows with an attendant increase in the sea surface temperature. As the insolation decreases and the surface heat budget changes sign, the surface heat loss results in a fall in surface temperature and the destabilization of the near-surface layer. The resultant convective instability erodes the thermal stratification, returning the upper layer to a state close to
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that before diurnal heating began. In the heating season, on average, there will be more heat in the upper ocean at the end of the diurnal cycle, and in the cooling season there will be less. On days when the wind speed is greater than a few meters per second, the wind-induced turbulent mixing prevents the growth of the diurnal thermocline and the heat input during the day, and removed at night, is distributed throughout the mixed layer. Figure 4 shows measurements of the diurnal heating, expressed as a difference between the ‘skin’ temperature and a bulk temperature at the depth of a few meters, as a function of wind speed and time of day.
The magnitude of the surface temperature signal of diurnal warming is very strongly dependent on wind speed, and can be eroded very quickly if winds increase in the course of a day. The upper ocean of course exhibits variability on timescales longer than a year, often with profound consequences around the globe. The best known is the El Nin˜o–Southern Oscillation that results in a marked change in sea surface temperature, depth of the mixed layer, and consequently upper ocean heat content in the equatorial Pacific Ocean. The perturbations to the atmospheric circulation have effects on weather patterns, including rainfall, around the
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Figure 2 Maps of the mixed layer depth. Annual averages are shown along with monthly means for January and July. The left column shows mixed layer depths based on a potential density difference criterion, and the right column on a potential temperature difference. The deepest values are found at high latitudes in the winter hemisphere. A discrepancy in the estimates by a factor of 2 is seen in some regions. This translates into an equivalent uncertainty in the estimate of the heat content of the upper ocean. The figure is based on images produced at the NOAA-CIRES Climate Diagnostics Center, Boulder, Colorado, from their website at http:// www.cdc.noaa.gov.
globe. Other multiyear features include the North Atlantic Oscillation, Arctic Oscillation, and Pacific Decadal Oscillation, in all of which there is a shift in both atmospheric circulation and oceanic response. In the case of the Arctic Oscillation, determined from the strength of the polar vortex relative to midlatitude surface pressure, a negative phase results in high surface pressures in the Arctic, and a more uniform distribution of sea ice. This is considered the normal situation. The positive phase results in lower surface pressure fields over the Arctic Ocean, a
thinning of the ice cover, and intrusion of relatively warm Atlantic water into the Arctic Basin. These have consequences on the upper ocean salinity and density stratification, and on interactions with the atmosphere, although the complexities of these feedbacks are poorly understood. The heat and salinity content advected through imaginary boundaries extending across oceans from coast to coast and from the surface to depth are a measure of the transport of heat and salt. For example, to maintain the Earth’s radiative equilibrium
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UPPER OCEAN HEAT AND FRESHWATER BUDGETS
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−100 −10 −30 −50 −70 −90 400 300 200 100 0 250 125 0 −125 −250 Figure 3 Distributions of the components of the surface heat fluxes for Jan. and Jul. The warm colors indicate warming or less cooling of the ocean, and the cool colors indicate cooling or less warming of the ocean. The data are from the UK National Oceanography Center surface flux climatology (v1.1) and were obtained from http://www.noc.soton.ac.uk.
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with the sun and space the combined heat transport of the atmosphere and ocean from the Tropics toward the Poles is about 5.5 1015 W. How this is partitioned between the atmosphere and ocean is the subject of much research. Within the Atlantic Ocean, the northward transport of heat across 241 N is about 1.3 1015 W. Interestingly the average heat transport in the Atlantic is northward, even south of the Equator: 0.3 1015 W northward at 301 S and 0.6 1015 W at 111 S, although these estimates include transport at depth. The differences in heat transport between such lines at different latitudes provide estimates of the net heat absorbed by the upper ocean or given up to the atmosphere within the surface area of the oceans enclosed by the sections. Thus 77757 W m 2 are estimated to be released by the Atlantic Ocean to the atmosphere between 361 and 481 N, but only 8733 W m 2 between 221 and 361 N. In the North Pacific, 39719 W m 2 flow to the atmosphere between 241 and 481 N. Similarly the differences in the salt (or freshwater) content advected across these imaginary
boundaries indicate the imbalance between precipitation plus continental runoff and evaporation. Fresh Water
The large-scale patterns of upper ocean salinity (Figure 5) mirror the distribution of the annual freshwater flux at the sea surface (Figure 6), which is determined by the difference between rainfall and evaporation. The patterns of the components of the freshwater flux are quite zonal in character, with a band of heavy rainfall in the ITCZ and the maxima in evaporation occurring in the regions of the trade winds. There is very little known variability in the seasonal distribution of surface salinity, with the exceptions being in coastal regions where river run off often has a seasonal modulation, especially in the Bay of Bengal where the rainfall influencing the river discharge is dominated by the monsoons. The precipitation over the Bay of Bengal also shows a strong monsoonal influence, but over much of the oceans the seasonal variability is relatively
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UPPER OCEAN HEAT AND FRESHWATER BUDGETS Precipitation
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Figure 6 Global distributions of precipitation, evaporation, and freshwater flux at the ocean surface. Annual means are shown in the top row besides monthly averages for Jan. (middle row) and Jul. (bottom row). The color scale is at left for precipitation (positive mass flux into the ocean) and evaporation (positive mass flux into the atmosphere). The color scale for the freshwater flux is at right (positive mass flux into the atmosphere). The figures were generated from the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data Set (HOAPS) (http://www.hoaps.zmaw.de).
muted. Similarly for evaporation, although variations in the Northern Hemisphere signal are greater than those in the Southern Hemisphere. Pronounced maxima in the wintertime evaporation occur over the Gulf Stream and Kuroshio, and represent enhanced moisture fluxes from the sea surface driven by cold, dry air flowing off the continents over the warm surface waters of the north-flowing currents (Figure 6). On shorter timescales, there is pronounced variability in rainfall associated with the passage of weather fronts at mid-latitudes and with individual clouds in the Tropics. These small-scale, shortduration rainfall events hinder the accurate determination of the freshwater flux into the sea surface. In the Tropics, the rainfall associated with individual cumulonimbus clouds has a diurnal signature, especially in the vicinity of islands, even small atolls, where the diurnal sea breeze can trigger convection that results in rainfall, either directly into the ocean, or as runoff from land. The Arctic Ocean is a particularly interesting area regarding the local freshwater budget as the vertical stability is constrained by the salinity gradients in the halocline. Freshwater volumes in the Arctic Ocean are often calculated relative to a seawater salinity of 34.8. The fresher surface waters are sustained by riverine inflow, primarily from the great Siberian rivers and the Mackenzie River in Canada, that between them annually contribute about 3200 km3.
The inflow from the Pacific Ocean through the Bering Strait is about 2500 km3. The freshwater outflow is mainly through the Canadian Archipelago as liquid (B3200 km3) and through Fram Strait (B2400 km3 as liquid and B2300 km3 as ice). The contribution of precipitation minus evaporation is c. 2000 km3. The fresh water generated by brine rejection during ice formation would be B10 000 km3, which is a relatively small proportion of the riverine and Bering Strait input. The residence time of fresh water in the Arctic Ocean is about 10 years.
Severe Storms An important consequence of variations in the upper ocean heat content is severe storm generation and intensification. The prediction of the strength and trajectory of land-falling hurricanes and cyclones benefits from knowledge of the upper ocean heat content in the path of the storm. A surface temperature of 26 1C is generally accepted as being necessary for hurricane development, but the rate of development depends on the heat in the upper ocean available to drive the storm’s intensification. The passage of a severe storm leaves a wake that is identifiable as a depression of the surface temperature of several degrees and a deficit in the upper ocean heat content. These may survive for several days and can influence the development of subsequent
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storms should they pass over the wake. There are several well-documented cases in the Atlantic where hurricanes approaching land have suddenly lost intensity as they follow, or cross, the path of a prior storm. The converse is also true and hurricanes can undergo sudden intensification when they pass over regions of high upper ocean heat content, as can result from the meandering of the Loop Current in the Gulf of Mexico, for example. Monitoring the upper ocean heat content has become important for severe storm forecasting in the Tropics, especially in terms of sudden intensification. Using a combination of satellite measurements of sea surface temperature, sea surface topography, and a simple ocean model, the spatial distribution of the heat content between the surface and the estimated depth of the 26 1C isotherm is calculated on a daily basis. This is referred to as the ‘tropical cyclone heat
potential’ (Figure 7) and indicates regions where intensification of severe storms is likely. The rate of heat transfer from ocean to atmosphere in a hurricane is very difficult to measure, and varies greatly with the size, intensity, and stage of development of the storm. Estimates range in the order of 1013–1014 W. We have already seen that the northward heat flux in the Atlantic Ocean at 241 N is B1.3 1015 W. Thus, even though severe storms grow and are sustained by large heat fluxes, the magnitudes of the associated flow are relatively small in comparison to the poleward oceanic heat transport which is ultimately released to the atmosphere.
Reactions to Climate Change Away from polar regions, the density of seawater is a strong function of its temperature, and a consequence 1 Jan. 2006
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Figure 7 Examples of daily maps of ‘tropical cyclone heat potential’ for 1 Jan., 15 Mar., 1 Jul., and 15 Sep. 2006. The March and September dates correspond roughly to the peak of cyclone activity in each hemisphere. The maps were derived from satellite measurements of sea surface temperature, sea surface topography, and a simple ocean model. The figure was derived from images generated by the NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Miami, Florida (http://www.aoml.noaa.gov).
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UPPER OCEAN HEAT AND FRESHWATER BUDGETS
of increasing temperatures as a result of global change is the expansion of the upper ocean, which will contribute to sea level rise. In fact, about half of the observed rise in global sea level during the twentieth century of 1–2 mm yr 1 can be attributable to expansion of the warming upper ocean. In addition to thermal expansion, another major impact of climate change is the increase in the upper ocean freshwater budget (reduction in salinity) as the land ice (glaciers and ice caps of Greenland and Antarctica) melt and the runoff enter the high-latitude oceans. This will result in an increase in the stability of the upper ocean and a consequent likely reduction in the mixed layer depths, especially in winter (Figure 2). Here the atmosphere is coupled to the heat available in a very deep ocean layer. Mixing heat and fresh water from the upper ocean to depth is also a driver of the global thermohaline circulation and disruption to this will also have significant consequences on the nearsurface components of the circulation and on the details of the poleward transfer of heat. This will impact global weather patterns, including rainfall over the ocean and land, in ways that are difficult to predict.
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Salinity Measurements. Upper Ocean Mean Horizontal Structure. Upper Ocean Mixing Processes. Upper Ocean Time and Space Variability. Upper Ocean Vertical Structure. Windand Buoyancy-Forced Upper Ocean. Wind Driven Circulation.
Further Reading
Improvements in our ability to determine the upper ocean heat and freshwater budgets, and monitor their changes with time, will occur in the near future with new satellite missions that will both continue the existing time series of sea surface temperature, topography and rainfall, and also introduce new variables: notably sea surface salinity. Additional information on the subsurface distributions of heat and fresh water will be provided by the autonomous profiling floats of the ARGO project that measure temperature and salinity from about 2000-m depth to a few meters below the surface. These will be augmented by AUVs, or ‘gliders’, roaming the oceans taking measurements along undulating paths, transmitting the data via satellite communications when they break the surface. The interpretation of the measurements, from both in situ and space-borne sensors, will be aided by increasingly complex, high-resolution models of the ocean state and the coupled ocean–atmosphere system.
Chen SS and Houze RA (1997) Diurnal variation and lifecycle of deep convective systems over the tropical Pacific warm pool. Quarterly Journal of the Royal Meteorological Society 123: 357--388. Foltz GR, Grodsky SA, Carton JA, and McPhaden MJ (2003) Seasonal mixed layer heat budget of the tropical Atlantic Ocean. Journal of Geophysical Research 108: 3146 (doi:10.1029/2002JC001584). Gill AE (1982) Atmosphere–Ocean Dynamics. San Diego, CA: Academic Press. Hasegawa T and Hanawa K (2003) Decadal-scale variability of upper ocean heat content in the tropical Pacific. Geophysical Research Letters 30: 1272 (doi:10.1029/2002GL016843). Josey SA, Kent EC, and Taylor PK (1999) New insights into the ocean heat budget closure problem from analysis of the SOC air–sea flux climatology. Journal of Climate 12: 2856--2880. Levitus S, Antonov J, and Boyer T (2005) Warming of the world ocean, 1955–2003. Geophysical Research Letters 32: L02604 (doi:10.1029/2004GL021592). Macdonald AM (1998) The global ocean circulation: A hydrographic estimate and regional analysis. Progress in Oceanography 41: 281--382. Peixoto JO and Oort AH (1992) Physics of Climate. New York: American Institute of Physics. Serreze MC, Barrett AP, Slater AG, et al. (2006) The largescale freshwater cycle of the Arctic. Journal of Geophysical Research 111: C11010 (doi:10.1029/2005JC003424). Shay LK, Goni GJ, and Black PG (2000) Effects of a warm oceanic feature on hurricane Opal. Monthly Weather Review 128: 1366--1383. Siedler G, Church J, and Gould J (eds.) (2001) Ocean Circulation and Climate: Observing and Modelling the Global Ocean. San Diego, CA: Academic Press. Willis JK, Roemmich D, and Cornuelle B (2004) Interannual variability in upper ocean heat content, temperature, and thermosteric expansion on global scales. Journal of Geophysical Research 109: C12036 (doi:10.1029/2003JC002260).
See also
Relevant Websites
Evaporation and Humidity. Heat and Momentum Fluxes at the Sea Surface. Heat Transport and Climate. Ocean Circulation. Ocean Circulation: Meridional Overturning Circulation. Open Ocean Convection. Satellite Remote Sensing of Sea Surface Temperatures. Satellite Remote Sensing:
http://www.remss.com – AMSR Data, Remote Sensing Systems. http://aquarius.gsfc.nasa.gov – Aquarius Mission Website, NASA. http://www.esr.org – Aquarius/SAC-D Satellite Mission, ESR.
Future Developments
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http://www.hoaps.zmaw.de – Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data. http://www.ghrsst-pp.org – High-Resolution SSTs from Satellites, GHRSST-PP. http://www.noc.soton.ac.uk – NOC Flux Climatology, at Ocean Observing and Climate pages of the National Oceanography Centre (NOC), and The World Ocean Circulation Experiment (WOCE) 1990–2002, NOC, Southhampton.
http://ushydro.ucsd.edu – Repeat Hydrography Project. http://www.cdc.noaa.gov – Search for Gridded Climate Data at PSD, ESRL Physical Sciences Division, NOAA. http://www.esa.int – SMOS, The Living Planet Programme, ESA. http://www.aoml.noaa.gov – Tropical Cyclone Heat Potential, Atlantic Oceanographic and Meteorological Laboratory (AOML).
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE M. Tomczak, Flinders University of South Australia, Adelaide, SA, Australia
following an introductory overview of some elementary property fields.
Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3083–3093, & 2001, Elsevier Ltd.
Introduction The upper ocean is the most variable, most accessible, and dynamically most active part of the marine environment. Its structure is of interest to many science disciplines. Historically, most studies of the upper ocean focused on its impact on shipping, fisheries, and recreation, involving physical and biological oceanographers and marine chemists. Increased recognition of the ocean’s role in climate variability and climate change has led to a growing interest in the upper ocean from meteorologists and climatologists. In the context of this article the upper ocean is defined as the ocean region from the surface to a depth of 1 km and excludes the shelf regions. Although the upper ocean is small in volume whencompared to the world ocean as a whole, it is of fundamental importance for life processes in the sea. It determines the framework for marine life through processes that operate on space scales from millimeters to hundreds of kilometers and on timescales from seconds to seasons. On larger space and timescales, its circulation and water mass renewal processes span typically a few thousand kilometers and several decades, which means that the upper ocean plays an important role in decadal variability of the climate system. (In comparison, circulation and water mass renewal timescales in the deeper ocean are of the order of centuries, and the water masses below the upper ocean are elements of climate change rather than climate variability.) The upper ocean can be subdivided into two regions. The upper region is controlled by air–sea interaction processes on timescales of less than a few months. It contains the oceanic mixed layer, the seasonal thermocline and, where it exists, the barrier layer. The lower region, known as the permanent thermocline, represents the transition from the upper ocean to the deeper oceanic layers. It extends to about 1 km depth in the subtropics, is some what shallower near the equator and absent poleward of the Subtropical Front. These elements of the upper ocean will be defined and described in more detail,
Horizontal Property Fields The annual mean sea surface temperature(SST) is determined by the heat exchange between ocean and atmosphere. If local solar heat input would be the only determinant, contours of constant SST would extend zonally around the globe, with highest values at the equator and lowest values at the poles. The actual SST field (Figure 1) comes close to thissimple distribution. Notable departures occur for two reasons. 1. Strong meridional currents transport warm water poleward in the western boundary currents along the east coasts of continents. Examples are theGulf Stream in the North Atlantic Ocean and the Kuroshio in the North Pacific Ocean. In contrast, cold water is transported equatorward along the west coast of continents. 2. In coastal upwelling regions, for example off the coasts of Peru and Chile or Namibia, SST is lowered as cold water is brought to the surface from several hundreds of meters depth. The annual mean sea surface salinity(SSS) is controlled by the exchange of fresh water between ocean and atmosphere and reflects it closely (Figure 2), the only departures being observed as a result of seasonal ice melting in the polar regions. As a result, the subtropics with their high evaporation and low rainfall are characterized by high salinities, while the regions of the westerly wind systems with their frequent rain-bearing storms are associated with low salinities(Figure 3). Persistent rainfall in the intertropical convergence zone produces a regional minimum in the SSS distribution near the equator. Departures from a strict zonal distribution are again observed, for the same reasons listed for the SST distribution. In addition, extreme evaporation rates in the vicinity of large deserts are reflected in high SSS, and large river run-off produced by monsoonal rainfall over south east Asia results in low SSS in the Gulf of Bengal. As a result, the SSS distribution of the north-west Indian Ocean shows a distinct departure from the normal zonal distribution. Seasonal variations of SST and SSS are mainly due to three factors.
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Figure 1 Annual mean sea surface temperature (1C) (the contour interval is 21C). (Reproduced from World Ocean Atlas 1994.)
1. Variations in heat and freshwater exchange between ocean and atmosphere are significant for the SST distribution, which shows a drop of SST in winter and a rise in summer, but much less important for the SSS distribution, since rainfall and evaporation do not vary much over the year inmost ocean regions. 2. Changes in the ocean current system, particularly in monsoonal regions where currents reverse twice a year, cause the water of some regions to be replaced by water of different SST and SSS. 3. Monsoonal variations of freshwater input from major rivers influences SSS regionally. The temperature distribution at 500 m depth (Figure 4) reflects the circulation of the upper ocean. At this depth the temperature shows little horizontal variation around a mean of 8–101C. Departures from this mean temperature are, however, observed. (1) The western basins of the subtropics have the highest temperatures in all oceans. They indicate the centres of the subtropical gyres (see below). (2) Polewardof 351 latitude temperatures fall rapidly as the polar regions are reached, an indication of the absence of the permanent thermocline (see below). The salinity distribution at 500 m depth (Figure 5) shows clear similarities to the temperature distribution
Figure 2 Mean meridional distribution of sea surface salinity and mean meridional freshwater balance (evaporation precipitation).
and a strong correlation between high temperatures and high salinities. The salinity field displays a totalrange nearly as large as the range seen at the surface (Figure 3). The mean salinity varies strongly between ocean basins, with the North Atlantic Ocean having
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE
Figure 3 Annual mean sea surface salinity. (Reproduced from World Ocean Atlas 1994.)
Figure 4 Annual mean potential temperature (1C) at 500 m depth. (Reproduced from World Ocean Atlas 1994.)
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Figure 5 Annual mean salinity (PSU) at 500 m depth.(Reproduced from World Ocean Atlas 1994.)
the highest salinity at this depth and the North Pacific Ocean the lowest. The horizontal oxygen distribution is chosen to represent conditions for marine life. Nutrient levels are inversely related to oxygen, and although the relationship varies between ocean basins, an oxygen maximum can always be interpreted as a nutrient minimum and an oxygen minimum as a nutrient maximum. At the sea surface the ocean is always saturated with oxygen. A map of sea surface oxygen would therefore only illustrate the dependence of the saturation concentration on temperature (and to a minor degree salinity) and show an oxygen concentration of 8 mll 1 or more at temperatures near freezing point and 4 mll 1 at the high temperatures in the equatorial region. The oxygen distribution at 500 m depth carries a dual signal. It reflects the dependence of the saturation concentration on temperature and salinity in the same way as at the surface but modified by the effect of water mass aging. If water is out of contact with the atmosphere for extended periods of time it experiences an increase in nutrient content from the remineralization of falling detritus; this process consumes oxygen. Water in the permanent thermocline can be a few decades old, which reduces its
oxygen content to 60–80% of the saturation value (Figure 6). The northern Indian Ocean is an exception to this rule; its long ventilation time (see below) produces oxygen values below 20% saturation. In the polar regions oxygen values at 500 m depth are generally closer to saturation as a result of winter convection in the mixed layer (see below).
The Mixed Layer and Seasonal Thermocline Exposed to the action of wind and waves, heating and cooling, and evaporation and rainfall, the ocean surface is a region of vigorous mixing. This produces a layer of uniform properties which extends from the surface down as far as the effect of mixing can reach. The vertical extent or thickness of this mixed layer is thus controlled by the time evolution of the mixing processes. It is smallest during spring and summer when the ocean experiences net heat gain (Figure 7).The heat which accumulates at the surface is mixed downward through the action of wind waves. During this period of warming the depth of the mixed layer is determined by the maximum depth which wave mixing can affect. Because winds
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE
179
Figure 6 Annual mean oxygen saturation (%) at 500 m depth(the contour interval is 10%). (Reproduced from World Ocean Atlas 1994.)
Temperature 1
2 3
Temperature 5
4
1 2 3
Depth
Depth
4
Warming cycle
Cooling cycle
Figure 7 Time evolution of the seasonal mixed layer. Left, the warming cycle; right, the cooling cycle. Numbers can be approximately taken as successive months, with the association shown in Table 1.
areoften weaker during midsummer than during spring, wind mixing does not reach quite so deep during the summer months, and the mixed layer may consist of two or more layers of uniform properties (Figure 7, line 4 of the warming cycle). During fall and winter the ocean loses heat. This cooling produces a density increase at the sea
surface. As a result, mixing during the cooling period is no longer controlled by wave mixing but by convection. The convection depth is determined by the depth to which the layer has to be mixed until static stability is reached. The mixed layer therefore increases with time during fall and winter and reaches its greatest vertical extent just before spring. The thin region of rapid temperature change below the mixed layer is known as the seasonal thermocline. It is strongest (i.e., is associated with the largest change in temperature) in summer and disappears in winter. In the tropics (within 201 of the equator) the heat loss during winter is not strong enough to erase the seasonal thermocline altogether, and the seasonal character of the thermocline is then only seen as a variation of the associated vertical temperature gradient. In the subtropics the mixed layer depth varies between 20–50 m during summer and 70–120 m during winter. In subpolar regions the mixed layer depth can grow to hundreds of meters during winter. Three locations of particularly deep winter mixed layers are the North Atlantic Ocean between the Bay of Biscay and Iceland, the eastern South Indian Ocean south of the Great Australian Bight and the region to the west
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE
Table 1
Association between number in Figure 7 and months Northern Hemisphere
Southern Hemisphere
Number in Figure 7
Warming cycle
Cooling cycle
Warming cycle
Cooling cycle
1 2 3 4 5
February April May June
June August September October January
August October November December
December February March April July
of southern Chile. In these regions mixed layer depths can exceed 500 m during late winter.
The Barrier Layer The mixed layer depth is often equated with the depth of the seasonal thermocline. Historically this view is the result of the paucity of salinity or direct density observations and the resulting need to establish information about the mixed layer from a vertical profile of temperature alone. This approach is acceptable in many situations, particularlyin the temperate and subpolar ocean regions. There are, however, situations where it can be quite misleading. A temperature profile obtained in the equatorial western Pacific Ocean, for example, can show uniform temperatures to depths of 80–100 m. Such deep homogeneity in a region where typical wind speeds
33
34
rarely exceed those of a light breeze cannot be produced by wave mixing. The truth is revealed in a vertical profile of salinity which shows a distinct salinity change at a much shallower depth, typically 25–50 m, indicating that wave mixing does not penetrate beyond this level and that active mixing is restricted to the upper 25–50 m. In these situations the upper ocean contains an additional layer known as the barrier layer (Figure 8). The mixed layer extends to the depth where the first density change is observed. This density change is the result of a salinity increase with depth and therefore associated with a halocline (a layer of rapid vertical salinity change). The temperature above and below the halocline is virtually identical. The barrier layer is the layer between the halocline and thethermocline. The barrier layer is of immense significance for the oceanic heat budget. In most ocean regions the mixed 20
S
21 33.0
22
24 t 25 34.2 S
23
0 T
S
S
Depth (m)
20
T
σt
40
Barrier layer
t 60
80
100 20 (A)
20
22 21
24 22
26 23
28 T °C 30 24
t
25
22
24
26
28
T °C 30
(B)
Figure 8 The structure of the upper ocean in the absence (A) and presence (B) of a barrier layer. T: temperature (1C),S: salinity, st: density. Note the uniformity of temperature(T) from the surface to the bottom of the barrier layer in(B). The stations were taken in the central South China Sea during September 1994.
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE
layer experiences a net heat gain at the surface during spring and summer and has to export heatin order to maintain its temperature in a steady state. If (as described in a previous section) the mixed layer extends down to the seasonal thermocline, this is achieved through the entrainment of colder water into the mixed layer from below. The presence of the barrier layer means that the water entrained from the region below the mixed layer is of the same temperature as the water in the mixed layer itself. The entrainment process is still active but does not achieve the necessary heat export. The barrier layer acts as a barrier to the vertical heat flux, and the heat gained by the mixed layer has to be exported through other means, mainly through horizontal advection by ocean currents and, if the mixed layer is sufficiently transparent to the incoming solar radiation, through direct downward heat transfer from the atmosphere to the barrier layer. The existence of the barrier layer has only come to light in the last decade or two when high-quality salinity measurements became available in greater numbers. It has now been documented for all tropical ocean regions. In the Pacific Ocean the regional extent of the barrier layer is closely linked with high local rainfall in the Intertropical and South Pacific Convergence Zones of the atmosphere. This suggests that the Pacific barrier layer is formed by the lowering of the salinity in the shallow mixed layer in response to local rainfall. In contrast, the barrier layer in the Indian Ocean varies seasonally in extent, and the observed lowering of the mixed layer salinity seems to be related to the spreading of fresh water from rivers during the rainy monsoon season. In the Atlantic Ocean the barrier layer is most likely the result of subduction of high salinity water from the subtropics under the shallow tropical mixed layer. There are also observations of seasonal barrier layers in other tropical ocean regions, such as the South China Sea.
The Subtropical Gyres and the Permanent Thermocline The permanent or oceanic the rmocline is the transition from the upper ocean to the deeper oceanic layers. It is characterized by a relatively rapid decrease of temperature with depth, with a total temperature drop of some 151C over its vertical extent, which varies from about 800 m in the subtropics to less than 200 m near the equator. This depth range does not display the relatively strong currents experienced in the upper ocean but still forms part of the general wind driven circulation, so its water moves with the same current systems seen at the sea surface but with lesser speed.
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The permanent thermocline is connected with the atmosphere through the Subtropical Convergence, broad region of the upper ocean poleward of the subtropics where the wind-driven surface currents converge, forcing water to submerge (‘subduct’) under the upper ocean layer and enter the permanent thermocline. This convergence is particularly intense in the subtropical front, a region of enhanced horizontal temperature change within the Subtropical Convergence found at about 351Nand 401S. The Subtropical Front is therefore considered the poleward limit of the permanent thermocline (Figure 9). There is also a zonal variation in the vertical extent, with smallest values in the east and largest values in the west. Taken together, the permanent thermocline appears bowl shaped, being deepest in the western parts of the subtropical ocean (25–301N and 30–351S). The shape is the result of geostrophic adjustment in the wind-driven circulation, which produces anticyclonic water movement in the subtropics known as the subtropical gyres. In most ocean regions the permanent thermocline is characterized by a tight temperature–salinity(TS) relationship, lower temperatures being associated with lower salinities. If temperature or salinity is plotted on a constant depth level across the permanent thermocline, the highest temperature and salinity values are found in the western subtropics (Figures 4 and 5). The tight TS relationship indicates the presence of a stable water mass, known as Central Water. This water mass is formed at the surface in the subtropical convergence, particularly at the downstream end of the western boundary currents, where it is subducted and from where it renews (‘ventilates’) the permanent thermocline by circulating in the subtropical gyres, moving equatorward in the east, westward with the equatorial current system and returning to the ventilation region in the west. As a result the age of the Central Water does not increase in a simple meridional direction from the subtropical front towards the equator but is lower in the east and higher in the west. As the Subtropical Front is a feature of both hemispheres, each ocean, with the exception of the Indian Ocean which does not reach far enough north to have a Subtropical Front in the northern hemisphere, has Central Water of northern and southern origins (Figure 9). Fronts between the different varieties of Central Water are a prominent feature of the permanent thermocline. These fronts are characterized by strong horizontal temperature and salinity gradients but relatively small density change because the effect of temperature on density is partly compensated by the effect of salinity. As a result smallscale mixing processes such as double diffusion,
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE
N 60° Subtropical Front North Atlantic Central Water
Subtropical Front
30°
Western North Pacific Central Water Indian 0°
Tr a Eastern nsit io n North Zo ne Pacific Central Water
North Pacific Equatorial Water
Australasian Mediterranean Water
South Pacific Equatorial Water
Central Water
Western South Pacific Central Water
30°
South Atlantic Central Water
Eastern South Transition Pacific Zone Central Water
l Front
Front
Subtropical
Subtropica
60° S
30°
60°
90°
120°
150° E 180° W 150°
120°
90°
60°
30°
W 0° E
30°
Figure 9 Regional distribution of the water masses of the permanent thermocline.
filamentation and interleaving are of particular importance in these fronts.
The Equatorial Region The equatorial current system occupies the region 151S–151N and is thus more than 3000 km wide. Most of itis taken up by the North and South Equatorial Currents, the westward flowing equatorial elements of the subtropical gyres discussed above. Between these two currents flows the North Equatorial Countercurrent as a relatively narrow band eastward along 51N in the Atlantic and Pacific Oceans and, during the north-east monsoon season, along 51S in the Indian Ocean. Another eastward current, the Equatorial Undercurrent, flows submerged along the equator, where it occupies the depth range 50–250 m as a narrow band ofonly 200 km width. Currents near the equator are generally strong, and for dynamical reasons transport across the equator is more or less restricted to the upper mixed layer and to a narrow regime of a few hundred kilometers width along the western boundary of the oceans. This restriction andthe narrow eastward
currents embedded in the general westward flow, shape the distribution of properties in the permanent thermocline near the equator. Insituations where subtropical gyres exist (the Atlantic and Pacific Oceans) in both hemispheres they enter the equatorial current system from the north east and from the south east, leaving a more or less stagnant region (‘shadow zone’) between them near the eastern coast. Figure 10 shows the age distribution for the Atlantic Ocean. The presence of particularly old water in the east indicates a stagnant region or ‘shadow zone’ between the subtropical gyres. The strong eastward flowing currents in the equatorial current system modify the age distribution in the permanent thermocline further. In Figure 10 the Equatorial Undercurrent manifests itself as a band of relatively young water, which is carried eastward. The Indian Ocean does not extend far enough to the north to have a subtropical convergence in the Northern Hemisphere. In the absence of a significant source of thermocline water masses north of theequator the water of the Northern Hemisphere can only be ventilated from the south. Figure 11 shows property fields of the permanent thermocline in the
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE 60
60
> 14
12
13
50
40
183
>
12 11.5
40
11
10
Latitude
20
> 12
ICW
30
(A)
0 20
_ 20
.6
>
35.4
35 35.2
35.1
10 _ 40 _ 100
35.0 _ 80
_ 60
_ 40 _ 20 Longitude
0
20
AAMW
>
34.8
34.6
0 Years
Figure 10 Pseudo age of Central Water in equatorial region of the Atlantic Ocean at 500 m depth. The quantity pseudo age expresses the time elapsed since the water had last contact with the atmosphere; it is determined by using anarbitrary but realistic oxygen consumption rate for the permanent thermocline. (Reproduced from Poole and Tomczak m (19) Optimum multiparameter analysis of the water mass structure in the Atlantic Ocean thermocline. Deep-Sea Research 46: 1895–1921.)
Indian Ocean and pathways of its water masses. The region between 51S and the equator is dominated by the westward flow of Australasian Mediterranean Water (AAMW), a water mass formed in the Indonesian seas. Its mass transport is relatively modest, and it is mixed into the surrounding waters before it reaches Africa. Indian Central Water(ICW) originates near 301S in large volume; it joins the anticyclonic circulation of the subtropical gyre and can be followed (at the depth level shown in Figure 11 by its temperature of 11.71C and salinity of 35.1) across the equator along the African coast and into the Northern Hemisphere. The flow into the Northern Hemisphere is thus severely restricted, and the ventilation of the northern Indian Ocean thermocline is unusually inefficient. This is reflected in the extremely low oxygen content throughout the northern Indian Ocean.
The Polar Regions Poleward of the subtropical front the upperocean changes character. As polar latitudes are approached the distinction between upper ocean and deeper layers disappears more and more. There is no
(B)
>3
5.2
35.1
< 0.5
3.0 4.0
35.2
>
O2 < 0.5 1.0 2.5
2.0
4.5 > 5.5
< 4.5 (C)
60°
80°
100°
120°
E
Figure 11 Climatological mean temperature (1C) (A),salinity (PSU) (B) and oxygen concentration (ml l 1) (C) in the Indian Ocean for the depth range 300–450 m, with pathways for Indian Central Water (ICW)and Australasian Mediterranean Water (AAMW). (Reproduced from Tomczak and Godfrey, 1994.)
permanent thermocline; temperature, salinity and all other properties are nearly uniform with depth. The surface mixed layer is, of course, still well defined as the layer affected by wave mixing, but its significance for the heat exchange with the atmosphere is greatly reduced because frequent convection events produced by surface cooling penetrate easily into the waters below themixed layer. Because in the polar regions the upper ocean and the deeper layers form a single dynamic unit, the horizontal structure of the upper ocean in these regions is strongly influenced by features of the deeper layers. Figure 12 shows the arrangement of the
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UPPER OCEAN MEAN HORIZONTAL STRUCTURE
W 0° E
Subantarctic front
F
AD
°S 60
B
CW
e
Zon
e
57°S
Zon
ne
Zo
Polar frontal
PF
Polar front
S 30 °
SAF
Subantarctic
ST
58°
Antarctic
184
59°
60°
61°
Continental water boundary
W 180°E
62°S
Continental zone
Figure 12 Fronts in the Southern Ocean. (Reproduced from Tomczak and Godfrey, 1994) STF, Subtropical Front; SAF, Subantarctic Front; PF, Polar Front; CWB, Continental Water boundary; AD, Antarctic Divergence.
various fronts in the Southern Ocean. The fronts are associated with the Antarctic Circumpolar Current. They occupy about 20% of its area but carry 75% of its transport. These fronts extend from the surface to the ocean floor and are thus not exclusive features of the upper ocean. At the low temperatures experienced in the polar seas the density is very insensitive to temperature changes and iscontrolled primarily by the salinity. During ice formation salt seeps out and accumulates under the ice, increasing the water density and causing it to sink. Salt from the upper ocean is thus transferred to the deep ocean basins. As a result, a significant amount of fresh water is added to the upper ocean when the ice melts and floats over the oceanic water. The resulting density gradient guarantees stability of the water column even in the presence of temperature inversions. A characteristic feature of the upper ocean in the polar regions is therefore the widespread existence of shallow temperature maxima. In the Arctic Ocean the water
below the upper ocean can be as much as 41C warmer than the mixed layer. Intermediate temperature maxima in the Antarctic Ocean are less pronounced (up to 0.51C) but occur persistently around Antarctica.
See also Ekman Transport and Pumping. Geophysical Heat Flow. Heat Transport and Climate. Satellite Remote Sensing of Sea Surface Temperatures. Satellite Remote Sensing: Salinity Measurements. Wind- and Buoyancy-Forced Upper Ocean. Wind Driven Circulation.
Further Reading Tomczak M and Godfrey JS (1994) Regional Oceanography: an Introduction. Oxford: Pergamon.
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UPPER OCEAN MIXING PROCESSES
The ocean’s effect on weather and climate is governed largely by processes occurring in the few tens of meters of water bordering the ocean surface. For example, water warmed at the surface ona sunny afternoon may remain available to warm the atmosphere that evening, or it may be mixed deeper into the ocean not to emerge for many years, depending on near-surface mixing processes. Local mixing of the upper ocean is predominantly forced from the state of the atmosphere directly above it. The daily cycle of heating and cooling, wind, rain, and changes in temperature and humidity associated with mesoscale weather features produce a hierarchy of physical processes that act and interact to stir the upper ocean. Some of these are well understood, whereas others have defied both observational description and theoretical understanding. This article begins with an example of in situ measurements of upper ocean properties. These observations illustrate the tremendous complexity of the physics, and at the same time reveal some intriguing regularities. We then describe a set of idealized model processes that appear relevant to the observations and in which the underlying physics is understood, at least at a rudimentary level. These idealized processes are first summarized, then discussed individually in greater detail. The article closes with a brief survey of methods for representing upper ocean mixing processes in large-scale ocean models. Over the past 20 years it has become possible to make intensive turbulence profiling observations that reveal the structure and evolution of upper ocean mixing. An example is shown in Figure 1, which illustrates mixed-layer1 evolution, temperature
structure and small-scale turbulence. The small white dotsin Figure 1 indicate the depth above which stratification is neutral or unstable and mixing is intense, and below which stratification is stable and mixing is suppressed. This represents a means of determining the vertical extent of the mixed layer directly forced by local atmospheric conditions. (We will call the mixed-layer depth D.) Following the change in sign from negative (surface heating) to positive (surface cooling) of the surface buoyancy flux, Jb0 , the mixed layer deepens. (Jb0 represents the flux of density (mass per unit volume) across the sea surface due to the combination of heating/cooling and evaporation/ precipitation.) The mixed layer shown in Figure 1 deepens each night, butthe rate of deepening and final depth vary. Each day, following the onset of daytime heating, the mixed layer becomes shallower. Significant vertical structure is evident within the nocturnal mixed layer. The maximum potential temperature (y) is found at mid-depth. Above this, y is smaller and decreases toward the surface at the rate of about 2 mK in 10 m. The adiabatic change in temperature, that due to compression of fluid parcels with increasing depth, is 1 mKin 10 m. The region above the temperature maximum is superadiabatic, and hence prone to convective instability. Below this superadiabatic surface layer is a layer of depth 10–30 m in which the temperature change is less than 1 mK. Within this mixed layer, the intensity of turbulence, as quantified by the turbulent kinetic energy dissipation rate, e, is relatively uniform and approximately equal to Jb0 . (e represents the rate at which turbulent motions in a fluid are dissipated to heat. It is an important term in the evolution equation for turbulent kinetic energy, signifying the tendency for turbulence to decay inthe absence of forcing.) Below the mixed layer, e generally (but not always) decreases, whereas above, e increases by 1–2 factors of 10. Below the mixed layer is a region of stable stratification that partially insulates the upper ocean from the ocean interior. Heat, momentum, and chemical species exchanged between the atmosphere and the ocean interior must traverse the centimeters thick cool
1 Strictly, a mixed layer refers to a layer of fluid which is not stratified (vertical gradients of potential temperature, salinity and potential density, averaged horizontally or in time, are zero. The terminology is most precise in the case of a convectively forced boundary layer. Elsewhere, oceanographers use the term loosely to describe the region of the ocean that responds most directly to
surface processes. Late in the day, following periods of strong heating, the mixed layer may be quite shallow (a few meters or less), extending to the diurnal thermocline. In winter and following series of storms, the mixed layer may extend vertically to hundreds of meters, marking the depth of the seasonal thermocline at midlatitudes.
J. N. Moum and W. D. Smyth, Oregon State University, Corvallis, OR, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3093–3100, & 2001, Elsevier Ltd.
Introduction
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UPPER OCEAN MIXING PROCESSES
7 0
_
10 J b (W kg 1)
2 0 _2 _4
(mK)
(A)
_ 40
_ 20
0
_ 10
(mK) _5 0
Depth (m)
_ 20
_ 40
_ 60
_ 80
2
_3
log10 (m s )
(B)
_6
_8
_4
Depth (m)
_ 20
_ 40
_ 60
_ 80 0
Jb (C)
03/16
03/18
_8
2
_6
_3
log10 (m s )
Figure 1 Observations of mixing in the upper ocean over a five-dayperiod. These observations were made in March 1987 in the North Pacific using a vertical turbulence profiler and shipboard meteorological sensors. (A) The variation in the surface buoyancy flux, Jb0 , which is dominated by surface heating and cooling. The red (blue) areas represent daytime heating (nighttime cooling). Variations in the intensity of nighttime cooling are primarily due to variations in winds. (B) Potential temperature referenced to the individual profile mean in order to emphasize vertical rather than horizontal structure (y; K). To the right is an averaged vertical profile from the time period indicated by the vertical bars at top and bottom of each of the left-hand panels. (C) The intensity of turbulence as indicated by the viscous dissipation rate of turbulence kinetic energy, e. To the right is an averaged profile with the mean value of Jb0 indicated by the vertical blue line. The dots in (B) and (C) represent the depth of the mixed layer as determined from individual profiles.
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UPPER OCEAN MIXING PROCESSES
skin at thevery surface, the surface layer, and the mixed layer to modify the stable layer below. These vertical transports are governed by a combination of processes, including those that affect only the surface itself (rainfall, breaking surface gravity waves), those that communicate directly from the surface throughout the entire mixed layer (convective plumes) or a good portion of it (Langmuir circulations) and also those processes that are forced at the surface but have effects concentrated at themixed-layer base (inertial shear, Kelvin–Helmholtz instability, propagating internal gravity waves). Several of these processes are represented in schematic form in Figure 2. Whereas Figure 1 represents the observed time evolution of the upper ocean at a single location, Figure 2 represents an idealized three-dimensional snapshot of some of the processes that contribute to this time evolution. Heating of the ocean’s surface, primarily by solar (short-wave) radiation, acts to stabilize the water column, thereby reducing upper ocean mixing. Solar radiation, which peaks at noon and is zero at night, penetrates the air–sea interface (limited by absorption and scattering to a few tens of meters), but
187
heat is lost at the surface by long-wave radiation, evaporative cooling and conduction throughout both day and night. The ability of the atmosphere to modify the upper ocean is limited by the rate at which heat and momentum can be transported across the air–sea interface. The limiting factor here is theviscous boundary layer at the surface, which permits only molecular diffusion through to the upper ocean. This layer is evidenced by the ocean’s coolskin, a thin thermal boundary layer (a few millimeters thick), across which a temperature difference of typically 0.1 K is maintained. Disruption ofthe cool skin permits direct transport by turbulent processes across theair–sea interface. Once disrupted, the cool skin reforms over a period of some tens of seconds. A clear understanding of processes that disrupt the coolskin is crucial to understanding how the upper ocean is mixed.
Convection Cooling at the sea surface creates parcels of cool, dense fluid, which later sink to a depth determined Wind
Cooling
Velocity shear
Sea surface
(z) Surface layer
Mixed layer
Breaking w ave bubble inje ction
Convecti
(K) 0.1
Wind row
Wind row
(x)
Cool skin
Wind row
Shear-induce d turbulence
(x)
z (m) 0.01
ir mu ng tion a L ula circ
on
Thermo cline Breakin g interna l waves Figure 2 Diagram showing processes that have been identified by a widerange of observational techniques as important contributors to mixing the upperocean in association with surface cooling and winds. The temperature (y) profiles shown here have the adiabatic temperature (that due to compression of fluid parcels with depth) removed; thisis termed potential temperature. The profile of velocity shear (vertical gradient of horizontal velocity) indicates no shear in the mixed layer and nonzero shear above. The form of the shear in the surface layer is a current area of research. Shear-induced turbulence near the surface may be responsible for temperature ramps observed from highly resolved horizontal measurements. Convective plumes and Langmuir circulations both act to redistribute fluid parcels vertically; during convection, they tend to movecool fluid downward. Wind-driven shear concentrated at the mixed-layer base (thermocline) may be sufficient to allow instabilities to grow, from which internal gravity waves propagate and turbulence is generated. At the surface, breaking waves inject bubbles and highly energetic turbulence beneath the sea surface and disrupt the ocean’s cool skin, clearing a pathway for more rapid heat transfer into the ocean.
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UPPER OCEAN MIXING PROCESSES
by the local stratification in a process known as convection. Cooling occurs almost every night and also sometimes in daytime in association with weather systems such as cold air outbreaks from continental landmasses. Convection may also be causedby an excess of evaporation over precipitation, which increases salinity, and hence density, at the surface. Winds aid convection by a variety of mechanisms that agitate the sea surface, thereby disrupting the viscous sublayer and permitting rapid transfer of heat through the surface (see below). Convection in the ocean is analogous to that found in the daytime atmospheric boundary layer, which is heated from below, and which has been studied in great detail. Recourse to atmospheric studies of convection has helped in understanding the ocean’s behavior. Surface tension and viscous forces initially prevent dense, surface fluid parcels from sinking. Once the fluid becomes sufficiently dense, however, these forces are overcome and fluid parcels sinkin the form of convective plumes. The relative motion of the plumes helps to generate small-scale turbulence, resulting in a turbulent field encompassing a range of scales from the depth of the mixed layer (typically 100 m) to a few millimeters. A clear feature of convection created bysurface cooling is the temperature profile of the upper ocean (Figure 1). Below the cool skin is an unstable surface layer that is the signature of plume formation. Below that is a well-mixed layer in which density (as well as temperature and salinity) is relatively uniform. The depth of convection is limited bythe local thermocline. Mixing due to penetrative convection into the thermocline represents another source of cooling of the mixed layer above. Within the convecting layer, there is an approximate balance between buoyant production of turbulent kinetic energy and viscous dissipation, as demonstrated by the observation eEJb0 . The means by which the mixed layer is restratified following nighttime convection are not clear. Whereas someone-dimensional models yield realistic time series of sea surface temperature, suggesting that restratification is a one-dimensional process (see below), other studies of this issue have shown onedimensional processes to account for only 60% of the stratification gained during the day. It has been suggested that lateral variations in temperature, due to lateral variations in surface fluxes, or perhaps lateral variations in salinity due to rainfall variability, may be converted by buoyant forces into vertical stratification. These indicate the potential importance of three-dimensional processes to restratification.
Wind Forcing Convection is aided by wind forcing, in part because winds help to disrupt the viscous sublayer at the sea surface, permitting more rapid transport of heat through the surface. In the simplest situation, winds produce a surface stress and a sheared current profile, yielding a classic wall-layer scaling of turbulence and fluxes in the surface layer, similar to the surface layer of the atmosphere. (Theory, supported by experimental observations, predicts a logarithmic velocity profile and constant stress layer in the turbulent layer adjacent to a solid boundary. This is typically found in the atmosphere during neutral stratification and is termed wall-layer scaling.) This simple case, however, seems to berare. The reason for the difference in behaviors of oceanic and atmospheric surface layers is the difference in the boundaries. The lower boundary of the atmosphere is solid (at least over land, where convection is well-understood), but the ocean’s upper boundary is free to support waves, ranging from centimeter-scale capillary waves, through wind waves (10s of meters) to swell (100s of meters). Thesmaller wind waves lose coherence rapidly, and are therefore governed by local forcing conditions. Swell is considerably more persistent, and may therefore reflect conditions at a location remote in space and time from the observation, e.g., a distant storm. Breaking Waves
Large scale breaking of waves is evidenced at the surface by whitecapping and surface foam, allowing visual detection from above. This process, which is not at all well understood, disrupts the ocean’s cool skin, a fact highlighted by acoustic detection of bubbles injected beneath the sea surface by breaking waves. Small-scale breaking, which has no visible signature (and is even less well understood but is thought to be due to instabilities formed in concert with the superposition of smaller-scale waves) also disrupts the ocean’s cool skin. An important challenge for oceanographers is to determine the prevalence of small-scale wave breaking and the statistics of cool skin disruption at the sea surface. The role of wave breaking in mixing is an issue of great interest at present. Turbulence observations in the surface layer under a variety of conditions have indicated that at times (generally lower winds and simpler wave states) the turbulence dissipation rate (and presumably other turbulence quantities including fluxes) behaves in accordance with simple wall-layer scaling and is in this way similar to the atmospheric surface layer. However, under higher winds, and perhaps more complicated wave states, turbulence dissipation rates greatly exceed those
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UPPER OCEAN MIXING PROCESSES
predicted by wall-layer scaling. This condition has been observed to depths of 30 m, well below a significant wave height from the surface, and constituting a significant fraction of the ocean’s mixed layer. (The significant wave height is defined as the average height of the highest third of surface displacement maxima. A few meters is generally regarded as a large value.) Evidently, an alternative to wall-layer scaling is needed for these cases. This is a problem of great importance in determining both transfer rates across the air–sea interface to the mixed layer below and the evolution of the mixed layer itself. It is at times when turbulence is most intense that most of the air–sea transfers and most of the mixed layer modification occurs. Langmuir Circulation
Langmuir circulations are coherent structures within the mixed layer that produce counter rotating vortices with axes aligned parallel to the wind. Their surface signature is familiar as windrows: lines of bubbles and surface debris aligned with the wind that mark the convergence zones between the vortices. These convergence zones are sites of downwind jets in the surface current. They concentrate bubble clouds produced by breaking waves, or bubbles produced by rain, which are then carried downward, enhancing gas-exchange rates with the atmosphere. Acoustical detection of bubbles provides an important method for examining the structure and evolution of Langmuir circulations. Langmuir circulations appear to be intimately related to the Stokes drift, a small net current parallel to the direction of wave propagation, generated by wave motions. Stokes drift is concentrated at the surface and is thus vertically sheared. Small perturbations in the wind-driven surface current generate vertical vorticity, which is tilted toward the horizontal (downwind) direction by the shear of the Stokes drift. The result of this tilting is a field of counterrotating vortices adjacent to the ocean surface, i.e., Langmuir cells. It is the convergence associated with these vortices that concentrates the wind-driven surface current into jets. Langmuir cells thus grow by a process of positive feedback. Ongoing acceleration of the surface current by the wind, together with convergence of the surface current by the Langmuir cells, provides a continuous source of coherent vertical vorticity (i.e., the jets), which is tilted by the mean shear to reinforce the cells. Downwelling speeds below the surface convergence have been observed to reach more than 0.2 m s1, comparable to peak downwind horizontal flow speeds. By comparison, the vertical velocity scale associated with convection, w ¼ ðJb0 DÞ1=3 is
189
closer to 0.01 m s1. Upward velocities representing the return flow to the surface appear to be smaller and spread over greater area. Maximum observed velocities are located well below the sea surface but also well above the mixed-layer base. Langmuir circulations are capable of rapidly moving fluid vertically, thereby enhancing and advecting the turbulence necessary to mix the weak near-surface stratification which forms in response to daytime heating. However, this mechanism does not seem to contribute significantly to mixing the base of the deeper mixed layer, which is influenced more by storms and strong cooling events. In contrast, penetration of the deep mixed layer base during convection (driven by the conversion of potential energy of dense fluid plumes created by surface cooling/evaporation into kinetic energy and turbulence) is believed to be an important means of deepening the mixed layer. So also is inertial shear, as explained next. Wind-Driven Shear
Wind-driven shear erodes the thermocline at the mixedlayer base. Wind-driven currents often veer with depth due to planetary rotation (cf. the Ekman spiral). Fluctuations in wind speed and direction result in persistent oscillations at near-inertial frequencies. Such oscillations are observed almost everywhere in the upper ocean, and dominate the horizontal velocity component of the internal wave field. Because near-inertial waves dominate the vertical shear, they are believed to be especially important sources of mixing at the base of the mixed layer. In the upper ocean, near-inertial waves are generally assumed to be the result of wind forcing. Rapid diffusion of momentum through the mixed layer tends to concentrate shear at the mixed layer base. This concentration increases the probability of small-scale instabilities. The tendency toward instability is quantified by the Richardson number, Ri ¼ N2/S2, where N2 ¼ (g/r) dr/dz, represents the stability of the water column, and shear, S, represents an energy source for instability. Small values of Ri (o1/4) are associated with Kelvin–Helmholtz instability. Through this instability, the inertial shear is concentrated into discrete vortices (Kelvin–Helmholtz billows) with axes aligned horizontally and perpendicular to the current. Ultimately, the billows overturn and generate small-scale turbulence and mixing. Some of the energy released by the instabilities propagates along the stratified layer as high frequency internal gravity waves. These processes are depicted in Figure 2. The mixing of fluid from below the mixed layer by inertial shear contributes to increasing the density of the mixed-layer and to mixedlayer deepening.
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UPPER OCEAN MIXING PROCESSES
Temperature Ramps
Another form of coherent structure in the upper ocean has been observed in both stable and unstable conditions. In the upper few meters temperature ramps, aligned with the wind and marked by horizontal temperature changes of 0.1 K in 0.1 m, indicate the upward transport of cool/warm fluid during stable/unstable conditions. This transport is driven by an instability triggered by the wind and perhaps similar to the Kelvin–Helmholtz instability discussed above. It is not yet clearly understood. Because it brings water of different temperature into close contact with the surface, and also because it causes large lateral gradients, this mechanism appears to be a potentially important factor in near-surface mixing.
Effects of Precipitation Rainfall on the sea surface can catalyze several important processes that act to both accentuate and reduce upper oceanmixing. Drops falling on the surface disrupt the viscous boundary layer, andmay carry air into the water by forming bubbles. Rain is commonly said to ‘knock downthe seas.’ The evidence for this is the reduction in breaking wave intensity and whitecapping at the sea surface. Smaller waves (o20 cm wavelength) may be damped by subsurface turbulence as heavy rainfall actsto transport momentum vertically, causing drag on the waves. The reduced roughness of the small-scale waves reduces the probability of the waves exciting flow separation on the crests of the long waves, and hence reduces the tendency of the long waves to break. While storm winds generate intense turbulence near the surface, associated rainfall can confine this turbulence tothe upper few meters, effectively insulating the water below from surface forcing. This is due to the low density of fresh rainwater relative to the saltier ocean water. Turbulence must work against gravity to mix the surface water downward, and turbulent mixing is therefore suppressed. So long asvertical mixing is inhibited, fluid heated during the day will be trapped near the sea surface. Preexisting turbulence below the surface will continue to mixfluid in the absence of direct surface forcing, until it decays due to viscous dissipation plus mixing, typically over the time scale of a buoyancy period, N1. Deposition of pools of fresh water on the sea surface, such as occurs during small-scale squalls, raises some interesting prospects for both lateral spreading and vertical mixing of the fresh water. In the warm pool area of the western equatorial Pacific, intense squalls are common. Fresh light puddles at the surface cause the surface density field to be
heterogeneous. Release of the density gradient may then occur as an internal bore forming on the surface density anomaly, causing a lateral spreading of the fresh puddle. Highly resolved horizontal profiles of temperature, salinity and density reveal sharp frontal interfaces, the features of which depend on the direction of the winds relative to the buoyancy-driven current. These are portrayed in Figure 3. When the wind opposes the buoyancy current, the density anomaly at the surface is reduced, possibly as a result of vertical mixing in the manner suggested in Figure 3B(B). This mechanism results in a rapid vertical redistribution of fresh water fromthe surface pool and a brake on the propagation of the buoyancy front. Similarly, an opposing ambient current results in shear at the base of the fresh layer, which may lead to instability and consequent mixing. The nature of these features has yet to be clearly established, as has the net effect on upper ocean mixing.
Ice on the Upper Ocean At high latitudes, the presence of an icelayer (up to a few meters thick) partially insulates the oceana Wind
No convection
Buoyancy-driven current
Dense water No entrainment
Wind drift current
(A) Wind Buoyancy-driven current
Convection Entrainment
Dense water
Wind drift current
(B)
Figure 3 Two ways in which the frontal interface of a fresh surface poolmay interact with ambient winds and currents. (A) The case in which the buoyancy-driven current, wind and ambient current are all in the same direction. In this case, the buoyancydriven current spreads and thins unabated. In (B), the buoyancydriven current is opposed by wind and ambient current. In this case, the frontal interface of the buoyancy-driven current may plunge below the ambient dense water, so that convection near the surface intensifies mixing at the frontal interface. Simultaneously, shearforced mixing at the base of the fresh puddle may increase entrainment of dense water from below.
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UPPER OCEAN MIXING PROCESSES
gainst surface forcing. This attenuates the effects of wind forcing on the upper ocean except at the lowest frequencies. The absence of surface waves prevents turbulence due to wave breaking and Langmuir circulation. However, a turbulence source is provided by the various topographic features found on the underside of the ice layer. These range in size from millimeter-scaledendritic structures to 10 m keels, and can generate significant mixing nearthe surface when the wind moves the ice relative to the water below or currents flow beneath the ice. Latent heat transfer associated with melting and freezing exerts a strong effect on the thermal structure of the upper ocean. Strong convection can occur under ice-free regions, in which the water surface is fully exposed to cooling and evaporative salinity increase. Such regions include leads (formed by diverging ice flow) and polynyas (where wind or currents remove ice as rapidly as it freezes). Convection can also be caused by the rejection of salt by newly formed ice, leaving dense, salty water near the surface.
Parameterizations of Upper Ocean Mixing Large-scale ocean and climate models are incapable of explicitly resolving the complex physics of the upper ocean,and will remain so for the foreseeable future. Since upper ocean processes are crucial in determining atmosphere–ocean fluxes, methods for their representation in large-scale models, i.e., parameterizations, are needed. The development of upper-ocean mixing parameterizations has drawn on extensive experience in the more general problem of turbulence modeling. Some parameterizations emphasize generality, working from first principles as much as possible, whereas others sacrifice generality to focus on properties specific to the upper ocean. An assumption common to all parameterizations presently in use is that the upper ocean is horizontally homogeneous, i.e., the goal is to represent vertical fluxes in terms of vertical variations in ocean structure, leaving horizontal fluxes to be handled by other methods. Such parameterizations are referred to as‘one-dimensional’ or ‘column’ models. Column modeling methods may be classified aslocal or nonlocal. In a local method, turbulent fluxes at a given depth are represented as functions of water column properties at that depth. For example, entrainment at the mixed-layer base may be determined solely by the local shear and stratification. Nonlocal methods allow fluxes to be influenced directly by remote events. For example, during nighttime
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convection, entrainment at the mixed-layer base may be influenced directly by changes in the surface cooling rate. In this case, the fact that large convection rolls cannot be represented explicitly in a column model necessitates the nonlocal approach. Nonlocal methods include ‘slab’ models, in which currents and water properties do not vary at all across the depth of the mixed layer. Local representations may often be derived systematically from the equations of motion, whereas nonlocal methods tend tobe ad hoc expressions of empirical knowledge. The most successful models combine local and nonlocal approaches. Many processes are now reasonably wellrepresented in upper ocean models. For example, entrainment via shear instability is parameterized using the local gradient Richardson number and/or a nonlocal (bulk) Richardson number pertaining to the whole mixed layer. Other modeling issues are subjects of intensive research. Nonlocal representations of heat fluxes have resulted in improved handling of nighttime convection, but the corresponding momentum fluxes have not yet been represented. Perhaps the most important problem at present is there presentation of surface wave effects. Local methods are able to describe the transmission of turbulent kinetic energy generated at the surface into the ocean interior. However, the dependence of that energy flux on surface forcingis complex and remains poorly understood. Current research into the physics of wave breaking, Langmuir circulation, wave-precipitation interactions, and other surface wave phenomena will lead to improved understanding, and ultimately to useful parameterizations.
See also Breaking Waves and Near-Surface Turbulence. Bubbles. Deep Convection. Heat and Momentum Fluxes at the Sea Surface. Internal Tides. Langmuir Circulation and Instability. Penetrating Shortwave Radiation. Surface Gravity and Capillary Waves. Three-Dimensional (3D) Turbulence. Under-Ice Boundary Layer. Upper Ocean Vertical Structure. Whitecaps and Foam. Wave Generation by Wind.
Further Reading Garrett C (1996) Processes in the surface mixed layer of the ocean. Dynamics of Atmospheres and Oceans 23: 19--34. Thorpe SA (1995) Dynamical processes at the sea surface. Progress in Oceanography 35: 315--352.
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS L. K. Shay, University of Miami, Miami, FL, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction Ocean temperature structure changes from profiler and remotely sensed data acquired during hurricane passage have been documented in the literature. These oceanic response measurements have emphasized the sea surface temperature (SST) cooling and deepening of the wind-forced ocean mixed layer (OML). The level of SST cooling and OML deepening process are associated with the oceanic current response, which has two major components (Figure 1). First, the momentum response is associated with the OML current divergence in the nearfield with a net transport away from the storm center. This divergent flow causes upwelling of the isotherms and an upward vertical velocity. Over the next half of the cycle, currents and their transport converge toward the track, forcing downwelling of warmer water into the thermocline. This cycle of upwelling and downwelling regimes occurs over distances of an inertial wavelength and is proportional to the product of the storm translation speed and the local inertial period. Over these distances, horizontal pressure gradients couple the wind-forced OML to the thermocline as part of the three-dimensional cold wake. In the Northern Hemisphere, wind-forced currents rotate anticyclonically (clockwise) with time and depth where the period of oscillation is close to the local inertial period (referred to as near-inertial). This near-inertial current vector rotation with depth creates significant vertical current shears across the OML base and the top of the seasonal thermocline that induces vertical mixing and cooling and deepening of the layer. For these two reasons, the upper ocean current transport and vertical current shear are central to understanding the ocean’s thermal response to hurricane forcing. The SST response, and by proxy the OML temperature response, typically decreases by 1–5 1C to the right of the storm track at one to two radii of maximum winds (Rmax) due to surface wind field asymmetries, known as the ‘rightward bias’. Although warm SSTs (Z26 1C) are required to maintain a
192
hurricane, maximum SST decreases and OML depth increases of 20–40 m are primarily due to entrainment mixing of the cooler thermocline water with the warmer OML water. Ocean mixing and cooling are a function of forced current shear (qv/qz ¼ s) that reduce the Richardson number (defined as the ratio of buoyancy frequency (N2) and (s2)) to decrease below criticality. The proportion of these physical processes to the cooling of the OML heat budget are sheardriven entrainment mixing (60–85%), surface heat and moisture fluxes (Qo) (5–15%), and horizontal advection by ocean currents (5–15%) under relatively quiescent initial ocean conditions (no background fronts or eddies). As per Figure 1, vertical motion (upwelling) increases the buoyancy frequency associated with more stratified water that tends to increase the Richardson number above criticality. In strong frontal regimes (e.g., the Loop Current (LC) and warm core rings (WCRs)) with deep OML, cooling induced by these physical processes is considerably less than observed elsewhere. During hurricane Opal’s passage in the Gulf of Mexico (GOM), SST cooling within a WCR was B1 1C compared to B3 1C on its periphery. In these regimes where the 26 1C isotherm is deep (i.e., 100 m), more turbulent mixing induced by vertical current shear is required to cool and deepen an already deep OML compared to the relatively thin OMLs. That the entrainment heat fluxes at the OML base are not significantly contributing to the SST cooling implies there is more heat for the hurricane itself via the heat and moisture surface fluxes. These regimes have less ‘negative feedback’ to atmosphere than typically observed over the cold wake. To accurately forecast hurricane intensity and structure change in coupled models, the ocean needs to be initialized correctly with both warm and cold fronts, rings and eddies observed in the tropical and subtropical global oceans. The objective of this article is to build upon the article by Shay in 2001 to document recent progress in this area of oceanic response to hurricanes with a focus on the western Atlantic Ocean basin. The rationale here is that in the GOM (Figure 1(c)), in situ measurements are more comprehensive under hurricane conditions than perhaps anywhere else on the globe. Second, once a hurricane moves over this basin, it is going to make landfall along the coasts of Mexico, Cuba, and the United States. In the first
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS (c)
(a)
32° N
Mississippi Alabama Louisiana
30° N
−200 m
26° N
WCR Envelope
24° N
Warm Core Ring
−200 m
22° N
Yucatan Straits
Transport
−200 m
Florida Current Cuba
96° W
92° W
88° W
84° W
80° W
xu
′
*
h ∆h
(z)
v mixing z
w Thermocline −8
Loop Current
Northwest Caribbean Sea
Mexico
20° N 100° W Qo
Florida
Texas
28° N
(b)
Georgia
−6
−4
−2
Upwelling 0 R max
2
4
6
8
Figure 1 (a) Tropical cyclone image and (b) a cross-section schematic of the physical processes that alter the OML depth (h: light gray line) forced by hurricane winds (u *) such as shear-induced mixing (qv/qz ¼ shear) and OML depth changes (Dh: dark gray line), upwelling (w) due to transport (arrows) by currents away from the storm center relative to the surface depression (Z0 ), and surface heat fluxes (Qo) from the ocean to the atmosphere, all of which may contribute to ocean cooling during TC passage. (c) States and countries surrounding the Gulf of Mexico and northwest Caribbean Sea and identification of the key oceanic features and processes and areas relative to the 200-m isobath. (a, b) Adapted from Shay LK (2001) Upper ocean structure: Response to strong forcing events. In: Weller RA, Thorpe SA, and Steele J (eds.) Encyclopedia of Ocean Sciences, pp. 3100–3114. London: Academic Press.
section following this, progress on understanding the wind forcing and the surface drag coefficient behavior at high winds is discussed within the context of the bulk aerodynamic formula. In the next section, the importance of temperature, current, and shear measurements with respect to model initialization are described. While cold wakes are usually observed in relatively quiescent oceans (i.e., hurricanes Gilbert (1988); Ivan, Frances (2004)), the oceanic response is not nearly as dramatic in warm features. This latter point has important consequences for coupled models to accurately simulate the atmospheric response where the sea–air transfers (e.g., surface fluxes) may not decrease to significant levels as observed over cold wakes. These physical processes for oceanic response are briefly documented here for recent hurricanes such as the LC, WCR, and cold core ring (CCR) interactions and coastal ocean response during hurricanes Lili in 2002, Ivan in 2004, and Katrina and Rita in 2005. Concluding remarks as well as suggested avenues for future research efforts are in the final section.
Atmospheric Forcing Central to the question of storm forcing and the ocean response is the strength of the surface wind stress and the wind stress curl defined at 10 m above the surface. Within the framework of the bulk aerodynamics formula, the wind stress is given by t ¼ ra cd W10 ðu10 i þ v10 jÞ where ra is the air density, cd is the surface drag coefficient, the magnitude of the 10-m wind (W10 ¼ O(u10 2 þ v10 2 ), where u10 and v10 represent the surface winds at 10 m in the east (i) and north (j) directions, respectively). Momentum transfer between the two fluids is characterized by the variations of wind speed with height and a surface drag coefficient that is a function of wind speed and surface roughness. It is difficult to acquire flux measurements for the high wind and wave conditions under the eyewall at 10 m; however, profilers have been deployed from
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
aircraft to measure the Lagrangian wind profiles in hurricanes. These profiler data suggest a logarithmic variation of mean wind speed in the lowest 200 m of the boundary layer. Based on this variation, the surface wind stress, roughness length, and neutral stability drag coefficient determined by the profile method indicate a leveling of the surface momentum flux as winds increase above hurricane force with a slight decrease of the drag coefficient with increasing winds. Donelan and colleagues found the characteristic behavior cd since surface conditions change from aerodynamically smooth to aerodynamically rough (cd increasing with wind speed) conditions. In rough flow, the drag coefficient is related to the height of the ‘roughness elements’ per unit distance downwind or the spatial average of the downwind slopes. In a hurricane, rapid changes in wind speed and direction occur over short distances compared to those required to approach full-wave development. The largest waves in the wind-sea move slowly compared to the wind and travel in directions differing from the surface winds. Under such circumstances, longer waves contribute to the roughness of the sea and a ‘saturation’ of the drag coefficient occurs after wind speeds exceed 33 m s 1 (Figure 2). Beyond this threshold, the surface does not become any rougher. These results suggest that there may be a limiting state in the aerodynamic roughness of the sea surface.
× 10−3
5
The oceanic response is usually characterized as a function of storm translation speed (Uh), radius of maximum winds (Rmax), surface wind stress at 10-m level (tmax), OML depth (h), and the strength of the seasonal thermocline either by reduced gravity (g0 ¼ g(r2 – r1)/r2 where r1 is the density of the upper layer of depth h1, and r2 is the density in the lower layer of depth h2 where r24r1) or buoyancy frequency (see Table 1). The latitude of the storm sets the local planetary vorticity through the local Coriolis parameter (f ¼ 2O sin(j), where O is the angular rotation rate of the Earth (7.29 10 5 s 1), and j is the latitude). The inverse of the local Coriolis parameter (f 1) is a fundamental timescale referred to as the inertial period (IP ¼ 2pf 1). The local IPs decrease poleward, for example, at 101 N, IP B70 h, at 241 N IP B30 h, and at 351 N IP B20 h. The relative importance of this parameter cannot be overemphasized in that at low latitudes such as the eastern Pacific Ocean (EPAC) warm pool, the nearinertial current and shear response will require over a day to develop during hurricane passage. By contrast, at the mid-latitudes, near-inertial motions will develop significant shears across the base of the OML much more quickly. Thus, the initial SST cooling and OML deepening will be minimal at lower latitudes compared to the mid-latitudes for the same oceanic stratification and storm structure.
Measured drag coefficients by various methods
Green squares = profile method (Ocampo-Torres et. al., 1994) Blue asterisks = profile method (Donelan et. al., 2004) Red circles = surface slope (Donelan et. al., 2004) Magenta dots = dissipation (Large and Pond, 1981)
4.5 Drag coeff. referred to 10 m
Air–Sea Parameters
4 3.5 3 2.5
∗
2
∗
∗ ∗
∗
1.5
∗
1
∗
0.5 0
0
5
10 15 20 25 30 35 40 Wind speed extrapolated to height of 10 m, U10 (m s−1)
45
50
Figure 2 Laboratory measurements of the neutral stability drag coefficient (10 3) by profile, eddy correlation (‘Reynolds’), and momentum budget methods. The drag coefficient refers to the wind speed measured at the standard anemometer height of 10 m. The drag coefficient formula of Large and Pond (1981) is also shown along with values from Ocampo-Torres et al. (1994) derived from field measurements. From Donelan MA, Haus BK, Reul N, et al. (2004) On the limiting aerodynamic roughness of the ocean in very strong winds. Geophysical Research Letters 31: L18306, figure 2 (doi: 1029/2004GRL019460).
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
195
Table 1 Air–sea parameters and scales for hurricanes Lili (2002) for both the LC and GOM common water, and Ivan (2004), Katrina (2005), and Rita (2005) over the GOM basin Parameter
Lili (LC)
Lili (GOM)
Ivan
Katrina
Rita
Radius of max. winds Max. wind stress Translational speed Wavelength Mixed layer depth Inertial period Thermocline thickness Barotropic phase speed Barotropic deformation radius Baroclinic phase speed Baroclinic deformation radius
Rmax (km) tmax (N m 2) Uh (m 1 s) L (km) h (m) IP (d) b (m) c0 (m 1 s) a0 (km) c1 (m 1 s) a1 (km)
25 7.1 6.9 770 110 1.3 200 120 2100 1.5 26
18 8.0 7.7 775 35 1.16 200 150 2400 2.8 46
32 6.7 5.5 594 35 1.25 200 72 1002 2.8 40
42 7.6 6.3 608 74 1.12 200 147 2250 2.5 38
19 8.7 4.7 454 70 1.12 200 150 2300 1.9 29
Froude number (Fr)
Uh/c1
2.5
2.8
2.2
2.5
2.5
Note that these parameters are based on where measurements were acquired; for example, Ivan moved over the DeSoto Canyon and over the shelf compared to Lili moving over the eastern side of the Yucatan Shelf, then into the central GOM. Katrina and Rita scales are based on the north-central GOM.
Ocean Structure
An important parameter governing the response is the wave phase speed of the first baroclinic mode due to oceanic density changes between the OML and the thermocline. In a two-layer model, both barotropic and baroclinic modes are permitted. The barotropic (i.e., depth-independent) mode is referred to as the external mode whereas the first baroclinic (depthdependent) mode is the first internal mode associated with vertical changes in the stratification. The phase speed of the first baroclinic mode (c1) is given by c1 2 ¼ g0 h1 h2 =ðh1 þ h2 Þ where the depth of the upper layer is h1, and the depth of the lower layer is h2. In the coastal ocean, phase speeds range from 0.1 to 0.5 m s 1, whereas in the deep ocean, this phase speed ranges between 1 and 3 m s 1 depending on the density contrast between the two layers. The barotropic mode has a phase speed c0 ¼ OgH where H represents the total depth (h1 þ h2), and is typically 100 times larger than the first baroclinic mode phase speed. An important nondimensional number for estimating the expected baroclinic response depends on the Froude number (ratio of the translation speed to the first baroclinic mode phase speed Uhc1 1). If the Froude number is less than unity (i.e., stationary or slowly moving storms), geostrophically balanced currents are generated by the positive wind stress curl causing an upwelling of cooler water induced by upper ocean transport directed away from the storm track (Figure 1). When the hurricane moves faster than the first baroclinic mode
phase speed, the ocean response is predominantly baroclinic associated with upwelling and downwelling of the isotherms and the generation of strong nearinertial motions in a spreading three-dimensional wake. The predominance of a geophysical process also depends upon the deformation radius of the first baroclinic mode (a1 1) defined as the ratio of the first mode phase speed (c1) and f. In the coastal regime, the deformation radius is 5–10 km, but in deeper water, it increases to 20–50 km due to larger phase speeds. For observed scales exceeding the deformation radius, Earth’s rotational effects, through the variations of f, dominate the oceanic dynamics where timescales are equal or greater than IP. Thus the oceanic mixed layer response to hurricanes is characterized as rotating, stratified shear flows forced by winds and waves. Basin-to-basin Variability
Profiles from the background GOM, LC subtropical water, and the tropical EPAC are used to illustrate differences in the buoyancy frequency profile (Figure 3). In an OML, the vertical density gradients (N) are essentially zero because of the vertical uniformity of temperature and salinity. Maximum buoyancy frequency (Nmax) in the Gulf is 12–14 cycles per hour (cph) located between the mixed layer depth (40 m) and the top of the seasonal thermocline compared to c. 5–6 cph in the LC water mass distributed over the upper part of the water column. In the EPAC, however, Nmax B20 cph due to the sharpness of the thermocline and halocline
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS (a)
(b)
0
Depth (m)
100
200
300 EPAC GOM LC
400
500 (c)
0
5
10 15 20 Temperature (°C)
25
30
33
34
(d)
0
35 36 Salinity (psu)
37
Depth (m)
100
200
300
400
500 1020
1022
1024
1026
Density (kg
1028
1030
0
5
m−3 )
10
15
20
25
N (cph)
Figure 3 (a) Temperature (1C), (b) salinity (practical salinity units, psu), (c) density (kg m 3), and (d) buoyancy frequency (N : cycles per hour) profiles from the eastern Pacific Ocean (red) , the GOM common water (green), and the LC water (blue) as measured from airborne expendable ocean profilers. Notice the marked difference between the gradients at the base of the OML between the three profiles.
(pycnocline) located at the base of the OML (i.e., 30 m). Beneath this maximum, buoyancy frequencies (Z3 cph) are concentrated in the seasonal thermocline over an approximate thermocline scale (b) of 200 m and exponentially decay with depth approaching 0.1 cph. In the LC water, Nmax ranges from 4 to 6 cph and remains relatively constant, and below the 20 1C isotherm depth (B250 m), buoyancy frequency decreases exponentially. The Richardson number increases with increases in the buoyancy frequency for a given current shear (s). This implies that a higher shear is needed in a regime like the EPAC to lower the Richardson number to below-critical values for the upper ocean to mix and cool compared to the water mass in the
GOM. Given a large N at lower latitudes (121 N) where the IP is long (B58 h) in the EPAC warm pool, SST cooling and OML deepening will be much less than in the GOM as observed during hurricane Juliette in September 2001 (not shown). Significant SST cooling of more than 5 1C only occurred when Juliette moved northwest where Nmax decreased to B14 cph at higher latitudes. Levels of SST cooling similar to those for the same hurricane in the GOM would be observed in the common water but not in the LC water mass since the 26 1C isotherm depth is 3–4 times deeper. These variations in the stratification represent a paradox for hurricane forecasters and are the rationale underlying the use of satellite radar altimetry in mapping isotherm depths and
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
estimating oceanic heat content (OHC) from surface height anomalies (SHAs) and assimilating them into oceanic models.
the 26 1C isotherm are large. In the LC regime, for example, this isotherm may be deeper than 150 m whereas in the common water the 26 1C isotherm is located at 40 m. The corresponding OHC relative to the 26 1C isotherm is given by
Gulf of Mexico Basin Warm subtropical water is transported poleward by upper-ocean currents from the tropics through the Caribbean Sea and into the GOM (see Figure 1(c)). This subtropical water exits the northwestern Caribbean Sea through the Yucatan Straits where the transport of B24 Sv (1 Sv ¼ 106 m3 s 1) forms the LC core. Given upper ocean currents B1 m s 1 of the LC, horizontal density gradients between this ocean feature and surrounding GOM common water occur over smaller scales due to markedly different temperature and salinity structure (Figure 4). Variations in isotherm depths and OHC values relative to In situ observations
OHC ¼ cp
Derived
26 dz
Temperature (°C), 19.7° N, 85.0° W
0
GDEM3 Climatology WOA01 Climatology Pre-Isidore MODAS Pre-Isidore, measured Pre-Isidore HYCOM-OI Pre-Isidore HYCOM-MODAS
50
20° N
r½TðzÞ
where cp is specific heat at constant pressure, D26 is the 26 1C isotherm depth, and OHC is zero wherever SST is less than 26 1C. Within the context of a twolayer model approach and a ‘hurricane season’ climatology, the 26 1C isotherm depth and its OHC relative to this depth are monitored using satellite techniques by combining SHA fields from satellite altimeters onboard the NASA Jason-1, US Navy Geosat Follow On, and European Research Satellite-2
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Figure 4 OHC (kJ cm 2) in the northwest Caribbean Sea and southeast GOM from an objective analysis of in situ aircraft measurements, satellite altimetry, HYCOM NRL-CH nowcast, and HYCOM NRL-MODAS nowcast (four left panels). Temperature (right top) and salinity (right bottom) vertical profiles at a location in the northwest Caribbean Sea, where red lines are climatological profiles (GDEM3 dashed, WOA01 solid), solid blue lines are observed profiles, dashed blue lines are MODAS profiles, and black lines are model nowcasts (HYCOM-NRL dashed and HYCOM-MODAS solid). Adapted from Halliwell GR, Jr., Shay LK, Jacob SD, Smedstad OM, and Uhlhorn EW (in press) Improving ocean model initialization for coupled tropical cyclone forecast models using GODAE nowcasts. Monthly Weather Review.
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(and Envisat) missions with observed SSTs. In the 1970s, Leipper coined the phrase ‘hurricane heat potential’, which represents integrated thermal structure relative to 26 1C water. In the LC regime, OHC values relative to this isotherm depth often exceed 100 kJ cm 2. For oceanic response studies, the key science issue is that such deep isotherms (and OHC levels) tend to be resistive to significant storm-induced cooling by forced near-inertial current shears across the base of deep OML. Loop Current Cycle
The LC is highly variable and when it penetrates beyond latitudes of 251 N, WCR shedding events occur at periods of 6–11 months when CCRs are located on their periphery prior to separation. By contrast, south of this latitude, WCR shedding periods increase to more than 17 months based on a series of metrics developed by Leben and colleagues. These WCRs, with diameters of approximately 200 km, then propagate west to southwest at average phase speeds of B5 km day 1, and remain in the GOM for several months. At any given time, two or three WCRs may be embedded within the complex GOM circulation patterns. Theoretical developments suggest that the LC cycle can be explained in terms of the momentum imbalance paradox theory. This theory predicts that when a northward-propagating anomalous density current (i.e., Yucatan Current) flows into an open basin (GOM) with a coast on its right (Cuba), the outflow balloons near its source forming a clockwiserotating bulge (e.g., LC) since the outflow cannot balance the along-shelf momentum flux after turning eastward. The ballooning of the current satisfies the momentum flux balance along the northern Cuban coast. The subsequent WCR separation from the LC is due to the planetary vorticity gradients where most of the inflow forces a downstream current and the remaining inflow forms a warm ring. Subtropical water emerging from the Caribbean Sea may enter the LC bulge prior to shedding events and impact the OHC distribution, and if in phase with the height of hurricane season may spell disaster for residents along the GOM. Model Initialization
Ocean models that assimilate data are an effective method for providing initial and boundary conditions in the oceanic component of coupled prediction models. The thermal energy available to intensify and maintain a hurricane depends on both the temperature and thickness of the upper ocean
warm layer. The ocean model must be initialized so that features associated with relatively large or small OHC are in the correct locations and T–S (and density) profiles, along with the OHC, are realistic. Ocean forecast systems based on the hybrid coordinate ocean model (HYCOM) have been evaluated in the northwest Caribbean Sea and GOM for September 2002 prior to hurricanes Isidore and Lili, and in September 2004 prior to Ivan. An examination of the initial analysis prior to Isidore is from an experimental forecast system in the Atlantic basin (Figure 4). This model assimilates altimeter-derived SHAs and SSTs. Comparison of OHC maps by the model and observations demonstrate that the analysis (labeled NRL-CH) reproduces the LC orientation but underestimates values of the heat content. In the Caribbean Sea, the thermal structure (T(z)) hindcast tends to follow the September ocean climatology but does not reproduce the larger observed OHC values. The model ocean is less saline than both climatology and profiler measurements above 250 m and less saline than those between 250 and 500 m. Evaluations of model products are needed prior to coupling to a hurricane model to insure that ocean features are in the correct locations with realistic structure. Mixing Parametrizations
One of the significant effects on the upper ocean heat budget and the heat flux to the atmosphere is the choice of entrainment mixing parametrizations at the OML base (see Figure 1). Sensitivity tests have been conducted using five schemes: K-profile parametrization (KPP); Goddard Institute for Space Studies level-2 closure (GISS); Mellor–Yamada level2.5 turbulence closure scheme (MY); quasi-slab dynamical instability model (Price–Weller–Pinkel dynamical instability model, PWP); and a turbulent balance model (Kraus–Turner turbulence balance model, KT). Simulated OML temperatures for realistic initial conditions suggest similar response except that the magnitude of the cooling differs as well as its lateral extent of the cooling patterns (Figure 5). Three higher-order turbulent mixing schemes (KPP, MY, and GISS) seem to be in agreement with observed SST cooling patterns with a maximum of 4 1C whereas PWP (KT) over- (under-) estimate SST cooling levels after hurricane Gilbert. This case is an example of ‘negative feedback’ to the atmosphere given these cooling levels due primarily to shear instability at the OML base. Similar to the post-season hurricane forecast verifications, more oceanic temperature, current, and salinity measurements must be acquired to evaluate these schemes to build a larger
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS Longitude (W) 96°
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Figure 5 Simulated mixed layer temperatures during hurricane Gilbert for mixing schemes (a) KPP, (b) PWP, (c) KT, (d) MY, and (e) GISS. Differences between these five cases are visible with PWP being the coolest and KT being the warmest. Black line indicates track of the storm at 06 GMT 16 Sep. 1988.
statistical base for the oceanic response to high-wind conditions in establishing error bars for the models.
Oceanic Response Recently observed interactions of severe hurricanes (category 3 or above) with warm ocean features such
as the LC and WCR (Lili in October 2002, Katrina and Rita in August and September 2005) are contrasted with hurricanes that interact with CCR (Ivan in September 04) and cold wakes (Gilbert in September 1988) in the GOM. The levels of observed upper cooling and OML depth patterns are predicated on the amount of shear-induced mixing in the upper ocean (see Figure 1). The SST response is
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
determined from an optimal interpolation scheme using the NASA TRMM microwave imager (TMI) and advanced microwave sensing radiometer (AMSR- E) where the diurnal cycle was removed from the data. LC Interactions
Hurricanes Isidore (21 September 2002) and Lili (02 October 2002) interacted with the LC in nearly the same area spaced about 10 days apart. For negative feedback regimes, one would anticipate that after the first hurricane, there would have been a significant ocean response with little thermal energy available for the second storm as Isidore moved slowly from Cuba to the Yucatan Peninsula. The cyclonic (counterclockwise) rotating surface wind stress (in the Northern Hemisphere) should have upwelled isotherms due to divergent wind-driven transport that may have been balanced by horizontal advection due to strong northward currents through the Yucatan Straits. While observed cooling levels in the straits were less than 1 1C, the upper ocean cooled by (a) 29 Sep. 2002
4.5 1C over the Yucatan Shelf. Since upwelling induced by the persistent trade wind regime maintains a seasonal thermocline close to the surface over this shelf, impulsive wind events force upwelling of colder thermocline water quickly due to transport away from the coast. Isidore remained over the Yucatan Peninsula and weakened to a tropical storm that then moved northward creating a cool wake of B28.5 1C SSTs across the central GOM. Lili reached hurricane status on 26 September while passing over the Caribbean Sea along a similar northwest trajectory as Isidore, making a first landfall along the Cuban coast (Figure 6). As Lili moved into the GOM basin, the storm intensified to a category 4 storm along the LC boundary just as Rmax decreased to form a new eyewall (where winds are a maximum). In the common water, the SST cooling was more than 2 1C due to shear-induced mixing compared to less than 1 1C SST cooling in the LC (Figure 6(c)). This suggests that ‘less negative feedback’ (minimal ocean cooling) to hurricane Lili occurred over the LC than over the common water. Afterward, Lili began a weakening cycle to category
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Figure 6 (a) Pre-Lili, (b) post-Lili, (c) pre–post-Lili SST (1C) field from AVHRR data, courtesy of RSMAS Remote Sensing Laboratory, and (d) measurement grid conducted by NOAA research aircraft on 2 Oct. 2002 (open symbols represent nonfunction probes). Panel (c) is relative to the track and intensity of Lili and the position of the LC. Notice the cold wake in the GOM common water compared to essentially no cold wake in the LC. More details of the response in the LC is given in Figure 9. Black box represents the region where in situ measurements from aircraft expendable were acquired during Lili’s passage.
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
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suggestive of ‘less negative feedback’ to the storm as it crossed over the Yucatan Straits. Given the 10-day time interval between Isidore and Lili, pre-Lili SSTs warmed to over 29 1C in the experimental domain. After Lili’s passage, SSTs decreased to 28.5 1C in the LC; however, along the northern extremity of the measurement domain, SSTs cooled to 27 1C in the Gulf of Mexico common water (GCW), which equates to more than 2 1C cooling. The GCW mixes quickly due to current shears across the OML base forcing the layer to deepen. In the LC itself, there was little evidence of cooling and layer deepening. Given the advective timescale (LV 1 where L is cross-stream scale and V is the maximum current of the LC) of about a day, heat transport from the Caribbean Sea occurs rapidly and will offset temperature decreases induced by upwelling of the isotherms and mixing as in the hurricane Isidore case. The observed current shears during the hurricane were 1.5 10 2 s 1 or about a factor of 2–3 less
80
1 status due to enhanced atmospheric shear, dry-air intrusion along the western edge, and interacting with the shelf water cooled by Isidore. As shown in Figure 6(d), oceanic and atmospheric profilers were deployed in the south-central part of the GOM from research aircraft. The design strategy was to measure upper-ocean response to a propagating and mature hurricane over the LC. Multiple research flights deployed profilers in the same location before, during, and after passage, which captured not only the LC response to Lili but also to Isidore as the hurricane intensified to category 3 status moving across the Yucatan Straits 10 days early. The minimal LC response highlights the importance of this current system for intensity changes. These profiler data were objectively analyzed over a 31 31 domain in latitude and longitude with a vertical penetration to 750-m depth and aligned with the hurricane path (Figure 7). A day after Isidore, SSTs that remained were above 28 1C, which is
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Figure 7 Objective analysis of SSTs (1C) and MLDs (m). Left columns are SSTs and DSSTs and right columns show MLDs and DMLDs for pre-storm, storm, and post-storm (Wake 1) measurements from Lili in the southeastern GOM as per Figure 6(c). Panels are in storm-coordinate system for cross-track (X/Rmax) and along-track (Y/Rmax) based on Rmax and the storm track orientation at 292 1 T North as in Figure 6(c) centered at 23.21 N and 86.11 W. The DSST (1C) and DMLD (m) are estimated by subtracting the prestorm data from the storm and post-storm data and the arrows represent current measurements from airborne expendable current profilers. Blue shaded areas are more than 2 1C consistent with satellite-derived SSTs in Figure 6(c).
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
than observed previously in quiescent regimes due to the strength of this background upper ocean flow of the LC. This lack of shear-induced mixing has implications for hurricane intensity as they move over the deep, warm pools of the LC, which represent a reservoir of thermal energy for hurricanes to tap. Cold and Warm Core Ring Interactions
Hurricane Ivan (Sep. 04) entered the GOM as a category 5 storm and then weakened to a category 4 storm due to a combination of lower OHC, vertical shear in the atmosphere associated with an upperlevel trough, and drier air being drawn into its circulation. During its GOM trajectory, Ivan encountered two CCRs and a WCR where the surface pressure decreased by B10 mb during a brief encounter. Shelf water, cooled by hurricane Frances (10 days earlier) along the northern GOM along with increasing atmospheric shear, acted to oppose intensification during an eyewall replacement cycle (defined as the formation of a secondary eyewall that replaces a collapsing inner eyewall). As shown in Figure 8, pre- and post-SSTs to Ivan reveal the location of both WCR and CCR located
along the track of hurricane Ivan and the cold wake due to enhanced current shear instability. The SST difference field, shown in Figure 8(c), indicates that both the WCR and CCR SSTs are eroded away by the strong forcing. The SSTs over the CCRs indicate cooling levels exceeding 4 1C along and to the right of Ivan’s track that were embedded within the cool wake of about 3.5 1C of Ivan. The northern CCR may have been partially responsible for the observed weakening of Ivan as suggested by Walker and colleagues. Notice that just as in the case of Lili, SST cooling of less than 1 1C was observed in the LC in the southern part of the basin. Prior to landfall, Ivan moved over 14 acoustic Doppler current profiler (ADCP) moorings that were deployed as part of the Slope to Shelf Energetics and Exchange Dynamics (SEED) project (Figure 8(d)), as discussed by Teague and colleagues. These profiler measurements provided the evolution of the current (and shear) structure from the deep ocean across the shelf break and over the continental shelf. The current shear response, estimated over 4-m vertical scales, is shown in Figure 9 based on objectively analyzed data from these moorings. Over the shelf, the current shears increased due to hurricane Ivan strong
(a) 11 Sep. 2004
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Figure 8 Same as Figure 6 except for hurricane Ivan in Sep. 2004 and panel (d) represents ADCP mooring locations during the SEED experiment in the northern GOM in the white box in panel (c).
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
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Figure 9 Spatial evolution of the rotated current shear magnitude normalized by observed shears from the ADCP measurements (white dots) normalized by observed shears in the LC of 1.5 10 2 s 1 (color) during Lili starting at 2100 GMT 15 Sep. every 6 h. Black contours (25-m intervals) represent the depth of the maximum shears based on the current profiles from the moored ADCP. Cross-track (x) and along-track (y) are normalized by the observed Rmax of 32 km. These ADCP data were provided by the Naval Research Laboratory through their SEED project
winds. The normalized shear magnitude over the shelf (depths of 100 m) is larger by a factor of 4 compared to normalized values over the deeper part of the mooring array (500–1000 m). Notice that the current shear rotates anticyclonically (clockwise) in time over 6-h intervals associated with the forced near-inertial response (periods slightly shorter than the local inertial period). In this measurement domain, the local inertial period is close to 24 h which is close to the diurnal tide. By removing the relatively weak tidal currents and digitally filtering the records, the analysis revealed that the predominant response was due to
forced near-inertial motions. These motions have a characteristic timescale for the phase of each mode to separate from the wind-forced OML current response when the wind stress scale (2Rmax) exceeds the deformation radius associated with the first baroclinic mode (B40 km). This timescale increases with the number of baroclinic modes due to decreasing phase speeds. The resultant vertical energy propagation from the OML response is associated with the predominance of the anticyclonic (clockwise) rotating energy with depth and time that is about 4 times larger than the cyclonic (counterclockwise) rotating component.
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the LC and rapidly intensified to similar intensity as Katrina. After Rita interacted with the eastern tip of the WCR, the hurricane began a weakening cycle due to the cooler water associated with a CCR located on the periphery of the WCR similar to Ivan and cooler water on the shelf. Pre- and post-SST analyses include an interval a few days prior and subsequent to hurricane passage to quantify cooling levels in the oceanic response (Figure 11). Prior to Katrina, SSTs exceeded 31 1C in the GOM without any clear evidence of the LC. Subsequent to Katrina, maximum cooling occurred on the right side of the track with SST decreasing to about 28 1C over the outer West Florida Shelf where OML typically lies close to the surface. Observed SSTs decreased by more than 4 1C along the LC’s periphery, mainly due to shear-induced mixing and upwelling over the shelf. As Katrina moved over the LC, the SST response was less than 2 1C as expected
In 2005, hurricane Katrina deepened to a category 5 storm over the LC’s western flank with an estimated wind stress of B7 N m 2. The variations of Katrina’s intensity correspond well with the large OHC values in the LC and the lobe-like structure (eventually a WCR) in the northern GOM. Since SSTs exceeding 30 1C were nearly uniformly distributed in this regime, the LC structure was not apparent in the SST signals. This deeper heat reservoir of the LC provided more heat for the hurricane where satellite-inferred OHC values exceeded 120 kJ cm 2 or more than 5 times the threshold suggested by early studies to sustain a hurricane. Within the next 2 weeks, Rita formed and moved through the Florida Straits into the GOM basin (Figure 10(c)). While Rita’s path did not exactly follow Katrina’s trajectory in the south-central Gulf, Rita moved toward the north-northwest over (a)
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Figure 10 Left panels (a, c) represent pre-storm OHC (kJ cm : color) and 26 1C isotherm depth (m: black contour) based on a hurricane season climatology, SSTs, Jason-1, and GEOSAT Follow-on (GFO) radar altimetry measurements relative to the track and intensity of hurricane Katrina (a, b) and Rita (c, d).
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS (a) 25 Aug. 2005
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Figure 11 Same as Figure 6 except for the hurricane Katrina case where SST were from optimally interpolated TMI data from http:// www.remss.com. Panel (d) represents sampling pattern from aircraft centered on the WCR on 15 September 2005.
over the deeper subtropical water, consistent with the weaker LC response to Lili. These deeper warm pools tend to resist the development of strong shear-induced mixing episodes. Similarly, pre-Rita SSTs ranged from 28.5 to 29 1C over most of the GOM except for the shelf waters cooled by Katrina. However, after Rita’s passage, the dramatic SSTs cooling of 3–4 1C occurred because of the combination of upwelling and cold water advection associated with a CCR that moved between the WCR and the LC. This scenario was analogous to the Ivan case with the CCRs embedded in the cold wake. To illustrate this effect, oceanic profiler measurements were acquired on 15 and 26 September 2005 in a pattern centered on the LC and the lobe-like structure that eventually became the WCR. The earlier research flight was originally conceived as a post-Katrina experiment in an area where it rapidly intensified over the LC and WCR complex to assess altimeter-derived estimates of isotherm depths and OHC variations. Pairs of profilers, deployed in the
center of this WCR structure, confirmed similar depths of the OML of 75 m where the 26 1C isotherm was located at about 120 m. Hurricane Rita’s trajectory clipped the northeastern part of this warm structure as the storm was weakening prior to landfall on the Texas–Louisiana border. While the OHC levels remained relatively the same in this area between pre- and post-Rita (Figure 12), the dramatic cooling between the LC and shed WCR on 26 September was primarily due to the advection of a CCR moving between these ocean features. In addition to upwelling, vertical mixing cooled the ocean as suggested by the vertical sections (Figures 12(c) and 12(d)). Over this period, the WCR propagated westward at a translation speed of 12 km day 1, or nearly double their speeds. Within the WCR, the 26 1C isotherm depth decreased from a maximum depth of 115 m to B88 m. An important research question emerging from the profiler analysis is whether the strong winds associated with Rita forced the WCR to separate prematurely and propagate faster toward the west.
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Figure 12 (a) Pre-Rita and (b) post-Rita analysis of observed (color) and satellite-inferred (contours) of OHC (kJ cm 2) relative to Rita’s intensity (colored circles) and track and corresponding OHC (kJ cm 2: top panels) and vertical thermal structure sections (1C) along 26.51 N transect from (c) pre-Rita and (d) post-Rita.
Summary Progress has been made in understanding the basic oceanic and atmospheric processes that occur during hurricane passage. There is a continuing need to isolate fundamental physical processes involved in these interactions through focused experimental, empirical, theoretical, and numerical approaches. The GOM is one such basin where detailed process studies can focus on the oceanic response to the hurricane forcing as well as the atmospheric response to ocean forcing. Observational evidence is mounting that the warm and cold core features and the LC system are important to the coupled response during hurricane passage. This is not unique to the GOM as this behavior has also been recently observed in other regions such as the western Pacific Ocean and the Bay of Bengal. Thus, it is a global problem that needs to be addressed.
This coupled variability occurs over the storm scales that include fundamental length scales such as the radius of maximum winds and radius to galeforce winds. The fundamental science questions are that how the ocean and atmosphere are coupled, and that what are the appropriate timescales of this interaction? These questions are not easily answered, given especially the lack of coupled measurements spanning the spectrum of hurricane parameters such as strength, radius, and speed. One school of thought is that the only important process with respect to the ocean is under the eyewall where ocean cooling occurs. However, observed cooling under the eyewall is not just due to the surface flux alone (see Figure 1). In this regime, the maximum winds and heat and moisture fluxes occur; however, the broad surface circulation over the ocean also has nonzero fluxes that contribute the thermal
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
energy buildup toward the eyewall of a hurricane. The importance of stress-induced mixing and current shear instabilities in surface cooling and deepening of the surface mixed layer cannot be overstated. The deeper this layer (and 26 1C isotherm depth), the more is the heat available to the storm through the heat and moisture fluxes. Notwithstanding, it is not just the magnitude of the OHC, since the depth of the warm water is important to sustaining these surface fluxes. Future research needs to focus on these multiple scale aspects associated with the atmospheric response to ocean forcing (minimal negative feedback) and to continue studies of the
oceanic response to hurricanes over a spectrum of oceanic conditions. High-quality ocean measurements are central to addressing these questions and improving coupled models. For the first time, a strong near-inertial current response was observed by newly developed Electromagnetic Autonomous Profiling Explorer (EMAPEX) floats deployed in front of hurricane Frances (2004) by Sanford and colleagues (Figure 13). These profiling floats have provided the evolving near-inertial, internal wave radiation in unprecedented detail that includes not only the temperature and salinity (and thus density), but also the horizontal current 1.5
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Figure 13 Current (U, V in m s 1), salinity (psu), and density or st (kg m 3) response at Rmax during the passage of hurricane Frances (2004) as measured by an EM-APEX float deployed from USAF WC-130 1 day ahead of the storm. Three floats were successfully deployed in the projected cross-track direction as part of the ONR Coupled Boundary Layer Air–Sea Transfer program. Reprinted from Sanford TB, Dunlap JH, Carlson JA, Webb DC, and Girton JB (2005) Autonomous velocity and density profiler: EMAPEX. In: Proceedings of the IEEE/OES 8th Working Conference on Current Measurement Technology, IEEE Cat No. 05CH37650, pp. 152–156 (ISBN: 0-7803-8989-1), @ 2005 IEEE.
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structure. Notice that the phase propagation of the forced near-inertial currents is upward associated with downward energy propagation from the OML as current vectors rotate anticyclonically (clockwise) with time and depth (in the Northern Hemisphere). Velocity shears associated with these near-inertial currents force mixing events as manifested in a large fraction of the observed SST cooling of more than 2 1C (and layer deepening). Given these measurements of the basic state variables, the evolution of the Richardson numbers forced by a hurricane can be determined to evaluate mixing parametrization schemes used in coupled models for forecasting at the national centers. The variability of the surface drag coefficient has received considerable attention over the last 5 years. Several treatments have concluded that there is a leveling off or a saturation value at B3073 m s 1. The ratio of the enthalpy (heat and moisture) coefficient and the drag coefficient is central to air–sea fluxes impacting the hurricane boundary layer. In this context, the relationship between the coupled processes such as wave breaking and the generation of sea spray and how this is linked to localized air–sea
fluxes remains a fertile research area. A key element of this topic is the atmospheric response to the oceanic forcing where there seem to be contrasting viewpoints. One argument is that the air–sea interactions are occurring over surface wave (wind-wave) time and space scales and cause significant intensity changes by more than a category due to very large surface drag coefficients. While, these sub-mesoscale phenomena may affect air–sea fluxes, the first-order balances are primarily between the atmospheric and oceanic mixed layers. The forced surface waves modulate the heat and momentum fluxes. Future Research
A promising avenue of research has focused on the upper ocean’s role on intensity change. Climatologically, for the western Atlantic basin, the expected number of category 5 storms is one approximately every 3 years. Over the last 4 years, there have been a total of six category 5 storms, well above this mean. Based on extensive deliberations by the international tropical cyclone community, intensity and structure changes are primarily due to environmental
32° N
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Figure 14 LC/WCR complex based on satellite-derived 26 1C isotherm depth (gray area) and generalized westward propagation of the WCR in the GOM (darker gray) based on 2005 altimeter data relative to the storm tracks (red: severe storms) over several decades (legend) based on best track data from the NHC and 200-m contour (black). FC represents the Florida current that flows through the Straits of Florida. TC best tracks were provided by the National Hurricane Center through their website http:// www.nhc.noaa.gov/pastall.shtml.
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UPPER OCEAN STRUCTURE: RESPONSES TO STRONG ATMOSPHERIC FORCING EVENTS
conditions such as atmospheric circulation, internal dynamics, and oceanic circulation processes. Gyrescale ocean circulation redistributes ocean heat throughout the basins primarily through poleward advection and transport along its western boundary. While there is an open scientific question whether the increased frequency of occurrence of severe hurricanes is due to global warming or natural cycle associated with geophysical processes, the severe hurricanes during the 2005 season interacted with the warm Caribbean Current and the LC. As shown here and in recently published papers, the oceanic response over these regimes differs considerably from that observed quiescent regimes. The key issue is the level of observed ocean cooling in these regimes that is considerably less (i.e., ‘less negative feedback’) than compared to other areas where the cooling is more dramatic. Since winds begin to mix the thin ‘skin’ layer of SST well in front of the storm, the surface temperature reflects the temperature of the oceanic mixed layer under high winds. This point is often overlooked in atmospheric models where SSTs are prescribed or weakly coupled to an ocean where the basic state is at rest. As discussed above, intense hurricanes in the GOM may have encountered the LC and WCR during their lifetimes (Figure 14). With the exception of hurricane Allen (1980), which maintained severe status outside the envelope of this oceanic variability, when hurricanes encounter these features, changes in hurricane intensity are often observed even though warm SSTs prevail during summer months over most of the basin. As noted above, during a 7-week period in 2005, Katrina, Rita, and Wilma all rapidly deepened to catagory 5 status in less than 24 h. Lowest central pressures for this unprecedented hurricane trifecta over a 7-week timescale were 896, 892, and 882 mb. Until Wilma, Gilbert in 1988 held the lowest surface pressure record of 888 mb in the basin. With surface winds in excess of 70 m s 1 within 36 h of landfall over the LC and WCR complex, Katrina and Rita had a pronounced impact on the northern GOM coast as well as offshore structures such as oil rigs. If these oceanic conditions had prevailed during the summer of 1969, hurricane Camille, the strongest land-falling hurricane on record in the Atlantic Ocean basin, may have aligned with the axis of this warm current system. Given the natural variability of this deep warm reservoir, such interactions must be explored in more detail for not only the oceanic response, but also the potential feedbacks to the hurricanes where ocean cooling is minimized with respect to the next-generation forecast models.
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Acknowledgments L.K. Shay gratefully acknowledges NSF support and the support of the NOAA Aircraft Operations Center. Mr. Bill Teague provided Ivan current data; and Drs. Mark Donelan, Brian Haus, George Halliwell, S. Daniel Jacob, and Tom Sanford shared material. SSTs were provided by Remote Sensing Systems website (http://www.remss.com), courtesy of Dr. Chelle Gentemann. Benjamin Jaimes, Eric Uhlhorn, and Jodi Brewster also contributed to this article.
See also Breaking Waves and Near-Surface Turbulence. Upper Ocean Mixing Processes. Upper Ocean Time and Space Variability. Upper Ocean Vertical Structure.
Further Reading Chassignet EP, Smith L, Halliwell GR, and Bleck R (2003) North Atlantic simulations with the hybrid coordinate ocean model (HYCOM): Impact of the vertical coordinate choice and resolution, reference density, and thermobaricity. Journal of Physical Oceanography 33: 2504--2526. D’Asaro EA (2003) The ocean boundary layer under hurricane Dennis. Journal of Physical Oceanography 33: 561--579. Donelan MA, Haus BK, Reul N, et al. (2004) On the limiting aerodynamic roughness of the ocean in very strong winds. Geophysical Research Letters 31: L18306 (doi: 1029/2004GRL019460). Gentemann C, Donlon CJ, Stuart-Menteth A, and Wentz F (2003) Diurnal signals in satellite sea surface temperature measurements. Geophysical Research Letters 30(3): 1140--1143. Halliwell GR, Jr., Shay LK, Jacob SD, Smedstad OM, and Uhlhorn EW (in press) Improving ocean model initialization for coupled tropical cyclone forecast models using GODAE nowcasts. Monthly Weather Review. Jacob SD and Shay LK (2003) The role of oceanic mesoscale features on the tropical cyclone-induced mixed layer response. Journal of Physical Oceanography 33: 649--676. Large WG and Pond S (1981) Open ocean momentum flux measurements in moderate to strong wind. Journal of Physical Oceanography 11: 324--336. Leben RR (2005) Altimeter derived Loop Current metrics. In: Sturges W and Lugo-Fernandez A (eds.) Geophysical Monograph, No. 161: Circulation in the Gulf of Mexico: Observations and Models, pp. 181--201. Washington, DC: American Geophysical Union. Lugo-Fernandez A (2007) Is the Loop Current a chaotic oscillator? Journal of Physical Oceanography 37: 1455--1469.
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Nof D (2005) The momentum imbalance paradox revisited. Journal of Physical Oceanography 35: 1928--1939. Ocampo-Torres FJ, Donelan MA, Merzi N, and Jai F (1994) Laboratory measurements of mass transfer of carbon dioxide and water vapour for smooth and rough flow conditions. Tellus 46B: 16--32. Powell MD, Vickery PJ, and Reinhold TA (2003) Reduced drag coefficient for high wind speeds in tropical cyclones. Nature 422: 279--283. Sanford TB, Dunlap JH, Carlson JA, Webb DC, and Girton JB (2005) Autonomous velocity and density profiler: EM-APEX. In: Proceedings of the IEEE/OES 8th Working Conference on Current Measurement Technology, IEEE Cat No. 05CH37650, pp. 152–156 (ISBN: 0-7803-8989-1). Shay LK (2001) Upper ocean structure: Response to strong forcing events. In: Weller RA, Thorpe SA, and Steele J (eds.) Encyclopedia of Ocean Sciences, pp. 3100--3114. London: Academic Press. Shay LK and Uhlhorn EW (2008) Loop Current response to hurricanes Isidore and Lili. Monthly Weather Review 136 (doi: 10.1175/2008MWR2169).
Sturges W and Leben R (2000) Frequency of ring separations from the Loop Current in the Gulf of Mexico: A revised estimate. Journal of Physical Oceanography 30: 1814--1819. Teague WJ, Jarosz E, Carnes MR, Mitchell DA, and Hogan PJ (2006) Low frequency current variability observed at the shelf break in the northern Gulf of Mexico: May–October 2004. Continental Shelf Research 26: 2559--2582 (doi:10.1016/j.csr.2006.08.002). Vukovich FM (2007) Climatology of ocean features in the Gulf of Mexico using satellite remote sensing data. Journal of Physical Oceanography 37: 689--707. Walker N, Leben RR, and Balasubramanian S (2005) Hurricane forced upwelling and chlorophyll a enhancement within cold core cyclones in the Gulf of Mexico. Geophysical Research Letter 32: L18610 (doi: 10. 1029/2005GL023716).
Relevant Website http://www.remss.com – Remote Sensing Systems Home Page.
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UPPER OCEAN TIME AND SPACE VARIABILITY D. L. Rudnick, University of California, San Diego, CA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3114–3120, & 2001, Elsevier Ltd.
The processes discussed below are ordered roughly by increasing time and space scales (Figure 1). Most of the processes are covered in greater detail elsewhere in this volume. It is hoped that this section will provide a convenient introduction to the variability of the upper ocean, and that the reader can proceed to the more in-depth articles as needed.
Introduction
Turbulence and Mixing
The upper ocean is the region of the ocean in direct contact with the atmosphere. Air–sea fluxes of momentum, heat, and fresh water are the primary external forces acting upon the upper ocean (see Heat and Momentum Fluxes at the Sea Surface; Evaporation and Humidity; Wind- and Buoyancy-Forced Upper Ocean). These fluxes impose the temporal and spatial scales of the overlying atmosphere. The internal dynamics of the ocean cause variability at scales distinct from the forcing. This combination of forcing and dynamics creates the tapestry of oceanic phenomena at timescales ranging from minutes to decades and length scales from centimeters to thousands of kilometers. This article is concerned primarily with the physical processes causing time and space variability in the upper ocean. The physical balances to be considered are the conservation of mass, heat, salt, and momentum. Thus, physical phenomena are discussed with special reference to their effects on the temporal and spatial variability of temperature, salinity, density, and velocity. While many other biological, chemical, and optical properties of the ocean are affected by the phenomena outlined below, their discussion is covered by other articles in this volume. The most striking feature often seen in vertical profiles of the upper ocean is the surface mixed layer, a layer that is vertically uniform in temperature, salinity, and horizontal velocity (see Upper Ocean Vertical Structure and Upper Ocean Mean Horizontal Structure). The turbulence that mixes this layer derives its energy from wind and surface cooling. The region immediately below the mixed layer tends to be stratified, and is often called the seasonal thermocline because its stratification varies with the seasons. The seasonal thermocline extends down a few hundred meters to roughly 1000 m. Beneath the seasonal thermocline is the permanent thermocline whose stratification is constant on timescales of at least decades. Here the discussion is concerned with variability of the mixed layer and seasonal thermocline.
The upper ocean is distinguished from the interior of the ocean partly because of the very high levels of turbulence present (see Breaking Waves and NearSurface Turbulence and Upper Ocean Mixing Processes). The smallest scale of motion worthy of note in the ocean is the Kolmogoroff scale, on the order of 1 cm, where energy is dissipated by molecular viscosity. At this scale, the ocean can be considered isotropic; that is, properties vary in the same way regardless of the direction in which they are measured. At much larger scales than the Kolmogoroff scale, the vertical stratification of the ocean becomes important. In the seasonal thermocline, a dominant mechanism for mixing is the Kelvin-Helmholtz instability, in which a vertical shear of horizontal velocity causes the overturn of stratified water (see Internal Waves). The resulting ‘billows’ are observed tobe on the order of 1 m thick and to decay on the order of an hour. A great deal of observational and theoretical work in the last 20 years has been devoted to relating the strength of this mixing to larger (in the order of 10 m) and more easily measurable quantities such as shear and stratification. The resulting Henyey-Gregg parameterization is one of the most fundamentally important achievements of modern oceanography.
Langmuir Circulation and Convection Turbulence in the mixed layer is fundamentally different from that in the seasonal thermocline. Because the mixed layer is nearly unstratified, the largest eddies can be as large as the layer is thick, often about 100 m. These large eddies have come to be called Langmuir cells in honor of Irving Langmuir, the Nobel laureate in chemistry who first described them. Langmuir cells are elongated vortices whose axes are horizontal and oriented nearly parallel to the wind. The cells have radii comparable in size to the mixed layer depth, and can be as long as 1–2 km. Langmuir cells often appear in pairs with opposite
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Tides
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senses of rotation. The cells thus create alternating regions of surface convergence and divergence. The regions of convergence collect material floating on the surface such as oil and seaweed. Langmuir first became aware of these cells after noticing lines of floating seaweed during a crossing of the Atlantic. Langmuir cells are forced by a combination of wind and surface waves, and are established typically within an hour after the wind starts blowing. Langmuir cells disappear quickly after the wind stops. Recent research indicates that Langmuir cells often vacillate in strength on the timescale of roughly 15 minutes. Convection cells forced by surface cooling also cause the mixed layer to be homogenized and to deepen (see Open Ocean Convection). A typical feature in the mixed layer is the daily cycle of stratification, with daytime heating causing nearsurface stratification and nighttime cooling causing convection that destroys this stratification and
deepens the mixed layer. The vertical extent of convection cells corresponds to the depth of the mixed layer (of order 100 m); the cells have an aspect ratio of one so their horizontal and vertical scales are equal. Because solar heating has a large, essentially global, scale the daily heating and cooling of the upper ocean is coherent and predictable over large scales. Horizontal velocity in the mixed layer also varies strongly at a 24 h period, as the daily cycle of stratification affects the depth to which the wind forces currents. The deepest mixed layers in the oceans, at high latitudes, are convectively mixed. Convection cells are thus more effective at deepening the mixed layer than are Langmuir cells.
Internal Waves Just as there are gravity waves on the surface of the ocean, there are gravity waves in the thermocline.
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UPPER OCEAN TIME AND SPACE VARIABILITY
These thermocline gravity waves, modified by the Earth’s rotation, are known as internal waves (see Internal Waves). They exist in a range of frequencies bounded at the lower end by the inertial frequency f and at the upper end by the buoyancy frequency N. A parcel of water given an initial velocity will travel in a circle under the influence of the Coriolis force. The inertial frequency f, twice the local vertical component of the Earth’s rotation vector, is the frequency of rotation around such a circle. The resulting horizontal current is known as an inertial oscillation. The inertial period is 12 h at the poles, 24 h at 301 latitude, and infinite at the equator because local vertical is normal to the Earth’s axis of rotation. The buoyancy frequency N, proportional to the square root of the vertical density gradient, is the frequency of oscillation of a water parcel given a displacement in the vertical. The resulting vertical motion has a frequency of less than one to several cycles per hour in typical ocean stratification. Internal waves oscillate in planes tilted from the horizontal as a function of the frequency between f and N. Internal waves have amplitudes on the order of tens of meters. They may be coherent over vertical scales that approach the depth of the ocean, particularly at high frequencies near N. Lower frequency internal waves, approaching f, have shorter vertical wavelengths often of order 100 m or less. The horizontal wavelength of an internal wave is related to its frequency and vertical wavelength through the internal wave dispersion relation. For a given vertical wavelength, a high frequency internal wave will have shorter horizontal wavelength than a low frequency wave. At the low frequency end of the internal wave spectrum, the near-inertial waves are especially important in the upper ocean. Near-inertial waves are quite ubiquitous because they are so readily excited by wind forcing on the ocean’s surface. In measurements of horizontal current, inertial oscillations are often the most obvious variability because horizontal currents ‘ring’ at the resonant inertial frequency. Just as a bell has a distinctive tone when struck, the ocean has inertial currents when hit, for example, by a storm. Strong inertial currents are one of the indications in the ocean of the recent passage of a hurricane. The radius of an inertial current circle is its speed divided by its rotation rate, U/f. If the current speed is 0.1 ms 1, then for a midlatitude inertial frequency of 10 4 s 1, the radius is 1 km. In the aftermath of a storm, the inertial currents and radii may be nearly an order of magnitude larger. Nearinertial waves are a dominant mechanism for transporting wind-driven momentum downward from the mixed layer to the seasonal thermocline and into the
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interior. Because near-inertial motions have short vertical scales, they dominate the shear spectrum in the ocean. This shear eventually leads to enhanced turbulence and mixing the penetration of inertial shear into the ocean and the geography of shear and mixing are active topics of research. Tides are well known to anyone who has spent at least a day at the beach. The dominant tidal periods are near one day and one-half day. Tides are most obvious to the casual observer of the sea surface, and they are easily seen in records of horizontal current in the open ocean. Internal tides exist as well, for example forced by tidal flow over bumps on the ocean bottom (see Internal Waves). These internal tides, seen as variability in density and velocity at a location, are a form of internal wave and are governed by the same dynamics. Isolated pulses of tidal internal waves, known as ‘solitons,’ are prevalent in certain regions of rough bottom topography, and are a field of current research.
Fronts and Eddies While vertically uniform, the mixed layer can vary in the horizontal on a wide range of scales. We have already discussed Langmuir circulation and convection cells on scales of order 100 m, but there may be horizontal variability on longer scales. Just as there are fronts in the atmosphere, visible for example in the satellite pictures of clouds shown on the evening television news, there are fronts in the ocean. Fronts in the ocean separate regions of warm and cool water, or fresh and salty water. The most obvious fronts in the mixed layer have widths on the order of 10–100 km, and typically persist for weeks. Fronts of this size have currents directed along the front as a result of the geostrophic momentum balance. That is, the Coriolis force balances the pressure gradient due to having water of varying density across the front. The less dense (usually warmer) water is on the right side of the current in the Northern Hemisphere (the sense of the current is the opposite in the Southern Hemisphere). Fronts in the mixed layer are sites of enhanced vertical circulation on the order of tens of meters per day. Strong biological productivity at fronts is attributed to this vertical circulation which brings deeper water rich in nutrients to the surface. Fronts at scales shorter than 10 km also exist in the mixed layer. At these shorter scales, the geostrophic balance may not be expected to hold. Typical fronts at these scales are observed to be warm and salty on one side and cold and fresh on the other such that the density contrast across the front vanishes. Such a
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front is often said to be compensated, since temperature and salinity gradients compensate in their effect on density. The presence of compensated fronts in the mixed layer is consistent with a horizontal mixing that is an increasing function of the horizontal density gradient. That is, small-scale horizontal density fronts do not persist as long as compensated fronts. Because of their small scale, fronts of order 1 km are poorly observed in the ocean, and are a topic of current research. Observed fronts are usually not observed to be perfectly straight, rather they wiggle. The wiggles, or perturbations, often grow to be large in comparison with the width of the front. When the perturbations grow large enough, the front may turn back on itself and a detached eddy is formed. The eddies often have sizes on the order of 10 km, when they are confined in depth to the mixed layer. This length scale is related to the Rossby radius of deformation; at scales larger than the Rossby radius flows tend to be geostrophic. The Rossby radius for the mixed layer is given by: pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi gHDr=r f where g is acceleration due to gravity, H is the depth of the mixed layer, r is the density of the water, and Dr is the change in density across the mixed layer base. For a typical mixed layer, H is 100 m and Dr is 0.2 kg m 3, g is 9.8 m s 2, and r is 1025 kg m 3, so the Rossby radius is about 6 km. Eddies that extend deeper have larger radii, as can be inferred from the formula for the Rossby radius. Large eddies can persist for as long as several months, while smaller eddies are shorter lived. The small-scale mixed layer eddies, a prominent feature in satellite photos of the sea surface, are typically observed to rotate in the counterclockwise direction in the Northern Hemisphere, and clockwise south of the equator. Again, because of their small size, they have been inadequately observed and are a topic of current research.
Wind-forced Currents (see Wind Driven Circulation) One of the oldest theories of ocean circulation is due to V.W. Ekman, who in 1905 suggested a balance between the Coriolis force and the stress due to wind blowing over the ocean surface. The prediction of this theory for a steady wind is a current that spirals to the right (in the Northern Hemisphere) and decays with depth. This spiral structure was not clearly observed in the ocean until the 1980s with the advent
of moorings with modern current meters. Although the details of the stress parameterization used by Ekman were found to be inadequate to describe observations, the general picture of a spiral remains valid to this day. An alternative theoretical construct to explain upper ocean structure is the bulk mixed layer model. Oceanic properties, such as temperature, salinity, and velocity, are assumed to be vertically uniform in the mixed layer, with a region of very strong vertical gradients at the mixed layer base. The mixed layer is then forced by air–sea fluxes of heat, fresh water, and momentum at the surface, and by turbulent fluxes at the base. The bulk mixed layer model has proven remarkably successful at predicting some basic features of the upper ocean, particularly the vertical temperature structure. Interestingly, the disparate conceptual models of the Ekman spiral and the bulk mixed layer can be rationalized. The upper ocean velocity structure is often, but certainly not always, observed to be vertically uniform near the surface with a region of high shear beneath, in accordance with the bulk mixed layer model. On the other hand, long time averages of ocean current tend to have a spiral structure, in qualitative agreement with the Ekman spiral. This is so if the averages are long enough to span many cycles of mixed layer shoaling and deepening, as due to the daily cycle of surface heating. Thus the timeaverage current spiral may be very different from a typical snapshot of a nearly vertically uniform current. The averaged wind-driven spiral extends downward to a depth comparable to, but slightly deeper than, the mixed layer. The shape of the spiral is strongly influenced by higher frequency variability in the stratification, such as the daily cycle in mixed layer depth discussed above. A spiral is observed in response to temporally variable winds, as well as to steady winds. The temporally variable spiral may have a different vertical structure to the steady spiral. In particular, the current spirals to the left with depth in response to a wind that rotates more rapidly than f in a clockwise direction, in contrast to the steady spiral to the right. Regardless of the detailed velocity structure in the upper ocean, the net transport caused by a steady wind is 901 to the right of the wind in the Northern Hemisphere (and to the left in the Southern Hemisphere). This transport (the vertical integral of velocity) is called the Ekman transport. The Ekman transport is proportional to the wind stress and inversely proportional to the inertial frequency. Thus wind of a given strength will cause more transport near the equator than it would closer to the poles.
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UPPER OCEAN TIME AND SPACE VARIABILITY
The spectrum of wind over the midlatitude ocean peaks at periods of a few to several days. These periods correspond to the time required for a typical storm to pass. The wind-driven current and transport is thus prominent at these periods. Atmospheric storms have typical horizontal sizes of a few to several hundred kilometers, and the direct oceanic response to these storms has similar horizontal scales. The prominent large-scale features of the wind field such as the westerlies in midlatitudes and the trade winds in the tropics directly force currents in the upper ocean. These currents have large horizontal length scales that reflect the winds.
Seasonal Cycles Just as the seasons cause well-known changes in weather, the annual cycle is one of the most robust signals in the ocean. Summer brings greater heat flux from the atmosphere to the ocean, and warmer ocean temperatures. As the ocean warms up at the surface, stratification increases and the mixed layer becomes shallower. The heat flux reverses in many locations during the winter and the ocean cools at the surface. The resulting convection causes the mixed layer to deepen; at some high latitude locations the mixed layer can deepen to several hundred meters in the winter. Winter conditions in high and midlatitude mixed layers are very important to the general circulation of the oceans, as it is these waters that penetrate into the thermocline and set properties that persist for decades. Along with cooler temperatures, winter brings typically stormier weather and more wind and precipitation. Wind-driven currents often peak during the winter in midlatitudes, at the same time that salinity decreases in response to the increased precipitation. Seasonal cycles occur over the whole globe in an extremely coherent fashion, because they are driven primarily by the solar heat flux. However, the seasonal cycle can vary at different oceanic locations. For example, the seasonal cycle at the equator is smaller than that at midlatitudes because solar heat flux varies less over the year. The Arabian Sea has a pronounced semi-annual cycle. Cold northerly winds in winter cool the ocean and deepen the mixed layer as typical for midlatitudes. More unusual is a second period of relatively low ocean temperatures and deep mixed layers during the summer south-west monsoon. Wind-driven mixing causes the cooling during the south-west monsoon as cool water is mixed up to the surface. The Arabian Sea monsoon is the classic
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example of a seasonal wind driven by land–sea temperature differences. Monsoons also exist overthe south-west USA and south-east Asia, among others. Additional local seasonal effects may be caused by river outflows and weather patterns influenced by orography.
Climatic Signals The ocean has significant variability at periods longer than 1 year. The most well known recurrent interannual climatic phenomenon is El Nin˜o (see El Nin˜o Southern Oscillation (ENSO)). An El Nin˜o occurs when trade winds reverse at the equator causing upwelling to cease off the coast of South America. The most obvious consequence of an El Nin˜o is dramatically elevated ocean temperatures at the equator. These high temperatures progress poleward from the equator along the coast of the Americas, affecting water properties in large regions of the Pacific. El Nin˜o has been hypothesized to start with anomalous winds in the western equatorial Pacific, eventually having an effect on the global ocean and atmosphere. El Nin˜os occur sporadically every roughly 3–7 years, and are becoming more predictable as observations and models of the phenomenon improve. The reverse phase of El Nin˜o, the so-called La Nina, is remarkable for exceptionally low equatorial temperatures and strong trade winds. Oscillations with periods of a decade and longer also exist in the ocean and atmosphere. Such oscillations are apparent in the ocean as basin-scale variations in sea surface temperature, for example. Salinity and velocity are also likely variable on decadal timescales, although the observational database for these is sparse in comparison with that for temperature. Atmospheric decadal oscillations in temperature and precipitation are well established. Scientists are actively researching whether and how the ocean and atmosphere are coupled on decadal timescales. The basic idea is that the ocean absorbs heat from the atmosphere and stores it for many years because of the ocean’s relatively high heat capacity. This heat may penetrate into the ocean interior and be redistributed by advective processes. The heat may resurface a decade or more later to affect the atmosphere through anomalous heat flux. The coupled ocean–atmosphere process just described is controversial, and the observations to support its existence are inadequate. A major challenge for the immediate future is to obtain the measurements needed to resolve such processes of significance to climate.
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Conclusion
Further Reading
The upper ocean varies on a wide range of temporal and spatial scales. Processes range from mixing occurring on scales of centimeters and minutes to decadal climatic oscillations of entire ocean basins. Fundamental to the ocean is the fact that these processes can rarely be studied in isolation. That is, processes occurring on one scale affect processes on other scales. For example, decadal changes in ocean stratification are strongly affected by turbulent mixing at the smallest scales. Turbulent mixing is modulated by the internal wave field, and internal waves are focused and steered by geostrophic fronts and eddies. The interaction among processes of different scales is likely to receive increasing attention from ocean scientists in the coming years.
See also Breaking Waves and Near-Surface Turbulence. Double-Diffusive Convection. El Nin˜o Southern Oscillation (ENSO). Evaporation and Humidity. Heat and Momentum Fluxes at the Sea Surface. Internal Waves. Open Ocean Convection. Upper Ocean Mean Horizontal Structure. Upper Ocean Mixing Processes. Upper Ocean Vertical Structure. Wind- and Buoyancy-Forced Upper Ocean.
Davis RE, de Szoeke R, Halpern D, and Niiler P (1981) Variability in the upper ocean during MILE. Part I: The heat and momentum balances. Deep-Sea Research 28: 1427--1452. Ekman VW (1905) On the influence of the earth’s rotation on ocean currents. Arkiv Matematik, Astronomi och Fysik 2: 1--52. Eriksen CC, Weller RA, Rudnick DL, Pollard RT, and Regier LA (1991) Ocean frontal variability in the Frontal Air–Sea Interaction Experiment. Journal of Geophysical Research 96: 8569--8591. Gill AE (1982) Atmosphere–Ocean Dynamics. New York: Academic Press. Gregg MC (1989) Scaling turbulent dissipation in the thermocline. Journal of Geophysical Research 94: 9686--9698. Langmuir I (1938) Surface motion of water induced by wind. Science 87: 119--123. Lighthill MJ and Pearce RP (eds.) (1981) Monsoon Dynamics. Cambridge: Cambridge University Press. Munk W (1981) Internal waves and small-scale processes. In: Warren BA and Wunsch C (eds.) Evolution of Physical Oceanography, pp. 264--291. Cambridge, USA: MIT Press. Philander SG (1990) El Nin˜o, La Nin˜a, and the Southern Oscillation. San Diego: Academic Press. Roden GI (1984) Mesoscale oceanic fronts of the North Pacific. Annals of Geophysics 2: 399--410.
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UPPER OCEAN VERTICAL STRUCTURE J. Sprintall, University of California San Diego, La Jolla, CA, USA M. F. Cronin, NOAA Pacific Marine Environmental Laboratory, Seattle, WA, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction The upper ocean connects the surface forcing from winds, heat, and fresh water, with the quiescent deeper ocean where this heat and fresh water are sequestered and released on longer time- and global scales. Classically the surface layer includes both an upper mixed layer that is subject to the direct influence of the atmosphere, and also a highly stratified zone below the mixed layer where vertical property gradients are strong. Although all water within the surface layer has been exposed to the atmosphere at some point in time, water most directly exposed lies within the mixed layer. Thus, the surface layer vertical structure reflects not only immediate changes in response to the surface forcing, but also changes associated with earlier forcing events. These forcing events may have occurred either locally in the region, or remotely at other locations and transferred by ocean currents. This article first defines the major features of the upper ocean vertical structure and discusses what causes and maintains them. We then show numerous examples of the rich variability in the shapes and forms that these vertical structures can assume through variation in the atmospheric forcing.
radiometers. In contrast, in situ sensors generally measure the ‘bulk’ SST over the top few meters of the water column. The cool skin temperature is generally around 0.1–0.5 K cooler than the bulk temperature. As the air–sea fluxes are transported through the molecular layer almost instantaneously, the upper mixed layer can generally be considered to be in direct contact with the atmosphere. For this reason, when defining the depth of the surface layer, the changes in water properties are generally made relative to the bulk SST measurement. The upper mixed layer is the site of active air–sea exchanges. Energy for the mixed layer to change its vertical structure comes from wind mixing or through a surface buoyancy flux. Wind mixing causes vertical turbulence in the upper mixed layer through waves, and by the entrainment of cooler water through the bottom of the mixed layer. Wind forcing also results in advection by upper ocean currents that can change the water properties and thus the vertical structure of the mixed layer. Surface buoyancy forcing is due to heat and fresh water fluxed across the air–sea interface. Cooling and evaporation induce convective mixing and overturning, whereas heating and rainfall cause the mixed layer to restratify in depth and display alternate levels of greater and lesser vertical
Solar radiation
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Major Features of the Upper Ocean Vertical Structure The vertical structure of the upper ocean is primarily defined by the temperature and salinity, which together control the water column’s density structure. Within the ocean surface layer, a number of distinct layers can be distinguished that are formed by different processes over different timescales: the upper mixed layer, the seasonal pycnocline, and the permanent pycnocline (Figure 1). Right at the ocean surface in the top few millimeters, a cool ‘skin’ exists with lowered temperature caused by the combined heat losses from long-wave radiation, sensible and latent heat fluxes. The cool skin is only a few millimeters thick, and is the actual sea surface temperature (SST) measured by airborne infrared
Turbulence Entrainment Depth
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Figure 1 Conceptual diagram of the vertical structure in the surface layer, and the forcing and physics that govern its existence. The depth of the mixed layer, the seasonal pycnocline, and the main pycnocline are indicated.
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property gradients. Thus, if strong enough, the wind and buoyancy fluxes can generate sufficient turbulence so that the upper portion of the surface layer has a thick, homogeneous (low vertical gradient or stratification), well-mixed layer in temperature, salinity, and density. Wind and buoyancy forcing also affect the vertical structure of the velocity or shear (vertical gradient of horizontal velocity) in the upper mixed layer. Upper ocean processes, such as inertial shear, Langmuir circulations, internal gravity waves, and Kelvin–Helmholtz instabilities, that alter the velocity profile in the surface layer are an active area of research, and are more fully discussed in Upper Ocean Mixing Processes. Temporal and spatial variations in the strength and relative contributions of the atmospheric forcing can cause substantial variability in the water properties and thickness of the upper mixed layer. Large temporal variation can occur on daily and seasonal timescales due to changes in the solar radiation. For example, during the daily cycle the sun heats the ocean, causing the upper surface to become increasingly warm and weakly stratified. The ‘classic’ vertically uniform mixed layer, as depicted in Figure 1, may not be present in the upper ocean surface layer. As the sun sets, the surface waters are cooled and sink, generating turbulent convection that causes entrainment of water from below and mixing that produces the vertically well-mixed layer. Similarly, the mixed layer structure can exhibit significant horizontal variations. The large latitudinal differences in solar radiation result in mixed layers that generally increase in depth from the equator to the Poles. Even in the east–west direction, boundary currents and differential surface forcing can result in mixed layers that assume different vertical structures, although generally the annual variations of temperature along any given latitude will be small. Temporal and spatial variability in the vertical structure of the mixed layer, and the physics that govern this variability are covered elsewhere (see Upper Ocean Mean Horizontal Structure, Upper Ocean Time and Space Variability, and Wind- and Buoyancy-Forced Upper Ocean). Separating the upper mixed layer from the deeper ocean is a region typically characterized by substantial vertical gradients in water properties. In temperature, this highly stratified vertical zone is referred to as the thermocline, in salinity it is the halocline, and in density it is the pycnocline. To maintain stability in the water column, lighter (less dense) water must lie above heavier (denser) water. It follows then, that the pycnocline is a region where density increases rapidly with depth. Although the thermocline and the halocline may not always
exactly coincide in their depth range, one or the other property will control the density structure to form the pycnocline. In mid-latitudes during summer, surface heating from the sun can cause a shallow seasonal thermocline (pycnocline) that connects the upper mixed layer to the deeper more permanent thermocline or ‘main pycnocline’ (see Figure 1). Similarly, in the subpolar regions, the seasonal summer inputs of fresh water at the surface through rainfall, rivers, or ice melt can result in a seasonal halocline (pycnocline) separating the fresh surface from the deeper saltier waters. Whereas the seasonal pycnocline disappears every winter, the permanent pycnocline is always present in these areas. The vertical density gradient in the main pycnocline is very strong, and the turbulence within the upper mixed layer induced by the air–sea exchanges of wind and heat cannot overcome the great stability of the main pycnocline to penetrate into the deeper ocean. The stability of the main pycnocline acts as a barrier against turbulent mixing processes, and beneath this depth the water has not had contact with the surface for a very long time. Therefore the main pycnocline marks the depth limit of the upper ocean surface layer. In some polar regions, particularly in the far North and South Atlantic, no permanent thermocline exists. The presence of an isothermal water column suggests that the cold, dense waters are continuously sinking to great depths. No stable permanent pycnocline or thermocline exists as a barrier to the vertical passage of the surface water properties that extend to the bottom. In some cases, such as along the shelf in Antarctica’s Weddell Sea in the South Atlantic, salinity can also play a role in dense water formation. When ice forms from the seawater in this region, it consists primarily of fresh water, and leaves behind a more saline and thus denser surface water that must also sink. The vertical flow of the dense waters in the polar regions is the source of the world’s deep and bottom waters that then slowly mix and spread horizontally via the large-scale thermohaline ocean circulation to fill the deep-ocean basins. In fact, the thermohaline circulation also plays an important role in maintaining the permanent thermocline at a relatively constant depth in the low and middle latitudes. Despite the fact that the pycnocline is extremely stable, it might be assumed that on some long-enough timescale it could be eroded away through mixing of water above and below it. Humboldt recognized early in the nineteenth century that ocean circulation must help maintain the low temperatures of the deeper oceans; the equatorward movement of the cold deep and bottom water masses are continually renewed through
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UPPER OCEAN VERTICAL STRUCTURE
sinking (or ‘convection’) in the polar region. However, it was not until the mid-twentieth century that Stommel suggested that there was also a slow but continual upward movement of this cool water to balance the downward diffusion of heat from the surface. It is this balance, that actually occurs over very small space and timescales that sustains the permanent thermocline observed at middle and low latitudes. Thus, the vertical structure of the upper ocean helps us to understand not only the wind- and thermohaline-forced ocean circulation, but also the response between the coupled air–sea system and the deeper ocean on a global scale.
Definitions Surface Layer Depth
There is no generally accepted definition of the surface layer depth. Conceptually the surface layer includes the mixed layer, where active air–sea exchanges are occurring, plus those waters in the seasonal thermocline that connect the mixed layer and to the permanent thermocline. Note the important detail that the surface layer includes the mixed layer, a fact that has often been blurred in the criteria used to determine their respective depth levels. A satisfactory depth criterion for the surface layer should thus include all the major features of the upper ocean surface layer described above and illustrated in Figure 1. Further, the surface layer depth criterion should be applicable to all geographic regimes, and include those waters that have recently been in contact with the atmosphere, at least on timescales of up to a year. Finally, the definition should preferably be based on readily measurable properties such as temperature, salinity, or density. Ideally then, we could specify the surface layer to be the depth where, for instance, the temperature is equal to the previous winter’s minimum SST. However in practice, this surface layer definition would vary temporally, making it difficult to decipher the year-to-year variability. Oceanographers therefore generally prefer a static criterion, and thus modify the definition to be the depth where the temperature is equal to the coldest SST ever observed using any historical data available at a particular geographic location. This definition is analogous to a local ‘ventilation’ depth: the deepest surface to which recent atmospheric influence has been felt at least over the timescale of the available historical data. The definition suggested for the surface layer is also primarily one-dimensional, involving only the temperature and salinity information from a given location. Lateral advective effects have not been
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included. The roles of velocity and shear, and other three-dimensional processes in the surface layer structure (e.g., Langmuir circulations, internal gravity waves, and Kelvin–Helmholtz instabilities), may on occasion be important. However, their roles are harder to quantify and have not, as yet, been adequately incorporated into a working definition for the depth of the surface layer. Mixed Layer Depth
The mixed layer is the upper portion of the surface layer where active air–sea exchanges generate surface turbulence which causes the water to mix and become vertically uniform in temperature and salinity, and thus density. Very small vertical property gradients can still occur within the mixed layer in response to, for example, adiabatic heating or thermocline erosion. Direct measurements of the upper layer turbulence through dissipation rates provide an accurate and instant measurement of the active ‘mixing’ depth. However, while the technology is improving rapidly, turbulence scales are very small and difficult to detect, and their measurement is not widespread at present. Furthermore, the purpose of defining a mixed layer depth is to obtain more of an integrated measurement of the depth to which surface fluxes have penetrated in the recent past (daily and longer timescales). For this reason, as in the surface layer depth criterion, definitions of the mixed layer depth are most commonly based on temperature, salinity, or density. The mixed layer depth must define the depth of the transition from a homogeneous upper layer to the stratified layer of the pycnocline. Several definitions of the mixed layer depth exist in the literature. One commonly used mixed layer depth criterion determines the depth where a critical temperature or density gradient corresponding to the top of the maximum property gradient (i.e., the thermocline or pycnocline) is exceeded. The critical gradient criteria range between 0.02 and 0.05 1C m 1 in temperature, and 0.005 and 0.015 kg m 3 in density. This criterion may be sensitive to the vertical depth interval over which the gradient is calculated. Another mixed layer depth criterion determines a net temperature or density change from the surface isotherm or isopycnal. Common values used for the net change criterion are 0.2–1 1C in temperature from the surface isotherm, or 0.03–0.125 kg m 3 from the surface isopycnal. Because of the different dynamical processes associated with the molecular skin SST, oceanographers generally prefer the readily determined bulk SST estimate as the surface reference temperature. Ranges of the temperature and density values used in
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Figure 2 Temperature (black line), salinity (blue line), and density (green line) during March 1995 from expendable conductivity– temperature–depth profiles in the Pacific Ocean at (a) 6.91 N, 173.21 W and (b) 61 S, 1661 W. In temperature, mixed layer depth is calculated using criteria of a net temperature change of 0.51 C (crossed box) and 1 1C (circle) from the sea surface; and a temperature gradient criteria of 0.01 1C m1 (small cross). In density, mixed layer depth is determined using criteria of a net density change of 0.125st units from the surface isopycnal (crossed box), a density gradient of 0.01st units m1 (circle), and the thermal expansion method of eqn [1] (cross). Note the barrier layer defined as the difference between the deeper isothermal layer and the shallow density-defined mixed layer in (b).
both mixed layer depth definitions will distinguish weakly stratified regions from unstratified. Another form of the net change criterion used to define the mixed layer depth (mld) takes advantage of the equivalence of temperature and density changes based upon the thermal expansion coefficient (a0 ¼ dTdr/dT, where dT is the net change in temperature from the surface, e.g., 0.2–1 1C, and dr/dT is calculated from the equation of state for seawater using surface temperature and salinity values). This criterion thus determines the depth at which density is greater than the surface density by an amount equivalent to the dT temperature change. In this way, this definition has the advantage of revealing mixed layers where salinity stratification may be important, such as in barrier layers, which are discussed further below. Criteria based on salinity changes, although inherent in the density criterion, are not evident in the literature as typically heat fluxes are large compared to freshwater fluxes, and the gravitational stability of the water column is often controlled by the temperature stratification. In addition, subsurface salinity observations are not as regularly available as temperature. To illustrate the differences between the mixed layer depth criteria, Figure 2(a) shows the mixed
layer depth from an expendable conductivity– temperature–depth (XCTD: see Expendable Sensors) profile, using the net temperature (0.5 1C) and density (0.125 kg m 3) change criteria, the gradient density criterion (0.01 kg m 3), and a net change criterion based on the thermal expansion coefficient with dT ¼ 0.51C. In this particular case, there is little difference between the mixed layer depth determined from any method or property. However, Figure 2(b) shows an XCTD cast from the western Pacific Ocean, and the strong salinity halocline that defines the bottom of the upper mixed layer is only correctly identified using the density-defined criteria. Finally, to illustrate the distinction between the surface layer and the upper mixed layer, Figure 3(a) shows a temperature section of the upper 300 m from Auckland to Seattle during April 1996. The corresponding temperature stratification (i.e., the vertical temperature gradient) is shown in Figure 3(b). The surface layer, determined as the depth of the climatological minimum SST isotherm, and also the mixed layer depth from a 1 1C net temperature change from the surface (i.e., SST – 1 1C) are indicated on both panels. This cross-equatorial north–south section also serves to illustrate the seasonal differences expected in the mixed layer. In the early fall of the Southern
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UPPER OCEAN VERTICAL STRUCTURE
Hemisphere, the net temperature mixed layer depth criterion picks out the top of the remaining seasonal thermocline, as depicted by the increase in temperature stratification in Figure 3(b). The mixed layer depth criterion therefore excludes information about the depth of the prior winter local wind stirring or heat exchange at the air–sea surface that has been successfully captured in the surface layer using the historical minimum SST criterion. In the Northern Hemisphere tropical regions where there is little seasonal cycle, the surface layer and the mixed layer criteria are nearly coincident. The depth of the mixed layer and the surface layer extend down to the main thermocline. Finally, in the early-spring northern latitudes, the mixed layer criterion again mainly picks out the upper layer of increased stratification that was likely caused through early seasonal surface heating. The surface layer definition lies deeper in the water column near the main thermocline, and below a second layer of (a)
Auckland
relatively low stratification (Figure 3(b)). The deeper, weakly stratified region indicates the presence of fossil layers, which are defined in the next section.
Variability in Upper Ocean Vertical Structure Fossil Layers
Fossil layers are nearly isothermal layers that separate the upper well-mixed layer from a deeper wellstratified layer (see Figure 3(b), 31–371 N). The fact that these layers are warmer than the local minimum SST defining the surface layer depth, indicates that they have at some time been subject to local surface forcing. The solar heating and reduced wind stirring of spring can cause the upper layer to become thermally restratified. The newly formed upper mixed layer of light, warm water is separated from the
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older, deeper winter mixed layer by a well-stratified thermocline. The fairly stable waters in this seasonal thermocline may isolate the lower isothermal layer and prevent further modification of its properties, so that this layer retains the water characteristics of its winter formation period and becomes ‘fossilized’. Hence, fossil layers tend to form in regions with significant seasonal heating, a large annual range in wind stress, and deep winter mixed layers. These conditions can be found at the poleward edges of the subtropical gyres. In the northeast Pacific Ocean off California and in the southwest Pacific Ocean near New Zealand, particularly deep and thick fossil layers have been associated with the formation of subtropical mode waters. As with the fossil layers, the mode waters are distinguishable by low vertical gradients in temperature and density, and thus a narrow range or ‘mode’ of property characteristics. The isothermal layer or thermostad of winter water trapped in the fossilized layers may be subducted into the permanent thermocline through the action of Ekman pumping, in response to a curl in the wind field. The mode waters are then transported, retaining their characteristic thermostad, with flow in the subtropical gyre. Not all fossil layers are associated with mode water formation regions. Shallow fossil layers have also been observed where there are strong diurnal cycles, such as in the western equatorial Pacific Ocean. Here, the fossil layers are formed through the same alternating processes of heating/cooling and wind mixing as found in the mode water formation regions. Fossil layers have also been observed around areas of abrupt topography, such as along-island chains, where strong currents are found. In this case, the fossil layers are probably formed by the advection of water with properties different from those found in the upper mixed layer. Barrier Layers
In some regions, the freshwater flux can dominate the mixed-layer thermodynamics. This is evident in the Tropics where heavy precipitation can cause a surfacetrapped freshwater pool that forms a shallower mixed layer within a deeper nearly isothermal layer. The region between the shallower density-defined well-mixed layer and the deeper isothermal layer (Figure 2(b)) is referred to as a salinity-stratified barrier layer. Recent evidence suggests that barrier layers can also be formed through advection of fresh surface water, especially in the equatorial region of the western Pacific. In this region, westerly wind bursts can give rise to surface-intensified freshwater jets
that tilt the zonal salinity gradient into the vertical, generating a shallow halocline above the top of the thermocline. Furthermore, the vertical shear within the mixed layer may become enhanced in response to a depth-dependent pressure gradient setup by the salinity gradient and the trapping of the wind-forced momentum above the salinity barrier layer. This increased shear then leads to further surface intensified advection of freshwater and stratification that can prolong the life of the barrier layer. The barrier layer may have important implications on the heat balance within the surface layer because, as the name suggests, it effectively limits interaction between the ocean mixed layer and the deeper permanent thermocline. Even if under light wind conditions water is entrained from below into the mixed layer, it will have the same temperature as the water in this upper layer. Thus, there is no heat flux through the bottom of the mixed layer and other sinks must come into play to balance the solar warming that is confined to the surface, or more likely, the barrier layer is transient in nature. Inversions
Occasionally temperature stratification within the surface layer can be inverted (i.e., cool water lies above warmer water). The temperature inversion can be maintained in a stable water column since it is density-compensated by a corresponding salinity increase with depth throughout the inversion layer. Inversions are a ubiquitous feature in the vertical structure of the surface layer from the equator to subpolar latitudes, although their shape and formation mechanisms may differ. Inversions that form in response to a change in the seasonal heating at the surface are most commonly found in the subpolar regions. They can form when the relatively warmer surface water of summer is trapped by the cooler, fresher conditions that exist during winter. The vertical structure of the surface layer has a well-mixed upper layer in temperature, salinity, and density, lying above the inversion layer that contains the halocline and subsequent pycnocline (Figure 4(a)). Conversely, during summer, the weak subpolar solar heating can trap the very cold surface waters of winter, sandwiching them between the warmer surface and deeper layers. In this case, the vertical structure of the surface layer consists of a temperature minimum layer below the warm stratified surface layer, and above the relatively warmer deeper layer (Figure 4(b)). The density-defined mixed layer occurs above the temperature minimum. With continual but slow summer heating, the cold water found in this inversion layer slowly mixes with the
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UPPER OCEAN VERTICAL STRUCTURE
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Figure 4 Temperature (black line), salinity (blue line), and density (st, green line) from XCTD casts at (a) 58.21 N, 147.31 W in March 1996, (b) 611 S, 63.91 W in January 1997, (c) 11.91 S, 176.11 W in August 1998, and (d) 33.51 N, 134.61 W in May 1995. Note the presence of temperature inversions at the base of the mixed layer in all casts.
warmer water masses above and below, and erodes away. Inversions can also form through horizontal advection of water with different properties known as water-mass interleaving. For example, in the Tropics
where there may be velocity shear between opposing currents, inversions are typically characterized as small abrupt features (often only meters thick) found at the base of a well-mixed upper layer and at the top of the halocline and pycnocline (Figure 4(c)). Just west of
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San Francisco (130–1401 W), the low temperature and salinity properties of the Subantarctic Water Mass found in the California Current transition toward the higher-salinity water masses formed in the evaporative regime of the mid-subtropical gyre. The interleaving of the various water masses results in inversions that are quite different in structure from those observed in the tropical Pacific or the subpolar regions (Figure 4(d)). The surface layer vertical structure may be further complicated by frequent energetic eddies and meanders that perturb the flow and have their own distinctive water properties. In the transition zone, the inversions can be thick, and occur well within the pycnocline and not at the base of the mixed layer (Figure 4(d)). Typically there may be sharp gradients in temperature and salinity, both horizontally and vertically, that are characteristic of water-mass interleaving from the advective penetrations of the currents and eddies.
Other Properties That Define the Upper Ocean Vertical Structure Other water properties, such as dissolved oxygen and nutrients (e.g., phosphates, silica, and nitrates), can also vary in structure in the upper ocean surface layer. These properties are considered to be nonconservative, that is, their distribution in the water column may change as they are produced or consumed by marine organisms. Thus, although they are of great importance to the marine biology, their value in defining the physical structure of the upper ocean surface layer must be viewed with caution. In addition, until recently these properties were not routinely measured on hydrographic cruises. Nonetheless, the dissolved oxygen saturation of the upper ocean has been a particularly useful property for determining the depth of penetration of air–sea exchanges, and also for tracing water masses. For example, in the far North Pacific Ocean, it has been suggested that the degree of saturation of the dissolved oxygen concentration may be a better indicator than temperature or density for determining the surface-layer depth of convective events. During summer, the upper layer may be restratified in temperature and salinity through local warming or freshening at the surface, or through the horizontal advection of less dense waters. However, these surface processes typically do not erode the high-oxygen saturation signature of the deeper winter convection. Thus the deep high-oxygen saturation level provides a clear record of the depth of convective penetration from the air–sea exchange of the previous winter, and a unique signal for defining the true depth of the surface layer.
Conclusions In its simplest form the vertical structure of the upper surface layer can be characterized as having a nearsurface well-mixed layer, below which there may exist a seasonal thermocline, where temperature changes relatively rapidly, connected to the permanent thermocline or main pycnocline. The vertical structure is primarily defined by stratification in the water properties of temperature, salinity, and density, although in some regions oxygen saturation and nutrient distribution can play an important biochemical role. The vertical structure of the surface layer can be complex and variable. There exist distinct variations in the forms and thickness of the upper-layer structure both in time and in space, through transient variations in the air–sea forcing from winds, heat, and fresh water that cause the turbulent mixing of the upper ocean. Understanding the variation in the upper ocean vertical structure is crucial for understanding the coupled air–sea climate system, and the storage of the heat and fresh water that is ultimately redistributed throughout the world oceans by the general circulation.
See also Air–Sea Gas Exchange. Bottom Water Formation. Deep Convection. Ekman Transport and Pumping. Expendable Sensors. Heat and Momentum Fluxes at the Sea Surface. Ocean Circulation: Meridional Overturning Circulation. Ocean Subduction. Open Ocean Convection. Penetrating Shortwave Radiation. Penetrating Shortwave Radiation. Upper Ocean Heat and Freshwater Budgets. Upper Ocean Mean Horizontal Structure. Upper Ocean Mixing Processes. Upper Ocean Time and Space Variability. Water Types and Water Masses. Windand Buoyancy-Forced Upper Ocean. Wind Driven Circulation.
Further Reading Cronin MF and McPhaden MJ (2002) Barrier layer formation during westerly wind bursts. Journal of Geophysical Research 107 (doi:10.1029/2001JC00 1171). Kraus EB and Businger JA (1994) Oxford Monographs on Geology and Geophysics: Atmosphere–Ocean Interaction, 2nd edn. New York: Oxford University Press. Philips OM (1977) The Dynamics of the Upper Ocean, 2nd edn. London: Cambridge University Press. Reid JL (1982) On the use of dissolved oxygen concentration as an indicator of winter convection. Naval Research Reviews 3: 28--39.
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UPWELLING ECOSYSTEMS R. T. Barber, Duke University Marine Laboratory, Beaufort, NC, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3128–3135, & 2001, Elsevier Ltd.
Introduction An ecosystem is a natural unit in which physical and biological processes interact to organize the flow of energy, mass, and information. The result of this selforganizing activity is that each kind of ecosystem has a characteristic trophic structure and material cycle, some degree of internal homogeneity, objectively definable boundaries, and predictable patterns of seasonality. Oceanic ecosystems are those ecosystems that exist in the open ocean independently of solid substrates; for example, oceanic ecosystems are fundamentally distinct from coral or intertidal ecosystems. Upwelling ecosystems are those that occupy regions of the ocean where there is a persistent upward motion of sea water that transports subsurface water with increased inorganic plant nutrients into the sunlit surface layer. The upwelling water is not only rich in nutrients, but also frequently cooler than the surface water it replaces; this results in a variety of atmospheric changes, such as coastal deserts or arid zones. The increased nutrient supply and favorable light regime of upwelling ecosystems, however, distinguish them from other oceanic ecosystems and generate characteristic food webs that are both quantitatively and qualitatively different from those of other oceanic ecosystems. For persistent upwelling to take place it is necessary for the surface layer to be displaced laterally in a process physical oceanographers call divergence and then for subsurface water to flow upward to replace the displaced water. The physical concept of upwelling is simple in principle but, as with many ocean processes, it becomes surprisingly complex when real examples are studied. To begin with, there are two fundamental kinds of upwelling ecosystems: coastal and oceanic. They differ in the nature of their divergence. In coastal upwelling, the surface layer diverges from the coastline and flows offshore in a shallow layer; subsurface water flows inshore toward the coast, up to the surface layer, then offshore in the surface divergence. In contrast, oceanic upwelling, which occurs in many regions of the ocean, depends on the divergence of one surface layer of water from
another. One such oceanic divergence is created when an increasing gradient in wind strength forces one surface layer to move faster, thereby leaving behind, or diverging from, another surface layer. Major regions of this kind of oceanic upwelling are found in high latitudes in the Subpolar gyres of the Northern Hemisphere and the Antarctic divergence in the Southern Ocean. The food webs of polar upwelling ecosystems are described elsewhere in the Encyclopedia and this article will focus on coastal and equatorial upwelling ecosystems that occur in low and mid-latitude regions of the world’s oceans. The physical boundary organizing oceanic divergence in equatorial upwelling is the Coriolis force, which changes sign at the equator, causing the easterly Trade Winds to force a northward divergence north of the Equator and a southward divergence south of the Equator. Both coastal and equatorial upwelling ecosystems have been well studied in recent years, so they are among the best known of oceanic ecosystems. The physical processes of equatorial upwelling are described elsewhere in the Encyclopedia. This article describes the quantitative and qualitative character of the food webs of coastal upwelling ecosystems, focusing especially on how their physical forces and chemical conditions affect the way food webs pass organic material to higher trophic level organisms such as fish, birds, marine mammals, and humans.
Why are Upwelling Ecosystem Food Webs different? In low- and mid-latitude oceanic systems where there is annual net positive heat flux, warming of the surface layer produces a density barrier, the pycnocline, that prevents subsurface nutrient-rich water from mixing into the sunlit surface layer. The nutrientdepleted condition of these surface waters severely limits their annual quantity of new primary productivity, and the food webs of these stratified oceanic regions have low phytoplankton biomass, as shown especially clearly in satellite images of ocean color. In the high-latitude polar regions where there is annual net negative heat flux, the surface waters cool, become unstable, and mix with the underlying nutrient-rich subsurface waters. The concentration of inorganic nutrients in well-mixed high-latitude waters is high during polar fall, winter, and spring during periods of strong winds, heat loss to the atmosphere, short day length, and low sun angle. But
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during periods of deep convective mixing the phytoplankton population may spend so much time below the euphotic zone that there is no net positive primary production. The primary producers under these conditions are said to be light-limited. Upwelling is a circulation pattern that overrides both the nutrient limitation of stratified low- and mid-latitude waters and the light limitation of highlatitude polar waters. Upwelling ecosystem food webs are different from those of other oceanic ecosystems because (1) optimal conditions of nutrient supply are provided by the upward flow of cool, nutrient-rich subsurface water into the sunlit surface layer and (2) optimal light conditions are provided for maximal photosynthetic production of new organic matter in the divergent horizontal flow of upwelled water as it gains heat from the sun, producing a well-stabilized, stratified surface flow. Optimal nutrient conditions are formally defined as having nutrient [NO3 , PO4 3 , Si(OH)4] concentrations well above those that saturate the phytoplankton cell’s nutrient uptake mechanism; i.e., [N]bKs, where [N] is nutrient concentration in mole units and Ks in one-half the concentration required for nutrient uptake saturation. Optimal light conditions are formally defined as having a level of irradiance, or photon flux density, in the upper waters that exceeds considerably the irradiance required to saturate the photosynthetic capacity of the phytoplankton assemblage; i.e., [E]bKE where [E] is irradiance in mol photons m 2 s 1 in surface waters and KE is irradiance at saturation. In coastal and equatorial upwelling ecosystems, optimal nutrient and light conditions for high primary production are maintained for several months or longer each year, and in low-latitude Trade Wind regions they persist for the entire year; therefore, the annual quantity of new organic matter generated by primary productivity is much higher in upwelling regions than in other oceanic ecosystems that are nutrient- or light-limited or dependent on one or two seasonal pulses of convective mixing.
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Figure 1 Conceptual diagram of the coastal upwelling ecosystem during (A) normal (cool) conditions and (B) El Nin˜o (warm) conditions. (1) is the alongshore wind blowing toward the Equator; (2) is the wind-driven net offshore surface layer, called the Ekman layer, whose direction of flow is 901 to the left of the wind direction in the Southern Hemisphere because of the Coriolis force; (3) is the upwelling that replaces the water moved offshore in (2); (4) is the euphotic zone where productivity is high relative to other oceanic ecosystems and where high-density blooms of large diatoms accumulate; (5) is the downward flux of ungrazed diatoms and other components of the food web, such as macrozooplankton and fish eggs and larvae; (6) is the subsurface (40–80 m) onshore flow of nutrient-rich water (shown in darker shading) that feeds into the upwelling and recycles material and organisms that sink out of the Ekman layer; (7) is the thermocline and nutricline that separate cool, nutrient-rich subsurface water from the surface layer of warm and nutrientdepleted water. This is an original figure designed by RT Barber in 1983.
The Physical Setting Upwelling is a response of the ocean to wind-driven divergence of the surface layer. As the wind begins to blow across the surface of the ocean, a thin surface slab of water (25–50 m thick) is set in motion by friction of the wind (Figure 1). This wind-driven layer or Ekman layer (named for the Swedish oceanographer who in 1905 worked out how wind drives ocean currents), as a result of the Coriolis force, has a net movement 901 to the right (left) of
the wind in the Northern (Southern) Hemisphere. Four of the major coastal upwelling systems are located in the eastern boundary of the ocean basins along the west coasts of the continents where equatorward winds are part of stationary or seasonal mid-ocean high-pressure systems. These four coastal upwelling regions off the west coasts of North America, South America, north-west Africa, and south-west Africa are in the four great eastern
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boundary current systems, the California Current, Peru Current System, Canary Current, and Benguela Current. The fifth major coastal upwelling region is in a western boundary current, the Somali Current, where strong summer monsoon winds blowing along the coast of the Arabian peninsula set in motion a north-east flow that then diverges from the coast due to Coriolis deflection to the right in the Northern Hemisphere. In all five regions winds blow parallel to the coast for a long enough period of time (months) and over a sufficiently large length of coastline to develop a distinct coastal upwelling ecosystem. Coastal upwelling is a mesoscale (10–100 km) physical response to a large-scale coastal wind field. The major zone of upwelling is relatively small, extending offshore only 25–50 km from the coast, and the water upwelling to the surface layer is coming from a relatively shallow depth of 40–80 m or just below the pycnocline. Because of a basin-wide tilt in the east/west direction, the pycnocline in the eastern boundary current regions is shallower than in other regions of the ocean basin, making nutrient-rich subpycnocline water readily available for entrainment into the upwelling circulation.
The Chemical Environment The sine qua non of coastal upwelling is high concentrations of the new inorganic plant nutrients nitrate (NO3 ), phosphate (PO4 3 ), and silicate or silicic acid (Si[OH]4) that are well in excess of the half-saturation concentrations for nutrient uptake. Typical concentrations are as high as 15–20 mmol l 1 of NO3, with the other macronutrients occurring in appropriate proportional concentrations according to the Redfield ratio. The highest nutrient concentrations and lowest water temperatures are inshore in the most recently upwelled water; there is frequently a strong offshore spatial gradient in nutrient concentration, but the spatial domains of the five great coastal upwelling ecosystems vary remarkably. In the Peruvian upwelling near 151S latitude the onshore/ offshore gradients are steep, with nitrate concentrations decreasing from 20 to 2 mmol l 1 in an offshore distance p50 km; in the Somali Current off the coast of Oman the initial inshore concentrations are lower, about 10 mmol l 1, but remain elevated for 500–700 km offshore. The supply of new nutrients advected into the euphotic zone sets up the highly productive character of upwelling ecosystems, but nutrients regenerated or recycled in the euphotic zone are also unusually abundant in coastal upwelling. High-productivity fuels increased heterotrophic consumption by protozoans, crustaceans, and vertebrates, and these consumers,
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along with heterotrophic bacteria, bring about increased regeneration of nutrients. Regeneration of nutrients from particulate organic matter that sinks out of the offshore surface flow and into the subsurface inshore flow results in nutrient ‘trapping’ that maintains elevated nutrient concentrations in bottom waters of the continental shelf. These regenerated nutrients, together with short-term storage of regenerated nutrients in surficial sediments beneath the upwelling circulation, provide a flywheel to the nutrient supply process that dampens variations in the wind-driven vertical transport of new nutrients from deep water. An additional important chemical consequence of trapping by the two-layered partitioning of organic particles in coastal upwelling is the generation of zones of intense oxygen depletion. The great oxygen minimum zones of the four eastern boundary currents and the Somali Current are fueled by enhanced productivity in the narrow coastal upwelling zone. In addition to water column oxygen depletion, shelf and slope sediments under coastal upwelling are frequently anoxic and colonized by large anaerobic bacterial mats. These benthic hypoxic and anoxic zones are two sites of intense denitrification, a microbial process by which nitrate is converted to nitrogen gas. Occasionally, oceanographers have found complete denitrification in a midwater anoxic layer beneath upwelling systems; these processes of benthic and water column denitrification may be a major global feedback mechanism involved in the regulation of fixed, or biologically available, nitrogen. Another important chemical consequence of the reducing conditions generated in anoxic and hypoxic sediments beneath coastal upwelling involves the cycling of iron. Iron is an essential micronutrient for the maintenance of high rates of primary productivity. Studies in the coastal upwelling ecosystem of the California Current System showed that resuspension and dissolution of iron from sediments generated enhanced concentrations of iron in the bottom boundary currents. Subsequent upwelling of this subsurface water during episodes of strong upwelling resulted in elevated iron concentrations in the euphotic layer. Particle sedimentation to anoxic or hypoxic sediments followed by resuspension and dissolution is a positive feedback that enhances the productive potential of coastal upwelling, especially compared to open ocean equatorial upwelling.
A Milestone in Quantifying Food Web Function The basic food webs of upwelling ecosystems differ in both quantity and quality from those of other
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oceanic ecosystems. A milestone in understanding these differences was made by John Ryther, who in 1969 provided a quantitative explanation of why fish yields vary by about 200-fold from the richest coastal upwelling ecosystems to the poorest ocean gyres. Variations in productivity are, of course, well known from terrestrial ecosystems, but on land a lack of water from either aridity in deserts or freezing in polar regions is responsible for the productive poverty of the poorest regions. Understanding why the food web of the benign low-latitude gyre ecosystem was so poor in fish production was much more difficult. Part of the explanation was proposed in 1955 by Sverdrup who stated simply that reduced physical supply of nutrients to the euphotic zone is the reason for the low productivity, biomass, and fish yields of stratified oceanic gyre ecosystems. Ryther amplified this simple physical explanation by considering, along with the physics and chemistry, the biological properties of the food web that lead to fish production. First, Ryther estimated that about half the fish caught in the world are caught in coastal upwelling ecosystems, the smallest of the ocean ecosystems. Why? To begin, Sverdrup was correct: the physical processes of upwelling and subsequent stratification provide optimal nutrients and light to support high primary productivity. However, more is involved. The phytoplankton, especially diatoms, that thrive in coastal upwelling are large – so large that some portion of the diatoms can be eaten directly by fish or other large grazers such as euphausids. This means that in coastal upwelling the food web leading to fish is often very short, involving only one, or at most two, trophic transfers. Ryther estimated that in the Peru upwelling ecosystem half of the diet of the small pelagic clupeid fish such as anchovies is phytoplankton and the other half is composed of crustacean zooplankton such as euphausids. On average, then, the length of the food web from primary producers to fish had 1.5 transfers: large diatoms to anchovies, or large diatoms to euphausids to larger fish such as mackerel. At each ecological transfer, a large portion (80–90%) of the energy of the food is used to support the organism and that portion cannot be passed up the food web. Ryther also noted that in the phytoplankton-rich waters of the spatially small coastal upwelling regions, grazers do not have to work so hard to get food; therefore, the efficiency of transfer through the food web is increased relative to that of a poor environment such as the low-latitude gyre, where grazers have to cover larger distances and filter large volumes of water to get adequate food. Ryther proposed that fish yields are high in the coastal upwelling ecosystem because of
(1) high initial primary productivity, (2) large phytoplankton that can be grazed directly, (3) short food webs with few transfers, and finally, (4) increased efficiency at each transfer. These effects multiply and lead to high yields of fish that are 200 times the yield of gyre ecosystems. These high yields are exploited by seabirds, marine mammals and, of course, humans.
Food Web Structure and Function Coastal upwelling ecosystems are typically dominated by chain-forming and colonial diatoms with individual cell diameters of 5–30 mm. The growth rates of these large cells are surprisingly as fast as those of the much smaller autotrophic pico- and nanoplankton that are the basis of the microbial loop. The larger diatoms are more effective than pico- or nanoplankton at taking up high concentrations of new nutrients; this property, together with their more favorable photosynthesis/respiration ratio, makes diatoms considerably more efficient at new production. New production uses nutrients carried into the system by upwelling, while regenerated production is based on nutrients recycled in the euphotic zone. The f-ratio measures the proportion of new production; f-ratios of coastal upwelling are as high as any in the oceans, with values ranging from 0.3 to 0.8 and 0.5 being a representative value. Primary productivity values in the most productive portion of the upwelling ecosystem range from 1.0 to 6.0 mg C m 2 d 1. Representative inshore values for the California Current System are 1.0–3.0 mg C m 2 d 1; for the Peru Current System 2.0–6.0 mg C m 2 d 1; for the Canary Current 1.0 – 3.0 mg C m 2 d 1; and for the Somali Current 1.0–2.0 mg C m 2 d 1. High f-ratios and high primary productivity indicate that more organic material can be exported via the food web to higher trophic levels such as fish, birds, and marine mammals or exported vertically as particle flux to deep water or sediments. A second element in Ryther’s hypothesis was that large diatoms could be grazed directly by clupeid fishes. Why are the phytoplankton in coastal upwelling large? One explanation comes from a model study of diatom sinking and circulation in the Peruvian upwelling region. Small phytoplankton that sank slowly or maintained themselves in the euphotic zone were consistently carried in the surface Ekman layer to the oligotrophic offshore waters; large diatoms that sank rapidly fell into the subsurface onshore circulation and were carried back into the upwelling cycle (Figure 1A). Large size that confers
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UPWELLING ECOSYSTEMS
fast sinking is an adaptation that keeps diatoms in the highly productive upwelling habitat for several growth cycles. In addition, newly upwelled water contains large numbers of diatom resting spores, indicating that diatoms sink to sediment, remain there in a resting stage, then become resuspended and transported into the euphotic zone by episodes of strong upwelling. Large size confers rapid sinking, which enhances both recirculation and resuspension, but it also makes the large diatoms efficient prey for fish and large zooplankton like euphausids. The biomass of larger phytoplankton such as diatoms is more variable in time and space than the biomass of pico- and nanophytoplankton. The abundance of small phytoplankton is efficiently controlled by their fast-growing protozoan microzooplankton grazers. The micrograzers can grow as rapidly as their prey, so there is no opportunity for uncoupling of prey and predator abundance; picoand nanoplankton, therefore, rarely form blooms. In contrast, diatoms are grazed by larger organisms with longer reproductive cycles, such as clupeid fish with a 1-year cycle or copepods and euphausids with a cycle of 10–40 days or longer. Clearly, the zooplankton or fish cannot reproduce fast enough to keep up their abundance in pace with a diatom bloom; at times, therefore, large diatoms can accumulate in dense blooms with low initial grazing losses. While fish and zooplankton cannot match growth rates with diatoms, they do have mobility and behavior that enable them to find and move into patches of abundant food. In practice, however, coupling of the growth rates of diatoms and their animal grazers frequently breaks down, and when this happens high biomass blooms become evident in the ocean color satellite images in upwelling regions. Phytoplankton cells, especially large cells that are not grazed or consumed by heterotrophic microorganisms, rapidly sink out of the water column when ungrazed biomass accumulates in a dense bloom (Figure 1A). If nutrients are depleted by the high-biomass bloom, phytoplankton lose the ability to regulate their buoyancy and sink rapidly at rates as high as 100 m d 1. Sediments under coastal upwelling ecosystems are characterized by the highest rate of organic deposition found in the ocean. These high deposition rates indicate that the large diatom/ large grazer food path is relatively more important to the throughput of material than the microbial or picophytoplankton/nanophytoplankton/protozoan grazer path. The microbial path is always present in the two-path upwelling food web and it does increase in absolute productivity during increased upwelling; however, the huge increase in biomass and productivity of the large diatom/large grazer food
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path dominates export of new organic material. The large diatom food path does not replace the picophytoplankton/nanophytoplankton path, but it becomes so numerically overwhelming that it appears as though there is a shift in the character of the food web. In coastal upwelling ecosystems there is enough time and space constancy in the physical response that macrozooplankton and shoaling pelagic fish have been able to evolve adaptations that enable them to exploit this rich but small habitat, and these adaptations affect the efficiency of transfer of primary production to higher trophic levels. Zooplankton such as copepods and euphausids have limited ability to swim against onshore–offshore currents, but they have considerable ability to migrate up and down rapidly. Some upwelling zooplankton species have evolved behavior that causes them, when saturated with food in the offshore flow, to migrate down into the onshore flow, which then carries them back into the upwelling circulation for another cycle. Other species remain in the food-rich habitat by having eggs or juvenile life stages that sink into the subsurface onshore flow. The adaptations of macrozooplankton to the physics of upwelling are remarkable examples of how the evolution of upwelling organisms differs from the evolution of organisms of other oceanic ecosystems. Parallel adaptations are present in the shoaling pelagic fish that dominate the fish biomass of coastal upwelling ecosystems. These behavioral adaptations have optimized feeding, reproduction, and growth for the sardines, anchovies, and mackerel that make up the bulk of the fish harvested from coastal upwelling ecosystems.
Climatic Forcing and Food Web Responses Adaptations to the specific upwelling circulation pattern confer great fitness advantage to phytoplankton, zooplankton, fish, birds, and marine mammals when the upwelling pattern is prevalent, but the coastal upwelling ecosystems are buffeted by strong interannual and interdecadal climate variability. The El Nin˜o–Southern Oscillation (ENSO) phenomenon is the best-known example of largescale, climate-driven biological variability. El Nin˜o is defined by the appearance and persistence, for 6–18 months, of anomalously warm water in the coastal and equatorial ocean off Peru and Ecuador. The anomalous ocean conditions of El Nin˜o are accompanied by large reductions of plankton, fish, and sea birds in the normally rich upwelling region. To
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understand how this climate variability causes these large decreases in abundance, consider how El Nin˜o temporarily alters the physical pattern of the upwelling circulation. One discovery of recent decades is that during El Nin˜o events the coastal winds that drive coastal upwelling do not stop entirely (Figure 1B). In fact, coastal winds sometimes intensify during El Nin˜o because of increased thermal differences between land and sea. Therefore, coastal upwelling as a physical process continues, but because the ENSO process has depressed the thermocline and nutricline to a depth below the depth at which water is entrained into the upwelling circulation (40–80 m), the water upwelled is warm and low in nutrients. As a result, during El Nin˜o the upwelling circulation transports only warm, nutrient-depleted water to the surface layer. The physics of upwelling continues, but the chemistry of upwelling stops very dramatically. This conceptual model of El Nin˜o forcing and food web response, shown in Figure 1B, indicates that El Nin˜o affects the upwelling ecosystem by decreasing the nutrients supplied to the euphotic layer, which causes primary production to decrease proportionally. In this manner the supply of nutrients is reduced as El Nin˜o strengthens in intensity, and the decrease in new primary production available to fuel the food web causes proportional reductions in the growth and reproductive success of fish, birds, and marine mammals. Obviously, temperature, nutrients, primary productivity and higher trophic level productivity are tightly linked in coastal upwelling ecosystems, but by far the most dramatic link is the climate variability/fish variability link. That is, the most impressive biological consequence of El Nin˜o is its effect on the abundance and catch of Peruvian anchovy (Engraulis ringens), the basis of the world’s largest single-species fishery. Figure 2 shows the covariation of thermal conditions and anchovy harvest from the 1950s to the present. This relationship is causal in the sense that temperature is a proxy for nutrients, and nutrient decreases (temperature increases) are always accompanied by reduction in the productivity of the food web including the catch of anchovies. Note that the temperature/nutrient variability works in both directions. Each local minimum in catch is associated with a warm anomaly and each local maximum is associated with cool, nutrient-rich conditions. The period of very low catch from 1976 to 1985 is often cited as an example of the destruction of a fishery by overfishing, but Figure 2 indicates that the anchovy stock failed to recover from 1972 and 1976 El Nin˜o events because there was little upwelling of cool, nutrient-rich waters during that decade. The coastal winds were normal
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Annual catch (106 t)
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Figure 2 The association of sea surface temperature (SST) anomaly along the coast of Peru and Ecuador with the annual catch of Peruvian anchovy, showing that each minimum of catch is associated with a period of anomalously warm water. Note that the SST anomaly scale is inverted, with red showing the warm anomalies. The anomaly is calculated from SST in the Peru coastal area (Nin˜o 1) and the eastern equatorial Pacific (Nin˜o 2). Warmer water at the sea surface means that warmer water is being entrained into the upwelling cell because the thermocline has deepened owing to large-scale, basin-wide responses to changes in Trade Winds. The nutricline also deepens, so that the warmer water is also lower in nutrient concentration. Temperature is a proxy in this figure for nutrient concentration. The close association of SST anomaly and anchovy catch suggests that natural thermal and nutrient variability, not overfishing, is the process controlling the interannual variability of this particular fish stock.
or even stronger than normal during this decade, but the increased heat storage in the upper ocean apparently kept the thermocline and nutricline anomalously deep from 1976 to 1985. The extreme variability of anchovy abundance sends shock waves into the global economy, because fishmeal from upwelling ecosystems is a commodity that is necessary for a variety of animal production processes. The social hardship of this climate-driven variability affects many people, but the upwelling ecosystem is not in the least damaged by ENSO variability. The food web has evolved to exploit the productive phase of the ENSO cycle and persist through the unproductive phase. Figure 2 shows that as long as a period of cool, high-nutrient conditions follows the warm event, the coastal upwelling system recovers to its previous high productivity. The climate process that appears to have the potential to alter or disrupt this ecosystem is the lower-frequency, decadal anomaly that prevailed from 1976 to 1985 and again in the mid-1990s. A decadal anomaly that causes relative nutrient poverty appears to have greater long-term food web consequences than short
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periods of extreme nutrient depletion during El Nin˜o events. How is the character of the coastal upwelling ecosystem altered during a strong El Nin˜o? When the group of equatorially and coastally trapped waves excited during onset of an ENSO event forces the nutricline below the depth where upwelling entrains water, the coastal system rapidly develops a typical assemblage of tropical plankton. Dense blooms of diatoms are missing, but the tropical pico- and nanophytoplankton-based food web is healthy and has productivity levels typical of tropical waters. The diversity of phytoplankton, zooplankton, and fish is high – as would be expected in tropical waters. The response of the upwelling food web to climate variability emphasizes the resilience of oceanic ecosystems to strong transient perturbations; their resilience to the effects of persistent change, however, is unknown.
Glossary Antarctic divergence The zone of upwelling driven by the Antarctic Circumpolar Current (ACC). Convective mixing Vertical mixing produced by the increasing density of a fluid in the upper layer, especially during winter in temperate and polar regions. Denitrification A microbial process that takes place under anoxic conditions, converting nitrate to N2 gas. Diatom A taxonomic group of phytoplankton that are nonmotile, have silicon frustules, and are capable of rapid growth. Ecosystem A natural unit in which physical and biological processes interact to organize the flow of energy, mass, and information. Ekman layer The surface layer of the ocean that responds directly to the wind. Euphotic zone The surface layer of the ocean where there is adequate sunlight for net positive photosynthesis. Nutrients Dissolved mineral salts necessary for primary productivity and phytoplankton growth; macronutrients are phosphate, nitrate, and silicate; micronutrients are iron, zinc, manganese, and other trace metals. Oxygen minimum zone A mid-water layer along the eastern boundary regions of the oceans in which oxygen concentrations are significantly reduced relative to the layers above and below it. Phytoplankton Photosynthetic single-called plants or bacteria that drift with ocean currents and are the major primary producers for oceanic food webs; very small phytoplankton are called
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picoplankton and small phytoplankton are called nanoplankton; all of these are o2 mm in diameter. Primary productivity The use of chemical or radiant energy to synthesize new organic matter from inorganic precursors. Pycnocline The layer where density changes most rapidly with depth and separates the surface mixed layer from deeper ocean waters. Southern Ocean The circumpolar ocean in the Southern Hemisphere between the Subtropical Front and the continent of Antarctica. Stratification The formation of distinct layers with different densities (see ‘pycnocline’ above); stratification inhibits mixing or exchange between the nutrient-rich deeper water and the sunlit surface layer. Subpolar gyres Large cyclonic water masses in the Northern Hemisphere between the subtropical front and the polar front. Tropical Pertaining to the regions that, under the influence of the Trade Winds, are permanently stratified. Upwelling Upward vertical movement of water into the surface mixed layer produced by divergence of the surface waters. Zooplankton Animals that float or drift with ocean currents; microzooplankton are protozoan plankton that graze on small phytoplankton; mesozooplankton are crustaceans that graze on larger phytoplankton such as diatoms.
See also Antarctic Circumpolar Current. California and Alaska Currents. Canary and Portugal Currents. Ekman Transport and Pumping. El Nin˜o Southern Oscillation (ENSO). El Nin˜o Southern Oscillation (ENSO) Models. Fisheries and Climate. Iron Fertilization. Microbial Loops. Network Analysis of Food Webs. Nitrogen Cycle. Satellite Remote Sensing: Ocean Color. Ocean Gyre Ecosystems. Pacific Ocean Equatorial Currents. Pelagic Biogeography. Pelagic Fishes. Plankton. Plankton and Climate. Polar Ecosystems. Primary Production Distribution. Primary Production Processes. Redfield Ratio. Small Pelagic Species Fisheries. Somali Current.
Further Reading Bakun A (1990) Global climate change and intensification of coastal ocean upwelling. Science 247: 198--201. Barber RT and Chavez FP (1983) Biological consequences of El Nin˜o. Science 222: 1203--1210.
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UPWELLING ECOSYSTEMS
Barber RT and Smith RL (1981) Coastal upwelling ecosystems. In: Longhurst A (ed.) Analysis of Marine Ecosystems, pp. 31--68. New York: Academic Press. Longhurst A (1998) Ecological Geography of the Sea. San Diego: Academic Press. Pauly D and Christensen V (1995) Primary production required to sustain global fisheries. Nature 374: 255--257. Richards FA (ed.) (1981) Coastal Upwelling. Washington, DC: American Geophysical Union. Ryther JH (1969) Photosynthesis and fish production in the sea. Science 166: 72--76.
Smith RL (1992) Coastal upwelling in the modern ocean. In: Summerhayes CP, Prell WL and Emeis K-C (eds) Upwelling Systems: Evolution Since the Early Miocene, Geological Society Special Publication 64, pp. 9–28. London: The Geological Society. Summerhayes CP, Emeis K-C, Angel MV, Smith RL and Zeitschel B (eds.) Upwelling in the Ocean Modern Processes and Ancient Records. Chichester: Wiley Sverdrup HU (1955) The place of physical oceanography in oceanographic research. Journal of Marine Research 14: 287.
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URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW M. M. R. van der Loeff, Alfred-Wegener-Institut fu¨r Polar und Meereforschung Bremerhaven, Germany Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3135–3145, & 2001, Elsevier Ltd.
Introduction Natural radioactivity provides tracers in a wide range of characteristic timescales and reactivities, which can be used as tools to study the rate of reaction and transport processes in the ocean. Apart from cosmogenic nuclides and the long-lived radioisotope K-40, the natural radioactivity in the ocean is primarily derived from the decay series of three radionuclides that were produced in the period of nucleosynthesis preceding the birth of our solar system: Uranium-238, Thorium-232, and Uranium-235 (a fourth series, including Uranium-233, has already decayed away). The remaining activity of these socalled primordial nuclides in the Earth’s crust, and the range of half-lives and reactivities of the elements in their decay schemes, control the present distribution of U-series nuclides in the ocean.
The Distribution of Radionuclides of the Uranium Thorium Series in the Ocean Distribution of 238U, 235U, 234U, and 232Th (see Uranium-Thorium Series Isotopes in Ocean Profiles)
Uranium is supplied to the ocean by rivers. In sea water it is stabilized by a strong complexation as uranyl carbonate UO2(CO3)4 3 , causing its long residence time in the ocean. U follows closely the distribution of salinity with 238U (in dpm l1) ¼ 0.0704* salinity. (Note: dpm ¼ disintegrations per minute. The SI Unit Bq, 60 dpm ¼ 1 Bq, is not used in the literature on natural radioactivity in the ocean.) Under anoxic conditions, U is reduced from the soluble (VI) to the insoluble (IV) oxidation state and rapidly removed from sea water. Reductive removal occurs especially in sediments underlying high productivity or low-oxygen bottom waters. Locally this may influence the U–salinity relationship. Salinity-corrected U contents have a variation of 3.8% in the world ocean and are about 1% higher in the
Paci c than in the Atlantic Ocean. At lower salinities in estuaries, salinity-corrected U contents are much more variable as a result of removal and release processes and of interaction with organic complexants and colloids. 235 U is chemically equivalent to 238U and occurs with a 235U/238U activity ratio of 0.046. As a result of the preferential mobilization of 234U during chemical weathering, the river supply of 234U activity exceeds the supply of 238U, causing a 234U/238U ratio in the ocean greater than unity. The isotopic composition of uranium in sea water with salinity 35 is shown in Table 1. Like U, 232Th is a component of the Earth’s crust and is present in the lithogenic fraction of every marine sediment. As a result of its high particle reactivity, Th is rapidly removed from the water column. The 232Th activity in the ocean is very low (around 3 105 dpm l1 or 0.1 ng/kg) and its distribution can be compared to that of other particlereactive elements like Al or Fe. Distribution of Isotopes from the Three Decay Series
In all three decay series, isotopes of relatively soluble elements like U, Ra, and Rn, decay to isotopes of highly particle-reactive elements (Th, Pa, Po, Pb), and vice versa (Figure 1), resulting in widely different distributions in the water column (Table 2) (see Uranium-Thorium Series Isotopes in Ocean Pro les). In a closed system, given enough time, all nuclides in a decay series reach secular equilibrium. This means that growth is balanced by decay, and that all intermediate nuclides have the same activity. In a natural open system, however, reaction and transport
Table 1 Average isotopic uranium composition of sea water with salinity 35 Parameter
Value
235
3.238 ng g1 0.0460 1.14470.002
U þ 238U concentration U/238U activity ratio 234 238 U/ U activity ratio Isotope activity 238 U 234 U 235 U
235
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2.46 dpm l1 2.82 dpm l1 0.113 dpm l1
233
234
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
Element Uranium
Uranium-238 series U-238 4.5*109 y
Protactinium Thorium
Pa-234 1.2 min
Th-234 24.1 d
Th-232 series
U-234 245500 y
U-235 7.0*108 y
Th-230 75400 y
Th-232 1.4*1010 y
Ra-226 1600 y
Ra-228 5.75 y
Actinium Radium
U-235 series
Ac-228 6.1 h
Th-228 Th-231 1.91 y 25.5 h Ra-224 3.7 d
Pa-231 32800 y
Th-227 18.7 d
Ac-227 21.8 y Ra-223 11.4 d
Francium Rn-222 3.8 d
Radon Astatine
Po-218 3.1 min
Polonium Bismuth
Pb-214 26.8 min
Lead -decay Z: _ 2 N: _ 4
-decay Z: +1 N: +/_ 0
Po-214 0.00014 s Bi-214 19.9 min
Pb-210 22.3 y
Po-210 138 d Bi-210 5.0 d
Decay series of short-lived nuclides
Pb-206 stable
Pb-208 stable
Symbol of the element Pa-231 32500 y
Mass number
Pb-207 stable Particle reactivity
Half-life
Low Intermediate High
Figure 1 The natural uranium-thorium decay series, colored according to particle reactivity. The arrows represent decay with the changes in atomic number (Z) and number of nucleons (N) indicated. All three series end with a stable lead isotope.
Table 2 List of the elements (with isotopes of half-life t1/241 day) in the U decay series with their scavenging residence time in deep and surface ocean and their estimated particle-water partition coefficient Kd, showing the relative mobility of U, Ra, and Rn Element
Scavenging residence time (years) Deep sea
U Pa Th Ac Ra Rn
Pb Po
Surface ocean 450 000 o1 o1
130 30 decays (430) 1000 decays
50–100 decays (42)
Kd (cm3 g1)
500 1 106 1 107 0.4–2 105
0.2–3 104 gas exchange 0 with atmosphere 2 1 107 0.6 2 107
Disequilibrium: The Basis for Flux Calculations (Figure 2) Mobile Parent with Particle-reactive Daughter (Table 3)
Tracers in this group are produced in the water column and removed on sinking particles, a process called scavenging. They allow us to determine particle transport rates in the ocean. In a simple box model the total daughter activity (AtD) is determined by decay (decay constant l ¼ ln(2)/ t1/2), ingrowth from the parent nuclide (activity Ap, production rate of daughter nuclide PD ¼ lAp) and removal on sinking particles J (Figure 3): dAtD ¼ PD lAtD J ¼lðAP AtD Þ J dt
½1
In steady-state the flux is directly related to the depletion of the daughter with respect to the parent:
cause a separation between parent and daughter nuclides. The resulting disequilibria between parent and daughter nuclide can be used to calculate the rate of the responsible processes.
J ¼ lðAP AtD Þ
½2
and the residence time of the daughter nuclide with respect to scavenging, tsc , is given by the quotient of
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235
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
222Rn
238
U
Rivers: U,Ra
222Rn
228Th
228Ra 232Th 238U
210Pb
234Th
228Ra 234U
228Th
230Th
226Ra
226Ra
222Rn
222Rn
210Po
210Pb
238U
234Th
210Pb 234U
232Th
228Ra
235U
230Th
230Th
226Ra
222Rn
231Pa
210Pb
231Pa
227Ac
Figure 2 Schematic diagram of radioactive decay (horizontal arrows) and typical transport processes in ocean and atmosphere that can be traced by the nuclides described here (vertical arrows). (Adapted with permission from Ernst WG and Morin JG (eds.) 1980 The Environment of the Deep Sea. Englewood Cliffs, NJ: Prentice Hall.)
Table 3
Isotope pairs with mobile parents and particle-reactive daughters
Mother
Daughter
Half-life
Source
Oceanographic applications
234
230Th
75200 y
water column
238
234Th
24.1 d
water column
228
228Th
1.9 y
235
231
32500 y
water column, in deep sea and continental shelf water column
sediment trap calibration, reconstruction of past vertical rain, sediment focusing export production, calibration of shallow sediment trap resuspension budgets, bioturbation scavenging in coastal waters, bioturbation
226
210
210
210
22.3 y 138 d
water column, atmosphere water column
U U Ra U Ra Pb
Pa Pb Po
activity and removal rate: tsc ¼
AtD AtD ¼ J lðAP AtD Þ
½3
Elements in this group are described below. Thorium 230Th is produced at a known rate from U in sea water. The highly reactive element is rapidly adsorbed onto particles and transported 234
boundary scavenging, paleoproductivity, refined sediment trap calibration boundary scavenging, bioturbation scavenging in surface ocean
down in the water column when these particles sink out. As the adsorption is reversible, a steady-state distribution is achieved, in which both particulate and dissolved activities increase linearly with depth (see Uranium-Thorium Series Isotopes in Ocean Pro les). At any depth, disregarding horizontal advection, the vertical flux of 230ThXS (‘xs’ meaning in excess of the activity supported by the parent nuclide, in this case the small amount of 234U on the sinking particles) must equal its production from
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236
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW 234
Parent nuclide Ap
PD =AP
Dissolved + particulate daughter nuclide ADt
ADt Sedimentation J Figure 3 Schematic diagram of the scavenging of a particlereactive daughter nuclide (decay constant l) produced in the water column from a soluble parent. 234
U in the overlying water column (depth z in meters), which amounts to: P230 ¼ l230 A234 z ¼ 9:19 106 ðy1 Þ 2820 ðdpm m3 ÞzðmÞ ¼ 0:0259 z ðdpm m2 y1 Þ
½4
This known, constant 230Th flux, depending only on water depth, is a powerful tool to quantify errors in the determination of rain rates of other components of the particle flux, either by sediment traps or through the accumulation rate of a marine sediment. The collection ef ciency of sediment traps, known to be highly variable and dependent on trap design, turbulence, and flow rates, can be derived from a comparison of the intercepted 230Th flux F230 with the theoretical flux P230 (see below for a re nement of this procedure using 231 Pa). The vertical rain rate Ri of any component i of the particle flux can be derived from the ratio of the concentration Ci to the 230Th activity in the particles A230, using: Ri ¼
Ci P230 A230
½5
In a similar way, the past flux of 230Thxs to the sea floor, 0F230, derived from decay-corrected 230Th activities (0A230) in dated sediment core sections, can be compared to the theoretical rain rate. The ratio C ¼ 0F230/P230, the focusing factor, is used to determine to what extent the sediment core location has been subject to focusing or winnowing during certain geological periods. The preserved vertical rain rate of sediment components corrected for such redistribution effects follows in analogy to eqn [5]: Ri ¼ 0
Ci P230 A230
Th is produced from the decay of 238U in sea water. In the deep ocean, approximately 3% of its activity is on particles and removal is so slow compared with its half-life (24.1 days) that total (dissolved þ particulate) 234Th is in secular equilibrium with 238U. In coastal and productive surface waters, however, scavenging (Figure 3) causes a strong depletion of 234Th (Figure 4). Following eqn [2], the depth-integrated depletion in the surface water yields the export flux of 234Th. If required, the calculation can be re ned to include advection and nonsteady-state situations. The resulting flux of 234 Th out of the surface layer of the ocean is the most suitable way to calibrate shallow sediment traps. The export flux of other constituents, like organic carbon or biogenic silica, can be derived from the export flux of 234Th if the ratio of these constituents to particulate 234Th in the vertical flux is known. This ratio is variable and depends, for example, on particle size, and the uncertainty in the determination of this ratio limits the quality of 234 Th-based estimates of export production from the upper ocean. A very similar situation exists near the seafloor, where resuspended sediment particles scavenge 234Th from the bottom water. The resulting depletion of 234 Th in the benthic nepheloid layer (BNL) is a measure of the intensity of the resuspension-sedimentation cycle on a timescale of weeks. The tracer thus shows whether a nepheloid layer is advected over large distances or sustained by local resuspension. Mass balance requires that the activity removed from surface waters and from the BNL is balanced by excess activities below (i.e. activities in excess of the activities supported by 238U). Excess activities have sometimes been observed in mineralization horizons in the water column below the euphotic zone and are common in the surface sediment. The distribution of excess 234Th in the sediment is used to calculate bioturbation rates on short timescales. The half-life of 1.9 years makes 228Th useful as a tracer for particle flux on a seasonal or interannual timescale. However, due to the highly inhomogeneous distribution of its parent 228Ra, the interpretation is much more complicated than in the case of 234Th, for example. As regards multiple Th isotopes as an in situ coagulometer, it has been shown that Th isotopes in the ocean are in reversible exchange between the particulate and dissolved form (Figure 5) and in steadystate, including radioactive decay we have:
½6
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Apart A
diss
¼
k1 lþk1
½7
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
234Th/238U
0.5
0
237
ratio
1.0 0
0.5
1.0
Depth (m)
0
200
400
7 Nov
9 Dec
600 Figure 4 234Th : 238U ratio before (left) and during (right) a plankton bloom in the Bransfield Strait, Antarctic Peninsula. The left profile in each diagram represents dissolved, the right profile total 234Th activities. More 234Th was adsorbed to particles (shaded) in the bloom. Total 234Th was probably in equilibrium with 238U in November, but became depleted in the surface water in December (hatched) due to particle export. (Adapted from Scavenging and particle ux: seasonal and regional variations in the Southern Ocean (Atlandic sector). Marine Chemistry 35, Rutgers van der Loeff and Berger, 553–567, Copyright (1991) with permission from Elsevier.)
Adsorption Dissolved nuclide Adiss
k1
Particulate nuclide Apart
k _1 Desorption
Protactinium 231Pa is produced from the decay of U in sea water. The behavior of 231 Pa is very similar to that of 230Th, and these two uranium daughters are produced throughout the water column in a constant activity ratio, given by the production rate of 231Pa divided by the production rate of 230Th or A235 l231/A234 l230 ¼ 0:093. The major application of 231Pa lies in the combined use of these two tracers, whose exact production ratio is known. The approximately 10 times lower reactivity of 231Pa allows it to be transported laterally over larger distances than 230Th before being scavenged. The resulting basin-wide fractionation between 231Pa and 230Th is the basis for the use of the 231Pa/230Th ratio as a tracer of productivity. In areas of high particle flux the particles have a 231Pa/230Th ratio 40.093, whereas particles sinking in low productivity gyres have a ratio o0.093. The 231Pa/230Th ratio stored in the sediment, after proper correction for decay since deposition, is a powerful tool for the reconstruction of paleoproductivity. The fractionation between Th and Pa depends on particle composition and has been found to be much lower when opal is abundant. The tracer loses much of its value in a diatom-dominated system like the Southern Ocean. A related application of the 231Pa/230Th ratio is a correction to the 230Th-based calibration of sediment trap ef ciency. The removal of both nuclides from sea water can be divided into a vertically scavenged component (V230; V231) and a component 235
Figure 5 Box model of the reversible exchange between the dissolved and particulate form of a nuclide with adsorption and desorption rate constants k1 and k1.
where Apart and Adiss are the particulate and dissolved activities, k1 is the desorption rate constants. If the distribution of two or more isotopes (usually 234Th and 230Th or 228Th and 234Th) between dissolved and particulate forms is known, k1 and k1 can be calculated. Values for 1/k1 derived for thorium are on the order of a month in bloom situations and 41 year in clear deep water, much longer than expected from adsorption theory. This is explained when thorium adsorbs to colloidal-sized particules and the rate limiting steps, which determine the distribution of the tracers over dissolved and lterable form, are the coagulation and disaggregation with rate constants k2 and k2 respectively (Figure 6). Thus, when aggregation is clearly slower than adsorption (ðk2 5k1 Þ thorium isotopes provide a way to derive particle aggregation rates in situ.
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238
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW Adsorption Parent nuclide
Aggregation
k1
Dissolved daughter nuclide
Small particles/ colloids daughter nuclide
k_1 Desorption
k2
Large particles daughter nuclide
k_2 Disaggregation
Sedimentation J Figure 6 Conceptual model, including the models depicted in Figure 3 and Figure 5, of the processes thought to control scavenging of radionuclides. (Adapted from Seasonality in the ux of natural radionuclides and plutonium in the deep Sargasso Sea. Deep-Sea Research 32, Bacon MP et al., 273–286, Copyright 1985 with permission from Elsevier Science.)
Lead 210Pb (half-life 22.3 years) is produced from Rn, the immediate daughter of 226Ra. 222Rn emanation from land is the major source of 210Pb deposition from the atmosphere (Figure 2). 222Rn emanation from surface sea water accounts for only 2% of 222Rn in the atmosphere, but is a signi cant source in remote areas like the Antarctic Ocean. Below the surface water, seawater 226Ra becomes the most important source. The high particle reactivity makes 210Pb a tracer for particle flux. This is shown most clearly by the good correlation between the fluxes of 210Pb and of biogenic material in sediment traps. Thus, low 210Pb activities (or 210Pb/226Ra ratios) in surface and deep water, high 210Pb fluxes in traps, and high inventories in the sediment all point to high particle fluxes and consequently high productivity. (Note, however, that in hemipelagic sediments in productive ocean areas the redox cycling of Mn can cause additional nearbottom scavenging of Pb.) Due to this removal on biogenic particles, 210Pb shows strong boundary scavenging similar to 231Pa, with accumulation rates in the sediments of productive (especially eastern) ocean boundaries that are far above local production and atmospheric deposition, whereas the flux to deep-sea sediments in oligotrophic central gyre regions can be very low. Consequently, the flux of 210 Pb into and its inventory in surface sediments is highly variable in space. But as long as the (yearly averaged) scavenging conditions do not change with time, the 210Pb flux to the sediment at a certain location can be considered constant, a prerequisite for the interpretation of 210Pb pro les to derive sedimentation and bioturbation rates. Due to the relatively well-known production and input rates of 210Pb, the scavenging residence time tsc 222
P230, P231 Production
H230, H231 Horizontal advection
V230, V231 Vertical flux Figure 7 Box model used to derive the vertical ux of
230
Th.
transported horizontally by eddy mixing or advection (H230; H231) (Figure 7). P230 ¼ V230 þH230
½8
P231 ¼ V231 þH231
½9
The calibration of sediment traps is based on the comparison of the intercepted 230Th flux F230 with the predicted vertical flux V230. In the original 230Thbased calibration procedure (eqn [4]), H230 is neglected and F230 is compared directly to the production rate P230. Since P230 (eqn [4]) and P231 are known and the V230/V231 ratio can be measured as the 230ThXS/231 PaXS ratio in the sediment trap material, it is suf cient to estimate the H230/H231 ratio from water column distributions to solve eqns [8] and [9] for V230 and obtain a re ned estimate of trapping ef ciency.
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URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
can be derived from the distribution of 210Pb in the ocean (compare eqn[3]). tsc was found to increase from about 2 years in the surface ocean to about 35 years in the deep Atlantic and 150 years in the deep Paci c, a result that is used to understand the behavior of stable lead. This illustrates how 210Pb is a useful analog for stable lead, the study of which is complicated by the extreme risk of contamination (see Anthropogenic Trace Elements in the Ocean). Polonium 210Po, the immediate daughter of 210Pb, is highly particle-reactive. The 138-day half-life of 210 Po makes the 210Po/210Pb tracer pair a suitable extension to 234Th as tracer for seasonal particle flux from the surface ocean. The non-homogeneous distribution and reactivity of the parent 210Pb implies that 210Po can only be used if concurrent accurate measurements are made of 210Pb. As a result of the strong af nity for organic material and cytoplasm, 210Po accumulates in the food chain and 210Po/210Pb activity ratios from around 3 in phytoplankton to around 12 in zooplankton have been reported. A high excess 210Po activity is therefore indicative of a pathway including zooplankton. The preference of Po for organic material in comparison with Pb and Th, which may adsorb on any surface, can be exploited to distinguish between the fluxes of organic carbon and other components of the particle flux. Reactive Parent with Mobile Daughter (Table 4)
This type of tracer is used to quantify diffusion, advection, and mixing rates of water masses, for example, the distribution of 222Rn near the seafloor. The parent, 226Ra, has a far higher activity in marine sediments (222Rn emanation rate As226 of order 100 dpm l1 wet sediment) than in the bottom water 1 (Aw 226 of order 0.2 dpm l ). This gradient causes a Table 4
239
diffusion of the daughter 222Rn from the sediment into the water column, and a typical vertical distribution as shown in Figure 8. The distribution of 222Rn, A222, can be described by the diffusion-reaction equation: dA222 d2 A222 ¼ lðA226 A222 Þ þ D dt dz2
½12
where D is the diffusion coef cient. This yields in steady state: pffiffiffiffiffiffiffiffiffi A222 ¼ A226 ðAo222 A226 Þe ðl=DÞ z ½13 A solution valid for the sediment and the water column (if z is de ned positive as the distance to the interface), where Ao222 signi es the 222Rn activity at the interface (Figure 8). In the sediment, this corresponds to an integrated depletion of: rffiffiffiffi D s 0 ½14 Is ¼ ðA226 A222 Þ l maintained by a
222
Rn release rate of: Fs ¼ lIs
½15
In the water column, this flux causes an excess activity which is transported upwards by turbulent diffusion (coef cient K). The integrated 222Rn excess in the bottom water is given by: rffiffiffiffi K 0 w ½16 Iw ¼ ðA222 A226 Þ l maintained by a supply from the sediment Fw ¼ lIw
½17
Note that mass balance requires that Fs ¼ Fw and that the depletion in the sediment equals the excess in the water column (Is ¼ Iw). The example shows how the
Isotope pairs with a particle-reactive parent and a mobile daughter
Mother
Daughter
Half-life
Source
Oceanographic application
231
227
232
228
22 y 5.8 y
deep-sea sediments all terrigenous sediments
230
226
228
224
1600 y 3.6 d
227
223
11.4 d
226
222
3.8 d
deep-sea sediments 232 Th (sediment) 228 Ra (sediment þ water column) 235 U (sediment) 231 Pa (sediment þ water column) (deep-sea) sediments
ocean circulation, upwelling tracing of shelf water sources, mixing in deep-sea and surface water ocean circulation, ground-water inputs mixing in shelf waters and estuaries
Pa Th Th Th
Th
Ra
Ac Ra Ra Ra
Ra
Rn
mixing in shelf waters and estuaries
mixing in bottom water, air–sea gas exchange, ground-water inputs
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240
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
Bottom water
Height
100 m
Rn-222 A226S Iw
A222O Is
Depth
0
A226W
_ 0.1 m
Sediment 0.2
100 _1
A222, A226 (dpm l ) Figure 8 Generalized distribution of 226Ra and 222Rn in surface sediments and bottom water (note change in horizontal and vertical scales). The cumulative 222Rn depletion in the sediment (Is, shaded) is balanced by the 222Rn excess in the bottom water (Iw, hatched). The vertical extent of the disequilibrium is 3 orders of magnitude larger in the water column than in the sediment, corresponding to the 6 orders of magnitude difference in diffusion coefficient (on the order of 10 cm2 s1 in the bottom water as opposed to 105 cm2 s1 in the sediment).
diffusion coef cient in the sediment and the vertical eddy diffusion coef cient in the bottom water can be derived from measurements of the vertical distribution of this tracer using eqn [13]. Elements in this group are described below. Actinium 227Ac is produced by the decay of 231Pa. Over 99% of 231Pa produced in the water column resides in the sediment, with highest speci c activities in slowly accumulating deep-sea sediments. As actinium is relatively mobile, it is released to the pore water and from there to the overlying water, very similar to the behavior of 226 Ra and 228Ra. This results in a strong signal from the deep seafloor on top of a background concentration, which is given by the distribution of 231 Pa in the ocean. The nuclide is therefore a potential tracer for vertical mixing and advection (e.g. upwelling) on a decennium timescale. Radium Radium is relatively mobile and the major source of the isotope 226Ra is the production from the 230Th in the upper layer of sediments. Just like 227Ac, this source is strongest over deep-sea
sediments with a slow accumulation rate. The intermediate reactivity of radium (Table 2) and its half-life (1600 years) in the order of the ocean mixing time (around 1000 years) explain its distribution as a ‘biointermediate’ element: 226Ra activities are low in surface waters but never become depleted. They increase with depth and with the age of water masses in the conveyor-belt circulation to reach highest values in the deep north Paci c around 340 dpm m3. Extensive attempts in the GEOSECS program to use the isotope as a tracer of ocean circulation and water mass age proved unsuccessful as a result of the diffuse nature of the source. Even a normalization with barium, an element that can to a certain extent be regarded as a stable analog of radium, could not suf ciently account for this variation. Ground waters sometimes have high 226Ra activities. The isotope can then be used to trace groundwater inputs to the coastal ocean. 228 Ra is also produced in marine sediments, but in contrast to 226Ra and 227Ac, its parent 232Th is present in the terrigenous fraction of all sediments irrespective of water depth. In combination with the relatively short half-life (5.8 years), this results in a distribution in the open ocean with enhanced concentrations near the seafloor of the deep ocean and near the continental slope, while the activities can accumulate to highest values over extensive continental shelf areas. The vertical distribution in the deep sea (Figure 9) resembles the exponential decay that would be expected in a one-dimensional (1-D) model with the source in the seafloor, vertical mixing, and radioactive decay (eqn [13]). This would allow the tracer to be used to derive the vertical mixing rate in the deep ocean. However, it has been shown that even in a large ocean basin like the north-east Atlantic, horizontal mixing is so strong that the vertical distribution is influenced by inputs from slope sediments, making the 1-D model inadequate. The inputs of shelf waters to the open ocean cause the high activities in the surface waters, illustrated by a typical pro le in Figure 9. This surface water signal has a strong gradient from the continental shelf to the inner ocean, which has been used to derive horizontal eddy diffusion coef cients in a way analogous to eqn [13]. As the distribution of 228Ra has been shown to vary with time, a steady-state distribution can usually not be assumed, and a repeated sampling is required. Moreover, the horizontal distribution is affected by advection and vertical diffusion, making the interpretation rather complicated. The combination of various radium isotopes (see below), can alleviate some of these problems.
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URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
_2
0
0
1.0
228Ra Activity (10 2.0
241
_
dpm kg 1) 3.0
4.0
1
Depth (km)
2
3
4
5
6 Figure 9 Typical 228Ra activity profiles in the water column in the North Atlantic, showing the enrichment near the sea oor and in the surface water. (Adapted with permission from Ivanovich M and Harmon RS (eds) 1992 Uranium-series Disequilibrium, 2nd edn).
In surface current systems away from the continents, 228Ra becomes a powerful tracer for waters that have been in contact with the continental shelf. The 228 Ra enrichment in surface waters in the equatorial Paci c point to shelf sources off New Guinea, from where the isotope is carried eastward in the North Equatorial Counter Current. In this plume, the vertical distribution of the isotope has been used to derive vertical mixing rates. A very high accumulation of 228Ra is observed in the transpolar drift in the central Arctic Ocean, a signal derived from the extensive Siberian shelves. Due to their short half lives, 224Ra (3.4 days) and 223 Ra (11.4 days) are interesting only in the immediate vicinity of their sources. In the open ocean they are close to secular equilibrium with their parents 228 Th and 227Ac, but in coastal waters these tracers
are being developed to study mixing rates. Their distribution is controlled here by sources in the estuary and on the shelf, mixing and decay. Horizontal mixing rates have been obtained from the distribution of 223Ra and 224Ra across the shelf using eqn [13]. As with 228Ra, this procedure is limited to cases where the mixing can be considered to be one-dimensional, but the steady-state requirement is more easily met at these short timescales. The 223Ra/224Ra activity ratio, which decays with a half-life of 5.4 days, yields the age of a water mass since its contact with the source, irrespective of the nature of the mixing process with offshore waters. Radon With its half-life of 3.8 days, the readily soluble gas 222Rn is in secular equilibrium with its parent 226Ra in the interior ocean. At the
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242
URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
Table 5 Summary of the processes that can be investigated using the natural uranium-thorium decay series Processes Particle fluxes Boundary scavenging (Paleo) productivity Export production Scavenging, trace metal behavior Sediment trap efficiencies Aggregation rates of particles and colloids Sediment redistribution in bottom water Resuspension near sea oor Water masses Shelf interaction/horizontal mixing rates Vertical mixing rates Upwelling Ground-water inputs Gas exchange Exchange with atmosphere
Tracers
231
Pa/230Th, 210Pb Pa/230Th, 210Pb 234 Th 234 Th, 230Th, 210Pb, 210 Po 234 Th, 230Th, 231 Pa Joint Th isotopes 231
230
Th
234
210
228
224
223
222
228
227
Th,
Ra,
Rn, Ac 226 Ra,
Pb
Ra, Ra,
Ra Ac
227
222
Rn
222
Rn
boundaries of the ocean, however, inputs from sediments and release to the atmosphere create concentration gradients carrying useful kinetic information. The distribution of excess 222Rn near the seafloor is used to quantify vertical diffusion (see above, Figure 8) and ground-water inputs; the depletion of 222Rn in surface waters has been used to quantify the air–sea gas exchange rate.
Summary The accurate clocks provided by the uranium-thorium decay series enable us to extract rate information from the measurement of radioactive disequilibria in the ocean. Among the wide spectrum of available tracers, a mother–daughter pair with appropriate reactivities and half-lives can be found for a multitude of processes related to particle transport, water mass transport and mixing, and gas exchange (Table 5).
Glossary Adiss dissolved activity AP parent activity Apart particulate activity A222 222Rn activity Ao222 222Rn activity at sediment–water interface
A226 226Ra activity 226 Ra activity in the bottom water Aw 226 s A226 radon emanation rate in sediment A230 230Th activity in the particles A234 activity of 234U 0 A230 decay-corrected 230Th activities A235 235U activity AtD total daughter activity Ci concentration of component i D diffusion coef cient Fs 222Rn release rate Fw 222Rn input rate F230 intercepted 230Th flux 0 F230 past flux of 230Thxs to the seafloor H230 horizontal flux of 230Th H231 horizontal flux of 231Pa Is 222Rn depletion in the sediment Iw 222Rn excess in the bottom water J sedimentaion rate K turbulent diffusion coef cient Kd particle-water partition coef cient l decay constant k1 adsorption rate constant k 1 desorption rate constant k2 coagulation rate constant k 2 disaggregation rate constant N number of nucleons PD production rate P230 production rate of 230Th 231 Paxs excess activity of 231Pa P231 production rate of 231Pa t time t1/2 half-life 230 Thxs excess activity of 230Th Ri rain rate of component i V230 vertical flux of 230Th V231 vertical flux of 231Pa z depth Z atomic number l230 decay constant of 230Th l231 decay constant of 231Pa tsc scavenging residence time C focusing factor
See also Air–Sea Gas Exchange. Anthropogenic Trace Elements in the Ocean. Dispersion and Diffusion in the Deep Ocean. Hydrothermal Vent Fluids, Chemistry of. Nepheloid Layers. Ocean Margin Sediments. Sediment Chronologies. Sedimentary Record, Reconstruction of Productivity from the. Tracers of Ocean Productivity. Uranium-Thorium Series Isotopes in Ocean Profiles.
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URANIUM-THORIUM DECAY SERIES IN THE OCEANS: OVERVIEW
Further Reading Bacon MP and Anderson RF (1982) Distribution of thorium isotopes between dissolved and particulate forms in the deep sea. Journal of Geophysical Research 87: 2045--2056. Broecker WS and Peng T-H (1982) Tracers in the Sea. Columbia University, New York: Lamont-Doherty Geological Observatory. Eldigio Press. Cochran JK (1992) The oceanic chemistry of the Uranium and Thorium-series nuclides. In: Ivanovich M and Harmon RS (eds.) Uranium-series Disequilibrium: Applications to Earth, Marine, and Environmental
243
Sciences, 2nd edn. pp. 334--395. Oxford: Clarendon Press. Firestone RB (1998) Table of Isotopes, 8th edn. In: Baglin CM (ed) and Chu SYF (CD-ROM ed) New York: Wiley. Grasshoff K, Kremling K, and Ehrhardt M (1999) Methods of Seawater Analysis, 3rd edn, pp. 365–397. Weinheim: Wiley-VCH. Santschi PH and Honeyman BD (1991) Radioisotopes as tracers for the interactions between trace elements, colloids and particles in natural waters. In: Vernet J-P (ed.) Trace Metals in the Environment 1. Heavy Metals in the Environment, pp. 229--246. Amsterdam: Elsevier..
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES S. Krishnaswami, Physical Research Laboratory, Ahmedabad, India Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3146–3156, & 2001, Elsevier Ltd.
Natural radioactivity in the environment originates from two sources. First, primordial radionuclides which were incorporated into the Earth at the time of its formation are still present in it because of their long half-lives. 238U, 235U, 232Th and their decay series (Figure 1), 40K, 87Rb and 187Re are examples of this category. Second, cosmic ray-produced
238
U Series
238
U
232
Th Series
232
Th
4.5 × 109 y 234
Th 24.1 d
228
Ra 5.75 y
Th
U 2.5 × 105 y
230Th
7.5 × 104 y 226
Ra 1600 y
222
Rn 3.83 d
U Series
U
Ra 3.66 d
208
Pb
7.04 × 108 y
231
Pa 3.28 × 104 y
227
Ac 21.8 y
1.91 y 224
Supply of U/Th Isotopes to the Sea
235
1.4 × 1010 y
228
234
235
227
Th 18.7 d
223
Ra 11.4 d
207
Pb
210
Pb 22.3 y
210
Po 138 d
206
Pb
Figure 1 238U, 232Th and 235U decay series: Only the isotopes of interest in water column process studies are shown.
244
isotopes which are generated continuously in the atmosphere and earth’s crust through interactions of cosmic rays with their constituents. 3H, 14C and 10Be are some of the isotopes belonging to this group. The distribution of all these isotopes in the oceans is governed by their supply, radioactive decay, water mixing and their biogeochemical reactivity (the tendency to participate in biological and chemical processes) in sea water. Water circulation plays a dominant role in the dispersion of isotopes which are biogeochemically ‘passive’ (e.g. 3H, Rn), whereas biological uptake and release, solute–particle interactions and chemical scavenging exert major control in the distribution of biogeochemically ‘active’ elements (e.g. C, Si, Th, Pb, Po). Systematic study of the isotopes of these two groups in the sea can yield important information on the physical and biogeochemical processes occurring in sea water.
These nuclides enter the oceans through three principal pathways. Fluvial Transport
This is the main supply route for 238U, 235U, 234U and 232Th to the sea. These isotopes are transported both in soluble and suspended phases. Their dissolved concentrations in rivers depend on water chemistry and their geochemical behavior. In rivers, uranium is quite soluble and is transported mainly as uranyl carbonate, UO2(CO3)4 3 , complex. The dissolved uranium concentration in rivers is generally in the range of 0.1–1.0 mg l1. During chemical weathering 235U is also released to rivers in the same 235 U/238U ratio as their natural abundance (1/137.8). This is unlike that of 234U, a progeny of 238U (Figure 1) which is released preferentially to solution due to a-recoil effects. As a result, the 234U/238U activity ratios of river waters are generally in excess of that in the host rock and the secular equilibrium value of 1.0 and often fall in the range of 1.1–1.5. The concentration of dissolved 232Th in rivers, B0.01 mg l1 is significantly lower than that of 238U, although their abundances in the upper continental crust are comparable. This is because 232Th (and other Th isotopes) is more resistant to weathering and is highly particle-reactive (the property to be
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES
associated with particles) in natural waters and hence is rapidly adsorbed from solution to particles. It is likely that even the reported dissolved 232Th concentrations are upper limits, as recent results, based on smaller volume samples and high sensitivity mass-spectrometric measurements seem to show that dissolved 232Th in rivers is associated with smaller particles (o0.45 mm size). Similar to 232Th, the bulk of 230Th and 210Pb is also associated with particles in rivers and hence is transported mainly in particulate form from continents. 226 Ra and 228Ra are two other members of the UTh series (Figure 1) for which dissolved concentration data are available for several rivers, these show that they are present at levels of B0.1 d.p.m. l1. The available data show that there are significant differences between the abundances of U, Ra isotopes and 232Th in the host rocks and in river waters. The various physicochemical processes occurring during the mobilization and transport of these nuclides contribute to these differences. Rivers also transport U/Th series nuclides in particulate phase to the sea. These nuclides exist in two forms in the particulate phase, one as a part of their lattice structure and the other as surface coating resulting from their adsorption from solution. Analysis of suspended particulate matter from rivers shows the existence of radioactive disequilibria among the members of the same radioactive decay chain. In general, particulate phases are characterized by 234U/238U, 226Ra/230Th activity ratios o1 and 230Th/234U and 210Pb/226Ra41, caused by preferential mobilization of U and Ra over Th and Pb isotopes. Soluble and suspended materials from rivers enter the open ocean through estuaries. The interactions of sea water with the riverine materials can modify the dissolved concentrations of many nuclides and hence their fluxes to the open sea. Studies of U/Th series isotopes in estuaries show that in many cases their distribution is governed by processes in addition to simple mixing of river and sea water. For example, in the case of U there is evidence for both its addition and removal during transit through estuaries. Similarly, many estuaries have 226Ra concentration higher than that expected from water mixing considerations resulting from its desorption from riverine particles and/or its diffusion from estuarine sediments. Estuaries also seem to act as a filter for riverine 232Th. The behavior of radionuclides in estuaries could be influenced by their association with colloids. Recent studies of uranium in Kalix River show that a significant part is bound to colloids which is removed in the estuaries through flocculation. Similarly, colloids
245
seem to have a significant control on the 230Th–232Th distribution in estuarine waters.
In situ Production
Radioactive decay of dissolved radionuclides in the water column is an important supply mechanism for several U/Th series nuclides. This is the dominant mode of supply for 234Th, 228Th, 230Th, 210Po, 210Pb, and 231Pa. The supply rates of these nuclides to sea water can be precisely determined by measuring the concentrations of their parents. This is unlike the case of nuclides supplied via rivers whose fluxes are relatively more difficult to ascertain because of large spatial and temporal variations in their riverine concentrations and their modifications in estuaries.
Supply at Air–Sea and Sediment–Water Interfaces
A few of the U/Th nuclides are supplied to the sea via atmospheric deposition and diffusion through sediment pore waters. Decay of 222Rn in the atmosphere to 210Pb and its subsequent removal by wet and dry deposition is an important source of dissolved 210Pb to the sea. As the bulk of the 222Rn in the atmosphere is of continental origin, the flux of 210Pb via this route depends on factors such as distance from land and aerosol residence times. 210Po is also deposited on the sea surface through this source, but its flux is o10% of that of 210Pb. Leaching of atmospheric dust by sea water can also contribute to nuclide fluxes near the air–sea interface, this mechanism has been suggested as a source for dissolved 232Th. Diffusion out of sediments forms a significant input for Ra isotopes, 227Ac and 222Rn into overlying water. All these nuclides are produced in sediments through a-decay (Figure 1). The recoil associated with their production enhances their mobility from sediments to pore waters from where they diffuse to overlying sea water. Their diffusive fluxes depend on the nature of sediments, their accumulation rates, and the parent concentrations in them. 234U is another isotope for which supply through diffusion from sediments may be important for its oceanic budget. In addition to diffusion out of sediments, 226Ra and 222Rn are also introduced into bottom waters through vent waters associated with hydrothermal circulation along the spreading ridges. The flux of 226 Ra from this source though is comparable to that from rivers; its contribution to the overall 226Ra budget of the oceans is small. This flux, however, can overwhelm 226Ra diffusing out of sediments along the ridges on a local scale.
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246
URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES
Distribution in the Oceans Uranium 238
U and 235U are progenitors of a number of particle-reactive nuclides in sea water which find applications in the study of several water column and sedimentary processes. The study of uranium distribution in the sea is therefore essential to a better understanding of the radioactive disequilibrium between 238U–234Th, 234U–230Th, 238U–234U, and 235 U–231Pa in sea water. Uranium in sea water is almost entirely in solution as UO2(CO3)4 3 . Considerable data on its concentration and 234U/238U activity ratios are available in the literature, most of which are based on a-spectrometry. These results show that uranium concentration in salinity normalized open ocean sea water (35%) are the same within experimental uncertainties, 3.370.2 mg l1. Measurements with highly sensitive mass-spectrometric techniques also yield quite similar values, but with a much better precision (B0.2%) and narrower range, 3.162–3.282 ng g1 35% salinity water (Figure 2). The B3.8% spread even in the recent data is intriguing and is difficult to account for as uranium is expected to be uniformly distributed in the oceans because of its long residence time, B(2–4) 105 years. More controlled sampling and analysis of uranium in sea water are needed to address this issue better. The mass-spectrometric measurements of uranium have also provided data showing that the 238 U/235U atomic ratio in sea water is 137.17– 138.60, identical within errors to the natural abundance ratio of 137.88.
0
Depth (m)
2000
4000
140 150 δ234U
160
Figure 2 238U concentration (ng g1 35% salinity water) and d(234U) in the Pacific ( ) and the Atlantic (J) waters. Data from Chen et al. (1986).
dð234 UÞ ¼ ½ðRs =Re Þ 1 103
½1
where Rs and Re are 234U/238U atomic ratios in sample and at radioactive equilibrium respectively. The d(234U) in the major oceans (Figure 2) are same within analytical precision and average 14472. Coralline CaCO3 and ferromanganese deposits forming from sea water incorporate 234U/238U in the ratio of 1.144, the same as that in seawater. The decay of excess 234U in these deposits has been used as a chronometer to determine their ages and growth rates. Th Isotopes
Pacific Atlantic
6000 3.10 3.15 3.20 3.25 3.30 130 Uranium (ng g–1)
Studies of uranium distribution in anoxic marine basins (e.g., the Black Sea and the Saanich Inlet) have been a topic of interest as sediments of such basins are known to be depositories for authigenic uranium. These measurements show that even in these basins, where H2S is abundant, uranium exists predominantly in þ 6 state and its scavenging removal from the water column forms only a minor component of its depositional flux in sediments. The preferential mobilization of 234U during weathering and its supply by diffusion from deep-sea sediments causes its activity in sea water to be in excess of that of 238U. The 234U/238U activity ratio of sea water, determined by a-spectrometry, indicates that it is quite homogenous in open ocean waters with a mean value of 1.1470.02. Mass-spectrometric measurements have confirmed the above observations of 234U excess with a much better precision and have also led to the use of ‘d notation’ to describe 234U–238U radioactive disequilibrium.
Among the U/Th series nuclides, the Th isotopes (232Th, 230Th, 228Th, and 234Th), because of their property to attach themselves to particles, are the most extensively used nuclides to investigate particle cycling and deposition in the oceans, processes which have direct relevance to carbon export, solute-particle interactions and particle dynamics. 232Th, 230Th and 228Th are generally measured by a-spectrometry and 234Th by b or g counting. Highly sensitive massspectrometric techniques have now become available for precise measurements of 232Th and 230Th in sea water. Dissolved 232Th concentration in sea water centers around a few tens of picograms per liter. It is uncertain if the measured 232Th is truly dissolved or is associated with small particles/colloids. Some 232Th profiles show a surface maximum which has been attributed to its release from atmospheric dust.
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES 234
Th is continuously produced in sea water from the decay of 238U at a nearly uniform rate of B2.4 atoms l1 min1. It has been observed that 234Th activity in the surface B200 m is generally deficient relative to its parent 238U suggesting its removal by particles, the mechanism of how this is accomplished, however, is not well understood. This result has been attested by several studies (Figure 3). The residence time of Th in the upper layers of the ocean is determined based on 234Th–238U disequilibrium and the relation; t¼
R tl ð1 RÞ
½2
where R is the 234Th/238U activity ratio and tl is the radioactive mean life of 234Th (36.8 days). More complex models considering reversible Th exchange, particle remineralization, aggregation and breakup have also been used to treat the 234Th data which allow better understanding of processes regulating both particle and Th cycling. All these studies demonstrate that Th removal by particle scavenging is ubiquitous in surface water and occurs very rapidly, on timescales of a few days to a few months. Much of this variability in the residence time of Th appears to be dictated by particle concentration, short residence times are typical of coastal and biologically productive areas where particles are generally more abundant. These observations have prompted the use of the 234Th–238U pair as a survey tool to determine the export fluxes of carbon from the euphotic zone. The results, though encouraging, suggest the need for a more rigorous validation of the assumptions and parameters used. 0
238
11°N
228
Th activity in the sea exhibits significant lateral and depth variations with higher concentration in the surface and bottom waters and low values in the ocean interior (Figure 4). This pattern is governed by the distribution of its parent 228Ra, which determines its production (see section on Ra isotopes). Analogous to 234Th, the distribution of 228Th in the upper layers of the sea is also determined by particle scavenging which causes the 228Th/228Ra activity ratio to be o1, the disequilibrium being more pronounced near coasts where particles are more abundant. The residence time of Th in surface waters calculated from 234Th–228U and 228Th–228Ra pairs yields similar values. Profiles of 228Th activity in bottom waters show a decreasing trend with height above the sediment–water interface. In many of these profiles 228Th is in radioactive equilibrium with 228Ra and in a few others it is deficient. Some of these profile data have been used as a proxy for 228Ra to derive eddy diffusion rates in bottom waters. Systematic measurements of 230Th activity–depth profiles in soluble and suspended phases of sea water have become available only during the past two decades. 230Th is produced from 234U at a nearly uniform rate of B2.7 atoms l1 min1. The dissolved 230 Th activity in deep waters of the North Atlantic is B(5–10) 104 d.p.m. l1 and in the North Pacific it is B2 times higher. In comparison, the particle 230 Th concentrations are about an order of magnitude lower (Figure 5). These values are far less than would be expected if 230Th were in radioactive
0
U 2000
15°N
Depth (m)
Depth (m)
100
238
U
247
200
4000
300 6000 0
1
2 3 0 1 Activity (d.p.m. kg–1)
2
3
Figure 3 234Th –238U profiles from the Arabian Sea. Note the clear deficiency of 234Th in the upper layers relative to 238U. (Modified from Sarin et al., 1996.)
2
0 228Th
(d.p.m. (1000 kg)–1)
4
Figure 4 228Th distribution in the Pacific. The higher activity levels of 228Th in near-surface and near-bottom waters reflect that of its parent 228Ra. Data from Nozaki et al. (1981).
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248
URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES 0
Dissolved
0
Particulate
2000 Depth (m)
Depth (m)
2000
4000
6000
4000
0
1
2 230Th
3 0.00 0.06 0.12 0.18
0.2
0
(d.p.m. (1000 kg)–1)
0.4
231Pa
Figure 5 Water-column distributions of dissolved and particulate 230Th. Dissolved 230Th data from the North Pacific (Nozaki et al. 1981) and particulate 230Th from the Indian Ocean (Krishnaswami et al. 1981). The steady increase in the 230Th activities in both the phases is evident.
equilibrium with 234U, B2.7 d.p.m. l1, reinforcing the intense particle-reactive nature of Th isotopes and the occurrence of particle scavenging throughout the seawater column. More importantly, these studies showed that both the soluble and particulate 230 Th activities increase steadily with depth (Figure 5), an observation which led to the hypothesis of reversible exchange of Th between soluble and suspended pools to explain its distribution. In this model the equations governing the distribution of Th in the two phases are: Suspended Th:
S
6000
¯ k1 C ¼ ðl þ k2 ÞC
½3
dC¯ þ k1 C ðl þ k2 ÞC¯ ¼ 0 dz
½4
P þ k2 C¯ ¼ ðl þ k1 ÞC
½5
Soluble Th:
¯ are where P is the production rate of 230Th, C and C the 230Th concentrations in soluble and suspended phases, k1 and k2 are the first order adsorption and desorption rate constants, respectively, and S is the settling velocity of particles. Analysis of Th isotope data using this model suggests that adsorption of Th occurs on timescales of a year or so, whereas its release from particles to solution is much faster, i.e. a few months, and that the particles in sea are at
0.6
0.8
–1
(d.p.m. (1000 kg) )
Figure 6 231Pa distribution in the north-west Pacific. Data from Nozaki and Nakanishi (1985).
equilibrium with Th in solution. Modified versions of the above model include processes such as particle aggregation and breakup, remineralization and release of Th to solution. The timescales of some of these processes also have been derived from the Th isotope data. 231
Pa,
210
Po, and
210
Pb
These three isotopes share a property with Th, in that all of them are particle reactive. 231Pa is a member of the 235U series (Figure 1) and is produced in sea water at a rate of B0.11 atoms l1 min1. Analogous to 230Th, 231Pa is also removed from sea water by adsorption onto particles, causing its activity to be quite low and deficient relative to 235U (Figure 6). The 231Pa/235U activity ratio in deep waters of the western Pacific is B5 103. Measurements of 230Th/231Pa ratios in dissolved, suspended, and settling particles have led to a better understanding of the role of their scavenging by vertically settling particles in the open ocean in relation to their removal on continental margins. The dissolved 230Th/231Pa in sea water is B5, less than the production ratio of B10.8 and those in suspended and settling particles of B20, indicating that 230 Th is preferentially sequestered onto settling particles. This, coupled with the longer residence time of 231 Pa (a few hundred years) compared to 230Th (a few tens of years), has led to the suggestion that 231 Pa is laterally transported from open ocean areas to more intense scavenging regimes such as the continental margins, where it is removed. The
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES
0
Depth (m)
chemical homologues. 210Pb occurs in excess over 226 Ra in surface water (Figure 9) resulting from its supply from the atmosphere. This excess, however, is less than that would be expected from the known
4 Arabian Sea Off Mexico Mediterranean 2 Bay of Bengal N. Atlantic
210
Po Removal rate constant (y–1)
Red Sea
Caribbean S. China Sea N. Pacific
0 0
0.2
0.4
0.6
Chlorophyll a (µg l–1) Figure 8 Interrelation between 210Po scavenging rate and chlorophyll a concentrations in various oceanic regions. (Modified from Nozaki et al., 1998.) 210
0
Pb excess (d.p.m. (100 kg)–1) 10 20 30
0
Depth (m)
measurements of settling fluxes of 230Th and 231Pa using sediment traps and 230Th/231Pa ratios in sediments from various oceanic regions support this connection. 210 Po is supplied to sea almost entirely through its in situ production from the decay of 210Pb (Figure 1), a minor contribution comes from its atmospheric deposition at the air–sea interface. 210Po is deficient relative to 210Pb in surface waters (210Po/210Pb B0.5, Figure 7), the deficiency being more pronounced in biologically productive regimes. The residence time of 210Po in surface waters of the world oceans is in the range of 170.5 years. The 210 Po/210Pb ratio at the base of the euphotic zone falls between 1.0 and 2.0 and often exceeds the secular equilibrium value of unity (Figure 7), below B200 m 210Po and 210Pb are in equilibrium. The 210 Po profiles in the upper thermocline have been modeled to obtain eddy diffusion coefficients and derive fluxes of nutrients into the euphotic zone from its base. The nature of 210Po profiles in the thermocline and the observation that it is enriched in phytoand zooplankton indicates that it is a ‘nutrient like’ element in its behavior and organic matter cycling significantly influences its distribution in the sea. The strong dependence of 210Po removal rate on chlorophyll a abundance in various oceans (Figure 8) is another proof for the coupling between 210Po and biological activity. In deep and bottom waters, 210Po and 210Pb are generally in equilibrium except in areas of hydrothermal activity where Fe/Mn oxides cause preferential removal of 210Po resulting in 210Po/210Pb activity ratio o1. The studies of 210Pb–226Ra systematics in the oceans have considerably enhanced our understanding of scavenging processes, particularly in the deep sea and the marine geochemistries of lead and its
249
1000
400
2000 800
6 9 12 0.4 Activity (d.p.m. (100 kg)–1)
1.0
1.6
210Po/210Pb
Figure 7 210Po–210Pb disequilibrium in the Indian Ocean. 210Po ( ) is deficient relative to 210Pb (J) near the surface and is in excess at 100–200 m. Data from Cochran et al. (1983).
Figure 9 210Pb excess over 226Ra in the upper thermocline from several stations of the Pacific. This excess results from its atmospheric deposition. (Modified from Nozaki et al., 1980.)
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES
supply rate of 210Pb from the atmosphere if it is removed only through its radioactive decay. This led to the proposal that 210Pb is scavenged from surface to deep waters on timescales of a few years. In many profiles, excess 210Pb shows exponential decrease with depth (Figure 9), which has been modeled to derive apparent eddy diffusion coefficients. Measurements of 210Pb–226Ra in the deep sea produced a surprise result in that 210Pb was found to be deficient relative to 226Ra with 210Pb/226Ra of B0.5 (Figure 10). This was unexpected from the available estimates of the residence time of lead in the deep sea, i.e., a few thousands of years, orders of magnitude more than 210Pb mean-life. Numerous subsequent studies have confirmed this deficiency of 210Pb, though with significant variability in its extent and has led to the conclusion that 210Pb is rapidly and continuously removed from the deep sea on timescales of B50–200 years. The residence time is much shorter, B2–5 years, in anoxic basins such as the Cariaco Trench and the Black Sea. Two other important findings of these studies are that the extent of 210 Pb–226Ra disequilibrium increases from open ocean regimes to continental margins and topographic highs and that there is a significant concentration gradient in 210Pb activity from ocean interior to ocean margins. These results coupled with 210Pb data in suspended and settling particles form the basis for the proposal that 210Pb is removed from deep sea both by vertically settling particles and by lateral transport to margins and subsequent uptake
at the sediment–water interface. Processes contributing to enhanced uptake in continental margins are still being debated; adsorption on Fe/Mn oxides formed due to their redox cycling in sediments and the effect of higher particle fluxes, both biogenic and continental, have been suggested. It is the 210Pb studies which brought to light the role of continental margins in sequestering particle-reactive species from the sea, a sink which is now known to be important for other nuclides such as 231Pa and 10Be. 222
Rn
The decay of 226Ra in water generates the noble gas Rn; both these are in equilibrium in the water column, except near the air–sea and sea–sediment interfaces. 222Rn escapes from sea water to the atmosphere near the air–sea boundary, causing it to be deficient relative to 226Ra, whereas close to the sediment–water interface 222Rn is in excess over 226 Ra due to its diffusion out of bottom sediments (Figure 11). These disequilibria serve as tracers for mixing rate studies in these boundary layers. In addition, the surface water data have been used to derive 222Rn emanation rates and parameters pertaining to air–sea gas exchange. 222 Rn excess in bottom waters decreases with height above the interface, however, the 222Rn activity profiles show distinct variations. Commonly 222
5450
0
5450
Depth (m)
250
5650
5850
2000
0
1
2
Depth (m)
Depth (m)
Log excess radon
4000
5650
K = 440 ± 140 cm2 s−1 Excess radon
6000
0
20 40 0 20 Activity (d.p.m. (100 kg)–1)
40
5850 20
Figure 10 210Pb ( )–226Ra (J) disequilibrium in sea water. The deficiency of 210Pb in the ocean interior is attributed to its removal by vertically settling particles and at the ocean margins. Data from Craig et al. (1973), Chung and Craig (1980) and Nozaki et al. (1980).
36
24
48
60
Rn (d.p.m. (100 kg)−1)
222
Figure 11 Example of bottom water 222Rn profile in the Atlantic. The calculated vertical eddy diffusion coefficient is also given. (Modified from Sarmiento et al., 1976.)
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES 0
the 222Rn activity decreases exponentially with height above bottom (Figure 11) which allows the determination of eddy diffusion coefficient in these waters. In these cases the 222Rn distribution is assumed to be governed by the equation: d2 C lC ¼ 0 dz2
40
60
80
100 223
Ra
1
½6
where K is the eddy diffusion coefficient and z height above bottom with 222Rn activity C. The values of K calculated from the 222Rn data span about two orders of magnitude, 1–100 cm2 s1. Other types of 222 Rn profiles include those with a two-layer structure and those without specific trend suggesting that its transport via advection and eddy diffusion along isopycnals and non-steady-state condition also need to be considered while describing its distribution. These studies also demonstrated a strong dependence between 222Rn-based eddy diffusion and the stability of bottom water column. Ra Isotopes
Ra isotopes, particularly, 226Ra and 228Ra have found extensive applications in water circulation studies. All the Ra isotopes, 224Ra, 223Ra, 228Ra, and 226 Ra enter the oceans mainly through diffusion from sediments and by desorption from river particulates and are commonly measured by a and g counting techniques. 224Ra and 223Ra, because of their very short half-lives (Figure 1), are useful for studying mixing processes occurring on timescales of a few days to a few weeks which restricts their utility to regions close to their point of injection such as coastal and estuarine waters (Figure 12). The halflife of 228Ra is also short, 5.7 years, and hence its concentration decreases with increasing distance from its source, the sediment–water interface, e.g., from coast to open sea (Figure 13) surface waters to ocean interior and height above the ocean floor (Figure 14). These distributions have been modeled, by treating them as a balance between eddy diffusion and radioactive decay (eqn [6]), to determine the rates of lateral and vertical mixing occurring on timescales of 1–30 years in the thermocline and near bottom waters. 226 Ra is the longest lived among the Ra isotopes, with a half-life comparable to that of deep ocean mixing times. The potential of 226Ra as a tracer to study large-scale ocean mixing was exploited using a one-dimensional vertical advection–diffusion model to describe its distribution in the water column. Subsequent studies brought to light the importance of biological uptake and cycling in influencing 226Ra
−1 In Activity (d.p.m. (100 l)−1)
K
20
−3
224
Ra
3
1
−1
−3 0
20
40
60
80
Distance offshore (km) Figure 12 Distributions of 223Ra and 224Ra activities as a function of distance off-shore from Winyah Bay off Carolina Coast, USA. These profiles have been modeled to yield horizontal eddy diffusion coefficients. (Modified from Moore, 1999.)
distribution, processes which were later included in the 226Ra model. Figure 15 shows typical profiles of 226Ra in the oceans. Its concentration in surface waters falls in the range of 0.0770.01 d.p.m. l1 which steadily increases with depth such that its abundance in the deep waters of the Pacific>Indian>Atlantic (Figure 15). 226Ra concentration in the North Pacific bottom water is B0.4 d.p.m. l1, some of the highest in the world’s oceans. 226 Ra distribution in the ocean has been modeled to derive eddy diffusivities and advection rates taking into consideration its input by diffusion from sediments, loss by radioactive decay, and dispersion
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES
0
Ky = 4 ×105 cm2 s−1
0.5
Ky = 4 ×107 cm2 s−1
2000 Depth (m)
0.2
228
Ra (d.p.m. (100 kg)−1)
2.0
0.1 4000
0
400
800 Distance offshore (km)
1200
Figure 13 228Ra distribution as a function of distance from the coast off California. Values of horizontal eddy diffusion coefficient can be derived from these profiles. Note that 228Ra mixes farther into the open sea than 223Ra and 224Ra (Figure 12) because of its longer half-life. (Modified from Cochran, 1992.)
227
0
2.0 228
4.0 −1
Ra (d.p.m. (100 kg) )
Figure 14 Example of 228Ra depth profile in the North Atlantic. The high concentrations near the surface and near the sediment– water interface is due to its supply by diffusion from sediments. Lateral transport also plays an important role in determining surface water concentrations. (Modified from Cochran, 1992.)
0
2000 Depth (m)
through water mixing, particulate scavenging and regeneration. It has been shown that particulate scavenging and regeneration plays a crucial role in contributing to the progressive increase in 226Ra deep water concentration from the Atlantic to the Pacific. Attempts to learn more about particulate transport processes in influencing 226Ra distribution using Ba as its stable analogue and Ra–Ba and Ra–Si correlations have met with limited success and have clearly brought out the presence of more 226Ra in deep waters than expected from their Ba content (Figure 16). This ‘excess’ is the nascent 226Ra diffusing out of deep sea sediments and which is yet to take part in particulate scavenging and recycling. Such excesses are quite significant and are easily discernible in the bottom waters of the eastern Pacific.
6000
4000
Ac
The first measurement of 227Ac in sea water was only reported in the mid-1980s. These results showed that its concentration increases steadily from surface to bottom water (Figure 17) and that its activity in ocean interior and deep waters is considerably in excess of its parent 231Pa (Figure 17). The diffusion of 227Ac out of bottom sediments is the source of its
6000
0 226Ra
20 (d.p.m. (100 kg)−1)
40
Figure 15 Typical distributions of 226Ra in the water column of the Pacific ( ) and Atlantic (J) oceans. Data from Broecker et al. (1976) and Chung and Craig (1980).
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URANIUM-THORIUM SERIES ISOTOPES IN OCEAN PROFILES
excess in bottom waters, analogous to those of Ra isotopes. Measurements of 227Ac in pore waters have confirmed this hypothesis. 227Ac distribution can serve as an additional tracer in studies of water mixing processes occurring on decadal timescales, thus complementing the 228Ra applications.
226
Ra (d.p.m. (kg)−1)
0.4
0.3
0.2
253
Summary The distribution of U/Th series nuclides in the sea is regulated by physical and biogeochemical processes occurring in the water column and at the air–sea and sea–sediment interfaces. These processes often create radioactive disequilibria among the members of the U/Th decay chains. These disequilibria serve as powerful ‘tools’ to examine and quantify several processes in the sea, such as water circulation on various timescales (days to thousands of years), particle-scavenging, solute–particle interactions, particle dynamics and transformation and air–sea gas exchange. The understanding of these processes and elucidation of their timescales have direct relevance to studies such as dispersal of chemical species in the sea, contaminant transport and sites of their removal and particulate carbon fluxes through the water column. Recent advances in sampling and measurements of U/Th series nuclides have considerably enhanced the scope of their application in the study of water column processes.
See also
0.1
Estuarine Circulation. River Inputs. UraniumThorium Decay Series in the Oceans Overview. 0
40
80
120
160
Ba (nm kg−1)
Further Reading
Figure 16 Ra–Ba correlation in the north-east Pacific. The presence of ‘excess Ra’ (enclosed in ellipses) is clearly discernible in bottom waters. (Modified from Ku et al., 1980.)
0 231
Pa
Depth (m)
2000
4000
6000
0
1
2 3 Ac (d.p.m. (100 kg)−1)
4
227
Figure 17 227Ac profile in the Pacific Ocean. Its large excess over 231Pa is due to its diffusion out of sediments. (Modified from Nozaki, 1984.)
Anderson RF, Bacon MP, and Brewer PG (1983) Removal of Th-230 and Pa-231 from the open ocean. Earth and Planetary Science Letters 62: 7--23. Anderson PS, Wasserburg GJ, Chen JH, Papanastassiou DA, and Ingri J (1995) 238U–234U and 232Th–230Th in the Baltic sea and in river water. Earth and Planetary Science Letters 130: 218--234. Bacon MP and Anderson RF (1982) Distribution of thorium isotopes between dissolved and particulate forms in the deep sea. Journal of Geophysical Research 87: 2045--2056. Bhat SG, Krishnaswami S, Lal D, and Rama and Moore WS (1969) Thorium-234/Uranium-238 ratios in the ocean. Earth and Planetary Science Letters 5: 483--491. Broecker WS, Goddard J, and Sarmiento J (1976) The distribution of 226Ra in the Atlantic Ocean. Earth and Planetary Science Letters 32: 220--235. Broecker WS and Peng JH (1982) Tracers in the Sea. New York: Eldigio Press, Lamont-Doherty Geological Observatory. Chen JH, Edwards RL, and Wesserburg GJ (1986) 238U, 234 U and 232Th in sea water. Earth and Planetary Science Letters 80: 241--251. Chen JH, Edwards RL, and Wasserburg GJ (1992) Mass spectrometry and application to uranium series disequilibrium. In: Ivanovich M and Harmon RS (eds.)
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Uranium Series Disequilibrium: Applications to Earth, Marine and Environmental Sciences, 2nd edn pp. 174– 206. Oxford: Clarenden Press. Chung Y and Craig H (1980) 226Ra in the Pacific Ocean. Earth and Planetary Science Letters 49: 267--292. Coale KH and Bruland KW (1985) Th-234 : U-238 disequilibria within the California Current. Limnology and Oceanography 30: 22--33. Cochran JK (1992) The oceanic chemistry of the uranium and thorium series nuclides. In: Ivanovich M and Harmon RS (eds.) Uranium Series Disequilibrium Applications to Earth, Marine and Environmental Sciences, 2nd edn, pp. 334–395. Oxford: Clarenden Press. Cochran JK, Bacon MP, Krishnaswami S, and Turekian KK (1983) 210Po and 210Pb distribution in the central and eastern Indian Ocean. Earth and Planetary Science Letters 65: 433--452. Craig H, Krishnaswami S, and Somayajulu BLK (1973) 210 Pb–226Ra radioactive disequilibrium in the deep sea. Earth and Planetary Science Letters 17: 295. Dunne JP, Murray JW, Young J, Balistrieri LS, and Bishop J (1997) 234Th and particle cycling in the central equatorial Pacific. Deep Sea Research II 44: 2049--2083. Krishnaswami S (1999) Thorium: element and geochemistry. In: Marshall CP and Fairbridge RW (eds.) Encyclopedia of Geochemistry, pp. 630--635. Dordrecht: Kluwer Academic. Krishnaswami S, Sarin MM, and Somayajulu BLK (1981) Chemical and radiochemical investigations of surface and deep particles of the Indian ocean. Earth and Planetary Science Letters 54: 81--96. Krishnaswami S and Turekian KK (1982) U-238, Ra-226 and Pb-210 in some vent waters of the Galapagos spreading center. Geophysical Research Letters 9: 827--830. Ku TL, Huh CA, and Chen PS (1980) Meridional distribution of 226Ra in the eastern Pacific along GEOSECS cruise track. Earth and Planetary Science Letters 49: 293--308. Ku TL, Knauss KG, and Mathieu GG (1977) Uranium in open ocean: concentration and isotopic composition. Deep Sea Research 24: 1005--1017.
Moore WS (1992) Radionuclides of the uranium and thorium decay series in the estuarine environment, In: Ivanovich M and Harmon RS (eds.) Uranium Series Disequilibrium. Applications to Earth, Marine and Environmental Sciences, 2nd edn. pp. 334--395. Oxford: Clarenden Press. Moore WS (1999) Application of 226Ra, 228Ra, 223Ra and 224 Ra in coastal waters to assessing coastal mixing rates and ground water discharge to the oceans. Proceedings of the Indian Academy of Sciences (Earth and Planetary Sciences) 107: 109--116. Nozaki Y (1984) Excess, Ac-227 in deep ocean water. Nature 310: 486--488. Nozaki Y, Dobashi F, Kato Y, and Yamamoto Y (1998) Distribution of Ra isotopes and the 210Pb and 210Po balance in surface sea waters of the mid-northern hemisphere. Deep Sea Research I 45: 1263--1284. Nozaki Y and Nakanishi T (1985) 231Pa and 230Th profiles in the open ocean water column. Deep Sea Research 32: 1209--1220. Nozaki Y, Turekian KK, and Von Damm K (1980) 210Pb in GEOSECS water profiles from the north Pacific. Earth and Planetary Sciences Letters 49: 393--400. Nozaki Y, Horibe Y, and Tsubota H (1981) The water column distributions of thorium isotopes in the western north Pacific. Earth and Planetary Sciences Letters 54: 203--216. Roy-Barman M, Chen JH, and Wasserburg GJ (1996) 230 Th–232Th systematics in the central Pacific Ocean: the sources and fate of thorium. Earth and Planetary Science Letters 139: 351--363. Sarin MM, Rengarajan R, and Ramaswamy V (1996) 234 Th scavenging and particle export fluxes from upper 100 m of the Arabian Sea. Current Science 71: 888--893. Sarmiento JL, Feely HW, Moore WS, Bainbridge AE, and Broecker WS (1976) The relationship between vertical eddy diffusion and buoyancy gradient in the deep sea. Earth and Planetary Letters 32: 357--370.
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VEHICLES FOR DEEP SEA EXPLORATION S. E. Humphris, Woods Hole Oceanographic Institution, Woods Hole, MA, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction Exploring the deep sea has captured the imagination of humankind ever since Leonardo da Vinci made drawings of a submarine more than 500 years ago, and Jules Verne published 20 000 Leagues under the Sea in 1875. Since the early twentieth century, people have been venturing into the ocean in bathyspheres and bathyscaphs. However, it was not until 1960 that the dream to go to the bottom of the deepest part of the ocean was realized, when Jacques Piccard and a US Navy lieutenant, Don Walsh, descended to the bottom of the Mariana Trench (10 915 m or 6.8 mil) in Trieste (Figure 1). This vehicle consisted of a float chamber filled with gasoline for buoyancy, and a separate pressure sphere for the personnel, allowing for a free dive rather than a tethered one. Containers filled with iron shot served as ballast to make the submersible sink. After a 5-h trip to the bottom, and barely 20 min of observations there, the iron shot was released and Trieste floated back to the surface. Since that courageous feat almost 50 years ago, dramatic advances in deep submergence vehicles and technologies have enabled scientists to routinely
explore the ocean depths. For many years, researchers have towed instruments near the seafloor to collect various kinds of data (e.g., acoustic, magnetic, and photographic) remotely. With the development of sophisticated acoustic and imaging systems designed to resolve a wide range of ocean floor features, towed vehicle systems have become increasingly complex. Some now use fiber-optic, rather than coaxial, cable as tethers and hence are able to transmit imagery as well as data in real time. Examples of deep-towed vehicle systems are included in Table 1 and Figure 2, and they tend to fall into two categories. Geophysical systems, such as SAR (IFREMER, France), TOBI (National Oceanography Centre, Southampton, UK), and Deep Tow 4KS (JAMSTEC, Japan), collect sonar imagery, bathymetry, sub-bottom profiles, and magnetics data, as they are towed tens to hundreds of meters off the bottom. Imaging systems, such as TowCam (WHOI, USA), Scampi (IFREMER, France), and Deep Tow 6KC (JAMSTEC, Japan), are towed a few meters off the bottom and provide both video and digital imagery of the seafloor. However, since the 1960s, scientists have been transported to the deep ocean and seafloor in submersibles, or human-occupied vehicles (HOVs), to make direct observations, collect samples, and deploy instruments. More recently, two other types of deep submergence vehicles – remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) – have been developed that promise to greatly expand our capabilities to map, measure, and sample in remote and inhospitable parts of the ocean, and to provide the continual presence necessary to study processes that change over time.
Human-occupied Vehicles
Figure 1 The bathyscaph Trieste hoisted out of the water in a tropical port, around 1959. Photo was released by the US Navy Electronics Laboratory, San Diego, California (US Naval Historical Center Photograph). Photo #NH 96801: US Navy Bathyscaphe Trieste (1958–63).
The deep-sea exploration vehicles most familiar to the general public are submersibles, or HOVs. This technology allows a human presence in much of the world’s oceans, with the deepest diving vehicles capable of reaching 99% of the seafloor. There exist about 10 submersibles available worldwide for scientific research and exploration that can dive to depths greater than 1000 m (Table 2 and Figure 3). All require a dedicated support ship. These battery-operated vehicles allow two to four individuals (pilot(s) and scientist(s)) to descend into the ocean to make observations and gather data and samples. The duration of a dive is limited by battery life, human
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VEHICLES FOR DEEP SEA EXPLORATION
Table 1 Examples of deep-towed vehicle systems for deep-sea research and exploration (systems that can operate at depths Z1000 m) Vehicle
Operating organization
Maximum operating depth (m)
Purpose
TowCam
WHOI, USA
6500
Deep-Tow Survey System
COMRA, China
6000
DSL-120A IMI-30
HMRG, USA HMRG, USA
6000 6000
Scampi Syste`me Acoustique Remorque´ (SAR) SHRIMP TOBI BRIDGET Deep Tow 6KC Deep Tow 4KC Deep Tow 4KS
IFREMER, France IFREMER, France
6000 6000
NOC, UK NOC, UK NOC, UK JAMSTEC, Japan JAMSTEC, Japan JAMSTEC, Japan
6000 6000 6000 6000 4000 4000
Photo imagery; CTD; volcanic glass samples; water samples Sidescan, bathymetry; sub-bottom profiling Sidescan; bathymetry Sidescan; bathymetry; sub-bottom profiling Photo and video imagery Sidescan; sub-bottom profiling; magnetics; bathymetry Photo and video imagery Sidescan; bathymetry; magnetics Geochemistry Photo and video imagery Photo and video imagery Sidescan; sub-bottom profiling
WHOI, Woods Hole Oceanographic Institution, USA; COMRA, China Ocean Mineral Resources R&D Association; HMRG, Hawai’i Mapping Research Group, USA; IFREMER, French Research Institute for Exploration of the Sea; NOC, National Oceanographic Centre, Southampton, UK; JAMSTEC, Japan Marine Science & Technology Center. (a)
(b)
(c)
(d)
Figure 2 Examples of deep-towed vehicle systems. (a) SHRIMP, (b) Deep Tow, (c) Tow Cam, and (d) DSL-120A. (a) Courtesy of David Edge, National Oceanography Centre, UK. (b) & JAMSTEC, Japan, with permission. (c) Photo by Dan Fornari, WHOI, USA. (d) Courtesy of WHOI, USA.
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VEHICLES FOR DEEP SEA EXPLORATION
Table 2
HOVs for deep-sea research and exploration (vehicles that can operate at depths Z1000 m)
Vehicle
Operating organization
Maximum operating depth (m)
HOV (under construction) Shinkai 6500 Replacement HOV (in planning stages) MIR I and II Nautile Alvin Pisces IV Pisces V Johnson-Sea-Link I and II
COMRA, China JAMSTEC, Japan NDSF, WHOI, USA P.P. Shirshov Institute of Oceanology, Russia IFREMER, France NDSF, WHOI, USA HURL, USA HURL, USA HBOI, USA
7000 6500 6500 6000 6000 4500 2170 2090 1000
257
Abbreviations as in Table 1; NDSF, National Deep Submergence Facility; HURL, Hawaii Undersea Research Laboratory; HBOI, Harbor Branch Oceanographic Institution, USA.
endurance, and safety protocols, and typically does not exceed 8–10 h, including transit time to and from the working depth (about 4 h for a seafloor depth of 4000 m). (The Russian MIR submersibles are an exception; they operate on a 100-kWh battery that can accommodate dive times in excess of 12 h.) Housed in a personnel sphere (Figure 4), the divers are maintained at atmospheric pressure despite the everincreasing external pressure with depth (1 atm every 10 m). Cameras on pan and tilt mounts with zoom and focus controls are located on the exterior of the vehicles, as well as quartz iodide and/or metal halide lights to illuminate the area. Submersibles are also equipped with robotic arms that can be used to manipulate equipment or pick up samples, and a basket, usually mounted on the front of the vehicle, to transport instruments, equipment, or samples. These vehicles can handle heavy payloads, maintaining neutral buoyancy as their weight changes through a variable ballast control system. All these capabilities, together with their slow speeds (1–2 knots), make submersibles best suited to detailed observations, imaging, and sampling in localized areas, rather than operating in a survey mode. Many significant discoveries during the past four decades of marine research have resulted from observations and samples taken from submersibles. Through direct observations from submersibles, biologists have discovered many previously unknown animals, and have documented that gelatinous animals (cnidarians, ctenophores, etc.) form a dominant ecological component of mid-water communities. These soft-bodied, fragile animals would have been destroyed by the trawl nets used in earlier days to sample these depths. Submersibles have enabled geologists to explore the global mid-ocean ridge system, and have provided them with a detailed view of the nature of volcanic and tectonic activity during the formation of oceanic crust. Submersibles played an
important role in the discovery of hydrothermal vents and their exotic communities of organisms, and continue to be used extensively for investigation of these extreme deep-sea environments. HOVs will continue to provide important capabilities for deep-sea research at least for the foreseeable future. Although rapid progress is being made in videography and photography to develop capabilities that match those of the human eye, there is still no substitute for the direct, three-dimensional view that allows divers to make contextual observations and integrate them with the cognitive ability of the human brain. In recognition of this continuing need, there are two submersibles that are under construction or in the planning stages. The China Ocean Mineral Resources R&D Association (COMRA) is constructing their first submersible that will have a maximum operating depth of 7000 m. It is expected to be operational in 2007. In the United States, over 40 years after the submersible Alvin was delivered in 1964, the National Deep Submergence Facility at Woods Hole Oceanographic Institution is in the planning stages for a new and improved replacement HOV with an increased operating depth of 6500 m.
Remotely Operated Vehicles Over the past 20 years, marine scientists have begun to routinely use ROVs to collect deep-sea data and samples. ROVs were originally developed for use in the ocean by the military for remote observations, but were adapted in the mid-1970s by the offshore energy industry to support deep-water operations. There are many ROVs commercially operated today, ranging from small, portable vehicles used for shallowwater inspections to heavy, work-class, deepwater ROVs used by the offshore oil and gas industry in support of subsea cable laying, retrieval, and repair.
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VEHICLES FOR DEEP SEA EXPLORATION (a)
(b)
(c)
Figure 3 Examples of HOVs used to conduct scientific research. (a) Shinkai 6500, (b) Sea Link, and (c) Nautile. (a) & JAMSTEC, Japan, with permission. (b) Courtesy of Harbor Branch Oceanographic Institution, USA. (c) & IFREMER, France, with permission; O. Dugornay.
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VEHICLES FOR DEEP SEA EXPLORATION Personnel hatch
Main ballast vent
Communication transducer
High pressure air spheres (2)
259
Thrusters (1 of 6)
Lifting T
Video light
Sonar
Video camera
Light bar Variable ballast spheres (4)
35-mm cameras Video cameras
Strobes Motor controller for relay pressure vessels
Starboard manipulator
Batteries
Variable ballast sphere Descent weights Pilot view port Port manipulator Ski
Sample basket
Figure 4 Cutaway illustration of the submersible Alvin showing the major components of an HOV. Illustration by E. Paul Oberlander, WHOI, USA.
There are about a dozen ROVs that are available to the international scientific community (Table 3 and Figure 5). While some of these have dedicated support ships, many can operate in the ‘flyaway’ mode; that is, they can be shipped to, and operated on, a number of different ships. Unlike the HOVs, ROVs are unoccupied, and are tethered to a support ship usually by a fiber-optic cable that has sufficient bandwidth to accommodate a wide variety of oceanographic sensors and imaging tools. The cable provides power and communications from the ship to the ROV, allowing control of the vehicle by a pilot on board the ship. The pilot can also use the manipulator arm(s) to collect samples and perform experiments. The cable transmits images and data from the ROV to the control room on board the ship where monitors display the images of the seafloor or water column in real time. These capabilities, together with their excellent power and lift, allow ROVs to perform many of the same operations as HOVs. Obvious advantages of using ROVs are that they remove the human risk factor from deep-sea research
and exploration and, through the shipboard control room (Figure 6), allow a number of scientists and engineers to discuss the incoming data and make collective decisions about the operations. Another distinct advantage is their ability to remain underwater for extended periods of time because power is provided continuously from the ship. This endurance means that scientists can make observations over periods of many days, instead of a few hours a day, and gives them the flexibility to react to unexpected events. The disadvantage of an ROV is that its tether constrains operations because the range of the vehicle with respect to the ship cannot exceed a few hundred meters. Movement of the ship must therefore be carefully coordinated with the movements of the vehicle – this requires a ship equipped with a dynamic positioning system. In addition, the tether is heavy and produces drag on the vehicle, making it less maneuverable and vulnerable to entanglement in rugged terrain. However, with careful tether management, ROVs are well suited to mapping and surveying small areas, as well as to making
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Table 3
ROVs for deep-sea research and exploration (vehicles that can operate at depths Z1000 m)
Vehicle
Operating organization
Maximum operating depth (m)
Nereus (hybrid) (under construction) Kaiko 7000 Isis Jason II ATV CV (Wireline Reentry System) Victor 6000 ROV (on order) ROPOS Tiburon Quest Hercules Sea Dragon 3500 Hyper Dolphin Aglantha Ventana Cherokee
NDSF, WHOI, USA JAMSTEC, Japan NOC, UK NDSF, WHOI, USA SIO, USA SIO, USA IFREMER, France NOAA Office of Ocean Exploration, USA CSSF, Canada MBARI, USA Research Centre Ocean Margins, Germany Institute for Exploration, USA COMRA, China JAMSTEC, Japan Institute of Marine Research, Norway MBARI, USA Research Centre Ocean Margins, Germany
11 000 7000 6500 6500 6000 6000 6000 6000 5000 4000 4000 4000 3500 3000 2000 1500 1000
Abbreviations as in Tables 1 and 2; SIO, Scripps Institution of Oceanography; CSSF, Canadian Scientific Submersible Facility; MBARI, Monterey Bay Aquarium Research Institute; SIO, Scripps Institution of Oceanography.
more detailed observations, imaging, and sampling of specific features. While many of the ROVs available to the scientific community have a wide range of capabilities, a few are purpose-built. For example, the Wireline Reentry System known as CV, and operated by Scripps Institution of Oceanography, is a direct hang-down vehicle designed specifically for precision placement of heavy payloads on the seafloor or in drill holes (Figure 7). Unlike conventional, near-neutrally buoyant ROVs, the Wireline Reentry System can handle payloads of a few thousand kilograms, depending on the water depth. It has been used, for example, to install seismometer packages in, and recover instruments packages from, seafloor drill holes in water depths up to 5500 m, as well as to deploy precision acoustic ranging units on the axis of the mid-ocean ridge. Another ROV being built at Woods Hole Oceanographic Institution for a specific purpose is Nereus (Figure 8). More correctly referred to as a hybrid remotely operated vehicle, or HROV, because it will be able to switch back and forth to operate as either an AUV or an ROV on the same cruise, Nereus will be capable of exploring the deepest parts of the world’s oceans, as well as bringing ROV capabilities to ice-covered oceans, such as the Arctic. The HROV will use a lightweight fiber-optic micro-cable, only 1/32 of an inch in diameter, allowing it to operate at great depth without the high-drag and expensive cables typically used with ROV systems. Once the HROV reaches the bottom, it will conduct its
mission while paying out as much as 20 km (about 11 mi) of micro-cable. Once the mission is complete, the HROV will detach from the micro-cable and guide itself to the sea surface for recovery, while the micro-cable is recovered for reuse. In 2008–09, almost 50 years after the dive of the Trieste, Nereus will dive to the bottom of the Mariana Trench.
Autonomous Underwater Vehicles Although the concept of AUVs has been around for more than a century, it is only in the last decade or two that AUVs have been applied to deep-sea research and exploration. AUV technology is in a phase of rapid growth and expanding diversity. There are now more than 50 companies or institutions around the world operating AUVs for a variety of purposes. For example, the offshore gas and oil industry uses them for geologic hazards surveys and pipeline inspections, the military uses them for locating mines in harbors among other applications, and AUVs have been used to search for cracks in the aqueducts that supply water to New York City. There are currently about a dozen AUVs being used specifically for deep-sea exploration (Table 4 and Figure 9), although the numbers continue to increase. These unoccupied, untethered vehicles are preprogrammed and deployed to drift, drive, or glide through the ocean without real-time intervention from human operators. All power is supplied by energy systems carried within the AUV. Data are
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(a)
(b)
(c)
(d)
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Figure 5 Examples of ROVs used for deep-sea research. (a) ROV Kaiko, (b) ROV Jason II, (c) ROV Tiburon, and (d) ROV Victor 6000. (a) & JAMSTEC, Japan, with permission. (b) Photo by Tom Bolmer, WHOI, USA. (c) Photo by Todd Walsh & 2006, MBARI, USA, with permission. (d) & IFREMER, France, with permission; M. Bonnefoy.
recorded and are then either transmitted via satellite when the AUV comes to the surface, or are downloaded when the vehicle is recovered. They are generally more portable than HOVs and ROVs and can be deployed off a wide variety of ships. By virtue of their relatively small size, limited capacity for scientific payloads, and autonomous nature, AUVs do not have the range of capabilities of HOVs and ROVs. They are, however, much better suited than HOVs and ROVs to surveying large areas of the ocean that would take years to cover by any other means. They can run missions of many hours or days on their battery power and, with their streamlined shape, can travel many kilometers collecting data of various types depending on which sensors they are carrying.
Hence, AUVs are frequently used to identify regions of interest for further exploration by HOVs and ROVs. Unlike HOVs and ROVs that are designed with the flexibility to carry different sensors and equipment for different purposes, AUV system design and attributes are driven by the specific research application. Some, such as the autonomous drifters and gliders (essentially drifters with wings and a buoyancy change mechanism that allow the vehicle to change heading, pitch, and roll, and to move horizontally while ascending and descending in the water column), are designed for research in the water column to better understand the circulation of the ocean and its influence on climate. While satellites provide
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Figure 6 Portable control van for the ROV Jason II constructed from two shipping containers assembled on board the R/V Knorr. & Dive and Discover, WHOI, USA.
global coverage of conditions at the sea surface, AUVs are likely to be the only way to continuously access data from the ocean depths. Equipped with oceanographic sensors that measure temperature, salinity, current speed, and phytoplankton abundance, drifters and gliders profile the water column by sinking to a preprogrammed depth, and then rising to the surface where they transmit their data via satellite back to the scientist on shore. By deploying hundreds to thousands of these vehicles, scientists will achieve a long-term presence in the ocean, and will be able to make comprehensive studies of vast oceanic regions. Other, more sophisticated AUVs are also used to investigate water column characteristics, and ephemeral or localized phenomena, such as algal blooms. The first of the Dorado Class of AUVs, operated by Monterey Bay Aquarium Research Institute, was deployed in late 2001 to measure the inflow of water into the Arctic basin through the Fram Strait. Autosub, operated by the National Oceanography Centre, Southampton, UK, was deployed to measure flow over the sills in the Strait of Sicily. The REMUS (Remote Environmental Monitoring UnitS) class of AUVs is extremely versatile and they have been used on many types of missions. The standard configuration includes an up- and downlooking acoustic Doppler current profiler (ADCP), sidescan sonar, a conductivity–temperature (CT) profiler, and a light scattering sensor. However, many other instruments have been integrated into it for specific missions, including fluorometers, bioluminescence sensors, radiometers, acoustic modems, forward-looking sonar, altimeters, and acoustic Doppler velocimeters. REMUS can also carry a video plankton recorder, a plankton pump, video cameras,
Figure 7 The Wireline Reentry System, known as the CV, operated by Scripps Institution of Oceanography. This specialized ROV can precisely place heavy payloads on the seafloor and in drill holes. The control vehicle, which weighs about 500 kg in water, is deployed at the end of a 17.3-mm (0.68’’) electromechanical (coax) or electro-optico-mechanical (three copper conductors, three optical fibers) oceanographic cable. The vehicle consists of a steel frame equipped with two horizontal thrusters mounted orthogonal to each other to control lateral position. The vertical position is controlled by winch operation. Instrumentation includes a compass, pressure gauge, lights, video camera, sonar systems, and electronic interfaces to electrical releases and to a logging probe. Courtesy of Scripps Institution of Oceanography – Marine Physical Laboratory, USA.
electronic still cameras, and, most recently, a towed acoustic array. Still other AUVs are designed specifically for nearbottom work. They have proved particularly useful for near-bottom surveying and mapping, which can be accomplished autonomously while the support ship simultaneously conducts other, more traditional, operations. One of the earliest vehicles to provide this capability was the Autonomous Benthic Explorer (ABE) developed at Woods Hole Oceanographic Institution. ABE was designed to be extremely stable in pitch and roll and to be reasonably efficient in forward travel. All the buoyancy is built into the two
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upper pods, while the majority of the weight (the batteries and the main pressure housing) is in the central lower section. The three-hull structure also allows the seven vertical and lateral thrusters to be
Figure 8 Schematic illustration of the HROV, Nereus, currently under construction at Woods Hole Oceanographic Institution, USA, in its autonomous mode (upper) and its ROV mode (lower). Illustration by E. Paul Oberlander, WHOI, USA.
Table 4
263
placed between the hulls where they are protected. ABE is most efficient traveling forward, but it can also move backward, up or down, left or right, and can hover and turn in place. Equipment that it usually carries includes temperature and salinity sensors, an optical backscatter sensor, a magnetometer to measure near-bottom magnetic fields, and an acoustic altimeter to make bathymetric measurements and for its automated bottom following. ABE can dive to depths of 5500 m for 16–34 h, and it uses acoustic transponder navigation to follow preprogrammed track lines automatically. Its capability to maintain a precise course over rugged seafloor terrain gives it the ability to make high-precision seafloor bathymetric maps with features a few tens of centimeters tall and less than a meter long being identifiable. Other AUVs have been specifically developed for high-resolution optical and acoustic imaging of the seafloor. For example, SeaBED, also developed at Woods Hole Oceanographic Institution, was designed specifically to further the growing interests in seafloor optical imaging – specifically, high-resolution color imaging and the processes of photo-mosaicking and three-dimensional image reconstruction. In addition to requiring high-quality sensors, this imposes additional constraints on the ability of the AUV to carry out structured surveys, while closely following the seafloor. The distribution of the four thrusters, coupled with the passive stability inherent in a twohulled vehicle with a large metacentric height, allows SeaBED to survey close to the seafloor, even in very rugged terrain. In the future, AUVs will play an important role in the development of long-term seafloor observatories.
Examples of AUVs for deep-sea research and exploration (vehicles that can operate at depths Z1000 m)
Vehicle
Operating organization
Maximum operating depth (m)
Dorado Class CR-01, CR-02 Sentry REMUS Class Autosub 6000 Autonomous Benthic Explorer Explorer 5000 Jaguar/Puma Urashima (hybrid) Aster x Bluefin AUV Bluefin 21 AUV Odyssey Class SeaBED Autosub 3 Spray Gliders Seaglider
MBARI, USA COMRA, China WHOI, USA WHOI, USA NOC, UK NDSF, WHOI, USA Research Centre Ocean Margins, Germany WHOI, USA JAMSTEC, Japan IFREMER, France Alfred Wegener Institute, Germany SIO, USA MIT, USA WHOI, USA National Oceanography Centre, UK WHOI, USA Univ. of Washington, USA
6000 6000 6000 6000 6000 5500 5000 5000 3500 3000 3000 3000 3000 2000 1600 1500 1000
Abbreviations as in Tables 1–3.
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VEHICLES FOR DEEP SEA EXPLORATION (a)
(b)
(c)
(d)
(e)
(f)
Figure 9 Examples of AUVs used in oceanographic research. (a) The Spray Glider, (b) Urashima, (c) Autosub, (d) SeaBED, (e) Dorado Class, and (f) ABE. (a) Photo by Jane Dunworth-Baker, WHOI, USA. (b) & JAMSTEC, Japan, with permission. (c) Courtesy of Gwyn Griffiths, National Oceanography Centre, Southampton, UK. (d) Photo by Tom Kleindinst, WHOI, USA. (e) Photo by Todd Walsh & 2004, MBARI, USA, with permission. (f) Photo by Dan Fornari, WHOI, USA.
Apart from providing the high-resolution maps needed to optimally place geological, chemical, and biological sensors as part of an observatory, AUVs will also operate in a rapid response mode. It is envisaged that deep-sea observatories will include
docking stations for AUVs, and there are a number of research groups currently working on developing this technology. When an event – most likely a seismic event – is detected, scientists on shore will be able to program the AUV, via satellite and a cable to
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VEHICLES FOR DEEP SEA EXPLORATION
a surface buoy, to leave its dock and conduct surveys in the vicinity of the event. The AUV will then return to its dock and return the data to shore for assessment by scientists as to whether further investigation with ships is warranted.
Navigating Deep-sea Vehicles Unlike glider and drifter AUVs that can come to the sea surface and determine their positions using a Global Positioning System (GPS), deep-sea vehicles working at the bottom of the ocean have no such reference system because the GPS system’s radio frequency signals are blocked by seawater. The technique that has been the standard for threedimensional acoustic navigation of deep-sea vehicles is long-baseline (LBL) navigation – a technique developed more than 30 years ago. LBL operates on the principle that the distance between an underwater vehicle and a fixed acoustic transponder can be related precisely to the time of flight of an acoustic signal propagating between the vehicle and transponder. Two or more acoustic transponders are dropped over the side of the surface ship and anchored at locations selected to optimize the acoustic range and geometry of planned seafloor operations. Each transponder is a complete subsurface mooring comprised of an anchor, a tether, and a buoyant battery-powered acoustic transponder. The positions of the transponders on the seafloor are determined by using the GPS on board the ship and ranging to them acoustically while the ship circles the point where each transponder was dropped. The positions of the transponders on the seafloor can be determined this way with an accuracy of about 10 m. Transponders have accurate clocks to measure time very precisely, and they are synchronized with the clocks on the vehicle and on the ship. Each transponder is set to listen for acoustic signals (or pings) transmitted either from the deep-sea vehicle or the ship at a specific frequency. When each transponder hears these acoustic signals, it is programmed to transmit an acoustic signal back to the vehicle and the ship. Each transponder pings at a different frequency, so the ship and the vehicle can discern which transponder sent it. The time of flight of the acoustic signals gives a measure of distance to each transponder, and using simple triangulation, the unique point in three-dimensional space where all distances measured from all the transponders and the ship intersect can be calculated. More recently, conventional LBL navigation has been combined with Doppler navigation data, which measures apparent bottom velocity of the vehicle, for better short-term accuracy.
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The Future The technological breakthroughs in deep-sea vehicle design over the last 40 years have resulted in unprecedented access to the deep ocean. While each type of vehicle has its own advantages and disadvantages, the complementary capacities of all types of deep-submergence vehicles provide synergies that are revolutionizing how scientists conduct research in the deep ocean. They are learning how to exploit those synergies by using a nested survey strategy that employs a combination of tools in sequence for investigations at increasingly finer scales: ship-based swath-mapping systems and towed vehicle systems for reconnaissance over large areas to identify features of interest, followed by more detailed, high-resolution mapping, imagery, and chemical sensing with AUVs, and finally, seafloor observations and experimentation using HOVs and ROVs. A demonstration of the power of such an approach occurred on a cruise to the Gala´pagos Rift in 2002. The investigative strategy was directed toward ensuring that all potential sites of hydrothermal venting in the rift valley were identified and investigated visually with the HOV Alvin. The AUV ABE was deployed at night to conduct highresolution mapping of the seafloor and collect conductivity–temperature–depth (CTD) data in the lower water column to detect sites of venting. Upon its recovery in the morning, micro-bathymetry maps and temperature anomaly maps were quickly generated, compiled with previous data, and then given to the scientists diving in Alvin that day for their use in directing the dive. Today, the vehicles are being deployed in various combinations to attack a range of multidisciplinary problems. Deep-sea vehicles will also play indispensable roles in establishing and servicing long-term seafloor observatories that will be critical for time-series investigations to understand the dynamic processes going on beneath the ocean. AUVs will undertake a variety of mapping and sampling missions while using fixed observatory installations to recharge batteries, offload data, and receive new instructions. They will be used to extend the spatial observational capability of seafloor observatories through surveying activities, and will document horizontal variability in seafloor and water column properties – necessary for establishing the context of point measurements made by fixed instrumentation. HOVs and ROVs will be required to install, service, and repair equipment and instrumentation on the seafloor and in drill holes, as well as collect samples as part of time-series measurements. The additional capabilities that these vehicles will need for service
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and repair activities will likely build on ROV tools that are currently being used in the commercial undersea cable industry. Deep-sea vehicles will clearly have a role to play in deep-sea research for the foreseeable future, and they will be at the vanguard of a new era of ocean exploration.
See also Dispersion from Hydrothermal Vents. Gliders. Hydrothermal Vent Biota. Hydrothermal Vent Deposits. Hydrothermal Vent Ecology. Hydrothermal Vent Fauna, Physiology of. Hydrothermal Vent Fluids, Chemistry of. Platforms: Autonomous Underwater Vehicles.
National Research Council (2004) Future Needs of Deep Submergence Science. Washington, DC: National Academies Press. Reves-Sohn R (2004) Unique vehicles for a unique environment. Oceanus 42: 25--27. Rona P (2001) Deep-diving manned research submersibles. Marine Technology Society Journal 33: 13--25. Rudnick DL, Davis RE, Eriksen CC, Fratantoni DM, and Perry MJ (2004) Underwater gliders for ocean research. Marine Technology Society Journal 38: 48--59. Shank T, Fornari D, Yoerger D, et al. (2003) Deep submergence synergy: Alvin and ABE explore the Gala´pagos Rift at 86 1 W. EOS, Transactions of the American Geophysical Union 84(425): 432--433. Yoerger D, Bradley AM, Walden BB, Singh H, and Bachmayer R (1998) Surveying a subsea lava flow using the Autonomous Benthic Explorer (ABE). International Journal of Systems Science 29: 1031--1044.
Relevant Websites Further Reading Bachmayer R, Humphris S, Fornari D, et al. (1998) Oceanographic exploration of hydrothermal vent sites on the Mid-Atlantic Ridge at 371 N 321 W using remotely operated vehicles. Marine Technology Society Journal 32: 37--47. Davis RE, Eriksen CE, and Jones CP (2002) Autonomous buoyancy-driven underwater gliders. In: Griffiths G (ed.) The Technology and Applications of Autonomous Underwater Vehicles, pp. 37--58. London: Taylor and Francis. De Moustier C, Spiess FN, Jabson D, et al. (2000) Deep-sea borehole re-entry with fiber optic wireline technology. Proceedings of the 2000 International Symposium on Underwater Technology, Tokyo, 23–26 May 2000, pp. 379–384. Fornari D (2004) Realizing the dreams of da Vinci and Verne. Oceanus 42: 20--24. Fornari DJ, Humphris SE, and Perfit MR (1997) Deep submergence science takes a new approach. EOS, Transactions of the American Geophysical Union 78: 402--408. Fryer P, Fornari DJ, Perfit M, et al. (2002) Being there: The continuing need for human presence in the deep ocean for scientific research and discovery. EOS, Transactions of the American Geophysical Union 83(526): 532--533. Funnell C (2004) Jane’s Underwater Technology 2004– 2005, 800pp, 23rd edn. Alexandria, VA: Jane’s Information Group. National Research Council (2004) Exploration of the Seas: Voyage into the Unknown. Washington, DC: National Academies Press.
http://auvlab.mit.edu – AUV Lab Vehicles, AUV Lab at MIT Sea Grant. http://www.ropos.com – Canadian Scientific Submersible Facility. http://www.comra.org – China Ocean Mineral Resources R&D Association. http://divediscover.whoi.edu – Dive and Discover: Expeditions to the Seafloor. http://www.soest.hawaii.edu – Hawai’i Undersea Research Laboratory (HURL), School of Ocean and Earth Science and Technology. http://www.ifremer.fr – IFREMER Fleet. http://www.mbari.org – Marine Operations: Vessels and Vehicles, Monterey Bay Aquarium Research Institute. http://www.mpl.ucsd.edu – Marine Physical Laboratory, Scripps Institution of Oceanography. http://www.noc.soton.ac.uk – National Oceanography Centre, Southampton. http://www.jamstec.go.jp – Research Vessels, Facilities, and Equipment, JAMSTEC. http://www.apl.washington.edu – Seaglider, Applied Physics Laboratory, University of Washington. http://www.whoi.edu – Ships and Technology: National Deep Submergence Facility, Woods Hole Oceanographic Institution. http://www.rcom.marum.de – Technology page, MARUM.
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VIRAL AND BACTERIAL CONTAMINATION OF BEACHES J. Bartram, World Health Organization, Geneva, Switzerland H. Salas, CEPIS/HEP/Pan American Health Organization, Lima, Peru A. Dufour, United States Environmental Protection Agency, OH, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3157–3166, & 2001, Elsevier Ltd.
Introduction Interest in the contamination of beaches by microbes is driven by concern for human health. The agents of concern are human pathogens, microorganisms capable of causing disease. Most are derived from human feces; therefore disposal of excreta and waterborne sewage are of particular importance in their control. Pathogens derived from animal feces may also be significant in some circumstances. The human population of concern constitutes primarily the recreational users, whether local residents, visitors, or tourists. Recreational use of natural waters (including coastal waters) is common worldwide and the associated tourism may be an important component of local and/or national economy. Scientific underpinning and insight into public health concern for fecal pollution of beaches developed rapidly from around 1980. Approaches to regulation and control (including monitoring) have yet to respond to the increased body of knowledge, although some insights into potential approaches are available. This article draws heavily on two recent substantial publications: the World Health Organization Guidelines for Safe Recreational Water Environment, released as a ‘draft for consultation’ in 1998, and Monitoring Bathing Waters by Bartram and Rees, published in 2000.
Public Health Basis for Concern Recreational waters typically contain a mixture of pathogenic (i.e., disease-causing) and nonpathogenic microbes derived from multiple sources. These sources include sewage effluents, non-sewage excreta disposals (such as septic tanks), the recreational user population (through defecation and/or shedding), industrial processes (including food processing, for
example), farming activities (especially feed lots and animal husbandry), and wildlife, in addition to the indigenous aquatic microflora. Exposure to pathogens in recreational waters may lead to adverse health effects if a suitable quantity (infectious dose) of a pathogen is ingested and colonizes (infects) a suitable site in the body and leads to disease. What constitutes an infectious dose varies with the agent (pathogen) concerned, the form in which it is encountered, the conditions (route) of exposure, and host susceptibility and immune status. For some viruses and protozoa, this may bevery few viable infectious particles (conceptually one). The infectious dose for bacteria varies widely from few particles (e.g., some Shigella spp., the cause of bacillary dysentery) to large numbers(e.g. 108 for Vibrio cholerae, the cause of cholera). In all cases it is important to recall that microorganisms rarely exist as homogeneous dispersions in water and are often aggregated on particles, where they may be partially protected from environmental stresses and as a result of which the probability of ingestion of an infectious dose is increased. Transmission of disease through recreational water use is biologically plausible and is supported by a generalized dose–response model and the overall body of evidence. For infectious disease acquired through recreational water use, most attention has been paidto diseases transmitted by the fecal–oral route, in which pathogens are excreted in feces, are ingested by mouth, and establish infection in the alimentary canal. Other routes of infectious disease transmission may also be significant as a result of exposure though recreational water use. Surface exposure can lead to ear infections and inhalation exposure may result in respiratory infections. Sewage-polluted waters typically contain a range of pathogens and both individuals and recreational user populations are rarely limited to exposure to a single encounter with a single pathogen. The effects of multiple and simultaneous or consecutive exposure to pathogens remain poorly understood. Water is not a natural ambient medium for the human body, and use of water (whether contaminated or not) for recreational purposes may compromise the body’s natural defenses. The most obvious example of this concerns the eye. Epidemiological studies support the logical inference that
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recreational water use involving repeated immersion will increase the likelihood of eye infection through compromising natural resistance mechanisms, regardless of the quality of the water. On the basis of a review of all identified and accessible publications concerning epidemiological studies on health outcomes associated with recreational water exposure, the WHO has recently concluded the following:
•
•
• •
The rate of occurrence of certain symptoms or symptom groups is significantly related to the count of fecal indicator bacteria. An increase in outcome rate with increasing indicator count is reported in most studies. Mainly gastrointestinal symptoms (including ‘highlycredible’ or ‘objective’ gastrointestinal symptoms) are associated with fecal indicator bacteria such as enterococci, fecal streptococci, thermotolerant coliforms and Escherichia coli. Overall relative risks for gastroenteric symptoms of exposure to relatively clean water lie between 1.0 and 2.5. Overall relative risks of swimming in relatively polluted water versus swimming in clean water vary between 0.4 and 3.
•
•
Many studies suggest continuously increasing risk models with thresholds for various indicator organisms and health outcomes. Most of thesuggested threshold values are low in comparison with the water qualities often encountered in coastal waters used for recreation. The indicator organisms that correlate best with health outcome are enterococci/fecal streptococci for marine and freshwater, and E.coli for freshwater. Other indicators showing correlation are fecal coliforms and staphylococci. The latter may correlate with density of bathers and were reported to be significantly associated with ear, skin, respiratory, and enteric diseases.
In assessing the adequacy of the overall body of evidence for the association of bathing water quality and gastrointestinal symptoms, WHO referred to Bradford Hill’s criteria forcausation in environmental studies (Table 1). Seven of the nine criteria were fulfilled. The criterion on specificity of association was considered inapplicable because the etiological agents were suspected to be numerous and relatively outcome-nonspecific. Results of experiments on the impact of preventive actions on health outcome frequency have not been reported.
Table 1 Criteria for causation in environmental studies (according to Bradford Hill, 1965). Application to bathing water quality and gastrointestinal symptoms
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This degree of fulfillment suggests that the association is causal. Because of the study areas used, especially for the available randomized controlled trials, the results are primarily indicated for adult populations in temperate climates. Greater susceptibility among younger age groups has been shown and the overall roles of endemicity and immunity in relation to exposure and response are inadequately understood. The overall conclusions of the work of WHOconcerning fecal contamination of recreational waters and the different potential adverse health outcomes among user groups were as follows:
•
•
•
•
• •
The overall body of evidence suggests a casual relationship between increasing exposure to fecal contamination and frequency of gastroenteritis. Limited information concerning the dose–response relationships narrows the ability to apply cost–benefit approaches to control. Misclassification of exposure is likely to produce artificially lowthreshold values in observational studies. The one randomized trial indicated a higher threshold of 33 fecal streptococci per 100 ml for gastrointestinal symptoms. A cause–effect relationship between fecal pollution or bather-derived pollution and acute febrile respiratory illness is biologically plausible since associations have been reported and a significant exposure–response relationship with a threshold of 59 fecal streptococci per 100 ml was reported. Associations between ear infections and microbiological indicators of fecal pollution and bather load have been reported. A significant dose–response effect has been reported in one study. A cause–effect relationship between fecal or bather derived pollution and ear infection is biologically plausible. Increased rates of eye symptoms have been reported among bathers and evidence suggests that bathing, regardless of water quality, compromises the eye’s immune defenses. Despite biological plausibility, no credible evidence is available for increased rates of eye ailments associated with water pollution. No credible evidence is available for an association of skin disease with either water exposure or microbiological water quality. Most investigations have either not addressed severe health outcomes such as hepatitis, enteric fever, or poliomyelitis or have not been undertaken in areas of low or zero endemicity. By inference, transmission of enteric hepatitis viruses and of poliomyelitis – should exposure of
269
susceptible persons occur – is biologically plausible, and one study reported enteric fever (typhoid) causation. The WHO work of 1998 led to the derivation of draft guideline values as summarized in Table 2.
Sources and Control The principal sources of fecal pollution are sewage (and industrial) discharges, combined sewer overflows, urban runoff, and agriculture. These may lead to pollution remote from their source or point of discharge because of transport in rivers or through currents in coastal areas or lakes. The public health significance of any of these sources may be modified by a number of factors, some of which provide management opportunities for controlling human health risk. With regard to public health, most attention has, logically, been paid to sewage as the source of fecal pollution. Pollution abatement measures for sewage may be grouped into three disposal alternatives, although there is some variation within and overlap between these: treatment, dispersion through sea outfalls, and discharge not to surface water bodies(e.g., to agriculture or ground water injection). Where significant attention has been paid to sewage management, it has often been found that other sources of fecal contamination are also significant. Most important among these are combined sewer overflows (and ‘sanitary sewer’ overflows) and riverine discharges to coastal areas and lakes. Combined sewer overflows(CSOs) generally operate as a result of rainfall. Their effect is rapid and discharge may be directly to areas used for recreation. Riverine discharge may derive from agriculture, from upstream sewage discharges (treated or otherwise), and from upstream CSOs. The effect may be continuous (e.g., from upstream sewage treatment) or rainfallrelated (agricultural runoff, urban runoff, CSOs). Where it is rainfall-related, the effect on downstream recreational water use areas may persist for several days. In river systems the decrease in microbiological concentrations downstream of a source (conventionally termed ‘die-off’) largely reflects sedimentation. After settlement in riverbed sediments, survival times are significantly increased and re-suspension will occur when river flow increases. Because of this and the increased inputs from sources such as CSOs and urban and agricultural runoff during rainfall events, rivers may demonstrate a close correlation between flow and bacterial indicator concentration.
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Table 2
Draft guideline values for microbiological quality of marine recreational waters (fecal streptococci per 100 ml)
The efficiency of removal of major groups of microorganisms of concern in various types of treatment processes is described in Table 3. Advanced sewage treatment (for instance based upon ultrafiltration or nanofiltration) can also be effective in removal of viruses and other pathogens. The role and efficiency of ultraviolet light, ozone, and other disinfectants are being critically re-evaluated. Treatment in oxidation ponds may remove significant numbers of pathogens, especially the larger protozoan cysts and helminth ova. However, short-circuiting due to poor design, thermal gradients, or hydraulic overload may reduce residence time from the typical design range of 30–90 days.
During detention in oxidation ponds, pathogens are removed or inactivated by sedimentation, sunlight, temperature, predation, and time. Disposal of sewage through properly designedlong-sea outfalls provides a high degree of protection for human health, minimizing the risk that bathers will come into contact with sewage. In addition, long-sea outfalls reduce demand on land area in comparison with treatment systems, but they may be considered to have unacceptable environmental impacts (for instance, nutrient discharge into areas wheredilution or flushing is limited). They tend to have high capital costs, although these are comparable to those of land-based treatment systems
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Table 3
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Pathogen removal during sewage treatment
depending on the degree of treatment, whereas recurrent costs are relatively much lower. Ludwig (1988) has presented a comparison of costs and ecological impacts of long-sea outfalls versus treatment levels. Diffuser length, depth, and orientation, as well as the area and spacing of ports are key design considerations. Pathogens are diluted and dispersed and suffer die-off in the marine environment. These are major considerationsin length of outfall and outfall locations. Pretreatment by screening removes large particulates and ‘floatables’. Grease and oil removal are also often undertaken. Re-use of wastewater and groundwater recharge are two methods of sewage disposal that have minimal impact upon recreational waters. Especially in arid areas, sewage can be a safe and important resource (of water and nutrients) used for agricultural purposes such as crop irrigation. Direct injection or infiltration of sewagefor ground water recharge generally presents very low risk for human healththrough recreational water use. Control of human health hazards associated with recreational use of the water environment may be achieved through control of the hazard itself (that is, pollution control) or through control of exposure. Fecal pollution of recreational waters may be subject to substantial variability whether temporally (e.g., time-limited changes in response to rainfall) or spatially (e.g., because, as aresult of the effects of discharge and currents, one part of a beach may behighly contaminated while another part is of good quality). This temporaland spatial variability
provides opportunities to reduce human exposure while pollution control is planned or implemented or in areas where pollution control cannot or will not be implemented for reasons such as cost. The measures used may include public education, control/ limitation of access, or posting of advisory notices; they are often relatively affordable and can be implemented relatively rapidly.
Monitoring, Assessment and Regulation Present regulatory schemes for the microbiological quality of recreational water are primarily or exclusively based upon percentage compliance with fecal indicator counts(Table 4). These regulations and standards have had some success in driving cleanup, increasing public awareness, and contributing to improved personal choice. Not withstanding these successes, a number of constraints are evident in established approaches to regulation and standardsetting:
• • •
Management actions are retrospective and can only be deployed after human exposure to the hazard. The risk to human health is primarily from human feces, the traditional indicators of which may also derive from other sources. There is poor interlaboratory and international comparability of microbiological analytical data.
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VIRAL AND BACTERIAL CONTAMINATION OF BEACHES
Table 4
Microbiological quality of water guidelines/standards per100 mli
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VIRAL AND BACTERIAL CONTAMINATION OF BEACHES
Table 5
273
Risk potential to human health through exposure tosewage
Treatment
Discharge type
Nonec Preliminary Primary (including septic tanks) Secondary Secondary plus disinfection Tertiary Tertiary plus disinfection Lagoons
Directly on beach
Short outfalla
Effective outfallb
Very high Very high Very high High Medium Medium Very Low High
High High High High Medium Medium Very Low High
NA Low Low Low Very Low Very Low Very Low Low
a
The relative risk is modified by population size. Relative risk is increased for discharges from large populations and decreased for discharges from small populations. b This assumes that the design capacity has not been exceeded and that climatic and oceanic extreme conditions are considered in the design objective (i.e., no sewage on the beach zone). c Includes combined sewer overflows. NA, not applicable. Reproduced with permission from Bartram and Rees (2000).
Table 6
Risk potential to human health through exposure to sewage through riverine flow and discharge
Dilution effecta,
b
High population with low river flow Low population with low river flow Medium population with medium river flow High population with high river flow Low population with high river flow
Treatment level None
Primary
Secondary
Secondary plus disinfection
Lagoon
Very high Very high High High High
Very high High Medium Medium Medium
High Medium Low Low Very low
Low Very Very Very Very
Medium Medium Low Low Very low
low low low low
a The population factor includes all the population upstream from the beach to be classified and assumes no instream reduction in hazard factor used to classify the beach. b Stream flow is the 10% flow during the period of active beach use. Stream flow assumes no dispersion plug flow conditions to the beach. Reproduced with permission from Bartram and Rees (2000).
•
While beaches are classified as ‘safe’ or ‘unsafe’, there is a gradient of increasing frequency and variety of adverse health effects with increasing fecal pollution and it is desirable to promote incremental improvements by prioritizing ‘worst failures’.
The present form of regulation also tends to focus attention upon sewage, treatment, and outfall management as the principal or only effective solutions. Owing to high costs of these measures, local authorities may be effectively disenfranchised and few options for effective local intervention in securing bather safety appear to be available. A modified approach to regulation of recreational water quality could provide for improved protection of public health, possibly with reduced monitoring effort and greater scope for interventions, especially
within the scope for local authority intervention. This was discussed in detail at an international meeting of experts in 1998 leading to the development of the ‘Annapolis Protocol’. Table 7 Risk potential to human health through exposure to sewage from bathers Bather shedding
Category
High bather density, high dilutiona Low bather density, high dilution High bather density, low dilutiona, b Low bather density, low dilutionb
Low Very low Medium Low
a Move to next higher category if no sanitary facilities are available at beach site. b If no water movement. Reproduced with permission from Bartram and Rees (2000).
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VIRAL AND BACTERIAL CONTAMINATION OF BEACHES
Table 8
Possible sewage contamination indicators and their functions
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VIRAL AND BACTERIAL CONTAMINATION OF BEACHES
The ‘Annapolis Protocol’requires field-testing and improvement based upon the experience gained before application. Its application leads to a classification scheme through which a beach may be assigned to a class related to health risk. By enabling local management to respond to sporadic or limited areas of pollution (and thereby to upgrade the classification of a beach), it provides significant incentive for local management action as well as for pollution abatement. The protocol recognizes that a large number of factors can influence the safety of a given beach. In order to better reflect risk to public health, the classification scheme takes account of three aspects: 1. Counts of fecal indicator bacteria in samples collected from the water adjoining the beach. 2. An inspection-based assessment of the susceptibility of the area to direct influence from human fecal contamination. 3. Assessment of the effectiveness of management interventions if they are deployed to reduce human exposure at times or in places of increased risk. The process of beach classification is undertaken in two phases: 1. Initial classification based upon the combination of inspection-based assessment and the results of microbiological monitoring. 2. Taking account of the management interventions. Inspection-based assessment takes account of the three most important sources of human fecal contamination for public health: sewage (including CSO and storm water discharges); riverine discharges where the river is receiving water from sewage
275
discharges and is used either directly for recreation or discharges near a coastal or lake area used for recreation; and bather-derived contamination. The result of assessment is an estimate of relative risk potential in bands as outlined in Tables 5, 6 and 7 Use of microbial and nonmicrobial indicators of fecal pollution requires an understanding of their characteristics and properties and their applicability for different purposes. Some very basic indicators such as sanitary plastics and grease in marine environments may be used for some purposes under some circumstances. Some newer indicators areunder extensive study, but conventional fecal indicator bacteria remain those of greatest importance. Indicators of fecal contamination and their principal uses are summarized in Table 8. By combining the results of microbiological testing with those of inspection, it is possible to derive a primary beach classification using a simple lookup table of the type outlined in Table 9. This primary classification may be modified to take account of management interventions that reduce or prevent exposure at times when or in areas where pollution is unusually high. Such ‘reclassification’ requires a database adequate to describe the times or locations of elevated contamination and demonstration that management action is effective. Since this ‘reclassification’ may have significant economic importance, independent audit and verification may be appropriate. Implementation of a monitoring and assessment scheme of the type envisaged in the Annapolis Protocol would belikely to have a significant impact upon the nature and cost of monitoring activities. In comparison with established practice, it would typically involve a greater emphasis on inspection and relatively less on sampling and analysis than
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VIRAL AND BACTERIAL CONTAMINATION OF BEACHES
Table 9
Primary classification matrix
Sanitary inspection category (susceptibility to fecal influence)
Very low Low Moderate High Very high
Microbiological assessment category (indicator counts)
A
B
C
D
E
Excellent Excellent Gooda Gooda Faira
Excellent Good Good Faira Faira
Good Good Fair Fair Poora
Good ( þ ) Fair Fair Poor Very poor
Fair ( þ ) Fair ( þ ) Poor Very poor Very poor
a
Unexpected result requiring verification. ( þ ) implies non-sewage sources of fecal indicators (e.g., livestock) and this should be verified. Reproduced with permission from Bartram and Rees (2000).
is presently common place. At the level of an administrative area with a number of diverse beaches, it would imply an increased short-term monitoring effort when beginning monitoring, but a decreased overall workloadin the medium to longterm. Recreational use of the water environment provides benefits as well as potential dangers for human health andwell-being. It may also create economic benefits but can add tocompeting local demands upon a finite and sometimes already over-exploited local environment. Regulation, monitoring, and assessmentof areas of coastal recreational water use should be seen or undertaken not in isolation but within this broader context. Integrated approaches to management that take account of overlapping, competing, and sometimes incompatible uses ofthe coastal environment have been increasingly developed and applied in recent years. Extensive guidance concerning integrated coastal management is now available. However, recreational use of coastal areas is also significantly affected by river discharge and therefore upstream discharge and land use practice. While the need to integrate management around the water cycle is recognized, no substantial experience has yet accrued and tools for its implementation remain unavailable.
See also Pollution: Approaches to Pollution Control. Sandy Beaches, Biology of.
Further Reading Bartram J and Rees G (eds.) (2000) Monitoring Bathing Waters. London: EFN Spon. Bradford-Hill A (1965) The environment and disease: association or causation? Proceedings of the Royal Society of Medicine 58: 295--300. Esrey S, Feachem R, and Hughes J (1985) Interventions for the control of diarrhoeal diseases among young children: improving water supplies and excreta disposal facilities. Bulletin of the World Health Organization 63(4): 757--772. Ludwig RG (1988) Environmental Impact Assessment. Siting and Design of Submarine Outfalls. An EIA Guidance Document. MARC Report No. 43. Geneva: Monitoring and Assessment Research Centre/World Health Organization. Mara D and Cairncross S (1989) Guidelines for the Safe Use of Wastewater and Excreta in Agriculture and Aquaculture. Geneva: WHO. WHO (1998) Guidelines for Safe Recreational-water Environments: Coastal and Freshwaters. Draft for Consultation. Document EOS/DRAFT/98.14 Geneva: World Health Organization.
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VOLCANIC HELIUM J. E. Lupton, Hatfield Marine Science Center, Newport, OR, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3166–3173, & 2001, Elsevier Ltd.
Introduction Volcanic activity along the global mid-ocean ridge system and at active seamounts introduces a heliumrich signal into the ocean basins that can be used to trace patterns of ocean circulation and mixing. Helium is extracted from oceanic volcanic rocks by circulating sea water and then injected into the ocean as helium dissolved in submarine hydrothermal vent fluids. Hydrothermal venting produces plumes in the ocean that are highly enriched in a variety of tracers, including heat, helium, manganese, iron, methane, and hydrogen. Among these, volcanic helium is a particularly useful tracer because it has such a high concentration in hydrothermal fluids relative to the background values ofhelium in sea water, and because it is stable and conservative, i.e., helium does not decay radioactively and is not affected by any chemical or biological processes. By making careful measurements of the relative abundance of heliumisotopes, it is possible to trace hydrothermal helium plumes for thousands of kilometers from the source regions. There are two stable isotopes of helium, 3He and 4 He, which vary in their ratio by over three orders of magnitude in terrestrial samples. The Earth’s atmosphere is well mixed with respect to helium and contains helium with a uniform isotopic composition of 3He/4He ¼ 1.39 106. Atmospheric helium is a convenient standard for helium isotope determinations, and terrestrial 3He/4He ratios are usually normalized to the air ratio and expressed in units of R=RA , where R ¼ 3He/4He and RA ¼ ð3 He=4 HeÞair . In contrast to atmospheric helium (R=RA ¼ 1), the radiogenic helium produced by a-decay of U and Th series isotopes has a much lower ratioof R=RA 0:1, while the volcanic helium that is derived from the Earth’s mantle is highly enriched in 3He (R=RA ¼ 5230). Thus volcanic helium has an isotopic composition distinct from other sources such as atmospheric helium or the helium produced by radioactive decay. This 3He-rich mantle helium is sometimes called ‘primordial’ helium, since it is thought to be the remnant of a primitive component
trapped in the Earth’s interior since the time of its formation. This trapped component probably had 3 He/4He ¼ 1 104or 100 RA , similar to the helium found trapped in meteorites or in the solar wind, but has been modified to R ¼ 30RA by dilution with radiogenic helium since the time the Earth was formed. Although there is a wide variety of volcanic sources in the oceans, including subduction zone volcanoes and hot spot volcanoes, most of the oceanic volcanic helium is derived from activity along the global mid-oceanridge system. While the 3 He/4He ratio of mantle helium shows a wide range of variation, the helium from mid-ocean ridgesfalls in a much narrower range of R=RA ¼ 729. In order of decreasing importance, the most abundant forms of helium in sea water are dissolved atmospheric helium, volcanic helium, and to a lesser degree radiogenic helium from sediments. Thereis also an input of pure 3He into the oceans from tritium(3H), the radioactive isotope of hydrogen, which decays to3He with a half-life of 12.4 years. Because tritium isgenerally found only in the upper ocean, 3 He from tritium decay(tritiogenic helium) is only significant at depths less than about 1000 m. Although there are only two isotopes of helium, it is still possible to clearly distinguish submarine volcanic helium from the other components because of its high 3He/4He ratio and because volcanic helium is introduced at mid-depth rather thanat the ocean surface or on the abyssal plain. Units
For samples highly enriched in helium such as volcanic rocks and hydrothermal vent fluids, the helium isotope ratio is usually expressed in the R=RA notation described above. However, for the relatively small variations observed in sea water samples, the 3 He/4He variations are usually expressed as dð3 HeÞ, which is the percentage deviation from the ratio in air, defined as in eqn [1]. dð3 HeÞ ¼ 100½ðR=RA Þ 1
½1
Here again R ¼3 He=4 He and RA ¼ ð3 He=4 HeÞair . Thus R=RA ¼ 1:50 is equivalent to dð3 HeÞ ¼ 50%.
History and Background The first attempt to detect nonatmospheric helium in the oceans was made by Suess and Wa¨nke in 1965, who predicted that the deep oceans should contain
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278
VOLCANIC HELIUM
excess 4He due to U and Th decay in sediments and in the ocean crust. Although they were correct about the existence of radiogenic helium in the oceans, their measurements were of insufficient precision to detect any 4He enrichment above the dissolved air component. It is now known that the input of3Herich volcanic helium has a greater effect on both the3He/4He ratio and the 4He concentration insea water than does the input of radiogenic helium. Mantle or volcanic helium was first detectedon the Earth as an excess in the 3He/4He ratio indeep Pacific waters. Although this oceanic 3He excess is derived from the helium residing in oceanic volcanic rocks, it was not until about five years later that mantle helium was directly measured in the volcanic rocks themselves. Clarke et al. in 1969 reported a 21% excess in the 3He concentration at mid-depth above that expected forair-saturated water, and correctly attributed this excess to a flux ofprimordial helium leaking from the Earth’s interior into the oceans and inturn into the atmosphere (see Figure 1). Using a box model for oceanic helium, they were able to estimate the global 3He flux from the oceans into the atmosphere at 2 atoms 3He cm2, a number that isstill in reasonable agreement with more recent flux estimates of 4–5atoms 3He cm2. The discovery of excess 3He inthe oceans from localized sources distributed along the global midocean ridge system led immediately to the use of this tracer for oceanographic studies. The Geochemical Ocean Sections Study (GEOSECS), which began in 1972, provided the first maps of the global distribution of helium in the oceans. Since then, several
other oceanographic programs, including the World Ocean Circulation Experiment (WOCE), have added to our knowledge of the global helium distribution. To illustrate the presence of volcanic helium in the oceans, a typical helium profile in the north Pacific Ocean is shown in Figure 2. The figure shows thevertical variation in the 3He/4He ratio expressed as dð3 HeÞ in%, and the 4He concentration in nmol kg1. The values expected for air-saturated water (dashed lines) are shown for comparison. For the calculation of air-saturated values it is assumed that each water parcel equilibrated with the atmosphere at the potential temperature of the sample. This profile exhibits a broad maximum in the deep water, reaching avalue of dð3 HeÞ ¼ 25:0% at B1850 m depth. Although this station is located at a distance of over 1500 km from the nearest active spreading center, the profile still exhibits a clear excess in 3 He/4He in the 1500–3500 m depth range due to input of volcanic helium from the mid-ocean ridge system. The secondary maximum in the dð3 HeÞ profile at B350 m depth is due to excess 3He produced by tritium decay. That this peak is tritiogenichelium is evident because the peak in dð3 HeÞ at 350 m depth is absent from the 4He profile, indicating input of pure 3He as would be expected for tritium decay. At the ocean surface dð3 HeÞ ¼ 1:4%, which is very close to the expected value of dð3 HeÞ ¼ 1:35% for water in equilibriumwith air (3He is slightly less soluble in water than4He). The absolute 4He concentration (Figure 2B) also increases with depth, but not as dramatically as the 3 He/4He ratio. Part of the 4He increase is due to the
Helium escape
3
Interplanetary space
_6
4
He/ He = 10
Atmosphere
Oceans U, Th decay 3
4
_7
He/ He = 10
Ocean current Crust
3
4
_5
He/ He = 10
Mantle
Figure 1 A schematic of the terrestrial helium budget, indicating the flux of helium from the Earth’s mantle into the oceans, and in turn into the atmosphere.
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VOLCANIC HELIUM 3
0
He (%) 10
4
20
30
1.6
279
_1
He (nmol kg ) 1.9 1.7 1.8
2.0
0
Depth (m)
_1000
_2000
_3000
_ 4000
_ 5000 (B)
(A)
Figure 2 A typical helium profile collected at 28.51N, 121.61W in the north Pacific Ocean. (A) The 3He/4Heratio expressed as dð3 HeÞ% plotted versus depth. The sharppeak at B350 m depth is due to tritium decay, while the broad maximum centered at B2000 m depth is due to volcanic helium introduced along themid-ocean ridge system. The dashed line represents the dð3 HeÞ for sea water in equilibrium with air. (B) The 4He concentration plotted versus depth for the same samples. The dashed line represents the 4He concentration expected for sea water in equilibrium with air.
higher solubility of heliumin the colder deep waters, as shown by the expected solubility values for airsaturated water (dashed line). However, much of the4He excess above solubility equilibrium is due to the finite amountof 4He present in the volcanic helium signal. At B2500 m depth, the profile has 4 He ¼ 1.92 nmol kg1, about 10%higher than the value of 1.75 nmol kg1 for air-saturated water at those conditions. The distinct isotopic signature of oceanic volcanic helium can be seen by plotting the 3He concentration versus the 4He concentration as shown in Figure 3. In this plot the slope of the trends corresponds to the isotopic ratio of the end-member helium that has been added to the water samples. The thin solid line corresponds to the atmospheric ratio (3He/4He ¼ 1.39 106 or R=RA ¼ 1), and addition of air would cause the values to migrate along this line. As expected, the range of equilibrium solubility values falls directly on the atmospheric line. Although the measured samples (filled circles) near the ocean surface also fall on this line, the deeper samples fall off the atmospheric trend, defining a much steeper slope. This steeper slope is direct evidence that the helium
that has been added tothe deep ocean has a higher 3 He/4He ratio than air.
Mid-ocean Ridge Helium The input of volcanic helium has affected the helium content of all the major ocean basins, although the magnitude of this effect varies greatly. To a large degree, the amount of the excess volcanic helium in each of the ocean basins is controlled by the relative strength of the hydrothermal input, which is in turn roughly proportional to the spreading rate of the ridges. In the Pacific Ocean, where the fastest ridge-crest spreading rates are found, the 3He/4He values at mid-depth average dð3 HeÞ ¼ 20% for the entire Pacific basin (Figure 4). The Indian Ocean, which has ridges spreading at intermediate rates, has dð3 HeÞ values averaging about 10–15%. Finally, the Atlantic Ocean, which is bisected by the slow-spreading Mid-Atlantic Ridge, has the lowest 3He enrichments, averaging dð3 HeÞ ¼ 025% (Figure 4).
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VOLCANIC HELIUM
3.5
3.0
Range of equilibrium solubility
4228 m
_1
He (fmol kg )
It has been recognized for several decades that the distribution of mantle 3He has great potential for delineating the patterns of circulation and mixing of deep and intermediate water masses. This potential is probably greatest in the Pacific Ocean, becauseof the strong 3He signal in that ocean. The helium field atmid-depth in the Pacific has been mapped in considerable detail (Figure 5). This work has identified several distinct helium plumes emanating from active hydrothermal systems distributed along the midocean ridges. In the eastern equatorial Pacific, two jets of helium-rich water originate at latitude 101N and at 141S on the crest of the East Pacific Rise (EPR)and protrude westward into the interior of the basin. Between these two helium jets there is a minimum in the 3He signal on the Equator. This distinct pattern in the helium distribution requires westward transport atmid-depth in the core of these helium plumes, and suggests eastward transport on the Equator (see dashed arrows in Figure 5). A separate helium plume is present in the far northeast Pacific produced by input on the Juan de Fuca and Gorda Ridges(JdFR). Although this helium signal is weaker than the helium plumes from the EPR, the JdFR helium is still traceable as a distinct plume that trends south-west into the interior of the north Pacific basin. Farther south at B201N, a low-3He tongue penetrates from the west, implying eastward transport at this latitude. Thus the helium field defines a cyclonic (clockwise) circulation pattern at B2000 mdepth in the northeast Pacific.
1852 m
R =RA
2.5
3
13 m 2.0
1.5 1.5
1.6
1.7 4
1.9
1.8
_1
2.0
He (nmol kg )
Figure 3 The 3He concentration (in fmol kg1 or 1015 mol kg1) plotted versus 4He concentration (in nmol kg1or 109 mol kg1) for the samples shown in Figure 2. In this plot the slope of any trend corresponds to the isotopic ratio of the end-member helium that has been added to the water samples. The depths in meters of three representative samples are indicated. The thick solid line represents the range of equilibrium solubility values expected for air saturated water (Weiss, 1970; 1971). As expected, the equilibrium solubility values fall on the thin solid line, which is the mixing relation expected for air helium (R ¼ RA ). The steep slope of the dashed line, which isa best fit to the sea water samples, indicates that helium with an elevated 3He/4He ratio (R4RA ) has been added.
30
Slow Intermediate Fast
25
15
30 35
40
<5
35
20
25
5
20 15 10
10
Figure 4 Map of dð3 HeÞ% at mid-depth in the world ocean. The location of the mid-ocean ridges is shown, and the relative spreading rate is indicated by the width of the lines.
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VOLCANIC HELIUM
281
JdFR GEOSECS WOCE, NOAA, Helios
40°N
20°N
Latitude
34
26
0°
? ?
EPR
20°S 18
26
26
40°S
18
26
10
18
60°S 140°E
160°E
160°W 140°W Longitude
180°
120°W
100°W
80°W
Figure 5 Map of dð3 HeÞ% contoured on a surface at 2500 m depth in the Pacific. Contour interval is 4%. The major helium sources lie along the East Pacific Rise (EPR) and the Juan de Fuca Ridge (JdFR) systems. The dashed arrows indicate areas where the helium plumes define regional circulation patterns. Data along WOCE lines P4 and P6 are from Jenkins (unpublished data). All other data are from Lupton (1998).
60°N WOCE P1 WOCE P2 WOCE P4 (WHOI) WOCE P16 (WHOI) WOCE P17N WOCE P17C WOCE P18 WOCE P19 CGC-91 DISCO S94F
50°N
Latitude
40°N
30°N
20 22
20°N 18
22
10°N
140°E
160°E
180°
160°W Longitude
140°W
120°W
100°W
Figure 6 Map of dð3 HeÞ% contoured on a surface at 1100 m depth in the north Pacific, showing the broad lateral extent of a helium plume emanating from Loihi Seamount on the south-eastern flank of the Island of Hawaii. As indicated in the key, data are from several different expeditions.
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VOLCANIC HELIUM
Hot Spot Helium
the Hawaiian-Emperor seamount chain. Unlike midocean ridges, which are submarine, many hot spot volcanoes are subaerial and do not necessarily have direct input into the oceans. Furthermore, hot spot volcanoes have not been explored extensively for their volcanic and hydrothermal activity. Nevertheless, there are several known examples of submarine hydrothermal input at hot spots. Macdonald Seamount in the south Pacific has active vents on its
In addition to the volcanism along the global midocean ridge system, the oceans are also affected by hot spot volcanoes. Over 100 hot spots have been identified on the Earth’s surface,and many of them are located within the ocean basins. One of the bestknown examples is the Hawaiian hot spot, which over time has generated the Hawaiian Islands and 34°S
(A) Stn 56
35°S
36°S Stn 7 37°S
38°S North Island 39°S 174°E
(A)
175°E
177°E
176°E
178°E
180°E
179°E
Station no. 8
7 64
63
15 16
62
20 21
19
61
26
60
36
41,42,43 50 59 39 44 45 54 48 49 56
(B)
_ 0.5 6060 30 20 16 8
Depth (km)
_ 1.0
8
0
4
4
4
8
8
_ 1.5
12
2
16
6
12 16
20
_ 2.0
Healy 20
Rumble III
_ 2.5
_ 3.0
(B)
Tangaroa
Rumble V
Silent II
_ 36.4°S
Brothers
Rumble II East
Clark
_ 36.2°S
_ 36.0°S
_ 35.8°S
_ 35.6°S
_ 35.4°S
_ 35.2°S
_ 35.0°S
_ 34.8°S
Latitude
Figure 7 (A) Map showing location of hydrographic stations along the southern end of the Kermadec Arc northeast of New Zealand. (B) dð3 HeÞ% contoured in section view along the southern end of the Kermadec Arc, showing 3He-rich water-column plumes emanating from several of these subduction zone volcanoes. From de Ronde et al. (2000).
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VOLCANIC HELIUM
summit that inject volatiles into the overlying water column at a depth of B130 m. Loihi Seamount, situated on the south-eastern flank of the island of Hawaii, also has active ventsnear its summit at a depth of B1000 m. Loihi is of considerable importance because it is thought to be the current locus of the Hawaiian hot spot. Loihi lavas and hydrothermal fluids contain helium with a very primitive signature ofR=RA ¼ 25230, indicating a deep mantle origin. It has been known for some time that hydrothermal venting on Loihi Seamount produces water column plumes that can bedetected with tracers such as temperature, manganese, iron, and methane. However, these tracers are not useful for far-field studies of the Loihi plume because they are either rapidly removed from the water column or arepresent in low concentrations. Because helium is a stable, conservative tracerthat is highly enriched in Loihi vent fluids, the helium signal from Loihi is detectable at considerable distances from the Hawaiian Islands. As shown in Figure 6, a map of dð3 HeÞ on a surface at 1100 m depth reveals a 3Herich plume that extends eastward from the Hawaiian Islands for several thousand kilometers, reaching the coast of Mexico at its greatest extent. This far-field plume produced by the Hawaiian hot spot clearly defines an eastward transport at B1000 m depth in this region ofthe north Pacific. Furthermore, because the end-member helium introduced at Loihi has a 3 He/4He ratio three times higher than mid-ocean ridge helium, it should be possible to distinguish the Loihihelium from mid-ocean ridge helium with accurate measurements of3He and 4He concentrations. The ability to distinguish hot spot helium from midocean ridge helium has been demonstrated for the Loihi helium plume near Hawaii but not yet in the far-field.
Subduction Zone Helium Submarine volcanism also occurs alongconvergent margins, particularly in regions where two oceanic plates are converging. However, very little is known about the incidence of submarine hydrothermal activity associated with this type of volcanism. Studies of subaerial volcanoes at convergent margins have shown that these volcanoes emit mantle helium with an isotopic ratio of R=RA ¼ 327, lower than in midocean ridges. Thus the volcanic helium from subduction zones represents a third type of mantle helium that isisotopically distinct from mid-ocean ridge and hot spot helium. One clear example of oceanic helium plumesfrom subduction zone volcanism is shown in Figure 7,
283
which shows the results of a survey along the southern end of the Kermadec Arc northeast of New Zealand. The Kermadec Arc consists of a series of discrete volcanoes generated by the subduction of the Pacific plate beneath the Australian plate. At the southern end of the arcthese volcanoes are submarine, while farther north some of them are subaerial volcanoes, including Curtis Island, Macauley Island, and Raoul Island. The survey shown in Figure 7 consisted of a series of hydrographic casts along the arc, and many of the casts were lowered directly over the summits of these arc volcanoes. The section shown in Figure 7B shows a series of 3Herich found at a variety of depths between 150 m for Rumble III volcano down to 1400 m for Brothers volcano. A plot of 3He versus 4He concentration for these samples (notshown), indicated an average 3 He/4He ratio of R=RA ¼ 6, in agreement with previous studies of helium from subaerial subduction zone volcanoes. Although the lateral extent of the helium plumes from the Kermadec Arc is not known, this survey confirms that subduction zone volcanoes do produce helium plumes that can be used to trace ocean currents. Furthermore, these subduction zone plumes are potentially quite valuable for tracer studies, since they occur at a wide variety of depths and are generally much shallower than plumes produced at mid-ocean ridges (Figure 7B).
See also Current Systems in the Atlantic Ocean. Current Systems in the Indian Ocean. Hydrothermal Vent Deposits. Hydrothermal Vent Fluids, Chemistry of. Mid-Ocean Ridge Geochemistry and Petrology. Mid-Ocean Ridge Tectonics, Volcanism, and Geomorphology. Noble Gases and the Cryosphere. Ocean Circulation. Propagating Rifts and Microplates. Seamounts and Off-Ridge Volcanism. Ocean Circulation: Meridional Overturning Circulation. Tritium–Helium Dating.
Further Reading Clarke WB, Beg MA, and Craig H (1969) Excess 3He in the sea: evidence for terrestrial primordial helium. Earth and Planetary Science Letters 6: 213--220. Craig H, Clarke WB, and Beg MA (1975) Excess 3He in deep water on the East Pacific Rise. Earth and Planetary Science Letters 26: 125--132. Craig H and Lupton JE (1981) Helium-3 and mantle volatiles in the ocean and the oceanic crust. In: Emiliani C (ed.) The Sea, vol. 7, pp. 391–428. New York: Wiley.
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Krylov A Ya, Mamyrin BA, Khabarin L, Maxina TI, and Silin Yu I (1974) Helium isotopes in ocean floor bedrock. Geokhimiya 8: 1220--1225. Lupton JE (1983) Terrestrial inert gases: isotope tracer studies and clues to primordial components in the mantle. Annual Review of Earth and Planetary Science 11: 371--414. Lupton JE (1995) Hydrothermal plumes: near and far field. In: Humphris S et al. (eds.) Seafloor Hydrothermal Systems, Physical, Chemical, Biological, and Geological Interactions, Geophysical Monograph Series, vol. 91, pp. 317–346. Washington, DC: American Geophysical Union. Lupton JE (1998) Hydrothermal helium plumes in the Pacific Ocean. Journal of Geophysical Research 103: 15855--15868.
Lupton JE and Craig H (1975) Excess 3He in oceanic basalts: evidence for terrestrial primordial helium. Earth and Planetary Science Letters 26: 133--139. Suess HE and Wa¨nke H (1965) On the possibility of a helium flux through the ocean floor. Progress in Oceanography 3: 347--353. Weiss RF (1970) Helium isotope effect in solution in water and seawater. Science 168: 247--248. Weiss RF (1971) Solubility of helium and neon in water and seawater. Journal of Chemical Engineering Data 16: 235--241.
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VORTICAL MODES E. L. Kunze, University of Washington, Seattle, WA, USA
spectral distributions of vortical mode shear and strain variance are still unknown.
Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3174–3178, & 2001, Elsevier Ltd.
Potential Vorticity In a rotating buoyancy-stratified fluid, potential vorticity is: P q ¼ ð2O þ r vÞ rhðr; pÞ
Introduction In the late 1970s, moored measurements in the ocean found that gradient quantities such as shear and strain exhibited frequency behavior inconsistent with linear internal gravity waves. While this behavior could arise from Doppler shifting or other nonlinearities within the internal wave spectrum, it was also realized that geostrophic, or nonlinear potential vorticity-carrying, motions might be contributing to fine-scale variance. In their simplest form, these could take the form of thin layers of varying stratification with large horizontal extent and little shear associated with them, so-called ‘passive fine-structure’. These perturbations would be subinertial in a water-following frame, and spread tracers much more efficiently along isopycnals (density surfaces) through stirring and shear dispersion than internal waves. The term ‘vortical mode’ was originally coined to refer to the zero-frequency eigenmode of the linear stratified f -plane equations associated with potential vorticity-carrying perturbations, that is, geostrophy, regardless of scale. However, the vortical mode has come to denote both linear and nonlinear subinertial (intrinsic frequencies o{f ) ocean finestructure with vertical wavelengths lz o100 m which cannot be described as internal gravity waves. The term vortical mode will be used in this sense here. In the sections below, potential vorticity is defined, its role on basin scales and mesoscales briefly described, then evidence for potential vorticity-carrying fine-structure in the ocean interior is discussed. Such evidence is indirect and inferential. Fine-scale vortical modes are expected to arise from (i) the potential enstrophy cascade of geostrophic turbulence, (ii) mixing in turbulent patches, (iii) bottom friction and eddy-shedding of flow past topography, and (iv) double diffusion. Interpretation of fine-scale observations is challenging because of the presence of finescale internal waves and nonlinear advection by large-scale internal waves. As a result, the spatial and
½1
where 2O ¼ ð0; f cotðlatitudeÞ; f Þ is the planetary vorticity vector associated with Earth’s O, rotation f ¼ 2jOjsinðlatitudeÞ the Coriolis frequency, the relative r v vorticity, and hðr; pÞ any well-behaved function of density and pressure. It is convenient to use the buoyancy b ¼ gr0 =r0 for hðr; pÞ where r0 ¼ rðx; y; zÞ r0 . The vertical gradient of buoyancy @b=@z ¼ N 2 is the stratification, or buoyancy frequency squared. The potential vorticity can be thought of as the dot product of the absolute vorticity vector and the stratification vector, that is, a multiplication of the stratification vector rb with that component of the absolute vorticity vector 2O þ r v parallel to it (Figure 1). As shown by Hans Ertel in 1942, potential vorticity is conserved following a fluid parcel in the absence of irreversible processes.1 That is, potential vorticity is invariant without forcing by wind stresses, radiation, and evaporation/precipitation at the sea surface, molecular dissipation by microscale turbulence and double diffusion in the ocean interior, or stresses and geothermal heating at the bottom. Potential vorticity perturbations arestable if 2O P is everywhere of the same sign. Relative to a background potential vorticity ¯ 2 , unstable in a rotating stratified fluid P ¼ f N conditions can arise from (i) fine-scale stratification
1 In a rotating buoyancy-stratified fluid, the potential vorticity of a water parcel is conserved in the absence of dissipative processes. The potential vorticity is
P q ¼ ð2O þ r vÞ rhðr; pÞ where 2O ¼ ð0; f cotðlatitudeÞ; f Þ, f is the planetary vorticity vector associated with Earth’s rotation f ¼ 2jOjsinðlatitudeÞ the Coriolis frequency, r v the relative vorticity, and hðr; pÞ any well-behaved function of density and pressure. The potential vorticity can be thought of as the dot product of the absolute vorticity vector and the stratification vector, that is, a multiplication of the stratification vector rb with that component of the absolute vorticity vector 2O þ r v parallel to it. As a conserved quantity, it is a useful dynamical tracer.
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VORTICAL MODES 2Ω + × v ∆
b
∆
1
2
Figure 1 Schematic of potential vorticity, which is the buoyancy gradient vector Ob times that component of the absolute vorticity 2O þ r v vector parallel with it. When isopycnals are flat, the absolute vorticity is just the Coriolis frequency f plus the vertical relative vorticity. When isopycnals are sloped as shown, horizontal vorticities (vertical shears) also become important.
¯ 2 Þ (equivalent of strain @x=@zB perturbations BOðN Oð1Þ), (ii) relative vorticity xBOðf Þ (equivalent to vorticity Rossby numbers Rz ¼ z=f BOð1Þ), or (iii) vertical shears @v=@zBOð1Þ (equivalentto gradient Richardson numbers Ri ¼ N2 =ð@v=@zÞ2 BOð1Þ.
In Figure 2, the relationship between the ratio of available potential to horizontal kinetic energy PE/KE and scaled aspect ratio ðNH=fLÞ2 ¼ ðNkH =fkz Þ2 is shown for geostrophic (thick dashed) and nonzero vorticity Rossby numbers (thin dashed and dotted), as well as linear internal gravity waves (thick dotted). At low aspect ratios (large horizontal compared to vertical scales), potential exceeds kinetic energy. At highaspect ratios, kinetic energy dominates. At vorticity Rossby numbers of 1, there is little potential energy because the Coriolis and centripetal acceleration terms balance. For vorticities exceeding f of either sign (@Rz @441, there is excess potential energy. These relations are independent of scale.
Basin Scales Basin scale potential vorticity structure does not fit into our definition of the vortical mode. However, the dynamics ofpotential vorticity anomalies should be independent of scale and much of our intuition comes from studies on these larger scales. Moreover, it is not yet known whether a spectral gap exists separating large- and small-scale potential vorticity perturbations.
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_ 0.5
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_5
+0.8 102
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(NkH)2/(fkz)2 Figure 2 Dynamic diagram describing the dependence of ratio of available potential to horizontal kinetic energy RE ¼ PE=KE (energy Burger number) on scaled aspect ratio RL ¼ ðNH=fLÞ2 (length scale Burger number), where HBkz1 is the vertical scale and LBkH1 the horizontal scale. The thick dashed diagonal corresponds to geostrophy (linear vortical modes). Rz ¼ z/f is the vorticity Rossby number. The thin diagonals correspond to nonzero negative (dotted) and positive (dashed) vorticity Rossby number vortical modes. Nonzero Rossby number vortical modes in the domain above the Ric ¼ 1 curve have vertical shears exceeding the buoyancy frequency N. The thick dotted curve is the relation for linear internal gravity waves for N=f ¼ 40. (Reproduced with permission from Kunze and Sanford, 1993.)
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VORTICAL MODES
On basin scales O (1000 km), baroclinic potential vorticity anomalies are linear and quasigeostrophic, associated with the large-scale gyres. Potential energy greatly exceeds kinetic energy for these very low aspect ratio motions (Figure 2). Potential vorticity can be simplified to f ðyÞN2 ðx; y; zÞ. This ‘stretching vorticity’ is a powerful dynamicaltracer, facilitating diagnosis of the gyre-scale circulation. Ventilatedwind-driven waters can be tracked from their winter outcrop. Under theassumption that, once a water parcel enters the pycnocline, its behavior can beexplained by inviscid quasigeostrophic dynamics on a bplane, potential vorticity conservation determines the stratification along particlepaths, a powerful constraint in ideal thermocline theory. Unventilated watersin shadow zones (backwaters isolated from direct atmospheric forcing)become homogenized over time. Also on these scales, long planetary Rossby waveshave potential vorticity as their restoring forces.
Mesoscale Similarly, mesoscale O(10–100 km) potential vorticity-carrying structures do not fit into our definition of the vortical mode, but are better understood. They have lower aspect ratios than basin scale anomalies. These include western boundary currents like the Gulf Stream and Kuroshio, rings, eddies, fronts, short Rossby waves, Meddies, and other submesoscale thermocline vortices. Vertical relative vorticity is often important on these scales, PCð f þ r vÞN 2 . Baroclinic and barotropic instability are means of transferringpotential vorticity toward smaller scales as part of the potential enstrophy cascade of 2-D geostrophic turbulence which tends to coalesce potential vorticity into coherent vortices resembling Meddies. This 2-D upscale energy cascade will be arrested by planetary Rossby wave radiation ifamplitudes are too weak to overcome the b-effect ðb ¼ qf =qyÞ. Rossby waveradiation is unlikely to be important for vortical mode because groupvelocities are very small for small vertical scales.
Fine-scale On the fine-scale O(100–1000 m), the vortical mode has been invoked on vertical scales of 1–10 m to account for (i) fine-structure contamination of internal waves in mooring measurements and (ii) scaledependent isopycnal diffusivities from tracer release experiments that are too large to be explained by internal wave shear dispersion.
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Sampling designed to minimize instrument motion contamination of internal wave measurements in the Internal Wave Experiment [e.g. (IWEX)] reveals that Eulerian frequency spectra offine-scale fluctuations such as shear and strain are not consistent withlinear internal gravity waves. Because of strong advective nonlinearity onthese scales, particularly from internal wave heaving, subinertial geostrophic finestructure would be Doppler shifted into the internal wave frequency band, f oooN. However, Doppler shifting will also smear fine-scale internal waves across all frequencies, so it isunclear whether ‘finestructure’ contamination is not justdue to fine-scale internal gravity waves of different intrinsicfrequencies becoming confused. Efforts to reduce Doppler shifting by examining time-series on isopycnal surfaces or with a water-following float have found signals much more compatible with linear internal wave dynamics. Lagrangian time-series have not yet been of sufficient duration to characterize subinertial variances. Isopycnal diffusivities increase with scaleso that a fine-scale patch diffuses more and more rapidly as it spreads with time. On 0.1–1.0 km scales, 0.0770.04 m2s1 diffusivities were inferred from a North Atlantic Tracer Release Experiment (NATRE). These may be explicable from internal wave shear dispersion in which vertical turbulent diffusion is spread horizontally by vertically varying horizontal displacements. However, 1–30 km diffusivities of 1–3 m2 s1 cannot be accounted for by either shear dispersion due to internal waves or persistent largescale (100 m) vertical shears. The vortical mode has been invoked to explain the O(10 km) diffusivities. Arguing that excess fine-scale strain is associated with the vortical mode, and assuming that dominant aspect ratios for the internal wave and vortical modefields are the same and independent of vertical wavenumber, yields quantitatively plausible horizontal diffusivities.
Generation Mechanisms Potential vorticity can only be modified by irreversible processes, and even then remains conserved within a volume containing all the dissipation. Moreover, it cannot flux across isopycnals. This puts severe restrictions on sources for the vortical mode. Away from atmospheric forcing, potential vorticity can only be altered through molecular dissipation. Fine-scale vortical modes are expected to arise from: 1. The potential enstrophy cascade of geostrophic turbulence, including baroclinic instability, although atmospherically forced mesoscale property
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anomalies appear to be smoothed out in only a few months. 2. Mixing and dissipation in micro-scale turbulence patches. 3. Bottom friction and eddy-shedding of flow past topography. 4. Double-diffusive layering and interleaving. Whether any of these mechanisms is sufficient to maintain a widespread or universal vortical mode field is unknown. The third and fourth mechanisms in particular are expected to be highly localized.
Observational Challenge The fine-scale poses considerable observational challenges because of the presence of energetic finescale internal waves, and nonlinear advection by large-scale internal waves.Measurements in the wake of a seamount found potential vorticity structure on vertical wavelengths of 50–200 m and horizontal scales of O(1 km), which was attributed to shedding of bottom boundary layers or flow separation (Figure 3). Strong coherent vortices with horizontal
scales O(1 km) have been found in a number of ocean pycnoclines, generated by either bottomhugging flows encountering abrupt changes in topography or deep convection. However, whether a universal vortical mode spectrum exists throughout the ocean, analogous to the canonical internal wave spectrum, has not been established since it has yet to be isolated from the omnipresent internal wave field. Four methods have been attempted to identifypotential vorticity-carrying fine-structure. 1. Intrinsic frequency should be subinertial ðo{f Þ for the vortical mode and superinertial for gravity waves away from boundaries where Kelvin and other bottom-trapped topographic waves, while not vortical modes, can have subinertial frequencies. For large-scale flows that experience little Doppler shifting ðv rÞc, where c represents ðu; v; w; bÞ, this isunambiguous from fixed Eulerian measurements. However, fine-structure with vertical wavelengths 1–10 m is strongly advected both vertically and horizontally by largerscale internal wave flows, so that Eulerian frequency measurements such as moorings are no
Figure 3 Energy ratios versus scaled aspect ratios (as inFigure 2) in the wake of a seamount.Gray bars emanating from the left axis correspond to horizontal wavelengthsexceeding 8.5 km (survey averages) with vertical wavelengths marked.These intersect the geostrophic curve (thick dashed diagonal) forvertical wavelengths lz ¼ 50 and 200 m, lie near theinternal wave curve (thick dotted curve) for lz ¼ 100, 130 and 400 m, and between the curves(corresponding to kinetic energy being dominated by near-inertialwaves and potential energy by geostrophic motions) otherwise. Black dots() correspond to scales resolved by the survey. At lower aspectratios, these mostly cluster near the internal wave curve. At higher aspectratios, they fall slightly below the internal wave curve, suggesting excesshorizontal kinetic energy. Gray bars emanating from the right axis denotehorizontal wavelengths 0.3 km (incoherent scales) at various verticalwavelengths. Two of these intersect the internal wave curve. The remainder,with scaled aspect ratios of O(10), lie below it, again suggestingexcess horizontal kinetic energy, possibly from the vortical mode. Very littleenergy is associated with higher aspect ratio estimates, so these may bealiased. (Reproduced with permission from Kunze and Sanford,1993.)
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VORTICAL MODES
longer unambiguous. Lagrangian time-series are necessary to identify the intrinsic frequency. Water-following measurements of shear and strain have yet to be made forsufficient duration to reliably identify the vortical mode. 2. Potential vorticity anomalies should be associated with vortical modes but not internal gravity waves (except possibly advection of background gradients – which should be small given the short timescales of internal waves). From the definition of potential vorticity in [1], this requires resolving fine-scale gradients on both the vertical and horizontal, which is difficult in itself. Moreover, since gradient quantities such as relative vorticity and buoyancygradients rb have blue horizontal wavenumber spectra, i.e. more variance at smaller than larger scales, sampling must be designed to filter out variance at scales smaller than those of interest. 3. The ratio of relative vorticity to horizontal divergence. Forlinear (geostrophic) vortical mode, vorticity greatly exceeds horizontal divergence (which vanishes in the steady geostrophic limit). For internal waves, the horizontal divergence is greater or equalto the relative vorticity. This approach has the same problems of spatial resolution as the potential vorticity method. 4. Ratio of horizontal kinetic to available potential energy (shear/strain ratio) HKE/APE as a function of dynamic lengthscale ratio ð fL=NHÞ2 . These differ for linear internal waves and geostrophic flow (Figure 2). This approach also suffers potential contamination by aliasing, in this case, by larger scales.
Conclusions Observational evidence for vortical mode finestructure in the ocean is sparse, largely indirect, and
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inferential. As a result, the spatial and spectral distributions of vorticalmode variances are unknown. Given their potentially important role in submeso scale isopycnal stirring, the oceanic vortical mode warrants further study.
See also Acoustics, Deep Ocean. Acoustics, Shallow Water. Dispersion and Diffusion in the Deep Ocean. Dispersion in Shallow Seas. Double-Diffusive Convection. Flows in Straits and Channels. General Circulation Models. Internal Tidal Mixing. Internal Tides. Internal Waves. Meddies and SubSurface Eddies. Overflows and Cascades. Patch Dynamics. Rossby Waves. Three-Dimensional (3D) Turbulence. Tracer Release Experiments. Upper Ocean Mixing Processes.
Further Reading Schro¨der W (ed.) (1991) Geophysical Hydrodynamics and Ertel’s Potential Vorticity (Selected Papers of Hans Ertel ). Bremen-Ro¨nnebeck, Germany: Interdivisional Commission of History of IAGA. Huang RX (1991) The three-dimensional structure of wind-driven gyres: Ventilation and subduction. Reviews of Geophysics 29: 590--609. Kunze E and Sanford TB (1993) Submesoscale dynamics near a seamount. Journal of Physical Oceanography 23: 2567--2601. Ledwell JR, Watson AJ, and Law CS (1998) Mixing of a tracer in the pycnocline. Journal of Geophysical Research 103: 21499--21529. Mu¨ller P, Olbers DJ, and Willebrand J (1978) The IWEX spectrum. Journal of Geophysical Research 83: 479--500. Mu¨ller P (1995) Ertel’s potential vorticity theorem in physical oceanography. Reviews of Geophysics 33: 67--97.
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WATER TYPES AND WATER MASSES W. J. Emery, University of Colorado, Boulder, CO, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3179–3187, & 2001, Elsevier Ltd.
Introduction Much of what is known today about the currents of the deep ocean has been inferred from studies of the water properties such as temperature, salinity, dissolved oxygen and nutrients. These are quantities that can be observed with standard hydrographic measurement techniques which collect temperatures and samples of water with a number of sampling bottles strung along a wire to provide the depth resolution needed. Salinity or ‘salt content’ is then measured by an analysis of the water sample, which combined with the corresponding temperature value at that ‘bottle’ sample yields temperature and salinity as a function of depth of the sample. Modern observational methods have in part replaced this sample bottle method with electronic profiling systems at least for temperature and salinity but many of the important descriptive quantities such as oxygen and nutrients still require bottle samples accomplished today with a ‘rosette’ sampler integrated with the electronic profiling systems. These new electronic profiling systems have been in use for over 30 years but the majority of data useful for studying the properties of the deep and open ocean still comes from the time before the advent of modern electronic profiling systems. This knowledge is important in the interpretation of the data since the measurements from sampling bottles have very different error characteristics than those from modern electronic profiling systems. This article reviews the mean properties of the open ocean, concentrating on the distributions of the major water masses and their relationships to the currents of the ocean. Most of this information is taken from published material including the few papers that directly address water mass structure along with the many atlases that seek to describe the distribution of water masses in the ocean. Coincident with the shift from bottle sampling to electronic profiling is the shift from publishing information about water masses and ocean currents in large atlases to the more routine research paper. In these papers the specific water mass characteristics are in general, only a small portion of
the total paper requiring an oceanographer interested primarily in the water mass distribution to review the entire paper to extract the water mass information. Although water mass characteristics often play important roles in today’s oceanographic research efforts there are few studies devoted solely to a better description of the distributions and characteristics of global water masses.
What is a Water Mass? The concept of a ‘water mass’ is borrowed from meteorology, which classifies different atmospheric characteristics as ‘air masses’. In the early part of the twentieth century physical oceanographers also sought to borrow another meteorological concept separating the ocean waters into a ‘warm’ and ‘cold’ water spheres. This designation has not survived in modern physical oceanography but the more general concept of water masses persists. Some oceanographers regard these as real, objective physical entities, building blocks from which the oceanic stratification (vertical structure) is constructed. At the opposite extreme, other oceanographers consider water masses to be mainly descriptive words, summary shorthand for pointing to prominent features in property distributions. The concept adopted for this discussion is squarely in the middle, identifying some ‘core’ water mass properties that are the building blocks. In most parts of the ocean the stratification is defined by mixing in both vertical and horizontal orientations of the various water masses that advect into the location. Thus, the maps of the various water mass distributions identify a ‘formation region’ where it is believed that the core water mass has acquired its basic characteristics at the surface of the ocean. This introduces a fundamental concept first discussed in 1939 that the properties of the various subsurface water masses were originally formed at the surface in the source region of that particular water mass. Since temperature and salinity are considered to be ‘conservative properties’ (a conservative property is only changed at the sea surface) these characteristics would slowly erode as the water properties were advected at depth to various parts of the ocean.
Descriptive Tools: The TS Curve Before beginning to talk about and describe the global distribution of water masses some of the basic
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tools used in such a description are introduced. One of the most basic tools is the use of property vs. property plots to summarize the analysis by making extrema easy to locate. The most popular of these is the temperature–salinity or TS diagram, which relates density to the observed values of temperature and salinity. Originally the TS curve was constructed for a single hydrographic cast and thus related the TS values collected for a single bottle sample with the salinity computed from that sample. In this way there was a direct relationship between the TS pair and the depth of the sample. As the historical hydrographic record expanded it became possible to compute TS curves from a combination of various temperature/salinity profiles. This approach amounted to plotting the TS curve as a scatter diagram (Figure 1) where the salinity values were then averaged over a selected temperature interval to generate a discrete TS curve. An average of all of the data in a 101 square just north east of Hawaii in this TS curve is typical of features that can be found in all TS curves. In this example the temperature/salinity pair remained the same while the depth of this pair oscillated vertically by tens of meters resulting in the absence of a precise relationship between TS pairs and depth. As sensed either by ‘bottle casts’ or by electronic profilers these vertical variations express themselves as increased variability in the temperature or salinity profiles while the TS curve continues to retain its shape now independent of depth. Hence composite TS curves computed from a number of closely spaced hydrographic stations no longer have a specific relationship between temperature, salinity, and depth. As with the more traditional ‘single station’ TS curve these area average TS curves can be used to
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Figure 1 Example of TS ‘scatter plot’ for all data within a 101 square with mean TS curve (centre line) and curves for one standard deviation in salinity on either side. (1% 7 1 PSU.)
define and locate water masses which is done by locating extrema in salinity associated with particular water masses. Ignoring the near-surface values, the salinity minimum in this TS curve is at about 101C where there is a clear divergence of TS values as they move up the temperature scale from the coldest temperatures near the bottom of Figure 1. There are two separate clusters of points at this salinity minimum temperature with one terminating at about 131C and the other transitioning up to the highest temperatures. It is this termination of points that results in a sharp turn in the mean TS curve and causes a very wide standard deviation. These two clusters of points represent two different intermediate level water masses. The relatively high salinity values that appear to terminate at 131C represent the Antarctic Intermediate Water (AIW) formed near the Antarctic continent, reaching its northern terminus after flowing up from the south. The coincident less salty points indicate the presence of North Pacific Intermediate Water moving south from its formation region in the northern Gulf of Alaska. Although there is no general practice in water mass terminology it is generally accepted that a ‘water type’ refers to a single point on a characteristic diagram such as a TS curve. As introduced above, ‘water mass’ refers to some portion or segment of the characteristic curve which described the ‘core properties’ of that water mass. In the above example the salinity characteristics of the two intermediate waters was a salinity minimum, which was the overall characteristic of the two intermediate waters. The extrema associated with a particular water mass may not remain at the same salinity value. Instead as one moves away from the formation zone for the AIW, which is at the oceanographic ‘polar front’ the sharp minimum that marks the AIW water and has sunk from the surface down to about 1000 m and start to erode, broadening the salinity minimum and slowly increasing its magnitude. By comparing conditions of the salinity extreme at a location with the salinity characteristics typical of the formation region one can estimate the amount of the source water mass still present at the distant location. Called the ‘core-layer’ method this procedure was a crucial development in the early study of the ocean water masses and long-term mean currents. Many variants of the TS curve have been introduced over the years. One form that is particularly instructive is the ‘volumetric TS curve’. Here the oceanographer subjectively decides just how much volume is associated with a particular water mass. This becomes a three-dimensional relationship, which can be plotted, in a perspective format
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WATER TYPES AND WATER MASSES
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Pacific Deep
Po te
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Figure 2 Simulated three-dimensional T–S–V diagram for the cold water masses of the world ocean.
(Figure 2). In this plot the two horizontal axes are temperature and salinity while the elevation represents the volume with those particular TS characteristics. For this presentation only the deeper water mass characteristics have been plotted which can be seen by the restriction of the temperature scale to 1.0 to 4.01C. The arrows show which parts of the ocean various features are from. That the Atlantic is the saltiest of the oceans is very clear with a branch to high salinity values at higher temperatures. The largest volume water mass is the Pacific deep water that fills most of the Pacific below the intermediate waters at about 1000 m.
Global Water Mass Distribution Before we turn to the TS curve description of the water masses we need to indicate the geographic distribution of the basic water masses. The reader is cautioned that only the major water masses, which most oceanographers accept and agree upon, will be discussed. In a particular region of interest close inspection will reveal a great variety of smaller water mass classifications, which can be almost infinite, as higher resolution is obtained in both horizontal and vertical coverage. Table 1 presents the TS characteristics of the world’s water masses. Here the area name is given together with the corresponding acronym, and the appropriate temperature and salinity range. Recall that the property extreme becomes less distinct because of diffusion the further one goes from the
source region so it is necessary to define a range of properties. This is also consistent with the view that a water mass refers to a segment of the TS curve rather than a single point. Here the water masses have been divided, as is traditionally the case, into deep and abyssal waters, intermediate waters and upper waters. Although the upper waters have the largest property ranges they occupy the smallest ocean volume. The reverse is true of the deep and bottom waters, which have a fairly restricted range but occupy a substantial portion of the ocean. Since most ocean water mass properties are established at the ocean’s surface those water masses which spend most of their time isolated far from the surface will diffuse the least and have the longest lifetime. Surface waters on the other hand are strongly influenced by fluctuations at the ocean surface which rapidly erode the water mass properties. In mean average TS curves as in Figure 1 the spread of the standard deviation at the highest temperatures reflects this influence from the heat and freshwater flux exchange that occurs near and at the ocean’s surface. To accompany Table 1 global maps of water mass at all three of these levels are presented. The upper waters in Figure 3 have the most complex distributions with significant meridional and zonal changes. We have also indicated a best guess at the formation regions for the corresponding water mass as indicated by the hatched regions. For its relatively small size the Indian Ocean has a very complex upper water mass structure. This is caused by some unique geographic conditions. First is the monsoon,
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Table 1
Temperature–salinity characteristics of the world’s water masses
which completely changes the wind patterns twice a year. This causes reversals in ocean currents, which also influence the water masses by altering the contributions of the very saline Arabian Gulf and the
fresh Bay of Bengal into the main body of the Indian Ocean. All of the major rivers in India flow to the east and discharge into the Bay of Bengal making it a very fresh body of ocean water. To the west of
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295
WATER TYPES AND WATER MASSES 60° E 30° 90° E
150° 150° E 120° 180° 120° W
60° 0° W 90° 30° 30° E ASUW
N 0° S
WNPCW ASW Arab. Sea Water
Ind ian E qu
IEW
BBW Bengal Bay Wat.
atorial Wa.t
20° S. Indian Centr. Water 40°
60°
IUW
W NACW West. N. Atl. Centr. Water
ENPCW
West. N. Pacific Centr. Water
r ppS u ba t. er Wa
East. N. Pacific Transition Water
East. N. Pacific Centr. Water
W AC EN
t. r Wa Pac. Subarctic Uppe
ct
PSUW
40°
20°
. Atl U
60°
ic
Ice
Atl. N. at. st. Ea ntr. W Ce
PEW
Indo. Upper Wat. West. S. Pacific Centr. Water PCW ESPCW S W
c Surface Water Subantarcti
Su Antarctic
rface Water
E 30° 90° 150° E 60° 120°
40°
20° N 0°
Pacific Equatorial Water
SICW
60°
East S. Pacific Centr. Water
Subantarctic Surf ace Wa t er Antarctic Surface Water
E
South Atlantic Centr. Water
S 20°
SACW
East. S. Pacific Transition Water
150° 150° 90° W 180° 120° 60°
tic Surface Water tarc ban Su ic Surface Wat tarct . An
40°
60°
E W 60° 0° 30° 30°
Figure 3 Global distribution of upper waters (0–500 m). Water masses are labeled in abbreviated form with their boundaries indicated by solid lines. Formation regions for these water masses are marked by cross-hatching and labeled with the corresponding acronym title.
the Indian subcontinent is the Arabian Sea with its connection to the Persian Gulf and the Red Sea, both locations of extremely salty water making the west side of India very salty and the east side very fresh. The other upper ocean water masses in the Indian Ocean are those associated with the Antarctic Circumpolar Current (ACC) and are found at all of the longitudes in the Southern Ocean. As the largest ocean basin the Pacific has the strongest east–west variations in upper water masses with east and west central waters in both the north and south hemispheres. Unique to the Pacific is the fairly wide band of the Pacific Equatorial Water, which is strongly linked to the equatorial upwelling, which may not exist in El Nin˜o years. Neither of the other two ocean basins has this equatorial water mass in the upper ocean. The Atlantic has northern hemisphere upper water masses that can be separated east–west and the South Atlantic upper water mass cannot be separated east–west into two parts. Note the interaction between the North Atlantic and the Arctic Ocean through the Norwegian Sea and Fram Strait. Also in these locations there are source regions for a number of Atlantic water masses. Compared with the other two oceans the Atlantic has the most water mass source regions which produce a large part of the deep and bottom waters of the world ocean. The chart of intermediate water masses in Figure 4 is much simpler than that of the upper ocean water masses (Figure 3). This reflects the fact that there are far fewer intermediate waters and those that are present fill large volumes of the intermediate
depth ocean. The North Atlantic has the most complex horizontal structure of the three oceans. Here intermediate waters form at the source regions in the northern North Atlantic. One exception is the Mediterranean Intermediate Water, which is a consequence of climatic conditions in the Mediterranean Sea. This salty water flows out through the Straits of Gibraltar at about 320 m depth where it then descends to 1000 m where it sinks below the vertical range of the less saline Antarctic Intermediate Water (AIW) and joins with the higher salinity of the deeper North Atlantic Deep Water (NADW), which maintains the salinity maximum indicative of the NADW. In the Southern Ocean the formation region for the AIW is marked as the location of the oceanic polar front, which is known to vary considerably in strength and location moving the formation region north and south. It can clearly be seen in all of the ocean basins that this AIW fills a large part of the ocean. In the Pacific the AIW extends north to about 201N where it meets the North Pacific Intermediate Water (NPIW) as shown in Figure 1. The AIW reaches about the same latitude in the North Atlantic but it only reaches to about 51S in the Indian Ocean. In the Pacific the northern intermediate waters are mostly from the North Pacific where the NPIW is formed. There is, however, another smaller volume intermediate water that is formed in the transition region west of California mostly as a consequence of coastal upwelling. A similar intermediate water formation zone can be found in the south Pacific mainly off the coast of South America, which generates a minor intermediate water mass.
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296
WATER TYPES AND WATER MASSES 60˚ E 30˚ 90˚ E
150˚ 150˚ E 120˚ 180˚ 120˚ W
60˚ 0˚ W 90˚ 30˚ 30˚ E
Arctic Int. Water AIW 60˚
W t. A at tl
PSIW c Int. Pacific Subarcti
0˚
c
CIW Calif. Int. Water
CIW
RSP
MW
MW
20˚ N
Red SeaPerf Gulf Int. Water
IIW Indo. I
S
0˚ S
nt. Water
East S. Pacific Int Water
20˚ Antarctic Int. Water
ES
Antarctic Int. Water 40˚ AAIW
60˚
40˚
20˚
PIW
N
er Wat
Su b
40˚
20˚
60˚
SIW EA WA SIW s Ea t. In ti We . arc tic Int st. Ar t. Sub arc Med ter . Wa t er Wa
Antarctic Int. Water A AI W
AAIW
E 30˚ 90˚ 150˚ E 60˚ 120˚
E
150˚ 150˚ 90˚ W 180˚ 120˚ 60˚
W
40˚
60˚
E 60˚ 0˚ 30˚ 30˚
Figure 4 Global distribution of intermediate water (550–1500 m). Lines, labels and hatching follow the same format as described for Figure 3.
60° E 30° 90° E ADW
Arctic Deep Water
150° 150° E 120° 180° 120° W
60° 0° W 90° 30° 30° E ADW Arctic Deep Water
Arctic Deep Water
ADW
60°
DW
60°
NA
40°
40°
20°
20°
N
N 0°
0°
S
S 20°
20°
40°
60°
40°
Antarctic Bottom Water
Antarctic
Antarctic Bottom Water
Bottom Water
60°
AAB W 4000 m Depth contour E 30° 90° 150° E 60° 120°
E
150° 150° 90° W 180° 120° 60°
W
E 60° 0° 30° 30°
Figure 5 Global distribution of deep and abyssal waters (1500–bottom). Contour lines describe the spreading of abyssal water (primarily AABW). The formation of NADW is indicated by hatching and its spreading terminus, near the Antarctic, by a dashed line which also suggests the global communication of this deep water around the Antarctic. The formation and distribution of CDW is not shown since it overlies the abyssal water in both the Pacific and Indian Oceans.
The deep and bottom waters mapped in Figure 5 are restricted in their movements to the deeper reaches of the ocean. For this reason the 4000 m depth contour is plotted in Figure 5 and a good correspondence can be seen between the distribution of bottom water and the deepest bottom topography. Some interesting aspects of this bottom water can be seen in the eastern South Atlantic. As the dense bottom water makes its way north from the Southern Ocean in the east it runs into the Walvis Ridge which
blocks it from further northward extension. Instead the bottom water flows north along the west of the mid-Atlantic ridge and finding a deep passage in the Romanche Gap flows eastward and then south to fill the basin north of the Walvis Ridge. A similar complex pattern of distribution can be seen in the Indian Ocean where the east and west portions of the basin fill from the south separately because of the central ridge in the bottom topography. In spite of the requisite depth of the North Pacific the Antarctic
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WATER TYPES AND WATER MASSES
Summary TS Relationships As pointed out earlier one of the best ways to detect specific water masses is with the TS relationship whether computed for single hydrographic casts or from a historical accumulation of such hydro casts. Here traditional practice is followed and the summary TS curves are divided into the major ocean basins starting with the Atlantic (Figure 6). Once again the higher salinities typical of the Atlantic can clearly be seen. The highest salinities are introduced by the Mediterranean outflow marked as MW in Figure 6. This joins with water from the North Atlantic to become part of the NADW, which is marked by a salinity maximum in these TS curves. The AAIW is indicated by the sharp salinity minimum at lower temperatures. The source water for the AAIW is marked by a dark square in the figure. The AABW is a single point, which now does not represent a ‘water type’ but rather a water mass. The difference is that this water mass has very constant TS properties represented by a single point in the TS
20 t =
15
Temperature (°C)
Bottom Water (AABW) does not extend as far northward in the North Pacific meaning that some variant of the AABW, created by mixing with other deep and intermediate waters, occupies the most northern reaches of the deep North Pacific. Because the North Pacific is essentially ‘cut-off’ from the Arctic there is no formation region of deep and bottom water in the North Pacific. The three-dimensional TS curve of Figure 2 showed that the most abundant water mass marked by the highest peak in this TS curve corresponded to Pacific Deep Water. Table 1 shows there is something called ‘Circumpolar Deep Water’ in the deeper reaches of both the Pacific and Indian Oceans. This water mass is not formed at the surface but is instead a mixture of North Atlantic Deep Water (NADW), AABW and the two intermediate waters present in the Pacific. The AABW forms in the Weddell Sea as the product of very cold, dense, fresh water flowing off the continental shelf which then sinks and encounters the upwelling NADW which adds a little salinity to the cold, fresh water, making it even denser. This very dense product of Weddell Sea shelf water and NADW becomes the AABW which then sinks to the very bottom and flows out of the Weddell Sea to fill most of the bottom layers of the world ocean. It is probable that a similar process works in the Ross Sea and some other areas of the continental shelf to form additional AABW but the Weddell Sea is thought to be the primary formation region of AABW.
297
26
CW SA
CW NA
W 27
W AC
EN
MW
10 28
5 AAIW
0
_2
WASIM
EASIW
NADW
AABW
34
35 Salinity (‰)
36
Figure 6 Characteristic temperature–salinity (TS) curves for the main water masses of the Atlantic Ocean. Water masses are labeled by the appropriate acronym (see Table 1) and core water properties are indicated by a dark square with an arrow to suggest their spread. The cross-isopycnal nature of some of these arrows is not intended to suggest a mixing process but merely to connect source waters with their corresponding characteristic extrema.
curves. Note that this is the densest water on this TS diagram (the density lines are shown as the dashed curves in the TS diagram marked as st ¼ ). The rather long segments stretching to the highest temperature and salinity values represent the upper water in the Atlantic. Although this occupies a large portion of the TS space it only covers a relatively small part of the upper ocean when compared to the large volumes occupied by the deep and bottom water masses. From this TS diagram it can be seen that the upper waters are slightly different in the South Atlantic, the East North Atlantic and the West North Atlantic. Of these differences the South Atlantic differs more strongly from the other two than they do from each other. By comparison with Figure 6 the Pacific TS curves of the Pacific (Figure 7) are very fresh with all but the highest upper water mass having salinities below 35%. The bottom property anchoring this curve is the Circumpolar Deep Water (CDW) which is used to identify a wide range of TS properties that are known to be deep and bottom water but have not been identified in terms of a specific formation region and TS properties. As with the AABW a single point at the bottom of the curves represents the CDW. The relationship between the AAIW and the Pacific Subarctic Intermediate Waters (PSIW) can be clearly seen in this diagram. The AAIW is colder and saltier than the PSIW, which is generally a bit higher in the water column indicated by the lower density of this feature. There are no external sources of deep salinity as for the Mediterranean
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WATER TYPES AND WATER MASSES
0
_2
W
34
28
CDW
35 Salinity (‰)
6
t = 2
IEW
15
CW SP
PSIW
AAIW
BBW
20
36
CW SI
10
W AS 27
RSPGIW
IUW
W
26
27
PE W
E
PC
10
5
t =
W PC CW W N NA PT W ES
ES
Temperature (°C)
15
EN
PT
W
20
Temperature (°C)
298
28
IIW
5 AAIW
0 _2
CDW
34
35
36
Salinity (‰)
Figure 7 Characteristic temperature–salinity (TS) curves for the main water masses of the Pacific Ocean. All labels as in Figure 6.
Water in the Atlantic. Instead there is a confusing plethora of upper water masses that clearly separate the east–west, and north–south portions of the basin. There is therefore Eastern North Pacific Central Water (ENPCW) and Western North Pacific Central Water (WNPCW), as well as Eastern South Pacific Central Water (ESPCW) and Western South Pacific Central Water (WSPCW). The central waters all refer to open ocean upper water masses. The more coastal water masses such as the Eastern North Pacific Transition Water (ENPTW) are typical of the change in upper water mass properties that occurs near the coastal regions. The same is also true of the South Pacific. In general the fresher upper-layer water masses of the Pacific are located in the east where river runoff introduces a lot of fresh water into the upper ocean. To the west the upper water masses are saltier as shown by the quasi-linear portions of the TS curves corresponding to the western upper water masses. The Pacific Equatorial Water (PEW) is unique in the Pacific probably due to the well-developed equatorial circulation system. As seen in Figure 7 the PEW TS properties lie between the east and west central waters. The Indian Ocean TS curves in Figure 8 are quite different from either the Atlantic or the Pacific. Overall the Indian Ocean is saltier than the Pacific but not quite as salty as the Atlantic. Also like the Atlantic the Indian Ocean receives salinity input from a marginal sea as the Red Sea deposits its salt-laden water into the Arabian Sea. Its presence is noted in Figure 8 as the black square marked RSPGIW (Red Sea–Persian Gulf Intermediate Water). Added at the sill depth of the Red Sea this
Figure 8 Characteristic temperature–salinity (TS) curves for the main water masses of the Indian Ocean. All labels as in Figure 6.
intermediate water contributes to a salinity maximum that is seasonally dependent. The bottom water is the same CDW as seen in the Pacific. Unlike the Pacific the Indian Ocean equatorial water masses are nearly isohaline above the point representing the CDW. In fact the line that represents the Indian Ocean Equatorial Water (IEW) runs almost straight up from the CDW at about 01C to the maximum temperature at 201C. There is an expression of the AAIW in the curve that corresponds to the South Indian Ocean Central Water (SICW). A competing Indonesian Intermediate Water (IIW) has higher temperature and higher salinity characteristics which result in it having an only slightly lower density creating the weak salinity minimum in the curve transitioning to the Indian Ocean Upper Water (IUW). The warmest and saltiest part of these TS curves represents the Arabian Sea Water (ASW) on the western side of the Indian subcontinent.
Discussion and Conclusion The descriptions provided in this review cover only the most general of water masses, their core properties and their geographic distribution. In most regions of the ocean it is possible to resolve the water mass structure into even finer elements describing more precisely the differences in temperature and salinity. In addition other important properties can be used to specify water masses not obvious in the TS curves. Although dissolved oxygen is often used to define water mass boundaries care must be taken as this nonconservative property is influenced by
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WATER TYPES AND WATER MASSES
biological activity and the chemical dissolution of dead organic material falling through the water column. Nutrients also suffer from modification within the water column making their interpretation as water mass boundaries more difficult. Characteristic diagrams that plot oxygen against salinity or nutrients can be used to seek extrema that mark the boundaries of various water masses. The higher vertical resolution property profiles possible with electronic profiling instruments also make it possible to resolve water mass structure that was not even visible with the lower vertical resolution of earlier bottle sampling. Again this complexity is only merited in local water mass descriptions and cannot be used on the global scale description. At this global scale the descriptive data available from the accumulation of historical hydrographic data are adequate to map the largescale water mass distribution as in this review article.
299
See also California and Alaska Currents. Kuroshio and Oyashio Currents. Ocean Circulation. Ocean Subduction. Pacific Ocean Equatorial Currents. Wind Driven Circulation.
Further Reading Emery WJ and Meincke J (1986) Global water masses summary and review. Oceanologica Acta 9: 383--391. Iselin CO’D (1939) The influence of vertical and lateral turbulence on the characteristics of the waters at middepths. Transactions of the American Geophysical Union 20: 414--417. Pickard GL and Emery WJ (1992) Descriptive Physical Oceanography, 5th edn. Oxford: Pergamon Press. Worthington LV (1981) The water masses of the world ocean some results of a fine-scale census. In: Warren BA and Wunsch C (eds.) Evolution of Physical Oceanography: ch. 2, pp. 42--69. Cambridge, MA: MIT Press.
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WAVE ENERGY M. E. McCormick and D. R. B. Kraemer, The Johns Hopkins University, Baltimore, MD, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3187–3191, & 2001, Elsevier Ltd.
Introduction In the last half of the twentieth century, humankind finally realized that fossil fuel resources are finite and that use of those fuels has environmental consequences. These realizations have prompted the search for other energy resources that are both renewable and environmentally ‘friendly’. One such resource is the ocean wind wave. This is a form of solar energy in that the sun is partly responsible for the winds that generate water waves. The exploitation of water waves has been a goal for thousands of years. Until recent times, however, only sporadic efforts were made, and these were generally directed at a specific function. In the 1960s, Yoshio Masuda, the ‘renaissance man’ of wave energy conversion, came up with a scheme to convert the energy of water waves into electricity by using a floating pneumatic device. Originally, the Masuda system was used to power remote navigation aides, such as buoys. One such buoy system was purchased by the US Coast Guard which, in turn, requested an analysis of the performance of the system. The results of that analysis were reported by McCormick (1974). This was the first of a long list of theoretical
and experimental studies of the pneumatic and other wave energy conversion systems. (For summaries of some of the works, see the Further Reading section.) The most recent collective type of publication is that edited by Nicholls (1999), written under the joint sponsorship of the Engineering Committee on Oceanic Resources (ECOR) and the Japan Marine Science and Technology Center (JAMSTEC). In the late 1970s and early 1980s, JAMSTEC co-sponsored a full-scale trial of a floating, offshore pneumatic system called the Kaimei. The 80 m long, 10 m wide Kaimei (Figures 1 and 2) was designed to produce approximately 1.25 MW of electricity while operating in the Sea of Japan. This power was to be produced by 10 pneumatic turbo-generators. Eight of these (produced in Japan) utilized a unidirectional turbine. The other two utilized bi-directional turbines designed by Wells in the UK and McCormick in the USA. Unfortunately, the designed electrical power production was never attained by the system. The Wells turbine was found to be the most effective for wave energy conversion, and is now being used to power fixed pneumatic systems in the Azores, in India, and on the island of Islay off of the coast of Scotland. Most of the published works resulting from research, development, and demonstration efforts are directed at the production of electrical energy. However, Hicks et al. (1988) described a wave energy conversion technique that could be used to produce potable water from ocean salt water. This technique had been developed earlier by Pleass and Hicks. Their work resulted in a commercial system
Wave-induced air flow Air turbine Capture Chambers
Oscillating water column
Figure 1 Schematic diagram of the Kaimei wave energy conversion system, consisting of 10 capture chambers and 10 pneumaticelectric generating systems.
300
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WAVE ENERGY
Figure 4 The McCabe wave pump located 500 m off the coast of Kilbaha, County Clare, Ireland.
Figure 2 The Kaimei deployed in the Sea of Japan.
called the Del Buoy, and inspired the efforts of others to apply the McCabe wave pump (Figures 3 and 4) to the production of potable water. The high-pressure pumps located between the barges pump sea water through a reverse osmosis (RO) desalination system located on the shore. The first deployment of the McCabe wave pump occurred in 1996 in the Shannon River, western Ireland. A second deployment of the system is expected in the spring of the year 2000 at the same location.
Wave Power: Resource and Exploitation A mathematical expression for the power of water waves is obtained from the linear wave theory. Simply put, the expression is based on the waves having a sinusoidal profile, as sketched in Figure 5. The wave power (energy flux) expression is: 1 P ¼ rgH 2 bcG 8
wave crest width of interest in meters, and the vector cG is called the group velocity. In deep water, defined as water depth (h) greater than half of the wave length (l), the group velocity (in m s1) is approximately: c gT 7cG 7C C 2 4p
½2
where c is the wave celerity (the actual speed of the wave), and T is the period of the wave in seconds. In shallow water, defined as where hrl=20, the group velocity is approximated by: pffiffiffiffiffiffi ½3 7cG 7CcC gh Consider an average wave approaching the central Atlantic states of the contiguous United States. The average wave height and period of waves in deep water are approximately 1 m and 7 s, respectively. For this wave, the wave power per crest width is:
½1
where r is the mass density of salt water (approximately 1030 kg m3), g is the gravitational acceleration (9.81 m s2), H is the wave height in meters, b is the
7P7 1 ¼ rg2 H 2 TC6:90ðkW=mÞ b 32p
c Power barge Damping plate Water intake
H
To RO unit
Figure 3 Sketch of the McCabe wave pump.
½4
from eqn[1] combined with the expression in eqn [2].
Pumps
Pitching motion
301
Figure 5 Wave notation.
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WAVE ENERGY
The percentage of this power that can be captured depends on both the width of the capturing system and the frequency (or period) characteristics of the system. Each wave power system has one fundamental frequency (fn). If the inverse of that frequency (1/fn ¼ Tn) is the same as the average wave period, then the system is in resonance with the average wave, and the maximum amount of wave power will be extracted by the wave power system. This, then, is the design goal, i.e. to design the system to resonate with the design wave. When resonance is achieved, then another phenomenon occurs which is of benefit to the system: i.e. resonant focusing, where diffraction draws energy toward the system. For a single degree of freedom wave power system, such as the heaving buoy sketched in Figure 6, the wave power absorbed by the system comes from a crest width equal to the width of the system (B) plus an additional width equal to the wavelength divided by 2p. Hence, in deep water, the total power available to the single degree of freedom system operating in the average wave is:
7P7 ¼
1 l rg2 H 2 T B þ 32p p
½5
(A)
To water pump
To power grid
Flotation collar of diameter B
Oscillating water column
Water intake (B) Figure 6 Floating oscillating water column wave energy converter, designed to produce electrical power for either potable water production or electricity. (A) Plan view; (B) elevation.
where the wavelength in deep water is approximately: lC
gT 2 2p
½6
Thus, for the aforementioned average wave, the deep-water wavelength is about 76.5 m. Consider an ideal 1 m diameter heaving system operating in the 1 m, 7 s average wave. For this wave, the wave power captured by the system is 6:90ð1 þ 76:5=2pÞ kW, or approximately 91 kW. If bus-bar conversion efficiency is 50%, then about 45.5 kW will be supplied to the power grid for consumption. In the contiguous United States, each citizen requires about 1 kW, on average, at any time. Hence, this system would supply 87.5 citizens. To use the same system coupled with a RO desalinator to supply potable water, the value of the osmotic pressure of the desalinator’s membranes is required. This value is 23 atmospheres or approximately 23 bars. From fluid mechanics, the power is equal to the volume rate of flow in the system multiplied by the back pressure. Hence, the 1 m diameter system would supply approximately 5 (US) gallons of salt water per second to the RO unit. Half of this flow would become product (potable) water, while the other half would be brine waste. This ideal system would supply 2.5 gallons per second (about 225 000 gallons per day) of potable water. Each US citizen residing in the contiguous United States uses about 60 gallons per day, on average. So, the wavepowered desalination system would satisfy the daily potable water needs of approximately 3700 citizens. The numbers presented in the last two paragraphs illustrate the potential of wave energy conversion. The electrical and water producing systems described are ideal. In actuality, the waves in the sea are random in nature. The system, then, must be tuned to some design wave, such as that having an average wave period.
Economics of Wave Power Conversion The economics of ocean wave energy conversion vary, depending on both the product (electricity or potable water) and the location. To illustrate this, consider the following two cases. First, on Lord Howe Island in the South Pacific, the cost of electrical energy is about 45 (US) cents per kilo-Watt hour (kWh). Electricity produced by wave energy conversion would cost about 15 cents/kWh. Hence, for such an application, wave energy conversion would be extremely cost-effective. On the other hand, in San
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WAVE ENERGY
Diego, California, the energy cost is about 13 cents/ kWh, making wave energy conversion cost-ineffective. For the production of potable water, the McCabe wave pump, coupled with a RO system, will produce potable water at approximately US $1.10 per cubic meter (265 US gallons). On some remote islands, the cost of potable water is approximately $4.00 per gallon. On the coast of Saudi Arabia, on the Arabian Sea, the cost of potable water is $3.10 per cubic meter. Therefore, these locations, wave-powered desalination systems are very cost-effective.
Concluding remarks The reader is encouraged to consult the Further Reading section for more information on wave energy conversion. There are many activities presently underway in this area of technology. These can be found on the Internet by searching the world wide web for wave energy conversion.
See also Coastal Trapped Waves. Internal Waves. Seiches. Storm Surges. Surface Gravity and Capillary Waves. Tides. Tsunami. Wave Generation by Wind. Waves on Beaches.
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Further Reading Count B (ed.) (1980) Power from Sea Waves. London: Academic Press. Hicks D, Pleass CM, and Mitcheson G (1988) Delbuoy Wave-Powered Seawater Desalination System. Proceedings of OCEANS’88, US Department of Energy, pp. 1049–1055. McCormick ME (1981) Ocean Wave Energy Conversion. New York: Wiley-Interscience. McCormick ME (1974) An analysis of power generating buoys. Journal of Hydronautics 8: 77--82. McCormick ME, McCabe RP, and Kraemer DRB (1999) Utilization of a hinged-barge wave energy conversion system. International Journal of Power Energy Systems 19: 11--16. McCormick ME and Murtagh JF (1992) Large-Scale Experimental Study of the McCabe Wave Pump. US Naval Academy Report EW-3-92, January. McCormick M, Murtagh J, and McCabe P (1998) LargeScale Experimental Study of the McCabe Wave Pump. European Wave Energy Conference (European Union), Patras, Greece, Paper H1. Nicholls HB (1999) Workshop Group on Wave Energy Conversion. Engineering Committee on Oceanic Resources (ECOR), St Johns, Newfoundland, Canada. Ross D (1998) Power from the Waves. Oxford: Oxford University Press. Shaw R (1982) Wave Energy. A Design Challenge. Chichester, UK: Ellis Horwood.
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WAVE GENERATION BY WIND J. A. T. Bye, The University of Melbourne, Melbourne, VIC, Australia A. V. Babanin, Swinburne University of Technology, Melbourne, VIC, Australia & 2009 Elsevier Ltd. All rights reserved.
Introduction The prime focus in this article is on ocean waves (which have always captured the scientific imagination), although results from wind-wave tank studies are also introduced wherever appropriate. Growth mechanisms fall naturally into three phases: (a) the onset of waves on a calm sea surface, (b) mature growth in the confused sea state under moderate winds, and (c) sea-spray-dominated wave environments under very high wind speeds. Of these three phases, (b) has the greatest general importance, and numerous practical formulas have been developed over the years to represent its properties. Figure 1 illustrates the sea state which occurs at the top end of phase (b) in a strong gale (wind speed c. 25 ms 1, Beaufort force 9). An important consideration is that wave generation by wind involves three main physical processes: (1) direct input from the wind, (2) nonlinear transfer between wavenumbers, and (3) wave dissipation. This article is specifically dedicated to (1); however, we briefly review (2) and (3) below. Nonlinear interactions within the wave system can only be neglected for infinitesimal waves. To a first approximation, the wind wave can be regarded as almost sinusoidal with negligible steepness (i.e., linear), but its very weak mean nonlinearity (i.e., finite steepness and deviation of its shape from the sinusoid) is generally believed to control the evolution of the wave
Figure 1 The sea state during a strong gale.
304
field. Theoretical models of the air–sea boundary layer indicate that the input of momentum from the wind is centered in the short gravity waves. The wind pumps energy mostly into short (high-frequency) and slowly moving waves of the wave field which then transfer this energy across the continuous spectrum of waves of all scales mainly toward longer (lower-frequency) components, which may be traveling at speeds close to the wind speed, thus allowing them to grow into the dominant waves of frequencies close to the peak frequency of the wave (energy) spectrum. The transfer of energy toward shorter (higher-frequency) waves where it is dissipated occurs at a much less significant rate. Wave breaking is the major player in the third important mechanism, which drives wave evolution – wave energy dissipation. The Southern Ocean has the greatest potential for wave growth due to the never ceasing progression of intense storm systems over vast expanses of sea surface, unimpeded by land masses. Yet, wave models (http://www.knmi.nl/waveatlas/) indicate that the significant wave height (the average crest-to-trough height of the one-third highest waves) rarely goes beyond 10 m. The process, which controls the wave growth, is the dissipation by wave breaking, and to a lesser extent radiation of wave energy away from the storm centers, and into the adjacent seas.
Theories of Wave Growth Phase (a): The Onset of Waves
We consider firstly the initial generation of waves over a flat water surface, independently of the simultaneous generation of a surface drift current. The key theoretical result is that the initial wavelength which can be excited on the air–water interface is a wave of wavelength 17 mm, which is the capillary gravity wave of minimum phase speed 230 mm s 1, controlled by gravity and surface tension. The classical Kelvin–Helmholtz analysis completed in 1871, which relies on random natural disturbances present on the water surface, shows that this wave can only be excited by a velocity shear across the sea surface exceeding 6.5 m s 1. Observations, however, show that waves are generated at much lower wind speeds, of order 1–2 m s 1. In order to resolve this dilemma, another mechanism was proposed by Phillips in 1957. It takes into account the turbulent structure of wind flow. Turbulent pressure pulsations in the air create infinitesimal hollows and ridges in the water surface, which, once the
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WAVE GENERATION BY WIND
pressure pulsation is removed, may start propagating as free waves (similarly to the waves from a thrown stone). If the phase speed of such free waves is the same as the advection speed of the pressure pulsations by the wind, a resonant coupling can occur which will then lead these waves to grow beyond the infinitesimal stage. The first wave to be generated as the wind speed increases is likely to be the wave of minimum phase speed, propagating at an angle to the wind direction. Laboratory observations indicate that at slightly higher wind speeds, wave growth results from a shear flow instability mechanism. These two processes acting in the open ocean give rise to cat’s paws, which are groups of capillary-gravity wavelets (ripples) generated by wind gusts. These results are applicable for clean water surfaces. In the presence of surfactants (surface-active agents), which lower the surface tension, ripple growth is inhibited, and at a sufficiently high surfactant concentration it may be totally suppressed. Phytoplankton are a major source of surfactants that produce surface films, and hence slicks, which are regions of relatively smooth sea surface. Phase (b): Mature Growth
Once the finite-height waves exist, other and much more efficient processes take over the air–sea interaction. Jeffreys in 1924 and 1925 pioneered the analytical research of the wind input to the existing waves by employing effects of the wave-induced pressure pulsations in the air. Potential theory predicts such pressure fluctuations to be in antiphase with the waves, which results in zero average momentum/ energy flux. Jeffreys hypothesised a wind-sheltering effect due to presence of the waves which causes a
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shift of the induced pressure maximum toward the windward wave face and brings about positive flux from the wind to the waves. The original theory of Jeffreys was based on an assumed phenomenon of the air-flow separation over wave crests. Experiments conducted between 1930 and 1950 with wind blown over solid waves found such an effect to be small and the theory fell into a long disrepute. Jeffreys’ sheltering ideas are now coming back, with both experimental and theoretical evidence lending support to his qualitative conclusions. The period from 1957 until the beginning of the new century was dominated by the Miles theory (MT) of wave generation. This linear and quasi-laminar theory, originally suggested by Miles, was later modified by Janssen to allow for feedback changes of the airflow due to growing wind-wave seas. MT regards the air turbulence to be important only in forming the mean boundary-layer wind profile. In such a profile, a critical height exists where the wind speed equals the phase speed of the waves (Figure 2). Wave-induced air motion at this height leads to waterslope-coherent air-pressure perturbations at the water surface and hence to energy transfer to the waves. MT however fails to comprehensively describe known features of the air–sea interaction. For example, for adverse winds the critical height does not exist and therefore no wind-wave energy transfer is expected, but attenuation of waves by such winds is observed. Therefore, a number of nonlinear and fully turbulent alternatives have been developed over the past 40 years. One of the most consistent fully turbulent approaches is the two-layer theory first suggested by Townsend, and advanced by Belcher and Hunt (TBH). TBH revives the sheltering idea in a new form: by considering perturbations of the turbulent shear
U(Z ) − c z x
Direction of wave propagation
Figure 2 Mean streamlines in the turbulent flow over waves according to the MT, in a frame of reference moving with the wave. The critical layer occurs at the height (Z) where the wave speed (C) equals the wind speed (U(Z)). Reproduced from Phillips OM (1966) The Dynamics of the Upper Ocean, figure 4.3. Cambridge, UK: Cambridge University Press, with permission from Cambridge University Press.
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stresses, which are asymmetric along the wave profile. While still in need of experimental verification, particularly for realistic non-monochromatic threedimensional wave fields, this theory has been extensively and successfully utilized in phase-resolvent numerical simulations of the air–sea interaction by Makin and Kudryavtsev. TBH and similar theories attract serious attention because the nature of the air–sea interface is often nonlinear and always fully turbulent. Air–sea interaction is also superimposed by a variety of physical phenomena, which alter the wave growth. Wave breaking appears to cause air-flow separation, which brings the ideas of Jeffreys back in their original form; and gustiness and nonstationarity of the wind, the presence of swell and wave groups, nonlinearity of wave shapes, modulation of surface roughness by the longer waves have all been found to cause either a reduction or an enhancement of the wind-wave input. These processes of active wave generation give rise to the windsea in which a simple measure of the sea state, relevant to wave growth, is the wave age (c=u ) where c is the wave speed of the dominant waves, and u is the friction velocity in the air (the square root of the wind stress divided by the air density). The age of the windsea increases with fetch (the distance from the coast over which the wind is blowing), and the windsea becomes ‘fully developed’, that is, the energy flux from the wind and the dissipation flux are in balance, at a wave age of about 35. Empirical relations for the properties of the fully developed sea in terms of the wind speed (U) at 10 m (approximately the height of the bridge on large ships) given by Toba are: Hs ¼ 0.30U2/g and Ts ¼ 8.6U/g in which Ts ( ¼ 2pc/g) is the significant wave period and g is the acceleration of gravity. As the fetch increases, Hs and Ts both increase toward their fully developed values, and the wave spectrum spreads to lower frequencies. Older seas of wave age greater than 35 can also exist after the wind has moderated. The observations of the velocity structure in the atmospheric boundary layer by Hristov, Miller, and Friehe have shown directly the existence of the MT critical layer mechanism for fast-moving waves of wave age about 30. It is not yet known whether it operates for younger wave age, where a quasilaminar theory may not be appropriate.
the two fluids. In recent times, it has been realized that this model is inadequate, especially at very high wind speeds. The link between the two phases is the breaking wave. In moderate winds (less than about 25 m s 1) the sea state is characterized by whitecapping due to the production of foam in a roller on the wave crests, and also foam streaks on the sea surface (Figure 1), whereas at very high wind speeds (greater than about 30 m s 1, Beaufort force 12) the air is filled with foam. This transition arises from the structure of the breaking waves. In moderate winds, the roller remains attached to the parent wave and dissipates by the formation of foam streaks down its forward face, the trailing face of the wave remaining almost foam free. In this situation the airflow separates over the troughs and reattaches at the crests of the wave, producing Jeffreys-like phase shifts between the pressure and the underlying wave surface which enhance the energy flux to the wave. At very high wind speeds, on the other hand, the foam detaches from the wave crests, and is jetted forward into the air where it disperses vertically and horizontally before returning to the water surface. This process implies a return of momentum to the atmosphere, and hence the sea surface drag coefficient (which is an overall measure of the efficiency of momentum transfer from the atmosphere to the ocean both to waves and turbulence), which has been rising in phase (b), becomes ‘capped’ and possibly even reduces in phase (c). The all-pervasive presence of spray in extreme winds has prompted the anecdotal statement that ‘‘in hurricane conditions the air is too thick to breathe and too thin to swim in.’’ In summary, at very high wind speeds, the airflow effectively streams over the wave elements, which are reduced to acting as sources of spray. The spray then stabilizes the wind profile, and caps the sea surface drag coefficient, and interestingly, this feedback most likely allows the hurricanes to exist in the first place. This analysis has been greatly stimulated by the dropwindsonde observations of Powell, Vickery, and Reinhold in which wind profiles in hurricanes were measured for the first time, and also subsequently by experiments in high-wind-speed wind-wave tanks.
Experiments and Observations Phase (c): Very High Wind-speed Wave Environments
The processes discussed in the previous two subsections are all grounded in two-layer fluid dynamics in which there exists a sharp interface between
Direct Measurements of Wave Growth Rates
The wind-to-wave energy input, which for each wave component is proportional to the time average of the product of the sea surface slope and sea surface atmospheric pressure, is the only source function,
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WAVE GENERATION BY WIND
responsible for wave development, which can so far be measured directly, although this is an extremely difficult experimental task, and only a handful of attempts have been undertaken. The principal theoretical difficulty is that the sea surface atmospheric pressure must be estimated by extrapolating downward from the measurement level. The pressure pulsations of interest are of the order of 10 5 10 4 of the mean atmospheric pressure and therefore require very sensitive probes. The surface-coherent oscillations are superposed, at the same frequencies, by random turbulent fluctuations, which are tens and hundreds of times greater in magnitude. This implies that a sophisticated data analysis is required to separate the signal buried in the noise. The wave-induced pressure decays rapidly away from the wavy surface and thus, particularly for short wave scales, it has to be sensed very close to the surface, below the wave crests of dominant waves. At the same time, the air-pressure probes have to stay dry. The last requirement leads either to measurements being conducted above the crests, which limits the estimates to the amplification of the dominant waves only, or to the use of a wavefollowing technique. The latter has a limited capability beyond the laboratory conditions and involves further complications due to multiple corrections needed to recover the signal contaminated by air motion in the tubes connecting the pressure probes with pressure transducers. The first field experiment of the kind, conducted by Snyder and others in 1981, resulted in a parameterization of wind input across the wave spectrum, which has been frequently used until now. Most of these measurements, however, were taken by stationary wave probes above the wave crests, and the winds involved were very light, mostly around 4 m s 1. Waves at such winds are known not to break, and this fact implies an air–sea energy balance, very different from that at moderate and strong winds. Therefore, extrapolation of these results into normal wave conditions has to be exercised with great caution. Another field experiment was conducted by Hsiao and Shemdin in 1983. It used a wave-following technology and thus was able to obtain a spectral set of measurements somewhat beyond the dominant wave scales. This study produced a parameterization in which the growth rates were very low. Its drawback comes from the fact, that in the majority of circumstances the measured waves were ‘quite old’, half of the records being above the limit for the fully developed windsea. For such waves, the growth rates are expected to be very small if not zero, and given the measurement and analysis errors, the
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interpretation of the low growth values becomes quite uncertain. On the other hand, a set of precision wavefollowing measurements conducted by Donelan in 1999 in a wind-wave tank where the waves were very young (c/uE1), produced a growth rate 2.5 times that of Hsiao and Shemdin’s, and also demonstrated a very significant wave attenuation rate by the adverse wind. The differences between these two data sets stimulated the latest campaign undertaken by Donelan and others in 2006. The Lake George experiment in Australia employed precision laboratory instruments in a field site. The site was chosen such that it provided a variety of wind-wave conditions, including very strongly wind-forced and very steep waves normally unavailable for measuring in the open ocean. The results revealed some new properties of the air–sea interaction, in which wave growth rates merged with previous results at moderate winds, but deviated significantly in strong wind conditions with continually breaking steep waves, in which full flow separation, that is, detachment of the streamlines of the airflow at the wave crest and reattachment well up the windward face of the preceding wave, occurred leading to a reduction of the wind input. This reduction means that as the winds become stronger the wind-to-wave input will keep growing, but the growth rates will be reduced compared to simple extrapolations to extreme conditions of the input measured at moderate winds. This behavior, which is consistent with that in very high wind speeds in the open ocean, did not appear to be associated with spray production. It is worth mentioning that one of the key properties of the wind input – its directional distribution – has never been measured. It was assumed to be a cosine function by Plant, but no data on the wind input directional distribution are available. Such measurements cannot be made adequately in a windwave tank, and are a formidable task in the field where a spatial array of wave-following pressure probes would have to be operated. Directional wave input distribution, nevertheless, is an integral part of any wave forecast model and therefore this problem remains a major challenge for the experimentalists.
Reverse Momentum Transfer
Nonlinear interactions transfer energy to the longer, faster-propagating waves, which after leaving the region of generation are known as swell. The swell may travel at a speed greater than the local wind speed, and even propagate in the opposite direction
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to the wind, leading to the possibility of reverse momentum transfer from the waves to the wind. The direct effect of waves propagating faster than the wind has been measured in a wind-wave tank by Donelan; however, when the results were applied to swell propagating in the ocean, the damping effect was found to be much too large. This is well known to surfers, who rely on the arrival of swells from distant storms: their propagation across the Pacific Ocean (over a distance of c. 10 000 km) was measured in a classical campaign conducted by Snodgrass and others in 1963. Reverse momentum transfer has also been observed in wind profiles. In Lake Ontario, while a swell was running against a very light wind, the wind speed increased downward (toward the sea surface) due to the propagation of the swell, rather than the normal decrease. This is a clear example of reverse momentum transfer arising from the presence of a wave train of nonlocal origin. Reverse momentum transfer, however, is a ubiquitous process in windseas in which part of the wind input is returned to the atmosphere by the dissipation process, especially the injection of spray.
Numerical Modeling of the Wind Input Over the past few decades, numerical modeling of ocean waves has developed into a largely independent field of study. Two different kinds of models have been used to study the wind input. Historically, spectral models based on known physics were the first. Their progress is described in great detail in the book by Komen and others. Given the uncertainties of such predictions due to simultaneous action of the multiple wave dynamics processes, the capacity of such models to scrutinize the wind input function is limited. For example, very high quality synoptic analyses of weather systems are necessary in order to discriminate between the various coupling mechanisms for wave growth by comparing observational wave data from wave buoys with the predictions of coupled wind-wave simulations. In these models the formulation of the wave energy dissipation is based on tuning the total energy balance. Csanady, in a lucid textbook on air–sea interaction, notes that in a fetch-limited windsea only about 6% of the momentum transferred from the wind to the water supports the downwind growth of the dominant waves, the remainder being accounted for locally by the dissipation stress, that is, the rate of loss of momentum from the wave field to the ocean. The phase-resolvent models are another kind of numerical simulations of air–sea interaction, which
reproduce wind input and wave evolution in physical rather than wavenumber space. Such models solve the basic fully nonlinear equations of fluid mechanics explicitly and recent advances in numerical techniques allow us to reproduce the water surface, airflow, and wave motion with potentially absolute precision and unlimited temporal and spatial resolution. Use of such models to forecast waves globally is obviously not feasible, but they now constitute a very effective tool for dedicated studies of wind–wave interaction. The interested reader is referred to recent research by Makin and Kudryavtsev, and by Chalikov and Sheinin.
Conclusions It is clear from this article that there are still many tasks ahead to fully understand wave generation by wind. The nonlocal aspects of wave generation by wind are a particularly challenging topic. Contemporary interest lies with our climate system. The interface between the atmosphere and the ocean is vital in this regard. This holistic view calls urgently for further study, especially of extreme events in which major momentum transfers occur, affecting the land through the initiation of hurricanes, and the sea through mixing below the wave boundary layer into the deep ocean.
See also Breaking Waves and Near-Surface Turbulence. Rogue Waves. Surface Gravity and Capillary Waves. Tsunami. Wind- and Buoyancy-Forced Upper Ocean.
Further Reading Belcher SE and Hunt JCR (1998) Turbulent flow over hills and waves. Annual Review of Fluid Mechanics 30: 507--538. Bye JAT and Jenkins AD (2006) Drag coefficient reduction at very high wind speeds. Journal of Geophysical Research 111: C03024 (doi:10.1029/2005JC003114). Chalikov D and Sheinin D (2005) Modeling extreme waves based on equations of potential flow with a free surface. Journal of Computational Physics 210: 247--273. Csanady GT (2001) Air–Sea Interaction Laws and Mechanisms, 239pp. Cambridge, UK: Cambridge University Press. Donelan MA (1999) Wind-induced growth and attenuation of laboratory waves. In: Sajjadi SG, Thomas NH, and Hunt JCR (eds.) Wind-Over-Wave Couplings: Perspectives and Prospects, pp. 183--194. Oxford, UK: Clarendon.
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WAVE GENERATION BY WIND
Donelan MA, Babanin AV, Young IR, and Banner ML (2006) Wave follower measurements of the wind input spectral function. Part 2: Parameterization of the wind input. Journal of Physical Oceanography 36: 1672--1688. Hristov T, Friehe C, and Miller S (2003) Dynamical coupling of wind and ocean waves through waveinduced air flow. Nature 422: 55--58. Jones ISF and Toba Y (eds.) (2001) Wind Stress over the Ocean, 307pp. Cambridge, UK: Cambridge University Press. Komen GI, Cavaleri L, Donelan M, Hasselmann K, Hasselmann S, and Janssen PAEM (1994) Dynamics and Modelling of Ocean Waves, 532pp. Cambridge, UK: Cambridge University Press. Kudryavtsev VN and Makin VK (2007) Aerodynamic roughness of the sea surface at high winds. BoundaryLayer Meteorology 125: 289--303. Makin VK and Kudryavtsev VN (2003) Wind-over-waves coupling. In: Sajjadi SG and Hunt LJ (eds.) Wind Over Waves II: Forecasting and Fundamentals of Applications, pp. 46--56. Chichester: Horwood Publishing.
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Phillips OM (1966) The Dynamics of the Upper Ocean. Cambridge, UK: Cambridge University Press. Powell MD, Vickery PJ, and Reinhold TA (2003) Reduced drag coefficient for high wind speeds in tropical cyclones. Nature 422: 279--283. Snodgrass FE, Groves GW, Hasselmann KF, Miller GR, Munk WH, and Powers WH (1966) Propagation of ocean swell across the Pacific. Philosophical Transactions of the Royal Society of London 259: 431--497. Toba Y (1972) Local balance in the air–sea boundary processes. Part I: On the growth process of wind waves. Journal of the Oceanographical Society of Japan 28: 15--26. Young IR (1999) Wind Generated Ocean Waves, 288pp. Oxford, UK: Elsevier.
Relevant Website http://www.knmi.nl/waveatlas – The KNMI/ERA-40 Wave Atlas.
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WAVES ON BEACHES
310
Incident waves
Offshore
Wave motions are one of the most familiar of oceanographic phenomena. The waves that we see on beaches were originally generated by ocean winds and storms, sometimes at long distances from their final destination. In fact, groups of waves, generated by large storms, have been tracked from the Southern Ocean near Australia all the way to Alaska. Open ocean waves can be thought of as simple sinusoids that are superimposed to yield a realistic sea. Waves entering the nearshore, called incident waves, can have wave periods (T, the time between consecutive passages of wave crests) ranging from 2 to 20 s, with 10 s a typical value. Wave heights (H, the vertical distance from the trough to peak of a wave) can exceed 10 m, but are typically 1 m, representing an energy density, of 1250 J m2 (r is the density of sea water, g is the acceleration of gravity) and a flux of power impinging on the coast of about 10 kW per meter of coastline. Although this is a substantial amount of power, it is not enough to make broad commercial exploitation of wave power economical at the time of writing. Of interest in this section are the dynamics of waves once they progress into the shallow beach environment such that the ocean bottom begins to restrict the water motions. Most people are familiar with refraction (the turning of waves toward the beach), wave breaking, and swash (the back and forth motion of the water’s edge), but are less familiar with the other types of fluid motion that are generated near the beach. Figure 1 illustrates schematically the evolution of ocean wave energy as it moves from deep water (top of the figure) through progressively shallower water toward the beach (bottom of the figure). Offshore, most energy lies in waves of roughly 10 s period (middle of the figure). However, the processes of shoaling distribute that energy to both higher frequencies (right half of the figure) and lower frequencies (left half) including mean flows. In general, these processes can be distinguished as those that
Beach Topography
Shoaling
Introduction
Cross-shore location
This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3194–3201, & 2001, Elsevier Ltd.
Shoaling
Infragravity
High frequency
Wind waves
Beach Topography
Break point
Copyright & 2001 Elsevier Ltd.
occur offshore of the surf zone (where waves become overly steep and break) and those that occur within the surf zone. The axes of Figure 1, cross-shore position and frequency, are two of several variables that can be used to structure a discussion of near-shore fluid dynamics. Other important distinctions that will be made include whether the incident waves are monochromatic (single frequency) versus random (including a range of frequencies), depth-averaged versus depth-dependent, longshore uniform (requiring consideration of only one horizontal dimension, 1HD) versus long shore variable (2HD), and linear versus nonlinear.
Breaking
'Mean' flows
Shoreline
R. A. Holman, Oregon State University, Corvallis, OR, USA
Infragravity
Wind waves
High frequency
Turbulence
Far infragravity Swash
Reflection
0.001
0.01
0.1
1.0
10
Frequency (Hz) Figure 1 Schematic of important near-shore processes showing how the incident wave energy that drives the system evolves as the waves progress from offshore to the shoreline (top to bottom of figure). Wave evolution is grouped into processes occurring seaward of the breakpoint (labeled ‘shoaling’) and those within the surf zone (denoted ‘breaking’). In both cases, energy is spread to lower (left) and higher (right) frequencies. The beach topography provides the bottom boundary condition for flow, so is important to wave processes. In turn, the waves move sediment, slowly changing the topography. Wind and tides may be important in some settings, but are not shown here.
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WAVES ON BEACHES
The Dynamics of Incident Waves Much of the early progress in understanding nearshore waves was based on the examination of a monochromatic wave train, propagating onto a long shore uniform beach (1HD). Many observable properties can be explained in terms of a few principles including conservation of wave crests, of momentum, and of energy. Most dynamics are depthaveraged. Table 1 lists a number of properties of monochromatic ocean waves, in the linear limit of infinitesimal wave amplitude (known as linear, or Airy wave theory). The general expressions (center column) contain complicated forms that can be substantially simplified for both shallow (depths less than 1/20 of the deep water wavelength, L0 ) and deep (depths greater than 1/2 L0 ) water limits. The speed of wave propagation is known as the celerity or phase speed, c, to distinguish it from the velocity of the actual water particles. In deep water, c depends only on the wave period (independent of depth). However, as the wave enters shallower water, the wavelength decreases and the phase speed becomes slower (contrary to common belief, this is not a result of bottom friction). An interesting consequence of the slowing is wave refraction, the turning of waves toward the coast. For a wave approaching the coast at any angle, the end in shallower water will always progress more slowly than Table 1
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the deeper end. By propagating faster, the deeper end will begin to catch up to the shallow end, effectively turning the wave toward the beach (refraction). In shallow water, the general expression for celerity, c ¼ ðghÞ1=2 , depends only on depth so that waves of all periods propagate at the same speed. The energy density of Airy waves (energy per unit area) is the sum of kinetic and potential energy components and depends only on the square of the wave height (Table 1). Perhaps of more interest is the rate at which this energy is propagated by the wave train, known as the wave power, P, or wave energy flux. In deep water, wave energy progresses at half the speed of wave phase (individual wave crests will out-run the energy packet), whereas in shallow water energy travels at the same speed as wave phase and the flux depends only on H 2 h1=2 . Offshore of the surf zone, wave energy is conserved since there is no breaking dissipation and energy loss through bottom friction has been shown to be negligible except over very wide flat seas. Thus, as the depth, h, decreases, the wave height, H, must increase to conserve H 2 h1=2 . This is a phenomenon familiar to beachgoers as the looming up of a wave just before breaking. The combined result of shoaling is reduced wavelength and increased wave height, hence waves that become increasingly steep and may become unstable and break. One criterion for breaking is that
Kinematic relationships of linear wavesa
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the increasing water particle velocities (u in Table 1) exceed the decreasing wave phase speed such that the water leaps ahead of the wave in a curling or plunging breaker. From the relationships in Table 1, it can be found that this occurs. when g, the wave height to depth ratio ðg ¼ H=hÞ exceeds a value of 2. Of course, for waves that have steepened to the point of breaking, the approximations of infinitesimal waves, inherent in Airy wave theory, are badly violated. However, observations show that g does reach a limiting value of approximately 1 for monochromatic waves and 0.4 for a random wave field. As waves continue to break across the surf zone, the wave height decreases in a way that g is approximately maintained, and the wave field is said to be saturated (cannot get any larger). The above-saturation condition implies that wave heights will be zero at the shoreline and there will be no swash, in contradiction to common observation. Instead, it can be shown that very small amplitude waves, incident on a sloping beach, will not break unless their shoreline amplitude, as , exceeds a value determined by s2 as rk gb2
½1
where k is an O(1) constant. For larger amplitudes, the wave amplitude at any cross-shore position is the sum of a standing wave contribution of this maximum value plus a dissipative residual that obeys the saturation relationship. The ratio of terms on the left-hand side of eqn.[1] is important to a wide range of nearshore phenomena and is often re-written as the Iribarren number, x0 ¼
b ðHs =L0 Þ1=2
½2
where the measure of wave amplitude is replaced by the offshore significant wave height,1 Hs. This form clarifies the importance of beach steepness, made dynamically important by comparing it to the wave steepness, Hs =L0 . For very large values of x0 , the beach acts as a wall and is reflective to incident
1
Although the peak to trough vertical distance for monochromatic waves is a unique and hence sensible measure of wave height, for random waves this scale is a statistical quantity, representing a distribution. A single measure, often chosen to represent the random wave Reld, is the significant wave height, Hs, defined as the average height of the largest one-third of the waves. This statistic was chosen historically as best representing the value that would be visually estimated by a semitrained observer. It is usually calculated as four times the standard deviation of the sea surface times series.
waves (the non-breaking case from eqn. [1]). For smaller values, the presence of the sloping beach takes on increasing importance as the waves begin to break as the plunging breakers that surfers like, where water is thrown ahead of the wave and the advancing crest resembles a tube. Still smaller beach steepnesses (and x0 ) are associated with spilling breakers in which a volume of frothy turbulence is pushed along with the advancing wave front.
Radiation Stress: the Forcing of Mean Flows and Set-up The above discussion is based on the assumption of linearity, strictly true only for waves of infinitesimal amplitude. Because the dynamics are linear, energy in a wave of some particular period, say 10 s, will always be at that same period. In fact, once wave amplitude is no longer negligible, there are a number of nonlinear interactions that may transfer energy to other frequencies, for example to drive currents (zero frequency). Nonlinear terms describe the action of a wave motion on itself and arise in the momentum equation from the advective terms, uru, and from the integrated effect of the pressure term. For waves, the time-averaged effect of these terms can easily be calculated and expressed in terms of the radiation stress, S, defined as the excess momentum flux due to the presence of waves. Since a rate of change of momentum is the equivalent of a force by Newton’s second law, radiation stress allows us to understand the time-averaged force exerted by waves on the water column through which they propagate. A spatial gradient in radiation stress, for instance a larger flux of momentum entering a particular location than exiting, would then force a current. Radiation stress is a tensor such that Sij is the flux of i-directed momentum in the j-direction. For waves in shallow water, approaching the coast at an angle y, the components of the radiation stress tensor are " S¼
Sxx
Sxy
Syx
Syy
#
" ¼E
ðcos2 y þ 1=2Þ cos y sin y cos y sin y ðsin2 y þ 1=2Þ
# ½3
where x is the cross-shore distance measured positive to seaward from the shoreline and y is the long-shore distance measured in a right-hand coordinate system with z positive upward from the still water level. For a wave propagating straight toward the beach (y ¼ 0) Sxx ¼ 3=2E is the shoreward flux of shoreward-directed momentum. The increase of wave height (hence energy, E) associated with shoaling outside the surf zone must be accompanied by an
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WAVES ON BEACHES
increasing shoreward flux of momentum (radiation stress). This gradient, in turn, provides an offshore thrust, pushing water away from the break point and yielding a lowering of mean sea level called setdown. As the waves start to break and decrease in height through the surf zone, the decreasing radiation stress pushes water against the shore until an opposing pressure gradient balances the radiation stress gradient. The resulting set-up at the shoreline, Z, ¯ a contributor to coastal erosion and flooding, is found to depend on the offshore significant wave height, Hs , as Z¯ max ¼ KHs x0
½4
where K is found empirically to be 0.45. If waves approach the beach at an angle, they also carry with them a shoreward flux of longshore-directed momentum, Syx . Cross-shore gradients in this quantity, due to the breaking of waves in the surf zone, provide a net long shore force that accelerates a long shore current, V¯ along the beach until the forcing just balances bottom friction. If the cross-shore structure of V¯ is solved for, a discontinuity is evident at the seaward limit of the surf zone, where the radiation stress forcing jumps from zero (seaward of the break point) to a large value (where the wave just begin to break). This discontinuity is an artifact of the fact that every wave breaks at exactly the same location for an assumed monochromatic wave forcing, and must be artificially smoothed by an assumed horizontal mixing for this case. However, a natural random wave field consists of an ensemble of waves with (for linear waves) a Rayleigh distribution of heights. Depthlimited breaking of such a wave field will be spread over a region from offshore, where a few largest waves break, to onshore where the smallest waves finally begin to dissipate. The spatially distributed nature of these contributions to the average radiation stress provides a natural smoothing, often obviating the need for additional horizontal smoothing.
Nonlinear Incident Waves The above discussion dwelt on the nonlinear transfer of energy from incident waves to mean flows. Nonlinearities will also transfer energy to higher frequencies, yielding a transformation of incident wave shape from sinusoidal to peaky and skewed forms. The Ursell number, ðH=LÞðL=hÞ3 , measures the strength of the nonlinearity. For monochromatic incident waves, this evolution was often modeled in terms of an ordered Stokes expansion of the wave form to produce a series of harmonics (multiples of the incident
313
wave frequency) that are locked to the incident wave. For waves with Ursell number of O(1), propagating in depths that are not large compared to the wave height, higher order theories must be used to model the finite amplitude dynamics. For a random sea under such theories, the total evolution of the spectrum must be found by summing the spectral evolution equations for all possible Fourier pairs (in other words, all frequencies in the sea can and will interact with all other frequencies). Such approaches are very successful in predicting the evolving shape and nonlinear statistics (important for driving sediment transport) for natural random wave fields outside the surf zone.
Vertically Dependent Processes Depth-independent models are successful in reproducing many nearshore fluid processes but cannot explain several important phenomena, for example undertow, offshore-directed currents that exist in the lower part of the water column under breaking waves. The primary cause of depth dependence arises from wave-breaking processes. When waves break, the organized orbital motions break down, either through the plunge of a curling jet of water thrown ahead of the advancing wave or as a turbulent foamy mass (called a roller) carried on the advancing crest. Both processes originate at the surface but drive turbulence and bubbles into the upper part of the water column. The transfer of momentum from wave motions to mean currents described by radiation stress gradients above does not account for the existence of an intermediate repository, the active turbulence of the roller, that decays slowly as it is carried with the progressing wave. This time delay causes a shift of the forcing of longshore currents, such that a current jet will occur landward of the location expected from study of the breaking locations of incident waves. The other consequence of the vertical dependence of the momentum transfer is that the shoreward thrust provided by wave breaking is concentrated near the surface. Set-up, the upward slope of sea level against the shore, will balance the depth averaged wave forcing. However, due to the vertical structure of the forcing, shoreward flows are driven near the top of the water column and a balancing return flow, the undertow, occurs in the lower water column. Undertow strengths can reach 1 m s1.
2HD Flows – Circulation All of the previous discussion was based on the assumption that all processes were long-shore uniform
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(1 HD) so that no long-shore gradients existed. It is rare in nature to have perfect long shore uniformity. Most commonly, some variability (often strong) exists in the underlying bathymetry. This can lead to refractive focusing (the concentration of wave energy by refraction of waves onto a shallower area) and the forcing of long-shore gradients in wave height, hence of setup. Since setup is simply a pressure head, longshore gradients will drive long-shore currents toward low points where the converging water will turn seaward in a jet called a rip current. It is possible to develop long-shore gradients in wave height (hence rips) in the absence of long-shore variations in bathymetry. Interactions between two elements of the wave field (either two incident wave trains from different directions or an incident wave and an edge wave, defined below) can force rip currents if the interacting trains always occur with a fixed relative phase.
Infragravity Waves and Edge Waves There is a further, very important consequence of the fact that natural wave fields are not monochromatic, but instead are random. For random waves, wave height is no longer constant but varies from wave to wave. Usually these variations are in the form of groups of five to eight waves, with heights gradually increasing then decreasing again. This observation is known as surf beat and is particularly familiar to surfers. A consequence of these slow variations is that the radiation stress of the waves is no longer constant, but also fluctuates with wave group timescales and forces flows (and waves) in the near-shore with corresponding wave periods. These waves have periods of 30–300 s and are called infragravity waves, in analogy to infrared light being lower frequency than its visible light counterpart. The direct forcing of infragravity motions described above can be thought of as a time-varying setup, with the largest waves in a group forcing shoreward flows that pile up in setup, followed by seaward flow as the setup gradients dominate over the weaker forcing of the small waves. If the modulations of the incident wave group are long shore uniform, this result of this setup disturbance will simply be a free (but low frequency) wave motion that propagates out to sea. However, in the normal case of wave groups with longshore (as well as time) variability, we can think of the response by tracing rays as the setup disturbance tries to propagate away. Rays that travel offshore at an angle to the beach will refract away from the beach normal (essentially the opposite of incident wave refraction, discussed
earlier). For rays starting at a sufficiently steep angle to the normal, refraction can completely turn the rays such that they re-approach and reflect from the shore in a repeating way and the energy is trapped within the shallow region of the beach. These trapped motions are called edge waves because the wave motions are trapped in the near-shore wave guide. (Any region wherein wave celerity is a minimum can similarly trap energy by refraction and is known as a wave guide. The deep ocean sound channel is a wellknown example and allows propagation of trapped acoustic energy across entire ocean basins.) Motions that do not completely refract and thus are lost to the wave guide are called leaky modes. The requirement that wave rays start at a sufficiently steep angle to be trapped by refraction can be expressed in terms of the long-shore component of wavenumber, ky . For large ky (waves with a large angle to the normal), rays will be trapped in edge waves whereas small ky motions will be leaky modes. The cutoff between these is s2 =g. In the same sense that waves that slosh in a bathtub occur as a discrete set of modes that exactly fit into the tub, edge waves occur in a set of modes that exactly fit between reflection at the shoreline and an exponentially decaying tail offshore. The detailed form of the waves depends on the details of the bathymetry causing the refraction. However, for the example of a plane beach of slope bðh ¼ xtanbÞ, the cross-shore forms of the lowest four modes (mode numbers, n ¼ 0, 1, 2, 3), are shown in Figure 2 and are given in Table 2. The existence of edge waves as a resonant mode of wave energy transmission in the near-shore has several impacts. First, the dispersion relation provides a selection for particular scales. For example, Figure 3 shows a spectrum of infragravity wave energy collected at Duck, North Carolina, USA. The concentration of energy into very clear, preferred scales is striking and has led to suggestions that edge waves may be responsible for the generation of sand bars with corresponding scales. Second, because edgewave energy is trapped in the near-shore, it can build to substantial levels even in the presence of weak, incremental forcing. Moreover, because edge-wave energy is large at the shoreline where the incident waves have decayed to their minimum due to breaking, edge waves may feasibly be the dominant fluid-forcing pattern on near-shore sediments in these regions. The magnitudes of infragravity energy (including edge waves and leaky modes) have been found to depend on the relative beach steepness as expressed by the Iribarren number (eqn. [2]). For steep beaches (high x0 ), very little infragravity energy can be
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WAVES ON BEACHES 1.0
Table 3 types
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Magnitude of infragravity waves on different beach
0.5
n=2
(x)
n=0 0
n=1 _ 0.5
0
10
20
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30
40
50
60
70
2x / g tan
aLeast squares regression slope between the significant swash height (computed from the infragravity band energy only) and the offshore significant wave height. Reproduced from Howd PA, Oltman-Shay J, and Holman RA (1991) Wave variance partitioning in the trough of a barred beach. Journal of Geophysical Research 96 (C7), 12781} 12795.)
Figure 2 Cross-shore structure of edge waves. Only the lowest four mode numbers of the larger set are shown. The mode number, n, describes the number of zero crossings of the modes. So, for example, a mode 1 edge wave always has a low offshore, opposite a shoreline high, and visa versa. Edge waves propagate along the beach.
representative beach locations, with mean values of x0 and of m, the linear regression slope between the measured significant swash magnitude,2Rs , in the infragravity band, and the offshore significant wave height, Hs .
Table 2 The average abundance of the refractory elements in the Earth’s crust, and their degree of enrichment, relative to aluminum, in the oceans
Shear Waves
generated and the beaches are termed reflective due to the high reflection coefficient for the incident waves. However, for low-sloping beaches (small x0 ), infragravity energy can be dominant, especially compared to the highly dissipated incident waves. On the Oregon Coast of the USA, for example, swash spectra have been analyzed in which 99% of the variation is at infragravity timescales (making beachcombing an energetic activity). Table 3 lists five
Up until the mid-1980s long shore currents were viewed as mean flows whose dynamics were readily described as in the above sections. However, field data from the Field Research Facility in Duck, North Carolina, provided surprising evidence that as longshore currents accelerated on a beach with a welldeveloped sand bar, the resulting current was not steady but instead developed slow fluctuations in strength and a meandering pattern in space. Typical wave periods of these wave are hundreds of seconds and long-shore wavelengths are just hundreds of meters (Figure 3). These very low frequencies are called far infragravity waves, in analogy to the relationship of far infrared to infrared optical frequencies. However, the wavelengths are several orders of magnitude shorter than that which would be expected for gravity waves (e.g., edge waves or leaky modes) of similar periods. These meanders have been named shear waves and arise due to an instability of strong currents, similar to the instability of a rising column of smoke. The name comes from the dependence of the dynamics (described briefly below) on the shear of the longshore current (the cross-shore gradient of the longshore current). A jet-like current with large shear, such as might develop on a barred beach where the wave forcing is concentrated over and near the bar,
2 Swash oscillations are commonly expressed in terms of their vertical component.
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WAVES ON BEACHES 1
0.050 0.045
2
2
1 0
0
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0.035 0.030 0.025 0.020 0.015 0.010 0.005
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have been shown to develop similar instabilities although with very larges scales. Similarly, under wave motions, the bottom boundary layer, matching the moving wave oscillations of the water column interior with zero velocity at the fixed boundary, is also unstable. It can be shown that a necessary condition for such an instability is the presence of an inflection point in the velocity profile (the spatial curvature of the current field changes sign), a requirement satisfied by long shore currents on a beach. In that case, crossshore perturbations will extract energy from the mean long-shore current at a rate that depends on the strength of the current shear. Thus, these perturbations will grow to become first wave-like meanders, then if friction is not strong, to become a field of turbulent eddies. The extent of this evolution (wave-like versus eddy-like) is not yet known for natural beach environments. Shear waves can clearly form an important component of the near-shore current field.) Root mean square (RMS) velocity fluctuations can reach 35 cm s1 in both cross-shore and long-shore components of flow. This corresponds to an RMS swing of the current of 70 cm s1, with many oscillations much larger.
Conclusions
% Power
Figure 3 The spectrum of low frequency wave motions, as measured by current meters sampling the long shore component of velocity, from Duck, North Carolina, USA. The vertical axis corresponds to frequency and the horizontal axis to along shore component of wavenumber. Positive wavenumbers describe wave motions propagating along the beach to the south. Surprisingly, wave energy is not spread broadly in frequency– wavenumber space, but concentrates on specific ridges. Black lines, indicating the theoretical dispersion lines for edge waves (mode numbers marked at figure top), provide a good match to much of the data at low frequencies with some offset at higher frequency associated with Doppler shifting by the long-shore current. The concentration of low-frequency energy angling up to the right corresponds to shear waves. (After Oltman-Shay J and Guza RT (1987) Infragravity edge wave observations on two California beaches. Journal of Physical Oceanography 17(5): 644–663.)
can develop strong shear waves. In contrast, for a broad, featureless planar beach, the shear of any generated long-shore current will be weak so that shear wave energy may be undetectable. This explains why shear waves were not discovered until field experiments were carried out on barred beaches. The instability by which shear waves are generated has a number of other analogs in nature. Large-scale coastal currents, flowing along a continental shelf,
As ocean waves propagate into the shoaling waters of the nearshore, they undergo a wide range of changes. Most people are familiar with the refraction, shoaling and eventual breaking of waves in a near-shore surf zone. However, this same energy can drive strong secondary flows. Wave breaking pushes water shoreward, yielding a super-elevation at the shoreline that can accentuate flooding and erosion. Waves arriving at an angle to the beach will drive strong currents along the beach that can transport large amounts of sediment. Often these currents form circulation cells, with strong rip currents spaced along the beach. Natural waves occur in groups, with heights that vary. The breaking of these fluctuating groups drives waves and currents at the same modulation timescale, called infragravity waves. These can be trapped in the nearshore by refraction as edge waves. Even long shore currents can develop instabilities called shear waves that drive meter-per-second fluctuations in the current strength with timescales of several minutes. The apparent physics that dominates different beaches around the world often appears to vary. For example, on low-sloping energetic beaches,
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WAVES ON BEACHES
infragravity energy often dominates the surf zone, whereas shear waves can be very important on barred beaches. In fact, the physics is unchanging in these environments, with only the observable manifestations of that physics changing. The unification of these diverse observations through parameters such as the Iribarren number is an important goal for future research.
Symbols Used E H Hs L L0 P Rs RMS S T V¯ X a as c cg g h k n
wave energy density wave height significant wave height wavelength deep water wave length wave power or energy flux significant swash height root mean square statistic radiation stress (wave momentum flux) wave period mean longshore current distance coordinate in the direction of wave propagation wave amplitude wave amplitude at the shoreline wave celerity, or phase velocity wave group velocity acceleration of gravity water depth wavenumber (inverse of wavelength) ratio of group velocity to celerity
m n u v x y z b g Z theta x0 r s j Z¯ max r
317
ratio of infragravity swash height to offshore wave height edge wave mode number water particle velocity under waves long-shore component of wave particle velocity cross-shore position coordinate long-shore position coordinate vertical coordinate beach slope ratio of wave height to local depth for breaking waves sea surface elevation angle of incidence of waves relative to normal Iribarren number density of water radial frequency 2p=T cross-shore structure function for edge waves mean set-up at the shoreline gradient operator
See also Beaches, Physical Processes Affecting. Breaking Waves and Near-Surface Turbulence. Coastal Trapped Waves. Sea Level Change. Surface Gravity and Capillary Waves. Wave Generation by Wind.
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WEDDELL SEA CIRCULATION E. Fahrbach and A. Beckmann, Alfred-WegenerInstitut fu¨r Polar- und Meeresforschung, Bremerhaven, Germany Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3201–3209, & 2001, Elsevier Ltd.
Introduction The Weddell Sea is an area of intense air–sea interaction and vertical exchange. The resulting cold water masses participate in the global thermohaline circulation as deep and bottom waters. The largescale horizontal circulation in the Weddell Sea is dominated by a cyclonic (clockwise) gyre conforming to the coastline and topographic features like midocean ridges and submarine escarpments. The flow is driven by both wind and thermohaline forcing. The meridional component at the eastern edge of the gyre transports upper ocean water from the Antarctic Circumpolar Current to the Antarctic Continent, where its density increases by ocean–ice– atmosphere interaction processes. Part of this newly formed water leaves the inner Weddell Sea northward and escapes through gaps and passages and thus ventilates the deep world ocean. Upwelling in the Antarctic Divergence and sinking plumes along the continental slope cause a large-scale overturning motion. Intermittently, open ocean deep convection might also play a role in deep water renewal. The observational database of direct current measurements is rather weak. Consequently, the most reliable basin-wide estimates of ocean currents are obtained from adequately validated numerical models.
Limits of the Weddell Sea Geographically, the Weddell Sea is a southern embayment of the Atlantic Ocean, bounded to the west by the Antarctic Peninsula up to Joinville Island, to the east by Coats Land on the Antarctic Continent with the north-eastern limit at 731250 S, 201000 W, and to the south by the Filchner–Ronne Ice Shelf. In these limits it covers an area of 2 800 000 km2. From an oceanographic point of view, however, it is more adequate to consider the closed cyclonic circulation cell as one dynamically connected regime; hence the Weddell Sea is often considered as the area of the Weddell Gyre which extends eastward as far as 301E or 401E (Figure 1). Then, the Weddell Sea is
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bounded to the north by the South Scotia, the North Weddell and the Southwest Indian Ridges where the Weddell Front marks the transition from the water masses of the Weddell Gyre to the Antarctic Circumpolar Current. At the eastern boundary no obvious front separates the Weddell and the Circumpolar water masses which leaves the eastern boundary diffuse. Obviously, limits based on water mass properties and current branches are time dependent.
The Effect of Ice–Ocean Interaction on the Currents Ocean currents are wind-driven and thermohalinedriven; the particular situation in the Weddell Sea is even more complex due to the presence of the seasonally variable sea ice belt. During the winter months, sea ice covers almost all of the Weddell Sea (exceptions are the occurrences of coastal or, less frequently, open ocean polynyas); during summer, only a relatively small area in the southwestern Weddell Sea remains ice covered. The presence of sea ice affects the ocean currents both through the modification of the momentum transfer from the wind to the ocean and through density changes caused by the salt gain during the freezing phase and the fresh water release during melting. In areas of stagnant sea ice the internal ice stresses balance the momentum supplied by the wind and the momentum input into the ocean is largely reduced; this situation is typical for the western Weddell Sea. The freeze and melt cycle of sea ice (and the corresponding freshwater fluxes) is an equally important component in the thermohaline forcing of the currents in the Weddell Sea; as freezing and melting regions are not identical, the sea ice drift with wind and ocean currents causes a net northward freshwater transport. This leads to a salt gain in the interior Weddell Sea and a freshwater gain at its northern boundary.
The Database on Ocean Currents in the Weddell Sea The database to derive ocean currents in the Weddell Sea is small compared to other ocean areas. This is due to a number of reasons.
•
The uninhabited Antarctic Continent does not require intensive shipping traffic and consequently
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WEDDELL SEA CIRCULATION
319
0°
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45°W
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Figure 1 Schematic representation of the Weddell Gyre and the Antarctic Circumpolar Current in the Atlantic and Indian sectors of the Southern Ocean. The locations of the two transects with direct current measurements are indicated by lines. AP, Antarctic Peninsula; FRIS, Filchner–Ronne Ice Shelf; JI, Joinville Island; KN, Kapp Norvegia; MR, Maud Rise.
• • •
•
no long-term records of ship observations are available. The sea ice cover restricts shipping traffic to selected areas and part of the year (austral summer). The sea ice does not move exactly with the surface ocean currents; consequently ice buoys or satellite-derived ice motion do not represent surface ocean currents. The weak stratification in polar and subpolar oceans implies a strong barotropic component of the currents. This restricts the reliability of current estimates by use of geostropic currents with unknown reference velocities or the geopotential anomaly (dynamic topography) with a fixed reference level. In large areas of the Weddell Sea the time-mean currents are relatively weak. They are therefore masked by high frequency motion (tides and inertial motion), especially when the period of observations is short.
Most of the current patterns in the Weddell Sea are derived indirectly either by tracking water mass properties or from the geopotential anomaly (dynamic topography) measurements. Water mass properties (Figure 2) give good qualitative results because water masses of circumpolar origin enter the Weddell Gyre in the north and the major modification areas are in the southern parts of the Weddell Sea. The modified water leaves the Weddell Sea to
the north. However, the regional variations in the water mass characteristics do not allow quantitative estimates of current velocities and volume transport. Because of the strong barotropic component, the current pattern derived from water mass properties holds for most of the water column except for the bottom water plumes and the boundary layers. In certain areas information on currents is available from moored instruments. They are concentrated on transects between Joinville Island and Kapp Norvegia, along the Greenwich Meridian and off the Filchner-Ronne Ice Shelf (Figure 3). The data allow to determine the horizontal and vertical structure of the currents on the basis of records which are at least several months long. However, moored instruments can not be used in the upper ocean layer due to the effect of sea ice and icebergs which might damage the moorings. In the eastern Weddell Gyre current information is available from ALACE floats drifting at approximately 750 m depth (Figure 3). Information on the surface currents (i.e., within the Ekman layer) can be obtained indirectly, if wind and sea ice motion is known. For example, weather center (e.g., European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP)) surface winds are used to calculate sea ice drift. Differences in observed and calculated ice buoy drift are then attributed to the surface currents. Iceberg drift data can be included in this analysis.
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Figure 2 Distribution of the potential temperature (1C) (A) and salinity in PSU (B) on a vertical transect from the northern tip of the Antarctic Peninsula (left) to Kapp Norvegia (right) obtained with RV Polarstern in 1996.
Uncertainties in these estimates arise from the highly variable contribution of internal ice forces (ice pressure). Furthermore, buoy observations are rare and require extensive interpolation or extrapolation in both time and space. The resulting flow fields are rather smooth and do not contain much detail. Some improvement may be gained from satellite-derived sea ice drift. As a direct consequence of the sparse observational data, the most consistent estimates of largescale ocean currents in the Weddell Sea stem from numerical models, which have been validated
rigorously against available observations. They extend into regions without observational data, include the upper ocean layers which are not accessible by moored instruments and cover time periods when no measurements are made. This is of particular interest because of the wide range of variability detected in the measurements. Current state-of-the-art numerical tools to simulate the large-scale circulation and water mass structure in the ocean are coupled sea ice-ocean models, which are driven by atmospheric data sets from weather center analyses. They allow for ocean
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WEDDELL SEA CIRCULATION
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Figure 3 Ocean currents in the Weddell Sea obtained by direct measurements with recording periods between several months and two years. The currents in the upper ocean layer to a depth of 750 m (A) include data from moored instruments and subsurface floats. Those in the near bottom layer (B) include data up to 200 m from the bottom.
and ice dynamics and thermodynamics, as well as the feedback between both components of the climate system. Advanced models of the Weddell Sea also include the ice shelf cavities (Filchner–Ronne Ice Shelf, Larsen Ice Shelf and the ice shelves in the eastern Weddell Sea). The ocean component is based on the hydrostatic primitive equations. For an optimal representation of ocean dynamics in shallow shelf areas and over a sloping bottom a terrain-following vertical coordinate is useful. The sea ice component describes sea ice as a viscous-plastic medium. The model computes temperature, salinity, horizontal and vertical motion in the ocean as well as ice and snow thickness, and ice concentration. The horizontal resolution varies between 20 and 100 km horizontally and 10 and 400 m vertically. This excludes many details of coastline and topography but preserves the ability to capture the main features necessary to simulate the large-scale features. Multiyear integrations are carried out with these models and averaged in time to obtain a picture of the general circulation.
A validation of the coupled model system has to take into account oceanic transport estimates along selected sections (see Figure 1), satellite-based observations of the annual cycle of sea ice concentration, pointwise measurements of sea ice thickness and Lagrangian observations of sea ice drift. In all four categories, agreement within the limits of measurement uncertainty can be achieved. A consistent picture of the three-dimensional ocean circulation in the Weddell Sea is obtained from multiyear simulations of the circumpolar ocean, using ECMWF atmospheric data for the late 1980s and early 1990s. The model indicates that the winddriven and thermohaline components are of similar importance in forcing the barotropic flow.
The Structure of the Ocean Currents in the Weddell Sea The dominant feature of the currents in the Weddell Sea is the cyclonic gyre. It appears clearly in the
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WEDDELL SEA CIRCULATION
time-mean streamlines and barotropic currents (Figure 4A) of the numerical model. There is a pronounced double cell structure, caused by either the presence of Maud Rise, a seamount with its center at 651S, 21300 E or/and the inflow from the north of water of circumpolar origin at about 201W. The volume transport across sections along the Greenwich Meridian amounts to 50 Sv. The transport across the section from the northern tip of the
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Figure 4 Annual mean current field in the Weddell Sea from a numerical simulation of the circumpolar ocean; (A) barotropic; (B) surface velocity vectors, and (C) bottom.
Antarctic Peninsula to Kapp Norvegia is 30 Sv (Figure 1). The velocities in the boundary currents are relatively high, up to 50 cm s1 and in the interior almost stagnant conditions prevail (Figure 3). The surface circulation in the eastern Weddell Gyre is characterized by the Antarctic Divergence, which divides the onshore flow south of 631S from the predominantly equatorward flow to the north (Figure 4B). This pattern is disrupted in the western Weddell Sea, where the presence of the Antarctic Peninsula causes a generally northward flow. The observed sea ice drift patterns reflect both this winddriven surface velocity field, and the barotropic flow, through the sea surface inclination. The wind-driven flow in the surface Ekman layer leads to coastal downwelling, with a corresponding offshore (downslope) component in the bottom boundary layer (Figure 4C). The near-bottom flow is clearly concentrated along the continental slope and numerical results suggest that part of it continues westward past the tip of the Antarctic Peninsula. The best-known part of the ocean current system in the Weddell Sea is the Antarctic Coastal Current which follows the Antarctic coastline from the east to the west. It is partly driven by the persistent Antarctic east winds and partly by thermohaline forcing evidenced by the differences between shelf and open ocean water masses. The east winds force an onshore Ekman transport which is balanced by an upward sea level inclination towards the coast which leads to westward currents along the coast. Its seaward extent is defined in various ways; either, it includes all westward flow between the coast and the center of the cyclonic gyre, or it is limited to the near-shore part including the ‘shelf front’ which is formed by differences between the water mass characteristics of the shelf waters and the open ocean surface layer. The near-shore water is seasonally highly variable and can be less or more saline than the open ocean water, depending on the relative importance of the melt water input from the continent and the salt release due to sea ice formation. Enhanced (vertical) mixing on the shelf also contributes to the horizontal water mass differences. The density gradient-related shelf front gives rise to a frontal jet. The frontal jet forms a local maximum of the coastal current. The path of the coastal current roughly follows the depth contours, i.e., is mainly along-slope. It is mainly barotropic, but a baroclinic component is superimposed which causes a decrease of the flow with depth but in certain areas the flow is bottomintensified. The flow speed in the coastal current averaged over weekly or monthly periods ranges between 10
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WEDDELL SEA CIRCULATION
and 50 cm s1. The corresponding volume transport amounts to 10 to 15 Sv. In some areas, the current may separate into two (or more) quasiparallel branches. This is often triggered by the bottom topography, e.g., near Kapp Norvegia where a relatively flat plateau interrupts the continental slope at 1500–2500 m depth. Eventually, an undercurrent towards the east is found on the upper slope. The core of the offshore branch of the coastal current (200–1500 m) transports warm deep water westward which originates from Circumpolar Deep Water (Figure 2). This warm and saline water mass can be used to trace the gyre flow along the coast. The westward-decreasing temperature and salinity anomaly reveals the exchange with the ambient water masses. In addition to the along-slope flow, cross-slope circulation cells transport modified warm deep water up the continental slope and on to the shelf, where it either loses its heat to the atmosphere or melts sea or shelf ice. The heat supply by warm deep water is the major heat source for shelf ice melt. In the open ocean it controls the sea ice thickness, because haline convection due to sea ice formation can bring the heat from the warm deep water into the surface mixed layer and control sea ice growth. In the southern Weddell Sea where the shelf widens to several hundred kilometers the Antarctic Coastal Current splits into two branches; one follows the coastline onto the shelf and the other continues along the continental slope. Both branches join again at the Antarctic Peninsula. The shelf areas in the southern and western Weddell Sea with a depth up to 500 m are the origin of downslope plumes of dense water. These water masses usually descend gradually down the slope as they follow the general along-slope path of the water masses of the coastal current. Alternatively, they may be guided directly downslope at topographical features like ridges or canyons. They form either Weddell Sea Deep Water by mixing with adjacent water masses or interleaving in intermediate depths, or Weddell Sea Bottom Water which mixes afterwards with the layers on top of it to form again Weddell Sea Deep Water, which fills most of the Weddell Basin. The northward flow along the Antarctic Peninsula is relatively well studied. It ranges between 25 and 30 Sv whereas the transport of newly formed Weddell Sea Bottom Water amounts only to a few Sv. At the tip of the Antarctic Peninsula, the Weddell Sea shelf waters are injected between those from the Antarctic Circumpolar Current and the Weddell Sea proper. By this process two fronts are formed: the Weddell Front in the south and the Scotia Front in the north which enclose the ‘Weddell–Scotia Confluence’ zone. Water masses from the Weddell–Scotia
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Confluence are dense enough to sink and to contribute to the renewal of the global oceans deep water. The location of the flow band is strongly controlled by bottom topography. Mixing and local atmosphere ocean exchange can cause further modifications. The Weddell Front follows the North Weddell and the Southwest Indian Ridges to the east. The related northern current band follows those structures and is strongly affected by their irregularities which generate meridional perturbations of the zonal field. It is most likely that Circumpolar Deep Water enters the Weddell Gyre in such excursions and that Weddell Sea Deep Water leaves it. Horizontal structures in the Warm Deep Water core in the gyre suggest this exchange and affect the gyre structure. A separation into two adjacent subgyres, as indicated earlier, might be due to those intrusions. The trapping of the gyre flow along the midocean ridge ends at the eastern edge of the Southwest Indian Ridge. There, the northern part of the gyre flow seems to split into an eddy field, consisting of cold eddies with water from the Weddell Gyre and warm eddies with a core of Circumpolar Deep Water. The eddies drift in the remnant flow field to the southwest and merge into the southern band of the gyre supplying the Warm Deep Water flow in the gyre.
Variability of the Circulation Seasonal variations in the Weddell Sea circulation have been observed in the Antarctic Coastal Current, which reaches a maximum in the austral winter. A similar cycle is superimposed on the flow of bottom water in the north-western Weddell Sea. However, outside the boundary currents the seasonal cycle can only be derived from numerical model results and appears to be relatively small. The Weddell Gyre transport is larger in winter than in summer, due to stronger winds. Thermohaline effects on the largescale circulation are not felt on a seasonal scale but on longer timescales. This interannual variability is dominated by variations in sea ice cover and formation. Numerical studies indicate that the signal of the Antarctic Circumpolar Wave (with a typical period of four years) influences the whole Weddell Sea. A four-year periodicity can be detected, mainly in response to meridional wind stress anomalies; strong southerly winds in the western Weddell Sea lead to increased ice export causing more ice formation and deep water production during the following winter. With a time lag of about one year, this newly formed
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bottom water will begin to cross the South Scotia Ridge northward and spread into the global ocean. Circulation fluctuations on longer timescales certainly exist, but they have not been investigated conclusively.
The Role of the Weddell Gyre in the Global Ocean Circulation A significant part of the water mass transformation in the Southern Ocean occurs in the Weddell Sea. A census of the water colder than 01C south of the Polar Front revealed that 66% of it was from Weddell Sea Bottom Water, 25% from Ade´lie Land Bottom Water and 7% from Ross Sea Bottom Water. Whereas the quasi-zonal Antarctic Circumpolar Current system is a barrier for meridional exchange, the subpolar gyres in the Ross and Weddell Seas have sufficiently strong meridional flow components to allow for significant meridional heat and freshwater transports. The eastern branch of the cyclonic circulation of the Weddell Gyre advects water masses from the subantarctic water belt towards the Antarctic coast where intense atmosphere–ocean interaction will lead to a decrease in temperature and an increase in salinity. This occurs mainly in coastal polynyas, induced by a strong offshore wind component with cold air from the continent. The irregular structure of the coastline forming capes and embayments leads regionally to offshore winds even if the large-scale directions of the winds is parallel to the coast. In the coastal polynyas the oceanic heat loss to the atmosphere can exceed 500 W m2. The salt gain due to sea ice formation has to compensate the fresh water gain by glacial melt water from the continent and precipitation which had desalinated the previously upwelled Circumpolar Deep Water. The relative importance of melting icebergs as a regional enhancement of the freshwater gain is still unclear. If the salt release is strong enough, the density increases until the water sinks and forms bottom water directly by plumes sinking down the continental slope or by further cooling during the circulation under the ice shelves. Both forms of dense shelf water form plumes on the continental slope which either reach the bottom of the Weddell Basin or enter the open ocean at a depth level according to their own density by interleaving. Due to the nonlinearity of the equation of state of sea water, descending plumes can be formed or enhanced by the thermobaric effect. Eventually the regime of the deep water renewal by plumes along the continental slopes can switch to deep open ocean convection. This was most likely
happening during the 1970s when a large open ocean polynya was observed west of Maud Rise. The polynya and open ocean convection are in intensive interaction, because the heat loss due to open water in winter cools the water column sufficiently to form deep water whilst on the other hand, the normal supply of Warm Deep Water from deeper layers can maintain the polynya. The polynya formation could be caused by advection of warmer water from the north or by changing atmospheric forcing. Weddell Sea Deep Water leaves the Weddell Sea to the north and represents the major cold source of water for the globally spreading bottom water. The water mass formation in the Weddell Sea, therefore, represents a major part of the global thermohaline overturning circulation. The combined effects of windinduced downwelling and thermohaline driven sinking of dense water masses from the shelves of the inner Weddell Sea generate a large-scale overturning motion in the Southern Ocean. Circumpolar ice–ocean model simulations indicate maximum overturning transports of about 20 Sv, half of which originate in the Weddell Sea sector. At the same time, estimates from observations show that only a relatively small part (2–3 Sv) seems to be directly in contact with the surface, thus ventilating the deep ocean.
See also Antarctic Circumpolar Current. Bottom Water Formation. Deep Convection. Ekman Transport and Pumping. General Circulation Models. Ice– ocean interaction. Non-Rotating Gravity Currents. Open Ocean Convection. Polynyas. Rotating Gravity Currents. Sea Ice. Sea Ice: Overview. Sub Ice-Shelf Circulation and Processes. Water Types and Water Masses.
Further Reading Beckmann A, Hellmer HH, and Timmermann R (1999) A numerical model of the Weddell Seal: arge-scale circulation and water mass distribution. Journal of Geophysical Research 104: 23 375--23 391. Carmack EC (1986) Circulation and mixing in ice-covered waters. In: Untersteiner N (ed.) The Geophysics of Sea Ice, pp. 641--712. New York: Plenum. Carmack EC (1990) Large-scale physical oceanography of polar oceans. In: Smith WO Jr (ed.) Polar Oceanography, Part A: Physical Science, pp. 171--222. San Diego: Academic Press. Fahrbach E, Klepikov A and Schro¨der M (1998) Circulation and water masses in the Weddell Sea. Physics of Ice-Covered Seas, vol. 2, pp. 569–604. Helsinki: Helsinki University Press.
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Gordon AL, Martinson DG, and Taylor HW (1981) The wind-driven circulation in the Weddell–Enderby Basin. Deep-Sea Research 28: 151--163. Haidvogel DB and Beckmann A (1988) Numerical modeling of the coastal ocean. In: Brink KH and Robinson AR (eds.) The Sea, vol. 10, pp. 457–482. New York: John Wiley and Sons. Hofmann EE and Klinck JM (1998) Hydrography and circulation of the Antarctic continental shelf: 1501E to the Greenwich meridian. In: Robinson AR and Brink KH (eds) The Sea, vol. 11, 997–1042. New York: John Wiley and Sons. Jacobs SS (ed.) (1985) Oceanology of the Antarctic Continental Shelf, Antarctic Research Series, 43. Washington, DC: American Geophysical Union.
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Jacobs SS and Weiss RF (eds.) (1998) Ocean, Ice and Atmosphere: Interactions at the Antarctic Continental Margin, Antarctic Research Series, 75. Washington DC: American Geophysical Union. Muench RD and Gordon AL (1995) Circulation and transport of water along the western Weddell Sea margin. Journal of Geophysical Research 100: 18503--18515. Orsi AH, Nowling Jr WD, and Whitworth III T (1993) On the circulation and stratification of the Weddell Gyre. Deep-Sea Research 40: 169--203. Whitworth III T, Nowling Jr WD, Orsi AH, Locarnini RA, and Smith SG (1994) Weddell Sea Shelf Water in the Bransfield Strait and Weddell–Scotia Confluence. Deep-Sea Research 41: 629--641.
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WET CHEMICAL ANALYZERS A. R. J. David, Bere Alston, Devon, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3209–3213, & 2001, Elsevier Ltd.
Introduction Since the early 1960s there has been a requirement for seawater laboratories to carry out increasing numbers of routine analyses, many of which were performed by traditional manual methods. The performance of standard manual methods was generally variable due to human error and the efficiency was poor. Method automation has since enabled increased numbers of samples to be analyzed with improved efficiency and reduced the risk of human error. Air-segmented continuous flow analyzers (CFA) and flow injection analyzers (FIA) have handled the bulk of this automation. Instrument manufacturers have continued to improve both hardware and software over the years, which has resulted in better reliability and analytical performance.
Air-segmented Continuous Flow Analyzers These instruments are in widespread use for the determination of nutrient concentrations in natural waters. The technique is based on the fundamental principles developed in 1957 and converts a series of
Flow rate: ml min N1NED Air Re-sample Sulfanilamide
Air Sample in Ammonium chloride Return
discrete samples into a continuous flowing carrier stream by a pumping system. Reagents are added by continuous pumping and merging of the sample carrier and reagent streams. The sample carrier stream is segmented with air before reagent addition, which typically allows between 20 and 80 samples to be processed in an hour. The insertion of standards in the sample carrier stream provides regular datum points during a particular analysis. There is usually no problem with distinguishing between the samples at the detection stage as the regular timing between stages is controlled. However, unless precautions are taken to prevent carryover, interaction can occur in a continuous system causing loss in discrimination between successive samples at the detection stage. Figure 1 shows a typical air-segmented CFA manifold arrangement for total oxidized nitrogen (TON) determinations. It can be seen that the manifold is relatively complex, with eight separate streams pumped at fast flow rates. The sample stream is air-segmented prior to merging with the ammonium chloride (10 g l1) carrier stream and the bubbles are removed by a debubbler before entering the cadmium wire reduction coil. Air-segmentation is then re-introduced into the sample stream before merging with the separate sulfanilamide and N1NED streams. A second debubbler finally removes the bubbles before entering the flow cell. Sophisticated laboratory CFA systems are used in shipborne laboratories for the routine determination of nitrate, nitrite, silicate, phosphate, and ammonia
1
0.10
Debubbler Flow cell
0.32 0.80 0.10 Debubbler Cu/Cd reduction column
0.10 0.32 0.20 0.60
Waste
Figure 1 Schematic diagram of a typical air-segmented continuous flow analyzer manifold (for total oxidized nitrogen).
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in sea water simultaneously. Although the technology is now very mature and the instruments perform extremely well in true laboratory conditions, the same cannot be said for shipborne applications. The main drawback with air-segmented systems is the need for a reproducible bubble pattern, which can be difficult to achieve when at sea in rough conditions. The air bubbles are compressible and therefore will create pulsations in the system and for most detector designs the bubbles have to be removed to avoid flow problems within the cell. Multichannel systems are complex and consequently require specialist knowledge of the system in order to achieve optimum performance in adverse conditions, which is not always possible when operating a watch system on a research cruise. However, these instruments have been in use for many years with standard validated methods and generally they are the standard by which other techniques are judged. In addition to the standard methods applied to CFA, various techniques have been developed over the years in order to eliminate some of the problems associated with air-segmented continuous flow techniques, e.g. the use of EDTA (ethylene diamine tetraacetic acid) to segment the carrier stream instead of air. The technique is also very flexible, allowing customized methods to be developed for a variety of additional chemical species and more sensitive methods for the normal nutrient species. For example, methods for the determination of nanomolar concentrations of nitrate and nitrite in sea water using an air-segmented CFA system have been developed. Air-segmented CFA has been widely used at sea for the analysis of all major nutrient species and until the mid-1980s was the only technique that was available at a reasonable cost for automated analysis.
Flow Injection Analysis Flow injection analysis (FIA) techniques were developed to overcome some of the practical problems associated with air-segmented CFA that were perceived by some workers. Flow injection analysis differs from air-segmented CFA in that the sample is injected directly into a moving liquid carrier stream without the addition of air. The main distinction between air-segmented CFA and FIA is that the continuous mixing of sample and reagents in a turbulent stream segmented by bubbles is replaced by the periodic mixing in an unsegmented laminar stream. The periodic mixing in a FIA system is achieved by injecting the sample (or reagent in the case of reverse flow injection) into a liquid carrier
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stream flowing to the detector, where the analyte forms a colored species in the reaction zone, which contains both sample and reagent. The reaction does not have to go to completion, and as the flow is incompressible, the extent of the reaction will be similar in all samples. This gives significant advantages over air-segmented CFA, including faster analysis rates and less complicated equipment, which has resulted in FIA being readily adapted to the analysis of seawater nutrients. In the late 1970s, methods were described for the simultaneous determination of nitrite and nitrate by FIA. This allowed up to 30 samples per hour to be analyzed with a relative precision of 1% in the range 0–0.05 mM for Nitrite-N and 0–0.1 mM for NitrateN. Similar work was carried out later that year, where up to 90 samples were analyzed with a relative precision of 0.5 and 1.5% for nitrite and nitrate respectively; in the range of 0.1–0.5 mg l1 for Nitrite-N and 1–5 mg l1 for Nitrate-N. Further developments of this method, which utilized copperized cadmium wire in a pre-valve in-valve reduction technique, allowed synchronous determinations of nitrite and (nitrite þ nitrate) using one manifold and detector. In the early 1980s, methods were described which were modifications to previous methods that utilized reverse flow injection analysis, whereby the sample was the carrier stream and reagents were injected into it. This method gave a limit of detection (LOD) of 0.1 mM and allowed up to 70 samples per hour to be analyzed with a relative precision of 1%. FIA is finding increased use in the water industry, where laboratories that had previously used air-segmented CFA have introduced FIA to complement their working practices. FIA is the preferred technique for small batch sizes and lowlevel concentrations, where speed of analysis is essential to eliminate the risk of airborne contamination. FIA techniques are also readily adaptable to online monitoring of a watercourse. Over the past 20 years commercially available FIA instruments have established flow injection analysis as a reliable technique with the level of sensitivity for monitoring micronutrient species in the environment. Like CFA, it has also been accepted as a standard method for the examination of waters and associated materials. FIA is also finding increasing applications in research, routine analysis, teaching of analytical chemistry, monitoring of chemical processes, sensor testing and development, and enhancing the performance of various instruments. It is also used for the measurement of diffusion coefficients, reaction rates, stability constants, composition of complexes and extraction constants and solubility products.
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The versatility of FIA has allowed the technique to be adapted to different detection systems such as electrochemistry, molecular spectroscopy, and atomic spectroscopy, using numerous manifold configurations. FIA systems can also be designed to dilute or to preconcentrate the analyte; to perform separations based on solvent extraction, ion exchange, gas diffusion or dialysis; and to prepare unstable reagents in situ. Figure 2 shows a typical FIA manifold arrangement for the determination of total oxidized nitrogen (TON). The basic principle of FIA is the injection of a liquid sample into a moving, unsegmented carrier stream of a suitable liquid. The injected sample forms a zone, which is transported towards a detector that continuously records the absorbance, electrode potential or other parameter as the sample passes through the detector. Optimization and design of the flow channels to achieve maximum sampling frequency, best reagent and sample economies, and proper exploitation of the chemistries is possible through understanding of the physical and chemical processes taking place during the movement of the fluids through the FIA manifold. The simplest FIA analyzer, shown schematically in Figure 3, consists of a pump, which is used to propel the carrier stream through a narrow tube; an injection port, by means of which a well-defined volume of a sample solution is injected into the carrier stream in a reproducible manner; and a microreactor in which the sample zone reacts with the components of the sample stream, forming a species which is sensed by a flow-through detector and recorded.
Flow rate: ml min
The height, width, and areas of a typical peak output from a simple FIA system are all related to the concentration of the analyte. The time span between the sample injection and the peak height is the residence time during which the chemical reaction takes place. With rapid response times, typically in the range of 5–20 s, a sampling frequency of two samples per minute can be achieved. The injected sample volumes may be between 1 and 300 ml, which in turn requires typically between 0.5 and 5 ml of reagent per sampling cycle. This makes FIA a simple, automated micro-chemical technique, which is capable of a high sampling rate and a low sample and reagent consumption. FIA is based on the combination of three principles: sample injection, controlled dispersion of the injected sample zone, and reproducible timing of its movement from the injection point to the detector. The chemical reactions take place whilst the sample material is dispersing within the reagent. The physical dispersion processes form the concentration gradient of the sample zone. The sample zone broadens as it moves downstream and changes from the original asymmetrical shape to a more symmetrical and eventually Gaussian form. For standard conditions, the procedure is totally reproducible in
Pump
Injection valve
Reaction zone
Waste Figure 3 Schematic diagram of a simple FIA system.
1
Sample
Ammonium chloride
Injection Reduction column valve 0.32
Flow cell Reaction coil
Sample loop Sulfanilamide N1NED
Detector
0.16 0.16
Figure 2 Schematic diagram showing a typical FI manifold (for total oxidized nitrogen).
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that one injected sample behaves in the same way as all other subsequently injected samples.
In Situ Monitoring As greater pressure is placed upon the environment through anthropogenic activities and climatic changes, effective monitoring and control of nutrient enrichment is vital to protect what is becoming a very delicately balanced marine environment. For example, quantitative knowledge of nutrients and primary production is essential for investigating the ecology and biogeochemistry of aquatic ecosystems. Until recently, the only way to monitor nutrient levels has been to collect discrete samples or use research vessels with onboard laboratory facilities to steam through a particular area of study. Collected samples are either analyzed at the collection site if convenient or transported to a central laboratory to be analyzed later. Monitoring schemes such as these may not detect short-term changes such as algal bloom conditions, storm events, or point discharges between sampling events. In addition, weather conditions and the high cost and logistics of using research vessels for routine studies may not allow complete data sets to be compiled. Therefore, the current problems associated with compiling longterm or continuous data can be summarized as follows:
• • • • •
High cost and logistics of using research vessels for long-term routine surveys. Samples collected for analysis at a later time rely on good sample preservation techniques. This can lead to erroneous results with no means of replacing samples. Existing methods require some degree of human input to perform tasks, which can introduce experimental error. Research cruise weather conditions may not permit complete data sets to be compiled. Post-cruise processing of data can take several months.
There is also considerable evidence to suggest that many of the sample preservation techniques introduce some level of variance into nutrient determinations. For example, freezing of coastal and estuarine water at 101C for nitrate determination was found to give variance on samples tested, whereas freezing at 201C was found to be acceptable. The US EPA methodology for analysis for anions in water states that unpreserved samples must be analyzed within 48 hours otherwise they can be preserved with sulfuric acid at pHo2 for 28 days. However, this has been
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shown to have an effect on environmental samples where nitrite is converted to nitrate by further microbial activity, whereas pH 12 is thought to eliminate the conversion-causing bacteria. Consequently, significant errors may be introduced into preserved samples and in both cases the cost and logistics of continuously monitoring a particular environment would generally be prohibitive. In Situ Instruments
Advances in analytical chemistry have made it feasible to perform a wide range of chemical determinations in situ. The development of field automated methods, e.g. flow injection, has been particularly important in this respect. The application of in situ automated FIA techniques can produce low-cost, rapid analysis with high sampling frequency analytical systems that are simple and easily maintained. Early examples of FIA based field instruments successfully completed field trials on the River Frome in Dorset. In situ FIA techniques have also been developed for environmental monitoring of phosphate, ammonia, and aluminum, all using solid-state LED/photodiode detectors. These early systems were based on mainspowered microcomputers which are unsuitable for use in portable battery-powered systems. Since then, advances in microchip technology have resulted in the availability of specialized microcontroller devices for control and automation of a variety of everyday uses. This technology has been exploited in the development of in situ FIA monitoring systems for the analysis of nitrate and phosphate in natural waters. All functions required for field-based operation, i.e. control of peristaltic pumps, injection and switching valves, data acquisition, processing, and logging were controlled automatically. The early development systems were powered by 12 V sealed lead-acid batteries, which were capable of 2–3 week’s operation depending on the mode of operation. However, there are additional constraints for the in situ monitoring of sea water, i.e. systems must be made more rugged and capable of being submersed to facilitate measurements at a particular point in the water column. In the late 1980s, the use of a submersible FIA system was reported to monitor silicate, sulfide, and nitrate concentrations in sea water that gave good correlation with laboratory techniques. The effects of extremes of temperature, pressure, and salinity on flow analysis and chemistries used in these systems have all been studied. During 1996 a submersible nitrate sensor based on FIA techniques was successfully tested in estuarine and coastal waters, over complete tidal cycles, and to depths of 40 m.
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Commercially available submersible FIA instruments permit laboratory FIA methods to be used in situ. Other commercially available wet chemistry field instruments, which utilize the same basic proven chemistries as the CFA and FIA instruments, are available. For example, some instruments utilize rugged microprocessor-controlled syringe systems and a unique design of manifold for the collection of the sample, reagent addition, and colorimetric determination of the resultant colored species. Field instruments enable a wide range of chemical determinations to be performed in situ and as the technology matures greater use of these will be made in the years to come.
See also Nitrogen Isotopes in the Ocean.
Further Reading Crompton TR (1989) Analysis of Seawater. Sevenoaks: Butterworths.
David ARJ, McCormack T, Morris AW, and Worsfold PJ (1998) Anal. Chim. Acta 361: 63. Grasshoff K, Ehrhardt M, and Kremling K (1976) Methods of Seawater Analysis. New York: Verlag Chemie. HMSO (1981) Oxidised Nitrogen in Waters: Methods of Examination of Waters and Associated Materials. London: HMSO. HMSO (1988) Discrete and Air Segmented Automated Methods of Analysis including Robots, An Essay Review, 2nd edn: Methods for the Examination of Waters and Associated Materials. London: HMSO. HMSO (1990) Flow Injection Analysis, An Essay Review and Analytical Methods: Methods for the Examination of Waters and Associated Materials. London: HMSO. Karlberg B and Pacey GE (1989) Flow Injection Analysis – A Practical Guide. Amsterdam: Elsevier. Ruzicka J and Hansen EH (1988) Flow Injection Analysis, 2nd edn. Chichester: Wiley Interscience. Strickland JDH and Parsons TRA (1972) Practical Handbook of Seawater Analysis, 2nd edn. US EPA No. 353.2 (1979) Methods for the Chemical Analysis of Water and Wastes. Washington: Valcarcel MD and Luque de Castro MD (1987) Flow Injection Analysis – Principles and Applications. Chichester: Ellis Horwood.
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WHITECAPS AND FOAM E. C. Monahan, University of Connecticut at Avery Point, Groton, CT, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3213–3219, & 2001, Elsevier Ltd.
Introduction Oceanic whitecaps and sea foam are, respectively, the transient and semipermanent bubble aggregates that are found on the surface of the ocean when certain meteorological conditions prevail. These features are of sufficient size to be detectable by eye, and an individual whitecap or foam patch can readily be recorded using standard low-resolution photographic or video systems. When they are present in sufficient number on the sea surface they alter the general visual albedo, and microwave emissivity, of that surface, thus rendering their collective presence detectable by various satellite-borne instruments. Almost all the bubbles that make up these structures were initially produced at the sea surface by breaking waves, and to understand the presence and distribution of whitecaps and foam patches it is necessary to first consider the genesis, and fate within the oceanic surface layer, of these bubbles. It will become apparent from the discussions contained in the following sections that the bubbles whose presence in great numbers is signaled by the appearance of whitecaps play a major role in the air–sea exchange of gases that are important in establishing our climate, and in the production of the sea-salt aerosol that contributes to the pool of cloud condensation nuclei in the atmosphere over the ocean. These same bubbles facilitate the sea-to-air transfer of heat and moisture, and scavenge from the bulk sea water and carry to the ocean surface various surfactant organic, and adhering inorganic, materials.
Spilling Wave Crests: Stage A Whitecaps When a wave breaks in the more typical spilling mode, and even more so when a wave collapses in a plunging fashion, great numbers of bubbles are formed and constrained initially to a relatively small volume of water, typically extending beneath the surface a distance no greater than the height of the source wave and having lateral dimensions of only a
few meters at most. Although these intense bubble clouds, often called alpha plumes, are individually often of convoluted shape, the concentration of bubbles in these alpha-plumes tends to decrease exponentially with depth, with an e-folding, or scale, depth that increases modestly from less than a meter to several meters, as the sea state increases in response to increasing wind speeds. The concentration of bubbles within an alpha-plume that has just been formed can be so great that the aggregate fraction of the water volume occupied by these bubbles, the void fraction in the terminology of the underwater acoustician, reaches 20% or even 30%. The size spectrum of the bubbles within such a plume is very broad, the bubbles present having radii ranging from several micrometers up to almost 10 mm (see Figure 1). Although there is no clear consensus on where the peak in the alpha-plume bubble number density spectrum lies, many authors would contend that it falls at a bubble radius of 50 mm or less. It has been suggested that the amplitude of this spectrum then falls off with increasing bubble radius in such a fashion that for over perhaps a decade of radius the total volume of the bubbles falling within a unit increment of size remains almost constant. It is thought that at even larger bubble radii this spectrum ‘rolls off’ even more rapidly, with less and less air being contained in those bubbles that fall in the larger and larger size ‘bins’, but there are as yet insufficient unambiguous observations to verify this contention. The manifestation on the sea surface of an alphaplume, the stage A whitecap, is the most readily detected category of whitecap or foam patch. Although bubbles on the surface in a stage A whitecap typically burst within a second of having arrived at the air– water interface, there is often a certain momentary ‘packing’ of bubbles, both vertically and laterally, on this surface, which results in this category of whitecap being truly white, with an albedo of about 0.5 which does not vary significantly over the entire visible portion of the electromagnetic spectrum. Since the visible albedo of the sea surface away from whitecaps is often 0.03–0.08, the average albedo of this surface will be noticeably increased when even a small fraction of the ocean surface is covered by spilling wave crests. Many of the satellite-borne passive microwave radiometers detect the electromagnetic emissions from the sea surface at wavelengths on the order of 10 mm. At such wavelengths a stage A whitecap is an almost perfect emitter, what in optics would be deemed a ‘black body’, while the
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rest of the sea surface at these wavelengths has a microwave emissivity on only 30% or 40%. Thus it only requires a small fraction of the ocean surface to be covered by stage A whitecaps for there to be a measurable increase in the apparent microwave brightness temperature of this surface. An observer located within an alpha-plume would observe, once the downward movement associated with the spilling event had been dissipated, a high level of small scale turbulence, and, superimposed on top of the rapid random motions caused by this turbulence, a clear upward movement of the larger bubbles. The reduction of gravitational potential energy associated with the upward motion of these big bubbles frees energy that then contributes to the mixing and turbulence within the plume, and this enhanced mixing, which extends to the very surface of the stage A whitecap, greatly increases the effective air–sea gas transfer coefficient, or ‘piston velocity’, associated with this whitecap, as compared to the gas transfer coefficient associated with the wind ruffled but whitecap-less adjacent portions of the ocean surface. These upward moving bubbles drag water along with them, and the resulting upward, buoyant, flow often induces two-dimensional, horizontal divergence at the surface; factors which also enhance the air–sea exchange of gases. Further, for gases that diffuse slowly through water, the fact that each bubble is a gas vacuole traveling from the body of the water to the air–sea interface can be an important consideration. These large bubbles, with their large cross-sectional areas and rapid rise velocities, are also important in the scavenging and transport to the sea surface of the various surfaceactive materials that are often present in high concentrations in the oceanic mixed layer.
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Bubble radius (µm)
Figure 1 The number of bubbles per cubic meter of sea water, per micrometer bubble radius increment, as a function of bubble radius, as to be expected in (A) the alpha plume beneath a stage A whitecap, (B) the beta plume beneath a stage B whitecap, (C and D) in various portions of a gamma plume, and (E) the background, near-surface bubble layer. See Monahan and Van Pattern (1989) for further details.
Decaying Foam Patches: Stage B Whitecaps Within seconds of a wave ceasing to break, the associated stage A whitecap has been transformed in a decaying foam patch, a stage B whitecap. As a consequence of the intense turbulence present in the alpha plume that had been present beneath the stage A whitecap, the initial lateral extent of the stage B whitecap (and of the top of the beta-plume which is located beneath it) is typically considerably greater than that of a stage A whitecap, some would contend upwards of ten times greater. The greatest discrepancies in size between parent stage A whitecaps and the initial daughter stage B whitecaps occur in those cases where the wave crest spills persistently, or episodically, as it moves along over the sea surface
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WHITECAPS AND FOAM
0.1
B4 B2
A2 B3
0.01
A3 B1
A1 WA and WB
leaving in its wake a long stage B whitecap, or a series of decaying foam patches with short distances between them. As was the case with the stage A whitecap, most of the bubbles that come to the surface in a stage B whitecap burst within a second of their arrival at the interface, and thus a stage B whitecap owes its existence, as did its precursor stage A whitecap, to the continuing arrival at the surface of new bubbles from the dependent bubble plume or cloud. The concentration of bubbles within the associated beta-plume is much smaller than it was in the alpha-plume that preceded it, for three reasons: (1) the plume has been diffused over a greater volume of sea water; (2) many of the large bubbles that were present in the precursor alpha plume have by now reached the sea surface and burst; and (3) most of the very smallest bubbles, those with radii of only a few micrometers, have gone into solution (see Figure 1). (The very smallest bubbles can dissolve even when the oceanic surface layer is saturated with respect to nitrogen and oxygen, because at a depth of even a meter they are subjected to significant additional hydrostatic pressure, and because with their small radii they experience a marked increase in internal pressure due to the influence of surface tension.) The stage B whitecap decays by being torn into tattered foam patches by the turbulence of the surface layer, and by having these ever and ever smaller patches fading as the supply of bubbles from the associated portions of the beta-plume becomes exhausted. The cumulative effect of these factors is that the visually resolvable macroscopic area of a stage B whitecap decreases exponentially with time, with a characteristic e-folding time of 3–4 s. A stage B whitecap appears to the eye as a group of irregularly shaped pale blue, or green, areas clustered on the ocean surface. The visible albedo of a stage B whitecap is initially intermediate between that of a stage A whitecap and that of the ruffled sea surface, but within a few seconds its albedo approaches the low value associated with the wave-roughened sea surface. As a consequence of the relatively larger initial area of stage B whitecaps as compared to stage A whitecaps, and on account of the fact that the characteristic lifetime of a stage B whitecap is considerably greater than that of a stage A one, at any instant the fraction of the ocean surface covered by stage B whitecaps is typically at least an order of magnitude greater than the fraction covered by stage A whitecaps (see Figure 2). The beta plume beneath each stage B whitecap is relatively rich in bubbles of intermediate size, with some investigators suggesting that the bubble number density spectrum for this plume has a peak at a bubble radius of about 50 mm (see Figure 1). When
333
0.001 A3
A2
0.0001
0.00001 1
2
5
_
10
20
50
U (m s 1) Figure 2 The fraction of the ocean surface covered by stage A (curves A1–A3) and stage B (curves B1–B4) whitecaps as a function of 10 m-elevation wind speed. See Monahan and Van Pattern (1989) for further details.
bubbles of this size burst at the surface in a whitecap they inject into the atmosphere droplets of several micrometers radius, called jet droplets, which contribute to the sea-to-air transfer of moisture and latent, and often sensible, heat. The rupture of the upper, exposed, hemisphere of these bubbles when they burst on the sea surface also produces smaller
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WHITECAPS AND FOAM
droplets, called film droplets, which constitute a significant fraction of the cloud condensation nuclei in the maritime troposphere. The largest bubbles produced by a breaking wave, most of which reach the surface in the stage A whitecap, are even more effective at generating these film droplets when they burst. Because bubbles are relatively scarce within stage B whitecaps, these sea surface manifestations of beta plumes have visual albedos and microwave emissivities not greatly different from those of the adjacent, wind ruffled, surface, and are thus much more difficult to detect by remote sensing than are stage A whitecaps.
Wind-dependence of Oceanic Whitecap Coverage The frequency of wave breaking, and the average intensity of the individual breaking wave, both increase with increasing wind speed. The combined effect of these two factors is that the fraction of the sea surface covered at any moment by spilling wave crests, i.e. by stage A whitecaps, increases rapidly with strengthening wind speed. This can be seen from Figure 2, where the curves labeled A1, A2, etc. are summary descriptions of the dependence of stage A whitecap coverage on 10 m-elevation wind speed. Curve A1, describing the most comprehensive set of stage A whitecap observations (actually a combination of four such sets), is described by eqn [1]. WA ¼ 3:16 107 U3:2
½1
where WA is the fraction of the sea surface covered at any instant by spilling wave crests and U is the 10 melevation wind speed expressed in meters per second. Understandably, the fraction of the sea surface covered instantaneously by decaying foam patches, i.e. by stage B whitecaps, shows a similar strong dependence on wind speed. This can be seen from the steep slopes of the curves B1, B2, etc., on the log–log plot in Figure 2. Eqn [2] defines curve B1, which is a summary description of extensive observations, from both the Atlantic and Pacific Oceans, of stage B whitecap coverage made by several investigators. WB ¼ 3:84 106 U3:41
½2
Here WB represents the instantaneous fraction of the sea surface covered by decaying foam patches, and U is again the 10 m-elevation wind speed. The fact that for both categories of whitecap the fraction of the ocean surface occupied by these features varies with the wind speed raised to something slightly more
than the third power, is consistent with the contention that whitecap coverage varies with the friction velocity (see Heat and Momentum Fluxes at the Sea Surface and Wave Generation by Wind) raised to the third power. It should be stressed that although whitecap coverage, both stage A and stage B, is most sensitive to wind speed, it also varies with the thermal stability of the lower marine atmospheric boundary layer, and with wind duration and fetch. Any factor that influences sea state will also affect whitecap coverage. For near-neutral atmospheric stability, oceanic whitecap coverage begins to be noticed when the 10 m-elevation wind speed reaches 3 or 4 m s1. (There is not a distinct threshold for the onset of whitecapping at a wind speed of 7 m s1 as was contended in some of the early literature on this subject.) Since whitecap coverage, particularly stage A coverage, is readily detectable from space, and given that whitecap coverage is very sensitive to wind speed, it is apparent that satellite observations of whitecap coverage can be routinely used to infer over-water wind speeds.
Stabilized Sea Foam Many of the first bubbles to rise to the sea surface after a breaking wave has entrained air, not only scavenge organic material from the upper meter or so of the sea but also, as they reach the air–sea interface, accrue some of the organic material that is often found on that surface (not necessarily in the form of coherent slicks). As a consequence of accreting on their surface considerable dissolved, and other, organic material, such ‘early rising’ bubbles may become stabilized, and hence they may not break immediately, but rather persist on the ocean surface for protracted periods. If such a bubble has managed to coat its entire upper hemisphere with such surfactant material, the markedly reduced surface tension of its film ‘cap’ that results from this circumstance may enable this bubble to persist indefinitely at the air–water interface. Such bubbles are certainly present at the sea surface long enough to be winnowed into windrows, those distinctive, essentially downwind, foam and seaweed streaks that appears on the sea surface when a strong wind has been blowing consistently. Often organized convective motions are present in the upper layer of the ocean. Such Langmuir cells have associated with them lines of horizontal, two-dimensional, surface convergence and divergence, oriented for the most part downwind. When such Langmuir cells are present, stabilized bubbles will be drawn into the
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WHITECAPS AND FOAM
convergence zones, and since they are buoyant, they will remain to form fairly uniformly spaced foam lines on the sea surface marking the locations of such zones (Figure 3). It should be noted that the ‘late arriving’ bubbles, representing the vast majority of the bubbles rising within any alpha-plume, do not persist on the air–sea interface for more than a second or so, even when the surface waters are quite organically rich. The ability of bubbles to effectively scavenge surfactant organic matter from the bulk sea water and transport this material to the sea surface provides what has been described as an ‘organic memory’ to the upper mixed layer of the ocean. The more
335
bubbles that have been injected into the upper layer of the ocean by breaking waves in the recent past, the more organic material has been brought to the sea surface and remains there. Although wave action is ‘a two way street’, in that the same waves which upon breaking produce the bubbles that carry organic material to the air–water interface also stir and mix the surface layer, none-the-less the net effect of high sea states is to alter the partition of organic matter between the bulk fluid and the interface in favor of the interface. This can be inferred from the observation that as a high wind event persists, more and more foam lines, containing more and more stabilized bubbles, appear on the ocean surface. In
_1
d
in
W
10
m
s
Windrows
SW SF A
10
m
B LC
10
m
10 m
90° Rotation
Figure 3 A view looking obliquely down at the sea surface showing stage A and stage B whitecaps, foam and spume lines, and simultaneously a view looking obliquely up toward the same sea surface showing the alpha- and beta-plumes associated with these whitecaps, the gamma-plumes, and the near-surface bubble layer. The influence on these features of a classical Langmuir circulation, which is indicated by arrows, is depicted. A, Stage A whitecap; B, Stage B whitecap; SF, stabilized foam; SW, seaweed; LC, Langmuir circulation; a, plume of stage A whitecap; b, plume of stage B whitecap; g, old (microbubble) plume; Z, background bubble layer; y bubble curtain. From Monahan and Lu, 1990.
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stormy conditions, such foam, or spume, can be blown off the crests of waves, along with quite large drops of water, called ‘spume drops’, adding further to the indeterminacy that often prevails in such circumstances regarding the actual location of the air– water interface. Not only do the above-mentioned Langmuir cells advent buoyant stabilized bubbles into the surface convergence zones, these same cells are believed to move the residual, long-lasting, gamma bubble plumes (those left after the dissipation of the beta plumes) into these same zones. (Alpha bubble plumes have readily detectable stage A whitecaps as their sea surface signatures, and the location of the betaplumes into which these alpha-plumes decay can be determined from the position on the sea surface of their associated stage B whitecaps, but the large, diffuse, bubble-poor gamma-plumes into which the beta-plumes decay, have no apparent surface manifestation.) The influence of Langmuir cells on stabilized sea surface foam, on gamma-plumes, and on the near surface layer that contains an ever sparser concentration of small bubbles, is depicted in Figure 3.
Global Implications As can be seen from the curves in Figure 2, even at quite high wind speeds such as 15 m s1 (33.5 miles h1), only a small fraction of the sea surface is covered by stage B whitecaps (0.04 or 4%), and an even smaller fraction of that surface is covered by stage A whitecaps (0.002 or 0.2%). Yet the total area of all the world’s oceans is very great (3.61 1014 m2), and as a consequence the total area of the global ocean covered by whitecaps at any instant is considerable. If a wind speed of 7 m s1 is taken as a representative value, then at any instant some 7.0 1010 m2, i.e. some 70 000 km2, of stage A whitecap area is present on the surface of the global ocean. Following from this, and including such additional information as the terminal rise velocity of bubbles, it can be deduced that some 7.2 1011 m2, i.e. some 720 000 km2 of individual bubble surface area are destroyed each second in all the stage A whitecaps present on the surface of all the oceans, and an equal area of bubble surface is being generated in the same interval. The vast amount of bubble surface area destroyed each second on the surface of all the world’s oceans, and the great volume of water (some 2.5 1011 m3) swept by all the bubbles that burst on
the sea surface each second, have profound implications for the global rate of air–sea exchange of moisture, heat and gases. An additional preliminary calculation following along these lines, suggests that all the bubbles breaking on the sea surface each year collect some 2 Gt of carbon during their rise to the ocean surface.
See also Heat and Momentum Fluxes at the Sea Surface. Wave Generation by Wind.
Further Reading Andreas EL, Edson JB, Monahan EC, Rouault MP, and Smith SD (1995) The spray contribution to net evaporation from the sea review of recent progress. Boundary-Layer Meteorology 72: 3--52. Blanchard DC (1963) The electrification of the atmosphere by particles from bubbles in the sea. Progress in Oceanography 1: 73--202. Bortkovskii RS (1987) Air–Sea Exchange of Heat and Moisture During Storms, revised English edition. Dordrecht: D. Reidel [Kluwer]. Liss PS and Duce RA (eds.) (1997) The Sea Surface and Global Change. Cambridge: Cambridge University Press. Monahan EC and Lu M (1990) Acoustically relevant bubble assemblages and their dependence on meteorological parameters. IEEE Journal of Oceanic Engineering 15: 340--349. Monahan EC and MacNiocaill G (eds.) (1986) Oceanic Whitecaps, and Their Role in Air–Sea Exchange Processes. Dordrecht: D. Reidel [Kluwer]. Monahan EC and O’Muircheartiaigh IG (1980) Optimal power-law description of oceanic whitecap coverage dependence on wind speed. Journal of Physical Oceanography 10: 2094--2099. Monahan EC and O’Muircheartiaigh IG (1986) Whitecaps and the passive remote sensing of the ocean surface. International Journal of Remote Sensing 7: 627--642. Monahan EC and Van Patten MA (eds.) (1989) Climate and Health Implications of Bubble-Mediated Sea–Air Exchange. Groton: Connecticut Sea Grant College Program. Thorpe SA (1982) On the clouds of bubbles formed by breaking wind waves in deep water, and their role in air–sea gas transfer. philosophical Transactions of the Royal Society [London] A304: 155-210.
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WIND- AND BUOYANCY-FORCED UPPER OCEAN M. F. Cronin, NOAA Pacific Marine Environmental Laboratory, Seattle, WA, USA J. Sprintall, University of California San Diego, La Jolla, CA, USA Published by Elsevier Ltd.
Introduction Forcing from winds, heating and cooling, and rainfall and evaporation has a profound influence on the distribution of mass and momentum in the ocean. Although the effects from this wind and buoyancy forcing are ultimately felt throughout the entire ocean, the most immediate impact is on the surface mixed layer, the site of the active air–sea exchanges. The mixed layer is warmed by sunshine and cooled by radiation emitted from the surface and by latent heat loss due to evaporation (Figure 1). The mixed layer also tends to be cooled by sensible heat loss since the surface air temperature is generally cooler than the ocean surface. Evaporation and precipitation change the mixed layer salinity. These salinity and temperature changes define the ocean’s surface buoyancy. As the surface loses buoyancy, the surface water can become denser than water below it, causing convective overturning and mixing to occur. Wind forcing can also cause near-surface overturning and mixing, as well as localized overturning at the base of the mixed layer through shear-flow instability. This wind- and buoyancy-generated turbulence causes the surface water to be well mixed and vertically uniform in temperature, salinity, and density. Furthermore, the turbulence can entrain deeper water into the surface mixed layer, causing the surface temperature and salinity to change and the layer of well-mixed, vertically uniform water to thicken. Wind forcing also sets up oceanic currents and can cause changes in the mixed layer temperature and salinity through horizontal and vertical advection. Although the ocean is forced by the atmosphere, the atmosphere can also respond to ocean surface conditions, particularly sea surface temperature (SST). Direct thermal circulation, in which moist air rises over warm SSTs and descends over cool SSTs, is prevalent in the Tropics. The resulting atmospheric circulation cells influence the patterns of cloud, rain, and winds that combine to form the wind and buoyancy forcing for the ocean. Thus, the oceans and atmosphere form a coupled system, where it is
sometimes difficult to distinguish forcing from response. Because water has a density and effective heat capacity nearly 3 orders of magnitude greater than air, the ocean has mechanical and thermal inertia relative to the atmosphere. The ocean thus acts as a memory for the coupled ocean–atmosphere system. We begin with a discussion of air–sea interaction through surface heat fluxes, moisture fluxes, and wind forcing. The primary external force driving the ocean–atmosphere system is radiative warming from the Sun. Because of the fundamental importance of solar radiation, the surface wind and buoyancy forcing is illustrated here with two examples of the seasonal cycle. The first case describes the seasonal cycle in the North Pacific, and can be considered a classic example of a one-dimensional (involving only vertical processes) ocean response to wind and buoyancy forcing. In the second example, the seasonal cycle of the eastern tropical Pacific, the atmosphere and the ocean are coupled, so that wind and buoyancy forcing lead to a sequence of events that make cause and effect difficult to determine. The impact of wind and buoyancy forcing on the surface mixed layer and the deeper ocean is summarized in the conclusion.
Air–Sea Interaction Surface Heat Flux
As shown in Figure 1, the net surface heat flux entering the ocean (Q0) includes solar (shortwave) radiation (Qsw), net infrared (long-wave) radiation (Qlw), latent heat flux due to evaporation (Qlat), and sensible heat flux due to air and water having different surface temperatures (Qsen): Q0 ¼ Qsw þ Qlw þ Qlat þ Qsen
½1
The Earth’s seasons are largely defined by the annual cycle in the net surface heat flux associated with the astronomical orientation of the Earth relative to the Sun. The Earth’s tilt causes solar radiation to strike the winter hemisphere more obliquely than the summer hemisphere. As the Earth orbits the Sun, winter shifts to summer and summer shifts to winter, with the Sun directly overhead at the equator twice per year, in March and again in September. Thus, one might expect the seasonal cycle in the Tropics to be semiannual, rather than annual. However, as discussed later, in some parts of the
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(c) 2011 Elsevier Inc. All Rights Reserved. Internal wave radiation
Langmuir circulations
τ
Wave−current interaction
t
ds
win
s res
Precipitation
Aerosols
Bubble production and turbulence
Wave breaking
Sea spray
Shear at mixed layer base
Penetrating radiation
Evaporation
Infrared radiation
Figure 1 Schematic drawing of wind- and buoyancy-forced upper ocean processes. Courtesy Jayne Doucette, Woods Hole Oceanographic Institution.
Near-surface shear and microbreaking
Ekman spiral
Sensible heat transfer
Visible radiation
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WIND- AND BUOYANCY-FORCED UPPER OCEAN
equatorial oceans, the annual cycle dominates due to coupled ocean–atmosphere–land interactions. Solar radiation entering the Earth’s atmosphere is absorbed, scattered, and reflected by water in both its liquid and vapor forms. Consequently, the amount of solar radiation which crosses the ocean surface, Qsw, also depends on the cloud structures. The amount of solar radiation absorbed by the ocean mixed layer depends on the transmission properties of light in water and can be estimated as the difference between the solar radiation entering the surface and the solar radiation penetrating through the base of the mixed layer. The Earth’s surface also radiates energy at longer wavelengths similar to a black body (i.e., proportional to the fourth power of the surface temperature in units kelvin). Infrared radiation emitted by the atmosphere and clouds can reflect against the ocean surface and become upwelling infrared radiation. Thus net long-wave radiation, Qlw, is the combination of the outgoing and incoming infrared radiation and tends to cool the ocean. The ocean and atmosphere also exchange heat via conduction (‘sensible’ heat flux). When the ocean and atmosphere have different surface temperatures, sensible heat flux will act to reduce this temperature difference. Thus when the ocean is warmer than the air (which is nearly always the case), sensible heat flux will tend to cool the ocean and warm the atmosphere. Likewise, the vapor pressure at the air–sea interface is saturated with water while the air just above the interface typically has relative humidity less than 100%. Thus, moisture tends to evaporate from the ocean and in doing so, the ocean loses heat at a rate of
Qlat ¼ Lðrfw EÞ
½2
where Qlat is the latent heat flux, L is the latent heat of evaporation, rfw is the freshwater density, and E is the rate of evaporation. Qlat has units W m–2, and (rfwE) has units kg s 1 m–2. The latent heat flux is nearly always larger than the sensible heat flux due to conduction. When the evaporated moisture condenses in the atmosphere to form clouds, heat is released, affecting the large-scale wind patterns. Air–sea heat and moisture transfer occur through turbulent processes and is amplified by sea spray, bubble production, and wave breaking. Sensible and latent heat loss thus also depend on the speed of the surface wind relative to the ocean surface flow, |ua – us|. Using similarity arguments, the latent (Qlat) and sensible (Qsen) heat fluxes can be expressed in
339
terms of ‘bulk’ properties at and near the ocean surface: Qlat ¼ ra LCE jua us jðqa qs Þ
½4
Qsen ¼ ra cpa CH jua us jðTa Ts Þ
½4
where ra is the air density, cpa is the specific heat of air, CE and CH are the transfer coefficients of latent and sensible heat flux, qs is the saturated specific humidity at Ts, the SST, and qa and Ts are, respectively, the specific humidity and temperature of the air at a few meters above the air–sea interface. The sign convention used here is that a negative flux tends to cool the ocean surface. The transfer coefficients, CE and CH, depend upon the wind speed and stability properties of the atmospheric boundary layer, making estimations of the heat fluxes quite difficult. Most algorithms estimate the turbulent heat fluxes iteratively, using first estimates of the heat fluxes to compute the transfer coefficients. Further, the dependence of heat flux on wind speed and SST causes the system to be coupled since the heat fluxes can change the wind speed and SST. Figure 2 shows the climatological net surface heat flux, Q0, and SST for the entire globe. Several patterns are evident. (Note that the spatial structure of the climatological latent heat flux can be inferred from the climatological evaporation shown in Figure 3(a).) In general, the Tropics are heated more than the poles, causing warmer SST in the tropics and cooler SST at the poles. Also, there are significant zonal asymmetries in both the net surface heat flux and SST. The largest ocean surface heat losses occur over the mid-latitude western boundary currents. In these regions, latent and sensible heat loss are enhanced due to the strong winds which are cool and dry as they blow off the continent and over the warm water carried poleward by the western boundary currents. In contrast, the ocean’s latent and sensible heat loss are reduced in the eastern boundary region where marine winds blow over the cool water. Consequently, the eastern boundary is a region where the ocean gains heat from the atmosphere. These spatial patterns exemplify the rich variability in the ocean–atmosphere climate system that occurs on a variety of spatial and temporal scales. In particular, seasonal conditions can often be quite different from mean climatology. The seasonal warming and cooling in the north Pacific and eastern equatorial Pacific are discussed later. Thermal and Haline Buoyancy Fluxes
Since the density of seawater depends on temperature and salinity, air–sea heat and moisture fluxes can
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WIND- AND BUOYANCY-FORCED UPPER OCEAN
(a)
(b)
80 N 40 N 0 40 S 80 S 60 E
120 E
180
120 W
60 W
0
125 100 75 50 25 0 25 50 75 100 125 150 175 200
80 N 40 N 0 40 S 80 S 60 E
120 E
180
120 W
60 W
0
30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 2
1
10 ms
Figure 2 Mean climatologies of (a) net surface heat flux (W m–2) and (b) SST (1C), and surface winds (m s–1). The scale vector for the winds is shown below (b). Climatologies provided by da Silva et al. (1994). A positive net surface heat flux acts to warm the ocean.
(a)
12
80 N
11
(b)
12
80 N
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10 9
40 N
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60 W
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Figure 3 Mean climatologies of (a) evaporation and (b) precipitation from da Silva et al. (1994). Both have units of mm day–1 and share the scale shown on the right.
change the surface density, making the water column more or less buoyant. Specifically, the net surface heat flux (Q0), rate of evaporation (E), and precipitation (P) can be expressed as a buoyancy flux (B0): B0 ¼ gaQ0 =ðrcp Þ þ gbðE PÞS0
½5
where g is gravity, r is ocean density, cp is specific heat of water, S0 is surface salinity, a is the effective thermal expansion coefficient ðr1 @r=@TÞ, and b is the effective haline contraction coefficient ðr1 @r=@SÞ. Q0 has units W m–2 and E and P have units m s–1. B0 has units m2 s–3 and can be interpreted (when multiplied by density and integrated over a volume) as the buoyant production of turbulent kinetic energy (or destruction of available potential energy). A negative (i.e., downward) buoyancy flux, due to either surface warming or precipitation, tends to make the ocean surface more buoyant and stable. Conversely, a positive buoyancy flux, due to either
surface cooling or evaporation, tends to make the ocean surface less buoyant. As the water column loses buoyancy, it can become convectively unstable with heavy water lying over lighter water. Turbulent kinetic energy, generated by the ensuing convective overturning, can then cause deeper, generally cooler water to be entrained and mixed into the surface mixed layer (Figure 1). Thus entrainment mixing typically causes the SST to cool and the mixed layer to deepen. As discussed in the next section, entrainment mixing can also be generated by wind forcing, through wind stirring and shear at the base of the mixed layer. Figure 3 shows the climatological evaporation and precipitation fields. Note that in terms of buoyancy, a 20 W m–2 heat flux is approximately equivalent to a 5 mm day–1 rain rate. Thus, in some regions of the world oceans, the freshwater flux term in eqn [5] dominates the buoyancy flux, and hence is a major factor in the mixed layer thermodynamics. For
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WIND- AND BUOYANCY-FORCED UPPER OCEAN
example, in the tropical regions, heavy precipitation can result in a surface-trapped freshwater pool that forms a shallower mixed layer within a deeper, nearly isothermal layer. The difference between the shallower mixed layer of uniform density and the deeper isothermal layer is referred to as a salinitystratified barrier layer. As the name suggests, a barrier layer can effectively limit turbulent mixing of heat between the ocean surface and the deeper thermocline since the barrier layer water has nearly the same temperature as the mixed layer. In subpolar latitudes, freshwater fluxes can also dominate the surface layer buoyancy profile. During the winter season, atmospheric cooling of the ocean, and stronger wind mixing leaves the water-column isothermal to great depths. Then, wintertime ice formation extracts fresh water from the surface layer, leaving a saltier brine that further increases the surface density, decreases the buoyancy, and enhances the deep convection. This process can lead to deepwater formation as the cold and salty dense water sinks and spreads horizontally, forcing the deep, slow thermohaline circulation. Conversely, in summer when the ice shelf and icebergs melt, fresh water is released, and the density in the surface layer is reduced so that the resultant stable halocline (pycnocline) inhibits the sinking of water. Wind Forcing
The influence of the winds on the ocean circulation and mass field cannot be overstated. Wind blowing over the ocean surface causes a tangential stress (‘wind stress’) at the interface which acts as a vertical flux of horizontal momentum. Similar to the air–sea fluxes of heat and moisture, this air–sea flux of horizontal momentum, s0, can be expressed in terms of bulk properties as s0 ¼ ra CD jua us jðua us Þ
½6
where ra is the air density, and CD is the drag coefficient. The direction of the stress is determined by the orientation of the surface wind, ua, relative to the ocean surface flow, us. The units of the surface wind stress are N m–2. Wind stress can also be expressed in terms of an oceanic frictional velocity, u (i.e., s0 ¼ ru 2 ). With frictional velocity related to the wind-generated velocity shear through the nondimensional ‘von Ka´rma´n constant’, k, the shear production of turbulent kinetic energy by the wind can be expressed as: rðkzÞ1 u 3 . The mechanisms by which the momentum flux extends below the interface are not well understood. Some of the wind stress goes into generating ocean
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surface waves. However, most of the wave momentum later becomes available for generating currents through wave breaking, and wave–wave and wave–current interactions. For example, wave– current interactions associated with Langmuir circulation can set up large coherent vortices that carry momentum to near the base of the mixed layer. As with convective overturning, wind stirring can entrain cooler thermocline water into the mixed layer, producing a colder and deeper mixed layer. Likewise, current shear at the base of the mixed layer can cause ‘Kelvin–Helmholtz’ shear instability that further mix properties within and at the base of the mixed layer. Variability in the depth of the well-mixed layer can be understood through consideration of the turbulent kinetic energy (TKE) budget. For example, for a stable buoyancy flux (i.e., ‘forced convection’), the depth, LMO, at which there is just sufficient mechanical energy available from the wind to mix the input of buoyancy uniformly is referred to as the Monin–Obukhov depth scale: LMO ¼ u 3 =ðkB0 Þ
½7
At depths below LMO, buoyant suppression of turbulence exceeds the mechanical production and there tends to be little surface-generated turbulence. Typically, however, other terms in the TKE budget cannot be ignored. In particular, for an unstable buoyancy flux (i.e., ‘free convection’), the production of potential energy through entrainment becomes important. Thus the mixed layer depth is rarely equivalent to the Monin–Obukhov depth scale. Over timescales at and longer than roughly a day, the Earth’s spinning tends to cause a rotation of the vertical flux of momentum. From the noninertial perspective of an observer on the rotating Earth, the tendency to rotate appears as a force, referred to as the Coriolis force. When the wind ceases, inertial motion tends to continue and accounts for a significant fraction of the total kinetic energy in the global ocean. Vertical shear in the currents and inertial oscillations generated by the winds can cause ‘Kelvin– Helmholtz’ shear instability and be a significant source of TKE. For sustained winds beyond the inertial timescale, Coriolis turning causes the wind-forced surface layer transport (‘Ekman transport’) to be perpendicular to the wind stress. Because the projection of the Earth’s axis onto the local vertical axis (direction in which gravity acts) changes sign at the equator, the Ekman transport is to the right of the wind stress in the Northern Hemisphere and to the left of the wind stress in the Southern Hemisphere. Convergence and divergence of this Ekman transport leads to vertical
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WIND- AND BUOYANCY-FORCED UPPER OCEAN
motion which can deform the thermocline and thereby generate pressure gradients that set the subsurface waters in motion. In this way, meridional variations in the prevailing zonal wind stress drive the steady, large-scale ocean gyres. The influence of Ekman upwelling on SST can be seen along the eastern boundary of the ocean basins and along the equator (Figure 2(b)). Equatorward winds along the eastern boundaries of the Pacific and Atlantic Oceans cause an offshore-directed Ekman transport. Mass conservation requires that this water be replaced with upwelled water, water that is generally cooler than the surface waters outside the upwelling zone. Likewise, in the tropics, prevailing easterly trade winds cause poleward Ekman transport. At the equator, this poleward flow results in substantial surface divergence and upwelling. As with the eastern boundary, equatorial upwelling results in relatively cold SSTs (Figure 2(b)). Because of the geometry of the continents, the thermal equator favors the Northern Hemisphere and is generally found several degrees of latitude north of the equator. In the tropics, winds tend to flow from cool SSTs to warm SSTs, where deep atmospheric convection can occur. Thus, surface wind convergence in the Intertropical Convergence Zone (ITCZ) is associated with the thermal equator, north of the equator. The relationship between the SST gradient and winds accounts for an important coupling mechanism in the Tropics.
The Seasonal Cycle The North Pacific: A One-dimensional Ocean Response to Wind and Buoyancy Forcing
From 1949 through 1981, a ship (Ocean Weather Station Papa) was stationed in the North Pacific at 501 N 1451 W with the primary mission of taking routine ocean and atmosphere measurements. The seasonal climatology observed at this site (Figure 4) illustrates a classic near-one-dimensional ocean response to wind and buoyancy forcing. A one-dimensional response implies that only the vertical structure of the ocean is changed by the forcing. During springtime, layers of warmer and lighter water are formed in the upper surface in response to the increasing solar warming. By summer, this heating has built a stable (buoyant), shallow seasonal thermocline that traps the warm surface waters. In fall, storms are more frequent and net cooling sets in. By winter, the surface layer is mixed by wind stirring and convective overturning. The summer thermocline is eroded and the mixed layer deepens to the top of the permanent thermocline.
To first approximation, horizontal advection does not seem to be important in the seasonal heat budget. The progression appears to be consistent with a surface heat budget described by @T=@t ¼ Q0 =ðrcp HÞ
½8
where qT/qt is the local time rate of change of the mixed layer temperature, and H is the mixed layer depth. Since only vertical processes (e.g., turbulent mixing and surface forcing) affect the depth and temperature of the mixed layer, the heat budget can be considered one-dimensional. A similar one-dimensional progression occurs in response to the diurnal cycle of buoyancy forcing associated with daytime heating and nighttime cooling. Mixed layer depths can vary from just a few meters thick during daytime to several tens of meters thick during nighttime. Daytime and nighttime SSTs can sometimes differ by 41 1C. However, not all regions of the ocean have such an idealized mixed layer seasonal cycle. Our second example shows a more complicated seasonal cycle in which the tropical atmosphere and ocean are coupled.
The Eastern Equatorial Pacific: Coupled Ocean–Atmosphere Variability
Because there is no Coriolis turning at the equator, water and air flow are particularly susceptible to horizontal convergence and divergence. Small changes in the wind patterns can cause large variations in oceanic upwelling, resulting in significant changes in SST and consequently in the atmospheric heating patterns. This ocean and atmosphere coupling thus causes initial changes to the system that perpetuate further changes. At the equator, the Sun is overhead twice per year: in March and again in September. Therefore one might expect a semiannual cycle in the mixed layer properties. Although this is indeed found in some parts of the equatorial oceans (e.g., in the western equatorial Pacific), in the eastern equatorial Pacific the annual cycle dominates. During the warm season (February–April), the solar equinox causes a maximum in insolation, equatorial SST is warm, and the meridional SST gradient is weak. Consequently, the ITCZ is near the equator, and often a double ITCZ is observed that is symmetric about the equator. The weak winds associated with the ITCZ cause a reduction in latent heat loss, wind stirring, and upwelling, all of which lead to further warming of the equatorial SSTs. Thus the warm SST and surface heating are mutually reinforcing.
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WIND- AND BUOYANCY-FORCED UPPER OCEAN
343
Wind speed (m s1)
(a) 12 8 4
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Figure 4 Seasonal climatologies at the ocean weather station Papa in the north Pacific: (a) Wind speed, (b) net surface heat flux, and (c) upper ocean temperature. The bold line represents the base of the ocean mixed layer defined as the depth where the temperature is 0.5 1C cooler than the surface temperature. Wind speed and net surface heat flux climatologies are from da Silva et al. (1994).
Beginning in about April–May, SSTs begin to cool in the far eastern equatorial Pacific, perhaps in response to southerly winds associated with the continental monsoon. The cooler SSTs on the equator cause an increased meridional SST gradient that intensifies the southerly winds and the SST cooling in the far eastern Pacific. As the meridional SST gradient increases, the ITCZ begins to migrate northward. Likewise, the cool SST anomaly in the far east sets up a zonal SST gradient along the equator that intensifies the zonal trade winds to the west of the cool anomaly. These enhanced trade winds then produce SST cooling (through increased upwelling, wind stirring, and latent heat loss) that spreads westward (Figure 5).
By September, the equatorial cold tongue is fully formed. Stratus clouds, which tend to form over the very cool SSTs in the tropical Pacific, cause a reduction in solar radiation, despite the equinoctial increase. The large meridional gradient in SST associated with the fully formed cold tongue causes the ITCZ to be at its northernmost latitude. After the cold tongue is fully formed, the reduced zonal SST gradient within the cold tongue causes the trade winds to weaken there, leading to reduced SST cooling along the equator. Finally, by February, the increased solar radiation associated with the approaching vernal equinox causes the equatorial SSTs to warm and the cold tongue to disappear, bringing the coupled system back to the warm season conditions.
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WIND- AND BUOYANCY-FORCED UPPER OCEAN (a)
(b)
Feb.–Mar.–Apr.
May.–Jun.–Jul.
10 N
10 N
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Nov.–Dec.–Jan.
140 E
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10. ms1
Figure 5 Seasonal climatologies of the tropical Pacific SST (1C) and wind (m s–1): (a) Feb.–Mar.–Apr.; (b) May–Jun.–Jul.; (c) Aug.– Sep.–Oct.; and (d) Nov.–Dec.–Jan. Climatologies for wind are from da Silva et al. (1994) and for SSTs are from Reynolds and Smith (1994).
Conclusion Because the ocean mixed layer responds so rapidly to surface-generated turbulence through wind- and buoyancy-forced processes, the surface mixed layer can often be modeled successfully using onedimensional (vertical processes only) physics. Surface heating and cooling cause the ocean surface to warm and cool; evaporation and precipitation cause the ocean surface to become saltier and fresher. Stabilizing buoyancy forcing, whether from net surface heating or precipitation, stratifies the surface and isolates it from the deeper waters, whereas wind stirring and destabilizing buoyancy forcing generate surface turbulence that cause the surface properties to mix with deeper water. Eventually, however, one-dimensional models drift away from observations, particularly in regions with strong ocean– atmosphere coupling and oceanic current structures. The effects of horizontal advection are explicitly not included in one-dimensional models. Likewise, vertical advection depends on horizontal convergences
and divergences and therefore is not truly a one-dimensional process. Finally, wind and buoyancy forcing can themselves depend on the horizontal SST patterns, blurring the distinction between forcing and response. Although the mixed layer is the principal region of wind and buoyancy forcing, ultimately the effects are felt throughout the world’s oceans. Both the wind-driven motion below the mixed layer and the thermohaline motion in the relatively more quiescent deeper ocean originate through forcing in the surface layer that causes an adjustment in the mass field (i.e., density profile). In addition, buoyancy and wind forcing in the upper ocean define the property characteristics for all the individual major water masses found in the world oceans. On a global scale, there is surprisingly little mixing between water masses once they acquire the characteristic properties at their formation region and are vertically subducted or convected from the active surface layer. As these subducted water masses circulate through the global oceans and later outcrop, they can contain
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WIND- AND BUOYANCY-FORCED UPPER OCEAN
the memory of their origins at the surface through their water mass properties and thus can potentially induce decadal and centennial modes of variability in the ocean–atmosphere climate system.
Nomenclature B0 CD CE CH cp E g H L LMO P qa qs Q0 Qlat Qlw Qsen Qsw S0 Ta Ts ua us u* a b k r ra rfw s0
surface buoyancy flux drag coefficient latent heat flux transfer coefficient sensible heat flux transfer coefficient specific heat capacity of water rate of evaporation gravity mixed layer depth latent heat of evaporation Monin–Obkuhov depth scale precipitation specific humidity of the air saturated specific humidity at the sea surface temperature net surface heat flux entering ocean latent heat flux due to evaporation net infrared (long-wave) radiation sensible heat flux net solar (shortwave) radiation surface salinity air temperature surface ocean temperature air velocity surface ocean velocity oceanic frictional velocity thermal expansion coefficient haline contraction coefficient von Ka´rma´n constant ocean density air density density of fresh water wind stress
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See also Breaking Waves and Near-Surface Turbulence. Ekman Transport and Pumping. Langmuir Circulation and Instability. Ocean Circulation: Meridional Overturning Circulation. Pacific Ocean Equatorial Currents. Penetrating Shortwave Radiation. Sea Surface Exchanges of Momentum, Heat, and Fresh Water Determined by Satellite Remote Sensing. Upper Ocean Heat and Freshwater Budgets. Upper Ocean Time and Space Variability. Upper Ocean Vertical Structure. Water Types and Water Masses. Wind Driven Circulation.
Further Reading da Silva AM, Young CC, and Levitus S (1994) Atlas of Surface Marine Data 1994, Vol. 1: Algorithms and Procedures, NOAA Atlas NESDIS 6. Washington, DC: US Department of Commerce. Fairall CF, Bradley EF, Hare JE, Grachev AA, and Edson JB (2003) Bulk parameterization of air–sea fluxes: Updates and verification for the COARE algorithm. Journal of Climate 16: 571--591. Kraus EB and Businger JA (1994) Oxford Monographs on Geology and Geophysics: Atmosphere–Ocean Interaction, 2nd edn. New York: Oxford University Press. Large WG (1996) An observational and numerical investigation of the climatological heat and salt balances at OWS Papa. Journal of Climate 9: 1856--1876. Niiler PP and Kraus EB (1977) One-dimensional models of the upper ocean. In: Kraus EB (ed.) Modelling and Prediction of the Upper Layers of the Ocean, pp. 143--172. New York: Pergamon. Philander SG (1990) El Nin˜o, La Nin˜a, and the Southern Oscillation. San Diego, CA: Academic Press. Price JF, Weller RA, and Pinkel R (1986) Diurnal cycling: Observations and models of the upper ocean response to diurnal heating, cooling, and wind mixing. Journal of Geophysical Research 91: 8411--8427. Reynolds RW and Smith TM (1994) Improved global sea surface temperature analysis using optimum interpolation. Journal of Climate 7: 929--948.
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WIND DRIVEN CIRCULATION P. S. Bogden, Maine State Planning Office, Augusta, ME, USA C. A. Edwards, University of Connecticut, Groton, CT, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3227–3236, & 2001, Elsevier Ltd.
Introduction Winds represent a dominant source of energy for driving oceanic motions. At the ocean surface, such motions include surface gravity waves, which are familiar as the waves that break on beaches. Winds are also responsible for small-scale turbulent fluctuations just beneath the ocean surface. Turbulent motions can be created by breaking waves or by the nonlinear evolution of currents near the air–sea interface. Subsurface processes such as these can lead to easily observed windrows or scum lines on the sea surface. Winds also generate other complex and varied small-scale motions in the top few tens of meters of the ocean. However, the surface/wind-driven circulation described here refers instead to considerably larger-scale motions that compare in size to the ocean basins and extend as much as a kilometer or more below the surface. The textbook notion of the surface/wind-driven circulation includes most of the well-known surface currents, such as the intense poleward-flowing Gulf Stream in the western North Atlantic (Figure 1). Analogues of the Gulf Stream can be found in each of the major ocean basins, including the Kuroshio in the North Pacific, the Brazil Current in the South Atlantic, the East Australian Current in the South Pacific, and the Aghulas in the Indian. These ‘western boundary currents’ are not isolated structures. Rather, they represent the poleward return flow for basinscale motions that occupy middle latitudes in all major oceans. Each of the major ocean basins has an analogous set of large-scale current systems. The western boundary currents are quite intense, reaching velocities in excess of 1 m s1, while the interior flow speeds are considerably smaller in magnitude. The basin-scale patterns in the mid-latitude surface circulation are referred to as subtropical gyres. The gyres extend many hundreds of meters below the surface, reaching the bottom in some locations. Subtropical gyres rotate anticyclonically, that is, they rotate in a sense that is opposite to the sense of the earth’s rotation (clockwise in the northern hemisphere and counterclockwise in the south). In the
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North Atlantic and North Pacific, subpolar gyres reside to the north of the subtropical gyres. They too include intense western boundary currents. However, the subpolar gyres rotate cyclonically, in the opposite sense of the subtropical gyres and in the same sense as the earth. Rotation of the wind-driven gyres is related to the rotation of the earth through a simple, though nonintuitive, physical mechanism. This mechanism is fundamental to understanding how the wind drives large-scale flows. Our present understanding of the dynamics associated with the surface/wind-driven circulation developed largely during a 30-year period starting in the late 1940s. Before that time, oceanographers were aware of the gyre-scale features of the surface circulation. But it was not until the major theoretical advances in geophysical fluid dynamics beginning around 1947 that the surface circulation was conceptually linked to the winds.
Observations Oceanic wind systems exhibit a large-scale pattern that is common to the major ocean basins (Figure 2). Near the equator, trade winds blow from east to west. Near the poles, westerly winds blow from west to east. The ocean gyres have similar distributions of east–west flow. But the reasons for this are quite subtle. Moreover, there are profound differences between oceanic and atmospheric motion. North– south flows in the ocean are much more strongly pronounced than they are in the atmosphere, and winds fail to exhibit analogues of the intense poleward western boundary currents found in the ocean. Western boundary currents such as the Gulf Stream were evident in estimates of time-averaged surface circulation obtained over a century ago with ‘shipdrift’ data (Figure 3). Ship drift is the discrepancy between a ship’s position as obtained with dead reckoning and that obtained by more accurate navigation. Thus, ship drift can be attributed at least in part to ocean currents. The patterns of the surface circulation that emerge after averaging large numbers of such measurements are qualitatively correct. In general, however, accurate measurements of currents are difficult to obtain, particularly below the surface. Temperature and salinity measurements are relatively abundant, and they provide an alternative resource for estimating large-scale currents. Temperature and salinity determine seawater density. The density distribution provides information about the pressure
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WIND DRIVEN CIRCULATION
. dC
th or
I.C
Caribbean C.
y Curr
North Equatorial Current
CC
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Gyre AC
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eg rw
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n ya
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unter C.
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ial
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vina
sC .
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zil
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ela ngu t n rre Cu
rre
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60˚S 90˚S
Figure 1 Schematic of large-scale surface currents in the Atlantic Ocean. (From Tomczak and Godfrey (1994) Regional Oceanography: An Introduction.)
field, which in turn can be used to diagnose currents. For many decades, oceanographers have been routinely measuring vertical profiles of temperature and salinity. Consequently, detailed maps of the three-dimensional density structure exist for all the ocean basins. Such maps clearly show a region of anomalously large vertical gradients in temperature, salinity, and density known as the main thermocline. The main thermocline divides two regions of relatively less
stratified water near the surface and bottom. Thermocline depth varies substantially on the gyre scale, and can exceed 700 m depth in some regions. Lateral variations in the density field can be quite large as well, and these are associated with the currents that we refer to as the surface/wind-driven circulation. The first step in estimating currents from density involves computation of dynamic height using the principle of isostasy. Isostasy describes, for example,
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348
WIND DRIVEN CIRCULATION
30°E
60°E
90°E
120°E 150°E 180°W 150°W 120°W 90°W 60°W 30°W
0°
90°N
60°N _2
0.5 N m
30°N
0°
30°S
60°S 90°S
Figure 2 Global mean surface wind stress, which is related to wind [1]. (From Tomczak and Godfrey (1994) Regional Oceanography: An Introduction.)
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Figure 3 Surface currents inferred from ship-drift measurements. To simplify the presentation, there are three vector sizes in this figure indicated by the scale vectors at the bottom of the figure. A vector the size of vector 1 corresponds to flow speeds in the range 0–10 cm s1, vector 2 is 10–20 cm s1, vector 3 is more than 30 cm s1. While some of the values have questionable reliability, the vectors show the general patterns large-scale circulation at the ocean surface. From Stidd CK (1974) Ship Drift Components: Means and standard Deviations, SIO Reference Series 74-33 as appearing in Burkov VA 1980 General Circulation of the World Ocean. Gidrometeoizdat Publishers, Leningrad, published for the Division of Ocean Sciences, National Science Foundation, Washington, DC, by Amerind Publishing Co. Pvt. Ltd., New Delhi. 1993.
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WIND DRIVEN CIRCULATION
the pressure field in a glass of ice water. An ice cube represents a region where water is slightly less dense than its surroundings. Buoyancy forces elevate the surface of the ice cube above the surface of the surrounding fluid. Similarly, a region in the ocean with less dense water than its surroundings will have a slightly elevated sea surface. In the ocean, this result involves the tacit assumption that currents in the abyssal ocean are weak relative to those nearer the surface, as is usually the case. The ocean’s surface topography implied by the density field is referred to as dynamic height. Figure 4 shows dynamic height computed from density between 2000 and 200 m depth. The variations of a meter or more are large enough to account for the pressure gradients that force the large-scale gyres. The connection between pressure and large-scale currents involves the principle of ‘geostrophy’. Geostrophic currents arise from a balance of the forces involving pressure gradient forces and Coriolis accelerations. This balance is a consequence of the large horizontal scales of the flow combined with the rotation of the earth. If the earth were not rotating, the sea surface elevations would accelerate horizontal flows down the pressure gradient, as occurs with smaller-scale motions such as surface gravity waves. With large-scale geostrophic flows, however, the Coriolis effect gives rise to currents that flow perpendicular to the pressure gradient, as indicated by the arrows in Figure 4. Geostrophic currents such as those in Figure 4 provide evidence of the surface/wind-driven circulation.
30°E
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Wind-driven Surface Layer Surface Mixed Layer
The surface mixed layer is loosely defined as a part of the water column near the surface where observed temperature and salinity fields are vertically uniform. In practice this layer extends from the ocean surface to a depth where stratification in temperature or density exceeds some threshold value. Typically, the underlying water is more strongly stratified. The mixed-layer depth often undergoes large diurnal and seasonal variations, varying between 0 and 100 m. However, the surface mixed layer rarely occupies more than 1% of the total water column. Winds provide the primary source of mechanical forcing for the motions that homogenize water properties within the mixed layer. Mixing can also result from destabilizing effects of cooling and
19 21
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This point requires some explanation, since the geostrophic flows are associated with large-scale pressuregradient forces in the top kilometer of the ocean. As discussed below, winds directly drive motions in a relatively thin layer at the ocean surface known as the surface mixed layer. But these directly wind-driven flows give rise to other large-scale flows and, in turn, to the large-scale pressure gradients that can be estimated with dynamic height. Thus, it is accurate to refer to the large-scale geostrophic surface circulation as the winddriven circulation because the pressure gradients would not exist without the wind.
120°E 150°E 180°W 150°W 120°W 90°W 60°W 30°W <
349
<8
<6
60°S
90°S
Figure 4 Dynamic height (m2 s2) computed using the density field between 0 m and 2000 m depth, and assuming that the pressure field at 2000 m has no horizontal variation. Dynamic height is roughly proportional to the sea-surface height, in meters, multiplied by 10. (Based on Levitus (1982).)
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WIND DRIVEN CIRCULATION
evaporation near the surface, as these can temporarily give rise to localized regions where the surface water overlies less dense water. Restratification of a stable water column involves solar heating from above, reduced salinity from precipitation, and other more subtle processes. The detailed mechanisms by which wind generates small-scale motions (i.e., motions on scales smaller than the mixed-layer depth, such as breaking waves) are quite complex and incompletely understood. Nevertheless, the effect of wind on the surface mixed layer is commonly parameterized through a stress tw on the ocean surface. Wind stress has units of force per unit area. The standard empirical relation has the form of eqn [1]. tw ¼ rair Cd u2 ;
½1
where ra is the density of air, Cd E103 is a drag coefficient that may depend on wind speed and atmospheric stability, and u is the wind speed 10 m above the sea surface. Ten meters is the standard height that commercial ships use to mount their anemometers, and ship reports still account for most of the direct measurements of wind over the ocean. Ekman Dynamics
The small-scale motions that mix temperature and salinity also mix momentum. As a result, the momentum of the wind is efficiently transmitted throughout the mixed layer, thereby accelerating horizontal currents. The resulting motions have large horizontal length scales comparable to those of the wind systems that drive them. In 1905, V.W. Ekman developed a model revealing the influence of the earth’s rotation on such large-scale flows. His dynamical model presumed that the force associated with a divergence in the vertical momentum flux is balanced by Coriolis accelerations associated with the horizontal flows. The vertical momentum flux in this wind-driven Ekman layer is the result of turbulent mixing processes that Ekman parametrized using Fick’s law. Thus, the vertical turbulent flow of momentum is made proportional to the vertical gradient of the large-scale horizontal velocity. This parametrization involves an uncertain constant of proportionality called the vertical eddy viscosity Av. Ekman’s model predicts horizontal currents that simultaneously decrease and rotate with depth. Within this so-called Ekman spiral, currents decrease away from the surface with a vertical scale D known as the Ekman depth (eqn [2]). D ¼ ð2Av =f Þ1=2
½2
This relation provides our first introduction to the Coriolis parameter f ¼ 2O sin y, where y is latitude, which appears here because of Coriolis accelerations in the Ekman dynamics. The angular velocity of the earth is a vector of magnitude O ¼ 2 p day that is parallel to the earth’s axis of rotation. The Coriolis parameter equals twice the magnitude of the vector component that is parallel to the local vertical. The vertical component is the only component that creates horizontal Coriolis accelerations with horizontal flow. This dependence on the local vertical and the sphericity of the earth explain the sin y factor in the formula for f. Thus, for any given flow, Coriolis accelerations are strongest at the poles, negligible at the equator, and smoothly varying in between. As discussed below, this geometric detail has profound implications for the surface/wind-driven circulation. Consider a typical mixed-layer depth of 30 m at mid-latitudes, where f E104 s1 . By relating these two quantities to an Ekman depth D, one deduces a vertical eddy viscosity Av E0:05 m2 s1. This value is many orders of magnitude larger than the kinematic viscosity of water, vE106 m2 s1. The large value of Av indicates the efficiency of turbulent mixing compared with molecular diffusion. But Av arises from the use of Fick’s law to parametrize the turbulence, and Fick’s law is an oversimplified model for turbulence. In fact, details of the wind-mixed layer that depend heavily on Av , such as spiraling velocities, are rarely observed. There is, nevertheless, one very important and robust conclusion from Ekman theory. The net mass transport (the Ekman transport) within the mixed layer, i.e., the vertical integral of the horizontal flow, has magnitude UEkman ¼ t=ðrf Þ
½3
where r is the density of water. This result does not depend on Av . Thus, while the details and vertical extent of the Ekman flow depend on the complexities of mixing, the net Ekman transport does not. Furthermore, Ekman theory predicts that the net transport UEkman is directed 901 to the right of the wind in the northern hemisphere and 901 to the left of the wind in the southern hemisphere. This result is quite contrary to what one would find if the earth were not rotating. The Ekman transport describes the net horizontal motion in a thin surface mixed layer. Implications for flows in the interior of the ocean depend on the large-scale patterns in the wind stress, as shown in Figure 2. In particular, westward wind stress near the equator results in poleward Ekman mass transport and eastward wind stress at higher latitudes drives
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WIND DRIVEN CIRCULATION
equatorward Ekman transport. This pattern results in a convergence of fluid that gives rise to an elevated sea surface at the center of the clockwise wind system. Ultimately, this horizontally convergent Ekman transport has only one direction in which to go – down. The resultant downward motion at the base of the mixed layer, called Ekman pumping, occurs in all mid-latitude ocean basins. Likewise, at higher latitudes, counterclockwise wind systems cause horizontally divergent Ekman transport, a depressed sea surface, and an upward motion known as Ekman suction. In the classic wind-driven ocean circulation models discussed below, vertical Ekman flows drive the horizontal geostrophic flow. In fact, the net effect of all the complex motions in the mixed layer is often reduced to a simple prescription of the vertical Ekman-pumping velocity WEkman (eqn[4]). WEkman ¼ curlðtw =rf Þ
½4
where curl(tw =rf Þ) represents the curl of the surface wind-stress vector divided by rf. Thus, it is not simply the magnitude of the wind stress that determines the Ekman pumping velocities, but its spatial distribution. The Ekman-pumping velocity is often applied as a boundary condition at the sea surface associated with a negligibly thin mixed layer. On average, Ekman-pumping speeds rarely exceed 1 mm s1. Nevertheless, such minuscule vertical velocities give rise to the most massive current systems in the ocean. This remarkable fact reflects the enormous constraint that the earth’s rotation plays in large-scale ocean dynamics.
Large-scale Dynamics The directly wind-driven flows within the Ekman layer occupy only a small fraction of the total water column. In fact, the impact of the wind extends considerably deeper. The connection between the minute Ekman-pumping velocities and the tremendous horizontal flows associated with the surface/wind-driven circulation involves a balance of forces that is very different from that in the surface mixed layer. Far from continental boundaries, and below the surface mixed layer, the basin-scale circulation varies on length scales measured in thousands of kilometers. The time-averaged horizontal velocities sometimes exceed 1 m s1, but they more generally vary between 1 and 10 cm s1. With these scales, flows are plausibly geostrophic. Furthermore, when the density is uniform, geostrophic flows exhibit no vertical variation. Rather, they behave like a horizontal continuum of vertical columns of fluid. It is reasonable to
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approximate the region between the mixed layer and the thermocline as a region of constant density. In this region the geostrophic columns of fluid span many hundreds of meters. The earliest models of the ocean circulation obtained remarkable predictive skills by assuming that columnar geostrophic flow extends from the top to the bottom of the ocean. Downward Ekman-pumping velocities, as small as they may be, effectively compress the fluid columns. Under the influence of downward Ekman pumping, fluid columns below the mixed layer compress vertically and expand horizontally, as if they were conserving their total volume. Likewise, Ekman suction causes water columns to stretch vertically and contract horizontally. Because of the earth’s rotation, the effect of Ekman pumping and suction on large-scale motions is related to the principle of angular momentum conservation in classical mechanics. For example, a water column that undergoes the stretching effect of Ekman suction is not unlike a rotating figure skater who draws in her arms, thereby decreasing her moment of inertia and rotating more rapidly. (Note: The analogy is incomplete because Ekman pumping is a consequence of external forcing, whereas the spinning skater is unforced. Nevertheless, the comparison is physically relevant.) Ekman pumping is then similar to a skater extending her arms, which causes a reduction of rate of spin. The connection between water-column stretching and horizontal flow in the ocean involves one additional subtle point: Water columns on the earth rotate by virtue of their location on the earth’s surface. Vertical fluid columns that appear stationary in the earth’s frame of reference are actually rotating at a rate that is proportional to the vertical component of the earth’s angular velocity. The absolute rotation rate is the sum of the earth’s rotation plus the rotation relative to the earth. More precisely, the fluid’s absolute vorticity includes a contribution from the planetary vorticity, which has magnitude equal to the Coriolis parameter f, plus a contribution from its relative vorticity. Relative vorticity is measured from a frame of reference that is fixed on the earth’s surface. The earth itself rotates at a rate of one revolution per day. In comparison, large-scale ocean currents progress around an ocean basin at average speeds much less than 1 m s1, so the period of rotation associated with a complete circuit can be several years. Thus, the relative rotation rate of large-scale ocean currents is negligible compared with the rotation rate of the earth itself. For this reason, it is a very good approximation to neglect the relative vorticity and equate the vorticity of the large-scale circulation with f . The critically important result is that fluid columns change their vorticity by changing their latitude. Just
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WIND DRIVEN CIRCULATION
as the skater who extends her arms starts to rotate more slowly, a water column undergoing the compression of Ekman pumping will travel toward the equator where the magnitude of f is smaller. The physical mechanism that connects Ekman pumping and subsurface geostrophic flow was described mathematically by H.U. in 1947, and is summarized by the relation (eqn [5]). bV ¼ f ðWEkman Wdeep Þ
½5
V represents the meridional (positive northward) velocity integrated over the depth H of the water column, b ¼ ð1=RÞ@f =@y is the meridional variation in the Coriolis parameter, R is the radius of the earth, Ww is the Ekman pumping velocity, and Wdeep is a vertical velocity at depth H. In this model, V is the depth-integrated geostrophic velocity. While prescription of Wdeep is discussed further below, the early models of the wind-driven circulation assumed that Wdeep ¼ 0 at some depth well below the main thermocline. Thus, V can be estimated using the Sverdrup relation with WEkman prescribed using eqn [1], eqn [4] and measurements of wind. V computed in this way agrees remarkably well with V computed from geostrophic flows estimated from the observed density field. The agreement is good everywhere except near the western boundaries of the ocean basins.
origin. This calculation comes close to predicting the observed transport in the poleward-traveling Gulf Stream at some locations. But models that predict the structure and location of the return flow require fundamentally different dynamics. In 1948, H. Stommel developed a theory for the wind-driven circulation in which the ocean bottom exerts a frictional drag on the horizontal flow. In the ocean interior, the Stommel and Sverdrup dynamics are nearly indistinguishable, but bottom friction becomes important near the western boundary, allowing Stommel’s model to predict a closed circulation for the entire ocean basin (Figure 5). The friction-dominated western boundary layer contains the intense poleward analogue of the Gulf Stream. Stommel showed the remarkable fact that westward intensification of the wind-driven gyres is fundamentally linked to the latitudinal variation of the Coriolis parameter. That is, the Gulf Stream and its western-boundary analogues in all the ocean basins exist because of the sphericity of the rotating earth (Figure 6). Friction is the key to closing the circulation cell. In Stommel’s model the friction parametrization was 10 30
20
40
Westward Intensification While the Sverdrup relation provides guidance for the ocean interior, it cannot describe the basin-wide circulation. From a mathematical viewpoint, the Sverdrup relation is a purely local relation between wind stress and meridional flow, so it does not determine east–west flow within the basin. Moreover, the Sverdrup relation predicts that V will be large only where WEkman is large. In fact, V is observed to be largest in the intense western boundary currents found in each ocean basin, such as the Gulf Stream. This is problematic because WEkman fails to exhibit the westward intensification, or a change in sign. This means that the Sverdrup relation predicts weak western boundary flow in the wrong direction! Thus, the Sverdrup balance must break down, at least in certain regions. It is common to presume that Sverdrup theory holds everywhere in the ocean interior except near the western ocean boundary (and northern and southern boundaries if the wind-stress curl does not vanish there). Then, V can be integrated from east to west to determine the total transport required in a poleward western boundary current that returns the meridional Sverdrup transport back to its place of
1000 km
(A) 20 40 60 80
(B)
1000 km
Figure 5 Streamlines from Stommel’s model indicating the total flow in an idealized flat-bottom subtropical gyre. The flow is everywhere parallel to the streamlines in the direction indicated by the arrows. Flow intensity is greatest where the streamlines are closest together. (A) An idealized subtropical gyre for a rotating earth in which the Coriolis parameter varies with latitude. (B) Streamlines for a ‘uniformly’ rotating earth, that is, for a Coriolis parameter that does not vary with latitude. (From Stommel (1948).)
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WIND DRIVEN CIRCULATION
0
_ 50
20 40
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Figure 6 Contours of sea-surface height from Stommel’s model. (A) Sea-surface height consistent with the stream function of Figure 5. Features in this figure can be directly compared with the dynamic height computed from data in Figure 4. (B) Sea-surface height for Stommel’s model after setting the Coriolis parameter to a constant. This effectively removes the geometrical factor associated with sphericity. Stommel referred to this as the case of a ‘uniformly rotation ocean’. (C) The sea-surface height for the same wind distribution as in (A) and (B), but for a nonrotating ocean. (From Stommel (1948).)
chosen for its simplicity, but it is ultimately unrealistic. In 1950, W. Munk developed a similar flat-bottom model with lateral viscosity, an entirely different form of dissipation. Nevertheless, Munk’s model produces an intense western boundary current for the same reasons as does the Stommel model. The primary results from these frictional models are robust. Both theories deduce the zonal flow within the basin, and share the central conclusion that the return flow for the interior Sverdrup transport occurs in a meridional current near the western
353
edge of the basin. This current is an example of a boundary layer, a narrow region governed by different physical balances from those dominating the larger domain. In the western boundary layer, fluid columns can change latitude because dissipation changes their vorticity, thereby counteracting the effects introduced by the Ekman pumping or suction. Both models show that this dissipative mechanism can only occur in an intense western boundary layer. Dissipation in both models actually parametrizes many interesting smaller-scale phenomena. This is evident in Munk’s model. The horizontal viscosity needed to produce a realistic Gulf Stream is many orders of magnitude larger than molecular viscosity, larger even than Ekman’s vertical eddy viscosity, Av . Modern theories show that these viscous parametrizations for ocean turbulence greatly oversimplify the effect of small-scale motions on the large-scale circulation. More importantly, the Stommel and Munk models neglect the fact that the ocean has variable depth and density stratification.
Topography, Stratification, and Nonlinearity The simplified Stommel and Munk models describe the wind-driven circulation for a rectangular ocean that has uniform density, a flat bottom, and vertical side walls. It remains to put these idealized models in context for an ocean that has density stratification, mid-ocean ridges, and continental slopes and shelves. The flat-bottom constant-density models clearly oversimplify the ocean geometry. Were the midocean ridges placed on land, they would stand as tall as the Rockies and the Alps. The assumption of constant density turns out to be an oversimplification of comparable proportions. In flat-bottom models, deep currents are unimpeded by topographic obstructions. With realistic bathymetry, however, flow into regions of varying depth can lead to large vertical velocities. For rotating fluid columns, these vertical velocities affect vorticity. Computer models that add realistic bathymetry and Ekman pumping to the Stommel or Munk models show that such vertical velocities can substantially alter the horizontal flow pattern, so much so that the flows in the center of the ocean no longer resemble the observed surface circulation. Thus, in idealized constant-density models, realistic bathymetry eliminates the most remarkable similarities between the models and the ocean observations. This conundrum can be reconciled in a model that has variable density. In a constant-density ocean, geostrophic fluid columns extend all the way to the
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WIND DRIVEN CIRCULATION
bottom. This allows bottom topography to have an unrealistically strong influence on the flow. Density stratification reduces the vertical extent of columnar motion. Conceptually, a stratified ocean behaves almost like a series of distinct layers, each with variable thickness and constant density. For example, the main thermocline may be considered the interface between one continuum of fluid columns in a surface layer and a second continuum of fluid columns in an abyssal layer. Generalizations of the Stommel and Munk models have often treated the ocean as two distinct layers of fluid. The main thermocline varies smoothly compared with the ocean bottom. This means that there are fewer obstructions to the columnar flow above the thermocline than below. In this sense, the thermocline effectively isolates the ocean bathymetry from the surface circulation. In fact, observed currents above the main thermocline tend to be stronger. While the Sverdrup theory applies to the top-tobottom transport, stratification allows the flow to be surface intensified. Smaller abyssal velocities reduce the influence of bottom topography. Flat-bottom models describe a limiting case where the topographic effects are identically zero. Without question, the vertical extent of the largescale wind-driven circulation is linked to density stratification. Realistic models of the large-scale circulation must include thermodynamic processes that affect temperature, salinity, and density structure. For example, atmospheric processes change the heat and fresh water content of the surface mixed layer. Largescale motions can result when the water column becomes unstable, with more dense water overlying less dense water. The resulting motion is often referred to as the thermohaline circulation, as distinct from the wind-driven circulation, but the conclusion to be drawn from the more realistic ocean-circulation models is that the thermohaline circulation and the wind-driven circulation are inextricably linked. Additional factors come into play in the more comprehensive ocean models. For example, the persistent temperature and salinity structure of the ocean indicates that many large-scale features in the ocean have remained qualitatively unchanged for decades, perhaps even centuries. But there are no simple (linear) theories that predict the existence of the thermocline. The transport and mixing of density by ocean currents are inherently nonlinear effects. Other classes of nonlinearities inherent to fluid flow add other types of complexity. Such nonlinear effects account for Gulf Stream rings, mid-ocean eddies, and much of the distinctly nonsteady character of the ocean circulation. Ocean currents are remarkably variable. Variability on
much shorter timescales of weeks and months, and length scales of tens and hundreds of kilometers, often dominates the larger-scale flows discussed here. Thus, it is not appropriate to think of the ocean circulation as a sluggish, linear, and steady. Instead, it is more appropriate to think of the ocean as a complex turbulent environment with its own analogues of unpredictable atmospheric weather systems and climate variability. Nevertheless, the simplified theories of steady circulation illustrate important mechanisms that govern the time-averaged flows. In closing, two ocean regions deserve special mention: the equatorial ocean and the extreme southern ocean. Equatorial regions have substantially different dynamics compared with models discussed above because Coriolis accelerations are negligible on the equator, where f ¼ 0. The wind-related processes that govern El Nin˜o and the Southern Oscillation, for example, depend critically on this fact. The southern ocean distinguishes itself as the only region without a western (or eastern) continental boundary. This absence of boundaries produces a circulation characteristic of the atmosphere, with intense zonal flows that extend around the globe. They represent some of the most intense large-scale currents in the world, and derive much of their energy from the wind. So they too represent an important part of the surface/wind-driven circulation.
See also Atlantic Ocean Equatorial Currents. Benguela Current. Brazil and Falklands (Malvinas) Currents. Canary and Portugal Currents. Current Systems in the Atlantic Ocean. Florida Current, Gulf Stream, and Labrador Current. Surface Gravity and Capillary Waves.
Further Reading Henderschott MC (1987) Single layer models of the general circulation. In: Abarbanel HDI and Young WR (eds.) General Circulation of the Ocean. New York: Springer-Verlag. Pedlosky J (1996) Ocean Circulation Theory. New York: Springer-Verlag. Salmon R (1998) Lectures on Geophysical Fluid Dynamics. Oxford: Oxford University Press. Stommel H (1976) The Gulf Stream. Berkeley: University of California Press. Veronis G (1981) Dynamics of large-scale ocean circulation. In: Warren BA and Wunsch C (eds.) Evolution of Physical Oceanography. Cambridge. MA: MIT Press.
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS P. H. Wiebe, Woods Hole Oceanographic Institution, Woods Hole, MA, USA M. C. Benfield, Louisiana State University, Baton Rouge, LA, USA
until recent technological developments enabled the use of high-frequency acoustics and optical systems as well.
Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 6, pp 3237–3253, & 2001, Elsevier Ltd.
Introduction In the late 1800s and early 1900s, quantitative ocean plankton sampling began with non-opening/closing nets, opening/closing nets (mostly messenger-based), high-speed samplers, and planktobenthos net systems. Technology gains inelectrical/electronic systems enabled investigators to advance beyondsimple vertically or obliquely towed nets to multiple codend systems and multiple net systems in the 1950s and 1960s. Recent technological innovation has enabled net systems to be complemented or replaced by optical and acoustics-based systems. Multi-sensor zooplankton collection systems are now the norm and in the future, we can anticipate seeing the development of real-time four-dimensional plankton sampling and concurrent environmental measurements systems, and ocean-basin scale sampling with autonomous vehicles. From the beginning of modern biological oceanography in the late 1800s, remotely operated instruments have been fundamental to observing and collecting zooplankton. For most of the past century, biological sampling of the deep ocean has depended upon winches and steel cables to deploy a variety of instruments. The development of quantitative zooplankton collecting systems began with Victor Hensen in the 1880s (Figure 1A). His methods covered the whole scope of plankton sampling from the building and handling of nets to the final counting of organisms in the laboratory. Three kinds of samplers developed in parallel: waterbottle samplers that take discrete samples of a small volume of water (a few liters), pumping systems that sample intermediate volumes of water (tens of liters to tens of cubic meters), and nets of many different shapes and sizes that are towed vertically, horizontally, or obliquely and sample much larger volumes of water (tens to thousands of cubic meters) (Table 1). Net systems dominated the equipment normally used to sample zooplankton
Net Systems A variety of net systems have been developed over the past 100 þ years and versions of all of these devices are still in use today. They can be categorized into eight groups: non-opening/closing nets, simple opening/closing nets, high-speed samplers, neuston samplers, planktobenthos plankton nets, closing cod-end samplers, multiple-net systems, and moored plankton collection systems.
Non-opening/Closing Nets
Numerous variants of the simple non-opening/ closing plankton net have been developed, which are principally hauled vertically. Most are simple ringnets with mouth openings ranging from 25 to 113 cm in diameter and conical or cylinder-cone nets 300– 500 cm in length. Among the ring-nets that have been widely used are the Juday net (Figure 1B), International Standard Net, the British N-series nets, the Norpac net, the Indian Ocean Standard net (Figure 1C), the ICITA net, the WP2 net, the CalCOFI net, and the MARMAP Bongo net (Figure 1D). Early nets were made from silk, but today nets are made from a square mesh nylon netting. Typical meshes used on zooplankton nets range from 150 mm to 505 mm, although larger and smaller mesh sizes are available. Most of these nets are designed to be hauled vertically. They are lowered to depth cod-end first and then pulled back to the surface with animals being caught on the way up. Others, such as the CalCOFI net and the Bongo net are designed to be towed obliquely from the surface down to a maximum depth of tow and then back to the surface. The Reeve net was a simple ring-net with a very large cod-end bucket designed to capture zooplankton alive. The Isaacs-Kidd midwater trawl (IKMT) has been used to collect samples of the larger macrozooplankton and micronekton. It has a pentagonal mouth opening and a dihedral depressor vane as part of the mouth opening. Four sizes of IKMTs, 3 foot (91 cm), 6 foot (183 cm), 10 foot (304 cm), and 15 foot (457 cm) are often cited.
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
(B)
(A)
(C)
(E)
(D)
Figure 1 Some commonly used non-opening/closed nets. (A) The Hensen net. (Reproduced with permission from Winpenny, 1937.) (B) The Juday net; note the use of messenger release on this version of the net. (Reproduced with permission from Juday, 1916.) (C) The Indian Ocean Standard net. (Reproduced with permission from Currie, 1963.) (D) The Bongo net with CTD (c. 1999). (Photograph courtesy of P. Wiebe.) (E) The Tucker trawl. (Reproduced with permission from Tucker, 1951.)
Non-opening/closing nets with rectangular mouth openings were not widely used until the Tucker trawl was first described in 1951 (Figure 1E). This simple trawl design with a 180 cm 180 cm mouth opening gave rise to a substantial number of opening/closing net systems described below.
Simple Opening/Closing Nets
The development of nets that could obtain depthspecific samples evolved from those of very simple design (a simple ring net) at an early stage. In the late 1800s and early 1900s, there was considerable effort
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
Table 1
Summary of zooplankton sampling gear types
Sampling gear
Conventional methods Waterbottles Small nets Large nets High-speed samplers Pumps Multiple net systems Continuous plankton recorder Longhurst-Hardy plankton recorder MOCNESS BIONESS RMT Multinet
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Type of sampling
Size fraction
Resolving scale
Typical operating range
Vertical
Horizontal
Vertical
Horizontal
Discrete samples Vertically integrating Vertical, obliquely Horizontally integrating Obliquely, horizontally integrating Discrete samples
Micro/meso Micro/meso Meso/macro
0.1–1 m 5–100 m 5–1000 m
— — 50–5000 m
4000 m 500 m 1000 m
— — 10 km
Meso/macro
5–200 m
500–5000 m
200 m
10 km
Micro/meso
0.1–100 m
—
200 m
—
Horizontally integrating
Meso
10–100 m
10–100 m
100 m
1000 km
Obliquely, horizontally integrating Obliquely, horizontally integrating Obliquely, horizontally integrating Obliquely, horizontally integrating Vertically Obliquely, horizontally
Meso
5–20 m
15–100 m
1000 m
10 km
Meso/macro
1–200 m
100–2000 m
5000 m
20 km
Meso/macro
1–200 m
100–2000 m
5000 m
20 km
Meso/macro
1–200 m
100–2000 m
5000 m
20 km
Meso/macro
2–1000 m
100–2000 m
5000 m
5 km
Meso
0.5–1 m
5–1000 m
300 m
100s of km
Meso
0.5–1 m
5–1000 m
1000 m
10 km
Meso
0.5–1 m
5–1000 m
300 m
100s of km
Meso
0.01–1 m
5–1000 m
200 m
100s of km
Meso
0.1–1 m
5–1000 m
200 m
10 km
Meso/macro
0.5–1 m
5–1000 m
100 m
10 km
Meso/macro
0.5–1 m
1–1000 m
800 m
100s of km
Meso/macro
0.5–1 m
1–1000 m
1000 m
100s of km
Meso/macro
10 m
5–500 m
500 m
100s of km
Electronic optical or acoustical systems Electronic High resolution in the plankton-counter horizontal/vertical plane In situ silhouette High resolution in the camera net system horizontal/vertical plane Optical plankton counter High resolution in the horizontal/vertical plane Video plankton recorder High resolution in the horizontal/vertical plane Ichthyoplankton recorder High resolution in the horizontal/vertical plane Multifrequency acoustic High resolution in the profiler system horizontal/vertical plane Dual-beam acoustic High resolution in the profiler horizontal/vertical plane Split-beam acoustic High resolution in the profiler horizontal/vertical plane ADCP High resolution in the horizontal/vertical plane
Most vertical nets are hauled at a speed of 0.5–1 m s1. Normal speed for horizontal tows are B2 knots (1 m s1) and for high-speed samplers B5 knots (2.6 m s1). For further categorization of pumping systems which are used by a number of investigators, reference is made to the review paper by Miller and Judkins (1981). (Reproduced with permission from Sameoto D, Wiebe P, Runge S, et al. (2000) Collecting zooplankton. In: Harris R, Wiebe P, Lenz J, Skjoldal HR, and Huntley M (eds.) ICES Zooplankton Methodology Manual, pp. 55–81. New York: Academic Press.)
to develop devices that closed or opened and closed nets at depth. Most employed mechanical release devices which were attached to the towing wire and activated by messengers traveling down the towing wire. The single-messenger Nansen closing mechanism and its variants were very popular during most of early to mid-twentieth century (Figure 2). Doublemessenger systems that opened and then closed a net
quickly followed. In the mid-1930s, the Leavitt net system became popular and variants of this system are still being used today (Figure 2B). Another popular system still in use today is the Clarke and Bumpus sampler, a two-messenger zooplankton collection system that can be deployed as multiple units on the wire and has a positive means of opening and closing the mouth of the net (Figure 2C).
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Fig. 2. The net closed, as it is hauled up.
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Figure 2 Some commonly used simple opening/closing nets. (A) The single-messenger Nansen closing net. (Reproduced with permission from Nansen, 1915.) (B) The two-messenger Leavitt net. (Reproduced with permission from Leavitt, 1935.) (C) The twomessenger Clarke-Bumpus net. (Reproduced with permission from Clarke and Bumpus, 1939.) The plankton purse seine (D) represents an unusual way to collect plankton from a specific region. (Reproduced with permission from Murphy and Clutter, 1972.)
Mechanical tripping mechanisms activated by pressure, by combinations of messengers and flowmeter revolutions, or clocks have also been devised. Nontraditional approaches to collecting plankton include designs to catch plankton on the downward
fall of the net rather than the reverse – so-called pop-down nets; to sample under sea ice using the English umbrella net; to sample plankton from several depths simultaneously, using a combination of nets and a pumping system; to sample plankton from the nuclear submarine, SSN Seadragon; to open and
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
close a Tucker-style trawl using two towing cables, one for the top spreader bar and one for the bottom, with each cable going to a separate winch; and to capture plankton and fish larvae with a plankton purse seine (Figure 2D). High-speed Samplers
Most of the net systems described above were towed at speeds o3 knots (150 cm s1). High-speed samplers typically towed at speeds of 3–8 knots (150– 400 cm s1) were also developed in the late 1800s and early 1900s to sample in bad weather, for underway sampling between stations, or to reduce the effects of net avoidance by the larger zooplankton. The Hardy plankton indicator, developed in the 1920s, was the first widely used device. The original version was 17.8 cm in diameter and 91.4 cm in length with a circular filtering disk on which plankton were collected. It was subsequently modified (and renamed the standard plankton indicator) to make it smaller, more streamlined, and equipped with a depressor and stabilizing fins (Figure 3). An even smaller version, the Small Plankton Sampler, was developed. In the 1950s, it was further modified and named the Small Plankton Indicator, and in the 1960s, it was modified again so that multiple units could be used on the towing wire at speeds of 7–8 knots with a multiplane kit otter depressor at the end of the wire. Until the 1950s, only one high-speed collector was designed with a double-messenger system that enabled the mouth to be opened and closed; most could not make depth-specific collections. The ‘Gulf’ series of high-speed samplers developed in the 1950s and early 1960s gave rise to a number of high-speed samplers still in use today. The first was the Gulf I-A which looked similar to earlier highspeed samplers. The Gulf III was a much larger highspeed sampler that was enclosed in a metal case. The Gulf V was an unencased and scaled-down version of the Gulf III (Figure 3B). The Gulf III and Gulf V samplers have been very popular, and have been modified numerous times. In the early 1960s, a fivebucket cod-end sampling device was added to the Gulf III that was electrically activated from a deck unit through two-conductor cable. HAI (shark) was the German version of the Gulf III built in the mid1960s. A hemispherical nose cone and an opening/ closing lid were added to the HAI. This German system evolved further when ‘Nackthai’ (naked shark), a modified Gulf V sampler, was developed in the late 1960s. Also in the 1960s, the British modified the Gulf III sampler, which was subsequently called the Lowestoft sampler (Figure 3C). Subsequently, the Lowestoft sampler was scaled down
359
and made opened bodied; hence it became a modified Gulf V. The Ministry of Agriculture, Fisheries and Food MAFF/Guildline high-speed samplers, developed in the 1980s, were also modified Lowestoft samplers. These systems have a Guildline CTD sensor unit with oxygen, pH, and digital flowmeter as additional probes with telemetry through a conducting cable. Recently in the 1990s, the Gulf VII/ Pro net and MAFF/Guildline high-speed samplers were developed that are routinely towed at 5–7 knots. Other high-speed samplers were developed during the 1950s and 1960s, including a high-speed plankton sampler which could collect a series of samples during a tow; the ‘Bary Catcher’ that had an opening/ closing mechanism in the mouth of the sampler (Figure 3D); a vertical high-speed sampler with a rectangular mouth opening that could be closed using the Juday method; an automatic high-speed plankton sampler with 21 small nets that were sequentially closed by means of a cam/screw assembly driven by a ships log (propellor); and the Clarke Jet net that was an encased high-speed sampler with an elaborate internal passageway designed to reduce the flow speed of water within the sampler to that normally experienced by a slowly towed net. The continuous plankton recorder (CPR) is in a class by itself when it comes to high-speed plankton samplers, because it can take many samples and can be towed from commercial ships (Figure 3E). Originally built in the 1920s, it has evolved over the years to become the mainstay in a plankton survey program in the North Atlantic. This encased sampler weight 87 kg and is about 50 cm wide by 50 cm tall by 100 cm long. The 1.27 cm 1.27 cm rectangular aperture expands into a larger tunnel opening. The tunnel passes through the lower portion of the sampler and out of the back. Below the tunnel is one spool of silk gauze which threads across the tunnel and captures the plankton. A second spool of silk gauze lies above the tunnel and is threaded to meet the first gauze strip as it leaves the tunnel, sandwiching the plankton between the two strips. The gauze strips are wound up on a take-up spool which resides in a formalin-filled tank above the flowthrough tunnel, preserving the plankton. The take-up spool is driven by a propellor on the back of the sampler behind the tail fins. This sampler is usually towed at 20 knots from commercial transport vessels at a fixed depth of about 10 m below the surface, thus it only samples the surface layer of the ocean. The undulating oceanographic recorder (UOR) was developed in the 1970s to extend the vertical sampling capability of high-speed plankton collection systems. The UOR carries sensors to measure
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
(B)
(A)
(C)
(D)
5
6
7
(E)
Figure 3 Some examples of high-speed plankton samplers. (A) The standard plankton indicator. (Reproduced with permission from Hardy, 1936.) (B) The encased Gulf III sampler. (Reproduced with permission from Gehringer, 1952.) (C) The open-bodied Lowestoft sampler (Gulf V type). (Reproduced with permission from Lockwood, 1974.) (D) The Bary catcher. (Reproduced with permission from Bary, 1958.) (E) The continuous plankton recorder (CPR). (Reproduced with permission from Hardy, 1936.)
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
361
temperature, salinity, and pressure; data are logged internally at 30 observations per minute. A propellor drives the rollers winding up the gauze and provides the power for the electronics. Neuston Samplers
Nets to collect neuston, the zooplankton that live within a few centimeters of the sea surface, by-andlarge are non-opening/closing. The first net specifically designed to sample zooplankton neuston was built in about 1960. A rectangular mouth opening design is typical of most of the systems. Neuston nets come either with a single net which collects animals right at the water surface or vertically stacked sets of two to six nets extending from the surface to about 100 cm depth (Figure 4). Normally they are towed from a vessel, but a ‘push-net’ was developed in the 1970s with a pair of rectangular nets positioned sideby-side in a framework and mounted in front of a small catamaran boat that pushed the frame through the water at B2.6 knots.
(A) p
af
e
h
bb
The ocean bottom is also special habitat structure for zooplankton, and gear to sample zooplankton living here (‘planktobenthos’) was developed early. The first nets were designed in the 1890s specifically to sample plankton living very near the bottom. Nonopening/closing systems were succeeded by samplers with mechanically operated opening/closing doors or with a self-closing device (Figure 5A). An entirely different strategy has been to employ manned submersibles or deep-towed vehicles to collect deep-sea planktobenthos. A pair of nets mounted on the front of DSRV Alvin was used for making net collections at depths 41000 m in the 1970s; the pilot opened and closed the net (Figure 5B). A multiple net system was used on the Deep-Tow towed body. This system was attached to the bottom of the Deep-Tow and used for sampling within a few tens of meters above the deep-sea floor in the 1980s (Figure 5C). This net system was later adapted for use on DSRV Alvin for near-bottom studies of plankton in the vicinity of hydrothermal vent sites in the 1990s. On other benthic habitats, such as coral reefs, fixed or stationary net systems which orient to the current’s flow and filter out zooplankton drifting by, nets pushed by divers, and traps have been used to capture plankton close to the bottom. The Horizontal Plankton Sampler (HOPLASA) creates its own current to collect zooplankton on or near the bottom in coral reef areas with variable or little current flow (Figure 5D).
10 10 20
b c2
Planktobenthos Plankton Nets
20
20
n c1 ac
20 e
(B)
25
Detail A
Detail B
(C)
Figure 4 Neuston net samplers collect plankton living at the sea surface. (A) A single net system. (Reproduced with permission from David, 1965.) (B) A multinet system. (Reproduced with permission from Ellertsen, 1977.) (C) A push net. (Reproduced with permission from Miller, 1973.)
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362
ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
(A)
(B)
(D)
(C)
Figure 5 Some planktobenthos samplers. (A) Early system with opening/closing doors. (Reproduced with permission from Wickstead, 1953.) (B) DSR Alvin opening/closing system. (Reproduced with permission from Grice, 1972.) (C) The Deep-Tow multiple net system. (Reproduced with permission from Wishner, 1980.) (D) A system for coral reef sampling (HOPLASA). (Reproduced with permission from Rutzler, 1980.)
Closing Cod-end Systems
In the late 1950s and 1960s, conducting cables and transistorized electronics were beginning to be adapted for oceanographic use and sophisticated net
systems began to do more than collect animals at specific depth intervals. Single nets equipped with closing cod-end devices preceded multiple net systems by only a few years. One of the first systems
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364
ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
distributions of animals and losses of animals from the recorder box. The modified LHPR was used without a net on the conning-tower of the US Navy research submarine Dolphin in the 1980s. Another modification of the LHPR was made by the British in 1980s. They used an unenclosed Lowestoft sampler to mount a pair of recorder boxes to collect mesoand micro-zooplankton. The system acoustically telemetered depth, flow, and temperature. It also carried a chlorophyll sensor with a recorder system. The LHPR was further modified for use in catching Antarctic krill. A descendant of the LHPR developed in the 1990s is the Autosampling and Recording Instrumental Environmental Sampler (ARIES) (Figure 6C). This cod-end plankton sampling device is a stretched version of the Lowestoft-modified Gull III frame. It has a multiple cod-end system, water sampler, data logger, and an acoustical telemetry system. Multiple Net Systems
The development of multiple net systems began with the simple non-opening/closing Tucker trawl system. In the mid-1960s, timing clocks were used to open and close the Tucker trawl mouth. Then late in the 1960s, the British rectangular mouth opening trawl (RMT), which was opened and closed acoustically, was developed. The RMT was expanded into the NIO Combination Net (RMT 1 þ 8), which carries nets with 1 m2 and 8 m2 mouth openings (Figure 7A). This was expanded into a multiple net system with three sets of 1 m and 8 m nets controlled acoustically. The acoustic command and telemetry system for the RMT 1 þ 8 was replaced in the 1990s by a microcomputer-controlled unit connected by conducting cable to an underwater electronics unit. In a parallel development in the 1970s, a five-net and a nine-net Tucker Multiple Net Trawl was developed on the West Coast of the USA. The system was powered electrically through conducting wire and controlled from the surface. A modified Tucker trawl system, the Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS), with nine nets and a rigid mouth opening was built soon after on the US east coast (Figure 7E). The current versions of the MOCNESS are computer-controlled (Table 2). Sensors include pressure, temperature, conductivity, fluorometer, transmissometer, oxygen, and light. The design of the Be´ multiple plankton sampler (MPS) (Figure 7B), initially messenger operated in the late 1950s and then pressure-actuated in the 1960s, was the basis for the Bedford Institute of Oceanography Net and Environmental Sensing
System (BIONESS), with 10 nets, developed in the 1980s (Figure 7D). A modified version of the MPS was developed in Germany at about the same time and named the Multinet; it carried five nets, which were opened and closed electronically via conducting cable (Figure 7C). A scaled-up version of BIONESS built in the 1990s was the Large Opening Closing High Speed Net and Environmental Sampling System (LOCHNESS). Another variant of the MPS was the Ocean Research Institute’s (Japan) vertical multiple plankton sampler developed in the 1990s in which the nets are opened/closed by surface commands transmitted via conducting cable to an underwater unit. Moored Plankton Collection Systems
Only a few instrument systems have been developed that autonomously collect time-series samples of plankton from moorings. Most were patterned after the CPR or LHPR (e.g. the O’Hara automatic plankton sampler built in the 1980s; a modified version of the O’Hara system built in the 1990s; the moored, automated, serial zooplankton pump (MASZP) built in the late 1980s) (Figure 8). The lack of such systems may be due to the difficulty of powering them for long periods underwater.
Optical Systems Optical survey instruments can be divided into two categories, based on whether the systems produce an image of their zooplankton targets (e.g. video, photographic, and digital camera systems) or use the interruption of a light source to detect and estimate the size of particles (e.g. the optical plankton counter). The first attempts to quantify plankton optically appear to have been made in the 1950s using a beam of light projected into the chamber from a 300 W mercury vapor lamp and a Focabell camera (Orion Camera, Tokyo). Image-forming Systems Mounted on Non-opening/ Closing Nets
In the 1980s, a 35 mm still camera with a highcapacity film magazine in front of the cod-end of a plankton net attached to a rigid frame was used to take in situ silhouette photographs of zooplankton as they passed into the cod-end. This was a field application of the laboratory-based silhouette photography system developed in the late 1970s. The camera provided a series of photographic images at points along the trajectory of the net separated by o1 m. In the development of the ichthyoplankton recorder, the still camera was replaced with a video
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
(B)
(A)
365
(C)
Net Monitor Bar 1 Closing Bar (6) RMT 1 Opening Bar (7) Bar 2
Closing Bar (3) RMT 2 Opening Bar (4)
Bar 5
(E)
(D)
Figure 7 Some examples of multiple net plankton sampling systems. (A) The RMT 1 þ 8. (Reproduced with permission from Baker, 1973.) (B) The Be´ net. (Reproduced with permission from Be´, 1959.) (C) The Multinet. (Photograph courtesy of B. Niehof.) (D) The BIONESS. (Photograph courtesy of P. Wiebe, 1993.) (E) The 1 m2 MOCNESS. (Photograph courtesy of Wiebe, 1998.)
camera, which was located in front of the cod-end of a high-speed Gulf V-type net (Nackthai). It had an estimated horizontal spatial resolution of 3 cm. One consequence of going from camera film to video tape was a loss of image resolution. Stand-alone Image-forming Systems
The video plankton recorder (VPR) was developed in the early 1990s as a towed instrument capable of
imaging zooplankton within a defined volume of water (Figure 9A). The original VPR had four video cameras; each camera imaged concentrically located volumes of water ranging from 1 ml to 1000 ml, but it has been modified to a one- or two-camera system. It has been possible to image undisturbed animals in their natural orientations. The current VPR image processing system is capable of digitizing each video field in real time and scanning the fields for targets using user-defined search criteria for
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
Table 2
MOCNESS system dimensions and weights
System
Number of nets
Width of frame (m)
Height of frame (m)
Net width (m)
Mouth area Length of at 451 net (m) towing angle (m)
Approx. weight in air (kg)
Rec. wire diameter (mm)
MOCNESS-1/4 MOCNESS-1/4Double MOCNESS-1 MOCNESS-1-Double MOCNESS-2 MOCNESS-4 MOCNESS-10 MOCNESS-20
9 18/20
0.838 1.430
1.430 1.430
0.50 0.50
0.5 0.5
6.00 6.00
70 155
6.4 7.4
9 18/20 9 6 6 6
1.240 2.560 1.650 2.140 3.410 5.500
2.870 2.870 3.150 4.080 4.690 7.300
1.00 1.00 1.41 2.00 3.17 4.47
1.0 1.0 2.0 4.0 10.0 20.0
6.00 6.00 6.00 8.44 18.25 14.50
150 320 210 460 640 940
7.4 12.1 11.8 11.8 11.8 17.3
The MOCNESS systems are denoted by the mouth area when being towed. Thus a MOCNESS-1/4 has a 0.25 m2 mouth opening. The ‘Double’ systems have two sets of nets side-by-side in a single rigid framework. Nets can be opened and closed on one side and then opened and closed on the other.
brightness, focus, and size. The targets are identified using a zooplankton identification program to provide near-real-time maps of the zooplankton distributions. A number of VPR-based systems are currently in operation or under development: a single-camera system is mounted on the BIOMAPER II vehicle (described below); an internally recording VPR has been constructed and used to quantify radiolarians
Sampler unit
and foraminiferans; and one has been mounted on a 1 m2 MOCNESS net system to map the fine-scale distributions of the larval cod prey items. A moored system called the Autonomous Vertically Profiling Plankton Observatory (AVPPO) utilizes an internally recording, two-camera VPR, and has been deployed in coastal waters off New England. Image resolution constraints inherent in the use of standard video formats have driven the development
Flow generation & measurement unit
Time- or event-triggered automated, serial, plankton pump
Rubber hose connection Flow meter
Outboard motor
Intake 0 Control unit & pressure case
20
40
Supply spool
Centimetres Net storage reel Chafing rail Hall effect mechanism
Net storage chamber
Take-up spool Fixable bath
Collection net
Inlet Wind motor Filling tube housing
Preservative chamber
Takeup reel
Pump
Outlet
Drain plug
Carriage chassis Front view
Sampler unit
0
10
Motor
20
Centimetres Side view
(A)
(B)
Figure 8 Two examples of moored plankton collecting systems. (A) A modified version of the O’Hara sampler. (Reproduced with permission from Lewis and Heckl, 1991.) (B) MASZP. (Reproduced with permission from Doherty et al. 1993.)
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
367
(A)
(B)
(C)
Figure 9 Examples of optical or electrical systems for collecting zooplankton data. (A) The VPR. (Photograph courtesy of P. Alatalo, 1999.) (B) The in-situ zooplankton detecting device. (Photograph courtesy of P. Wiebe, c. 1972.) (C) The optical plankton counter (OPC). (Photograph courtesy of M. Zhou, 2000.)
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368
ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
of optical systems that utilizes higher-resolution formats. A modification of the continuous underway fish egg sampler (CUFES, described below) utilizes a line-scanning digital camera to quantify the abundances of fish eggs. The shadowed image particle profiling and evaluation recorder (SIPPER) utilizes high-resolution digital line-scanning cameras to quantify zooplankton passing through a laser light sheet. The SIPPER has been mounted either on a towed vehicle called the high-resolution sampler (HRS) or an AUV. The need for systems to quantify the abundance of ‘marine snow’ prompted development of profiling systems based on both still and video cameras. In the 1980s, a profiling system called the large amorphous aggregates (LAA) camera was constructed which employed a photographic camera and a pair of strobes to photograph marine aggregates. A video profiling instrument called the underwater video profiler (UVP) has been used to quantify the vertical distribution and size frequency of marine snow, and to examine the distributions of macrozooplankton. The UVP consists of a Hi-8 video camera imaging a collimated light sheet coupled with a CTD, data logger, and batteries. A profiling system called ZOOVIS recently has been developed around a high resolution (2048 2048 pixel) digital camera and CTD linked to a surface workstation via a fiber-optic cable. A color video camera has been mounted on the front of a Sea Owl II remotely operated vehicle (ROV) and used to quantify the vertical distribution of gelatinous zooplankton off the west coast of Sweden. Still holographic imaging of plankton in a laboratory was first reported in 1966. It was refined in the 1970s to record movies of live plankton in the laboratory. In the 1990s, a submersible internally recording in-line holographic camera that records up to 300 holograms on a film emulsion was developed. Many zooplankton produce or induce the production of bioluminescent light that can be detected with sensitive CCD cameras. One system is mounted on the Johnson SeaLink manned submersible and consists of an intensified silicon-intensified target (ISIT) video camera mounted on and aimed forward at a 1 m diameter transect screen to quantify the distribution, abundance, and identities of bioluminescent zooplankton. Particle Detection Systems
Particle detection systems refer to non-imageforming devices that utilize interruption of an electrical current or a light beam to detect and estimate the size of a passing particle. The first in situ particle counting and sizing system appeared in the late
1960s and was referred to as the in situ zooplankton detecting device (Figure 9B). A shipboard version of the device was connected to a continuously pumped stream of water and employed to analyze spatial heterogeneity of zooplankton in surface waters in relation to chlorophyll fluorescence and temperature. A version of this conductive zooplankton counter was deployed aboard a Batfish towed vehicle in the 1980s. A second group of particle detectors utilized photodetectors rather than changes in voltage. The Opto-Electronic Plankton Sizer was a laboratorybased system designed in the 1970s to automate the measurement of preserved plankton samples. The HIAC particle size analyzer was modified at the Lowestoft Laboratory during the late 1970s for plankton counting. The optical plankton counter (OPC) was developed during the mid-1980s (Figure 9C). This instrument measures changes in the intensity of a light beam that occur when a particle crosses the beam. The OPC has been mounted on a variety of towed platforms or in shore-based or shipboard applications. The OPC has also been incorporated into a shipboard device called the continuous underway fish egg sampling system (CUFES) which enumerates the distribution and abundance of fish eggs in surface waters. In spite of the prevalence of OPC systems in current use, interpretation of OPC data remains a subject of some controversy.
Optical Instruments for Nonquantitative Studies
The ecoSCOPE is an optical video-endoscope that enables direct observation of predator–prey interactions between juvenile fish and zooplankton. The ecoSCOPE has been operated from an ROV, from the keel of a sailing vessel, and in towed and moored modes, but the best recordings of predator/prey interactions have come from free-drifting deployments, when the instrument was hovering within schools of feeding juvenile herring. A software package called dynIMAGE animates sequential images keeping the fish and its prey in the middle of the viewing field. Optical sensors can provide valuable groundtruthing for acoustical sensors. In the 1990s, a megapixel digital still camera was mounted on a FishTV sonar array and the resulting system was named the Optical-Acoustical Submersible Imaging System (OASIS). In this system, high acoustic returns are used to trigger the camera taking a picture of the acoustical target. An analog video camera aimed at the focal point of an acoustic array mounted on the front of a MAXRover ROV has been used to take
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
pictures of individual zooplankton passing through the acoustic beam.
High-frequency Acoustics High-frequency acoustics (Z38–1000 kHz) provide the foundation for another class of tools to study zooplankton. The utility of the acoustic systems derives from their ability to operate with high ping rates and precision range-gating. Mapping planktonic distributions on a wide range of space and timescales is becoming possible because of the continued development of acoustics systems and appropriate groundtruthing methods. There are two fundamental measurements: volume backscattering (integration of the energy return from all individuals in a given ensonified volume, i.e. echo integration) and target strength (echo strength from an individual). Statistical procedures have been developed to estimate animal assemblage size distribution using the data from singlebeam transducers. In some cases, it is possible to extract estimates of animal target strength distribution in addition to volume backscattering from a series of single-beam transducers operating at different frequencies. Multi-beam acoustical systems provide a direct means of determining individual target strength (TS). The two current designs, dual-beam and splitbeam, both provide a hardware solution to the problem of TS determination.
The Current State of Plankton Sampling Systems The diversity of zooplankton samplers in use today reflects the fact that no single collection system adequately samples all zooplankton. Non-opening/ closing nets, such as the WP2, the modified Juday net, and the Bongo net, are used in large ocean surveys. Simple, double-messenger opening/closing nets similar to those developed in the first half of the last century are still manufactured and used. The Multinet, RMT 1 þ 8, BIONESS, and MOCNESS are widely used multiple-net systems that also carry additional sensors to measure other water properties. Plankton pumps are also being used, especially to collect micro-zooplankton. The advent of high-speed computers and towing cables with optical fibers and electrical conductors have enabled development of multi-sensor towed systems which provide real-time data while the instrument package is deployed. The MOCNESS has been equipped with a high-frequency acoustic system for forward or sideways range-gated viewing (Figure 10A). An EG&G Edgerton model 205
369
camera and aflash light were mounted on the top of a modified MOCNESS and on the top of BIONESS to take black and white photographs about 2 m in front of the net mouth. The BIONESS has also been equipped with an OPC and video lighting system, and used in conjunction with an echosounder. The BIo-Optical Multi-frequency Acoustical and Physical Environmental Recorder – BIOMAPER II – was developed to conduct high-speed, large-area surveys of zooplankton and environmental property distributions to depths of 500 m (Figure 10B). Mounted inside are a multi-frequency sonar (upwards-looking and downwards-looking pairs of transducers operating at five frequencies: 43, 120, 200, 420, and 1000 kHz), an environmental sensor package (CTD, fluorometer, transmissometer), and several other bio-optical sensors (down- and upwelling spectral radiometers, spectrally matched attenuation, and absorption meters). A single-camera video plankton recorder (VPR) system is mounted above and just forward of the nose piece. The lower four acoustical frequencies involve split-beam technology and are able to make target strength and echo integration measurements. A variety of vehicles have been built that actively change their vertical position without changing the towing wire length. Examples for surveying zooplankton include the undulating oceanographic recorder and SeaSoar equipped with optical (VPR and OPC) and/or acoustical (the Tracor Acoustical Profiling System, TAPS). Remotely operated vehicles (ROVs) have also been equipped with acoustical and video systems to study zooplankton. A SeaRover ROV was equipped with the same dual-beam acoustic system and environmental sensors. A VPR rigged to provide 3-D images of plankton and an environmental sensor package (temperature, conductivity, pressure, fluorescence) were mounted on the front of the ROV JASON and on the SeaRover ROV (Figure 10C). FishTV (FTV) has been used on a Phantom IV ROV and a combination of acoustics and video has been used on the front of a MAXRover ROV. Dual-beam acoustics (420 and 1000 kHz) have also been deployed on the DSRV Johnson SeaLink.
Future Developments The future promises vastly increased application of remote sensing techniques and sensor development, and real-time data telemetry, processing, and display. Three-dimensional (space) and four-dimensional visualization (space and time) of biological and acoustic data are also an increasingly important aspect of data processing. For a number of research
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370
ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
(A)
(B)
(C)
Figure 10 Examples of multi-sensor plankton sampling systems. (A) MOCNESS with a dual-beam acoustic system. (Photograph courtesy of P. Wiebe, 1994.) (B) BIOMAPER-II. (Photograph courtesy of P. Wiebe, 1999.) (C) The JASON-ROV with 3-D VPR system. (Photograph courtesy of P.Alatalo, 1995.)
programs today, the development of an image of the spatial arrangement of organisms is but the first step in efforts to study and understand their relationships to each other and to their environment. Thus, there is need for real-time 3-D and 4-D images. Autonomous self-propelled vehicles (AUVs) have only recently begun to be used widely to gatheroceanographic data. The remote environmental measuring units (REMUS) are a new class of small AUVs which can carry an impressive array of environmental sensors including a VPR. Another class of autonomous vehicles is epitomized by the autonomous benthic explorer (ABE), which is equipped with precise navigation and control systems that enable it to descend to a worksite, navigate preset tracklines or terrain-follow, and find a docking station. A much larger AUV which has been employed for biological studies is the Autosub-1 that carries a gyrocompass, ADCP, an echosounder, and acoustic
telemetry and surface radio electronics. It can be programmed to run a geographically based course using GPS surface positions and dead reckoning. The autonomous Lagrangian circulation explorer (ALACE) and the more recently developed profiling version (PALACE) floats that carry temperature and conductivity probes are vertically migrating neutrally buoyant drifters. They track the movements of water at depths between the surface and 1000–2000 m depth. Hundreds to thousands of the PALACE floats will be deployed over the next few years and it is expected that they will become a mainstay in the Global Ocean Observing System (GOOS). The next generation of neutrally buoyant floats is an autonomous glider named SPRAY. SPRAY will be able to sail along specific preprogrammed tracklines. A further step in their development is to provide biological instrumentation to complement the physical sensors.
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ZOOPLANKTON SAMPLING WITH NETS AND TRAWLS
High-resolution optical systems, suchas the VPR, combined with computer-based identification programs can now provide higher level taxa identifications in near-real time. Classification of species using acoustic signatures is less well developed and it now seems unlikely that the technology to develop speciesspecific acoustic signatures will be developed soon. Molecularly based species identification is likely to make significant strides in the next decade. It is now conceivable that this information will enable simultaneous analysis, identification, and quantification of all species occurring in a zooplankton sample.
See also Acoustic Scattering by Marine Organisms. Continuous Plankton Recorders. Grabs for Shelf Benthic Sampling. Marine Snow. Plankton. Platforms: Autonomous Underwater Vehicles. Satellite Remote Sensing SAR. Sea Ice. Sea Ice: Overview.
371
Further Reading Harris RP, Wiebe PH, Lenz J, Skjoldal HR, and Huntley M (eds.) (2000) ICES Zooplankton Methodology Manual. New York: Academic Press. Kofoid CA (1991) On a self-closing plankton net for horizontal towing. University of California Publications in Zoology 8: 312--340. Miller CB and Judkins DC (1981) Design of pumping systems for sampling zooplankton with descriptions of two high-capacity samplers for coastal studies. Biol Oceanogr 1: 29--56. Omori M and Ikeda Y (1976) Methods in Marine Zooplankton Ecology. New York: John Wiley & Sons. Schulze PC, Strickler JR, Bergstro¨m BI, et al. (1992) Video systems for in situ studies of zooplankton. Arch Hydrobiol Beih Ergebn Limnol 36: 1--21. Sprules WG, Bergstro¨m B, Cyr H, et al. (1992) Non-video optical instruments for studying zooplankton distribution and abundance. Arch Hydrobiol Beih Ergebn Limnol 36: 45--58. Tranter DJ (ed.) (1968) Part I. Reviews on Zooplankton Sampling Methods. Monographs on Oceanographic Methodology, Zooplankton Sampling. UNESCO
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APPENDIX 1. SI UNITS AND SOME EQUIVALENCES Wherever possible the units used are those of the International System of Units (SI). Other ‘‘conventional’’ units (such as the liter or calorie) are frequently used, especially in reporting data from earlier work. Recommendations on standardized scientific terminology and units are published periodically by international committees, but adherence to these remains poor in practice. Conversion between units often requires great care.
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APPENDIX 1. SI UNITS AND SOME EQUIVALENCES
SI base units and derived units may be used with multiplying prefixes (with the exception of kg, though prefixes may be applied to gram ¼ 103kg; for example, 1 Mg ¼ 106 g ¼ 106kg)
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APPENDIX 1. SI UNITS AND SOME EQUIVALENCES
375
The SI units for pressure is the pascal (1 Pa ¼ 1 N m2). Although the bar (1 bar ¼ 105 Pa) is also retained for the time being, it does not belong to the SI system. Various texts and scientific papers still refer to gas pressure in units of the torr (symbol: Torr), the bar, the conventional millimetre of mercury (symbol: mmHg), atmospheres (symbol: atm), and pounds per square inch (symbol: psi) – although these units will gradually disappear (see Conversions between Pressure Units). Irradiance is also measured in W m2. Note: 1 mol photons ¼ 6.02 1023 photons. The SI unit used for the amount of substance is the mole (symbol: mol), and for volume the SI unit is the cubic metre (symbol: m3). It is technically correct, therefore, to refer to concentration in units of molm3. However, because of the volumetric change that sea water experiences with depth, marine chemists prefer to express sea water concentrations in molal units, mol kg1.
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APPENDIX 2. USEFUL VALUES
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APPENDIX 3. PERIODIC TABLE OF THE ELEMENTS
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Elsevier Ltd
APPENDIX 4. THE GEOLOGIC TIME SCALE
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APPENDIX 5. PROPERTIES OF SEAWATER A5.1
The Equation of State
It is necessary to know the equation of state for the ocean very accurately to determine stability properties, particularly in the deep ocean. The equation of state defined by the Joint Panel on Oceanographic Tables and Standards fits available measurements with a standard error of 3.5 ppm for pressure up to 1000 bar, for temperatures between freezing and 40 1C, and for salinities between 0 and 42. The density r (kg m 3) is expressed in terms of pressure p (bar), temperature t (1C), and practical salinity S. The last quantity is defined in such a way that its value (in practical salinity units or psu) is very close to the old value expressed in parts per thousand (% or ppt). Its relation to previously defined measures of salinity is given by Lewis and Perkin. The equation for r is obtained in a sequence of steps. First, the density rw of pure water (S ¼ 0) is given by
The value at one standard atmosphere (p ¼ 0) is given by KðS; t; 0Þ ¼ Kw þ Sð54:674 6 0:603 459t þ 1:099 87 102 t2 6:167 0 105 t3 Þ þ S3=2 ð7:944 102 þ 1:648 3 102 t 5:300 9 104 t2 Þ and the value at pressure p by KðS; t; pÞ ¼ KðS; t; 0Þ þ pð3:239 908 þ 1:437 13 103 t þ 1:160 92 104 t2 5:779 05 107 t3 Þ þ pSð2:283 8 103 1:098 1 105 t 1:607 8 106 t2 Þ þ 1:910 75 104 pS3=2
rw ¼ 999:842 594 þ 6:793 952 102 t
þ p2 ð8:509 35 105 6:122 93
9:095 290 103 t2 þ 1:001 685 104 t3
106 t þ 5:278 7 108 t2 Þ
6 4
þ p2 Sð9:934 8 107 þ 2:081 6
1:120 083 10 t
9 5
þ 6:536 332 10 t
rðS; t; 0Þ ¼ rw þ Sð0:824 493 4:089 9 103 t þ 7:643 8 105 t2 8:246 7 107 t3 þ 5:387 5 109 t4 Þ þ S3=2 ð5:724 66 103 þ 1:022 7 104 t 1:654 6 106 t2 Þ þ 4:831 4 104 S2
½A5:2
Finally, the density at pressure p is given by rðS; t; 0Þ 1 p=KðS; t; pÞ
½A5:3
where K is the secant bulk modulus. The pure water value Kw is given by Kw ¼ 19 652:21 þ 148:420 6t 2:327 105t2 2 3
þ 1:360 477 10 t 5:155 288 105 t4
108 t þ 9:169 7 1010 t2 Þ
½A5:1
Second, the density at one standard atmosphere (effectively p ¼ 0) is given by
rðS; t; pÞ ¼
½A5:5
½A5:4
½A5:6
Values for checking the formula are r(0, 5, 0) ¼ 999.966 75, r(35, 5, 0) ¼ 1027.675 47, and r(35, 25, 1000) ¼ 1062.538 17. Since r is always close to 1000 kg m 3, values quoted are usually those of the difference (r 1000) in kg m 3 as is done in Table A5.1. The table is constructed so that values can be calculated for 98% of the ocean (see Figure A5.1). The maximum errors in density on straight linear interpolation are 0.013 kg m 3 for both temperature and pressure interpolation and only 0.006 for salinity interpolation in the range of salinities between 30 and 40. The error when combining all types of interpolation for the 98% range of values is less than 0.03 kg m 3.
A5.2
Other Quantities Related to Density
Older versions of the equation of state usually gave formulas not for calculating the absolute density r, but for the ‘specific gravity’ r/rm, where rm is the maximum density of pure water. Since this is always
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S
35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35
p (bar)
0 0 0 0 0 0 0 0 0 0 0 0 0 100 100 100 100 100 100 100 100 100 200 200 200 200 200 300 300 300 300 400 400 400 400 500 500 500 600 600 600
Table A5.1
r 1000 (kg m 3)
28.187 28.106 27.972 27.786 27.419 26.952 26.394 25.748 25.022 24.219 23.343 22.397 21.384 32.958 32.818 32.629 32.393 31.958 31.431 30.818 30.126 29.359 37.626 37.429 37.187 36.903 36.402 42.191 41.941 41.649 41.319 46.658 46.356 46.017 45.643 51.029 50.678 50.293 55.305 54.908 54.481
t (1C)
2 0 2 4 7 10 13 16 19 22 25 28 31 2 0 2 4 7 10 13 16 19 2 0 2 4 7 2 0 2 4 2 0 2 4 2 !0 2 2 0 2 0.814 0.808 0.801 0.796 0.788 0.781 0.775 0.769 0.764 0.760 0.756 0.752 0.749 0.805 0.799 0.793 0.788 0.781 0.774 0.769 0.763 0.759 0.797 0.791 0.786 0.781 0.774 0.789 0.783 0.778 0.774 0.781 0.776 0.771 0.767 0.773 0.769 0.764 0.766 0.762 0.758
@r/@S
254 526 781 1021 1357 1668 1958 2230 2489 2734 2970 3196 3413 552 799 1031 1251 1559 1844 2111 2363 2603 834 1058 1269 1469 1750 1101 1303 1494 1676 1351 1534 1707 1872 1587 1751 1907 1807 1954 2094
a (10 7 K 1) 33 31 28 26 23 20 17 15 14 12 11 9 8 31 28 26 24 21 18 16 14 13 28 26 24 22 19 26 24 22 20 24 22 20 19 22 20 19 20 18 17
@a/@S
3989 3987 3985 3985 3985 3986 3988 3991 3993 3996 3998 4000 4002 3953 3953 3954 3955 3957 3960 3963 3967 3970 3922 3923 3925 3927 3931 3893 3896 3899 3903 3867 3871 3876 3880 3844 3849 3854 3824 3829 3835
cp (J kg 1 K 1) 6.2 6.1 5.9 5.8 5.6 5.5 5.3 5.2 5.1 4.9 4.9 4.8 4.7 5.8 5.7 5.6 5.5 5.3 5.2 5.1 5.0 4.9 5.5 5.4 5.3 5.2 5.1 5.2 5.1 5.0 5.0 4.9 4.8 4.8 4.7 4.7 4.6 4.6 4.4 4.4 4.4
@cp/@S
2000 0 2000 4000 7000 10 000 13 000 16 000 19 000 22 000 25 000 28 000 31 000 2029 45 1939 3923 6901 9879 12 858 15 838 18 819 2076 107 1862 3832 6789 2140 186 1771 3728 2221 279 1665 3610 2316 386 1546 2426 506 1416
y (10 31C) 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 1 1 1 1 1 3 3 3 3 3 5 5 5 5 7 6 6 6 8 8 7 9 9 9
@y/@S
1439.7 1449.1 1458.1 1466.6 1478.7 1489.8 1500.2 1509.8 1518.7 1526.8 1534.4 1541.3 1547.6 1456.1 1465.5 1474.5 1483.1 1495.1 1506.3 1516.7 1526.4 1535.3 1472.8 1482.3 1491.2 1499.8 1511.8 1489.9 1499.3 1508.2 1516.6 1507.2 1516.5 1525.3 1533.7 1524.8 1534.0 1542.7 1542.6 1551.6 1560.2
cs (m s 1)
1.37 1.34 1.31 1.29 1.25 1.22 1.19 1.16 1.13 1.10 1.08 1.06 1.03 1.38 1.35 1.33 1.30 1.26 1.22 1.19 1.16 1.13 1.39 1.36 1.33 1.30 1.26 1.39 1.36 1.33 1.30 1.39 1.36 1.33 1.30 1.38 1.35 1.32 1.37 1.34 1.31
@cs /@S
380 APPENDIX 5. PROPERTIES OF SEAWATER
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APPENDIX 5. PROPERTIES OF SEAWATER 0°
10°
20°
30°
34
36
(28.5)
30
40
24
26
28
381
30
(17.5)
50 2 km
2 km
2 km
4 km
4 km
4 km
t
S
Figure A5.1 The ranges of temperature t (in 1C) and salinity S for 98% of the ocean as a function of depth and the corresponding ranges of density s and potential density sy. From Bryan K and Cox MD (1972) An approximate equation of state for numerical models of ocean circulation. Journal of Physical Oceanography 2: 510–514.
close to unity, a quantity called s was defined by r 1000 1 ¼ ðr rm Þ 1000 rm rm
½A5:7
A5.4
Since rm ¼ 999:975 kg m3
½A5:8
it follows that s, as defined above, is related to the (r 1000) values by s ¼ ðr 1000Þ þ 0:025
d ¼ vs ðS; t; pÞ vs ð35; 0; pÞ and usually reported in units of 10
A5.3
½A5:10 3
m kg
1
.
Expansion Coefficients
The thermal expansion coefficient a is given in Table A5.1 in units of 10 7 K 1 along with its S derivative. The maximum error from pressure interpolation is 2 units, that from temperature interpolation is 3 units, and that for salinity interpolation (30oSo40) is 2 units plus a possible round-off error of 2 units.
Specific Heat
The specific heat at surface pressure is given by Millero et al. and can be calculated in two stages. First, the value in J kg 1 K 1 for fresh water is given by cp ð0; t; 0Þ ¼ 4217:4 3:720 283t þ 0:141 285 5t2 2:654 387 103 t3
½A5:9
that is, 0.025 must be added to the values of (r 1000) on the table to obtain the old s value. The notation s, (sigma tau) was used for the value of s calculated at zero pressure, and sy (sigma theta) for the quantity corresponding to potential density. Another quantity commonly used in oceanography is the specific volume (or steric) ‘anomaly’ d defined by
8
The salinity expansion coefficient b can be calculated by using the given values of qr/qS.
þ 2:093 236 105 t4
½A5:11
Second, cp ðS; t; 0Þ ¼ cp ð0; t; 0Þ þ Sð7:644 4 þ 0:107 276t 1:383 9 103 t2 Þ þ S3=2 ð0:177 09 4:077 2 103 t þ 5:353 9 105 t2 Þ
½A5:12
The formula can be checked against the result cp(40, 40, 0) ¼ 3981.050. The standard deviation of the algorithm fit is 0.074. Values at nonzero pressures can be calculated by using eqn [A5.13] and the equation of state:
@cp @p
¼ T T
@ 2 vs @T 2
½A5:13 p
The values in Table A5.1 are based on the above formula and a polynomial fit for higher pressures derived from the equation of state by N.P. Fofonoff.
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382
APPENDIX 5. PROPERTIES OF SEAWATER Potential temperature (°C/dbar) × 10−1
The intrinsic interpolation errors in the table are 0.4, 0.1, and 0.3 J kg 1 K 1 for pressure, temperature, and salinity interpolation, respectively, and there are additional obvious round-off errors.
A5.5
0
½A5:14
k pr p
150 175
5
þ 8:319 8 10 t
7 2
5:406 5 10 t þ 4:027 4 109 t3 Þ pðS 35Þð1:743 9 105 2:977 8 107 tÞ p2 ð8:930 9 107 3:162 8 108 t þ 2:198 7 1010 t2 Þ þ 4:105 7
Pressure (dbar) × 101
200 225 250 275 300 325 350 375 400 425 450
109 ðS 35Þp2 p3 ð1:605 6 1010
475
þ 5:048 4 1012 tÞ
500
½A5:16
A check value is y(25, 10, 1000) ¼ 8.467 851 6, and the standard deviation of Bryden’s polynomial fit was 0.001 K. Values in Table A5.1 are given in millidegrees, the intrinsic interpolation errors being 2, 0.3, and 0 millidegrees for pressure, temperature, and salinity interpolation, respectively (Figure A5.2).
Speed of Sound
The speed of sound cs can be calculated from the equation of state, using eqn [A5.17] c2s ¼
θz
125
½A5:15
where pr is a reference pressure level (usually 1 bar) and k ¼ (g 1)/g, where g is the ratio of specific heats at constant pressure and at constant volume, can then be used to obtain y. The following algorithm, however, was derived by Bryden, using experimental compressibility data, to give y (1C) as a function of salinity S, temperature t (1C), and pressure p (bar) for 30oSo40, 2oto30, and 0opo1000:
A5.6
10
N
100
and therefore can be calculated from the above formulas. The definition of potential temperature
yðS; t; pÞ ¼ t pð3:650 4 10
9
75
gaT cp
4
Brunt-Väisälä frequency (cph) 2 3 4 5 6 7 8
1
50
The ‘adiabatic lapse rate’ G is given by
y ¼ T
0
0.05 0.10 0.15 0.20 0.25 0.30
25
Potential Temperature
G¼
0
−0.10 −0.05
@p @r y;S
Figure A5.2 A profile of buoyancy frequency N in the ocean. From the North Atlantic near 281 N, 701 W, courtesy of Dr. R.C. Millard.
0oto40, 0opo1000 with a standard deviation of 0.19 ms 1. Values in the table are given in meters per second, the intrinsic interpolation errors being 0.05, 0.10, and 0.04 ms 1 for pressure, temperature, and salinity interpolation, respectively.
A5.7
Freezing Point of Sea Water
The freezing point tf of sea water (1C) is given by ½A5:17 tf ðS; pÞ ¼ 0:057 5S þ 1:710 523
Values given in Table A5.1 use algorithms derived by Chen and Millero on the basis of direct measurements. The formula applies for 0oSo40,
103 S3=2 2:154 996 104 S2 7:53 103 p
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½A5:18
APPENDIX 5. PROPERTIES OF SEAWATER
The formula fits measurements to an accuracy of 70.004 K.
Further Reading Bryan K and Cox MD (1972) An approximate equation of state for numerical models of ocean circulation. Journal of Physical Oceanography 2: 510--514. Bryden HL (1973) New polynomials for thermal expansion, adiabatic temperature gradient and potential temperature gradient of sea water. Deep Sea Research 20: 401--408. Chen C-T and Millero FJ (1977) Speed of sound in seawater at high pressures. Journal of the Acoustical Society of America 62: 1129--1135. Dauphinee TM (1980) Introduction to the special issue on the Practical Salinity Scale 1978. IEEE, Journal of Oceanic Engineering OE 5: 1--2. Gill AE (1982) Atmosphere–Ocean Dynamics, International Geophysics Series Volume 30. San Diego, CA: Academic Press.
383
Kraus EB (1972) Atmosphere–Ocean Interaction. London: Oxford University Press. Lewis EL and Perkin RG (1981) The Practical Salinity Scale 1978: Conversion of existing data. Deep Sea Research 28A: 307--328. Millero FJ (1978) Freezing point of seawater. In: Eighth Report of the Joint Panel on Oceanographic Tables and Standards, UNESCO Technical Papers in Marine Science No. 28, Annex 6. Paris: UNESCO. Millero FJ, Chen C-T, Bradshaw A, and Schleicher K (1980) A new high pressure equation of state for seawater. Deep Sea Research 27A: 255--264. Millero FJ and Poisson A (1981) International oneatmosphere equation of state for seawater. Deep Sea Research 28A: 625--629. Millero FJ, Perron G, and Desnoyers JE (1973) Heat capacity of seawater solutions from 5 to 25 1C and 0.5 to 22% chlorinity. Journal of Geophysical Research 78: 4499--4507. UNESCO (1981) Tenth Report of the Joint Panel on Oceanographic Tables and Standards, UNESCO Technical Papers in Marine Science No. 36. Paris: UNESCO.
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APPENDIX 6. THE BEAUFORT WIND SCALE AND SEASTATE Beaufort wind scale
Wind description
Wind speed
Seastate
Mean (m s 1)
Range (m s 1)
Probable wave height Mean (m)
Maximum (m)
0 1
Calm Light airs
0 0.8
0–0.2 0.3–1.5
0 1
0.1
0.1
2
Light breeze
2.4
1.6–3.3
2
0.2
0.3
3
Gentle breeze
4.3
3.4–5.4
3
0.6
1.0
4
Moderate breeze
6.7
5.5–7.9
3–4
1.0
1.5
5
Fresh breeze
9.3
8.0–10.7
4
2.0
2.5
6
Strong breeze
12.3
10.8–13.8
5
3.0
4.0
7
Near gale
15.5
13.9–17.1
5–6
4.0
5.5
8
Gale
18.9
17.2–20.7
6–7
5.5
7.5
9
Severe gale
22.6
20.8–24.4
7
7.0
10.0
Description of sea
‘Calm’: Sea like a mirror ‘Calm’: Ripples with the appearance of scales are formed, but without foam crests ‘Smooth’: Small wavelets, still short, but more pronounced. Crests have a glassy appearance and do not break ‘Slight’: Large wavelets. Crests begin to break. Foam of glassy appearance. Perhaps scattered whitecaps ‘Slight–moderate’: Small waves, becoming larger; fairly frequent whitecaps ‘Moderate’: Moderate waves, taking a more pronounced long form; many whitecaps formed ‘Rough’: Large waves begin to form; the white foam crests are more extensive everywhere ‘Rough–very rough’: Sea heaps up and white foam begins to be blown in streaks along the direction of the wind ‘Very rough–high’: Moderately high waves of greater length; edges of crests begin to break into spindrift. The foam is blown in well-marked streaks along the direction of the wind ‘High’: High waves. Dense streaks of foam along the direction ofthe wind. Crests of waves begin to topple, tumble, and roll over. Spray may affect visibility (Continued )
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APPENDIX 6. THE BEAUFORT WIND SCALE AND SEASTATE
385
Continued Beaufort wind scale
Wind description
Wind speed
Seastate
Mean (m s 1)
Range (m s 1)
Probable wave height Mean (m)
Maximum (m)
10
Storm
26.4
24.5–28.4
8
9.0
12.5
11
Violent storm
30.5
28.5–32.6
8
11.5
16.0
12
Hurricane
–
32.7 þ
9
–
14.0 þ
Description of sea
‘Very high’: Very high waves with long overhanging crests. The resulting foam, in great patches, is blown in dense white streaks along the direction of the wind. On the whole the surface of the sea takes on a white appearance. The ‘tumbling’ of the sea becomes heavy and shock-like. Visibility affected ‘Very high’: Exceptionally high waves (small and medium-size ships might be for a time lost to view behind the waves). The sea is completely covered with long white patches of foam lying along the direction of the wind. Everywhere the edges of the wave crests are blown into froth. Visibility affected ‘Phenomenal’: The air is filled with foam and spray. Sea completely white with driving spray. Visibility very severely affected
The ‘Probable wave heights’ refer to well-developed wind waves in the open sea. There is a lag between the wind getting up and the sea increasing, which should be borne in mind. This table is derived from the UK Met Office table (http://www.metoffice.gov.uk/weather/marine/guide/beaufortscale.html) and the corresponding scale given in the Met Office Observers Handbook.
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APPENDIX 7. ESTIMATED MEAN OCEANIC CONCENTRATIONS OF THE ELEMENTS
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APPENDIX 7. ESTIMATED MEAN OCEANIC CONCENTRATIONS OF THE ELEMENTS
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387
388
APPENDIX 7. ESTIMATED MEAN OCEANIC CONCENTRATIONS OF THE ELEMENTS
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APPENDIX 8. ABBREVIATIONS AABW AAIW AASW AATSR ABE ABF ABW ACC ACD ACOUS ADAS ADCP ADEOS ADL ADV ADW AEE AFC AFGP AGCM AGDW AIRSAR AIS AISI AIW ALACE ALOS AMC AMIP AMS AMSR AMT AOCI AOGCM AOL AOP APC APE APFZ APTS ARIES ASDIC ASMR ASP AST ASUW ASW ATM ATOC ATP ATSR
Antarctic Bottom Water Antarctic Intermediate Surface Water Antarctic Surface Water Advanced ATSR Autonomous Benthic Explorer Angola–Benguela Front Arctic Bottom Water Antarctic Circumpolar Current aragonite compensation depth Arctic Climate Observations Using Underwater Sound (project) Airborne Diode Array Spectrometer acoustic Doppler current profiler Advanced Earth Observing Satellite aerobic diving limits Adventure Bank Vortex Adriatic Deep Water anomalously enriched elements Automatic Flow Cytometry antifreeze glycopeptides atmospheric general circulation model(s) Aegean Deep Water Airborne SAR Atlantic Ionian Stream Airborne Imaging Spectrometer Atlantic Intermediate Water Autonomous Lagrangian Circulation Explorer Advanced Land Observing Satellite axial magma chamber Atmospheric Model Intercomparison Project accelerator mass spectrometry Advanced Microwave Scanning Radiometer Atlantic Meridional Transect Airborne Ocean Color Instrument atmosphere–ocean general circulation models Airborne Oceanographic LIDAR apparent optical property Advanced Piston Corer available potential energy Antarctic Polar Frontal Zone astronomical polarity timescale Autosampling and Recording Instrumental Environmental Sampler Antisubmarine Detection Investigation Committee Advanced Scanning Microwave Radiometer amnesic shellfish poisoning axial summit trough Atlantic Subarctic Upper Water Arabian Sea Water; or antisubmarine warfare Airborne Topographic Mapper Acoustic Thermometry of Ocean Climate adenosine triphosphate Along-Track Scanning Radiometer
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390
APPENDIX 8. ABBREVIATIONS
AUV AVHRR AVIRIS AVP AVPPO AW AXBT AXSV AZP BB BBL BBW BCD BGE BGHS BI BIO BIOMASS BIONESS BMC BOD BP BR BSR BTM BWT CASI CBDW CCAMLR CCD CCrD CDOM CDW CFA CFC CFP CFT CHAMP Chl-a CIW CLE/CSV CLIVAR CMA CNES COIS COS COT CPR CRM CS2 CSA CSO CSSF CTD CUFES
autonomous underwater vehicle Advanced Very High Resolution Radiometer Airborne Visible/Infrared Imaging Spectrometer axial volcanic ridge(s) Autonomous Vertically Profiling Plankton Observatory Atlantic Water air-launched XBT air-launched XSV azaspirazid shellfish poisoning broadband benthic boundary layer Bengal Bay Water bacterial carbon demand bacterial growth efficiency base of gas hydrate stability baroclinic instability Bedford Institute of Oceanography (Canada) Biological Investigations of Marine Antarctic Systems and Stocks Bedford Institute of Oceanography Net and Environmental Sensing System Brazil/Malvinas Confluence biological oxygen demand bacterial production bacterial respiration bottom-simulating reflector Bermuda Testbed Mooring bottom water temperature Compact Airborne Spectrographic Imager Canadian Basin Deep Water Commission for the Conservation of Antarctic Marine Living Resources calcite compensation depth carbonate critical depth colored dissolved organic matter Circumpolar Deep Water; or Cretan Deep Water carbonate fluoroapatite; or continuous flow analyser chlorofluorocarbon ciguatera fish poisoning controlled flux technique Challenging Minisatellite Payload chlorophyll-a Californian Intermediate Water; or Cretan Intermediate Water competitive ligand equilibration with cathode stripping voltammetry Climate Variability and Predictability Program Chemical Manufacturers Association Centre Nationale d’Etudes Spatiales Coastal Ocean Imaging Spectrometer carbonyl sulfide cost of transport Continuous Plankton Recorder chemical remanent magnetization carbon disulfide Canadian Space Agency combined sewer overflow Canadian Scientific Submersible Facility conductivity, temperature, and depth; or conductivity–temperature–depth (profiler) continuous underway fish egg sampler
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APPENDIX 8. ABBREVIATIONS
CZCS D/O DCC DCM DCMU DDT DIC DIN DIP DMGe DMHg DMS DMSb DMSP DNA DOC DOM DON DOP DPASV dpm DRM DSDP DSL DSP DVM DW DWBC DWT EAC EACC EAIS EASIW EBDW ECMWF EEM EEZ EF EGC EIC EKE ELM EM EMDW EMT ENACW ENPCW ENPTW ENSO Envisat EOS EPI EPR EPS ERS
Coastal Zone Color Scanner Dansgaard–Oeschger direct current condenser deep chlorophyll maximum 3-(3,4-dichlorophenyl)-1,1-dimethylurea dichlorodiphenyltrichloroethane dissolved inorganic carbon dissolved inorganic nitrogen dissolved inorganic phosphorus dimethylgermanic acid dimethylmercury dimethyl sulfide dimethylantimonate Defense Meteorological Satellite Program; or 3-(dimethylsulfonium) propionate deoxyribonucleic acid dissolved organic carbon dissolved organic matter dissolved organic nitrogen dissolved organic phosphorus differential pulse anodic stripping voltammetry disintegrations per minute detrital remanent magnetization/depositional detrital remanent magnetization Deep Sea Drilling Project deep scattering layer diarrhetic shellfish poisoning diel vertical migration Deep Arctic Water deep western boundary current deadweight tonnage East Australian Current East Africa Coastal Current East Antarctic ice sheet Eastern Atlantic Subarctic Intermediate Water Eurasian Basin Deep Water European Centre for Medium-Range Weather Forecasts excitation–emission matrix (spectroscopy) exclusive economic zone enrichment factor East Greenland Current Equatorial Intermediate Current eddy kinetic energy external limiting membrane electromagnetic Eastern Mediterranean Deep Water Eastern Mediterranean Transient Eastern North Atlantic Central Water Eastern North Pacific Central Water Eastern North Pacific Transition Water El Nin˜o Southern Oscillation Environmental Satellite Earth Observing System epifluorescence microscopy East Pacific Rise extracellular polysaccharides Earth Resources Satellite
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391
392
APPENDIX 8. ABBREVIATIONS
ESA ESD ESMR ESPCW ESPIW ESPTW ESS ESSE ESTAR ETR EUC FAO FBI FCLS FDOM FFP FIA FID FLIP FMI FMP FMS FOM FPA FRAM FRR FRRF FSU FTIR FY GAC GBRUC GC GCM GCOS GEF GEOHAB GEOSECS GLI GLOBEC GLORIA GMOs GOCE GODAE GOM GOOS GPS GPTS GRACE GSNW GSSP GT HAB HCB HCH
European Space Agency equivalent spherical diameter Electrically Scanning Microwave Radiometer Eastern South Pacific Central Water Eastern South Pacific Intermediate Water Eastern South Pacific Transition Water evolutionarily stable strategy error subspace statistical estimation Electrically Scanning Thinned Array Radiometer electron transport rate Equatorial Undercurrent (UN) Food and Agriculture Organization fresh water–brackish water interface ferrochrome lignosulfate fluorescent (dissolved) organic matter fast field program flow injection analyzer flame ionization detector/detection Floating Instrument Platform Formation Micro-Image Fishery Management Plan formation scanner figure of merit fixed-potential amperometry Fine Resolution Antarctic Model fast repetition rate fast repetition rate fluorometry Florida State University Fourier transform infrared spectrometry/spectrometer first-year (ice) global area coverage Great Barrier Reef Undercurrent gas chromatography general circulation model Global Climate Observing System Global Environmental Facility Global Ecology and Oceanography HABs (program) Geochemical Ocean Sections Study Global Imager Global Ocean Ecosystem Dynamics geological long-range ASDIC genetically modified organism(s) Gravity Field and Steady-state Ocean Circulation Explorer Global Ocean Data Assimilation Experiment Gulf of Mexico Global Ocean Observing System Global Positioning System geomagnetic polarity timescale Gravity Recovery and Climate Experiment Gulf Stream North Wall (index) Global Boundary Stratotype Section and Point gross tonnage harmful algal bloom hexachlorobenzene hexachlorocyclohexane
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APPENDIX 8. ABBREVIATIONS
HE HEXMAX HEXOS HIRIS HMW HNDA HNLC HOPLASA HOPS HOT HPLC HRGB HRPT HRS HSSW HST IABO IAPSO IAS IBM IC ICCAT ICES ICJ ICNAF ICP ICP-MS ICRP ICSU ICZM IEW IFQ IFREMER IGBP IGW IIOE IIP IIW IKMT IMO INDEX INPFC IOC IOCCG IODP IOP IPCC IPI IPNV IPSFC IR IRD IRONEX IronEx II ISAV
393
Halmahera Eddy HEXOS Main Experiment Humidity Exchange Over the Sea (experiment) High-Resolution Imaging Spectometer high-molecular weight high natural dispersing areas high-nutrients, low-chlorophyll Horizontal Plankton Sampler Harvard Ocean Prediction System Hawaiian Ocean Time Series high-performance liquid chromatography hard rock guide base high-resolution picture transmission high-resolution sampler high-salinity shelf water high stand system tract International Association for Biological Oceanography International Association for the Physical Sciences of the Ocean Intra-Americas Sea individual-based model integrated circuit International Commission for the Conservation of Atlantic Tuna International Council for the Exploration of the Sea International Court of Justice International Commission for the Northwest Atlantic Fisheries International Conferences on Paleo-oceanography inductively coupled plasma mass spectrometry International Commission on Radiological Protection International Council for Science (formerly International Council of Scientific University) Integrated Coastal Zone Management Indian Equatorial Water Individual Fishery Quota l’Institut Francais de Recherche pour l’Exploitation de la Mer International Geosphere–Biosphere Program internal gravity waves International Indian Ocean Experiment (US Coast Guard) International Ice Patrol Indonesian Intermediate Water Isaacs–Kidd midwater trawl International Maritime Organization Indian Ocean Experiment International North Pacific Fisheries Commission International Oceanographic Commission International Ocean Color Coordinating Group Integrated Ocean Drilling Program inherent optical properties Intergovernmental Panel on Climate Change interpulse interval infectious pancreatic necrosis virus International Pacific Salmon Fisheries Commission infrared iceberg rafted detrital Iron Enrichment Experiment Iron Fertilization Experiment II infectious salmon anemia virus
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394
APPENDIX 8. ABBREVIATIONS
ISE ISV ISW ITCZ ITQ IUCN IUW IVF JAMSTEC JERS JGOFS JLS JOI JOIDES JPL K/T KE KHI KYM LAA LAC LADCP LADS LARS LBMP LCDW LDEO LDW LHPR LIA LIDAR LIP LIW LLD LME LMW LNG LNHC LNLC LOAEL LOCHNESS LOICZ LOOPS LPG LSFC LST MAB MAD MAR MARPOL MASZP MAW mbsf MBT MC
ion-selective electrode Ionian Shelfbreak Vortex ice shelf water Intertropical Convergence Zone individual transferable quota International Union for the Conservation of Nature Indonesian Upper Water in vivo fertilization Japan Marine Science and Technology Center Japan Environmental Resources Satellite Joint Global Ocean Flux Study join, leave, or stay Joint Oceanographic Institutions Incorporated Joint Oceanographic Institutions for Deep Earth Sampling Jet Propulsion Laboratory Cretaceous/Tertiary (boundary) kinetic energy Kelvin–Helmholtz Instability krill yield model large amorphous aggregates local area coverage Lowered Acoustic Doppler Current Profiler Laser Airborne Depth Sounder launch and recovery system land-based marine pollution Lower Circumpolar Deep Water Lamont–Doherty Earth Observatory Levantine Deep Water Longhurst–Hardy plankton recorder Little Ice Age light detection and ranging large igneous province Levantine Intermediate Water liquid line of defense large marine ecosystems low-molecular weight liquefied natural gas low-nitrate, high-chlorophyll low-nitrate, low-chlorophyll lowest observed adverse effect level Large Opening/Closing High Speed Net and Environmental Sampling System Land Ocean Interaction in the Coastal Zone (program) Littoral Ocean Observing and Prediction System liquefied petroleum gas laser-stimulated fluorescence of chlorophyll low stand systems tract Mid-Atlantic Bight Magnetic Airborne Detector Mid-Atlantic Ridge Marine Pollution (treaty) moored, automated, serial zooplankton pump Modified Atlantic Water meters below seafloor mechanical bathythermograph Mindanao Current; or Mozambique Current
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APPENDIX 8. ABBREVIATIONS
MCC MCP MCSST ME MFP MIJ MIZ MIZEX MMAs MMD MMGe MMHg MMJ MMSb MOBY MOC MOCNESS MOCS MODE MODIS MOM MOR MORB MPA MPS MSFCMA MSL MST MSVPA MSY MUC MVDF MW MWDW MWP MY NABE NADPH NADW NAFO NAO NASCO NASDA NASF NCAR NCC NCEP NDBC NDSF NEDT NEADS NEAFC NEC NECC NEE
Maltese Channel Crest Medieval Cold Period multichannel SST Mindanao Eddy matched field processing Mid-Ionian Jet marginal ice zone marginal ice zone experiments monomethylarsenate mass median diameter monomethylegermanic acid monomethylmercury Mid-Mediterranean Jet monomethylantimonate Marine Optical Buoy Meridional Overturning Circulation Multiple Opening/Closing Net and Environmental Sensing System Multichannel Ocean Color Sensor Mid-Ocean Dynamics Experiment Moderate Resolution Imaging Spectroradiometer modular ocean model mid-ocean ridge mid-ocean ridge basalt marine protected area multiple plankton sampler Magnuson–Stevens Fishery Conservation Management Act mean sea level Mediterranean Salt Tongue; or multisensor track multispecies virtual population analysis maximum sustainable yield Mindanao Undercurrent maximum variance distortion filter Mediterranean Water; or molecular weight modified warm deep water Medieval Warm Period multiyear (ice) North Atlantic Bloom Experiment reduced form of nicotinamide–adenine dinucleotide phosphate North Atlantic Deep Water Northwest Atlantic Fishery Organization North Atlantic Oscillation North Atlantic Salmon Conservation Organization Japanese National Space Development Agency North Atlantic Salmon Fund National Center for Atmospheric Research Norwegian Coastal Current National Centers for Environmental Prediction National Data Buoy Center National Deep Submergence Facility noise equivalent temperature difference North East Atlantic Dynamics Study North-east Atlantic Fisheries Commission North Equatorial Current North Equatorial Countercurrent nonenriched elements
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APPENDIX 8. ABBREVIATIONS
NEMO NEW NGCC NGCUC NLSST NM NMC NMHC NMR NOAA NOAEL NOSAMS NOSS NPAFC NPOESS NPP NRM NROSS NSP NSSC NTU NWP OBS OCMIP OCTS ODAS ODE ODP OGCM OI OML OMZ OOP OPA OPC OSC OTEC OTIP PAH PALACE PALK PAM PAR PBB PCBs PCG PCGC PCR PCS PCUC PDM pDRM PDW PE PEAS
Naval Earth Map Observer North-east Water New Guinea Coastal Current New Guinea Coastal Undercurrent nonlinear SST normal mode North-east Monsoon Current nonmethane hydrocarbons nuclear magnetic resonance National Oceanographic and Atmospheric Administration no observed adverse effect level National Ocean Sciences Accelerator Mass Spectrometry facility National Oceanographic Satellite System North Pacific Anadromous Fisheries National Polar-Orbiting Satellite System NPOESS Preparatory Program natural remanent magnetization Navy Remote Ocean Observing Satellite neurotoxic shellfish poisoning Northern Subsurface Countercurrent nephelometric turbidity unit numerical weather prediction ocean bottom seismograph Ocean Carbon Model Intercomparison Project Ocean Color and Temperature Sensor Ocean Data Acquisition System ordinary differential equation(s) Ocean Drilling Program ocean general circulation model optimal interpolation ocean mixed layer oxygen minimum zone object-oriented programming Oil Pollution Act optical plankton counter overlapping spreading centers Ocean Thermal Energy Conversion Optimal Thermal Interpolation Scheme polycyclic aromatic hydrocarbons Profiling Autonomous Lagrangian Circulation Explorer potential alkalinity pulse amplitude modulation photosynthetic available radiation passive broadband polychlorobiphenyls/polychlorinated biphenyls Panama–Columbia Gyre preparatory capillary gas chromatography polymerase chain reaction pressure core sampler Peru–Chile Undercurrent particulate detrital matter postdepositional detrital remanent magnetization Pacific Deep Water parabolic equation possible estuary-associated syndrome
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APPENDIX 8. ABBREVIATIONS
PEW PF PFSST PGE PHILLS PICES PML PMM PMT PN PNB PNM POC POCM POEM POM PON POP PP ppbv PPF ppmv pptv PRF PRN PS II PSC PSIW PSMSL PSP PSSF PSU PSUW PSW PTCS PV PW QSU RAD RAR RCB REE REMUS rf RMT RNA RO ROFI ROS ROV ROWS RPE RR rRNA RS
Pacific Equatorial Water Polar Front Pathfinder SST platinum-group elements Portable Hyper-spectral Imager for Low-Light Spectroscopy North Pacific Marine Science Organization Polar Mixed Layer photomultiplier module photomultiplier tube particulate nitrogen passive narrowband primary NO2 maximum particulate organic carbon Parallel Ocean Climate Model Physical Oceanography of the Eastern Mediterranean particulate organic matter particulate organic nitrogen persistent organic pollution primary production parts per billion by volume Pump and Probe Fluorometer parts per million by volume parts per trillion by volume pulse repetition frequency pseudo random noise Photosystem II Pacific Salmon Commission Pacific Subarctic Intermediate Water permanent service for mean sea level paralytic shellfish poisoning Passive Solar Stimulated Fluorescence practical salinity unit Pacific Subarctic Upper Water Polar Surface Water pressure and temperature core sampler potential vorticity Polar Water; or Pacific Water quinine sulfate unit ridge axis discontinuity real aperture radar rotary core barrel rare-earth elements remote environmental measuring units radiofrequency rectangular mouth opening trawl ribonucleic acid reverse osmosis region of fresh water influence reactive oxygen species remotely operated vehicle Radar Ocean Wave Spectrometer retinal pigment epithelium refracted-refracted (rays) ribosomal RNA remote sensing
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RSPGIW RSR RTE RTR RV SACW SAH SAHFOS SAMW SAR SAS SASW SAV SAVE SC SCAR SCOR SCUBA SCV SeaWiFS SEC SECC SEM SF6 SHOALS SICW SIMBIOS SINODE SIO SIPPER SIR SLFMR SMC SMMR SMOS SMOW SMR SNP SNR SOC SOFAR SOI SOIREE SP SPCZ SPE SPM SPMW SRA SSB SSH SSL SSM/I SSSC SST
Red Sea–Persian Gulf Intermediate Water refracted-surface-reflected (rays) radiative transfer equation relative tide range research vessel South Atlantic Central Water South Atlantic High Sir Alister Hardy Foundation for Ocean Science Subantarctic Mode Water synthetic aperture radar SeaWiFS Aircraft Simulator Subantarctic Surface Water submerged aquatic vegetation South Atlantic Ventilation Experiment Somali Current Scientific Committee for Antarctic Research Science Commission on Oceanic Research self-contained underwater breathing apparatus sub-mesoscale coherent vortex Sea-viewing Wide Field-of-view Sensor South Equatorial Current South Equatorial Countercurrent scanning electron microscopy sulfur hexafluoride Scanning Hydrographic Operational Airborne LIDAR Survey South Indian Central Water Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies Surface Indian Ocean Dynamic Experiment Scripps Institution of Oceanography Shadowed Image Particle Profiling and Evaluation Recorder Shuttle Imaging Radar Scanning Low Frequency Microwave Radiometer South-west Monsoon Current Scanning Multichannel Microwave Radiometer Soil Moisture and Ocean Salinity standard mean ocean water Scanning Microwave Radiometer soluble nonreactive phosphorus signal-to-noise ratio Southampton Oceanography Centre (UK) sound fixing and ranging Southern Oscillation Index Southern Ocean Iron Enrichment Experiment short period (instrumentation) South Pacific Convergence Zone solid-phase extraction suspended particulate matter subpolar mode water Scanning Radar Altimeter spawning stock biomass sea surface height sound-scattering layer Special Sensor Microwave/Imager South Subsurface Countercurrent sea surface temperature
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APPENDIX 8. ABBREVIATIONS
SSU rRNA SSXBT STCC STD STMW SVD SWG T/P TAC TAP TBT TDN TEM TEP TEU THC TIMS TIROS-N TKE TLC TLE TMI TMS TMW TMZ TOBI TOC TOGA TOMS TON TOVS TRM TRMM TS curve TST TTO TTONAS TTOTAS TU TW UBL UCDW ULES UML UN(O) UNCED UNCLOS UNEP UNESCO UOR uPDW UTC UUV UVP VACM
small subunit rRNA submarine-launched XBT Subtropical Countercurrent salinity, temperature, and depth (measuring instrument) Subtropical Mode Water singular-value decomposition Science Working Group(s) Topex/Poseidon (system) total allowable catch Transarctic Arctic Propagation (experiment) tributyltin total dissolved nitrogen transmission electron microscopy transparent exopolymer particles twenty-foot equivalent unit thermohaline circulation thermal ionization mass spectrometry Television and Infrared Observing Satellite-version N turbulent kinetic energy total lung capacity total lipid extract TRMM Microwave Imager tether management system Transitional Mediterranean Water turbidity maximum zone Towed Ocean Bottom Instrument total organic carbon Tropical Ocean–Global Atmosphere (program) Total Ozone Mapping Spectrometer total oxidized nitrate Total Ozone Vertical Sounder thermoremanent magnetization Tropical Rainfall Measuring Mission temperature–salinity curve transgressive stand systems tract Tropical Tracers in the Ocean (experiment) TTO North Atlantic Study TTO Tropical Atlantic Study tritium unit tropical waters under-ice boundary layer upper Circumpolar Deep Water upward-looking echo sounders upper mixed layer United Nations (Organization) United Nations Conference on Environment and Development United Nations Convention on the Law of the Sea United Nations Environmental Program United Nations Educational, Scientific, and Cultural Organization undulating oceanographic recorder Upper Polar Deep Water Coordinated Universal Time unmanned underwater vehicle underwater video profiler vector averaging current meter
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APPENDIX 8. ABBREVIATIONS
VAD VHSV VIIRS VISR VLCC VMCM VMM VMS VOC VPR VRM VSF WAIS WASIW WCP WCR WHO WHOI WIW WMDW WMO WNACW WNPCW WOCE WSC WSDW WSPCW WWGS WWSP XBT XCP XCTD XKT XSV
vertical advection diffusion viral hemorrhagic septicemia virus Visible and Infrared Imaging Radiometer Suite Visible and Infrared Scanning Radiometer very large crude carrier vector measuring current meter volume-weighted mean concentration vehicle monitoring system vapor-phase organic carbon or volatile organic compounds video plankton recorder viscous remanent magnetization volume scattering function West Antarctic Ice Sheet Western Atlantic Subarctic Intermediate Water World Climate Program warm core ring World Health Organization Woods Hole Oceanographic Institution Winter Intermediate Water Western Mediterranean Deep Water World Meteorological Organization West North Atlantic Central Water Western North Pacific Central Water World Ocean Circulation Experiment West Spitsbergen Current Weddell Sea Deep Water Western South Pacific Central Water Winter Weddell Gyre Study Winter Weddell Sea Project expendable bathythermograph expendable current profiler expendable conductivity–temperature–depth probe expendable optical irradiance probe expendable sound velocity probe
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APPENDIX 9. TAXONOMIC OUTLINE OF MARINE ORGANISMS L. P. Madin, Woods Hole Oceanographic Institution, Woods Hole, MA, USA Copyright & 2001 Elsevier Ltd.
Introduction This appendix is intended as a brief outline of the taxonomic categories of marine organisms, providing a classification and description of groups that are mentioned elsewhere in the Encyclopedia. It is presented at the level of Phylum (or equivalent) in most cases, but to the level of Class in large groups with many marine species. The few categories that contain no known marine species are not included in this list. The outline is intended as a list rather than any kind of phylogenetic tree. The three Domains listed are now considered, on genetic evidence, to be the three primary categories of living organisms on Earth. The definitions and relationships of many higher taxonomic groups are currently in flux owing to the advent of new molecular genetic data. This is particularly true for the Archaea, Bacteria, and Protista (also called Protozoa or Protoctista), in which numerous phylogenetic lineages have been identified in recent years that are neither consistent with classical categories based on morphological characters nor arranged in a comparable hierarchy. The accepted systematics of the Protista will probably change in the near future, reflecting this new genetic information. However, as these new categories are still being defined, and have not yet come into common usage in ocean sciences, this outline retains a more classical and widely known system for protists (Margulis and Schwartz, 1988), with names that will more likely be familiar to marine scientists. Where possible, the approximate number of known (named) species is given, with an indication of how many of these are marine. For many groups the described species may be only a small fraction of the probable true number of species. It should be apparent from perusal of the list that the ocean environment is home to the vast majority of the biological diversity on Earth. Notwithstanding the large numbers of insect species and flowering plants on land, the remarkable diversity of different body plans defining the higher taxonomic levels occurs almost entirely in the sea. Readers interested in recent work on the phylogeny and classification of any of these organisms are directed to the Further Reading list. Often the most up-to-date information will be found on the Web sites listed.
DOMAIN ARCHAEA Prokaryotic cells having particular cell lipids and genetic sequences that distinguish them from all other organisms. Many are extremophiles living at high temperatures or under unusual chemical conditions. Few have been cultured. ‘‘Species’’ are defined and classification is based mainly on molecular evidence. Increasing numbers of Archaea are being detected in marine environments. Korarchaeota
A poorly-known group of hyperthermophilic organisms thought to be near the evolutionary base of the Archaea, and perhaps the most primitive organisms known. Crenarchaeota
Primarily hyperthermophilic forms, including many sulfur-reducing species, but also species living at very low temperatures in the ocean.
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Euryarachaeota
A group containing methane-producing forms and others that live in extremely saline conditions.
DOMAIN BACTERIA A tremendously diverse domain of prokaryotic cells with particular genetic sequences and cell constituents. All photosynthetic and pathogenic forms are in this domain. A dozen major phylogenetic groups can be identified on genetic evidence, of which all but one include marine forms. Numbers of species are almost impossible to specify. Aquificales
Primitive hyperthermophiles with a chemoautotrophic metabolism. Known from hydrothermal environments. Green non-sulfur bacteria
A group including some photosynthetic and multicellular filamentous forms. Related forms may have produced ancient stromatolite structures in shallow seas. Proteobacteria
Purple bacteria; a large, metabolically and morphologically diverse group including some photosynthetic, chemoautotrophic, and nitrogen-fixing forms that occur in the ocean. There are also many pathogenic species. Gram-positive bacteria
Common soil-dwelling forms, but some also marine. Many form resting stages called endospores enabling survival under harsh conditions. Cyanobacteria
An ancient and diverse lineage of photosynthetic bacteria that include some of the most abundant and important primary producers in the ocean. Bacteroides, Flavobacterium and related forms
Gram-negative microbes occurring in freshwater and marine environments, as well as soils and deep-sea sediments. Green sulfur bacteria
Anaerobic forms that oxidize sulfur compounds to elemental sulfur and occupy a variety of marine environments. Deinococci
Highly radiation-resistant cells, which include forms found in terrestrial and marine thermal springs. Planctomyces
One of only two groups having cell walls that lack the component peptoglycan; found in freshwater and marine environments. Thermotoga
A group of anaerobic microbes found at shallow and deep-sea hydrothermal vents, and which includes some of the most thermophilic bacteria known.
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Spirochaetes
Flagellated cells with a unique helical morphology; most are parasites and some inhabit marine animals.
DOMAIN EUKARYA Single-celled or multicelled organisms with membrane-bounded nuclei containing the genetic material, and other specialized cellular organelles. Cell division is by some form of mitosis, and metabolism is usually aerobic. All protists, plants and animals are eukaryotes.
PROTISTA (also Protoctista, Protozoa) Single-celled (and some multicellular) organisms that are neither animals nor true plants. It is a diverse and polyphyletic group that includes protozoans, algae, seaweeds and slime molds. These categories are defined mostly by morphology. Phylum Dinoflagellata
Marine protozoans having unusual organization of their DNA, two locomotory flagella, and frequently encased in a rigid test. Dinoflagellates can be photosynthetic or heterotrophic; some live symbiotically in the tissues of other organisms. Approximately 3000 species, mostly marine. Phylum Rhizopoda (also Amoebozoa)
Amoebas; single-celled organisms lacking flagella or cilia and moving by pseudopodia. Some are encased in a test. There are several thousand species in terrestrial, freshwater and marine environments, as well as parasitic and pathogenic forms. Phylum Chrysophyta
A large group of unicellular algae that lack sexual stages and reproduce only by asexual division and formation of ‘‘swarmer’’ cells for dispersal. Most live in fresh water; the silicoflagellates are the only marine representatives. Phylum Haptophyta
Marine photosynthetic cells that alternate between a flagellated free-swimming stage and a resting coccolithophorid stage covered with calcareous plates. These stages were previously thought to be distinct species. Several hundred species. Phylum Euglenophyta
Flagellated protozoa that may be photosynthetic or heterotrophic, solitary, or colonial. They have flexible cell walls made of protein, and complex internal organelles. About 800 species including some marine. Phylum Cryptophyta
Also called cryptomonads, these cells are widely distributed in fresh and salt water, and as internal parasites. They lack sexual reproduction and swim with two flagella. Phylum Zoomastigina
Nonphotosynthetic cells with one to many flagella, including free-living, symbiotic, and parasitic species, with both sexual and asexual reproduction. The group is probably polyphyletic and includes hundreds of described species, with probably thousands more unknown; many are marine. Phylum Bacillariophyta
The diatoms; photosynthetic cells enclosed in elaborate siliceous tests consisting of two halves or valves. Diatoms are important components of the food chain in marine and fresh water, with about 12 000 species.
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Phylum Phaeophyta
The brown algae and seaweeds; macroscopic, photosynthetic, multicellular plantlike forms inhabiting intertidal, subtidal, or pelagic marine environments. About 1500 species, all marine. Phylum Rhodophyta
Red algae; complex multicellular seaweeds inhabiting intertidal and subtidal environments worldwide. All contain particular photosynthetic pigments that give them a reddish color. About 4000 species, mainly marine. Phylum Chlorophyta
Green algae, including single-celled forms and some multicellular seaweeds. They are important primary producers in all aquatic environments. There are about 7000 species, including many marine forms. Phylum Actinopoda
Heterotrophic protozoa having long filamentous cytoplasmic extensions called axopods, supported by silicabased or strontium-based skeletal elements. Important marine forms are the radiolarians and acantharians. Some harbor algal symbionts or form macroscopic colonies. About 4000 species, mostly marine. Phylum Foraminifera
Amoeboid protozoans with internally chambered, calcified, or agglutinated shells or tests. All are marine, living in benthic and pelagic habitats. About 4000, mainly benthic, extant species, but 30 000 fossil species. Phylum Ciliophora
The ciliates; single-celled organisms covered with short cilia that are used for locomotion and/or food gathering. Ciliate cells have two nuclei and reproduce by fission. The 8000 species live in freshwater and marine environments. Phylum Cnidosporidia
A diverse, polyphyletic group of heterotrophic microbes that are parasites and pathogens of animals, including many marine invertebrates and fish. About 850 species. Phylum Labyrinthulomycota
Slime nets; colonial protozoans that construct networks of slime pathways on the surface of various substrates. The osmotrophic cells move along the slimeways toward food sources. Only about 10 described species, including marine forms.
PLANTAE Plants are multicellular, photosynthetic organisms that develop from an embryo that is produced by sexual fusion. Plant cells have rigid cell walls and contain chloroplasts where photosynthesis occurs. Most of the 235 000 described species are terrestrial, with a few secondarily adapted to shallow marine environments. Phylum Angiospermophyta
Flowering plants; virtually all the familiar grasses, flowers, vegetables, shrubs, and trees on Earth belong in this group, comprising about 230 000 species. A few grasses live in salt marsh and shallow subtidal marine environments.
FUNGI Multicellular organisms that are neither motile nor photosynthetic, and form spores for reproduction. The basic structural elements of fungi are threadlike hyphae, which are partially divided into separate cells. Fungi
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range from microscopic yeasts and molds to large mushrooms and shelf fungi, and include some pathogenic forms. The vast majority of the 100 000 species are terrestrial. Phylum Ascomycota
A diverse group including yeasts, molds, and truffles. In the marine environment filamentous ascomycotes grow and feed on decomposing plant material. A few of the 30 000 species are found in marine environments. Phylum Basidiomycota
Complex, mainly terrestrial fungi including rusts, smuts, and mushrooms. Of some 25 000 species, only a handful are known from the marine environment, where they grow on marine grasses. ANIMALIA
Animals are motile, heterotrophic, multicellular organisms, all of which develop from a ball of cells called a blastula, which originates by fusion of gametes. Most animals have complex tissues, organs, and organ systems, and higher animals have well-developed nervous and sensory capabilities. Phylum Placozoa A simple, tiny multicellular marine organism resembling a large amoeba, lacking tissues or organs. Only one species known. Phylum Porifera There are about 10 000 species of sponges, animals with skeletons composed of spicules, but which lack tissues, organs, or definite symmetry. Sponges have free-swimming larvae and sessile adults that filter-feed. All but a few hundred species are marine. Class Calcarea.
Sponges with skeletons made up of calcareous spicules. About 500 species, all marine.
Class Demospongia. species.
Sponges with skeletons of spongy protein and/or silica, mainly marine. About 9500
Class Hexactinellida. species.
Glass sponges, with skeletons of six-rayed silica spicules. About 50 deep-sea
Phylum Cnidaria Radially symmetric animals with distinct tissues, including the jellyfishes, corals, anemones, and hydroids. All cnidarians are predators, using cnidocysts (nematocysts) to sting prey. Body forms include the polyp and medusa. Over 10 000 described species, nearly all marine. The group Myxozoa, previously considered protozoans or degenerate metazoans, are now thought to belong with the Cnidaria. Class Anthozoa. species.
Corals and sea anemones, having the polyp form only. About 6200 benthic marine
Class Hydrozoa. Most hydrozoans have a life cycle that alternates between an asexual polyp (hydroid) stage and a free-swimming, sexual medusa. Hydroid stages are usually colonial. Some coastal hydroid species lack the medusa and some oceanic species lack the hydroid. About 3000 species, nearly all marine. Class Scyphozoa. species.
More complex, larger jellyfish with simpler or absent polyp stages. About 200 marine
Class Cubozoa. Medusae with cuboidal body shape, well-developed nervous system and eyes, and highly toxic nematocysts. About 30 mainly tropical species.
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Phylum Ctenophora Comb jellies; transparent gelatinous animals that use fused plates of cilia (comb plates) for locomotion and sticky tentacles to capture prey. They have biradial symmetry and a more complex digestive system than Cnidarians. All 100 species are marine, mainly planktonic. Phylum Rhombozoa Simple, microscopic organisms that live as internal parasites in the kidneys of cephalopods. They have complex life cycles, and the group is sometimes considered a class of the phylum Mesozoa, along with the Orthonectida. About 65 species. Phylum Orthonectida About 20 species of simple, small organisms that are internal parasites of various marine worms, mollusks, and echinoderms. Phylum Platyhelminthes The flatworms, bilaterally symmetrical worms with three cell layers and distinct tissues, but no body cavity (coelom) and guts with only one opening. Most of the approximately 18 000 species are parasites in a wide range of hosts, but there are many free-living forms in all environments. Class Turbellaria. Free-living flatworms that are mainly predators or scavengers of other small organisms. Most are hermaphroditic. About 4500 species, including many marine forms. Class Monogenea. Ectoparasitic flatworms, mainly on skin or gills of marine fishes. Although previously included in the Trematoda, this group now appears to be evolutionarily distinct. About 1100 described species, but possibly many more. Class Trematoda. Parasitic flatworms or flukes, having digestive systems and complex life cycles, often among alternating hosts. There are about 8000 species of flukes, which infect both invertebrate and vertebrate hosts and cause some human diseases. Class Cestoda. Tapeworms; parasitic, segmented flatworms that lack digestive systems and live in the alimentary tracts of vertebrate hosts, including humans. About 5000 species, some in marine fishes or turtles. Phylum Nemertea Ribbon worms; long unsegmented worms with a complete digestive tract and a large cavity containing a proboscis that can be extended to sample the environment or capture prey. There are about 900 species, mainly benthic marine forms, but some freshwater or terrestrial. Phylum Gnathostomulida Minute, wormlike animals that live interstitially in marine sands and sediments. They feed on bacteria and protozoa using a specialized jaw, and are hermaphroditic. About 100 described species, but probably many more undiscovered. Phylum Gastrotricha Small wormlike organisms in freshwater and marine environments, living in sediments or on plants or animals. They feed on bacteria, protozoa, and detritus, using cilia to collect particles. About 500 species, half of them marine. Phylum Rotifera Small aquatic organisms with ciliated structures and complex jaws at the head. They have internal organs and complete guts, and feed either on particles or on small animals. Reproduction is sexual, but males are rare or unknown in many species. Of the 2000 species only about 50 are marine. Phylum Kinorhyncha Small, segmented animals with external spines that live interstitially in marine sediments or on the surfaces of seaweeds or sponges. There are about 150 species known. Phylum Loricifera Microscopic marine animals encased in a covering of spiny plates called a lorica, into which the head and neck can retract. Described only in 1983, the 10 known species of loriciferans live between and clinging to sand grains. Phylum Acanthocephala Parasitic worms in the guts of vertebrates, where they anchor to the intestine wall by spines on their head. About 1100 species., some living in marine fishes, turtles, and mammals.
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Phylum Cycliophora Described in 1995, this phylum comprises one known species, a microscopic animal that lives attached to the mouthparts of lobsters and collects particulate food. The life cycle is unusual and complex, with sexual and asexual stages. Phylum Entoprocta Small filter-feeding animals on stalks that live attached to various substrates either as single organisms or as colonies. A ring of ciliated tentacles surrounds the mouth and anus and creates water currents to collect food. About 150 species, all but one marine. Phylum Nematoda Roundworms; unsegmented worms with a layered cuticle, which molts during growth. Nematodes are among the most ubiquitous and numerous animals on Earth. They live in all environments and as parasites of most plants and animals. Of the 16 000 described species, a few thousand are marine. It is likely that many times more species exist. Phylum Nematomorpha Long, wiry, unsegmented worms, sometimes called horsehair worms. The gut is reduced or absent. Larval stages are internal parasites in arthropods and adults do not feed at all. A few of the 325 species are marine. Phylum Bryozoa Also called the Ectoprocta, a group of small colonial organisms that filter-feed using a tentaculate structure called the lophophore. Individual bryozoans are encased in tubular or boxlike housings and reproduce asexually to produce encrusting or plumose colonies attached to hard substrates. About 5000 species, all but 50 are marine. Phylum Phoronida Phoronids are tube-dwelling marine worms that also use a lophophore to collect particulate food. They are common in mud or sand, or attached to rocks or pilings. About a dozen widely distributed species are known. Phylum Brachiopoda Brachiopods are lophophorate, filter-feeding animals whose bodies are enclosed in bivalve shells. Most live secured by a stalk to hard substrates or in sediments, at depths from intertidal to 4000 m. Only about 335 living species, but over 30 000 fossil ones known. The living genus Lingula dates back over 400 million years. Phylum Mollusca A large and diverse phylum containing the familiar clams, snails, squid, and octopus. Mollusks possess mantle tissue that secretes a carbonate shell around the body, a belt of teeth called the radula for feeding, and a muscular foot variously modified for digging, crawling, or swimming. A diverse, widespread, and economically important group, mollusks have a long and complex taxonomic history, with between 50 000 and 100 000 described species. Most mollusks are marine but there are many freshwater and terrestrial snails Class Monoplacophora. Small, single-shelled animals living on hard surfaces, usually in the deep sea. Primitive in structure and thought to be similar to ancestral forms. Only 11 known species. Class Aplacophora. Small wormlike animals with calcareous spicules but no true shell. They lack the typical molluscan foot, but creep with cilia. About 250 species are known from various benthic marine environments. Class Caudofoveata. Shell-less wormlike animals that live in burrows in deep-sea sediments. Little is known of the ecology of the 70 known species. Class Polyplacophora. The chitons; mollusks having a shell of eight overlapping, articulating plates. All are marine and most live on intertidal or subtidal rocks, where they feed by scraping algae with their radulas. About 600 species. Class Gastropoda. The largest and most diverse class of mollusks, gastropods include aquatic and terrestrial snails, slugs, limpets, and nudibranchs. In most, the body sits on a muscular foot used for
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locomotion, and is enclosed in a conical or coiled shell. Gastropods may be filter feeders, grazers, or predators. By various counts there are 40 000 to 80 000 species, about half of them marine. Class Bivalvia. Bivalves or Pelecypods, mollusks with the body enclosed between two valves or shells hinged together, and closed by an adductor muscle. Most are filter feeders, drawing water into the shell cavity and filtering particles from it. Some bivalves attach to surfaces; others burrow into sediments. Most of the 8000 species are marine. Class Scaphopoda. Mollusks with a conical, tusk-shaped shell that is open at both ends. Scaphopods burrow into marine sediments and collect small food organisms with specialized tentacles. About 350 species. Class Cephalopoda. Squid, octopus, and Nautilus; in cephalopods the molluscan foot is modified into tentacles surrounding the mouth. Cephalopods are actively swimming predators with highly developed nervous and sensory systems. Nautilus and most extinct cephalopods have external chambered shells, while squid have reduced internal skeletons and octopus have none. All 650 species are marine. Phylum Priapulida Marine worms that burrow into sediments with only their mouths exposed at the surface. They are predatory on other small worms. The 10 known species live from estuarine to abyssal environments. Phylum Sipuncula About 320 species of unsegmented marine worms, with a retractable proboscis called the introvert. They are benthic, often living in sediments or among other animals. Tentacles around the mouth collect detritus and other particulate food. Phylum Echiura Unsegmented, benthic marine worms having an extensible proboscis that is used to collect detrital food. They live mainly within burrows in sediments. Considered by some to be a class of the Annelida. About 140 species. Phylum Annelida Segmented worms, a large group of diverse species, most having bodies divided into segments by internal septa, and with chitinous setae on the exterior body. There are about 12 000 species of annelids, in all aquatic and terrestrial environments. Class Polychaeta. Worms usually with distinct head region, numerous setae and paddle- or leg-like parapodia for locomotion. The group includes mobile, burrowing, attached, and symbiotic forms, feeding as predators, scavengers, filter or deposit feeders. About 8000 species, almost all marine. Class Oligochaeta. Worms lacking parapodia and with few setae; terrestrial forms include earthworms. Most of the 3100 species are freshwater or terrestrial. Class Hirudinea. Leeches; the body is not segmented internally and lacks setae on the exterior. Most are ectoparasites, feeding on blood of other animals, but some are predators. About 500 species, many marine. Phylum Tardigrada Water bears; minute animals with eight short legs that live in aquatic or moist terrestrial environments and suck juices from plants or animals. They are able to remain in a dried state for long periods, returning to active metabolism on rehydration. About 550 species, a few of them marine. Phylum Arthropoda The arthropods, or jointed-leg animals, are one of the most successful and widespread metazoan groups. All possess segmented bodies and articulated exoskeletons, which are molted during growth. Insects and arachnids are the dominant arthropods on land, but almost entirely absent from the sea, where crustaceans predominate. About 1 million described species, mostly insects, but many more probably exist. Class Merostomata. An ancient group of chelicerates now containing only 4 species of horseshoe crabs. They live in subtidal environments, and feed as predators and scavengers.
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Class Pycnogonida. Sea spiders; lacking the well-developed head, thorax, and abdomen of other arthropods. About 1000 species, entirely marine, which feed on body fluids of other animals and plants. Class Crustacea. Largely aquatic arthropods including copepods, amphipods, shrimp, barnacles, crabs, and lobster. Often with a calcified carapace covering the segmented body. All forms have a nauplius larva as the first of many molt stages. About 35 000 species, almost entirely marine, in all habitats. Phylum Pogonophora Thin, wormlike animals that live in tubes in sediment or attached to benthic surfaces. Pogonophorans lack digestive systems and obtain nutrition by absorption of dissolved organic nutrients. Pogonophorans are thought by some to be aberrant annelids. About 100 species, mostly in deep water. Phylum Vestimentifera Closely related to pogonophorans, these larger marine worms rely on symbiotic bacteria in their tissues to generate nutrition from the metabolism of inorganic chemical compounds. They are best known from deep-sea hydrothermal vents, where they can be over 2 m long. About a dozen species have been described. Phylum Echinodermata An entirely marine phylum including the sea stars, urchins, and brittle stars. All have a five-part radial symmetry, a water-vascular system, tube feet used for locomotion, respiration and feeding, and a skeleton made of minute calcareous ossicles or spicules. Over 6000 species. Class Crinoidea. Most ancient of the living echinoderms, crinoids have multiple pinnate arms used for filtering food particles from the water. Some are attached to the bottom by a stalk, others swim by movement of the arms. About 600 subtidal and deep-sea species. Class Asteroidea. The seastars, most with five radial arms, are slow-moving predators in intertidal and subtidal environments. About 1500 species. Class Ophiuroidea. Brittle stars, having five slender and flexible arms radiating from a central disk. Some are deposit or filter feeders, others predatory. About 2000 species, including many deep-sea forms. Class Concentricycloidea. Small discoidal organisms known only from submerged wood in the deep sea. They lack five-part symmetry and arms, and the body is covered by overlapping calcareous plates. Two known species. Class Echinoidea. Sea urchins; with a rigid, globular or flattened test made of calcareous ossicles and a complex mouth structure for grazing and chewing. Most are free-living in subtidal environments, but some burrow in sediments or rock. Approximately 950 species. Class Holothuroidea. Sea cucumbers; with an elongate, flexible body, bilateral symmetry and no arms. Most of the 1500 species are benthic deposit or filter feeders. Phylum Chaetognatha Arrow worms; planktonic marine organisms that are predatory on small zooplankton, using chitinous spines around the mouth to catch prey. The 100 species are mainly planktonic with a few benthic forms. Phylum Hemichordata Wormlike marine organisms that burrow in sediments or form colonies on hard substrates. Most are deposit or suspension feeders. About 100 species from shallow tropics to deep sea. Phylum Chordata A large and diverse phylum including the familiar vertebrates. All have a dorsal nerve cord that can form a brain, a notochord that becomes the vertebral column in vertebrates, and gill slits in the throat at some stage of development. Chordates live in all environments and are one of the most successful and widespread groups. Perhaps 45 000 species, about half marine forms (mainly fish).
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Subphylum Urochordata The tunicates; sessile or motile animals with the body enclosed in a tough, flexible tunic. Most are filter feeders. The notochord and dorsal nerve are seen only in larval stages, and sessile adults may be asymmetrical in form. About 3000 species, all marine. Class Ascidiacea. Sea squirts; sessile, filter-feeding tunicates that live mainly on hard benthic substrates. About 2700 species. Class Sorberacea. A small group of solitary, deep-sea tunicates that appear to prey on live organisms instead of filter-feeding. Class Larvacea. Minute planktonic tunicates (also called appendicularians) with small bodies and long tails. They filter feed using an external mucous structure that concentrates small particulate material for ingestion by the larvacean. About 200 species. Class Thaliacea. Pelagic tunicates with gelatinous, transparent bodies. They filter feed by creating a water current through their bodies. All have complex life-cycles with sexual and asexual, solitary, and colonial stages. About 100 species. Subphylum Cephalochordata Lancelets or ‘‘Amphioxus’’; small fish-shaped animals with notochords extending the length of the body. They burrow into substrates with the head end exposed and filter particulate food. About 20 species. Subphylum Vertebrata Chordates with a backbone replacing the notochord, and a distinct head region with brain. Approximately 42 000 species in all environments. Class Agnatha. Lampreys and hagfish; eel-like jawless fishes without scales, bones or fins. Most are scavengers or parasites on other fish. About 60 marine and freshwater species. Class Chondrichthyes. Sharks and rays; fish with cartilaginous bones and small denticle scales embedded in the skin. The 850 species are virtually all marine. Class Osteichthyes. The bony fishes; having bone skeletons, scales and often air bladders for buoyancy. Highly diverse and widely distributed in all marine and freshwater habitats, with about 25 000 species. Class Reptilia. Turtles, snakes and lizards. Most of the 6000 species are terrestrial except for a few marine turtles, crocodiles, and snakes. Class Aves. Birds; about 9000 species in all terrestrial habitats and many marine forms including penguins, albatrosses, gulls, etc. Class Mammalia. Four legged, endothermic animals usually with fur or hair, which mainly give live birth and suckle the young. Most of the 4500 species are terrestrial; marine forms include whales, dolphins, seals, and otters.
Further Reading Atlas RM (1997) Principles of Microbiology. Dubuque, IA: William C. Brown. Brusca RC and Brusca GJ (1990) Invertebrates. Sunderland, MA: Sinauer Associates. Cavalier-Smith T (1998) A revised six-kingdom system of life. Biological Reviews of the Cambridge Philosophical Society 73: 203--266. Margulis L, Corliss JO, Melkonian M, and Chapman DJ (1990) Handbook of Protoctista. Boston: Jones and Bartlett. Margulis L and Schwartz KV (1988) Five Kingdoms: An Illustrated Guide to the Phyla of Life on Earth. NewYork: WH Freeman. Nielsen C (1995) Animal Evolution: Interrelationships of the Living Phyla. Oxford: Oxford University Press. Patterson DJ (1999) The diversity of eukaryotes. American Naturalist 154(supplement): S96--S124.
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APPENDIX 9. TAXONOMIC OUTLINE OF MARINE ORGANISMS
Pechenik JA (2000) Biology of the Invertebrates. Boston: McGraw-Hill. Williams DD (2000) Invertebrate Phylogeny. Scarborough: CITD Press, University of Toronto. CD ROM.
Websites ‘‘Microscope’’: http://www.mbl.edu/baypaul/microscope/general/page_01.htm ‘‘Tree of Life’’ http://phylogeny.arizona.edu/tree/phylogeny.html
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APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS
Chart 1 Bathymetric chart of the Arctic Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
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APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 90°W
60°W
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30°E
60°N
30°N
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Chart 2 Bathymetric chart of the North Atlantic Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
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APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 60°W
30°W
0°
30°E 0°
30°S
60°S
Chart 3 Bathymetric chart of the South Atlantic Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
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APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 30°E
60°E
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30°S
60°S
Chart 4 Bathymetric chart of the Indian Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
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416 180°
APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 150°W
120°W
90°W
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30°N
0°
Chart 5 Bathymetric chart of the North-east Pacific Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
(c) 2011 Elsevier Inc. All Rights Reserved.
APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 120°E
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Chart 6 Bathymetric chart of the North-west Pacific Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
(c) 2011 Elsevier Inc. All Rights Reserved.
418 180°
APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 150°W
120°W
90°W 0°
30°S
60°S
Chart 7 Bathymetric chart of the South-east Pacific Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
(c) 2011 Elsevier Inc. All Rights Reserved.
APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 120°E
150°E
180°
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150°W 0°
30°S
60°S
Chart 8 Bathymetric chart of the South-west Pacific Ocean. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
(c) 2011 Elsevier Inc. All Rights Reserved.
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APPENDIX 10. BATHYMETRIC CHARTS OF THE OCEANS 120°E
150°E
180°
150°W 30°N
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30°S
60°S
Chart 9 Bathymetric chart of Ocean surrounding Australia and New Zealand. Based on the World Sheet of the General Bathymetric Chart of the Oceans (GEBCO), published by the Canadian Hydrographic Service, Ottawa, Canada, 1984; reproduced with permission of the International Hydrographic Organization and the Intergovernmental Oceanographic Commission (of UNESCO) (see http://www.ngdc.noaa.gov/mgg/gebco). The GEBCO bathymetry is currently maintained and updated through the GEBCO Digital Atlas which is published periodically on CD-ROM by the British Oceanographic Data Centre (see http://www.bodc.ac.uk).
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INDEX Notes Cross-reference terms in italics are general cross-references, or refer to subentry terms within the main entry (the main entry is not repeated to save space). Readers are also advised to refer to the end of each article for additional cross-references - not all of these cross-references have been included in the index cross-references. The index is arranged in set-out style with a maximum of three levels of heading. Major discussion of a subject is indicated by bold page numbers. Page numbers suffixed by T and F refer to Tables and Figures respectively. vs. indicates a comparison. This index is in letter-by-letter order, whereby hyphens and spaces within index headings are ignored in the alphabetization. For example, ‘oceanography’ is alphabetized before ‘ocean optics.’ Prefixes and terms in parentheses are excluded from the initial alphabetization. Where index subentries and sub-subentries pertaining to a subject have the same page number, they have been listed to indicate the comprehensiveness of the text. Abbreviations used in subentries AUV - autonomous underwater vehicle CPR - continuous plankton recorder d18O - oxygen isotope ratio DIC - dissolved inorganic carbon DOC - dissolved organic carbon ENSO - El Nin˜o Southern Oscillation MOC - meridional overturning circulation MOR - mid-ocean ridge NADW - North Atlantic Deep Water POC - particulate organic carbon ROV - remotely operated vehicle SAR - synthetic aperture radar SST - sea surface temperature Additional abbreviations are to be found within the index.
A A222, definition, 6:242 A226, definition, 6:242 A230, definition, 6:242 A234, definition, 6:242 0 A234, definition, 6:242 A235, definition, 6:242 AAAS (American Association for the Advancement of Science), 3:413 AABW see Antarctic Bottom Water (AABW) AAIW see Antarctic Intermediate Water (AAIW) Aanderaa RCM4 deep ocean rotor-vane instrument, 5:429F Aanderaa RCM8 current meter, 5:430T
Aanderaa RCM9 current meter, 5:429F, 5:430T AASW see Antarctic Surface Water (AASW) Abalone (Haliotis spp.) harvesting, 3:902–903 mariculture, 3:903–904, 3:904, 3:905F shell see Mother-of-pearl (nacre) stock enhancement/ocean ranching programs, 4:147T, 4:151–152, 4:152F Abbott’s booby, 4:373 see also Sulidae (gannets/boobies) ABE see Autonomous Benthic Explorer ABE Autonomous Benthic Explorer (AUV), 2:26F, 2:34, 2:35F, 4:474F ABF (Angola–Benguela Front), 1:326 Abiki, 5:344, 5:349
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Abiotic processes, regime shift drivers, 4:717 Abrolhos Islands, 3:444F, 3:445, 3:446 Abrupt climate change see Climate change, abrupt ABS see Acoustic backscatter system (ABS) Absolute humidity, definition, 2:325T Absolute salinity, 4:30 Absolute surface temperature, 5:127 Absolute velocity, nutrient fluxes and, inverse modeling, 3:302–304 Absolute velocity profiler, 2:292F Absolute vorticity conservation of, 4:781–782, 4:782F definition, 4:781–782 subtropical gyres, 6:351
422
Index
Absorbance (of EM radiation by a compound), 1:7–8 see also Absorbance spectroscopy Absorbance spectroscopy, chemical sensors, 1:7–14 background subtraction, 1:12 basic principles, 1:7–8 molecular recognition element, 1:10–11 optical fibers for, 1:8–9 optoelectronics, 1:9–10 reagent support material, 1:10 response characteristics, 1:10–11 sensor design, 1:11 see also Absorption spectra; Optical fibers; Reflectance spectroscopy Absorption (optical) coefficient, 3:244–245, 4:733, 6:109–110 components, 4:734 definition, 4:621 detritus, 3:245 gelbstoff, 3:245 Hydrolight simulation, 4:625–626, 4:625F oceanic water, 1:389F, 1:390–391 as bio-optical model quantity, 1:386T, 1:387 phytoplankton, 3:245 pure sea water, 3:245 sewage plume waters, 3:248–249, 3:251F see also Ocean optics Absorption spectra chlorophyll, 5:116F compared with fluorescence spectra, 2:582F gelbstoff, 4:734, 5:116F Abundance/biomass comparison (ABC) method, 4:536 ABW see Arctic Bottom Water (ABW) Abyssal, definition, 4:651 Abyssal circulation global pattern, 2:80, 2:81F see also Abyssal currents Abyssal currents, 1:15–30 Deep Western Boundary Currents see Deep Western Boundary Current (DWBC) diffusivity, 1:16, 1:18F, 1:19F cross-isopycnal, 1:16, 1:19F cross-isothermal, 1:16, 1:18F recirculation cells, 1:16–18, 1:20F, 1:29–30 Stommel–Arons concept, 1:16–18, 1:18F, 1:29 water sources, 1:18–26, 1:20F, 1:21F entrainment, 1:21F, 1:24 salinity distribution, 1:23F, 1:24F temperature distribution, 1:21F, 1:24 water sinks, 1:20–24, 1:20F see also specific currentssee specific oceans Abyssal depths, 4:126, 4:128 Abyssal gigantism, 1:354–355 Abyssal hills definition, 3:864–865 development models, 3:865F
horst/graben model, 3:865–866, 3:865F split volcano, 3:864–865, 3:865F whole volcano, 3:864–865, 3:865F East Pacific Rise (EPR), 3:865–866 fast-spreading ridges, 3:865–866, 3:865F lava flows elongate pillows, 3:865F syntectonic, 3:865–866, 3:865F magma supply, 3:864–865 propagation, 3:865–866, 3:866F slow-spreading ridges, 3:864–865 structure, 3:865–866 volcanic growth faults, 3:865–866, 3:865F Abyssal pelagic zone, 2:216 Abyssal plain, 5:463 Abyssal waters, 6:296–297, 6:296F mixing, 2:263–266, 2:268F see also Antarctic Bottom Water Abyssal zone, 1:351T, 1:354, 1:355 Acanthaster planci (crown-of-thorns starfish), 1:669 Acartia spp. copepods, 3:658 Acartia tonsa (copepod), 4:440, 4:441F Eurytemora affinis and, population interaction models, 4:554 ACC see Antarctic Circumpolar Current (ACC) Accelerator mass spectrometry (AMS), 3:881–883, 4:85, 4:640, 5:330–331 cosmogenic radionuclide tracers and, 1:684 data, 5:420 radiocarbon, 5:420 sample size, 5:423 Accelerometer, expendable bottom penetrometer probe (XBP), 2:348 Accessory pigments, 2:582 Accretionary prisms, 1:31–37 blueschists, 1:33, 1:33F chemosynthetic organisms, 1:34 erosion and redeposition, 1:32–33 faulting, 1:32–33, 1:35 decollement, 1:32, 1:32F, 1:35 fluid flow paths, 1:32F, 1:34 fluid pressure-related weakening, 1:34 fluids, 1:34 chemical composition, 1:34 expulsion, 1:32F, 1:34 fluid pressure-related weakening, 1:34 hydrocarbon formation, 1:32, 1:34 mineral dissolution, transport and precipitation, 1:34 sediment water content, 1:34 seismic reflection, 1:34 wedge theory, 1:35 geothermal gradients, 1:33, 1:34 hydrogen sulfide, 1:34 material origin and variation, 1:31–32 Cascadia subduction zone, 1:31–32 Marianas subduction zone, 1:31–32
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mechanics, 1:35 critical Coulomb wedge theory, 1:35, 1:35F fluid pressure, 1:35 melanges, 1:31, 1:33, 1:33F methane, 1:34 non-accretionary plate boundaries, 1:35–36, 1:36F landslides, 1:36 tectonic erosion, 1:35–36, 1:36F seafloor sediment accumulation, 1:32–33 offscraped deposits, 1:32, 1:32F, 1:36 supply, 1:31–32, 1:36 underplated deposits, 1:32, 1:32F, 1:36 underthrust sediments, 1:31F, 1:32, 1:32F, 1:33, 1:35–36, 1:36F water content, 1:34 seismic structure, 1:34 seismogenesis, 1:34–35 serpentine, 1:32 shape, 1:31, 1:35 solid material transfer, 1:32–34 stratigraphic record, 1:31–32 structure, 1:31–32, 1:31F, 1:32F decollement, 1:32, 1:32F, 1:35 melting zone, 1:31F, 1:32 mud volcanoes, 1:32, 1:32F thrust belts, comparison with, 1:33–34 volcanic arc magmas, 1:31F, 1:32 see also Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge seismic structure; Mid-ocean ridge tectonics, volcanism and geomorphology; Seismic structure Acetylcholine esterase, pesticide sensors and, 1:13 Acidification, threat to cold-water coral reefs, 1:624 Acid rain, seabirds and, 5:277 Ac-meters, 3:246 ACMRR (Advisory Committee on Marine Resources Research), 5:513 Acorn barnacle (Semibalanus balanoides), 1:332, 4:763 Acoustical systems see Acoustic systems Acoustic backscatter, diffuse seafloor flows, 1:71–72 temporal correlation, 1:72–73 Acoustic backscatter system (ABS), 1:39, 1:39F STABLE II, 1:46, 1:47 Acoustic Doppler current meters, 5:429–431, 5:429F, 5:430T, 6:153 North Sea measurements, 4:76, 4:78, 4:81 Acoustic Doppler current profiler (ADCP), 1:42, 3:450F, 3:451–454, 3:453F, 6:202–203, 6:262 hurricane Ivan, 6:203F internal waves, 3:268–269 see also Moorings; Single Point Current Meters
Index Acoustic Doppler velocimeter (ADV), 1:42 Acoustic floats, 2:174, 2:176–177 Acoustic imaging, high-frequency, 5:352 Acoustic measurement, sediment transport, 1:38–51 see also Sediment transport, acoustic measurement Acoustic modems, and moorings, 3:927, 3:927F Acoustic navigation autonomous underwater vehicles (AUV), 4:478 see also Sonar Acoustic navigation systems, manned submersibles (deep water), 3:509 Acoustic noise, 1:52–61 ambient noise, 1:52 active sonar systems, 5:505 measurement data, 1:52, 1:53F high frequency band (HF) see High frequency band (HF) hydrophone flow noise, 1:55 low frequency band (LF) see Low frequency band (LF) microseism noise, 1:54 midfrequency band (MF) see Midfrequency band (MF) molecular noise, 1:53F, 1:60 prevailing noise, definition, 1:52 reflection, 1:58 scattering, 1:56, 1:58 sources, 1:52 atmospheric turbulence, 1:54–55, 1:55 distant shipping see Ship(s) molecular agitation, 1:53F, 1:60 spatially discrete, 1:52 temporally intermittent, 1:52 wave–wave interactions see Wave–wave interactions whale vocalizations, 1:55, 1:56–57 wind driven sea surface processes see Wind-driven sea surface processes swell, 1:54 topographic influences, 1:56 transmission loss, 1:55–56, 1:56F ultralow frequency band (ULF) see Ultralow frequency band (ULF) Urick, R J, 1:52 vertical line array (VLA) data, 1:57F, 1:58–59, 1:59 very low frequency band (VLF) see Very low frequency band (VLF) waveguide, 1:54, 1:57–58, 1:58, 1:58–59 Wenz, G M, 1:52, 1:53F wind see Wind-driven sea surface processes; Wind speed see also Acoustics, Arctic; Acoustics, deep ocean; Acoustics, shallow water; Ship(s) Acoustic rays diffraction, 6:41–42 refracted-refracted, 6:42 refracted-surface-refracted, 6:42
sampling properties, 6:45, 6:46F travel time, 6:42–43, 6:43 vertical travel-time ambiguity, 6:53F Acoustic release, moorings, 3:920 Acoustic remote sensing, 1:83–86 characteristic shallow water signal, 1:84, 1:84F data inversion, 1:87–88 experiment setup, 1:87F geophone arrays, 1:87–88, 1:87F, 1:88F interface waves, 1:84F, 1:89 dispersion diagram, 1:89, 1:89F reflected waves, 1:84–86 angle of intromission case, 1:86–87 critical angle case, 1:85F, 1:86 grazing angle, 1:75, 1:84–86, 1:84F, 1:85F half-space seafloor, 1:84–86, 1:84F layered seafloor, 1:86F, 1:87, 1:87F phase shift, 1:86–87, 1:86F reflection coefficient, 1:84–86, 1:86–87, 1:86F reflection loss, 1:86F, 1:87, 1:87F refracted waves, 1:84F, 1:87–89 Herglotz-Bateman-Wieckert integration, 1:88–89, 1:89F Acoustic ripple profiler (ARP), 1:39, 1:39F, 1:40, 1:40F, 1:46, 1:50F 3-D, 1:40, 1:41F, 1:50 bed profile, 1:47F Acoustic ripple scanner (ARS), 1:38–39, 1:39F, 1:40, 1:41F Acoustics deep ocean see Acoustics, deep ocean icebergs, 3:188 sediments see Acoustics, marine sediments shallow water see Acoustics, shallow water small area bathymetry, 1:298–299 underwater, history, 3:122 see also Acoustic rays; Acoustic scattering (marine organisms) Acoustics, Arctic, 1:92–100 acoustic environment, 1:101 acoustic modes, 1:96–97, 1:97–98 current research, 1:99 history, 1:92–94 modal dispersion, 1:98F noise, 1:98–99 sound propagation, 1:95–98, 1:98F sound speed structure, 1:94–95 transmission loss, 1:96F variability, 1:95 Acoustics, deep ocean, 1:101–111 noise, 1:107–109 noise spectra, 1:108F reflection, 1:105F refraction, 1:103 scattering, 1:105–107 sonar equation, 1:109–110 sound propagation, 1:102 bottom loss, 1:104 Lloyd mirror effect, 1:102, 1:102F long-range, 1:102–103 models, 1:104–105, 1:106F
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paths, 1:103F short-range, 1:102 spreading loss, 1:103 volume attenuation, 1:103–104, 1:104F units, 1:101–102 Acoustics, marine sediments, 1:75–91 attenuation, 1:76–78, 1:80, 1:82, 1:90 Biot-Stoll model see Biot-Stoll model bulk density, 1:78, 1:78T, 1:80 bulk modulus, 1:78, 1:78T, 1:80 forward modeling, 1:90, 1:90F measurement of geoacoustic parameters, 1:80–81 in situ techniques see In situ measurement techniques laboratory, sediment core samples see Sediment core samples remote sensing see Acoustic remote sensing transmission loss technique, 1:89–90, 1:90F relationship between geoacoustic parameters, 1:81 porosity and relative compressional wave velocity, 1:81, 1:82F relative density and porosity, 1:81, 1:81F SAFARI, 1:90, 1:90F seafloor roughness, 1:80 sedimentary acoustic medium, 1:75, 1:78 sediment structure, 1:75, 1:75–76 composition, 1:75, 1:76F density, 1:75–76, 1:76F, 1:81, 1:81F deposition, 1:75 fluid saturation, 1:76–78 layering, 1:75, 1:75–76, 1:77F, 1:78–79, 1:79, 1:86F, 1:87 porosity, 1:76–78, 1:81, 1:81F, 1:82F sediment transport, 1:75 sediment type clay, 1:90F mud, 1:83T sand, 1:82F, 1:83T, 1:90F seismo-acoustic waves see Seismoacoustic waves shear modulus, 1:78, 1:78T, 1:84–86 water-sediment interface, seismoacoustic waves in, 1:78–79, 1:79F see also Acoustics, deep ocean; Acoustics, shallow water; Benthic boundary layer (BBL); Calcium carbonate (CaCO3); Clay minerals; Ocean margin sediments; Pore water chemistry; Seismic structure Acoustics, shallow water, 1:112–119 acoustic environment, 1:112–113 low-frequency cutoff, 1:117 modeling, 1:118–119, 1:119F ray paths, 1:112–113, 1:113F, 1:118F time domain, 1:118 geometrical dispersion, 1:118 measured pulse arrivals, 1:118, 1:118F time dispersion, 1:118
424
Index
Acoustics, shallow water (continued) transmission loss, 1:113–114 bottom reflection, 1:114–115, 1:115F boundary scattering, 1:115–116 data, 1:116–118 frequency dependence, 1:117–118, 1:117F geometrical spreading, 1:114 seasonal variability, 1:112–113 seawater attenuation, 1:114 variability, 1:117F Acoustic scattering (marine organisms), 1:62–70 area backscattering coefficient, 1:64 bandwidth, 1:70 bistatic cross-section, 1:63–64 challenges, 1:69 clams, 1:69 extinction cross-section, 1:64, 1:67 fish, 1:64–65 groups of organisms, 1:64 historical overview, 1:62 imaging, 1:70 jellyfish, 1:68–69 mammals, 1:69 organism classification, 1:63 orientational sensitivity and frequency, 1:65 parameters, 1:63 extrinsic, 1:63 intrinsic, 1:63 physical basis, 1:62–63 quantification, 1:63 measurement, 1:63–64 modeling, 1:63–64 nomenclature, 1:63 single organisms, 1:63–64 squid, 1:68 target strength, 1:64 volume scattering coefficient, 1:64 zooplankton, 1:67 gas-filled bodies, 1:68 hard-shelled, 1:67–68 liquid-like, 1:67 Acoustic scintillation thermography (AST), 1:71–74 application, 1:72–74 error, 1:74 method of operation, 1:71–72, 1:71F noise, 1:73 temporal correlation, 1:72–73 flow characteristics and, 1:73 Acoustic survey work, sensors, towed vehicles, 6:73–74 Acoustic systems high-frequency, zooplankton sampling, 6:368 oceanographic research vessels, 5:412 Acoustic Thermometry of Ocean Climate (ATOC), 6:54 Acoustic tomography, internal tides, 3:263–264 Acoustic transponder navigation, 6:262–263, 6:265 Acoustic travel time (ATT) current meters, 5:430T, 5:432–433, 5:434F
applications, 5:433 disadvantages, 5:433 techniques, 5:433 Acoustic waves, 5:138 sediment interaction see Acoustics, marine sediments; Biot-Stoll model ‘Acqua alta,’ Italy, 5:532 Actinium bottom water excess, 6:252–253 concentration depth profile, 6:253F seawater, 6:252–253 Actinium-227 (227Ac), 6:240 Actinologica Britannica (Gosse), 1:615, 1:615F Actinomycetes definition, 3:574 marine-derived, 3:571 Actinopterygii (ray-finned fishes), 2:468 Active layer, definition, 5:559–560 Active sensors, 3:108 Active sonars see Sonar systems, active sonar Active systems aircraft for remote sensing see Aircraft for remote sensing pump and probe fluorometry see Fluorometry, biological sensing Activity (A), definition, 4:82–83 Adaptations Antarctic fishes, 1:191–192 benthic boundary organisms, 1:332–333 benthic organisms, 1:348–349 bioluminescence, 4:5 demersal fishes, 2:460, 2:461 eels, 2:211 fish, 2:473 fish hearing, 2:479 fish locomotion, 2:394, 2:395–396F fish vision, 2:445 gelatinous zooplankton, 3:9 intertidal fishes, 3:280–281 mangroves, 3:496, 3:498F anaerobic soils, 3:496–497 salinity, 3:496 seeds/seedlings, 3:497–498 mesopelagic fishes, 3:751–754 micronekton, 4:5–6 noise masking, 3:630 salt marsh vegetation, 5:39 sandy beach macrofauna, 5:54–55 ADCP see Acoustic Doppler Current Profiler (ADCP) Adductors, 4:275 Adelie coast, 4:127–128 Ade´lie penguin (Pygoscelis adeliae), 5:522T, 5:525, 5:526F breeding age, 5:251–252 response to climate change, 5:261, 5:261F, 5:262F prehistoric, 5:257–258 see also Pygoscelis Aden, Gulf of see Gulf of Aden Adenosine triphosphate (ATP), 6:82–83, 6:85 ADEOS-I see Advanced Earth Observing Satellite
(c) 2011 Elsevier Inc. All Rights Reserved.
ADEOS II (Advanced Earth Observing Satellite II), 5:82 Adhemar, Joseph Alphonse, 4:504 Adiabatic lapse rate, seawater, 6:382 Adiss, definition, 6:242 ADJEX see Arctic Ice Dynamics Joint Experiment (ADJEX) Adjoint data assimilation, 1:366, 1:368–369 identical twin experiments and, 1:368–369 multiple parameter sets, 1:369 Adjoint equation, 2:7 ‘Adjoint method,’ data assimilation in models, 2:7 Adjustable proportion fluid mixture (APFM), 4:169 Administrative costs, marine protected areas, 3:676, 3:676F Admiralty law, 3:432 Law of the Sea distinguished from, 3:432 see also National Control and Admiralty Law Adriatic deep water, 1:751 Adriatic Sea hypoxia, historical data, 3:174 Mediterranean Sea circulation and, 3:714–715 Advanced ATSR (AATSR), 5:102 Advanced Earth Observing Satellite (ADEOS), 5:203 ocean color sensors, 5:118T Advanced Earth Observing Satellite II (ADEOS II), 5:82 Advanced Land Observing Satellite (ALOS), 5:103 Advanced microstructure profiler, 2:292F Advanced Microwave Scanning Radiometer (AMSR), 4:543, 5:82, 5:206 Advanced microwave sounding unit (AMSU-A), 5:207 Advanced piston corer (APC), 2:40, 2:41F operation, 2:52 Advanced Scatterometer (ASCAT), 5:203, 5:204T Advanced Very High Resolution Radiometer (AVHRR), 1:250, 4:543, 5:92, 5:94–95, 5:380 channels, 5:94 day-time contamination by reflected sunlight, 5:94 evaporation, estimation of, 2:329 non-linear SST and Pathfinder SST, 5:92–93 operating method, 5:94 post-process data, 5:92–93 scan geometry, 5:94–95, 5:95F Advection, 4:102, 6:165 definition, 3:774 horizontal, inversion formation and, 6:223–224 kinetic energy budget and, 2:263 ocean–atmosphere interactions, 2:244 pore water, 4:568
Index through surface sediments, and benthic flux measurements, 4:485 turbulent diffusion in maintenance of ocean thermocline, 4:208 Advection–diffusion balance, 4:732–734 Advection–diffusion equation, general circulation models, 3:20 Advection–diffusion models, chemical tracers and, 4:107 Advection–diffusion-reaction equation, small-scale patchiness models, 5:474, 5:476, 5:478, 5:481 Advective feedback, 1:3 Advective fluxes, upper ocean, 6:165 Advective salinity preconditioning, definition, 3:712–714 Adventure Bank Vortex (ABV), 2:5 Advisory Committee on Marine Resources Research (ACMRR), 5:513 ADW (Adriatic deep water), 1:751 Aegean Deep Water (AGDW), 3:713F formation, 3:712–714 A–E index (Ammonia parkinsoniana over Elphidium spp.), 3:177 hypoxia, 3:177 Aelotron, 1:154T Aeolian inputs, 1:120–127 fluvial inputs vs., 1:120 land–sea exchange, compounds see Land–sea global transfers marine sedimentation, influence on, 1:120 to sea surface, via atmosphere, 1:120 see also specific aeolian materials Aequorea aequorea, 4:705–707 Aerial traps, 2:541 Aerobic denitrification, 4:34–35 see also Denitrification Aerobic diving limit (ADL), marine mammals, 3:585, 3:585F Aerodynamics, towed vehicles see Towed vehicles Aerosol optical thickness (AOT), 1:250 global description, 1:251F Aerosols anthropogenic, 1:248 atmospheric, infrared atmospheric correction algorithms, SST measurement, 5:93 atmospheric transport, 1:248–257 cloud formation and, 3:401–403 composition, 1:249 concentration by location, 1:249T deposition, 1:250 dry, 1:252 mineral dust and Eolian iron, 1:252–254 nitrogen, 1:255–257 to oceans, 1:252–254 trace elements, 1:254 trace elements transported by rivers vs atmosphere, 1:254–255 wet, 1:250–252 wet/dry, estimation, 1:250 see also Mineral dust, deposition
from gas-phase reactions, 1:249 marine, conservative element levels in sea water and, 1:628 particles, atmospheric contaminant deposition, 1:238–239 particle size, 1:249 dry deposition rate, 1:252 removal mechanisms, 1:250 sources, 1:248–250 spectral range for remote sensing, 4:735T see also Particulate nitrogen; individual components (e.g. dust, nitrogen) Aerosol veil, 1:120–121 Aethia, 1:171T reproduction, 1:174 see also Alcidae (auks); specific species Aethia cristatella (crested auklet), 1:171, 1:173F Aethia pusilla (least auklet), 1:171, 1:173F Africa anthropogenic reactive nitrogen, 1:244–245, 1:245T continental margins, sediments, 4:141–142 El Nin˜o and, 2:228 precipitation, 2:230–231 river water, composition, 3:395T south-western, Matuyama Diatom Maximum, productivity reconstruction, 5:341F, 5:342 African Humid Period, 3:127 African penguin, 5:522, 5:522T, 5:523, 5:527–528 see also Spheniscus AFS (American Fisheries Society), 2:525 Agassiz, Louis, 4:504 AGCMs see Atmospheric general circulation models (AGCMs) AGDW see Aegean Deep Water (AGDW) Age-structured population models, 4:548 equations, 4:549 see also Population dynamic models Aggregates, marine definition, 4:182 gravel extraction see Offshore gravel mining sand extraction see Offshore sand mining supply and demand outlook, 4:189 Aggregation(s) benthic boundary layer effects see Benthic boundary layer (BBL) foraging seabirds, 5:230 see also Seabird(s) krill see Krill (Euphausiacea) particle dynamics see Particle aggregation dynamics phytoplankton blooms, 4:334F, 4:336 Aglantha, 6:260T Agriculture, ocean thermal energy conversion, 4:172
(c) 2011 Elsevier Inc. All Rights Reserved.
425
Agulhas Bank, Agulhas Current meanders, 1:128, 1:129F, 1:133, 1:133F, 1:133T see also Agulhas Current, southern Agulhas Current, 1:128–137, 1:129F, 1:730, 6:347F flow variability, 4:118F historical aspects, 1:128 importance, 1:128 large-scale circulation, 1:128–130, 1:129F, 1:130F northern, 1:129F, 1:131–133 characteristics, 1:131, 1:132T deep-sea eddies, 1:133 Durban, 1:129F, 1:131–132, 1:131F, 1:133, 1:133–134 Natal Pulse, 1:132, 1:132F, 1:134, 1:137 Port Elizabeth, 1:129F, 1:131, 1:133T spatial velocity structure, 1:131F retroflection, 1:134–135 loop, 1:134 ring shedding see Agulhas rings mesoscale variability, 1:134, 1:134F thermohaline characteristics, 1:132T, 1:134 rogue waves, 4:779 sources, 1:129F, 1:130–131, 1:130F southern, 1:133–134 filaments, 1:129F, 1:134 meanders, 1:129F, 1:133 sea surface temperatures, 1:133 shear-edge eddies, 1:133, 1:133F, 1:133T surface plumes, 1:133, 1:133F, 1:133T, 1:134 Tropical Surface Water, 1:133–134 volume flux, 1:133–134 wave propagation, 5:577 see also Ocean circulation Agulhas Return Current, 1:128, 1:135–136 Subtropical Convergence and, 1:128, 1:135–136, 1:136F, 1:136T Agulhas rings, 1:129F, 1:134, 1:135T, 3:119 Benguela Current system, 1:719F, 1:721, 1:726 physical properties, 1:134, 1:135T role in interbasin exchange of waters between South Indian and South Atlantic Oceans, 1:134–135, 1:135T Ahermatypic, definition, 1:677 AIDJEX experiment, 1:691–692 Air bubble entrainment breaking waves, 1:433 see also Bubble clouds; Bubbles density, 2:324 entrapment of, bubbles, 1:440 pollution coral impact, 1:674 see also Pollutants; Pollution temperature Black Sea, 1:403
426
Index
Air (continued) satellite remote sensing, 5:206–207, 5:207 Airborne laser fluorosensing, 1:139 Airborne lidar coastal mapping, see also Aircraft for remote sensing Airborne marine pollutants, environmental protection and Law of the Sea, 3:440–441 Airborne Oceanographic Lidar (AOL), 1:139 Airborne Topographic Mapper (ATM), 1:140, 1:141F Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), 1:142–144 accomplishments, 1:144 design based on satellite system, 1:142 high altitude and high speed flights, 1:142–143 see also Aircraft for remote sensing Air conditioning oceanographic research vessels, 5:412 ocean thermal energy conversion, 4:172 Aircraft dropping subsurface temperature probes (AXBTs), 2:5 Aircraft for remote sensing, 1:138–146 active systems/sensors, 1:138–139 airborne laser fluorosensing, 1:139 Airborne Oceanographic Lidar (AOL), 1:139 examples of data from AOL, 1:139, 1:140F laser-induced fluorescence, 1:139 airborne lidar coastal mapping, 1:139–141 Airborne Topographic Mapper (ATM), 1:140, 1:141F GPS kinematic differential, 1:139 other airborne lidar systems, 1:140–141 system accuracy, 1:139–140 pump and probe fluorometry, 1:141 determining phytoplankton photosynthesis, 1:141 advantages over satellites, 1:138 applications to oceanography, 1:138 disadvantages, 1:138 hyper-spectral systems, 1:142–144 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), 1:142–144 AVIRIS see Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Compact Airborne Spectographic Imager (CASI), 1:144 Portable Hyper-spectral Imager for Low-Light Spectroscopy (PHILLS), 1:144 instrumentation for studying ocean properties, 1:138 microwave salinometers see Microwave salinometers passive systems/sensors, 1:141–142 Multichannel Ocean Color Sensor (MOCS), 1:141–142
Ocean Data Acquisition System (ODAS) and SeaWiFS Aircraft Simulator (SAS), 1:142 long-time series aircraft studies, 1:142 phytoplankton cycle productivity, 1:142, 1:143F SAS replaces ODAS, 1:142 radiometers measuring reflected sunlight, 1:141–142 radar altimetry, 1:144 sensors used, 1:138 Synthetic Aperture Radar (SAR) systems, 1:144–145 see also Satellite oceanography; Upper ocean, time and space variability Airfoil aerodynamics of towed vehicles see Towed vehicles, aerodynamics probes, 6:151–152 Airlift mining system, 3:894, 3:895F Air pollution coral impact, 1:674 see also Pollutants; Pollution Air–sea fluxes, 3:447 heat see Air–sea heat flux Air–sea gas exchange, 1:147–156, 1:157 boundary layer time constant, 1:149–150 bubble clouds, 1:442 bubbles, 1:439 carbon dioxide cycle, 1:487 El Nin˜o Southern Oscillation and, 2:239 see also Carbon dioxide (CO2) controlled flux, 1:153–155 eddy correlation measurements, 1:153 empirical parametrization, 1:152–153 experiments, tracer release, 6:89–90 dual tracer, 6:89–90, 6:90F field data summary, 1:155F laboratory techniques, 1:153 mass boundary layers, 1:147–149 radiocarbon, 4:650–651 rough water surfaces, 1:150, 1:150–151 satellite remote sensing of SST application, 5:101 smooth water surfaces, 1:150 surface films, 1:151 trace gases, 1:157–162, 1:163–170 transfer resistance, 1:150 transfer velocity, 1:149 waves (surface) and, 1:151 wavy water surfaces, 1:150–151 whitecaps, 6:332 see also Controlled flux technique Air–sea heat flux, 6:337 global, 6:339, 6:340F Ocean Station Papa, 6:343F Southeast Asian Seas, 5:306 surface heat, 6:337–339 transfer processes, 5:202 see also Radiative fluxes Air–sea interaction, 6:337–339 bubbles, 1:439 evaporation see Evaporation
(c) 2011 Elsevier Inc. All Rights Reserved.
gas see Air–sea gas exchange humidity see Humidity surface, gravity and capillary waves, 5:573, 5:580 surface films, modifications by see Surface films surface heat flux see Air–sea heat flux thermal and haline buoyancy fluxes, 6:339–341 three-dimensional (3D) turbulence, 6:23 Air–sea interface fluxes, measurement of see Micrometeorological flux measurements see also Air–water interface Air–sea momentum transfer, 6:308 see also Wind forcing Air–sea transfer gas exchange see Air–sea gas exchange heat see Air–sea heat flux trace gases, 1:157–162, 1:163–170 see also specific gases Air-segmented continuous flow analyzers, 6:326–327 applications, shipborne laboratories, 6:326–327, 6:327 disadvantages, 6:326–327 methods to overcome, 6:327 flow injection analysis vs., 6:327 technique, 6:326 total oxidised nitrogen determinations, 6:326, 6:326F Air–water interface carbon dioxide transfer see Carbon dioxide definition, 3:6–7 estuaries, gas exchange across, 3:1 sea foam, 6:334–335 temperature difference vs. Ui, 3:204, 3:204F Airy isostasy, 3:85 Airy wave theory see Linear waves AIS see Atlantic Ionian Stream (AIS) AIW see Arctic Intermediate Water (AIW) Alabaminella weddellensis foraminifer, 1:346F, 1:347 ALACE see Autonomous Lagrangian Circulation Explorer; Autonomous Lagrangian Circulation Explorer (ALACE) Aland Sea, Baltic Sea circulation, 1:288, 1:289F Alaska earthquake (1964), 6:132F oil spills, satellite remote sensing, 5:104F salmon population, 4:703F sea ice cover, 5:141 tsunami (1964), 6:128 seafloor displacement, 6:131–132 Alaska, Gulf see Gulf of Alaska Alaska Coastal Current, 1:455, 1:457F, 1:458–459 flow, 1:456F, 1:459 importance to marine mammals and fish, 1:459
Index oil pollution and, 1:459 salinity, 1:457F, 1:459 Alaska Current, 1:455–457, 1:455F, 1:456F, 1:457–458 coastal current see Alaska Coastal Current eddies, 1:457–458, 1:458F flow, 1:455, 1:456F, 1:457–458 Alaskan Stream see Alaskan Stream historical aspects, 1:455–456 interannual and interdecadal variability, 1:464–465 El Nin˜o Southern Oscillation and, 1:464–465 Pacific Decadal Oscillation and, 1:465 origins, 1:455 topographic effects, 1:463–464 volume transport, 1:455 winds and, 1:457–458 see also Gulf of Alaska Alaska Gyre, 1:455, 1:456F, 3:359F, 3:365 coastal currents, 1:455, 1:458–459, 1:463 flow, 1:456F, 1:459 see also Alaska Coastal Current see also Alaska Current Alaskan Beaufort Sea, sub-sea permafrost, 5:566–567 Alaskan Gyre, chlorofluorocabon, 1:537 Alaskan pollock see Theragra chalcogramma (Alaska/walleye pollock) Alaskan Stream, 1:455F, 1:456F, 1:458 flow, 1:458, 3:359F, 3:365 surface salinities, 1:458 Alaska pollock see Theragra chalcogramma (Alaska/walleye pollock) Albacore tuna (Thunnus alalunga), 2:404–405, 2:404F Albatross, 4:296 sediment core collection, 4:297 US Fish Commission, 5:410–411 Albatrosses (Diomedeidae), 4:590, 5:279, 5:282–283 by-catch issues, 2:203, 5:517 importance of krill, 3:356 migration, 5:239–240 population declines, longline fishing and, 4:596 see also Procellariiformes (petrels); Seabird foraging ecology; specific species Albedo, 3:114, 3:205–206, 3:244, 4:379–380, 6:331–332 definition, 4:379 single-scattering, 4:622–623 wind speed, 4:380 Albermarle Sound, North Carolina, USA, 3:381F Albert I of Monaco, 2:172 Alborada, 4:770F Alca, 1:171T diet, 1:174 see also Alcidae (auks)
Alca torda (razorbill), 1:173F, 1:175 see also Alcidae (auks) Alcidae (auks), 1:171–177, 1:173F abundance, 1:171 characteristics and adaptations, 1:171–172 digestive system, 1:172 plumage, 1:172, 1:173F prolonged diving, 1:172 underwater swimming, 1:172 diet and foraging ecology, 1:172–174 distribution, 1:171 evolution, 1:171 fossils, 1:171 harvesting by humans, 1:175–177 commercial, 1:176 eggs, 1:176 skins, 1:176 techniques, 1:176 migration, 5:244–246 population dynamics, 1:175 postbreeding, 1:175 prebasic molt, 1:175 reproduction, 1:174–175 breeding sites, 1:174 chick-rearing, 1:175 egg incubation, 1:174–175 species, 1:171 systematics, 1:171, 1:171T genera, 1:171, 1:171T tribes, 1:171, 1:171T thermoregulation, 1:175 hatchlings, 1:175 threats human exploitation, 1:176 predation, 1:176–177 wintering, 1:175 see also Seabird(s); specific genera/ species Aldabra Atoll, island wakes, 3:343, 3:344–345 Aldrin seabirds as indicators of pollution, 5:275 structure, 1:552F Aleutian Archipelago, sea otter population, 5:201 Aleutian low-pressure cell, 4:710 ENSO events and, 4:699 Alexandrium spp. dinoflagellates, 4:440, 4:441F Alexandrium tamarense dinoflagellate, 3:557, 4:440F Algae acoustic scattering, 1:68–69 Chondrus crispus, 5:322F Chromalveolate algae, 3:553–554 definition, 4:425 comparison to ‘true’ plants, 4:425 cyanobacteria, 4:425 primary production, 4:425 diversity see Algae, diversity few shared characteristics, 5:317 general definition, 4:613–614 genomics and evolution see Algal genomics and evolution Gracilaria chilensis, 5:321F
(c) 2011 Elsevier Inc. All Rights Reserved.
427
importance to global photosynthesis, 5:317 importance to oceanic ecosystems, 5:317 iron requirements, nitrate vs. ammonia, 6:82–83 lipid biomarkers, 5:422F mariculture, 5:321F, 5:322F see also Seaweed mariculture Monostroma nitidum, 5:322F productivity measures, 2:584–586 salt marshes and mud flats, 5:44 SECAPS Continuous Culture System, 4:277F symbiotic relationships gelatinous zooplankton, 3:10 radiolarians, 4:613–614, 4:617 thermal discharges and pollution, 6:13–14 toxic, 4:433–436 oyster farming, 4:284 see also Algal blooms; Phytoplankton blooms zooxanthellae, 1:665 see also Algal blooms; Algal genomics and evolution; Cyanobacteria; Microphytobenthos; Phytobenthos; Phytoplankton blooms; Seaweed(s); Seaweed mariculture Algae, diversity (phytobenthos), 4:425–427 habitats, 4:427 epiphytes, 4:427 microphytobenthos, 4:427 seaweeds, 4:427 size diversity, 4:426 structural diversity, 4:426–427 advanced forms, 4:426 calcium carbonate secretion, 4:426 example of kelp, 4:426 heterotrophic production, 4:426–427 simple forms, 4:426 taxonomic classification, 4:427 comparison to higher plants, 4:427 distinguishing features, 4:427 seaweed divisions, 4:427 Algal blooms control by viruses, 4:470 harmful, monitoring, CPR survey, 1:638 Mediterranean mariculture problems, 3:533 monitoring, CPR survey, 1:638 North Sea, regime shifts and, 4:704 satellite remote sensing, 4:739 see also Coccolithophores, blooms; Phytoplankton blooms; Red tides Algal feeders, coral reef aquaria, 3:530T Algal genomics and evolution, 3:552–559 Chromalveolate algae, 3:553–554 evolution of oxygenic photosynthesis, 3:553–554 evolution of plastids, 3:554F photosynthesis, 3:554 secondary endosymbiosis, 3:553–554 transfer of genes, 3:554 diatoms, 3:554–555 C3-C4 metabolism, 3:555
428
Index
Algal genomics and evolution (continued) CO2 concentration mechanisms, 3:554–555 diversity and importance, 3:554–555 nitrogen metabolism, 3:555 silica, 3:555 Thalassiosira pseudonana genome, 3:554–555 Thalassiosira weissflogii, 3:554–555 dinoflagellates, 3:556–557 dinoflagellate-coral symbiosis, 3:556 diversity, 3:556 nuclear DNA, 3:556–557 plastic replacement, 3:557–558 Karenis brevis, 3:557–558, 3:558F plastids, 3:557 Alexandrium tamarense, 3:557 endosymbiosis and horizontal gene transfer, 3:557 green algae endosymbiosis, 3:557 peridinin dinoflagellates, 3:557 plastic loss and recruitment, 3:557 red tides, 3:556 saxitoxin production, 3:556 sequencing, 3:556–557 genomic perspective, 3:552 marine algae sequenced, 3:552 uses of genomics, 3:552 Haptophytes, 3:555–556 coccolithogenesis, 3:555–556 diversity and importance, 3:555–556 Emiliania blooms, 3:555–556 increasing importance of genomes, 3:559 photosynthesis in eukaryotes, 3:552–553 Arabidopsis thaliana, 3:553 cyanobacterial contribution to genome, 3:553 Cyanophora paradoxa, 3:553 endosymbiosis, 3:552–553 evolution of plastid import machinery, 3:553, 3:553F key evolutionary steps, 3:552–553 endosymbiotic gene transfer, 3:552–553 origin of the plastid, 3:552–553, 3:552F retention of organelle genome encoding, 3:552–553 picoeukaryotes, 3:558–559 diversity, 3:558–559 ecotypes, 3:558–559 Micromonas pusilla, 3:558–559 Ostreococcus spp., 3:558–559 Algerian Current, 3:717, 3:721, 4:792–793 Alginate, 4:430 Algorithms bio-optical, 4:735, 5:120 blue-green ratio see Bio-optical algorithms chlorophyll a, ocean color by satellite remote sensing, 5:120, 5:121F genetic, direct minimization methods, in data assimilation, 2:8
infrared atmospheric correction, SST measurement, 5:93 NASA Team, 5:83, 5:88F ocean color, coastal waters, 4:735 optimization for coastal water remote sensing, 4:736, 4:736F SeaWiFS, 4:628 SST, by satellite remote sensing see Satellite remote sensing of sea surface temperatures Aliasing, bathymetry, 1:300 Alkalinity depth profiles, estuarine sediments, 1:544F sea water, 1:627T determination, 1:626 plankton production and, 1:626–627 Alkanes, radiocarbon analysis, 5:426 Alkenone unsaturation index bias, 2:98 sea surface temperature and, 2:106F sea surface temperature paleothermometry and, 2:101T error sources, 2:106 Alle, 1:171T see also Alcidae (auks) Alle alle (little auk), 1:171, 1:173F Allochthonous radiocarbon, 5:420 Almadraba traps, 4:235 Almaz-1, 5:103 Almeria-Oran Jet, 3:717 Along-Track Scanning Radiometer (ATSR), 5:95–97 brightness temperature calibration, 5:96 infrared rotating scan mirror, 5:95–96, 5:95F relatively narrow swath width, 5:96–97 two brightness temperature measurements, 5:95 Alosa spp. (shad), hearing range, 2:477 Alpha plumes, whitecaps, 6:331 Alps, North Atlantic Oscillation and, 4:69 Altimeters in estimation of sea level variation, 5:180–181 rogue wave measurement, 4:776–777 satellite radar see Satellite radar altimeters satellite sea level data, 5:129–130 Topex/Poseidon see Topex/Poseidon satellite altimeter system Altimetry, 5:70 2004 Indian Ocean tsunami, 6:134 radar see Radar altimetry satellite see Satellite altimetry tomography and, 6:55F Altitude, atmospheric pressure changes with, 5:375 Aluminosilicate, 1:268 Aluminum cosmogenic isotopes, 1:679T oceanic sources, 1:680T production rates, 1:680T reservoir concentrations, 1:681, 1:681T
(c) 2011 Elsevier Inc. All Rights Reserved.
specific radioactivity, 1:682T crustal abundance, 4:688T dissolved, 4:689–690 depth profile, 4:691F properties in seawater, 4:688T surface distribution, 4:690F fluorescent sensing, 2:594, 2:594T inorganic side-reaction coefficient, 6:103, 6:103T oceanic, 1:195 Alvin deep-water manned submersible, 3:505–506, 3:509, 3:510F, 3:511, 6:257T, 6:259F, 6:265 deep submergence studies, 2:22–23, 2:23F, 2:24F, 2:27F, 2:30–33 key discoveries by, 2:23–24, 2:32F observations hydrothermal vent biota, Galapagos Rift, 3:133 hydrothermal vent fluids, chemistry of, 3:165F, 3:168 volcanic activity, East Pacific Rise (EPR), 3:168 Alvinella caudata (polychaete), 3:154F temperature tolerance, 3:153–154 Alvinella pompejana (polychaete), 3:134–135, 3:137F deep-sea ridges, microbiology, epibionts, 2:76–77, 2:76F Alvinocaris lusca (shrimp), 3:139F Amazonian manatee (Trichechus inunguis), 5:439 see also Manatees Amazon River dissolved loads, 4:759T Intra-Americas Sea (IAS), 3:288 river discharge, 4:755T sediment load/yield, 4:757T Amazon River water Intra-Americas Sea (IAS), 3:288 North Brazil Current (NBC), 2:561 Amazon submarine channel, 5:459 Ambient noise, 1:52 active sonar systems, 5:505 measurement data, 1:52, 1:53F see also Acoustic noise Ambulocetidae, 3:592 see also Cetaceans AMC see Axial magma chamber (AMC) AMCOR see Atlantic Marine Coring project American Association for the Advancement of Science, 3:413 American Fisheries Society (AFS), 2:525 American Geophysical Union, 3:278–279 American lobster (Homarus americanus), fisheries, 1:702 American Mediterranean see IntraAmericas Sea (IAS) American oyster, production, 4:275T American Samoa, aerosol concentrations, 1:249T Amirante Passage, 2:565F Ammodytes marinus (sand eel), total world catch, 2:91, 2:91T
Index Ammodytidae (sand eels), 2:379, 2:395–396F, 2:461 Ammonia absorptiometric sensor, 1:13 air–sea transfer, 1:160–161 nitrification, 1:160, 1:161F ocean thermal energy conversion, 4:169, 4:171 oxidation, isotope ratios and, 4:43T pollution, 5:277 in pore water, 4:565T profiles, 1:216F Black Sea, 1:405F un-ionized, mole fraction, aquarium fish mariculture, water quality, 3:527, 3:527T Ammonia parkinsoniana over Elphidium spp. (A–E index), 3:177 hypoxia, 3:177 Ammonification, 4:33–34, 4:33F, 4:34F see also Nitrogen cycle Ammonium (NH4+), 1:160, 5:45 assimilation, 4:44–45 atmospheric, 1:248–249 depth profiles, estuarine sediments, 1:544F nitrogen isotope ratios, 4:47–50 phytoplankton growth reaction, 4:579 requirement by microphytobenthos, 3:813 sea water concentrations, determination, 4:32 species selectivity, 3:813 subterranean estuaries, 3:96 suspended particles, 4:51 see also Nitrogen cycle Amorphous hydroxides, diagenetic reactions, 1:266T Amphidromes definition, 6:37 semidiurnal tides, 6:37, 6:37F, 6:38, 6:39F Amphipods aggregation, 1:334T Halice hesmonectes, 3:139 Ampullatus hyperoodon (bottlenose whale), diving characteristics, 3:583T AMS see Accelerator mass spectrometry AMSR see Advanced microwave scanning radiometer (AMSR) Amundsen Basin deep water, 1:219 temperature and salinity profiles, 1:213F, 1:214F, 1:217F Amundsen Sea, sea ice cover, 5:146–147 Amur River, Okhotsk Sea inflow, 4:201, 4:204–205, 4:205 Anableps anableps (four-eyed fish), 2:447F Anadromous fishes, harvesting, 2:501 Analcite, 1:265–266 Analogue-digital (A/D) converters, seawater profiling, 1:715 Analytical flow cytometry (AFC), 4:243–245
applications, 4:245–246 bacteria, 4:246–247, 4:246F larval fish, 4:247–248 phytoplankton, 4:245–246, 4:245T, 4:246F protozoa, 4:247, 4:247F viruses, 4:247 zooplankton, 4:247–248 artificial neural nets in, 4:246 cell sorting, 4:245 commercial instruments, 4:244–245 future trends, 4:248 in-situ, 4:248 photomultiplier tubes in, 4:244 technique, 4:243–245, 4:244F Analytic (closed form) solutions, coastal circulation models, 1:573 Anammox, 4:43–44 Anchor, coral disturbance/destruction, 1:675 Anchor moorings deployment, 3:928–929 release, 3:920 Anchor suction dredging, 4:185, 4:185F Anchoveta fisheries by-catch issues, 2:202 landings, trophic levels, 2:207 multispecies dynamics, 2:508, 2:509 fishing, 4:707 production, sea surface temperatures in North Pacific, 4:390F Anchovies (Engraulis spp.), 4:368 Benguela upwelling, population, 4:705–707 catch time series, 4:701F fisheries, multispecies dynamics, 2:508, 2:509 fishing, sardine population and, 4:707 northern, biomass time series, 4:700F see also specific Engraulis spp. Ancient, definition, 5:463 Ancient climates, ocean circulation and see Paleoceanography Andesitic glass, diagenetic reactions, 1:266T Anemometers calibration, 5:375–376 cone, 5:385 cup, wind speed, 5:375, 5:376F hot-film, 5:385 hot-wire, 5:384 K-Gill, 5:385–386, 5:385F propellor, 5:375, 5:376F sonic, 5:376F, 5:377, 5:386, 5:386F thrust, 5:385 Anemonefishes (Pomacentridae), 1:656, 1:657 Anemones, fluorescence, 2:582 Anesthesia, stress minimization, mariculture, 3:520 Angelfish (Pomacanthidae), 2:395–396F ‘Angels’, 2:614–615 Angiosperms, lipid biomarkers, 5:422F Angle of intromission, 1:86–87 Anglerfishes (Lophiiformes), 2:377, 2:472
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Angling, salmon harvesting, 5:1 Angola, coastal upwelling area off, productivity reconstruction, 5:340F, 5:341–342 Angola–Benguela Front, 1:326 Angola Current, 1:317F, 1:324 transport, 1:724T see also Atlantic Ocean current systems; Benguela Current Anguilla (eels), 2:208–217 see also Eels Anguilla anguilla (common eel), 2:214 mariculture, stock acquisition, 3:532 Anguilliformes (eels), 2:395–396F Anhingidae (darters), 4:370, 4:374–375 breeding patterns, 4:375 characteristics, 4:374–375 cormorants vs., 4:375 distribution, 4:374–375 feeding patterns/adaptations, 4:375, 4:376T species, 4:374–375 see also Pelecaniformes; specific species Animal(s) upper temperature limits, 6:12T see also Marine mammals Animal feeding particle dynamics and large particle production, 4:330, 4:331F, 4:333–335 large particle transformation, 4:336 see also Particle aggregation dynamics see also Fecal pellets Anisotropic structure, oceanic crust and upper mantle, 5:366 Anisotropic turbulence, 6:22–23, 6:23F Anistropy, 3:202–203 Anita, 4:770F ANN (artificial neural nets), in analytical flow cytometry, 4:246 Annapolis Protocol, 6:275, 6:275–276 Annapolis tidal power plant, 6:27, 6:28T Annelid worms (Arenicola spp.), 5:55F Anomalously enriched elements (AEEs), 1:124 ANOSIM, 4:536–537 Anoxia causes, 4:685 consequences direct effects, 3:177 secondary production, 3:179 effects, 4:685 fiords, 2:353–354 implications, 4:685 marine mammal adaptations see Marine mammals, diving physiology see also Hypoxia Anoxic environments, uranium, 6:246 Anoxic zones formation, 3:911–912 and sediment bioturbation, 3:911 Anseriformes, 5:266T see also Seabird(s) Antarctic see Antarctic Ocean Antarctica, 4:129 bottom water formation, 1:416–417
430
Index
Antarctica (continued) continental margins, primary production, 4:259T icebergs, 3:181, 3:188 ice shelves, distribution of, 3:210F sub-sea permafrost, 5:567 see also Antarctic Ocean; Antarctic sea ice; entries beginning Antarctic Antarctic bottom water (AABW), 1:178–179, 1:425, 2:80, 2:81F, 2:82F, 4:127, 4:127F, 4:130 Benguela region, 1:319–322, 1:322F, 1:324 circumpolar estimates, 1:420 continental shelf, 1:420 deep passages and, 2:566 definition, 1:415–416 diffusive convection and, 2:168 Drake Passage closure, 4:304 Panama Passage opening and, 4:305, 4:306F flow, 1:725–726, 1:725F formation, 1:416–418, 1:417F, 1:418–420 Weddell Sea, 6:297 generation, 1:24, 1:736 glacial climate change and, 1:3–4 glacial ice, 1:417–418 North Atlantic Deep Water and abyssal circulation, 1:26, 1:26F alternating dominance, 3:129–130 offshore water, temperatures, 1:418 seafloor, temperature potential, 1:416F sea ice role, 1:416–417 temperature–salinity (TS) characteristics, 6:294T, 6:297, 6:297F turbulent mixing, observations of, 2:123, 2:126 volume transport, 1:25F, 1:26 water properties, 1:180F see also Abyssal waters Antarctic Circumpolar Current (ACC), 1:178–190, 1:735, 1:738–740, 2:264F, 4:128, 4:129F, 4:131 abyssal water source, 1:20–24 Antarctic Bottom Water and, 1:418, 1:420, 4:122, 4:128 Antarctic ice sheet formation and, 4:325 circulation, 1:182–183 jets, 1:183 current speeds, 1:179–181 Deep Western Boundary currents and, 1:26 dynamics, 1:185–188 bottom form stress, 1:187 eddies, 1:187 eddies, overturning circulation and, 1:189 eddy activity, 1:187, 1:739, 1:742F effects on global circulation, 1:187 flow, 1:724 route, 1:422, 1:423F, 1:427, 4:127, 4:128, 6:319F freshwater fluxes, 4:123F fronts, 1:178, 1:181
biological populations and, 1:182 seafloor topography and, 1:183 transport, 1:184 high speed filaments, 1:739 internal waves, 2:127–128 isopycnals, 4:129–130, 4:130 jets, 1:187F, 1:427 mesoscale eddies, 3:756, 3:764 modeling, 1:185–187 North Atlantic Deep Water flowing into, 4:122 ocean fronts, 1:739, 1:740F polar, 1:739, 1:741F overturning circulation and, 1:188–189, 1:189 Polar Frontal Zone, 1:181–182 Rossby waves, 4:788 seafloor topography and, 1:738–739, 1:739F speed, simulated, 1:188F stratification, 2:261F, 2:267–268 stratification zones, 1:739, 1:740F structure, 1:178–182 surface speeds, 1:739, 1:740F temperature and salinity, 1:737F, 4:127 transport, 1:183–185, 1:724T, 1:735, 1:738 longitude and, 1:185 total, 1:178 variability, 1:185 volume, 1:184 turbulence in deep ocean due to, 2:127–128 variability, 1:188 water properties, 1:178–179, 1:180F latitude and, 1:179 water volume transferred by, 1:735 see also Antarctic Circumpolar Current; Antarctic Zone; Atlantic Ocean current systems; Polar Front; Polar Frontal Zone; Southern Antarctic Circumpolar Current front; Subantarctic Front; Subantarctic Zone Antarctic Circumpolar Wave, 6:323–324 Antarctic Coastal Current, 6:322 bottom topography, 6:322–323, 6:323 Circumpolar Deep Water, 6:323 extent, 6:322 flow speed, 6:322–323 forcing mechanisms, 6:322 frontal jet, 6:322 path, 6:322 seasonal variations, 6:323 volume transport, 6:322–323 water mass characteristics, 6:320F, 6:322, 6:323 see also Water types and water masses Weddell Sea Bottom Water, 6:323 Weddell Sea Deep Water, 6:323 Antarctic continent, 4:129 see also Antarctica Antarctic continental shelf, sub ice-shelf circulation, 5:544–545, 5:546F Antarctic Convergence see Antarctic Polar Frontal Zone (APFZ)
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Antarctic Divergence, 6:322 Antarctic divergence zone, 6:231 Antarctic fish(es), 1:191–194 adaptations, 1:191–192 antifreeze, 1:192 antifreeze glycopeptides, 1:192, 1:193F freezing points, 1:192 kidney adaptations, 1:192 cardiovascular adaptations, 1:192–194 high oxygen tension areas, 1:194 increased volume of blood, 1:193–194 lack of hemoglobin, 1:193 oxygen availability in seawater, 1:192–193 theories of oxygen uptake, 1:193 cold adaptation, 1:191–192 metabolic rates, 1:191–192 changes in taxonomic methods, 1:191 fish fauna, 1:191, 1:191T low diversity, 1:191 Antarctic fur seal see Arctocephalus gazella (Antarctic fur seal) Antarctic ice, zones, seabird associations, 5:229 Antarctic Ice Sheet formation Oi1 event, 4:325 oxygen isotope ratio and, 5:185–186, 5:186F lithosphere depression effects, 5:541–542 sea level variations and, 5:182–183, 5:183, 5:184 surface melting projections, 5:183 see also Antarctic sea ice; Ice sheets Antarctic Intermediate Water (AAIW), 1:26, 1:178–179, 3:447, 3:449F, 4:121F air–sea interactions, 1:424 Benguela region, 1:319–322, 1:322F, 1:324, 1:325F Brazil and Falklands (Malvinas) Currents, 1:423–424, 1:427 Brazil/Malvinas confluence (BMC), 1:426F formation, 1:188, 1:189F, 1:735–736 formation region, 6:295, 6:296F interleaving, 1:424 recirculated, 1:424, 1:425 salinity distribution, 1:23F, 1:24F, 1:25–26 temperature–salinity characteristics, 6:292, 6:294T, 6:297–298, 6:297, 6:297F, 6:298, 6:298F water properties, 1:180F Antarctic king crab see Paralomis spinosissima (Antarctic king crab) Antarctic krill see Euphausia superba (Antarctic krill) Antarctic neritic krill see Euphausia crystallarophias (ice krill) Antarctic Ocean diffusive convection, 2:167–168
Index icebergs, 3:181, 3:182, 3:188 sources and drift paths, 3:184F ice sheet formation, Oi1 event, 4:325 see also Antarctic Ice Sheet ice-shelves, 5:541, 5:543F melt ponds, 5:172 multiyear ice, 5:170 Non Polar Front, biogenic silica burial, 3:681T Polar Front, 5:514 biogenic silica burial, 3:681–682, 3:681T polynyas, 4:544 sea ice see Antarctic sea ice see also Southern Ocean Antarctic Peninsula, 5:86, 5:87–88 ice shelf stability, 3:209, 3:211 Antarctic petrel (Thalassoica antarctica), 5:253 Antarctic Polar Frontal Zone (APFZ), 5:514 biogenic silica burial, 3:681–682, 3:681T Antarctic sea ice Bellingshausen and Amundsen Seas, 5:86, 5:87F drift patterns, 5:160 extents, 5:85, 5:86 geographical extent, 5:146–150, 5:149F interannual variability, 5:150–151, 5:150F Ross Sea, 5:86, 5:87F Southern Hemisphere, 5:86, 5:87–88, 5:87F thickness, 5:154F, 5:155–157 model evaluation, 1:695F studies on, 5:176 Weddell Sea, 5:86, 5:87F see also Antarctic Circumpolar Current (ACC); Antarctic Ice Sheet; Southern Ocean, current systems; Weddell Sea Circulation Antarctic Slope Front, water properties, 1:180F Antarctic Surface Water (AASW), temperature–salinity characteristics, 6:294T Antarctic toothfish see Dissostichus mawsoni (Antarctic toothfish) Antarctic Treaty System, 3:668T, 5:513 Antarctic Zone, 1:181–182 Antennas, 5:128–129 Anthomedusae medusas, 3:10, 3:11F Anthropogenic activities see Human activities, adverse effects; Human exploitation Anthropogenic carbon, 4:105 definition, 4:113 Anthropogenic impacts, 2:160 beaked whales, 3:649 climate change, 2:483 coastal topography, 1:581–590 cold-water coral reefs, 1:622–624 coral reef fishes, 1:655 coral reefs, 1:667, 1:668–669, 1:669 definition, 3:565
demersal fishes, 2:465 dolphins and porpoises, 2:155, 2:159 of fisheries (effects) benthos, 3:476–477 ocean gyre systems, 4:137 see also Ecosystem(s), fishing effects; Southern Ocean fisheries fish hearing, 2:479–480 fish populations, 2:467 harmful algal blooms, 4:441 lagoons, 3:387, 3:387T mangroves, 3:503–504 noise see Marine mammals and ocean noise of noise see Marine mammals and ocean noise nutrient increases, 4:459–460 of overfishing, 2:379 polar ecosystems, 4:517 rocky shores, 4:768 salt marshes and mud flats, 5:46, 5:46–47 seabirds, 5:283 sperm whales, 3:649 threats to deep-sea fauna, 2:64–65 see also Antifouling materials; Coastal topography impacted by humans; Coastal zone management; Exotic species introductions; Global marine pollution; Global state of marine fishery resources; Habitat modification; Human activities, adverse effects; Large marine ecosystems (LMEs); Pollution; Pollution control approaches; Pollution solids Anthropogenic metals, estuarine sediments and, 1:549 Anthropogenic nitrogen, 1:255T, 4:42 Anthropogenic radionuclides, 5:329 Anthropogenic reactive nitrogen, production, estimates of, 1:245T Anthropogenic trace elements, 1:195–202 enhancements in coastal waters and embayments, 1:200 open-ocean, 2:256T, 2:258 cadmium, 1:200 lead see Lead mercury see Mercury tributyl tin, 1:200 zinc, 1:200 see also Pollution Antibiotics, mariculture, bacterial disease treatment, 3:520T, 3:521–522 Anticyclonic circulation, 2:216 Anticyclonic gyres Mediterranean Sea circulation, 3:718–720, 3:719F, 3:720 Red Sea circulation, 4:668–669 Antifouling materials, 1:203–210 alternative antifoulants, 1:206–209 biocidal coatings, 1:207–209 copper compounds, 1:207–208 ecotoxicological tests, 1:208–209 organic booster biocides, 1:208 research concerns, 1:208
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lines of research, 1:207 nonbiocidal alternatives, 1:209–210 categories, 1:209 foul release coatings, 1:209 hard marine coatings, 1:209–210 ‘smart’ coatings, 1:209, 1:209F post TBT ban research, 1:206–207 fouling processes, 1:203 historical developments, 1:203–205 effects of fouling on steel, 1:203 free association paints, 1:203 free association vs. copolymer paints, 1:204F historical methods, 1:203 paint matrices, properties, 1:203–204 self-polishing copolymer (SPC) paints, 1:204 benefits, 1:204–205 widespread use, 1:205 history of, 2:332–333 TBT (tributyltin), 1:203 TBT-based antifoulants, 1:205–206 effectiveness of regulations, 1:205 lethal and non-lethal effects, 1:205, 1:206F non-desirable impacts, 1:205, 1:207T paint chips problems, 1:205–206, 1:208F TBT ban, 1:205–206 Antigua and Barbuda, coastal erosion, 1:588 Antikythera wreck, raided, 3:696 Antillean Arc, 3:286F, 3:287 Antilles Current, 3:291, 3:293F Antimony (Sb), 3:781–782, 3:783 depth profile, 3:781–782, 3:781F methylated forms, 3:781–782 oxic vs. anoxic waters, 3:781–782 Antimony-125 (125Sb), nuclear fuel reprocessing, 4:84T Antisubmarine Detection Investigation Committee (ASDIC), 5:504 Anti-submarine warfare (ASW), 5:504 Anti-tropical distribution, definition, 2:160 Antonis Demades, 4:770F Antparos, 4:770F AO see Arctic Oscillation Ao222, definition, 6:242 AOP see Apparent optical properties (AOPs) Ap, definition, 6:242 Apart, definition, 6:242 Apectodinium, 4:322F Aperture synthesis, 5:129 APFZ (Antarctic Polar Frontal Zone), 5:514 Aphanopus carbo (black scabbardfish) see Black scabbardfish (Aphanopus carbo) Aphelion, 4:505–506 Aphotic zone biogeochemical processes, 4:90, 4:90F oxygen consumption depth profile, 6:95F tracing, 6:93, 6:94–95
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Index
Aphotic zone (continued) timescale, 6:95 tracer constraints, 6:94F Apoptosis, 3:565 Apparent optical properties (AOPs), 3:247, 4:623–624, 4:733, 6:109 chlorophyll concentration and, 1:388, 1:391, 1:392T, 1:393F definition, 4:619 inherent optical properties and, 3:247 measurements, 3:247, 3:247–248, 3:249F models, 1:385 see also Bio-optical models penetrating shortwave radiation, 4:379 quantities, 4:620T see also Inherent optical properties (IOPs); Ocean optics; Radiative transfer Appendicularia tunicates, 3:16, 3:17F, 3:18 Approximate dynamics, data assimilation in models, 2:1 Aptenodytes (penguins), 5:526 breeding patterns, 5:526 characteristics, 5:522T, 5:526, 5:526F distribution, 5:522T, 5:526 feeding patterns, 5:522T, 5:526 migration, 5:239 nests, 5:522T, 5:526 species, 5:522T, 5:526 see also Sphenisciformes (penguins); specific species Aptenodytes forsteri (emperor penguin), 5:522T, 5:526, 5:527 Aptenodytes patagonicus (king penguin), 5:522T, 5:526, 5:526F APTS see Astronomical polarity timescale (APTS) Aqaba, Gulf see Gulf of Aqaba Aqua AMSR-E, 5:83–84, 5:88–89 Aquaculture, 2:94 Arcachon Bay, France, 3:102 biotechnology applications, 3:562–563 see also Marine biotechnology copepod pests, 1:649 eels, 2:215 habitat modification, 3:102 impacts, marine biodiversity/habitats, 2:145–146 seaduck interactions, 5:270–271 thermal discharge from power stations, use of, 6:16 see also Exotic species introductions; Mariculture; Mariculture economic and social impacts; Seaweed mariculture Aquarium fish mariculture, 3:524–531 artificial sea water, 3:526 Widermann–Kramer formula, 3:527T behavior, 3:528 breeding, 3:529 coral reef see Coral reef aquaria diet, 3:528–529 diseases associated, 3:529 habitat, 3:528
health management, 3:529 historical aspects, 3:524–526 life span, 3:529 life support parameters, 3:526, 3:526T predation issues, 3:528 size issues, 3:529 species suitability, 3:526 stress responses, 3:529 water quality guidelines, 3:526, 3:526–528, 3:527T filtration, 3:525, 3:527, 3:528F salinity, 3:526, 3:527T toxicity parameters, 3:527, 3:527T water temperature range, 3:526 see also specific species Aquarium industry, coral collection, 1:671–672 Aquarius/SAC-D mission, 5:129, 5:130 Aquarius satellite, 6:166, 6:167F Aqua satellite, 5:82, 5:88–89, 5:118T Aquashuttle towed vehicle, 6:65, 6:72 Aquatic extremophiles, 3:565 Aquifers, 5:552 definition, 5:557 submarine groundwater discharge (SGD) and, 5:552, 5:553, 5:554 Aquificales (bacteria), 2:78 Aquitard, 5:557 AR see Autoregressive functions Arabian Sea carbon isotope ratio, 3:913F, 3:916F chlorofluorocabon, 1:538 monsoons, 3:910 historical variability, 3:914 indicators, 3:912–913 long-term evolution, 3:916 oxygen content, 3:913F particle flux variability, 6:1–2, 6:5 particulate inorganic carbon (PIC) flux, 1:372–373 particulate organic carbon (POC) flux, 3:310 salinity, 3:913F seasonal cycles, 6:215 sedimentary sequences, upwelling indicators, and monsoon activity, 3:911 uranium-thorium series profiles, 6:247F water temperature, 3:913F Arabian Sea Water (ASW), temperature–salinity characteristics, 6:294T, 6:298, 6:298F Arabidopsis thaliana (thale cress), 3:553 Arafura Sea, winds, 5:306 Aragonite, 1:445–446, 2:104–105 saturation state, 3:400 coastal waters, 3:400F solubility, 1:447 see also Aragonite critical depth Aragonite critical depth (ACD), 1:448 Arcachon Bay, France aquaculture, 3:102 oyster culture, 1:205, 1:207T Archaea, 1:269–270, 2:77 16S rRNA phylogenetic analysis, 2:75 Archaeoglobales, 2:77–78
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lipid biomarkers, 5:422F Methanococcus jannaschii, 2:77–78 Methanopyrus, 2:77–78 Pyrolobus fumarii, 2:77–78 Thermococcales, 2:77–78 Archaean Earth, deep-sea hydrothermal vents and the origin of life, 2:78–79 Archaeocetes, 3:591, 3:592–593 see also Cetaceans Archaeogastropod limpet (Neomphalus fretterae), vent fauna origins, 3:155–156 Archaeoglobales (archaea), 2:77–78 Archaeological artifacts documentation/recovery, of ship’s timbers, 3:697 preservation, deep-water sites favouring, 3:699 recovered by Throckmorton (Peter), 3:696 sites stripped of, 3:695–696 tagging of objects, early maritime archaeology, 3:697 see also Archaeology (maritime) Archaeology (maritime), 3:695–701 deep-water see Deep-water archaeology early history absence of archaeologist, 3:696 Antikythera wreck raided, 3:696 burial ships, 3:695 government salvage operation, 3:696 Greek government recovery of treasures, 3:696 land-locked boats, 3:695 mapping protocol established by Bass (George), 3:696 oldest intact ship, 3:695 Peter Throckmorton recovery of artifacts, 3:696 Roman wreck investigated by JacquesYves Cousteau, 3:696 SCUBA invented by Jacques-Yves Cousteau, 3:695 ship construction methods, 3:697 ship’s timbers documented and recovered, 3:697 shipwreck as time capsule, 3:695 sites stripped of artifacts, 3:695–696 techniques become standard, 3:696–697, 3:698F wire grids cover site, objects tagged, 3:697 wreck torn apart by salvage ship, 3:696 Yassi Adav wreck excavated, 3:696 early ideas, 3:695 early attempts, 3:695 emergence of discipline, 3:695 undiscovered sunken ships, 3:695 ethics, 3:699–701 American salvagers target Florida, 3:700 history of salvage creating difficulties, 3:699–700
Index Law of the Sea Convention sought, 3:701 laws protect offshore sites (not deepwater sites), 3:700–701 marine salvagers seek archaeological expertise, 3:700 treasure hunters relocate Spanish galleon, 3:700 uneasy relationship with divers, 3:700 expertise sought by marine salvagers, 3:700 growth, 3:697–698 Columbus to the American Civil War, 3:697 deep water search for major vessels, 3:698 Indian boats in Central American sinkholes, 3:697 insights into historical trade, 3:697 Kyrenia wreck raised by Michael Katzev, 3:697 Mary Rose recovered by Margaret Rule, 3:697 Mediterranean maritime archaeology, 3:697 PaleoIndian settlements in North America, 3:697 work in Northern Europe, 3:697 World War II vessels documented, 3:698 marine methodologies, 3:698–699 magnetic sensors, 3:698 remotely operated vehicles (ROVs), 3:699, 3:700F search strategies (by George Bass), 3:698, 3:698F SHARPS acoustic positioning system, 3:698–699 side-scan sonars introduced, 3:698 see also Archaeological artifacts Archeogastropod limpets, 3:135 Lepetodrilus elevatus, 3:136F, 3:138F Archimedes screw driven robotic miner, 3:893 Arctic (region) acoustics see Acoustics, Arctic climate, 5:86 continental margins, primary production, 4:259T diffusive convection, 2:167 eastern, mean ice draft, 5:152F ecosystems, 5:86 chlorinated hydrocarbons, 1:561 expeditions, 3:121 sea ice see Arctic sea ice thermohaline staircase, 2:167F warming, 5:85, 5:86 see also Arctic Basin; Polynyas; individual countries Arctic Basin, 4:126–127 circulation, 4:123 sea ice cover, 5:141 cover in future, 5:144
thickness, 5:151, 5:176 trends, 5:175 see also Arctic Ocean; Arctic sea ice Arctic Bottom Water (ABW), 2:80, 2:82F temperature–salinity characteristics, 6:294T Arctic Career, 4:770F Arctic charr (Salvelinus alpinus), 5:32 Arctic Climate Observations using Underwater Sound (ACOUS) experiment, 6:52–54 Arctic ice zones, seabird associations, 5:229 see also Arctic sea ice Arctic Ice Dynamics Joint Experiment (ADJEX), 5:159, 5:160–162 Arctic Intermediate Water (AIW) acoustics, 1:94–95 temperature–salinity characteristics, 6:294T Arctic Mediterranean Sea, 1:211, 1:212F intermediate circulation, 1:219F upper layer circulation, 1:216F water column profiles, 1:214F see also Arctic Ocean Arctic Ocean, 4:126 acoustics see Acoustics, Arctic Atlantic water inflow, 1:213, 1:218F see also Atlantic water bathymetric map, 1:93F benthic foraminifera, 1:339T bottom water formation, 1:218 geothermal heat flux and, 1:220 circulation, 1:211–225, 1:211–218 drivers, 1:218–221 mixing, 1:220–221 surface water, 1:212 transports, 1:223–224 variability, 1:221–223 see also Atlantic water deep water mixing, 1:219–220 salinity, 1:219–220 see also Atlantic water drifting stations, 5:162F eddies, 1:220–221 effect on global climate, 1:224 freshwater flux, 6:171 halocline, 1:212–213 heat flux, 1:224 icebergs, 3:181–182, 3:187 sources and drift paths, 3:183F ice cover, 1:222 ice export, 1:224 ice islands, 3:194 internal wave energy, 3:207 internal waves, 3:271 keels of pressure ridges, 3:191–193 krill, 3:351, 3:352–353 multiyear ice, 5:170 nuclear fuel reprocessing, 4:87–88 overflow through Denmark Strait, 4:266 overview, 1:211 Pacific water, 1:218F polynyas, 4:544 radioactive wastes, disposals of, 4:629
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river inputs, 4:759T salinity profiles, 1:213F, 2:120F sea ice, 5:160, 5:160F, 5:171, 5:175–176 see also Arctic sea ice shelf inflow, 1:220 sound speed profile, 1:94F, 1:95 temperature profiles, 1:213F, 2:120F vertical structure, 1:211 water masses, 1:211, 1:215T see also Arctic (region); Arctic Mediterranean Sea; Arctic Oscillation (AO); Arctic sea ice; Polar ecosystems Arctic Oscillation (AO), 4:66–67, 5:88–89, 6:167–168 Arctic Ocean Circulation and, 1:222 North Atlantic Oscillation and, 4:65, 4:67 sea ice cover and, 5:146 Arctic pressure fields, sea ice extent and, 5:147F Arctic sea ice, 5:160F, 5:171, 5:175–176 Arctic Basin see Arctic Basin Arctic Ocean, 5:85–86, 5:85F decrease, 5:85 drift patterns, 5:160 extents, 5:85, 5:88–89 geographical extent, 5:141–143, 5:142F, 5:143–146, 5:144F Kara and Barents Seas, 5:85–86, 5:85F Northern Hemisphere, 5:85–86, 5:85F, 5:87–88 oscillatory pattern, 5:85, 5:86 Seas of Okhotsk and Japan, 5:85–86, 5:85F thickness, 5:151–155, 5:152F see also Arctic Ocean; North Atlantic Oscillation (NAO); Okhotsk Sea, circulation; Polar ecosystems Arctic shelves, ice-induced gouging, 3:191–195 Arctocephalinae (fur seals), 3:590, 3:609T, 5:286T see also Otariidae (eared seals) Arctocephalus gazella (Antarctic fur seal), Southern Ocean fisheries, harvesting history, 5:513 ‘Area,’ the, Law of the Sea jurisdiction, 3:435 Area closures control systems, fishery management, 2:516, 2:546 fishery multispecies dynamics, 2:508 Arenicola spp. (annelid worms), 5:55F Argentine Basin, turbidity, 4:16 Argentine hake (Merluccius hubbsi) demersal fisheries, southwest Atlantic, 2:96, 2:97F total world catch, 2:91, 2:91T Argo, 5:75 Argo II optical/acoustic mapping systems, 2:22–23, 2:27F Argon atmospheric abundance, 4:55T cosmogenic isotopes, 1:679T oceanic sources, 1:680T
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Index
Argon (continued) production rate, 1:680T reservoir concentrations, 1:681T specific radioactivity, 1:682T tracer applications, 1:683T, 1:686 isotopes, origin of oceans, 4:262F phase partitioning, 4:56T as radioisotope source, 1:679 saturation responses, 4:57–58, 4:58F seawater concentration, 4:55T tracer applications, 1:686, 4:56–57 Argo program, 2:175 ARGO project, 6:165–166, 6:173 Argos satellite system, 2:174 ARIES (Autosampling and Recording Instrumental Environmental Sampler), 6:363–364, 6:363F Aristostomias spp. (barbeled dragonfishes), 2:453, 2:455F Arkona Basin, Baltic Sea circulation, 1:288, 1:289F, 1:290F, 1:294, 1:295 Arno, Italy, sediment load/yield, 4:757T Arnoux’ beaked whale, 3:648–649 Arrhenius, G O S, 5:339–340 Arrhenius, Svante, 4:509 Arribada, 5:213–214, 5:214F Arrow worms (Chaetognatha), 1:379–380 ARS see Acoustic ripple scanner Arsenic (As), 3:776, 3:780–781, 3:783 anoxic waters, 3:780–781 atmospheric deposition, 1:254T depth profile, 3:780–781, 3:781F detoxification by phytoplankton, 3:780–781 global atmosphere, emissions to, 1:242T methylated, 3:780–781, 3:781F oxic waters, 3:780–781 riverine flux, 1:254T toxicity, 3:780–781 Artemis, 4:770F Artificial neural nets (ANN), in analytical flow cytometry, 4:246 Artificial reef deployments, fishery stock manipulation, 2:532 Artificial reefs, 1:226–233 advances, 1:230–232 attachment surfaces, 1:229F description, 1:226 design/construction advances abiotic/biotic factors, 1:231 construction phases, 1:231 designs used, 1:231, 1:231F, 1:232F factors dictating design, 1:231 feasibility, 1:231–232 key aspects, 1:231 obsolete ships/platforms, 1:232 experimental modules, 1:229F history/origins, 1:226 planning, advances components, 1:230–231 emphasis of, 1:230 published guidelines, 1:230 purposes, 1:226 reef integration, 1:232 adaptative management, 1:232
evaluation, 1:232 realistic expectations, 1:232 ‘rigs to reefs’ program, 4:750–751 scientific understanding, 1:228–230 advances made, 1:228–229 attraction-production question, 1:229–230 continued debates/questions, 1:230 demographics and exploitation rates, 1:230 history of inquiry, 1:229 species use of reefs, 1:230 utilization, 1:226–228 aquaculture uses, 1:227–228 by artisanal fishing communities, 1:227 Caribbean countries, 1:226–227 ecosystem restoration, 1:228 India, 1:226–227, 1:227 Japan, 1:227, 1:227F Korea, 1:227–228 marine ranching programs, 1:227–228 natural material reefs, 1:226–227, 1:226F non-purpose artificial reefs, 1:228 southern Europe and Southeast Asia, 1:227 Spain, 1:228F Thailand, 1:227 tourism, 1:228 United States, 1:227, 1:228F see also Cold-water coral reefs; Coral reef(s) Artificial sea water, aquarium fish mariculture, 3:526 Wiedermann–Kramer formula, 3:527T Arus Lintas Indonen (ARLINDO) expedition, 5:316 As226, definition, 6:242 ASCAT (Advanced Scatterometer), 5:203 Ascent, glider, 3:62 ASDIC (Antisubmarine Detection Investigation Committee), 5:504 Ashmole, Phillip, 5:249 Asia anthropogenic reactive nitrogen, 1:244–245, 1:245T commercial salmon fisheries, 5:13 see also Pacific salmon fisheries decline in chum salmon, 5:17 land-sea fluxes, human impact, 3:401–403 monsoons evolution, 3:915–916 global climate and, 3:917 long-term evolution of, 3:917 port efficiency, 5:407 river water, composition, 3:395T see also Southeast Asia Asparagopsis armata algae, 4:428 Aspridonotus taeniatus (saber-toothed blenny), 2:377 Assateague Island, Maryland, USA, coastal erosion, 1:582 Assimilation efficiency, definition, 4:337
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AST see Acoustic scintillation thermography (AST) Astaxanthin, 3:569 structure, 3:570F Asterias amurensis (North Pacific sea star), 2:342 Aster X, 6:263T Astrochronology see Astronomical polarity timescale (APTS) Astrocopus spp. (stargazers), 2:474 Astronomical polarity timescale (APTS), 3:30–31, 3:31F applications, 3:30 geomagnetic polarity timescale vs., 3:30 see also Geomagnetic polarity timescale (GPTS) Astronomy tidal dissipation, 3:255 tidal forces, astronomical periods modulating, 6:35T Astyanax spp. fish, 2:481 ASUW see Atlantic Subarctic Upper Water (ASUW) ASW see Arabian Sea Water (ASW) ASW (anti-submarine warfare), 5:504 AtD, definition, 6:242 Atlantic see Atlantic Ocean Atlantic bluefin tuna see Thunnus thynnus (Atlantic bluefin tuna) Atlantic cod (Gadus morhua), 2:378 Baltic Sea populations, 2:488 camouflage, 2:461 demersal fishery landings, 2:90, 2:90F water temperature effects, 2:93, 2:93F diet, 2:463–464, 2:464F exploited population dynamics, 2:181–182, 2:182F, 2:183, 2:183F fishery multispecies dynamics, predation, 2:509, 2:509F, 2:510, 2:510F fishery stock manipulation historical aspects, 2:528–530 release quality, 2:530–531 migration, 2:406, 2:406F ontogenetic feeding shifts, 2:379 range extension, 2:487–488 role in fiordic ecosystems, 2:365 size limits, fishery management, 2:516 stock enhancement/ocean ranching programs, Norwegian evaluation, 4:150–151, 4:151F total world catch, 2:91, 2:91T turbulence effect on, 5:491 vertical migration patterns, 2:412 Atlantic herring (Clupea harengus), 2:375, 2:463–464, 2:484, 4:364 avoidance of turbulence, 5:491 demersal fishery landings, 2:90, 2:90F fishery stock manipulation, release quality, 2:530–531 migration, 2:405, 2:405F ontogenetic feeding shifts, 2:376, 2:376F pelagic fishery landings, 5:468, 5:469T schooling decisions, 2:440–441, 2:441F
Index stock biomass, pelagic fishery management, 5:472, 5:472F vertical migration, 2:442F Atlantic Ionian Stream (AIS), 2:5, 3:719F, 3:720, 3:720T jet, 1:748–751, 1:748F Atlantic mackerel (Scomber scombrus), 2:404–405, 2:405F see also Mackerel (Scomber scombrus) Atlantic Marine Coring (AMCOR) project, 5:554 Atlantic meridional overturning circulation (MOC), 1:224, 4:126, 4:129 cooling phase, 4:126 depth range, 4:126 mean temperature, 4:126 northward flow, 4:129 salt increase, 4:126 warming phase, 4:129 see also Meridional overturning circulation (MOC) Atlantic Multidecadal Oscillation (AMO), 4:713 see also North Atlantic Oscillation Atlantic Ocean basin structure, 1:718–720, 1:719F benthic foraminifera, 1:339T calcite, depth profile, 1:448F carbonate compensation depth, 1:453F carbonate saturation, 1:450–451 Central Water, pseudo age, 6:183F circulation modes, 1:3–4, 1:4F climate effects on fisheries, 2:487–488 continental margins, 4:256T primary production, 4:259T current systems see Atlantic Ocean current systems (below) deep passages, 2:566–569 density (neutral) profile, 2:261F Ekman transport, 2:225 El Nin˜o Southern Oscillation counterpart, 1:234, 1:236–237 equatorial currents see Atlantic Ocean equatorial currents ferromanganese oxide deposits, 3:488T geohistorical studies, 1:347 heat transport, 6:168–170 proportion of global total, 3:120 illite, 1:563–564 Intertropical Convergence Zone, 1:721–723 krill, 3:350–351, 3:350F, 3:351F, 3:353 low macrobenthic diversity, 3:473 variations, 3:473 magnetic anomalies (linear), 3:485F manganese nodules, 3:492, 3:494 mean albedos, 4:380, 4:380T neodymium isotope ratio depth profiles, 3:458F nepheloid layers, 4:14F nitrate transport, 3:304, 3:305F North see North Atlantic North Atlantic Oscillation Index, 2:216 North-eastern see North-eastern Atlantic
North-west see North-west Atlantic ocean gyre ecosystem, 4:133 overflow from Mediterranean, 4:265 oxygen isotope ratios, 4:272, 4:272F Pacific Ocean vs., 1:234, 1:236–237 pelagic fisheries, 4:368 planktonic foraminifera, 4:610F, 4:611F radiocarbon, 4:641F, 4:642 radiocarbon circulation model, 4:111, 4:111F radium-226 depth profile, 6:252F radium isotope distribution, 6:251, 6:252F salinity, meridional sections, 1:415F salinity contours, 3:458F sea–air flux of carbon dioxide, 1:493, 1:493T sea ice trends, 5:175 seamounts and off-ridge volcanism see Vesteris seamount silicate vertical profile, 3:678–679, 3:679F silicon flux, 1:372–373 sound speed contours, 1:102F South see South Atlantic southwest, demersal fisheries, 2:96, 2:97F subsurface passages, 1:15–16, 1:15F subtropical salinities, 5:128F see also Water types and water masses temperature, meridional sections, 1:415, 1:415F thermohaline circulation, 2:554 tides, 6:37 topography, 1:718, 1:719F trace element concentrations, 6:78 trace metal isotope ratios, 3:457 beryllium, 3:464F uranium isotope ratio depth profile, 6:246F water masses temperature–salinity characteristics, 6:292–293, 6:293F, 6:294T, 6:297, 6:297F upper waters, 6:295, 6:295F, 6:297 see also North Atlantic; North Atlantic Oscillation; South Atlantic Atlantic Ocean current systems, 1:718– 727 abyssal see Abyssal currents deep-ocean, 1:724–726, 1:725F equatorial see Atlantic Ocean equatorial currents future research, 1:726 historical developments, 1:720, 1:721F thermohaline circulation, 1:16, 1:17F transport, 1:724T warmwatersphere, 1:720–724, 1:722F, 1:723F, 1:724T North Atlantic subtropical gyre, 1:720–721, 1:722F, 1:723F, 1:724T South Atlantic subtropical gyre, 1:720–721, 1:722F, 1:723F, 1:724T Southern South Atlantic, 1:724T subpolar gyre, 1:724, 1:724T transport, 1:724T
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see also Ocean circulation; specific currents Atlantic Ocean equatorial currents, 1:234–237, 1:234F flow, 1:721–723, 1:722F, 1:723F, 1:724T Indian Ocean equatorial currents vs., 3:226, 3:236 interannual variations, 1:236–237 seasonal variations, 1:235–236, 1:235F stability, 1:237 time-averaged, 1:234–235 see also specific currents Atlantic puffin, 1:171, 1:173F see also Alcidae (auks) Atlantic Ridge, manganese nodules, 3:492 Atlantic ridley turtle, 5:217–218, 5:217F see also Sea turtles Atlantic salmon (Salmo salar), 2:377, 2:501 diet, 5:33 distribution, 5:30 ears, 2:477F farming production, 5:5, 5:6F, 5:24, 5:24T vaccination status, disease prevention, 3:522, 3:522T see also Atlantic salmon (Salmo salar) fisheries food, 5:33–34 life cycle, 5:31F mariculture, 2:334, 3:539 migration, 5:34F, 5:35F, 5:36F migration times, 4:148 movements, 5:33 predation, 5:35 recreational fishing, 5:1, 5:4, 5:4–5, 5:9 taxonomy, 5:29 wild, homing precision, 4:148 Atlantic salmon (Salmo salar) fisheries, 5:1–11 by-catch issues, 5:3–4 catch, 5:2–4, 5:3F, 5:8F by country, 5:3, 5:4T, 5:5F distant water, 5:2, 5:5–6, 5:6F economic value, 5:4–5 ghost fishing, 5:3–4 harvesting methods, 5:1–2, 5:6 historical aspects, 5:1 home water, 5:2, 5:2T, 5:8–9 management, 5:5–6 compensation arrangements, 5:8 precautionary approach, 5:9–10, 5:9F, 5:10F mixed stock, 5:2 restoration program, 5:5 stock enhancement/ocean ranching, 2:530, 4:147–148, 4:147T, 4:148 subsistence, 5:1 see also Atlantic salmon (Salmo salar), farming Atlantic Subarctic Upper Water (ASUW), temperature–salinity characteristics, 6:294T Atlantic sublayer, Arctic ocean, warming, 5:154–155
436
Index
Atlantic thermohaline circulation, 1:3, 1:4, 2:554 see also Thermohaline circulation Atlantic Water (AW) Arctic Ocean, 1:213 Barents Sea, 1:215 Barents Sea branch, 1:215 variability, 1:222 Canada basin, 1:216 current interleaving, 1:217F Fram Strait branch, 1:216 heat transport, 1:224 Mediterranean Sea entry, 1:745–746, 1:746 seismic reflection water-column profiling, 5:353F, 5:354 Severnaya Zemla, 1:217F St. Anna Trough, 1:215 variability, 1:221, 1:222 Atmosphere carbon dioxide flux, coastal zone, 3:400F circulation at low latitudes, 2:242 components of global climate system, 2:48F convective zones, 2:242 cosmogenic isotope concentrations, 1:681T El Nin˜o Southern Oscillation model and, 2:242 heat exchange with ocean, 3:116 heat transport, 3:114–115, 3:115F, 3:119 internal waves, 3:272 measure/unit of pressure, 1:355 metals, emission of, 1:242T oceanic forcing North Atlantic Oscillation (NAO), 4:71–72 see also Atmospheric forcing; Wind forcing ocean surface interactions, 5:91 as one-layer fluid on rotating sphere model, 2:242 trace metals, aeolian inputs, 1:126T concentration, 1:125T global emission rates, 1:124T transport of particulate material to ocean see Aerosols see also entries beginning atmospheric Atmosphere–ocean general circulation models (AOGCMs) future climate, 5:181 in paleoceanography, 4:305 see also Paleoceanography Atmosphere–sea ice–ocean system, 5:170–171 Atmospheric aerosols, infrared atmospheric correction algorithms, SST measurement, 5:93 Atmospheric boundary layer, storm surges, 5:536–537 Atmospheric carbon dioxide see Carbon dioxide (CO2) Atmospheric corrected algorithms, infrared,
see also Satellite remote sensing of sea surface temperatures Atmospheric correction, ocean color, 4:735, 5:119–120 Atmospheric deposition metals see Metal(s) nitrogen species see Nitrogen open ocean see Global ocean synthetic organic compounds, 1:241–242 Atmospheric forcing, 6:193–194 mixed layer properties and, 6:218 upper ocean structure response, 6:192–210 drag coefficient, 6:192–193, 6:193, 6:194, 6:208 see also Atmosphere, oceanic forcing Atmospheric general circulation models (AGCMs) application to paleoclimate problems, 4:303, 4:305, 4:307 North Atlantic Oscillation, 4:71 see also Paleoceanography Atmospheric lead flux, 1:243–244 Atmospheric nitrogen isotope ratio, 4:40 see also Dinitrogen (N2); Nitrogen (N) Atmospheric pressure, 1:355 Black Sea, 1:214F, 1:404F changes with altitude, 5:375 El Nin˜o Southern Oscillation and, 2:228 measurements, 5:375 North Atlantic Oscillation (NAO) and, 4:66F sea surface, measurement, 6:306–307 Atmospheric temperature, climate models, 2:608–609 Atmospheric turbulence, acoustic noise, 1:54–55, 1:55 Atmospheric windows, 5:91 Atoll lagoons, 3:377–378 Atolls, 1:662, 1:663F formation, coral reef geology, 1:666F formation theory (Darwin, Charles), 1:666F geomorphology, 3:34, 3:34F, 3:37 zonation, 1:664 see also Coral reef(s) Atomic absorption spectrophotometry (AAS), 2:104 Atomic emission spectrometry (AES), 2:103–104 Atomic weapons, 5:327 see also Bomb carbon ATP (adenosine triphosphate), 6:82–83, 6:85 ATSR see Along-Track Scanning Radiometer (ATSR) Attack angle, gliders, 3:63 Attenuation acoustics in marine sediments, 1:76–78, 1:80, 1:82, 1:90 light attenuation anomalies see Light attenuation anomalies Attenuation coefficient, as bio-optical model quantity, 1:386T
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ATV, 6:260T Audubon’s shearwaters (Puffinus Iherminieri), 4:590, 5:252 see also Procellariiformes (petrels) Auklet(s) crested, 1:171, 1:173F least, 1:171, 1:173F migration, 5:244–246 see also Alcidae (auks) Auks see Alcidae (auks) Aulostomus maculatus (trumpet fish), 2:377 Aurelia aurita, 1:69, 4:705 Austaush coefficient, Ae, 2:324–325 Australasian Mediterranean Water (AAMW), 6:182–183 Australia anthropogenic reactive nitrogen, 1:245T eastern, continental shelf, effects of East Australian Current, 2:194–195, 2:196F El Nin˜o events and, 2:228 Hoplostethus atlanticus (orange roughy) fishery, 4:230 Northwest Shelf, shoreline reconstruction, 3:58 southern, continental margins, sediments, 4:141–142 Australian salmon (Arripus trutta), 3:444–445 Austral islands, off-ridge non-plume related volcanism, 5:300 Authigenesis, 1:268 Authigenic deposits, 1:258–268 barites, 1:264–265 ferromanganese, 1:258–260 composition, 1:258–259 crusts, 1:261–262, 1:263F metal sources, 1:259–260 nodules, 1:258–260, 1:259F, 1:260F trace metal sources, 1:260–261 phosphites, South American shelf, 1:263F phosphorites, 1:262–264 silicates, 1:265–266 palygorskite and sepiolite, 1:266–268 smectites, 1:266–268 zeolites, 1:265–266 Authigenic mineral formation, 1:543–545 Authigenic minerals extraction, 3:890–898, 3:891F components, 3:896F density separation, 3:896 financial model, 3:892 lease, 3:892–893 lift, 3:893–895 magnetic separation, 3:896 metal sales, 3:897–898 mineral pick up, 3:893 processing, 3:895–897 refining process, 3:897–898 remediation of mine site, 3:898 solvent extraction, 3:897 steps, 3:890–891 survey the mine site, 3:891–892
Index transport, 3:893–895 see also specific minerals Autocatalysts, release of platinum group elements into environment, 4:502, 4:502F Autochthonous processes, 1:565–567 clay minerals, 1:565–567 Automatic feeding systems, salmonid farming, 5:26 Autonomous Benthic Explorer (ABE), 4:474F, 6:263T, 6:265, 6:370 appearance, 2:26F development at Woods Hole, 2:34, 6:262–263 tracklines , Juan de Fuca Ridge dives, 2:35F Autonomous Lagrangian Circulation Explorer (ALACE), 2:175F, 3:59, 6:370 ALACE floats, Weddell Sea circulation, 6:319, 6:321F Autonomous Ocean Sampling Network (AOSN) program, 3:60 Autonomous Ocean Sampling Network II (AOSN) program, 4:483, 4:483F Autonomous robot submersible shuttle (PLA) system, 3:892F Autonomous underwater hydrophones (AUH), 3:839 Autonomous underwater vehicles (AUVs), 3:511–512, 3:891, 4:473–484, 4:473, 6:260–265, 6:261–262 advantages, 4:473–475, 6:260–261 applications, 4:479–480, 6:260 mapping, 4:479–480 under-ice operations, 4:481–482 water-column profiling, 4:480–481 Arctic, acoustic research, 1:99 bathymetric survey, 4:480F compared with alternatives, 4:479 cost, 4:479, 4:479F CTD profilers in, 6:165–166 deep submergence and, 2:26F definition, 4:473–475 disadvantages, 6:260–261 drifters, 6:261–262 failure, 4:477 future prospects, 6:263–265 hull shape, 4:473 instrumentation, 6:261–262 mission types, 4:477 multiple thruster type, 4:473 navigation, 4:477–479 acoustic, 4:478 dead-reckoning, 4:478 geophysical parameter-based, 4:478–479 observation systems/observatories and, 4:482–483 performance modeling, 4:475 propulsion, 4:473, 4:476F range, 4:475 seafloor imaging, 6:263 software, 4:477 sonar, 4:479–480 systems, 4:475–477
thermal gradient engine, 4:474–475 types, 4:473, 4:474F water-column profiling, 4:480 zooplankton sampling, 6:370 see also Gliders (subaquatic) Autonomous Vertically Profiling Plankton Observatory (AVPPO), 6:366 Autoregressive (AR) functions, regime shifts, 4:720 Autosampling and Recording Instrumental Environmental Sampler (ARIES), 6:363–364, 6:363F Autosub 3, 6:263T Autosub 6000, 6:263T Autotrophic organisms, 4:103 Autotrophs, definition, 3:805 AUVs see Autonomous underwater vehicles (AUVs) Available potential energy (APE), meddies, 3:706–707 Average taxonomic distinctness, 4:535 Average taxonomic diversity, 4:535 AVHRR (Advanced Very High Resolution Radiometer), 4:543 AVIRIS see Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) AVPPO (Autonomous Vertically Profiling Plankton Observatory), 6:366 AVR see Axial volcanic ridges (AVR) Aw226, definition, 6:242 Axial magma chamber (AMC), 3:819F definition, 3:854–855 mid-ocean ridges, magma supply, 3:854–855 seismic structure, 3:829–830 characteristics, 3:830, 3:830–832 Costa Rica Rift, 3:830, 3:834F crystal mush zone, 3:830, 3:832, 3:833F depth, 3:834–836, 3:835, 3:835F early studies, 3:829–830 magma lens, 3:830, 3:834, 3:835F reflection, 3:829–830, 3:829F segmentation, 3:830 spreading rate, variation with, 3:832, 3:833F, 3:834, 3:835F see also East Pacific Rise (EPR); Midocean ridge seismic structure Axial summit trough, 3:819F definition, 3:860 East Pacific Rise (EPR), 3:860 hydrothermal vent deposits, 3:144–145 indicator of volcanic activity, 3:860 neovolcanic zone, 3:815 Axial volcanic ridges (AVR), 3:815–816 definition, 3:860–861 Azimuthal velocity, meddy ‘Sharon’, 3:703, 3:704F Azores Current, 1:467, 1:720–721, 2:556 Canary/Portugal Currents and, 1:467, 1:474, 1:476 transport, 1:724T see also Atlantic Ocean current systems; Canary Current; Portugal Current
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Azores High see North Atlantic Oscillation Azov Sea, 1:401
B Bab El Mandeb, Strait see Strait of Bab El Mandeb Babi Island, 6:128–129 Bacillus, 2:78 Back arc spreading centers, hydrothermal vent fluids, chemistry of, 3:164, 3:166F Backscatter acoustic see Acoustic backscatter microwave, 5:202–203 see also Scatterometry from ocean surfaces, satellite remote sensing, 5:104–105 Backscattering (optical) coefficient, 4:622, 4:733 as bio-optical model quantity, 1:386T, 1:387–388, 1:392–393 components, 4:734 Backscattering efficiency, as bio-optical model quantity, 1:386T, 1:387–388 Backscattering sensors, 3:246, 6:115 see also Nephelometry Backstripping method (for sea level estimation), 5:189–191, 5:190F, 5:193 Backup recovery, moorings, 3:921 Bacteria analytical flow cytometry, 4:246–247, 4:246F benefits to benthos, 1:351, 3:467 bioluminescence, 1:376, 1:377T, 1:380, 1:383–384, 1:527 chemoautotrophic, 1:355, 2:57–58 controlling agents, 4:465 deep-sea ridges 16S rRNA phylogenetic analysis, 2:75 Aquificales, 2:78 Bacillus, 2:78 Desulfurobacterium, 2:78 epsilon proteobacteria, 2:76–77, 2:77, 2:78 Thermotogales, 2:78 Thermus, 2:78 denitrification, 3:813–814 estuaries, 3:660 lipid biomarkers, 5:422F mats see Bacterial mats microbial loops see Microbial loops mortality, viruses contributing to, 4:465, 4:468–469 nitrogen cycle and, 4:32–33, 4:33T see also Nitrogen cycle as optical constituents of sea water, 4:624 photosynthesis, 4:425 as primary particles, 4:331F, 4:332 see also Particle aggregation dynamics removal by viruses, 4:465 salt marshes and mud flats, 5:44
438
Index
Bacteria (continued) sea ice ecosystems, 4:515–516 spores, tracer applications, 6:90 symbiotic relationships deep-sea animals, 1:355 fish, 1:380–381 squid, 1:380, 1:527 vent animals, 2:57–58 see also Bacterioplankton; Cyanobacteria; Microbes; Microbial loops Bacterial disease, mariculture see Mariculture Bacterial mats, 2:63, 2:73–75, 6:227 Peru-Chile Current System, 4:390 Bacterial production, 1:271F, 1:272, 1:273–274 Bacterial respiration, 1:272, 1:273–274 Bacteriophage, 4:467 of Bacteroides fragilis, sewage contamination, indicator/use, 6:274T Bacterioplankton, 1:269–275 abundance compared with phytoplankton, 1:272–273 euphotic zones, 1:273F gradient across zones, 1:272–273 biomass, 1:272–274 compared with phytoplankton, 1:273, 1:274T environmental assessments, 1:273 estimates, 1:273 food webs and biogeochemical cycles, 1:274–275 bacteriovores, 1:274 coastal and estuarine food webs, 1:275 nutrient cycling, 1:275 nutrient regeneration, 1:275 viruses, 1:275 see also Network analysis of food webs; Primary production measurement methods; Primary production processes functions, 1:269 growth and production, 1:272–274 identification methods, 1:270F identity and taxonomy, 1:269–271 domain Archaea, 1:269–270 domain Bacteria, 1:270–271 identification methods, 1:269 nutrition and physiology, 1:271–272 bacterial growth efficiency, 1:272 averages, 1:272 use of substrates, 1:272 dissolved organic matter, 1:269, 1:271 growth and primary production, 1:271–272, 1:271F nutrient limitation, 1:271 oligotrophs vs. copiotrophs, 1:272 sea water culture experiments, 1:271 production compared with phytoplankton, 1:274T measurement methods, 1:273–274
research improvements, 1:269 total bacterial carbon utilization, 1:274 see also Microbial loops; Plankton and small-scale physical processes Bacterivory, 3:805 Bacteroides fragilis phages, sewage contamination, indicator/use, 6:274T Baffin Bay icebergs, 3:181, 3:186–187 polynyas, 4:540 sea ice cover, 5:142–143 sea ice thickness, 5:151 Bahamonde’s beaked whale, 3:643 Baie d’Audierne, Brittany, France, 3:379F Baiji (Lipotes vexillifer) see Yangtze river dolphin (Lipotes vexillifer) Baird, Spencer Fullerton, 2:499–500 Baird’s beaked whale (Berardius bairdii), 3:643, 3:648, 3:649 Balaena mysticetus see Bowhead whale Balaenids see Right whales (balaenids) Balaenoptera musculus see Blue whale Balaenoptera musculus see Blue whale Balaenopterids (rorquals), 1:276, 1:277T, 3:594 growth and reproduction, 1:284 trophic level, 3:623F see also Baleen whales; specific species Baleen, definition, 1:287 Baleen whales (Mysticeti), 1:276–287, 3:592F, 3:606–607T annual feeding and reproductive cycle, 3:611–612, 3:611F behavior, 1:282–283 growth and reproduction, 1:284 migration, 1:283 social activity, 1:283–284 sound production, 1:282–283 swimming, 1:283 characteristics, 1:276–278, 1:278F, 3:591, 3:610F competition between species, 1:286–287 depletion, Southern Ocean, 2:510–511, 5:513 distribution, 1:278–279 ecology, 1:278–279 evolution, 3:593 exploitation, 3:637–638 extinct families, 3:593 feeding in gyre ecosystems, 4:135 food/feeding, 1:280–282, 1:281T daily consumption, 1:282 filter-feeding apparatus, 1:278F, 1:280–281, 3:615–616, 3:616F habitat, 1:278–279 importance of krill, 3:355 life history, 1:282–283 migration, 3:596–598 reasons for, 3:598 surveillance, 3:598 variation in patterns, 3:597–598, 3:597F annual, 3:597–598 intraspecific, 3:597
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parasites, 1:282 population status, 1:284–287 assessment, International Whaling Commission’s Scientific Committee, 1:285–286 recovery, 3:598 World Conservation Union ‘Red List’ categories, 1:285, 1:286T predators, 1:282 killer whales, 1:282 skeleton, 3:591F, 3:610F sound production, 1:358 taxonomy, 1:276, 1:276–278, 1:277–278, 1:277T, 3:593 family Balaenidae see Right whales family Balaenopteridae see Balaenopterids family Eschrichtiidae see Gray whale (Eschrichtius robustus) family Neobalaenidae see Pygmy right whales threatened species, 1:285, 1:286T threats, 1:284–285 toothed whales vs., 1:276 trophic level, 3:622, 3:623F see also Cetaceans; specific species Ballast law and regulation, 5:407 transport of non-indigenous species, 5:407 Ballasting, RAFOS float, 2:177 Ballast systems, manned submersibles (shallow water), 3:515 Baltic Current, origins, 1:291–292 Baltic Sea anoxic areas, 2:313, 2:317F climate effects on fisheries, 2:488 cyanobacterial bloom, 4:739F eutrophication, 2:308T, 2:318F habitat effects, 3:179–180 hypoxic areas, 2:317F iridium profile, 4:497, 4:499F manganese nodules, 3:488–489 multispecies dynamics, 2:505–506, 2:507F nitrogen, atmospheric input, 1:241T regime shifts, 4:704 salmon fisheries, 5:4 sea ice drift velocity, 5:163F Baltic Sea circulation, 1:288–296 Aland Sea, 1:288, 1:289F Belt Sea, 1:288–289, 1:289F, 1:290–291 bottom currents, 1:293 bottom topography, 1:288, 1:289F, 1:292, 1:293–294 channels Bornholm Channel, 1:288, 1:293 Stolpe Channel, 1:288, 1:290–291, 1:293 Danish straits see Danish Straits Darss sill, 1:288, 1:290F, 1:294, 1:295F downwelling, 1:293–294, 1:294F estuarine circulation, 1:289–292 Gulf of Bothnia, 1:288, 1:290–291, 1:296
Index Gulf of Finland, 1:288, 1:289, 1:289F, 1:290F, 1:296 halocline, 1:288, 1:290F hydrogen sulfide enrichment, 1:294–295 inflows, 1:288, 1:290–291, 1:293, 1:294–295 major events, 1:294–296, 1:295 bottom water renewal, 1:295 favorable conditions, 1:295 see also Danish Straits interannual variations, 1:288, 1:293 Kattegat, 1:288, 1:289, 1:289F, 1:290F, 1:294 see also Kattegat Kattegat front, 1:295 measurements, constraints, 1:288–289 Norwegian Coastal Current, 1:291–292 oscillatory currents, 1:296 inertial, 1:296 seiches, 1:296 western Baltic-Gulf of Finland system, 1:296 see also Seiches outflows, 1:288, 1:290–291, 1:294, 1:295T see also Danish Straits oxygen transport, 1:290–291, 1:294–295 river runoff, 1:288, 1:290–291 salinity, 1:288 distribution, 1:289, 1:290F, 1:291F major inflow events, 1:295 sea ice coverage, 1:288 seasonal variations, 1:288, 1:291–292 sea surface inclination, 1:290–291, 1:292, 1:292F Skagerrak, 1:288, 1:289F, 1:294 sub-basins, 1:288 Arkona Basin, 1:288, 1:289F, 1:290F, 1:294, 1:295 Bornholm Basin, 1:288, 1:289F, 1:290F, 1:295 Bothnian Bay, 1:288, 1:289F Bothnian Sea, 1:288, 1:289F Gdansk Basin, 1:288, 1:289F Gotland Basin, 1:288, 1:289, 1:289F, 1:290F, 1:292–293 Northern Basin, 1:288, 1:289F thermohaline circulation, 1:292–294 upwelling, 1:293–294, 1:294F water budget, 1:288, 1:291–292 wind driven circulation see Wind-driven circulation wind field, 1:292 major inflow events, 1:295 see also Ekman pumping; Ekman transport; Estuarine circulation; Rossby waves; Wave generation Baltic Sea sprat (Sprattus sprattus balticus) predation mortality, multispecies virtual population analysis, 2:510, 2:510F spawning biomass, 2:505–506, 2:507F Banach space, 3:312–313 Banda Aceh inundation areas, 6:136
inundation maps, 6:136F wave heights, 6:137F Banda Sea, 3:237–238, 5:305, 5:306 interannual variability, 3:243 monsoon response, 3:240 seasonal outflow, 3:240 upper layer velocity, 5:314F Bangladesh, storm surges, 5:531F, 5:532, 5:535F Barbados, island flow effects, 3:345, 3:345F Barbeled dragonfishes (Aristostomias spp.), 2:455F Barbers Point Harbor, Hawaii, seiches, 5:349 Barents Sea, 1:211, 4:126–127, 5:144–146 Arctic sea ice, 5:85–86, 5:85F Atlantic water, 1:215 inflow, 1:215–216 polynyas, 4:540 sea ice cover, 5:141–142 sound propagation losses, 1:117, 1:117F Barges, ocean-going, 5:403 Barite (barium sulfate), 1:264–265, 1:265F in sediments, as productivity proxy, 5:333, 5:337, 5:339F Barium elemental X-ray map, 1:265F Pacific accumulation rates, 1:264F radium ratio, 6:253F Barnacles (Cirripedia), wave resistance, 1:332 Barndoor skate (Raia laevis), demersal fishing impact, 2:92 Bar number, 1:310–311 Baroclinic, definition, 6:195 Baroclinical circulation model, Southern Caribbean Sea, 4:727–729, 4:729F Baroclinic flow, equatorial waves, 2:274 Baroclinic instability (BI) Antarctic Circumpolar Current, 1:187 eddies, 4:270–271 interaction parameter, 4:271 Baroclinic instability eddies, 4:270–271 Baroclinic pressure gradients, fiords, 2:354 Baroclinic tides see Internal tides Baroclinic wave phase speed, hurricanes, 6:195 Barometers aneroid, 5:375 inverse effect, storm surges, 5:531 mercury, 5:375 types, 5:375 Barotropic, definition, 6:195 Barotropic flow, fiords, 2:354 Barotropic pressure gradient, fiords, 2:354 Barotropic tides, tomography, 6:50 Barotropic wave phase speed, hurricanes, 6:195 Barracuda (Sphyraena spp.), 2:395–396F Barreleyes (Opisthoproctus spp.), 2:447F Barrier estuaries, 3:38
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439
Barrier islands, 3:38 Barrier layer, 6:222, 6:340–341 formation, 5:129–130, 5:130 freshwater flux, 6:222 Indian Ocean, 6:181 Pacific Ocean, 6:181 thermocline heat flux, 6:222 upper ocean horizontal structure, 6:180–181, 6:180F Barrier reefs geomorphology, 3:34, 3:34F, 3:37 see also Reef(s) Barrow, Alaska, temperature profiles, sub-sea permafrost, 5:560, 5:561F Barrow Strait, 1:223 Bary catcher, 6:359, 6:360F Basal melting, 5:541 ice shelf stability, 3:209 Basal shear zone, definition, 5:463 Basalt(s) continental flood, 3:218, 3:219–222, 3:220T, 3:223F, 3:225 see also Large igneous provinces (LIPs) diagenetic reactions, 1:266T geoacoustic properties, 1:116T magnetism, 3:481 mid-ocean ridge see Mid-ocean ridge basalt (MORB) seismic profiles, 5:364 Basalt(ic) glass(es), 4:600, 4:600F diagenetic reactions, 1:266T Basel convention, hazardous waste movement, 3:440 Basilosauridae, 3:592 see also Cetaceans Basin (ocean) changing volume over time, sea level variations and, 5:187–189, 5:188F deep see Deep basins definition, 5:447 fiords, 2:357 variability, hurricanes and mixed layer, 6:195–197 water volume, sea level variations and, 5:185–187, 5:186F see also individual basins Basin (river), alterations, eutrophication case studies, 2:315–317 Basin to basin fractionation, calcium carbonate, 1:450–451 Basking shark (Cetorhinus maximus), 2:375–376 Bass, George mapping protocol established, 3:696 marine search strategies, 3:698, 3:698F Bass Point, topographic eddies, 6:58–59, 6:59F, 6:60 Bass Strait, cascades, 4:265–266 Bastard sole (Paralichthys olivaceus), 2:334 Batchelor wavenumber, 6:21 Batfish towed vehicle, 6:65, 6:69 Bathyal, definition, 5:463 Bathyal zone, 1:351T, 1:354, 1:356
440
Index
Bathygobius soporator (frillfin goby), 3:282 Bathymetric map Arctic ocean, 1:93F Black Sea, 1:212F, 1:401F Indonesian Throughflow, 3:238F making, for large areas, 1:300–301 Southern Ocean, 1:186F Bathymetry, 1:297–304 aliasing, 1:300 ancillary data, 1:301 applications, 1:297–298 assembly and maintenance, 1:302–303 autonomous underwater vehicles (AUV), 4:480F, 6:262–263 data assembly/interpretation, 1:300–301 data types, 1:301T definition, 1:297, 1:298, 5:463 extent of mapping, 1:298 gravimetry and, 3:84–85 international cooperation, 1:302 large areas, 1:300–301 map making, 1:300–301 metadata, 1:301–302 navigational charts and, 1:298 potential field surface maps and, 1:297 resolution, 1:299–300 satellite altimetry, 1:301 scale, 1:297 small areas, 1:297, 1:298–299 acoustics, 1:298–299 nonacoustic methods, 1:299 surfaces, potential field surfaces vs, 1:298 surveys, deep submergence science studies, 2:34, 2:35F three dimensional, 1:617F uncertainty, 1:299, 1:302 wind driven circulation, 6:353, 6:354 see also Seafloor topography Bathymodiolid mussels see Mussels (Mytilus) Bathymodiolus thermophilus (mussel), 3:133–134, 3:135, 3:136F, 3:138F see also Mussels (Mytilus) Bathyphotometers, 1:382 factors affecting measurements, 1:382–383 types, 1:381F, 1:382–383 Bathyscaph, history, 3:505 Bathysiphon filiformis foraminifer, 1:340F Bathysphere, 3:506 history, 3:505, 3:506 Bathythermograph, 1:709 expendable see Expendable bathythermograph (XBT) mechanical, 2:345 Batoidea (rays), 2:395–396F, 2:474 tropical fisheries development, impact, 1:651–652 BATS (Bermuda Atlantic Time-series Study), 5:478, 5:479F Batteries autonomous underwater vehicles (AUV), 4:475, 6:260–261
gliders, 3:62 human-operated vehicles (HOV), 6:255–257 Batumi eddy, 1:404–407 Bauer Deep, clay mineral profile, smectic composition, 1:567T Bay of Bengal, 6:170–171 currents, eastward, 1:733 particle flux variability, 6:1–2 particulate organic carbon (POC) flux, 3:310 storm surges, 5:531F, 5:532, 5:535F Bay of Fundy, Gulf of Maine hydroelectric power generation, 1:575–576 tide waves, 6:26 Bay of Morlaix, multidimensional scaling diagram, 4:538, 4:538F B,B-carotene, structure, 3:570F BBL see Benthic boundary layer (BBL) BBW see Bengal Bay Water (BBW) BC (black carbon), 1:249 Beach(es), 1:305 degradation, coastal engineering, seawalls and, 1:585–586, 1:585F erosion, offshore dredging implications, 4:188 geological inheritance, 1:305, 1:313–314, 1:314F geomorphology see Beach states human impacts, 1:581–583, 1:587 microbial contamination, 6:267–276 Annapolis Protocol, 6:275 assessment, 6:271–276 control, 6:269–271 environmental studies, causation for, 6:268–269, 6:268T fecal pollution, 6:267 infectious disease transmission, 6:267 inspection-based assessment, 6:275 monitoring, 6:271–276 primary classification matrix, 6:276T public health basis for concern, 6:267–269 regulation, 6:271–276 sources, 6:267, 6:269–271 modifications, 1:313–314 geological inheritance, 1:313–314, 1:314F temperature, 1:314 biotic influences, 1:314 chemical influences, 1:314–315, 1:314F frozen beaches, 1:314, 1:314F nearshore zone, 1:305 nourishment, coastal engineering see Coastal engineering physical processes affecting, 1:305–315 tide range see Tide-dominated beaches; Tide-modified beaches waves see Wave-dominated beaches; Waves on beaches see also Coastal topography impacted by humans sandy, biology see Sandy beach biology sediments, 1:305
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sub-sea permafrost, 5:562 surf zone, 1:305 sweep zone, 3:35 tide-dominated/modified see Tidedominated beaches; Tide-modified beaches wave-dominated see Wave-dominated beaches waves on see Wave breaking; Waves on beaches see also specific beaches Beach cusps, 3:36 Beach seines, 2:536, 2:536–537, 2:537F Beach states, 3:35F, 3:36 dissipative, 3:37, 3:37F event timescales, 3:37, 3:37F factors affecting, 3:36 intermediate, 3:37F reflective, 3:37, 3:37F wave energy, 3:37, 3:37F Beaked whales (Ziphiidae), 3:606–607T, 3:628, 3:632, 3:643–650, 3:644T acoustics and sound, 3:648–649 acoustic behavior, 3:648–649 sound production mechanism, 3:649 anatomy and morphology, 3:643–645 distinguishing features, 3:643–644 lower jaw morphology, 3:645F rostrums, 3:650 skull asymmetry, 3:645 conservation, 3:649–650 current threats, 3:649–650 anthropogenic noise, 3:650 whaling industry, 3:649 distribution and abundance, 3:645–646 lack of information, 3:646 limited distributions, 3:645–646 foraging ecology, 3:646 competition between species, 3:646 diving ability, 3:646, 3:647F squid diet, 3:646 suction feeding, 3:646 predation, 3:649 predators and defence mechanisms, 3:649 relationship to other cetaceans, 3:645F research history, 3:643 social organization composition of groups, 3:648 intraspecific aggression, 3:647–648 taxonomy and phylogeny, 3:643 fossil records and evolution, 3:643 ongoing classification, 3:643 species diversity, 3:643 trophic level, 3:623F Beamforming active sonars, 5:505, 5:506, 5:507F, 5:508–509 advanced, 5:512 matched field processing (MFP), 5:512 passive sonar see Sonar systems, passive sonar plane wave model, 5:512 wavefront curvature, 5:512 see also Sonar systems
Index Beam transmissometry see Transmissometry Beam trawl nets, 2:537, 2:538F Bearded seal (Erignatus barbatus) song, 3:618–619, 3:619F see also Phocidae (earless/‘true’ seals) Beaufort coast, gouging, 3:193, 3:194–195 Beaufort Gyre, 1:212, 5:174–175 trends, 5:175 Beaufort scale, 1:109T, 3:107 Beaufort Sea gouge tracks, 3:193–194, 3:194F ice gouging, 3:191–193, 3:193F, 3:194F mean ice draft, 5:152F sea ice cover, interannual variation, 5:148F sound speed, 1:95 Becquerel (Bq), 4:82–83 Bedford Institute of Oceanography Net and Environmental Sensing System (BIONESS), 6:357T, 6:364, 6:365F Bedrock, phosphorus, 4:401, 4:403T see also Phosphorus cycle Beer-Lambert law, 1:7–8 Beer’s law, 6:164 transmittance of radiation, 5:388–389 Beggiatoa, 2:77, 4:566–567 Behavior acoustic, beaked whales (Ziphiidae), 3:648–649 aquarium fish mariculture, 3:528 baleen whales see Baleen whales (Mysticeti) bottlenose dolphins see Bottlenose dolphins (Tursiops truncatus) copepods see Copepod(s) coral reef fish see Coral reef fish demersal fishes, 2:460–461 see also Demersal fish fish reproductive see Fish reproduction fish schooling, 2:433F foraging, seabirds, 5:229–230 harvesting see Fisheries intertidal fishes, 3:281–283 marine mammals, 3:615–616 mesopelagic fishes, 3:750–754 Odobenidae (walruses), 3:615 Pelecaniformes, 4:376, 4:376T, 4:377F Phaethontidae (tropic birds), 4:371, 4:376T plankton, affecting small-scale patchiness, 5:485–486 predation see Predation behaviors sirenians, 5:440–442 see also individual fish/organisms Bellingshausen Sea, northern, seabird responses to climate change, 5:261, 5:261F Belt Sea, Baltic Sea circulation, 1:288–289, 1:289F, 1:290–291 Beluga whale (Delphinapterus leucas), 3:629–630 Be´ multiple plankton sampler, 6:364, 6:365F Bengal, Bay see Bay of Bengal
Bengal, Gulf of, western boundary currents, 1:732 Bengal Bay Water (BBW), temperature–salinity characteristics, 6:294T Benguela Current, 1:316–327, 1:317F Agulhas rings and, 1:719F, 1:721, 1:726 bathymetry, 1:317F filaments, 1:324–326 fronts, 1:317F, 1:324–326 historical aspects, 1:316 knowledge gaps, 1:327 large-scale circulation, 1:317F, 1:319–324, 1:323F research priorities, 1:327 salinity, 1:322F, 1:324 seabird responses to climate change, 5:264 shelf circulation, 1:317F, 1:323–324, 1:323F, 1:324 system boundaries, 1:317F, 1:320F, 1:324–326 system variability, 1:326 episodic events, 1:326–327 event-scale, 1:326 interannual, 1:326–327 seasonal, 1:326 transport, 1:721, 1:724T upwelling, 1:235, 1:316, 1:317–319, 1:319F, 1:320F, 4:705–707 northern area, 1:319 regime shift analysis, 4:719 southern area, 1:319 see also Coastal trapped waves water masses, 1:319–324, 1:322F, 1:325F water temperatures, 1:319–322, 1:322F surface, 1:319, 1:320F winds, 1:316–317, 1:318F see also Abyssal currents; Agulhas Current; Atlantic Ocean current systems; Atlantic Ocean equatorial currents; Canary Current; Portugal Current Benguela Nin˜os, 1:327 Benjamin-Feir index (BFI), 4:773 Benjamin-Feir instability, 2:579, 4:773 Benthal environment, definition, 1:356 Benthic, definition, 1:348 Benthic boundary layer (BBL) adaptations to resist shear stress, 1:332–333 behavioral adaptations, 1:332–333 skimming flow, 1:333 structural adaptations, 1:332 tube adaptations, 1:333, 1:333F wave resistance, 1:332 aggregation of organisms, 1:333, 1:334T achievement, 1:333 behavioral reasons, 1:333 bivalve reefs, 1:333 components, 6:141, 6:141F definition, 1:328 effects on organisms, 1:328–335 flow adaptations, 1:330
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441
‘evolutionary adaptation’ defined, 1:330 hydrodynamic measures, 1:328 instability, 6:316 juvenile/adult stage adaptations, 1:334 feeding adaptations, 1:331, 1:334 shear stress resistance, 1:332, 1:334 tube building, 1:333, 1:334 larval stage adaptations, 1:330–331, 1:334 adaptive strategies, 1:331T dispersal, 1:330 dispersal distances, 1:331 epifaunal life cycle, 1:330, 1:330F settlement process, 1:331 size, 1:330–331 organisms, 1:328–329 epifauna, 1:328–329, 1:329T epifauna types, 1:328–329 near-bottom swimmers, 1:328 suprabenthos (hyperbenthos), 1:329–330, 1:329T processes, application of transmissometry/nephelometry, 6:117T research needs, 1:334 structure and depth, 1:328 suspension-feeding adaptations, 1:331–332, 1:332T active suspension feeders, 1:331–332 deposit/suspension feeders, 1:332 facultative passive/active feeders, 1:332 passive suspension feeders, 1:331 requirement of rapid growth, 1:331 thickness, 6:141, 6:142–143 transport, 4:253F turbulence, 6:24, 6:24F, 6:141–147 bottom roughness and, 6:145–146 drag coefficient, 6:143, 6:145–146 height and, 6:145 velocity profiles, 6:145 seabed topography and, 6:145F see also Benthic organisms; Bottom water; Ekman layer; Logarithmic layer; Macrobenthos; Turbulence Benthic communities ecology/evolution, bioturbation and, 1:400 hypoxia, effects of, 3:179F offshore dredging effects, 4:188 see also Benthic boundary layer (BBL); Benthic organisms Benthic fauna, oxygen-minimum zones, 3:178–179 Benthic fish(es), 2:67 harvesting, 2:501 see also Deep-sea fish Benthic flux calculation from chamber measurements, 4:487–488 from sensor measurements, 4:491 eddies and, 4:493 flotation, 4:486 measurement, 4:485–486
442
Index
Benthic flux (continued) chamber incubation, 4:485 concentration gradient sampling, 4:485–486 flow near seabed and, 4:489, 4:492 pore water chemistry and, 4:564 Benthic flux chambers, 4:486 data examples, 4:488F limitations, 4:488–489 Benthic flux landers, 4:485–493 chamber landers, 4:486–488 general design, 4:486–488 limitations and design variations, 4:488–489 flux measurement strategies, 4:485–486 integrated sediment disturbing, 4:492–493 oxystat, 4:492–493 recovery, 4:486 sediment disturbance, 4:488–489, 4:491–492, 4:493 sensor landers, 4:489–491 design and operation, 4:489–491, 4:490F instrumentation, 4:490 limitations and variations, 4:491–492 microelectrode deployment apparatus, 4:489, 4:490F results, 4:490, 4:491F specialised, 4:492–493 Benthic foraminifera, 1:336–347 ecology, 1:339–340 abundance and diversity, 1:339–340 hard-substrate habitats, 1:340 soft sediment habitats, 1:339 well-oxygenated sites, 1:339, 1:339T environmental distribution controls, 1:342–344 CaCO3 dissolution, 1:342 currents, 1:344 depth, 1:342–343 lateral advection of water masses, 1:342–343 organic matter fluxes, 1:343 species’ optimal habitats, 1:343–344, 1:344F see also Floc layers low-oxygen environments, 1:344–345 foraminifera tolerances, 1:344–345, 1:345 related to organic flux, 1:344 microhabitats and temporal variability, 1:341–342 deep-sea diversity, 1:340F factors influencing distribution, 1:341, 1:341–342 food and oxygen variability, 1:342, 1:343F species distributions, 1:341, 1:341F, 1:342F role in benthic communities, 1:340–341 biostabilization, 1:340–341 bioturbation, 1:340–341
organic carbon cycling, 1:340 place in food webs, 1:340 examples, 1:337F, 1:338F general characteristics, 1:336 cell body, 1:336 test, 1:336 morphological/taxonomic diversity, 1:336 range of morphologies, 1:336 sizes, 1:336 taxonomic test characteristics, 1:336 d18O records, 1:505–506, 1:506–507, 1:507F long-term patterns, 1:507–508, 1:507F, 1:508F Mg/Ca ratios and, 1:509 planktonic foraminifers vs., 1:507, 1:507F, 1:508F as productivity proxies, 5:338, 5:338F research history, 1:336 multidisciplinary research, 1:336 research methodology, 1:336–339 collection methods, 1:337 distinguishing live and dead individuals, 1:338–339 influence of mesh size, 1:339 use in geological research, 1:336 use in paleo-oceanography, 1:345–347, 1:345T example, 1:347 factors making foraminifera useful, 1:345–346 limitations of accuracy, 1:346–347 paleoenvironmental attributes studied, 1:346 see also Cenozoic see also Planktonic foraminifera Benthic gigantism, 3:470F Benthic habitats, fishing gear damage, 2:145 Benthic infauna burrows, 1:395, 1:398 classification, 1:349 alternative groupings, 1:350–351 by size groups, 1:350, 1:350F communities, 1:350 definition, 1:395 fecal pellets, 1:395–396 percentage of benthos, 1:349–350 see also Benthic organisms; Deposit feeders Benthic macrofauna, hypoxia, 3:178–179 Benthic nepheloid layer (BNL), 6:236 Benthic organisms, 1:348–356, 2:216, 3:565 ‘benthic’ defined, 1:348 biodiversity, 2:143 depth-related patterns, 2:143–144 bioluminescence, 1:378–379 boundary layer see Benthic boundary layer (BBL) classification, 1:349–351 epifauna, 1:349 percentage of benthos, 1:349–350 infauna, 1:349 alternative groupings, 1:350–351
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communities, 1:350, 1:351T, 1:352T percentage of benthos, 1:349–350 size groups, 1:350, 1:350F see also Benthic infauna classification of zones, 1:351T deep-sea environment, 1:354–355 abyssal gigantism, 1:354–355 biodiversity theories, 1:355 cyclical events, 1:355 depth and food availability, 1:354–355 dominant species, 1:355 energy sources, 1:355 zones, 1:354 see also Deep-sea fauna; Deep-sea fish depth divisions, 1:348 distribution, 2:139 sediment influence on, 1:352 see also Benthic organisms, spatial distribution fauna, oxygen-minimum zones, 3:178–179 feeding habits, 1:351–352 bacterial breakdown of food, 1:351 dependence on detritus, 1:351 detrivores, 1:351–352 grazing and browsing, 1:352 predatory behavior, 1:352 sediment influence on distribution, 1:352, 1:352T fishes see Benthic fish; Deep-sea fish fishing gear disturbance, 2:204 foraminifera see Benthic foraminifera larvae, pelagic vs. nonpelagic, 1:353, 1:353F, 1:354, 1:354F macrofauna, hypoxia, 3:178–179 physical conditions, 1:348–349, 1:349F exposure to air, 1:349F level-bottom sediment, 1:349 light, 1:348, 1:349F salinity, 1:348–349, 1:349F substratum material, 1:349, 1:349F temperature, 1:348, 1:349F turbulence, 1:349F water level, 1:348 see also Tide(s) water pressure, 1:348 polar marine food webs, 4:517 primary productivity, 4:585 reproduction, 1:353–354 fecundity and mortality, 1:354 oviparity, 1:353 settlement process, 1:353–354 sexual/asexual reproduction, 1:353 strategies for dispersal/nondispersal, 1:353 viviparity, 1:353 spatial distribution, 1:352–353 competition for space, 1:352 horizontal, 1:352 vertical, 1:352–353 see also Benthic organisms, distribution see also Benthic boundary layer (BBL); Benthic foraminifera; Demersal
Index fish(es); Demersal fisheries; Grabs for shelf benthic sampling; Macrobenthos; Meiobenthos; Microphytobenthos; Phytobenthos; specific benthic organisms Benthic solute exchange, 4:252, 4:253F Benthogone rosea, 2:553F Benthopelagic fishes, 2:67 Benthos, 1:356 carbon isotype profile, Arabian Sea, 3:916F oxygen isotype profile, Arabian Sea, 3:915F see also Benthic organisms; entries beginning benthic Benthosema glaciale, small-scale patchiness, 00405:0065, 5:485–486 a-Benzoin oxime, 1:13 Berardius bairdii (Baird’s beaked whale), 3:643, 3:648, 3:649 ‘Berg’ winds, 1:316–317 see also Benguela Current Bering Sea 1998 regime shifts, fisheries, 2:487 biogenic silica burial, 3:681T, 3:682 coccolithophore bloom, 5:125–126, 5:125F fish abundance and yearly ice extent, satellite remote sensing, 5:109 food web, 2:598, 2:599F front near ice edge, SAR, 5:109, 5:109F kittiwake, 5:263 Okhotsk Sea and, 4:201, 4:202, 4:204 polar low SAR image, 5:107–108 polynyas, 4:540, 4:541, 4:543–544 seabird responses to climate change, 5:263 sea ice cover, 5:144–146 sub-sea permafrost, 5:566 trophic interactions, 3:622, 3:624F, 3:625 Bering Sea Gyre, 3:365 Bering Strait throughflow, 6:171 Arctic Ocean halocline and, 1:212–213 transport, 1:223 Berm, erosion/deposit, 1:306 Bermuda aerosol concentrations, 1:249T atmospheric lead concentrations, 1:243F cadmium concentrations, 1:200 helium-3 isotope ratio anomaly, 6:97F lead in corals, 1:197, 1:199F in surface waters, 1:197, 1:198F nitrate concentrations, 6:97F productivity tracer estimate comparison, 6:100T see also North Atlantic Bermuda Atlantic Time-series Study (BATS), 4:47F, 5:478, 5:479F Bermuda Testbed Mooring (BTM), optical systems, 3:249F data, 3:251–252, 3:252F
Bernoulli equation, 5:574 Bernoulli’s Law, 2:564 Beroida ctenophores, 3:13F, 3:14 Beryllium bioturbation tracer as, 1:396–397 cosmogenic isotopes, 1:679T oceanic sources, 1:680T production rates, 1:680T reservoir concentrations, 1:681, 1:681T specific radioactivity, 1:682T tracer applications, 1:685 isotope ratios depth profiles, 3:464F global distribution, 3:459F long-term tracer properties, 3:456T, 3:464 sediment chronologies, 5:328T, 5:330–331 source materials, 3:457–458 Beta effect, 4:121F, 4:122 see also Coriolis force; Coriolis parameter b-plume, 2:134–135 BFI see Benjamin-Feir index BF instability see Benjamin-Feir instability BHSZ (base hydrate stability zone), 3:792–793 see also Hydrate stability zone (HSZ) Bicarbonate (HCO-3) coral reef production, 1:665 in oceanic carbon cycle, 1:478–479 river water concentration, 3:395T see also Carbon cycle Bichir (Polypterus spp.), 2:468 BI (baroclinic instability) eddies, 4:270–271 Big-eye tuna (Thunnus obesus) acoustic scattering, 1:66 economic value, 4:237 Bilge water law and regulation, 5:407 transport of non-indigenous species, 5:407 Billfishes (Istiophotidae), 2:395–396F, 4:234 longline fishing, 4:237 open ocean fisheries see Pelagic fisheries world landings, 4:240 Bin averages, drifter velocity measurements, 2:171 Bingham plastics, sediment flows as, 5:455 Bioaccumulative metals, definition, 3:774 Bioacoustics, marine mammal see Marine mammals, bioacoustics Bioadhesives, research directions, 3:573 Bioavailable metals, definition, 3:774 Biocatalysis, marine organisms, 3:571–572 Biodiffusion, bioturbation and, 1:396, 1:396T Biodiversity of marine communities see Marine biodiversity BIOENV, 4:536–537 Biofuels, marine organisms, 3:572–573
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Biogenic flocculent material see Floc Biogenic gases, definition, 1:157 Biogenic silica burial, 3:681–682 sites, 3:681T dissolution, 3:680, 3:682, 3:684F aluminium and, 3:682–683 in marine sediments, 3:681T, 3:683–684, 3:684F diatom skeletons, 3:681, 3:683–684, 3:684F measurement, 3:684 radiolaria skeletons, 3:683–684 siliceous sponges, 3:683–684 silicoflagellates, 3:683–684 preservation, 3:682–683 Ross Sea studies, 3:683 see also Silica cycle Biogeochemical and ecological modeling, 4:89–104 applications, 4:89, 4:95F box models, 4:94–97, 4:96F challenges, 4:89–92 complexity, 4:93, 4:94F, 4:95F definition, 4:92 equations and approaches, 4:93 global 3D modeling, 4:98–102, 4:100F limitations and advantages, 4:92–93 NP and NPZ models, 4:97–98, 4:100F see also Biogeochemical data assimilation; Biogeochemical models Biogeochemical cycles, 4:90F estuarine sediments, 1:540F Southern Ocean overturning and, 1:189 see also Carbon cycle; Great Biogeochemical Loop; Nitrogen cycle; Phosphorus cycle Biogeochemical data assimilation, 1:364–370 challenges, 1:365 data requirements, 1:364 methods, 1:365–366 adjoint, 1:366, 1:368–369 data insertion, 1:367–368 simulated annealing, 1:366 models and, 1:364–365 model validation, 1:369 numerical twin experiments, 1:366–368 numerical twin models, 1:366F outlook, 1:369 see also Biogeochemical and ecological modeling; Biogeochemical models; Data assimilation; Data assimilation in models Biogeochemical models, 4:89–104 carbon cycle, 4:111–112 history, 1:364 ocean circulation and, 4:107–109 see also Biogeochemical and ecological modeling; Biogeochemical data assimilation Biogeochemical provinces, 4:359, 4:360F, 4:362F dynamic, 4:359–360
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Biogeochemical provinces (continued) seasonal production models, 4:359–360, 4:361T, 4:362F see also Pelagic biogeography; specific biomes Biogeochemical zonation, 4:566, 4:567F reactions, 4:566T zone boundaries, 4:566–567 Biogeochemistry key questions, 4:92 marine, modeling, 4:89–104 process rates, 4:106 subterranean estuaries, 3:94–96 see also Biogeochemical data assimilation; Carbon cycle; Carbon dioxide cycle; Nitrogen cycle; Numerical models; Phosphorus cycle Biogeography, pelagic see Pelagic biogeography Bioirrigation pore-water, 1:398–400, 1:399F sediment geochemistry and, 1:399–400 Biological assays copper complexation, 6:104T metal complexation, 6:104 Biological Investigations of Marine Antarctic Systems and Stocks (BIOMASS), 5:513 Biological models see Lagrangian biological models; Models/ modeling Biological oceanography, 3:123, 3:124 Biological pump, 1:371–375, 3:651 carbon cycle see Carbon cycle, biological pump marine mats, 3:651 marine organism calcification, 1:485F, 1:486 micronekton diurnal vertical migrations, 4:3 Bioluminescence, 1:376–384 applications, 1:383–384 oceanographic, fisheries and medical, 1:383–384 biochemistry, 1:376 luciferin/luciferase system, 1:376 cephalopods, 1:527 colors produced blue, 1:378, 1:382 blue-green, 1:378 green, 1:378 red, 1:382 yellow, 1:378–379 copepods, 1:648–649 definition, 1:376 fishes, 1:380–382 forms, 1:377T flashes, 1:376, 1:378 glow, 1:376, 1:379–380, 1:380 secretions, 1:376–378, 1:380 waves of light, 1:378 measuring, 1:382–383 bathyphotometers, 1:381F, 1:382 bioluminescent signatures, 1:383 identifying organisms, 1:383
seasonal and diel variability, 1:382–383 seasonal/diurnal variability, 1:382–383 see also Fish vertical migration stimulable bioluminescent potential, 1:382 see also Bathyphotometers micronekton see Micronekton microorganisms, 1:376 bacteria, 1:376, 1:380 dinoflagellates, 1:376, 5:492 radiolarians, 1:376 types, 1:376 occurrence, 1:376, 1:377T phenomena, 1:383 photocytes, 1:378, 1:378F, 1:379–380 photophores, 1:379–380 accessory optical structures, 1:379F fishes, 1:380–381 occlusion, 1:380, 1:380F pigments and reflectors, 1:378F shrimps and krill, 1:380 squids, 1:380 plankton, 1:376–380 cnidarians, 1:378 copepods, 1:376–378 ctenophores, 1:378 echinoderms, 1:378–379 ostracods, 1:376–378 tunicates, 1:379–380 worms, 1:378–379 squid and octopods, 1:380 see also Fish vision Biomagnified metals, definition, 3:774 BIOMAPER II (BIo-Optical Multi-frequency Acoustical and Physical Environmental Recorder), 6:369, 6:370F Biomass bacterioplankton see Bacterioplankton macrobenthos see Macrobenthos measurement fishery stock manipulation, 2:532 see also specific species microphytobenthos see Microphytobenthos networks, analysis of food webs see Network analysis of food webs as phosphorus reservoir, 4:401, 4:403T see also Phosphorus cycle terrestrial vs. marine, 4:678, 4:678T variability, microbial loops, 3:804, 3:805T see also Large marine ecosystems (LMEs); Phytoplankton; individual organisms/fish BIOMASS (Biological Investigations of Marine Antarctic Systems and Stocks), 5:513 Biomaterials marine organisms, 3:573 see also Marine biotechnology Biomineralization, 4:615
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BIONESS (Bedford Institute of Oceanography Net and Environmental Sensing System), 6:357T, 6:364, 6:365F Bio-optical algorithms, 4:735, 5:120 Bio-optical models, 1:385–394 Case 1 waters, 1:385, 1:386T, 1:390T, 1:391F, 1:392T, 1:393F, 1:394 Case 2 waters, 1:385, 1:386T, 1:394 chlorophyll concentration apparent optical properties and, 1:388, 1:391, 1:392T, 1:393F inherent optical properties and, 1:388, 1:389–390, 1:389F, 1:390T, 1:391F coastal waters, 4:734 concepts, 1:386T limitations, 1:394 oceanic waters related to biological state, 1:388–390, 1:393–394 for particles (individual/populations), 1:385–388, 1:387F, 1:393–394 quantities, 1:386T semianalytical, 1:393, 1:393F spectral domain, 1:385 theory, 1:386–387 see also Apparent optical properties (AOPs); Inherent optical properties (IOPs); Ocean color; Ocean optics; Optical particle characterization; Radiative transfer BIo-Optical Multi-frequency Acoustical and Physical Environmental Recorder (BIOMAPER II), 6:369, 6:370F Bio-optics, 3:244 research, 3:245 see also Ocean optics BIOPS optical system, 3:249F data, 3:250F see also Ocean optics Bioreactive elements, transport, 4:96 Bioremediation, 3:565 marine environment, 3:572 Biosphere deep-sea drilling to investigate, 2:48 Biostabilization, 3:811 Biostratigraphy, 3:25 Biosurfactants, 3:565 Biota transport, Intra-Americas Sea (IAS), 3:288, 3:289F Biotechnology see Marine biotechnology Biotoxins, 2:160 Biot-Stoll model, 1:76–78 input parameters, 1:76–78, 1:78T Bioturbation, 2:56–57, 2:59 benthic foraminifera ecology, 1:340–341 chemical tracers see Chemical tracers definition, 3:774 ecology and evolution of benthic communities, 1:400 geochemical effects, 1:397–398 irrigation and, 4:568–570 particle, 1:395–398 particle mixing model, 1:396 pore-water bioirrigation, 1:398–400, 1:399F
Index quantification, 1:396 radionuclides and, 5:328 sediment burial and, 4:143–144 sediment cores, 1:397 sediment profiles, 1:397 ‘Bipolar seesaw’, 1:1–2, 1:4 in Holocene millennial-scale climate fluctuation, 3:129–130, 3:129F, 3:130F Bipolar species, 4:361 Birds lagoons, 3:386 oil pollution, 4:197 salt marshes and mud flats, 5:45 see also Seabird(s) Birnessite, 1:258–259 Bismarck, maritime archaeology project, 3:698 Bismuth concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:695–696 depth profile, 4:697F properties in seawater, 4:688T Bit depth, seawater profile measurements, 1:715 Bivalves, 4:274 fisheries, seaduck interactions, 5:270–271 food safety, 4:285 habitat, 3:899 harvesting, 3:902 mariculture, 3:903–904 production, global, 3:905–906, 3:906F stock enhancement/ocean ranching programs, 4:147T, 4:152 toxin concentration, 3:903 see also Clams; Mollusks; Mussels (Mytilus); Oyster(s) Bjerkenes compensation mechanism, heat transport, 3:120 Black-body calibration, satellite remote sensing, 5:91, 5:94 emittance, 3:320, 3:320–322 radiance/radiation, 3:114, 3:114F, 3:320, 3:320F, 6:339 Black-browed albatross, 4:596, 5:240 see also Albatrosses Black carbon (BC), 1:249 Black guillemot (Cepphus grylle), 1:171, 5:258–259, 5:259F see also Alcidae (auks) Black-legged kittiwake see Kittiwake Black marlin see Makaira indica (black marlin) Black scabbardfish (Aphanopus carbo), 4:226 distribution, 4:226–227 open ocean demersal fisheries, 4:226–227, 4:227F FAO statistical areas, 4:226–227, 4:231T Black Sea, 1:409F air temperature, 1:403 atmospheric pressure, 1:214F, 1:404F
basin-scale circulation, 1:404–407 bathymetric map, 1:212F, 1:401F circulation, 1:401–414 current direction, 1:409F current velocities, 1:411F drifter paths, 1:411F drivers, 1:407 geostrophic currents, 1:219F, 1:408F Knipovich spectacles, 1:407F mesoscale features, 1:407–410 Rim Current, 1:404–407 temperature section, 1:401 variability, 1:410–412 continental slope, 1:409–410 drainage area, 1:211, 1:402, 1:403F eddies, 1:407–409 flora and fauna, 1:404 freshwater budget, 1:402T gyres, 1:404–407 history, 1:211, 1:402 hypoxia, human-caused, 3:174 introduction of Mnemiopsis leidyi, 3:18 islands, 1:211, 1:401 light attenuation, 4:738F Mediterranean Sea circulation, 3:710–725 mesoscale circulation, 1:413F meteorology, 1:402–404 overturning circulation, 1:412–413, 1:413 regime shifts, 4:699, 4:704–705 Rim Current reversal, 1:407 topography and, 1:410–411 salinity, transect profile, 1:217F, 1:406F seabed, 1:401 sea level, 1:402, 1:410F sea surface temperatures (SST), 1:413F shelf, 1:211 surface currents, 1:407 temperature, transect profile, 1:217F, 1:406F, 1:412F temporal variability of particle flux, 6:1 tides, 1:407 vertical profiles, 1:216F, 1:405F water budget, 1:402 water profiles, 1:404 wind speeds, 1:402–404 Black skimmer (Rynchops niger), 3:423F see also Rynchopidae (skimmers) ‘Black smokers’ deep submergence science and, 2:22, 2:23F see also Hydrothermal vent chimneys Black surf perch (Embiotica jacksoni), 2:376–377 Black turtle, 5:216–217, 5:216F see also Sea turtles Blainville’s beaked whale (Mesoplodon densirostris), 3:646, 3:647F, 3:648–649 Blake Outer Ridge, velocity profile, 6:145F Blake Plateau, ferromanganese deposits, 1:259 Blake Ridge, gas hydrates, 3:784, 3:785
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Blast fishing, coral impact, 1:652–653, 1:672, 2:205 Blending estimate, forecast data, estimation theory and, 2:7 Blennies Aspridonotus taeniatus (saber-toothed blenny), 2:377 Hemiemblemaria simulus (wrasse blenny), 2:423 Blind cavefish (Astyanax spp.), 2:481 Bloom cycles, transmissometers in tracking of, 6:117T Blooms algae see Algal blooms phytoplankton see Phytoplankton blooms planktonic, 4:100 Blue crab (Callinectes sapidus), world landings, 1:701T, 1:702 Blue damsel (Pomacentrus coelestris), aquarium mariculture, 3:528 Bluefin, 6:263T Bluefin 21, 6:263T Bluefin tuna economic value, 4:239 foraging strategies, behavior optimization, 2:377–378 mariculture, 4:241 see also Thunnus thynnus (Atlantic bluefin tuna) northern (Thunnus thynnus) see Thunnus thynnus (Atlantic bluefin tuna) Pacific (Thunnus orientalis), fisheries, 4:235 pole and line fishing, 4:235–236 southern (Thunnus maccoyii) see Thunnus maccoyii (southern bluefin tuna) stock enhancement/ocean ranching programs, 4:241 see also specific species Blue green algae see Cyanophytes Blue-green ratio algorithms, 4:735, 5:120 Blue grenadier see Hoki Blue ling (Molva dypterygia), open ocean demersal fisheries, 4:228 FAO statistical areas, 4:228, 4:231T Blue mussel (Mytilus edulis), 1:330F Blue penguin, 5:523 see also Little penguin Blueschists, accretionary prisms, 1:33, 1:33F Blue sharks (Prionace glauca), 4:135, 4:240 Blue tuskfish (Choerodon albigena), 2:453F Blue whale growth and maturation, 1:284, 3:612F, 3:613 lateral profile, 1:278F sound production, 1:282–283, 1:358 tracking, 1:358, 1:358F see also Baleen whales Blue whiting (Micromesistius poutassou) acoustic scattering, 1:66
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Blue whiting (Micromesistius poutassou) (continued) total world catch, 2:91, 2:91T Bluntsnout smooth-head (Xenodermichthys copie), 2:452F BMC see Brazil/Malvinas confluence (BMC) Boat(s) Indian (archaeology), in Central American sinkholes, 3:697 land-locked, early maritime archaeology, 3:695 workboats, oceanographic research vessels, 5:412 see also Ship(s) Boat dredging, 2:539, 2:539F, 3:901–902, 3:901F, 3:902F Boat-operated lift nets, 2:539, 2:539F Boat seines, 2:536, 2:537, 2:537F Body waves, 1:78, 1:78–79, 1:79 compressional waves see Compressional waves shear waves see Shear waves see also Acoustic remote sensing Bolivar Maru, 4:770F Boltzmann’s constant, 5:91 Bolus velocity, definition, 4:164, 4:164F Bomb carbon, 5:421–422 as tracer, 5:425 Bomb radiocarbon, 3:307–310 Bomb tritium, in precipitation, 6:119, 6:119F Bonamia, oyster farming, risks to, 4:283–284 Bonarelli event, 4:320 Bond cycles, 3:886–887 Bongo net, 6:355, 6:356F Boobies see Sulidae (gannets/boobies) Bookshelf faulting, 4:597–600 Booms, oil pollution, 4:193 Borate (B(OH)-4) determination, 1:626 see also Boric acid (B(OH)3) Borehole images microresistivity round, 2:50–51 logging and instrumentation, 2:52 Bores, 6:127 Boric acid (B(OH)3) borate (B(OH)-4) determination, 1:626 determination, 1:626 sound volume attenuation, 1:104, 1:104F Bornholm Basin, Baltic Sea circulation, 1:288, 1:289F, 1:290F, 1:295 Bornholm Channel, Baltic Sea circulation, 1:288, 1:293 Boron (B), concentration in sea water, 1:627T Bosphorus, flow historical aspects, 2:572 mixing, 2:575 Bosphorus Strait, circulation, 1:211, 1:402 Bosunbird, 4:372F see also Phaethontidae (tropic birds)
Bothnia, Gulf of, Baltic Sea circulation, 1:288, 1:290–291, 1:296 Bothnian Bay, Baltic Sea circulation, 1:288, 1:289F Bothnian Sea, Baltic Sea circulation, 1:288, 1:289F Boto (Inia geoffrensis), 2:157 Bottlenose dolphins (Tursiops truncatus), 2:153F calving, 2:155 feeding behaviors, 2:157, 2:158 habitats, 3:598 home ranges, 3:598–599 inshore forms, 3:598 mating strategies, 3:617 migration, 3:598–599 offshore forms, 3:598, 3:599 oxygen stores, 3:583F signature whistles, 2:157–158 social interactions, 2:158–159 see also Oceanic dolphins Bottlenose whale diving characteristics, 3:583T see also Beaked whales (Ziphiidae) Bottles, as drifters, 2:172 Bottle sampling, 6:291, 6:299 Bottom, oceans see Ocean bottom Bottom boundary layer Ekman, 3:451–454 instability, 6:316 turbulence, 6:24, 6:24F see also Benthic boundary layer (BBL) Bottom currents benthic flux measurement, 4:485 benthic flux measurement and, 4:485 non-rotating gravity currents, 4:59 idealized flow model, 4:59–60, 4:60F rotating gravity currents, 4:790–791, 4:791F, 4:793–794 Bottom currents, contour-following, 2:80, 2:80–81 Antarctic bottom water (AABW), 2:80, 2:81F, 2:82F Arctic bottom water (ABW), 2:80, 2:82F Coriolis force, 2:80 facies models for contourites, 2:80 sediment drifts, 2:80 see also Deep-sea sediment drifts sediment flux in deep basins, 2:80 variable flow velocity, 2:80–81 variation in deep-sea paleocirculation, 2:80 warm saline intermediate water, 2:80, 2:81 see also Bottom water formation; Thermohaline circulation Bottom current stress, measurement, 6:144–147 Bottoming point, 5:351 Bottom mixed nepheloid layer (BMNL), 4:8 sediment concentrations, 4:11–12 Bottom nepheloid layer (BNL), thickness, 4:11 Bottom otter trawl nets, 2:537, 2:538F Bottom pair trawl nets, 2:537, 2:538F
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Bottom penetrometer probe, expendable, see also Expendable sensors Bottom-simulating reflector (BSR) gas hydrates, 3:48 hydrate detection, 3:784 Bottom-simulating seismic reflector (BSR), 3:792–793 Bottom stress measurement, 6:144–147 storm surges, 5:532, 5:536, 5:538 Bottom topography Antarctic Coastal Current, 6:322–323, 6:323 Baltic Sea circulation, 1:288, 1:289F, 1:292, 1:293–294 Brazil and Falklands (Malvinas) Currents, 1:423F, 1:427 deep ocean, mixing mechanisms, 2:128 Intra-Americas Sea (IAS), 3:287, 3:288F current flow, 3:291 storm surges, 3:293 maps, satellite altimetry, 5:59, 5:60F Mediterranean Sea, 3:710, 3:711F shallow water, satellite remote sensing application, 5:105F, 5:107 topographic eddies, 6:60–62 turbulence, 6:62–63 see also Seafloor topography Bottom trawl nets, 2:537, 2:538F, 5:517 Bottom-up control, fishery multispecies dynamics, 2:508–509, 2:509F, 2:511 Bottom water currents see Bottom currents formation see Bottom water formation radiocarbon levels, 3:308F temperature (BWT), geophysical heat flow measurements and, 3:43 warming methane release from gas hydrates and, 3:787–788 Paleocene, 3:788 Bottom water formation, 1:415–421, 2:80 general circulation models (GCM), 3:22 Mediterranean Sea circulation, 3:712–714, 3:714–715 sea ice, 5:80 shelf water salinity, 1:415–416 southern Ocean, deep convection within, 1:420 Weddell Sea circulation, 6:324 in winter, 3:255 see also specific oceans Bouguer gravimetric correction, 3:82–83 Bouguer gravity anomaly, 3:873F Southwest Indian Ridge, 3:876F Boundary benthic see Benthic boundary layer (BBL) surface water masses, satellite remote sensing of SST, 5:99, 5:100F Boundary conditions coastal circulation models, 1:572, 1:579 forward numerical models see Forward numerical models general circulation model, 4:727
Index Boundary currents deep convection, 2:20, 2:21 Red Sea circulation, 4:668–669 Boundary determinations, Law of the Sea jurisdictions, 3:435 Boundary-element modeling, acoustic scattering, fish, 1:66 Boundary layer benthic see Benthic boundary layer (BBL) dissipation, scatter vs, 3:255–256 see also Internal tidal mixing mass, 1:148, 1:148F planetary, 3:198, 3:198–199 thermal see Thermal boundary layer thickness, air–sea gas exchange, 1:149 under-ice see Under-ice boundary layer (UBL) viscous, dissolved gas diffusion, 1:148 Boussinesq approximation, 2:604–605 coastal circulation models and, 1:572 density, 5:133–134 Boussinesq equations, Langmuir circulation, 3:406–407 Bowhead whale (Balaena mysticetus) acoustic noise, 1:99 growth and reproduction, 1:284 habitat, 1:279 lateral profile, 1:278F song, 3:618, 3:618F see also Baleen whales Box models, 4:94–97 carbon cycle, 1:519–520, 1:520F, 1:521–522, 4:108–109, 4:109F refinements, 4:109 chemical tracers and, 4:108–109 concept of, 1:519 fluxes, 1:519 differential equations, 1:519 overflows and, 4:270 reservoirs, 1:519 three-box, 4:96–97 turnover time, 1:519 two-box, 4:96 Boyle, E, introduction of cadmium/ calcium ratio, 5:337 BP (bacterial production), 1:271F, 1:272, 1:273–274 BR (bacterial respiration), 1:272, 1:273–274 Brachyramphus, 1:171T diet, 1:174 feeding patterns, 1:174 plumage, 1:172, 1:173F reproduction, 1:174 see also Alcidae (auks) Brachyramphus marmoratus (marbled murrelet), 1:173F Brachyuran crab (Bythograea thermydron), 3:133F, 3:135F, 3:136–138, 3:136F Brackish water, definition, 5:557 Bradford Hill’s criteria, environmental studies, 6:268–269 Bradshaw, A, 1:712, 1:713
Bragg resonant wave back scattering, 5:104–105 satellite remote sensing, 5:104–105, 5:104T Bramaputra see Ganges/Bramaputra Brazil El Nin˜o events and, 2:228 iron submarine groundwater discharge flux, 5:552–553 water, microbiological quality, 6:272T Brazil and Falklands (Malvinas) Currents, 1:422–430 abyssal water, 1:425 Antarctic Bottom Water, 1:425 Weddell Sea Deep Water (WSDW), 1:425, 1:426F, 1:427 Antarctic Intermediate Water (AAIW) see Antarctic Intermediate Water (AAIW) Brazil/Malvinas confluence (BMC) see Brazil/Malvinas confluence (BMC) circulation, 1:425 bottom topography, 1:423F, 1:427 Brazil Current, 1:425, 1:427–428 Malvinas Current, 1:425–427, 1:427–428 Malvinas Return Current, 1:427 recirculation, 1:424, 1:425, 1:427 upper layer, 1:422, 1:423F, 1:429F deep water, 1:424–425 Brazil Current, 1:425 Circumpolar Deep Water (CDW), 1:425 Malvinas Current, 1:425 North Atlantic Deep Water (NADW), 1:425 interleaving, 1:422–423, 1:427 origins, 1:425, 1:427 oxygen, dissolved, 1:425, 1:426F, 1:427 salinity, 1:422, 1:423F, 1:427 potential temperature–salinity diagram, 1:422, 1:424F salt transport, 1:427–428 seasonal variations, 1:428 temperature, 1:422, 1:425 heat transport, 1:427–428 potential temperature–salinity diagram, 1:422, 1:424F sea surface, 1:427–428, 1:428F, 1:429F transport Brazil Current, 1:425, 1:428–430 Malvinas Current, 1:427, 1:428–430 upper ocean, 1:422–423 Malvinas Current, 1:422–423 South Atlantic Central Water (SACW), 1:422, 1:424F Tropical Waters (TW), 1:422, 1:424F vertical stratification structure, 1:422 water masses, 1:422–423 see also Abyssal currents; Antarctic Circumpolar Current (ACC); Atlantic Ocean current systems; Elemental distribution; Falklands (Malvinas) Current; Intrusions; Mesoscale eddies; Ocean
(c) 2011 Elsevier Inc. All Rights Reserved.
447
circulation; Regional models; Satellite altimetry; Satellite remote sensing of sea surface temperatures; Southern Ocean, current systems; Upper ocean, time and space variability; Water types and water masses Brazil Basin abyss, Lagrangian vector time-series, 1:29, 1:29F internal tidal mixing, 3:256–257 mixing estimates, 2:297 mixing processes, 2:290–291 tracer release experiments, 6:92 turbulent mixing, observations of, 2:123, 2:124F, 2:126–127 Brazil Current, 1:720–721, 6:347F circulation, 1:425, 1:427–428 deep water, 1:425 transport, 1:721, 1:724T upper ocean, 1:422 see also Atlantic Ocean current systems; Brazil and Falklands (Malvinas) Currents Brazil/Malvinas confluence (BMC), 1:422, 1:427–430 interleaving, 1:427 mesoscale eddies, 1:427–428, 1:428F mixing, 1:427 oxygen, dissolved, 1:426F potential temperature, 1:424F, 1:426F salinity, 1:423F, 1:424F, 1:426F seasonal displacement, 1:428 mass transport, 1:428–430 variability, 1:427–428 see also Brazil and Falklands (Malvinas) Currents Breakers, 6:312 plunging, 1:431, 6:312 spilling see Spilling breakers Breaking rate, 1:433 Breaking waves, 6:306 air bubble entrainment, 1:151–152, 1:433 air fraction, 1:431 air–sea gas exchange and, 1:151–152 laboratory-generated, 1:433, 1:436 near-surface turbulence, 5:580 propagation speed and strength, 1:435–436 ships and offshore structures and, 1:431 turbulence beneath, 1:433–436 measurement, 1:434 turbulence shear forces, 1:433 vortex generation, 1:433 wave frequency distribution, 1:432–433 see also Plunging breakers; Spilling breakers; Wave breaking Break point, 6:310F, 6:311–312, 6:313 Breakwaters, offshore, 1:586–587 Brecciated clast, 5:463 Brecciated zone, definition, 5:463 Breeding aquarium fish mariculture, 3:529 see also individual birds/seals Brent Spar incident, 4:751
448
Index
BRIDGET, 6:256T Brightness temperature, 5:127, 5:128, 5:129, 5:131F errors, 5:130–131 model function, 5:130 sensitivity, 5:130 SST measurement by satellite, 5:91 temperature deficit relationship, 5:92 Brillouin’s index, 4:534 Brine, sea ice, composition, 5:172–173 Brine drainage, 5:563–564 Brine rejection, 4:127 Bristlemouths (Gonostomatidae), 4:1–3 Brittle stars (Ophiuroidea), 1:355, 2:59F Broadband (BB) ocean bottom seismometers, 5:369 characteristics, 5:369T, 5:371 LDEO-BB, 5:369T, 5:372F ORI-BB, 5:369T SIO/IGPP-BB, 5:369T, 5:370F SIO/ONR, 5:369T, 5:372F WHOI-BB, 5:369T Broadband pyrgeometers, 3:324, 3:324F Bromide (Br-), concentration in sea water, 1:627T Broodstock oysters, 4:277 Brown, Neil, 1:713, 1:713–714, 1:714–716, 1:716F Brown booby, 4:372F, 4:373 see also Sulidae (gannets/boobies) Browning, D G, acoustic noise, 1:59 Brown pelican, 4:371–373, 4:372F climate change responses, 5:259 see also Pelecanidae (pelicans) Brown seaweeds (Phaeophyta spp.), 4:427 mariculture, 5:319F, 5:320F Brown’s zones, 5:49–50 Brundtland report, 1:600 Brunhes-Matuyama event, 4:507, 4:509F Brunnich’s guillemot (Uria lomvia), 1:171, 1:173F see also Alcidae (auks) Brun’s formula, 3:80 Brunt Ice Shelf, 3:213 Brunt–Vaisala frequency, 3:207, 3:255–256, 3:763 see also Buoyancy frequency BSR see Bottom-simulating seismic reflector (BSR) BT see Bathythermograph BTM see Bermuda Testbed Mooring (BTM) Bubble clouds, 1:441–442 acoustic scattering, 1:107 air–sea gas exchange, 1:442 breaking waves and, 1:434 Bubbles, 1:439–444 acoustical properties, 1:443 backscatter, measurement of, 1:443 breathing frequency, 1:443 acoustic noise, 1:57, 1:58, 1:60, 5:580 acoustic scattering, 1:116 air–sea gas exchange and, 1:151–152 atmospheric, sources of, 1:439 benthic, sources of, 1:439
bursting, 1:442–443 film cap, shattering effects, 1:442–443 cavitation, 1:439 development, 1:440–442 developmental stage, 1:439 dispersion, 1:440–442 distribution, 1:443–444 entrainment, breaking waves, 1:433 foam see Sea foam formation, estuaries, methane release, 3:4 Langmuir circulation and, 3:410–412 optical properties, 1:443 resonance frequency, 1:65 sources, 1:439–440 surfacing, 1:442–443 upper ocean see Upper ocean wave breaking, 5:580 whitecaps see Whitecaps see also Bubble clouds Budgets energy see Energy budget ocean climate models see Ocean climate models tracers see Tracer budgets water see Water budget Bulgaria, Black Sea coast, 1:211, 1:401 Bulk density, seafloor sediments, 1:78, 1:78T, 1:80 Bulk formula, evaporation, 2:326, 2:329 Bulk models, mixed layer, 4:209, 6:214 Bulk modulus, seafloor sediments, 1:78, 1:78T, 1:80 Bullard heat flow probe, 3:42–43, 3:42F Bullard plot, 3:43–44 Bullia spp. (plough shells), 5:52F, 5:55, 5:56 Bundesanschalt fr Wasserbau, 1:154T Bunts, 2:536 definition, 2:536 Buoyancy deep-sea fishes, 2:71 hydrothermal plumes, 2:130, 2:131, 2:131F, 2:136–137 mesoscale eddies, 3:763 remotely operated vehicles (ROVs), 4:742 three-dimensional turbulence, 6:22–23 under-ice boundary layer, 6:157 Buoyancy currents, 5:391 fiords, 2:355 Buoyancy flux(es), 4:123, 6:339–340 coastal circulation models, 1:572 deep convection, 2:13, 2:15 definition, 4:123 downward, 5:383–384 ocean subduction, 4:156, 4:157F, 4:162–163 open ocean convection, 4:220, 4:223F sea surface, 4:163, 4:163F, 4:165 surface, 5:383 thermal and haline, 6:339–341 thermohaline circulation, 4:122 Buoyancy-fossils, 2:614 Buoyancy frequency, 6:212–213 diapycnal mixing and, 6:89F
(c) 2011 Elsevier Inc. All Rights Reserved.
internal waves, 3:268, 3:270 pressure and, 6:382F three dimensional turbulence, 6:22 Buoyancy length scale, definition, 4:221–222 Buoys data from, 5:88 moorings, 3:920, 3:923 shape, 3:920–921 tracer release experiments and, 6:90–91 Tropical Atmosphere-Ocean array, 2:231–234, 2:234F Burger number, 6:62, 6:286 meddies, 3:702 Burial ships, 3:695 Buried nodules, 3:492 Burning, in situ, oil pollution, 4:194 Burrow(s), 1:398 benthic infauna, 1:395, 1:398, 2:56F Darcy’s law and, 1:398 sandy sediments, 1:398 Burrowing epibenthic predators, 1:395 macrofauna adaptations, sandy beaches, 5:54–55, 5:55F sandy beach biology and, 5:49 Burt, P J, acoustic noise, 1:54–55, 1:55 Bushnell’s Turtle submarine, 3:513 Bussol’ Strait, 4:200F, 4:201, 4:206, 4:206–207 see also Okhotsk Sea Butterfly fish (Chaetodontidae), 2:395–396F aquarium mariculture, water temperature range, 3:526 Buzzards Bay, Massachusetts, seiches, 5:348 By-catch, 2:160, 3:565 deep-water sharks, 4:230–232 definition, 2:202 ecosystem effects, 2:201–204 fishing methods/gears, 2:544–546, 4:237 problem solutions, 2:203–204 resource conservation issues, 4:241–242 Salmo salar (Atlantic salmon) fisheries, 5:3–4 seabirds see Seabird(s) toothfish, 5:517 Bythites hollisi (bythitid fish), 3:139–140, 3:140F Bythitid fish (Bythites hollisi), 3:139–140, 3:140F Bythograea thermydron (brachyuran crab), 3:133F, 3:135F, 3:136–138, 3:136F
C CA (carbonic anhydrase), 6:83 Cable drag, tow cables see Tow cable drag Cabotage system, 5:406 Cadiz, Gulf of, subsurface eddy, 3:708 Cadmium (Cd) atmospheric deposition, 1:254T
Index biological uptake, phytoplankton, 6:80 chemical speciation in seawater, 6:79 concentrations N. Atlantic and N. Pacific, 6:101T in phytoplankton, 6:76T in seawater, 6:76, 6:76T depth profiles, 6:77F dissolved, 6:105 enhancement in coastal waters and embayments, 1:200 enrichment factor, 3:773T global atmosphere, emissions to, 1:242T metabolic functions, 6:83 North Sea, atmospheric deposition, 1:240F oceanic, 1:195, 1:200 organic complexation, 6:105 pollution, 3:768–769 anthropogenic and natural sources, 3:769T distribution, 3:771T human health, 3:774 riverine flux, 1:254T seabirds as indicators of pollution, 5:275, 5:276 toxicity, 6:107 see also Cadmium/calcium ratio Cadmium/calcium ratio, 3:455–456, 5:337 introduction by Boyle E, 5:337 phosphate content and, 5:333, 5:337, 5:337F as productivity proxy, calcareous shells, 5:337 see also Cadmium (Cd) Caffeine, sewage contamination, indicator/use, 6:274T Cage systems marine culture, 3:534 salmonid farming, 5:25, 5:26–27 Caicos drift, 4:15F Calanoida copepods, 1:640 biodiversity, 1:636–637, 1:637F body forms, 1:642F Calanoides carinatus, 1:649 Calanus finmarchicus see Calanus finmarchicus Calanoides carinatus, 1:649 Calanus, 4:456, 4:457F Calanus finmarchicus (zooplankton), 1:68F, 1:640, 1:642F, 1:648, 1:649F, 2:363–364, 3:661 abundance, North Atlantic Ocean index and, 1:634–635, 1:636F density, cod productivity effects, 4:150–151, 4:151F distribution Continuous Plankton Recorder survey, 1:633, 1:634F Great South Channel, 4:354F population persistence, 4:358 Calanus hegolandicus abundance, North Atlantic Ocean index and, 1:634–635 distribution, Continuous Plankton Recorder survey, 1:633, 1:634F
Calanus marshallae, stage-structured population model, 4:552, 4:553F Calcareous biogenic contourites, 2:86 Calcareous nanoplankton see Coccolithophores Calcareous shells, cadmium/calcium ratio as productivity proxy, 5:337 Calcification definition and equation, 1:610 marine organisms, biological pump and, 1:485F, 1:486 Calcite, 1:545 depth profile, 1:448F magnesium in, 2:103 saturation state, 3:400 coastal waters, 3:400F solubility, 1:447 in submarine groundwater discharge, 5:552 Calcite compensation depth (CCD) Cenozoic, 1:517, 1:517F Pacific, 1:447–448 Calcium (Ca, and Ca2+), 4:587 cosmogenic isotopes, 1:679T oceanic sources, 1:680T river water concentration, 1:627T, 3:395T sea water concentration, 1:627T determination, 1:626 Calcium carbonate (CaCO3), 1:445–454, 1:610, 1:613, 4:90–91 accumulation and preservation, 1:451 biogenic, 1:371–372 flux, 1:373F chemical weathering, 1:515 climate proxy, 3:885–886 concentration, zinc and, 6:83 content, Paleocene-Eocene Thermal Maximum, 4:321–323 coral reef production, 1:665 cycle, 4:90F depth profile, 1:446–450 diagenesis, 1:451–453 dissolution, 1:446–450 governing equation, 1:447 see also Carbonate compensation depth distribution, 1:450–451 global, 1:447F foraminiferal distributions, 1:342 impact of CO2 levels, 4:460 lysocline, 1:448 oxygen isotopic ratio determination, 1:502, 1:502–503 see also Oxygen isotope ratio planktonic, 1:371 producers, 1:445–446 saturation, 1:447 saturation state, coastal waters, 3:400F secreted by seaweeds, 4:426 in sedimentary sequences, 3:912 see also Aragonite; Calcite; Carbonate Calcium carbonate compensation depth (CCD), manganese nodules, 3:492, 3:493, 3:494 Calcium carbonate cycle, 4:90F
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449
Caldera collapse, tsunami and, 6:133 Calibration absorptiometric chemical sensors, 1:12 anemometers, 5:375–376 black-body, satellite remote sensing, 5:91, 5:94 for data assimilation in models, 2:2 narrow beam filter radiometers see Narrow beam filter radiometers Optical Plankton Counter (OPC), 4:249 population dynamic models, 4:550–552 radiocarbon (carbon-14, 14C) ocean models, 4:647–650 salinometers, 1:713F sensors ocean color, satellite remote sensing, 5:118–119 wind speed measurements, 5:375–376 single point current meters, 5:433–434 spacecraft instruments, 5:94 thermistors, 1:710 thermometers, 1:709–710, 1:710 transmissometers, 6:113 California fossil layers, 6:222 radium-228 distribution, 6:252F time series, California sardine and northern anchovy, 4:700F water, microbiological quality, 6:272T California, Gulf of, sedimentary records of Holocene climate variability, 3:126 California Cooperative Oceanic Fisheries Investigations (CalCOFI), 3:123 California Current, 1:459–463, 1:460F catch (anchovy and sardine), 4:701F flow, 1:459–461, 1:460F mesoscale eddies, formation of, 3:760, 3:762F origins, 1:455 regime shifts, 4:711–712 river plumes, 1:463 seabird responses to climate change direct, 5:259–261, 5:260F, 5:261F indirect, 5:262 sea surface temperature, 1:464F satellite-derived images, 1:461–463, 1:462F ‘spring transition’, 1:461 topographic effects, 1:463–464 upwelling, 1:461–463, 1:463, 1:464F variability eddy/meander field, 1:461–463, 1:462F ENSO phenomenon and, 1:464–465 interannual and interdecadal, 1:464–465 seasonal, 1:459, 1:460F on shorter-than-seasonal timescales, 1:461–463, 1:462F volume transport, 1:455 water properties, 1:463 California Intermediate Water (CIW), temperature–salinity characteristics, 6:294T
450
Index
California sardine, biomass time series, 4:700F California sea lion (Zalophus californianus) adaptation to light extremes, 3:587–588 diving characteristics, 3:583T myoglobin concentration, 3:584T oxygen store, 3:583F see also Otariinae (sea lions) California Undercurrent, 1:459, 1:460F Callinectes sapidus (blue crab), world landings, 1:701T, 1:702 Callorhinus ursinus (northern fur seal), 4:135 Calonectris diomedea (Cory’s shearwater), 5:253 see also Shearwater(s) Caloric half-years, 4:508, 4:509F Cal-Tech Patterson sampler, 2:255–257 Calvin-Benson cycle, 3:151–152, 3:160 Calving definition, 3:190 icebergs, 3:211 ice shelf stability, 3:211, 3:213–214 Calycophorae siphonophores, 3:12, 3:13F Calypso sediment coring system, 3:881–883 Calyptogena magnifica see Vesicomyid clams Cambrian strontium isotope ratios, 3:460F, 3:461 substrate revolution, 1:400 Camouflage cephalopods, 1:526–527 demersal fishes, 2:461 mesopelagic fishes, 3:751 Canada Atlantic salmon (Salmo salar) fisheries, 5:1–2, 5:3 catch, 5:8F, 5:9 East Coast, ice-induced gouging, 3:195–196 Pacific salmon fisheries, 5:12 catch, 5:14F, 5:15F, 5:17F, 5:19F, 5:20F, 5:21F chinook salmon, 5:14, 5:15F chum salmon, 5:17, 5:21F Fraser river block effect, 5:16 hatcheries, 5:18 management, 5:20, 5:21 pink salmon, 5:17, 5:20F sockeye salmon, 5:16, 5:18, 5:19F, 5:21 treaty, 5:21–22 salmonid farming, 5:14, 5:18, 5:24 Canada Basin, 1:211 boundary current, 1:216–218 eddies, 1:220–221 mean ice draft, 5:152F temperature and salinity profiles, 1:213F, 1:214F Canada Center for Inland Waters, 1:154T Canada Oceans Act 1997, 4:180 Canadian Arctic, polynyas, biological importance, 4:544
Canadian Arctic Archipelago, 5:170 sea ice cover, 5:141, 5:141–142 interannual trend, 5:146 Canadian Arctic Islands, 5:174 Canadian Basin Deep Water (CBDW), 1:219 eddies, 1:221F Canadian Scientific Submersible Facility, remotely-operated vehicles (ROV), 6:260T Canadian Space Agency, Radarsat-1 and Radasat-2, 5:103 Canary Current, 1:467–476, 1:720–721 Azores Current and, 1:467, 1:474, 1:476 coastal upwelling, 1:235, 1:467, 1:468–472 annual cycle, 1:469–470, 1:470F cross-shelf flow profiles, 1:472, 1:472F filaments, 1:472, 1:473F Trade Winds and, 1:467, 1:469, 1:471F, 1:476 geostrophic flow, 1:467, 1:468F seasonal variation, 1:467, 1:469F numerical models, 1:474–476, 1:476F origins, 1:467 poleward undercurrent, 1:472–474, 1:476 seasonal analysis, 1:473 structure, 1:472–473, 1:474F subsurface eddy formation, 1:473 spatial variability, 1:474, 1:475F transport, 1:724T unresolved questions, 1:476 see also Atlantic Ocean current systems; North Atlantic Subtropical Gyre Canary debrite, 5:459 Canary Islands, eddies, 3:345–346, 3:346F Cande, S C, geomagnetic polarity timescale development, 3:29F, 3:30 Cane-Zebiak model, 2:274 Canyons internal tides, 3:260–261 nepheloid layers and, 4:16–17 submarine, 5:462 definition, 5:465 Capacitance change hygrometers, 5:379 Capacitance sensors, humidity, 5:378–379 Cap de la Hague, France, 4:82 location, importance of, 4:82 nuclear fuel discharges coastal circulation, 4:87 regional setting, 4:85, 4:86F surface circulation, 4:87 reprocessing discharges, circulation of, 4:85–86 Cape Cod tidal front, temperature, 5:397F Cape fur seal, population, Benguela upwelling, 4:706F Cape gannet, population, Benguela upwelling, 4:706F Cape Leeuwin, 3:444, 3:444F, 3:445, 3:445F, 3:447, 3:451, 3:451F
(c) 2011 Elsevier Inc. All Rights Reserved.
Capelin (Mallotus villosus) biomass measurement, 2:509, 2:509F discarding issues, 2:202 Cape May, New Jersey, USA, coastal erosion, 1:585F Cape of Good Hope, ferromanganese deposits, 1:259 Cape petrel (Cape pigeon), 4:591F see also Procellariiformes (petrels) Caperea marginata see Pygmy right whales Capes Current, 3:444F, 3:445–446, 3:447, 3:451–454, 3:453F high-salinity flow, 3:445–446 Capesize bulkers, 5:402, 5:403–404, 5:403T Cape St. Vincent, meddy formation, 3:708–709 Cape Verde Islands, magnetic profile, 3:481F Capillary waves, 5:573, 5:576 parasitic, 5:575F, 5:580 generation, 5:579, 5:579F see also Surface, gravity and capillary waves Capital investment, Mediterranean mariculture, 3:533 ‘Capital stuffing,’ cost inefficiencies, fishery management, 2:515–516 Capture fisheries, economics annual catches, 2:491 application of game theory, 2:495 cooperative game theory, 2:495 examples, 2:495 non-cooperative game theory, 2:495 ecosystem-based fisheries management, 2:494 difficulties, 2:494 ecosystems crossing national borders, 2:494 factors favoring, 2:491 employment, 2:491 global trend in resource status, 2:491–492, 2:492F internationally shared fishery resources, 2:494–495 exclusive economic zones, 2:494 Law of the Sea Convention (1982), 2:494 maximum sustainable yield, 2:491 mobility, visibility and uncertainty, 2:493–494 multidisciplinary management, 2:492 open-access fisheries, 2:493 deterrent to investment, 2:493 educational role, 2:494 fisheries as non-renewable resource, 2:493–494 path to overexploitation, 2:494 problems, 2:493–494 reaching upper limit of capacity, 2:491 resources, 2:492–493 bionomic equilibrium, 2:493 history of discipline, 2:492–493 non-renewable resources investment, 2:493
Index positive v. negative investment, 2:493 real capital, 2:493 renewable resources investment, 2:493 temporal asset management, 2:493 shared fishery resources application of game theory, 2:495 straddling fish stocks, 2:495 straddling fish stocks, 2:495 UN assessment, 2:491–492 see also Fishery economics Carassius auratus see Goldfish (Carassius auratus) Carbamate pesticides, sensors, 1:13 Carbon (C) anthropogenic, 4:105 definition, 4:113 see also Carbon dioxide (CO2) C:n:p ratios, 4:587 coastal fluxes, 3:399F cosmogenic isotopes, 1:679T oceanic sources, 1:680T reservoir concentrations, 1:681, 1:681T specific radioactivity, 1:682T cross-shelf transport, episodic pulses, 5:481–485 cycle see Carbon cycle d13C, 5:529 see also Carbon isotope ratios (d13C) 14 d C, 5:420–421 D14C, coral-based paleoclimate records, 4:339T, 4:345, 4:346 decadal variability, 4:343 upwelling, 4:340–341 see also Radiocarbon (carbon-14, 14C) dissolved inorganic see Dissolved inorganic carbon (DIC) organic see Dissolved organic carbon (DOC) effect on pH, 1:495–496, 1:496F exospheric pool, 1:515, 1:515–516 export fluxes, estimated by adjoint method (inverse modeling), 3:304–310 fixation, 4:578 flux to deep water, 4:19 importance of, 1:477 inorganic dissolved see Dissolved inorganic carbon (DIC) pump, 4:682 isotopes abundance, 5:420 variations in ocean, 5:529 see also Carbon isotope ratios (d13C); Radiocarbon; specific isotopes isotopic fractionation, Cenozoic, 1:517–518, 1:518F isotopic ratio, planktonic–benthic foraminifera differences, 3:916F in marine biomass, 4:105–106 organic see Organic carbon (OC) pump, 4:682
radiocarbon see Radiocarbon (carbon-14, 14C) river fluxes, 3:397 sequestration by direct injection see Carbon sequestration by direct injection use in analysis of food webs, 4:19 see also Carbon dioxide (CO2); Carbon sequestration by direct injection; Dissolved inorganic carbon (DIC); Dissolved organic carbon (DOC); Nutrient(s) Carbon-12 (12C), 5:529 Carbon-13 (13C), 5:529 d13C, 5:529 Carbon-14 (14C) see Radiocarbon (carbon-14, 14C) Carbonate (CO23) accumulation flux during Cenozoic, 1:517, 1:517F model, 1:522F coral reef production, 1:665 dissolution in pore water, 4:566T in oceanic carbon cycle, 1:478–479 pump, 1:481F, 1:485F, 1:486 rocks, chemical weathering, 1:515 sediments, 4:141 land-sea carbon flux and, 3:400 sediments, Cenozoic, 1:517–518, 1:518F organic carbon and, 1:518F Carbonate compensation depth (CCD), 1:449F paleological record, 1:451, 1:453F Carbonate critical depth (CCrD), 1:448 Carbonate fluoroapatite (CFA), 1:261 as phosphorus sink, 4:410 Carbonate lysocline, 1:449 Carbonate metal complexes, 6:103 ‘Carbonate ocean’, 1:374 Carbonate oozes, 1:445, 1:446F Carbon cycle, 1:477–486, 4:90F, 4:106F, 4:455 biological pump, 1:481F, 1:484, 1:484F, 3:678 carbonate, 1:481F, 1:485F, 1:486 contribution of POC vs. DOC, 1:484–485 factors affecting efficiency, 1:484–485 community structure, 1:486 nutrient supply, 1:485–486 iron fertilization and, 3:331, 3:339–340, 3:339F, 3:340, 3:340F box models, 1:519–520, 1:520F, 1:521–522, 4:108–109, 4:109F refinements, 4:109 Cenozoic changes and associated processes, 1:514–516, 1:516–517 carbonate accumulation, 1:517, 1:517F Himalayan uplift, 1:516–517, 1:518 long-term regulation of atmospheric CO2, 1:515–516 lysocline, 1:517, 1:517F, 1:522 organic carbon subcycle, 1:517–519, 1:518F
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strontium isotopic ratio, 1:516–517, 1:516F, 1:522 weathering see Chemical weathering coastal margins, 4:252–260 continental margin environments, 4:252–260 global, 1:477–478 gas hydrates and, 1:478F, 3:788, 3:789 research programs, 1:478 importance of bacterioplankton, 1:274, 1:275 intermediate complexity models, 4:109–110 inverse models, 4:110 models, 4:112–113 box see Carbon cycle, box models Cenozoic oceans, 1:514–523 inverse (isotopic data use), 1:518F, 1:521–522 role of, 1:522 oceanic, 1:479–480 pelagic ecosystems, 2:597 role of seabirds, 5:282 shelf slope fronts and, 5:399 shore edge ecosystems, 4:254 solubility/exchange of CO2 between ocean/atmosphere, 1:480 carbon redistribution and, 1:481–484 oceanic circulation and, 1:481–484 ocean structure and, 1:480–481 solubility pump and, 1:480–481, 1:481F see also Carbon dioxide (CO2) cycle; Carbon system; Primary production measurement methods; Primary production processes Carbon dioxide (CO2), 4:90F, 4:94, 4:97F air–sea flux, 4:92, 4:258–260, 4:259T global distribution, 4:91F simulated, 4:101F anthropogenic, 1:477–478, 1:479F, 4:102 anthropogenic emission perturbations, 3:396, 3:398F, 3:399–400 atmospheric, 4:131 dissolved inorganic carbon and, 4:105 global warming and, 4:105 nutrient utilization and, 4:108–109 paleoceanographic research, 4:300 see also Carbon dioxide (CO2), prehistoric atmospheric concentration atmospheric–coastal water flux, 3:400F calcite dissolution and, 5:552 Cenozoic indicators of, 1:514, 1:514F long-term regulation, 1:515–516 PCO2 see Partial pressure of atmospheric carbon dioxide (PCO2) release due to tectonic processes, 3:789 coral reef production, 1:665 cycle see Carbon dioxide (CO2) cycle deep convection, 2:15 see also Carbon cycle
452
Index
Carbon dioxide (CO2) (continued) deglaciations and, 3:786 dissolved deep ocean, 1:371 depth profiles, estuarine sediments, 1:544F diffusion coefficients, 1:147T estuarine sediments, 1:544F oceanic carbon cycle, 1:478–479 regulation in surface waters, 3:651 sensors, 1:13–14 transfer to atmosphere, 1:480, 1:482F see also Dissolved inorganic carbon (DIC); Total inorganic carbon effect of CaCO3, 4:460 effect on pH, 1:613, 4:460 effects of coccolithophores, 1:611 estuaries, gas exchange in, 3:5, 3:5T fixing, 4:588 fluorescent sensing, 2:594, 2:594T gas analyzer, 1:488 greenhouse effect and, 4:509 as greenhouse gas, 3:786 ionogenic, calcite dissolution, 1:450 measurements, 3:123 oceanic sink, 4:92 ocean thermal energy conversion, 4:171 partial pressure see Partial pressure of atmospheric carbon dioxide (PCO2) photochemical flux, spectral dependence of, 4:422F photochemical production, 4:417F, 4:418 physical state at various pressures/ temperatures, 1:498, 1:499F prehistoric atmospheric concentration, 3:796–797, 4:319–320 Cretaceous, 4:320, 4:320–321 Oi1 event, 4:325 Phanerozoic, 4:320F radiocarbon, measurement of, 4:640 reactivity with seawater, 4:91–92 reduction, 4:585 sequestration by phytoplankton, 4:445, 4:450–451 solubility in sea water, 1:480 sources, 1:489–491 primary, 1:495 transfer across air–water interface, 1:480, 1:480F solubility pump, 1:481–484, 1:481F, 1:482F transfer coefficient, 3:2 transfer velocity, 1:152F two-box ocean models and, 4:96 see also Carbon cycle; Carbon dioxide (CO2) cycle; Carbon isotope excursions; Carbon sequestration by direct injection; Total carbon dioxide signature Carbon dioxide (CO2) cycle, 1:487–494 atmospheric change, implications of, 1:487 biological utilization, 1:489 history, 1:488 industrial emission rate, 1:487
methods, 1:488–489 sinks, 1:489–491 sources, 1:489–491 units, 1:487–488 see also Carbon cycle; Carbon dioxide (CO2); Primary production processes Carbon disulfide (CS2) air–sea transfer, 1:159–160 photochemical oxidation, 1:159, 4:419 Carbonic acid (H2CO3), in oceanic carbon cycle, 1:479 Carbonic anhydrase (CA), 6:83 Carbon isotope(s), see also Carbon (C) Carbon isotope excursions (CIE), 3:796–797 Paleocene-Eocene Thermal Maximum, 4:321 see also Carbon dioxide (CO2); Methane hydrate Carbon isotope ratios (d13C) ancient soil carbonate measurements, 1:514, 1:517–518, 1:518F coral-based paleoclimate records, 4:339–340, 4:339T, 4:341 cloud cover and upwelling, 4:340–341 gas hydrates and, 3:787–788 long-term tracer applications, 3:456 as productivity proxy, 5:333, 5:336–337 surface vs. subsurface waters, 5:336 see also Radiocarbon (carbon-14, 14C) Carbon monoxide (CO) air–sea transfer, 1:163T, 1:167–169 atmospheric sources and sinks, 1:169T estuaries, gas exchange in, 3:6 photochemical flux, spectral dependence of, 4:422F photochemical production, 4:417F, 4:418, 4:421F Carbon sequestration by direct injection, 1:495–501 carbon’s effect on pH, 1:495–496, 1:496F CO2 from power plants/factories, 1:496 effectiveness, 1:497–498 atmospheric CO2, 1:497, 1:497T computer modeling studies, 1:497 net retention over time, 1:497, 1:498F outgassing timescale, 1:497 use of tracers, 1:497 factors favoring oceanic methods, 1:495 injection methods, 1:498–500, 1:499F bypassing equilibration timescale, 1:499–500 CO2 lake, 1:498–499 hydrate reactor, 1:498 introduction to outflows, 1:498 rising droplet plume, 1:498 sinking plume, 1:499 interest in technology, 1:495 local impacts and public perception, 1:500 effects of pH and CO2 changes, 1:500 focus of studies, 1:500
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inclusion in research/debate, 1:500 significance of impacts, 1:500 ocean capacity, 1:496–497 carbonate system, 1:496 effects of long travel times, 1:496 effects of short travel times, 1:496 impacts on deep-ocean environments, 1:496–497 storage capacity, 1:496 target stabilization of CO2, 1:495 terrestrial methods, 1:495 Carbon system, modeling, 4:105–114 3D biogeochemical simulations, 4:111–112 global box models see Box models intermediate complexity/inverse models, 4:109–110 ocean circulation and biogeochemical models, 4:107–109 ocean tracers and dynamics, 4:107 as research tools, 4:112–113 thermocline models, 4:110–111, 4:110F see also Carbon cycle Carbon tetrachloride (CCl4), 1:531 chemical stability, 1:532 solubility, 1:532–533 Carbonyl sulfide (COS) air–sea transfer, 1:159 estuaries, gas exchange in, 3:6 photochemical flux, spectral dependence of, 4:422F photochemical oxidation, 1:159 photochemical production, 4:417, 4:417F Carcinus maenas (European green crab), 2:342 Cardigan Strait, 1:223 Caretta caretta (loggerhead turtle), 4:136, 5:214F, 5:218–219, 5:218F see also Sea turtles Carey, W M, acoustic noise, 1:59 Cargo flows, container, future developments, 5:408 global volume and types see World seaborne trade hazardous, environmental issues, laws/regulations, 5:406 Cargo ports, 5:407 Cargo ships see World fleet; Ship(s), cargo Caribbean Current, 2:561, 3:288, 3:288–289, 3:293F Caribbean Sea artificial reefs, 1:226–227 diurnal heating, 6:170F hurricanes, 6:193F marine protected areas, 1:654 storm surge prediction model, 5:537F Caribbean Sheets and Layers Transects (C-SALT) experiment, 2:163–164 Caridea (decapod shrimps), bioluminescence, 1:380 Carnegie, 3:479 Carnivores, 3:589, 3:589–591, 3:589T family Mustelidae see Mustelids
Index pinnipeds see Pinnipeds see also Marine mammals; specific species Carnot energy conversion, ocean thermal energy conversion, 4:167–168, 4:168 B,B-Carotene, structure, 3:570F Carotenoids, 3:569 Carp (Cyprinus carpio), 2:471F Carson, Rachael, 3:687 Cartagena Convention, 3:668T Cartesian coordinate system, current flow, 4:115, 4:116F Carthage, deep-water trade route from, 3:699 Cartilaginous fish, acoustic scattering, 1:65–67 Cascades, 4:265–271 definition, 4:265 flow characteristics, 4:266–267 parameters, 4:266–267 Cascadia subduction zone, accretionary prisms, 1:31–32 ‘Case 1’ waters, 4:732 bio-optical modeling see Bio-optical models definition, 1:386T, 4:619 Hydrolight simulations, 4:625, 4:625F, 4:626F, 4:627F, 4:628F ‘Case 2’ waters, 4:732 bio-optical modeling see Bio-optical models definition, 1:386T, 4:619 Hydrolight simulations, 4:625, 4:625F, 4:626F, 4:627F, 4:628F CASI (Compact Airborne Spectographic Imager), 1:144 Cassin’s auklet (Ptychoramphus aleuticus), 4:458 Cast nets, falling gear fishing methods, 2:539, 2:540F Catabolic, definition, 3:7 Catadromy, 2:216 Catch-dividing bucket, 6:362–363 Catch documentation scheme, Commission for the Conservation of Antarctic Marine Living Resources, 5:517 Catch quotas see Fishing quotas Category 5 hurricanes, 6:208–209 Catfish (Ictaluridae), 2:481 Cat’s paws, 6:304–305 Cattails, 3:898 Caulerpa taxifolia alga, 2:337, 2:342 Cavitation, 1:439, 1:439–440 CBDW see Canadian Basin Deep Water (CBDW) CCAMLR see Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) CCD see Calcite compensation depth (CCD) CDB (catch-dividing bucket), 6:362–363 CDOM see Gelbstoff CDVP see Coherent Doppler velocity profiler (CDVP)
CDW see Circumpolar Deep Water (CDW); Cretan Deep Water (CDW) CEAREX (Coordinated East Arctic Experiment), 1:92–93 Celebes Sea, 5:305, 5:306 upper layer velocity, 5:314F variability, 5:314 Cell wall(s), phytoplankton, varieties, 4:679–680 Celtic Sea front, chlorophyll concentration, 5:396F CEMP (Ecosystem Monitoring Program), Commission for the Conservation of Antarctic Marine Living Resources, 5:519 Cenozoic calcium compensation depth, 1:451 carbon cycle models see Carbon cycle carbon releases, 3:792 climate, 1:502–513 oxygen isotope records see Oxygen isotope ratio (d18O) climate change, 1:502, 1:514 mechanisms, 1:511–512 cooling, paleoceanographic research, 4:300 interocean gateways, opening/closing of, 4:303, 4:304F neodymium isotope ratios, 3:462F paleo-ocean modeling, 4:303 strontium isotope ratios, 3:460F, 3:461–462 see also Paleoceanography; specific epochs Center for Ocean Law and Policy, University of Virginia, 3:665 Central American Passage see Isthmus of Panama Central American sinkholes, Indian boats in (archaeology), 3:697 Central Equatorial Pacific, nitric oxide, 1:165, 1:166 Central Lau Basin, spreading mechanisms, 3:842F Central Pacific, seabird responses to climate change, 5:262 Central Pacific Basin, manganese nodules, 3:493 Central Water, 6:181 Centrophorus granulosus (gulper shark), over-exploitation vulnerability, 4:232 Centrophorus squamosus (leafscale gulper shark), open ocean demersal fisheries, FAO statistical areas, 4:231T, 4:232 Centroscymnus coelolepis (Portuguese dogfish), open ocean demersal fisheries, FAO statistical areas, 4:231T, 4:232 Cephalopods, 1:524–530 biology, 1:524–526 brain and senses, 1:526 buoyancy and jet propulsion, 1:524–526
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buoyancy, 1:526 jet propulsion, 1:526 central nervous system, 1:526 color and pattern, 1:526 ability to change, 1:526 chromatophore muscles, 1:526 chromatophores, 1:526 function, 1:526–527 iridophores, 1:526 leucophores, 1:526 escape and luminescence, 1:526–527 visual capabilities, 1:526–527 bioluminescence, 1:380 Cranchiidae family, 3:14–16, 3:15F description of class, 1:524 diagnosis(classification/features) of Cephalopoda, 1:524, 1:525T compared to other Mollusca, 1:524 compared to teleost fishes, 1:524–526 distribution, 1:524 ecology, 1:528 feeding and growth, 1:527 feeding methods, 1:527 food, 1:527 rates, 1:527 fisheries, 1:524, 1:529 commercial harvest, 1:529 historical and contemporary, 1:529 global biomass, 1:529 estimates, 1:529 uncertainty of data, 1:529 habitat, 3:899 harvesting, 3:902 life cycle, 1:527 common features, 1:524 population biology, 1:528 single generation life cycle, 1:528F, 1:529 production, global, 3:905–906, 3:906F reproduction, 1:527 maturation and mating, 1:527 spawning and death, 1:527–528 breeding seasons, 1:528 death, 1:528 fecundity, eggs and hatchlings, 1:527–528 locational spawning differences, 1:527 trophic relations, 1:528–529 consumption rates of predators, 1:529 importance as food, 1:529 prey and predators, 1:524 Cephalorhynchus dolphins, 2:149 Cephalorhynchus hectori (Hector’s dolphin), 2:153, 2:159 Cephaloscyllium ventriosum (swell shark), 2:448F Cepphus, 1:171T diet, 1:174 plumage, 1:172 see also Alcidae (auks) Cepphus grylle (Black guillemot), 1:171, 5:258–259, 5:259F CERES see Clouds and Earth’s Radiant Energy System experiment Cerium, 4:653, 4:654, 4:655T anomaly, 4:656–659
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Index
Cerium (continued) defining equation, 4:656–657 vertical profiles, 4:656–657, 4:660F dissolved, vertical profiles, 4:655, 4:658F isotopes, 4:654 redox reaction, 4:656–659 see also Rare earth elements (REEs) Cerorhinca, 1:171T diet, 1:174 reproduction, 1:174–175 see also Alcidae (auks) Cesium, 4:634 seabirds as indicators of pollution, 5:277 Cesium-137 (137Cs) atomic weapons and, 5:327 nuclear fuel reprocessing, 4:83, 4:84T, 4:85, 4:86–87 sediment chronologies, 5:328T sediment profile, 5:330, 5:331F Cestida ctenophores, 3:14 Cetaceans, 2:160 bioacoustics, 1:357 conservation status, 3:606–607T evolution, 3:591 exploitation, 3:635, 3:635–637, 3:636F, 3:637–638, 3:637F drive fisheries, 3:636 drive hunting, 3:636 history of, 3:635 migration and movement patterns, 3:596 odontocetes vs., 3:596 modern, 3:591, 3:591F phylogeny, 3:591–592, 3:592F suborders, 3:591 Archaeoceti, 3:591, 3:592–593 Mysticeti see Baleen whales Odontoceti see Odontocetes thermoregulation, 5:288 see also Beaked whales (Ziphiidae); Dolphins and porpoises; Marine mammals; Sperm whales (Physeteriidae and Kogiidae); specific species Cetorhinus maximus (basking shark), 2:375–376 CFA see Carbonate fluoroapatite CFCs see Chlorofluorocarbon(s) (CFCs) CFP (ciguatera fish poisoning), 4:432, 4:434T, 4:435T CFT (controlled flux technique), 1:153–155, 1:155F Chaetoceros diatoms, 4:434–436 Chaetoceros muelleri, 2:582F Chaetodontidae (butterfly fish) see Butterfly fish (Chaetodontidae) Chaetodon trifasciatus (melon butterfish), aquarium mariculture, 3:528–529 Chaetognatha (arrow worms), 1:379–380 Chain Fracture Zone, 2:565F, 2:566, 2:568F Chain transform fault, 3:841F Chalk formation, 1:451–453 geoacoustic properties, 1:116T
Challenger, HMS (survey ship1872-1876), 3:122, 5:410 Challenger Expedition, 4:296 drifter schematic, 2:172F sediment core collection, 4:296, 4:297F Chamber incubation (of benthic flux), 4:485 Chameleon profiler, 2:292F Champsocephalus gunnari see Mackerel icefish (Champsocephalus gunnari) Chandragupta, 4:770F Changjiang (Yantze River), hypoxia, 3:175 Channel-related drifts see Deep-sea sediment drifts Channels deep marine, 5:448F flows see Straits, flows Channichthyidae (icefishes), 1:193 see also Mackerel icefish (Champsocephalus gunnari) Chapman, N R, acoustic noise, 1:58F, 1:59 Chapman-Harris curves, 1:106 Charadriiformes, 5:266T Alcidae see Alcidae (auks) Laridae see Laridae (gulls) migration, 5:244 Rynchopidae see Rynchopidae (skimmers) Sternidae see Sternidae (terns) see also Seabird(s) ‘Charismatic organisms,’ fishery management research, 1:652 Charlie-Gibbs Fracture Zone, 2:565F, 2:569 Charr (Salvelinus), 5:29 salmonid farming, 5:23 Salvelinus alpinus (arctic charr), 5:32 Charter rates, shipping, 5:404–405, 5:404T Charting vessels see Mapping and charting vessels Chauliodus macouni (viperfish), 4:6F Cheju, aerosol concentrations, 1:249T Chelate, definition, 6:85 Chelation, definition, 6:85 Chelator, definition, 6:85 Chelonia mydas (green turtle), 2:408–409, 5:216–217, 5:216F see also Sea turtles Chelonia mydas agassizi (black turtle), 5:216–217, 5:216F see also Sea turtles Cheloniids, 5:212, 5:216–217 genera, 5:212 Caretta, 5:218–219 Chelonia, 5:216–217 Eretmochelys, 5:218 Lepidochelys, 5:217–218 Natator, 5:218–219 see also Sea turtles; specific species Chemical(s), marine sources see Marine organisms Chemical erosion, 1:450 Chemical lysocline, 1:449
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Chemical Manufacturers Association (CMA), 1:531–532 Chemical remanent magnetization (CRM), 3:26 sediments, 3:26–27 Chemical sensing, 2:589 see also Fluorometry, chemical sensing Chemical sensors absorptiometric, 1:7–14 applications, 1:12–13 background subtraction, 1:12–13 basic principles, 1:7–8 calibration and error correction, 1:12 design, 1:11–12, 1:11F molecular recognition element, 1:10–11 optical fibers, 1:8–9, 1:8F optoelectronics, 1:9–10 reagent support material, 1:10 response characteristics, 1:10–11 typical configuration, 1:11F wavelength selector, 1:9 evanescent wave, 1:11–12, 1:12F reflectometric, 1:8, 1:11 Chemical speciation, definition, 6:85 Chemical tracers, 4:105 air–sea gas exchange and, 1:153 bioturbation, 1:396, 1:396–397 homogenization, 1:397, 1:397F inert, 3:300 mixing estimation and, 2:290 model constraints, 4:111–112 modeling, mixing estimation and, 3:305 reactive, 3:300–302 submarine groundwater discharge, 3:92–94, 5:555–557 see also Radionuclides, tracers; Tracer budgets Chemical transduction, chemical sensors, 1:10, 1:11 see also Molecular recognition element Chemical weathering Cenozoic carbonate minerals, 1:515 hypotheses Franc¸ois’, 1:517 Raymo’s, 1:516, 1:517 Walker’s, 1:515–516, 1:517 silicate minerals, 1:515 air temperature dependency, 1:515–516 flux model, 1:521, 1:522F Himalayan uplift and, 1:516–517 rates, 1:516 see also Silica cycle of phosphorus from bedrock, 4:401, 4:402F Chemolithoautotrophy, 4:34 see also Nitrification Chemolithotrophs, 4:585 definition, 2:73 Chemolithotrophy, 4:585 Chemosynthesis, 3:149 Calvin-Benson cycle, 3:151–152, 3:160 carbon dioxide, 3:160, 3:160F
Index chemosynthetic process, 3:151–152, 3:152F energy yields, 3:151–152 food chains, 3:160, 3:162 hydrogen sulfide, 3:159–160, 3:160F, 3:161, 3:162 detoxification, 3:161, 3:162 transport, 3:161, 3:161F, 3:162 origin of life theory, 3:157 see also Deep-sea ridges, microbiology; Hydrothermal vent biota; Hydrothermal vent chimneys; Hydrothermal vent ecology; Hydrothermal vent fauna, physiology of Chemosynthetic organisms, accretionary prisms, 1:34 Chernobyl accident, 4:85 radioactive waste, 4:634 Cherokee, 6:260T Cherry salmon see Oncorhynchus masou (masu, cherry salmon) Chesapeake Bay atmospheric input of metals, 1:239, 1:239T eutrophication, 2:308T, 2:319F nutrient fractions, changing ratios, 2:314–315 fresh water outflow, 4:792 nitrogen, atmospheric input, 1:241T Chesapeake Bay Program, 4:284 Chetvertyy Strait, 4:201 Chile rocky shores harvesting, 4:768 salmonid farming, 5:24 tsunami (1960), 6:128 Chimaera monstrosa (Chimaeriformes), 2:452F Chimney ‘black smokers,’ deep submergence science and, 2:22, 2:23F convective see Convective chimney hydrothermal vent see Hydrothermal vent chimneys; Hydrothermal vent deposits China fishing fleet tonnage, 2:543 molluskan mariculture, 3:907, 3:907F China Ocean Mineral Resources R&D Association autonomous underwater vehicles, 6:263T deep-towed vehicles, 6:256T human-operated vehicles (HOV), 6:257, 6:257T China Sea, monsoons indicators, 3:913–914 long-term evolution of, 3:916–917 Chinese mitten crab (Eriocheir sinensis), 2:340 Chinook salmon see Oncorhynchus tshawytscha (chinook salmon) Chinstrap penguin (Pygoscelis antarctica), 5:522T, 5:525
response to climate change, 5:261, 5:261F prehistoric, 5:258 see also Pygoscelis Chionoecetes (snow, tanner crab), 1:702 world landings, 1:701T Chiridius armatus copepod, 2:363 Chirped surface wave groups, 4:772–773, 4:773F Chitin, 3:573 Chitosan, 3:573 Chloride (Cl-) concentration in river water, 1:627T concentration in sea water, 1:627T Chloride metal complexes, 6:103 Chlorinated hydrocarbons, 1:551–562 coastal ocean, 1:555–561 history, 1:553 marine environment, distribution in, 1:553–554 early 1970s, 1:553–554 1980s to present day, 1:554–555 open ocean, 1:554–555 structures, 1:552F trends in concentrations, 1:561, 1:561T see also specific chlorinated hydrocarbons Chlorinated pesticides, 1:551 environmental concerns, 1:551 human health concerns, 1:551 see also specific pesticides Chlorine, cosmogenic isotopes, 1:679T oceanic production, 1:679 oceanic sources, 1:680T reservoir concentrations, 1:681, 1:681T specific radioactivity, 1:682T Chlorine-36, cosmogenic isotopes, production rates, 1:680T Chlorine residuals, thermal discharges and pollution, 6:11–12 Chlorinity determination, 1:626 salinity and, 1:626, 2:249 Chlorobiphenyl congeners, 1:551 depth profile in sea water, 1:554, 1:557F lobster, 1:557–558 Chlorofluorocarbon(s) (CFCs), 1:418 atmospheric source, 1:531–532 chemical structures, 1:531 circulation tracers, 4:106–107, 4:107 distribution, 1:531 estuaries, gas exchange, 3:3 nuclear fuel reprocessing, 4:84–85 tracer applications, 1:684 uses, 1:531 Chlorofluorocarbon(s) (CFCs), in oceans, 1:531–538 age, 1:533–535 calculations, 1:533–535 caveats, 1:535–536 CFC-11/CFC-12 ratio, 1:534–535, 1:536F analytical techniques, 1:532 applications, 1:536–537 biogeochemical processes, 1:538 model constraints, 1:537–538
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thermohaline circulation, 1:537 upper ocean circulation, 1:537 chemical stability, 1:532 gas flux, 1:532–533 oceanic distribution, 1:533 solubility, 1:532–533 surface saturation, 1:533 tracers, 1:531 Chlorofluorocarbon-11 (CFC-11) chemical stability, 1:532 oceanic distribution/profile Atlantic, 3:300F eastern Atlantic, 1:533, 1:535F North Atlantic, 1:533, 1:534F North Pacific, 1:533, 1:534F Southern Ocean, 1:180F Chlorofluorocarbon-12 (CFC-12) chemical stability, 1:532 oceanic distribution North Atlantic, 1:533, 1:534F North Pacific, 1:533, 1:534F Chlorophyll autofluorescence, 4:245, 4:246F concentration Peru-Chile Current System (PCCS), 4:386F, 4:389, 4:389F polonium-210 and, 6:249, 6:249F concentration ([Chl]) apparent optical properties and, 1:388–389, 1:391, 1:392T, 1:393F as index of bio-optical state, 1:388 inherent optical properties and, 1:388–389, 1:389–390, 1:389F, 1:390T, 1:391F variation, 1:388 deep, maximum (DCM), 5:477–478, 5:477F fluorescence, 4:734 spectral range for remote sensing, 4:735T see also Chlorophyll a global distribution, 4:91F simulated, 4:101F prediction from phytoplankton nitrogen, 5:478 Southern California Bight, 4:102F spatial variability, Gulf of St Lawrence, 5:477, 5:477F spectral range for remote sensing, 4:735T Chlorophyll a algorithm, ocean color by satellite remote sensing, 5:120, 5:121F El Nin˜o event, 5:123F fluorescence, 2:581, 2:583 quantification, 2:587 ocean color and, 5:114, 5:125 bio-optical algorithms, 5:120, 5:121F SeaWiFS data, 5:122F, 5:123F Chlorophyll-specific absorption coefficient of phytoplankton, 1:386T, 1:389 Chlorophyta (green seaweeds), 4:427 Choerodon albigena (blue tuskfish), 2:453F Chondrus crispus algae, 5:322F
456
Index
Choshui (Taiwan), river discharge, 4:755T Christanaki, 4:770F Chromalveolate algae, 3:553–554 Chromium (Cr), 3:776, 3:777–778, 3:783 concentrations in ocean waters, 6:101T depth profile, 3:778, 3:778F oxic vs. anoxic waters, 3:778 Chromophoric dissolved organic matter (CDOM), 1:168 see also Gelbstoff Chromophoric molecules see Pigments Chrysler hysoscella, 4:705–707 Chrysochromulina, 2:313–314 Chrystal, G, 5:345 Chthamalus stellatus (Poli’s stellate barnacle), 4:763 Chukchi Cap, mean ice draft, 5:152F Chukchi Sea, 1:211, 1:218–219 polynyas, 4:540 seabird responses to climate change direct, 5:258–259, 5:259F indirect, 5:263–264 sound speed, 1:95 sub-sea permafrost, 5:566 Chum salmon see Oncorhynchus keta (chum salmon) Ci, definition, 6:242 Cichlid (Nannacara anomala), 2:456F Ciguatera fish poisoning, 4:432, 4:434T, 4:435T Circatidal vertical migration, 2:216 Circulation see Ocean circulation; see specific oceans/circulations/currents Circulation models biogeochemical/ecological models and, 4:93, 4:98–100 tomography and, 6:47 Circulation Obviation Retrofit Kit (CORK), 2:24–26, 2:31F, 2:43F, 2:44 Circulation patterns estuaries, 4:253 fiords, 2:353–358 Circulation proxies, 4:327T Circulation tracers, 4:106–107 Circumpolar Deep Water (CDW), 1:26, 1:27F, 1:178–179, 2:566, 4:127–128, 5:542, 6:297 Antarctic Coastal Current, 6:323 flow, 1:725–726, 1:725F Malvinas Current, 1:425 radiocarbon, 4:643–644 temperature–salinity characteristics, 6:294T, 6:297–298, 6:298, 6:298F water properties, 1:180F Weddell Gyre, 6:323 see also Lower Circumpolar Deep Water (LCDW); Upper Circumpolar Deep Water (UCDW) Cirripedia (barnacles), wave resistance, 1:332 Citandy, Indonesia dissolved loads, 4:759T river discharge, 4:757
CITES (Convention on International Trade in Endangered Species), 4:241–242 Ciutadella Harbor, Spain, rissaga, 5:349, 5:350 CIW see California Intermediate Water (CIW); Cretan Intermediate Water (CIW) Clades, 2:216 Claires (oyster fattening ponds), 4:281, 4:282F Clams, 2:58F acoustic scattering, 1:69 fisheries, seaduck interactions, 5:270–271 harvesting, 3:901 mariculture, 3:904 Italian market, 3:535 stock acquisition, 3:532 stock enhancement/ocean ranching, 4:146 see also Giant clam (Tridacna squamosa); Vesicomyid clams Clarion–Clipperton Zone, manganese nodules, 3:493, 3:494–495 Clarke–Bumpus net, 6:356–357, 6:358F ‘Classical limit,’ theories, 3:21 Classical sling psychrometer, 5:377–378 Classification/taxonomy (organisms) bacterioplankton, 1:269–271 beaked whales, 3:643 benthic organisms see Benthic organisms intertidal fishes, 3:280 meiobenthos, 3:726 phytobenthos see Phytobenthos radiolarians, 4:614–615 salmonids, 5:29 sirenians, 3:589, 3:589T, 3:608T, 5:436–437 see also specific fish/whales/organisms Clastic injections, 5:457F Clastic sediment, 5:463 Clasts, 5:460F brecciated, 5:463 see also Floating mud clasts Clathrates, 3:792 see also Methane hydrate Claude, G., 4:168, 4:169 Clausius–Clapeyron equation, 2:326–327 Clay(s), 1:266–268, 1:266 acoustics in marine sediments, 1:90F geoacoustic properties, 1:116T Clay minerals, 1:120–121, 1:563–571 autochthonous processes, 1:565–567 climate and, 1:563 coastal margins, 1:563 composition, 1:563 distribution, 1:563–565 ferriferous granules, 1:567 formation, 1:565–567 glaucony formation, 1:568F ocean margin sediments, 4:140–141 organic matter, 1:567–569 paleoenvironmental aspects, 1:569–570 climate, 1:569–570 currents, 1:570
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marine currents, 1:564–565 orbital correlation, 1:571T oxygen isotope ratios and, 1:570F Quaternary degradation, 1:568F tectonic activity, 1:565–566 time sensitivity, 1:569 river inputs, 1:627 in sedimentary sequences, 3:912 vertical profile, 1:566F see also Illite; Smectites Clay-oil flocculation, 4:192 Cleaner wrasse Labroides dimidiatus, aquarium mariculture, 3:528 Thalassoma bifasciatum, 2:423 Clear air turbulence (CAT), 2:614–615 CLE/CSV see Competitive ligand equilibration/adsorptive cathode stripping voltammetry CLIMAP project, 2:98, 2:99F, 2:108, 4:297 Climate change see Climate change effects on ocean gyre systems, 4:136–137 greenhouse see Greenhouse climates ocean modeling, 5:139 see also Climate models; Ocean climate models plankton and see Plankton and climate predictions, seasonal to interannual, 5:129–130 variability, millennial scale see millennial–scale climate variability warming, 5:86, 5:88–89 see also Climate change, abrupt; Global warming; Millennial-scale climate variability weather differences, 2:242 Climate: Long Range Investigation Mapping and Prediction (CLIMAP) project, 2:98, 2:99F, 2:108, 4:297 Climate change, 4:89 abrupt, 1:1–6 future risk, 1:5–6 mechanisms, 1:3–5 paleoclimatic data, 1:1–3 thresholds, 1:3 astronomical polarity timescale application, 3:30–31 Cenozoic, 1:502–513, 1:502 mechanisms, 1:511–512 climate variability, 4:461 coral-based paleoclimate research, 4:341–343, 4:343–345, 4:343F, 4:344F cyclic global, glacial cycles and sea level change, 3:50–51, 3:51F definition, 2:218 economics, 2:197 see also Economics of sea level rise effect on marine biodiversity, 2:146 effect on marine mammals, 2:218–221 analysis of the research, 2:219–220
Index animal/environment interactions, 2:218 classifying effects, 2:219 direct and indirect effects, 2:219 evidence, 2:219 lack/feebleness, 2:219 future work, 2:220 mammal resilience, 2:220 metapopulation structures, 2:220 risk-assessment processes, 2:220 habitat change factors, 2:219 normal environmental variation, 2:218–219 harmful algal blooms, 2:218–219 non-oscillatory climate change, 2:218 oscillatory climate change, 2:218 range retractions/population reductions, 2:218 effects on food webs, 2:379 fisheries concern, 2:503–504 gas hydrates and see Methane hydrate(s) ‘global thermometer,’ SST, 5:99 Holocene see Holocene, climate variability ice shelf stability, 3:211, 3:214–215 influence of primary production, 4:573–574 krill as indicator species, 3:356–357 methane hydrate reserves and, 3:792 ocean-driven, 3:125, 3:128–129 paleoceanography, 4:295, 4:299–300, 4:301 planktonic indicators, 4:455–456, 4:463F satellite oceanography, 5:76–77 seabird responses, 5:257–264 direct, 5:257, 5:258–259 California Current, 5:259–261, 5:260F, 5:261F Chukchi Sea, 5:258–259, 5:259F northern Bellinghausen Sea, 5:261, 5:261F Ross Sea, 5:261, 5:262F indirect, 5:257, 5:261–262 Benguela Current, 5:264 Bering Sea, 5:263 California Current, 5:262 central Pacific, 5:262 Chukchi Sea, 5:263–264 Gulf of Alaska, 5:263 North Atlantic, 5:264 Peru Current, 5:262–263, 5:263F prehistoric, 5:257–258 north-west Atlantic/Gulf of Mexico, 5:258 south-east Atlantic, 5:258 Southern Ocean, 5:257–258 storm surges, 5:539 upper ocean temperature and salinity and, 6:172–173 see also Carbon sequestration by direct injection; Economics of sea level rise; El Nin˜o Southern Oscillation (ENSO); Fisheries, and climate; Greenhouse climates; Greenhouse
gas; Plankton and climate; Sea level changes/variations Climate change forecast models, 5:99–101 Climate models climate change forecast, 5:99–101 fundamental methods, 5:133–140 subgrid-scale parametrization, 5:133–134 global see Global climate models (GCMs) greenhouse climate, 4:326–328 ground truthing of, 2:47–48 heat flux components, 2:608–609 in paleoceanography see Paleoceanography Climate prediction models, 5:129–130, 5:130 see also Data assimilation in models Climate research, 4:613–614 see also Plankton and climate Climate systems, 4:461, 4:461–462 components, 2:48F Earth, 2:47, 2:48F Climatic forcing, upwelling ecosystems see Upwelling ecosystems Climatic warming see Global warming; Climate, warming Clines, 2:216 Clinoptilite, 1:265–266 diagenetic reactions, 1:266T Clio pyrimidata (Pteropoda), 4:460 Closed form (analytic) solutions, coastal circulation models, 1:573 Closing cod-end systems, zooplankton sampling, 6:361, 6:363F Clostridium perfringens, sewage contamination, indicator/use, 6:274T Closures see Marine protected areas (MPAs) Cloud(s) contamination, infrared atmospheric corrected algorithms, SST measures, 5:93 cover, coral-based paleoclimate research, 4:339T, 4:340–341 movement, d18O values and, 1:503, 1:503F, 1:504F particulate matter and, 1:253 penetrated by satellite remote sensing, 5:103 satellite radiometry, 5:205 Cloud condensation nuclei (CCN), 3:401–403 Clouds and Earth’s Radiant Energy System (CERES) experiment, 5:205–206 Club finger coral (Stylophora pistillata), oil pollution effects, 1:673–674 Clupea harengus (Atlantic herring) see Atlantic herring (Clupea harengus) Clupea pallasii (Pacific herring), 4:364 Clupea sprattus (sprats), 4:366 Clupeoids acoustic scattering, 1:65
(c) 2011 Elsevier Inc. All Rights Reserved.
457
see also Herring (Clupea); Mackerel (Scomber scombrus) Cluster analysis, pollution, effects on marine communities, 4:536 Clustered seamounts, 5:292, 5:300 CMP see Common midpoint Cnidarians bioluminescence, 1:377T, 1:378 medusae, 3:10 CO2 see Carbon dioxide (CO2) Coagulation, particle, 4:330, 4:331F, 4:335–336 mechanisms, 4:332F, 4:335 sticking, 4:335 physical collision, 4:332F, 4:335 Brownian motion, 4:335 differential settlement, 4:332F diffusive capture, 4:332F, 4:335 filtration, 4:332F, 4:335 organism motility, 4:332F shear, 4:332F surface coagulation, 4:332F, 4:335 phytoplankton blooms, 4:334F, 4:336 rates, 4:335–336 theory, 4:335 see also Particle aggregation dynamics Coastal biome, 4:359, 4:361T, 4:362F boundary, 4:359 zooplankton community composition, 4:357T Coastal circulation, local vs remote, 1:572 Coastal circulation models, 1:572–580 applications, 1:575 coastal ecosystems, 1:576–577, 1:576F, 1:577F engineering, 1:575–576 Observational System Simulation Experiments, 1:578 operational forecast systems, 1:574F, 1:577–578, 1:578F, 1:579 sampling design, 1:578 sea level, 1:575, 1:575F Coastal Ocean Forecast System (COFS), 1:574F, 1:577–578, 1:578F computing capabilities affecting, 1:575, 1:578–579, 1:579 development, 1:573 domain, 1:572 equations and state variables, 1:572–575 analytic (closed form) solutions, 1:573 boundary conditions, 1:572, 1:579 higher-order discretization schemes, 1:573 horizontal discretization, 1:573, 1:579 initial conditions, 1:572 numerical approaches, 1:573, 1:579 vertical discretization, 1:573, 1:579 finite difference and finite element methods, 1:573, 1:574F future directions, 1:578–579 future roles, 1:579 horizontal two-dimensional, 1:575, 1:575–576 observational system advances affecting, 1:579
458
Index
Coastal circulation models (continued) process studies, 1:575 regional studies, 1:575 simulation models, as tools, 1:578–579 three-dimensional, 1:575 see also General circulation models (GCM); Heat flux; Momentum fluxes; Wind-driven circulation Coastal currents, 6:316 Norwegian Coastal Current, 4:792, 4:794F, 4:795 rotating gravity currents, 4:790–791, 4:792, 4:794 eddies, 4:791F, 4:795 Coastal ecosystems air–sea carbon flux, 4:260 application of coastal circulation models, 1:576–577 carbon flux to oceans, 4:260 chlorinated hydrocarbons, biogeochemical cycle, 1:558F eutrophication, 3:173, 3:174 material exchange processes, 4:252 polychlorinated biphenyls, 1:554 processes characterizing, 4:252–253 Coastal engineering, 1:585–586 beach nourishment, 1:587 description/purpose, 1:587 dune building, 1:587 profile changes, 1:587 scraping, 1:587 scraping effects, 1:587 effects, 1:585 groins/jetties, 1:586 descriptions and purposes, 1:586 downdrift beach loss, 1:586, 1:586F effect on deltas, 1:586 groin failure, 1:586 offshore breakwaters, 1:586–587 seawalls, 1:585–586, 1:585F beach degradation, 1:585–586, 1:585F descriptions, 1:585 effects, 1:585 policy issues, 1:586 purposes, 1:585 US sample, 1:586 see also Coastal topography impacted by humans Coastal environments biological productivity, 1:572 changes affecting fisheries, 1:572 diversity of marine species, 2:140–142 importance, 2:147 offshore extent, 1:572 Coastal erosion offshore dredging, implications of, 4:188 storm surges, 5:530 see also Erosion Coastal flooding, storm surges, 5:530, 5:532 warning system, 5:532, 5:536 Coastal inundation maps see Inundation maps Coastal jets, Baltic Sea circulation, 1:292, 1:292–293
Coastal mapping, airborne lidar see Aircraft for remote sensing Coastal margins groundwater flow, 3:89–90 water cycle, 3:89F Coastal morphology, storm surges, 5:531–532 Coastal ocean(s) atmospheric deposition, 1:239–240 metals, 1:239–240 chlorinated hydrocarbons, 1:555–561 components, 1:572 solid wall and open boundaries, 1:572, 1:579 as subset of global ocean basin, 1:572 topographic eddies, 6:63, 6:63F Coastal ocean dynamics application radar (CODAR), 4:483F Coastal Ocean Dynamics Experiment (CODE), 2:173–174 Coastal Ocean Forecast System (COFS), 1:574F, 1:577–578, 1:578F Coastal polynya, 1:418F Coastal processes, small-scale patchiness models, 5:481–485 Coastal reefs, 3:444–445 Coastal region/seas anoxia, 3:174 atmospheric deposition metals, 1:239–240 nitrogen species, 1:240–241 synthetic organic compounds, 1:241–242 eutrophication see Eutrophication hypoxia, 3:173, 3:174–175 metal pollution, 3:768F, 3:769 weather forecasting for, satellite remote sensing, 5:112–113 Coastal state waters, dumping prohibited, environmental protection and Law of the Sea, 3:440 Coastal topography impacted by humans, 1:581–590 beaches, processes affecting, 1:305–315 see also Beach(es) building/infrastructure construction, 1:583 effects, 1:583 excavation effects, 1:583 plugging dune gaps, 1:583 coastal engineering see Coastal engineering construction projects, 1:584–585 effects on tidal inlets, 1:584–585 examples, 1:584 construction site modifications, 1:583 dune notching, 1:583 effects, 1:583 dune building, 1:581–582 dune removal, 1:581 effects on whole-island system, 1:582 hard shoreline stabilization, 1:583 method and impacts, 1:583 human trait for change, 1:581 nonessential development, 1:581 rapid population increase, 1:581, 1:582F
(c) 2011 Elsevier Inc. All Rights Reserved.
sand mining, 1:588, 1:588F inshore-sourced replenishment, 1:589 offshore-sourced replenishment, 1:588–589 sand supply, 1:581–583, 1:584F, 1:587–589 dune modification, 1:587–588 inlet modification, 1:588 modification impacts, 1:587 upriver dam construction, 1:588 soft shoreline stabilization, 1:583–584 method and impacts, 1:584 types of modifications, 1:582–583 see also Beach(es),microbial contamination; Coastal zone management; Economics of sea level rise Coastal Transition Zone (California), simulations, food web and biooptical model, 5:481–485, 5:485F Coastal trapped waves, 1:591–598 alongshore flow, 1:596, 1:597 energy flux conservation, 1:596 hindcast, 1:597F scattering, 1:596 analysis parameters, 1:591 continental shelf waves see Continental shelf waves cross-shelf surface transport, 1:596 decay, 1:594–595 edge waves see Edge waves forwards propagation, 1:591, 1:591–592, 1:592, 1:592F definition, 1:597–598 density stratification, 1:593 ridge shelf geometry, 1:593 wind stress wave generation, 1:596 frictional decay, 1:594–595, 1:595, 1:597 generation, 1:596–597 identification, 1:591 imperfect trapping, 1:593F, 1:594 Kelvin waves see Kelvin waves mean flows, 1:595 baroclinic instability, 1:595 barotropic instability, 1:595 non-linear effects, 1:595 non-linear effects, 1:595–596 dispersion, 1:595 steepening, 1:595 wind forcing, 1:595 poleward-propagating waves, 1:596 Red Sea circulation, 4:675 scattering, 1:596 shelf geometry, 1:592–593, 1:593, 1:596, 1:597–598 broad shelf, 1:593, 1:596–597 depth profile, 1:592 islands, 1:592–593 ridges, 1:593 seamounts, 1:593 slope, 1:593–594 straight, 1:591–592, 1:593 trenches, 1:593 storm surges, 5:532 stratification see Stratification
Index topographic wave mechanism, 1:591–592, 1:592F wind forcing, 1:592, 1:594F, 1:595, 1:596 broad shelf, 1:596–597 longshore wind stress, 1:596 see also Coastal circulation models; Internal tides; Internal wave(s); Regional models; Rossby waves; Storm surges; Tide(s); Vortical modes; Wind-driven circulation Coastal upwelling centers, productivity reconstruction, 5:340–342, 5:340F plankton patchiness and, 5:481 see also Upwelling Coastal waters anthropogenic trace metal enhancements, 1:200 chlorinated hydrocarbons, 1:557 classification, 4:732, 4:733F colored dissolved organic matter influence, 4:415 optical properties, 4:732–734 bottom and, 4:734 polychlorinated biphenyls, 1:554 trace element concentrations, 6:76 see also Continental margins Coastal wind vectors, from calibrated SAR images, 5:103 Coastal zone(s) carbon dioxide flux, atmospheric, 3:400F land-sea fluxes, 3:396–399 bioessential elements, 3:397–399 global warming and, 3:399–401 nutrient element fluxes, 3:396–397 Coastal Zone Color Scanner (CZCS), 1:365, 5:114, 5:118T biomass in Mid-Atlantic Bight, 4:727, 4:728F sensor calibration stability, 5:118–119 Coastal zone management, 1:599–605 challenges, 1:599 coastal zone importance, 1:599 Coastal Zone Management Act 1972 (USA), 1:599–600 see also Coastal Zone Management Act 1972 (USA) crisis indicators, 1:603 rising coastal populations, 1:603 development of legislation, 1:599 evolution/development, 1:599–600 future directions, 1:603 growth of ICM initiatives, 1:603 integration efforts, 1:603–604 possible futures, 1:604 adapting mosaic, 1:604 consequences of ICM choices, 1:604 global orchestration, 1:604 Millenium Ecosystem Assessment, 1:604 order from strength, 1:604 technogarden, 1:604
integrated see Integrated coastal management (ICM) regional ICM initiatives, 1:601–603 1975 Mediterranean Action Plan, 1:602 European Union example, 1:602 regional ocean initiatives, 1:601–602, 1:602T strengths and weaknesses, 1:603 sustainable development and, 1:600 distribution of benefits, 1:600 elements of sustainability, 1:600 impact on environment/natural resources, 1:600 impact on quality of human life, 1:600 UN’s Our common future report (Brundtland report), 1:600 threats to sustainability, 1:599 see also Coastal topography impacted by humans; Economics of sea level rise Coastal Zone Management Act 1972 (USA), 1:599–600 aims, 1:599 North Carolina example, 1:599–600 Coast Guard’s International Ice Patrol, USA, 3:183–184, 3:184F CoAxial Segment, Juan de Fuca ridge, 3:845 Cobalt biological uptake, phytoplankton, 6:80, 6:81F concentration N. Atlantic and N. Pacific waters, 6:101T phytoplankton, 6:76T seawater, 6:76, 6:76T, 6:82F ferromanganese deposits, 1:260–261 distribution, 1:261, 1:262F inorganic speciation, 6:103 ligands, biogenic, 6:84 metabolic functions, 6:83 organic complexation, 6:106 sensors, absorptiometric, 1:13 see also Trace element(s) Coccolithophores, 1:606–614, 4:460, 4:461F biogeochemical impacts, 1:611–612 atmospheric CO2 levels, 1:611–612 carbon assimilation, 1:611 coccolith fluxes, 1:612 dissolution of coccoliths, 1:611 light scattering, 1:612 production of dimethylsulfoniopropionate (DMSP), 1:612 blooms, 1:607, 1:608F, 4:739 ocean color and, 5:125–126, 5:125F Calcidiscus quadriperforatus, 1:606F, 1:607F calcification, 1:610 calcite, 1:610 carbon uptake, 1:610 physiological mechanisms, 1:610 cell wall, 4:679 coccoliths, 1:609 embedded coccoliths, 1:611F
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function, 1:609 numbers, 1:609 scale, 1:609 types, 1:609 Coccolithus pelagicus, 1:606F combination coccosphere, 1:607F definition and description, 1:606 Discosphaera tubifera, 1:606F early studies, 1:606 ecological niches, 1:610–611 variability between species, 1:610–611 electron microscope images, 1:606F Emiliania huxleyi, 1:606F blooms, 1:607, 1:608F, 1:611 coccolith numbers, 1:609 genome, 1:610 research, 1:611 Florisphaera profunda, 1:606F, 1:609 fossil record, 1:612–613 calcareous nanoplankton, 1:612 chalk deposits, 1:612 Cretaceous peak, 1:612 K/T boundary data, 1:612 survival/non-survival during past catastrophes, 1:613 use in studying past environments, 1:612–613 future research, 1:613 acidification, 1:613 linking current and ancient records, 1:613 study of calcification rates, 1:613 Gephyrocapsa oceanica, 1:606F life cycle, 1:609–610 diploid and haploid stages, 1:609–610 gametes, 1:609–610 genome, 1:610 life spans, 1:610 sexual and asexual reproduction, 1:609–610 species and distribution, 1:606–609 concentrations, 1:609 difficulties in determining species numbers, 1:607 distribution, 1:607 species numbers, 1:607 see also Phytoplankton Coccolithophorids, 4:516 calcium carbonate production, 1:445 carbonate oozes, 1:446F Coccoliths, 1:371–372 Coccolithus pelagicus (coccolithophore), 1:606F Cocos-Nazca Ridge see Cocos-Nazca spreading center; Galapagos Spreading Center Cocos-Nazca spreading center propagating rifts and microplates, 4:597–600, 4:599F lithosphere characteristics, 4:597–600 see also Galapagos Spreading Center Cod (Gadus), 1:63, 4:456 Atlantic see Atlantic cod (Gadus morhua) biomass
460
Index
Cod (Gadus) (continued) Baltic Sea, 2:505–506, 2:507F north-west Atlantic, 2:505–506, 2:506F, 2:510 Pacific, population, El Nin˜o and, 4:704 CODAR see Coastal ocean dynamics application radar CODE (Coastal Ocean Dynamics Experiment), 2:173–174 Code of Conduct for Responsible Fishing, United Nations Committee on Fisheries, 2:515, 2:520 COFS (Coastal Ocean Forecast System), 1:574F, 1:577–578, 1:578F Coherent Doppler velocity profiler (CDVP), 1:39, 1:39F, 1:42F, 1:39, 1:39F, 1:42 single-axis vs. three-axis, 1:50 turbulent flow visualization, 1:43F Coho salmon see Oncorhynchus kisutch (coho salmon) Cold current rings (CCR), hurricane Ivan and, 6:202 Cold dense polar water, 4:126, 4:126–127, 4:130, 4:130–131 Colder equatorward flow, 4:126 Cold fresh water, 4:128, 4:129F, 4:130 Cold-water coral reefs, 1:615–625 cold-water corals, 1:615–616 species and distribution, 1:615–616 description, 1:615 Enallopsammia profunda, 1:615–616 feeding, growth and reproduction, 1:618–619 factors required for growth, 1:618 reproductive ecology, 1:618–619 understanding of cold-water coral growth, 1:618 future research, 1:624 genetic diversity, 1:619–620 molecular technologies, 1:619–620 Goniocorella dumosa, 1:615–616 habitats and biodiversity, 1:620–621 animal communities, 1:620, 1:620F fish habitats, 1:621 functional relationships between communities, 1:620–621 parasitism of corals, 1:621 sampling methodologies, 1:621 structural complexity, 1:620 historical background, 1:615 knowledge and research, 1:615 submersible research, 1:616F Lophelia pertusa, 1:615–616, 1:615F, 1:616F, 1:617F, 1:618 associated with Eunice norvegica worm, 1:620–621 growth on oil platforms, 1:623 molecular research, 1:619–620 parasites, 1:621 reproductive ecology, 1:618–619, 1:619F Madrepora oculata, 1:615–616, 1:618, 1:619–620, 1:620–621 mapping/photographing, 1:617F new research technologies
benthic landers, 1:621, 1:621F molecular technologies, 1:619–620 Oculina varicosa, 1:615–616 reef distribution and development, 1:616–618 complexity, 1:616, 1:618F distribution factors, 1:616–617 global distribution, 1:619F hydraulic theory, 1:617 limited understanding, 1:617–618 longevity, 1:616 Solenosmilia variabilis, 1:615–616 threats, 1:622–624 acidification of the oceans, 1:624 deep seabed mining, 1:624 fisheries, 1:622, 1:624F oil exploration, 1:622 sediment loads and, 1:623 timescales and archives, 1:621–622 environmental archives, 1:622, 1:623F global circulation patterns and, 1:622 reef ages, 1:622 see also Artificial reefs; Coral reef(s) Collective action, marine policy, 3:664–665 Collision coasts, 3:33 Colloidal particles, iron, 6:76 Colloids definition, 4:337 see also Particle aggregation dynamics Colombia El Nin˜o events and, 2:228 water, microbiological quality, 6:272T Color icebergs, 3:189 oceans see Ocean color phytoplankton see Phytoplankton, color Colored dissolved organic matter (CDOM), 4:379, 4:624 photochemical production, 4:414, 4:416F absorbed photons, effects of, 4:417 absorption spectra, 4:414, 4:415F photolysis, 4:417–418 spectral absorption, 6:110, 6:110F see also Gelbstoff Columbia river, plume, California Current, 1:463 Column modeling methods, upper ocean mixing, 6:191 Combined cycle gas turbine (CCGT), 6:10, 6:17 Combined sewer overflows (CSOs), 6:269 Comb jellies see Ctenophores Combustion, particulate emission, 1:248 nitrogen, 1:255T COMCOT see Cornell Multi-grid Coupled Tsunami Model Cometary impacts, sources of water, origin of oceans, 4:263 Commercial fisheries see Fisheries Commercial whaling baleen whales, 1:284–285, 3:637–638 decline of, 3:638 history, 1:284–285, 3:637
(c) 2011 Elsevier Inc. All Rights Reserved.
International Whaling Commission moratorium, 3:638 modern, 3:637–638 by aboriginal hunters, 3:638 sperm whale, 3:637–638 Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR), 4:232, 5:513 catch documentation scheme, 5:517 Ecosystem Monitoring Program, 5:519 establishment, reasons for, 5:513 harvesting requirements, 5:513 Southern Ocean fisheries management regime, 5:518 statistical areas, 5:514, 5:514F Commission for the Conservation of Southern Bluefin Tuna, 4:242 Common cormorant, 4:372F, 4:374, 4:374F see also Cormorants Common diving petrel, 4:591F, 5:252 see also Procellariiformes (petrels) Common dolphins (Delphinus spp.), 2:154F Common midpoint (CMP) records, 5:351 Common mummichog (Fundulus heteroclitus), 5:45 Common murre see Murre(s) Common reed (Phragmites australis), 5:46–47 Common scoter (Melanitta nigra) fisheries interactions, 5:270–271 see also Seabird(s) Common skate (Raia batis), demersal fishing impact, 2:92 Common tern, 3:423F see also Sternidae (terns) Communications, internal/external, oceanographic research vessels, 5:412 Compact Airborne Spectographic Imager (CASI), 1:144 Compasses, 4:478 Compensation arrangements, Salmo salar (Atlantic salmon) fisheries management, 5:8 Competition baleen whales (Mysticeti) species, 1:286–287 beaked whales (Ziphiidae) species, 3:646 fish feeding see Fish feeding and foraging ocean zoning conflicts and, 4:174 phytoplankton see Phytoplankton competition price, liner conferences, 5:406 resources, marine biotechnology policy issues, 3:564 salt marsh vegetation, 5:41 seabird foraging see Seabird(s) space for mariculture of Mediterranean species, 3:533 Competitive exclusion, 3:650 Competitive ligand equilibration/ adsorptive cathode stripping voltammetry (CLE/CSV), 6:104T
Index Competitors, oyster farming, risks to, 4:283 Complexity, biogeochemical models, 4:93, 4:94F, 4:95F Complex refractive index (m), electromagnetic wave propagation, 2:251–252 Compliance monitoring, application of nephelometry, 6:117T Composition of oceans, 4:263–264 salinity, 4:263–264 Compressee, floats, 2:177 Compressibility (of seawater) coefficient, 4:25 global energy budget and, 2:263 Compressional waves, acoustics in marine sediments, 1:79–80, 1:79, 1:79F, 1:83, 1:87–88 arrival times, 1:80, 1:80F, 1:88 first kind, 1:78 refracted, 1:87–88, 1:88, 1:88F second kind, 1:78 velocity, 1:78T, 1:80, 1:81, 1:82, 1:86, 1:88, 1:89, 1:89F and porosity, 1:81, 1:82F velocity-depth curve, 1:88–89, 1:89F see also Acoustic remote sensing Computation time, biogeochemical models, 4:95F Computer control, remotely operated vehicles (ROVs), 4:743, 4:744–745 Computer hardware, autonomous underwater vehicles (AUV), 4:477 Computer modeling, 5:86 see also Models/modeling Computers growth in power, general circulation model and, 3:21 power, ocean modeling and, 5:133, 5:134–135 COMRA see China Ocean Mineral Resources R&D Association Concentration-based model, definition, 4:103 Concentric banding, manganese nodules, 3:489, 3:489F Concholepas concholepas (loco), 4:768 Condensation, ocean thermal energy conversion, 4:171 Conductivity (sea water), 2:247–248 determining factors, 2:248–249, 2:249F ion concentrations, 2:248–249, 2:249F ion mobility, 2:249, 2:249F temperature, 2:249, 2:249F mechanism, 2:248, 2:248F metals vs., 2:247 ratio see Conductivity ratio (R) sensors, 6:153 source of ions, 2:247–248 see also Electrical properties of sea water Conductivity (electrical), measurement, 1:714–716, 1:715 digital, 1:715 salinity and, 1:716
Conductivity probe see Microconductivity probe Conductivity ratio (R), 2:249, 2:250 definition, 2:250 definition of salinity, 2:247, 2:249–251, 2:249F pressure and, 2:250 temperature and, 2:250 Conductivity-temperature-depth (CTD) package, 3:59 Conductivity-temperature-depth (CTD) profilers, 1:708–717, 1:713, 1:715F, 6:165–166 AUVs and, 6:165–166 conductivity measurement, 1:714–716 conductivity cell, 1:714, 1:715F extended deployment, 1:716 lowering speeds, 1:714 pressure measurement, 1:713–714 salinity measurement, 1:711–713, 1:713F calibration of salinometer, 1:713F resolution, 1:713 seismic reflection profiling and, 5:354, 5:354–358, 5:354F, 5:357F temperature measurement, 1:708–711 see also Expendable conductivitytemperature-depth profilers Conductivity-temperature-depth (CTD) recorders, towed vehicles, 6:68F, 6:72–73, 6:73F Cone anemometer, 5:385 Confined aquifer, definition, 5:557 Confined drifts see Deep-sea sediment drifts Congelation ice, 5:173, 5:547 Conger eel (Conger conger), 2:461 Congo River discharge, 4:755T productivity reconstruction, 5:340, 5:340F Conservation, 3:560–561 by-catch issues, 4:241–242 definition, 5:223 environmental see Environmental conservation Law of the Sea, underlying principles, 3:433 duty of states, 3:433 marine mammals, 3:613–614 see also specific species marine protected areas see Marine protected areas (MPAs) satellite remote imaging and, 4:739 seabird, 5:220–226 biology and, 5:220 methods, 5:223–226, 5:226 education, 5:225 elimination of predators, 5:224 fishing management, 5:223, 5:224 habitat creation/modification, 5:223 management of human disturbance, 5:225 management of hunting, 5:226 pollution reduction, 5:224
(c) 2011 Elsevier Inc. All Rights Reserved.
461
see also specific species sperm and beaked whales, 3:649–650 see also Ocean zoning Conservative elements (sea water), 1:626–629 major, 2:255 concentrations, 1:627T salinity and, 1:626, 1:628 determinations, 1:626 deviations hot vents and, 1:628, 1:628F marine aerosols and, 1:628 plankton production and, 1:626–627 river inputs and, 1:627–628 minor, 1:628, 2:255 see also Elemental distribution; Trace element(s); specific constituents Conservative tracers, 1:683 Consolidated sulfides, 3:890 Constant stress layer flow, 1:433–434 Construction activities coastal/beaches see Coastal topography impacted by humans corals, human disturbance/destruction of, 1:675 Container ports terminals, development, 5:407 top (by volume), 5:407, 5:408T Container ships, 5:401–402, 5:403T, 5:404, 5:406T charter rates, 5:404T Container terminals, improved/future improvements, 5:408 Contaminants defined, 4:526 industrial solids, 4:522–523 oil and human sewage, 3:67 radioactive waste and metals, 3:67 see also Antifouling materials; Pollutants Contiguous zone, Law of the Sea jurisdiction, 3:434 Continental boundaries, internal waves and, 5:359, 5:359F Continental breakup, sea level rise and, 5:187, 5:188F, 5:189 Continental crust, trace metal isotope ratios, 3:457T Continental drift, magnetic anomaly and, 3:483–484 Continental flood basalts, 3:218, 3:219–222, 3:220T, 3:223F, 3:225 see also Large igneous provinces (LIPs) Continental hyposography, estimation of long-term sea level changes, 5:189 Continental landmass elevation, and monsoon generation, 3:911 monsoon indicators, 3:914 topography/vegetation, and monsoon generation, 3:911 Continental margins, 4:254–260 Arctic, primary production, 4:259T biogeochemical modeling, 4:100–102 convergent, 4:139–140, 4:140F definition, 5:463
462
Index
Continental margins (continued) divergent, 4:139, 4:140F ecosystem, 4:254–260 islands and, 4:257–258 magnetic anomalies, 3:482–483 overall area and type, 4:256–257, 4:256T oversteepening, 4:142 sediment transport process initiation, 5:450 primary production, 4:258, 4:259T sediment, biogenic silica burial, 3:681T, 3:682, 3:683 sediment sequences, 4:144F sediment transport mechanisms, 4:143F shelf-dominated, 4:255–256 ecosystems, 4:257F, 4:258T slides see Slides slope-dominated see Slope-dominated continental margins transport processes, 4:253F see also Coastal waters Continental plates see Interplate fault Continental runoff, 6:120 Continental shelf, 1:356 Antarctic bottom water, 1:420 continental shelf waves see Continental shelf waves distribution and characteristics, 3:660–661 diversity of species, 2:142 geologically defined, 3:435 geometry, coastal trapped waves see Coastal trapped waves interfacial waves, 3:271–272 internal tides, 3:259, 3:261, 3:262F, 3:263, 6:38 internal waves, 3:271–272 Law of the Sea jurisdiction, 3:435 mineral resources see Mineral resources plankton communities see Plankton communities sampling station, 3:445–446 sediment transport processes, 4:142F sediment volumes, 4:138T seiches, 5:346–347 tides, 6:35–36, 6:37, 6:37–38, 6:38 unit areas, demersal fisheries, 2:94, 2:94F width, 3:397 see also Continental slope; Shelf break Continental shelf waves, 1:591–592 dispersion, 1:593F diurnal tidal currents, 1:596–597 frontal trapped, 1:595 mean flow, effect of, 1:595 rotating gravity currents, 4:794F, 4:795 storm surges, 5:532 stratification, 1:593–594 wave speeds, 1:592 wind forcing, 1:592, 1:594F Continental slope, 4:127, 4:127–128 Black Sea, 1:409–410 sediment volumes, 4:138T see also Coastal zone; Continental margins; Continental shelf
Continental topography, map, 3:867, 3:867F Continuous line bucket (CLB) system, 3:892F, 3:894–895 Continuous Plankton Recorder (CPR) survey, 1:630–639, 1:630 atlas, 1:633 database, 1:631–632 future directions, 1:638–639 history, 1:630–632, 1:631F methods, 1:632–633 instrumentation, 1:631F, 1:633, 6:357T, 6:359–361, 6:360F early, 1:630, 1:631F open access data policy, 1:631 results/data applications, 1:633, 1:639 biodiversity, 1:636–637, 1:637F Calanus and North Atlantic Oscillation, 1:634–635, 1:636F exceptional events, 1:638–639 Gulf Stream North Wall index and copepod numbers, 1:636, 1:637F harmful algal blooms, 1:637–638, 1:638F herring, 1:633–634, 1:635F kittiwake breeding success, 1:633–634, 1:635F marine plankton biogeography, 1:633, 1:634F nonindigenous species, 1:637–638 North Sea ecosystem regime shift, 1:635–636, 1:636F phytoplankton, 1:633–634, 1:635F weather, 1:633–634, 1:635F zooplankton, 1:633–634, 1:635F routes, 1:630, 1:632F see also Phytoplankton, color; Plankton Continuous stratification, 3:374–376, 3:375F Richardson number flux, 3:375–376 Continuous-time structured population models, 4:548 applications, 4:548 McKendrick–von Foerster equation, 4:548 von Foerster equation, 4:549 see also Population dynamic models Continuous underway fish egg sampling system (CUFES), 6:368 Continuous wavelet transformation, regime shift analysis, 4:720 Contorted bedding, 5:463 Contour currents see Bottom currents Contour-following bottom currents see Bottom currents, contour-following Contourite(s), 2:80, 5:448F calcareous and siliceous biogenic, 2:86 drifts see Deep-sea sediment drifts gravel-rich, 2:85–86 manganiferous, 2:86 muddy, 2:85 sandy, 2:85 sequences and current velocity, 2:88–89 biogenic contourites, 2:89 composite or partial sequences, 2:88, 2:88F
(c) 2011 Elsevier Inc. All Rights Reserved.
intense bottom currents, 2:88–89 paleocirculation changes, 2:89 see also Sea level changes/variations shale-clast or shale-clip layers, 2:86 silty, 2:85 see also Deep-sea sediment drifts Contourite sediment facies, 2:80, 2:85 bioturbational mottling, 2:85 bottom-current influence, 2:83 bottom-current reworked turbidities, 2:86–88 calcareous and siliceous biogenic contourites, 2:86 different contourite facies, 2:85, 2:86F, 2:87F gravel lags and pavements, 2:85–86 gravel-rich contourites, 2:85–86 manganiferous contourites, 2:86 muddy contourites, 2:85 sandy contourites, 2:85 shale-clast or shale-clip layers, 2:86 silty contourites, 2:85 Contourite sheet drifts see Deep-sea sediment drifts Contranatant migration, 2:216 Controlled Ecosystem Pollution Experiment (CEPEX), 3:734, 3:735F, 3:736F Controlled flux technique (CFT), 1:153–155, 1:155F Control systems, fishery management see Fishery management Control theory, data assimilation in models, 2:7 Convection deep see Deep convection double-diffusive see Double-diffusive convection eddy, formation of, 3:762 general circulation models (GCM), 3:22 oceanic, one-dimensional models, 4:214 open see Open ocean convection penetrative see Penetrative convection small-scale, data assimilation models, 2:10–11 subpolar regions, 5:130 thermal see Thermal convection thermocapillary, 4:218 thermohaline see Thermohaline convection tomography, 6:49–50 under-ice boundary layer, 6:161–162 upper ocean see Upper ocean see also Ocean convection plumes Convection cells, 4:218–219 Convective adjustment, 2:10–11 Convective chimney, 6:49–50 Greenland Sea, 6:49F, 6:50F ocean subduction, 4:164–165, 4:165, 4:165F Convective feedback, 1:3 Convective mixing, 6:231 Convective overturning, 3:255 Convective schemes, 2:11 Convective turbulence, 6:22
Index Convention for the Conservation of Antarctic Seals, 5:513 Convention for the Conservation of Salmon in the North Atlantic Ocean, 5:2, 5:6 Convention on International Trade in Endangered Species (CITES), 4:241–242 Convention on the Continental Shelf, mineral resources, 3:437 Convergent continental margins, 4:139–140, 4:140F Conveyor belt see Atlantic thermohaline circulation Conveyor-belt feeding, 1:395 Cook, Captain James, 3:121, 5:410 on East Australian Current, 2:187 Cooling, condition, coastal circulation models, 1:572 Cooling phase – deep water formation, 4:126–128 Cooling waters, planktonic organisms, effect on, 6:12–13 Cool skin, open ocean convection, 4:222 gas exchange, 4:222–223 sea surface temperature (SST), 4:222 temperature jump, 4:222 Coomassie stained particles (CSP), 4:332–333 Coordinated East Arctic Experiment (CEAREX), 1:92–93 Copenhagen standard seawater, 1:712 Copepod(s), 1:640–650, 4:455 abundance, Gulf Stream North Wall index and, 1:636, 1:637F Acartia spp., 3:658 Acartia tonsa, 4:440, 4:441F acoustic scattering, 1:67–68 Alaskan Gyre, 3:661 behavior, 1:647–648 diurnal vertical migration, 1:647–648, 1:648F factors influencing, 1:648 sensory mechanisms, 1:648 swimming, 1:648 nauplii, 1:648 speeds, 1:648 swimming-feeding interdependency, 1:648 biogeochemical role, 1:649–650 production of fecal pellets, 1:650 bioluminescence, 1:376–378, 1:648–649 calanoid, biodiversity, 1:636–637, 1:637F Calanoides carinatus, 1:649 Calanus finmarchicus, 1:640, 1:642F, 1:648, 1:649F, 2:363–364 see also Calanus finmarchicus (zooplankton) Chiridius armatus, 2:363 continental shelves, 3:660 distribution and habitats, 1:642–644 hyperbenthos, 1:643–644 marine caves, 1:643–644 marine sediments, 1:643 most abundant areas, 1:643
Pacific Ocean abundances, 1:645F parasites on other animals, 1:643 under polar ice, 1:645 sea surface, 1:645 see also Upwelling ecosystems diversity, 1:640, 3:730 escape responses, 5:489 estuaries, 3:658 life stages concentrations, 3:658 persistence, 3:658–660 feeding, 1:644–645 appendages, 1:645 behavior, 1:645 feeding rate, 1:645 food, 1:645 rate, 1:646F food source for krill, 3:355 growth and development, 1:645–646 egg development, 1:646 growth rates, 1:646–647, 1:646F molting, 1:645–646 nauplii, 1:644F nauplii and copepodites, 1:646 importance, 1:640 Lepeophtheirus salmonis (salmon louse), 1:650 Lernaeocera spp., 1:650 life histories, 1:648–649 bathypelagic species, 1:649 diapause, 1:649, 1:649F variations by habitat, 1:649 mating behavior, 5:491, 5:492F mesocosms use in research, 3:655 metabolism, 1:646–647 enzymatic activity, 1:647 excretion, 1:647 respiration, 1:647 morphology, 1:640–642 appendages, 1:644F body forms Calanoida, 1:641F Cyclopoida, 1:642F body morphology, 1:640–642 body sizes, 1:640 early life stages, 1:642–643 external anatomy, 1:643F internal anatomy, 1:643F maxilla, 1:645F Myticola intestinalis, 1:650 Neocalanus plumchrus, 3:661 Oithona spp., 3:661, 3:662 Peru-Chile Current System (PCCS), 4:389–390 as pests, 1:649 aquaculture and fisheries, 1:650 phenology changes, 4:458 population distributions, Lagrangian simulation, 3:392–393, 3:392F population interactions, models, 4:554 predation by higher trophic animals, 3:730 prosome and oil sac, 1:68F reproduction, 1:647 diapause eggs, 1:647 fecundity and spawning, 1:647 mating behavior, 1:647, 1:647F
(c) 2011 Elsevier Inc. All Rights Reserved.
463
roles in ecosystem, 1:650 control of phytoplankton, 1:650 fisheries, 1:650 food for other species, 1:650 nutrient recycling, 1:650 Southern Ocean food web, 4:518 subtropical gyres, 3:661–662 taxonomy, 1:640 orders included, 1:640 turbulence regime preferences, 5:491 Copiotrophs, 1:272 Copper (Cu) anthropogenic, 1:549 atmospheric deposition, 1:254T chemical speciation in seawater, 6:79 in coastal waters, 1:200 concentration N. Atlantic and N. Pacific waters, 6:101T in phytoplankton, 6:76T in seawater, 6:76, 6:76T depth profiles, 6:77F ferromanganese deposits, 1:260–261 nickel and, 1:262F global atmosphere, emissions to, 1:242T ligands, biogenic, 6:84 manganese nodules, 3:492, 3:493F, 3:494, 3:495 metabolic functions, 6:83 North Sea, direct atmospheric deposition, 1:240F organic complexes, 6:104 depth profile, 6:105F ionogenic, 6:106–107 pollution anthropogenic and natural sources, 3:769T enrichment factor, 3:773T seabirds as indicators, 5:275, 5:276 redox chemistry, 6:79 refinery, 3:897–898 riverine flux, 1:254T river sediment load/yield, 4:757T sensors, absorptiometric, 1:13 speciation, analytical techniques, 6:104T toxicity reduction, aquarium fish mariculture, 3:528 use in antifouling compounds, 1:207–208 see also Trace element(s) Copper refinery, 3:897–898 Coral(s), 3:444–445 biology, 4:338 animal–zooxanthellae symbiosis, 4:338–339 general, 4:338, 4:338F polyp, 4:338, 4:338F reproduction, 4:338 skeleton, 4:338F, 4:339 deposition, 4:339 high-density bands, 4:339 low-density bands, 4:339 blast fishing impact, 1:652–653, 1:672, 2:205
464
Index
Coral(s) (continued) bleaching satellite remote sensing of sea surface temperatures, 5:99 see also Coral reef(s) as climate proxy recorders, 4:338 see also Coral-based paleoclimate research cold-water, 1:615–616 species and distribution, 1:615–616 deep-sea, 4:345 deposition rates, 1:671 feeding methods, 1:671 fluorescence, 2:582 fossil, 4:345 heterotrophy, 4:338–339, 4:340–341 human disturbance/destruction, 1:671–677 collection, 1:671–672 construction activity effects, 1:675 discharge contaminants, 1:671, 1:673–674 fishing-related, 1:652–653, 1:672–673, 2:205 future issues/pressures, 1:677 indirect effects, 1:676–677 port activities, 1:675, 1:675–676 recreation-related, 1:675 shipping activities, 1:675–676 solid waste dumping, 1:674–675 war-related activities, 1:676 lead in, 1:197, 1:199F parasitism of, 1:621 photosynthesis, 4:338–339, 4:340–341 zooxanthellae, symbiotic relationship, 1:671 Coral-based paleoclimate research, 4:338–347, 4:341 deep-sea corals, 4:345 fossil corals, 4:345 future directions, 4:346 reconstruction of environmental variables, 4:339–340, 4:339T cloud cover, 4:339T, 4:340–341 from fluorescence patterns, 4:339T, 4:341 from growth records, 4:339, 4:339T from isotopes, 4:339–340, 4:339T see also specific isotopic ratios methods, 4:339–340, 4:340F improved, 4:346 pH, 4:339T, 4:341 river outflow, 4:339T, 4:341 salinity, 4:339T, 4:340 temperature, 4:339T, 4:340 from trace and minor elements, 4:339–340, 4:339T upwelling, 4:339T, 4:340–341 records, 4:341 Galapagos coral, 4:341–342, 4:343F interannual-to-decadal variation in climate and ENSO, 4:341–343, 4:343F, 4:344F long-term trends, 4:343–345, 4:344F seasonal variation in, 4:341 sea level rise data, 5:185
sites of, 4:338F, 4:341 see also El Nin˜o Southern Oscillation (ENSO) Coral reef(s), 1:660–670 aquaria/species see Coral reef aquaria artificial see Artificial reefs barrier, geomorphology, 3:34, 3:34F, 3:37 biodiversity, 2:142 biogeography, 1:667–668 continental drift, 1:660, 1:668 diversity patterns, 1:668F high diversity areas, 1:667 low diversity areas, 1:668 research needed, 1:668 speciation rates, 1:668 biology, 1:667–668 bleaching, 2:146 cold-water see Cold-water coral reefs definitions, 1:660 disturbances, management, 1:669 bleaching, 1:669 see also Coral(s), bleaching crown-of-thorns starfish, 1:669 frequency, 1:669 overfishing, 1:669 pollution, 1:669 ecosystem health, 1:668–669 reef interconnectivity, 1:669 movement, 1:669 pelagic life stages, 1:669 resilience, 1:660, 1:668–669 ecological resistance/resilience, 1:668 human impacts, 1:668–669 possible age influence, 1:668 fish see Coral reef fish fisheries, impacts marine biodiversity, 2:145 marine habitats, 2:145 general information, 1:660–662 geology, 1:664–665 calcification, 1:665 influence of CO2 levels, 1:665 production of CaCO3 and HCO-3 ions, 1:665 reaction of CaCO3, CO2 and water, 1:665 zooxanthellae, 1:665 oil exploration, 1:667 ancient reefs, 1:667 modern reefs, 1:667 porosity of reefs, 1:667 paleoecology, 1:665–666 evolution/history, 1:665–666, 1:665F plate tectonics, 1:666, 1:666F geomorphology, 1:666–667, 3:36–37 atoll formation, 1:666–667, 1:666F Darwin, Charles, 3:34, 3:34F, 3:37 event/geological timescales, 3:37 evolutionary sequence, 3:34F, 3:37 factors influencing shape, 1:667 sea level changes, 1:667 sediment source, 3:37 storms, 1:667
(c) 2011 Elsevier Inc. All Rights Reserved.
tectonics, 1:667 see also Atolls; Barrier reefs; Fringing reefs growth/settlement of scleractinian corals, 1:660 importance, 1:662 biodiversity/human use, 1:662 location of, 3:37 management, 1:669 approach, 1:660 assessments, 1:669 integrated coastal management, 1:669–670 oil pollution, 4:196 past climate research see Coral-based paleoclimate research radiocarbon, 4:638–639, 4:638F, 4:639F raised, tectonics and sea level change, 3:49, 3:50F regime shifts, 4:702 remote sensing, 4:740F structural, 1:660–661 atolls, 1:662, 1:663F barrier reefs, 1:661–662, 1:662F depth of reefs, 1:662 fringing reefs, 1:661–662, 1:661F threatened, time-series SST predicting, 5:99 types, 1:660–662 nonstructural communities, 1:660 zonation, 1:661F, 1:662–664 atolls, 1:664 channels in crest, 1:664 channels on lower reef slope, 1:664 fringing reef walls, 1:664 landward edge, 1:662–663 physical factors, 1:662–663 reef crest, 1:663–664 reef walls, 1:664 seaward edge, 1:663–664 storms, 1:664 tectonics, 1:664 upper reaches of reef slope, 1:664 see also Atolls; Cold-water coral reefs; Fringing reefs Coral reef aquaria, 3:529–530 algal feeders, 3:530T biological considerations, 3:530 faunal components, 3:530T, 3:531 filtration, 3:525, 3:528F, 3:530 living rock, 3:530–531 nutrients, 3:530, 3:530F water quality, 3:526, 3:527T, 3:530–531 challenges, 3:529–530 historical aspects, 3:525 physical considerations, 3:530 light requirements, 3:530 temperature, 3:530 water movement, 3:530 zooxanthellae, 3:529 see also Aquarium fish mariculture Coral reef fish(es), 1:655–659 behavior, 1:656 interactions, 1:656 mutualism, 1:656
Index piscivory and defense, 1:656–657 modes of piscivory, 1:656–657 predation-avoidance, 1:656–657 territoriality, 1:656 distribution and diversity, 1:655 anthropogenic threats, 1:655 diversity, 1:655 latitudinal distribution, 1:655 ecology, 1:658 advantages as research subjects, 1:658 community structure, 1:658 feeding guilds, 1:658 resource partitioning, 1:658 population dynamics, 1:658 metapopulations, 1:658 regulating mechanisms, 1:658 fisheries see Coral reef fisheries life cycle, 1:657–658 pelagic larval stage, 1:657 settlement, 1:657–658 spawning, 1:657 maintenance of diversity, 1:658–659 diversity hypotheses, 1:658–659 morphology, 1:655–656 typical traits, 1:655–656 vision and coloration, 1:656 reproduction, 1:657 sex reversal, 1:657 Coral reef fisheries, 1:651–654, 1:655 development, 1:651–652 ecosystem perspective, 1:652 environmental impact, 1:652–653 globalization impact, 1:651, 1:653 growth/development, 1:651 marine protected areas, 1:653–654 poverty issues, 1:653 sustainability and overfishing, 1:655 Coral Sea, as East Australian Current source, 2:187, 2:189, 2:195 Cord grasses, 4:254 Core definition, 5:463 Earth’s magnetic field and, 3:479 Core barrel extended see Extended core barrel rotary see Rotary core barrel Coring and logging tools, deep-sea drilling, 2:50 Advanced Piston Corer (APC), 2:50 Formation Microscanner (FMS), 2:50–51 laboratory equipment, 2:51 Pressure Core Sampler (PCS), 2:50 seafloor equipment, 2:51 Hard Rock Guide Base (HRGB), 2:51 reentry cones, 2:51 Coriolis force, 3:199, 4:723, 6:225 beta effect, 4:121F, 4:122 bottom currents, 2:80 coastal circulation models and, 1:572 deep ocean currents and, 2:565 opposing forces, 2:565–566 Ekman transport, 2:222–223 see also Ekman transport Equatorial Undercurrent, 1:234–235 equatorial waves and, 2:271
fluid parcels and, 5:137 geostrophic balance, 4:119 internal waves, 3:268 meddies, 3:705, 3:708–709 mesoscale eddies, 3:763 mixed-layer momentum flux and, 6:341 rotating gravity currents, 4:794 thermohaline circulation, 4:122 vector cross-product, 2:223 wind driven circulation, 4:120, 4:121F, 4:122 wind forcing and, 2:231 Coriolis parameter, 2:223, 2:605–606 hydrothermal vents, dispersion from, 2:132–133, 2:134–135 Rossby waves, 4:781–782, 4:784–785 wind driven circulation, 6:351, 6:352, 6:352F, 6:353F westward intensification, 6:352, 6:352F, 6:353F CORK (circulation obviation retrofit kit), 2:43F, 2:44 CORK (reentry cone seal), 2:50, 2:50F Cormorants breeding patterns, 4:374, 4:374F darters vs., 4:375 human exploitation/disturbance, 4:373, 5:267 line hunting, 4:374 plumage, 4:374, 4:375 shags vs., 4:373–374 zigzag hunting, 4:374 see also Phalacrocoracidae Cornell Multi-grid Coupled Tsunami Model (COMCOT), 6:134, 6:135–136 Cornet fishes (Fistulariidae), 2:395–396F Cornish, J W, acoustic noise, 1:58F, 1:59 Coronatae medusas, 3:10, 3:11F Corrals, traps, fishing methods/gears, 2:541, 2:541F Correlation velocity log, 4:478 Corrosion-resistant materials, remotely operated vehicles (ROVs), 4:745 Corrsin scale, three-dimensional (3D) turbulence, 6:22 Coryphaena hippurus see Dolphinfish (Coryphaena hippurus) Coryphaenoides rupestris see Roundnose grenadier (Coryphaenoides rupestris) Coryphaneodes subserrulatus see Whiptail (Coryphaneodes subserrulatus) Cory’s shearwater, 5:253 see also Procellariiformes (petrels) Coscinodiscus wailessii, 1:638 Cosmic dust, trace metal isotope ratios, 3:457T Cosmic radiation, 1:678, 5:130 atmospheric dissipation, 1:678–679 Cosmogenic isotopes, 1:678–687 atmospheric production, 1:679 data examples, 1:684–685 measurement techniques, 1:684 oceanic and atmospheric, 1:679–682 oceanic sources, 1:679, 1:680T
(c) 2011 Elsevier Inc. All Rights Reserved.
465
oceanographic applications, 1:682–684 potential tracer applications, 1:679, 1:679T production rates, 1:679, 1:680T land surface, 1:679 radioactivities, 1:682T reservoir inventories, 1:681T chemical properties and, 1:681 terrestrial, 1:678–679 tracer applications, 1:678, 1:681, 1:682 uranium-thorium series radionuclide tracers and, 1:685 tracer properties, 1:683T see also Carbon cycle; Isotopic ratios; Radiocarbon; Radioisotope tracers; Radionuclides Cosmonaut polynya, 4:543 Cosmopolitan distribution, 3:650 Cost(s) administrative, marine protected areas, 3:676, 3:676F AUV mission, 4:479, 4:479F fishery management, externalities, 2:518 gliders (subaquatic), 3:59 inefficiencies, fishery management, 2:515–516 RAFOS float, 2:177 sea level rise see Economics of sea level rise WOCE float, 2:175 Costa Rica Rift, seismic structure, axial magma chamber (AMC), 3:830, 3:834F Couette flow, 3:408 Coulomb force, 2:247–248 Counter-gradient flux, differential diffusion, 2:116 Countershading, 2:216 Coupled circulation-geochemical models, data assimilation, 1:365 Coupled models climate models, 4:131 storm surges, 5:537–538, 5:538, 5:538F Coupled sea ice-ocean models, 1:688–698 basic principles, 1:689 boundary conditions, 1:693–694 coordinate systems, 1:694 coupling, 1:693–694 time resolution, 1:694 dynamics, 1:691–693 basic equation, 1:689 evaluation, 1:694–695 ice variables, 1:689, 1:694–695 ocean variables, 1:695–696 parameter choices, 1:696 ice concentration, 1:690, 1:694–695 drift, 1:691 energy balances, 1:692F formation, 1:691 internal forces, 1:692–693 modeling approach, 1:689 rheology, 1:691–692 salinity, 1:691 thickness, 1:690, 1:695 volume, 1:691
466
Index
Coupled sea ice-ocean models (continued) numerical aspects, 1:689 open water, 1:691 processes, 1:688, 1:688F, 1:693F regions relevant, 1:688–689 snow layers, 1:689, 1:690 subgrid scale parametrization, 1:689 ice thickness, 1:689 ice volume, 1:689–690 thermodynamics, 1:690–691 basic equation, 1:689 Cousteau, Jacques Roman wreck investigation, 3:696 SCUBA invented, 3:695 Soucoupe, 3:513 Cover pots, falling gear fishing methods, 2:539 Cox number, fossil turbulence, 2:616, 2:617 CPR see Continuous Plankton Recorder (CPR) survey CR-01, 6:263T CR-02, 6:263T Crabs brachyuran, Bythograea thermydron, 3:133F, 3:135F, 3:136–138, 3:136F fisheries, 1:701–702 by-catch issues, 2:202 management techniques, 1:705–706 methods, 5:218 Southern Ocean, 5:517 world landings, 1:701–702, 1:701T see also Crustacean fisheries galatheid, Munidopsis subsquamosa, 3:136F, 3:138, 3:138F, 3:139F nurseries, 3:136–138 reproductive patterns, 1:701 see also Crustacean(s); specific species Crackspots, off-ridge non-plume related volcanism, 5:300–301 Craik-Leibovich theory, 3:406 Cranchiidae cephalopods, 3:14–16, 3:15F Cranes, oceanographic research vessels, 5:412 Crassostrea angulata (Portuguese oyster), mariculture, stock reduction, disease-related, 3:534 Crassostrea gigas see Japanese cupped oyster (Crassostrea gigas); Pacific oyster (Crassostrea gigas) Crassostrea virginica see Eastern oyster (Crassostrea virginica) Crayfish fisheries, 1:702 see also Crustacean fisheries see also specific species Creep, 5:450 see also Mass transport Crenarchetoal membrane lipids see TEX86 Crepidula fornicata (slipper limpet) mariculture, environmental impact, 3:908 oyster farming, risks to, 4:283 Crested auklet, 1:171, 1:173F see also Alcidae (auks)
Crested penguins see Eudyptes (crested penguins) Cretaceous, 4:319 climate, 4:320 modeling, 4:326 ocean anoxic events (OAE), 4:320 proxy data, 4:322F thermal maximum, 4:320 Late see Late Cretaceous Cretaceous Normal Quiet Zone, 3:26 see also Paleomagnetism Cretaceous/Tertiary (K/T) boundary, 4:315–316 isotope ratios, 3:462–463 orbital tuning and, 4:315–316 sedimentation rates across, 4:317F Cretan Arc Straits outflow, 3:716–717 Cretan cyclone, 1:748–751, 1:748F Cretan Deep Water (CDW), 3:712–714, 3:716–717 pathways, 1:750F, 1:751 Cretan Intermediate Water (CIW), 3:712–714, 3:713F, 3:714–715, 3:717 pathways, 1:749F, 1:751 Crimean Peninsula, 1:401 Critical angle, acoustic remote sensing, 1:85F, 1:86 Critical Coulomb wedge theory, accretionary prisms, 1:35, 1:35F Critical depth (acoustic), 1:102–103 CRM see Chemical remanent magnetization (CRM) Croll, James, 4:504 Crossover wind speed, 1:54–55, 1:59 Cross-shelf surface transport, coastal trapped waves, 1:596 Crouch, W W, acoustic noise, 1:54–55, 1:55 Crown-of-thorns starfish (Acanthaster planci), 1:669 Cruise ships, 5:404 Crust, oceanic age, heat flow and, 3:44F anisotropic structure, 5:366 chemistry, hydrothermal circulation and, 3:46 drilling, 5:363 formation, 2:49 lower, stratigraphic sequence, 2:49 magnetic layer, thickness, 3:481–482 remnant magnetization of, 3:27–28, 3:28F see also Geomagnetic polarity timescale (GPTS) seismic structure see Seismic structure thickness, 5:362T spreading rate and, 5:365–366 see also Mid-ocean ridge(s) (MOR) Crustacean(s) amphipodal aggregation, 1:334T biology, 1:699–700 bioluminescence, 1:377T Cystisoma spp., 3:16 deep-sea communities, 1:355 fecundity, 1:699
(c) 2011 Elsevier Inc. All Rights Reserved.
feeding, 1:699 freshwater species, 1:699–700 growth rates, 1:699 life history, 1:699–700 mariculture see Mariculture marine species, 1:699, 1:700–701 migration, 1:703 molting process, 1:699, 1:703 Phronima spp., 3:16 polar midwater fauna, 4:516–517 tanaids, 2:59F see also Benthic boundary layer (BBL); Copepod(s); specific species Crustacean fisheries, 1:699–707 assessment research, 1:702–705 model-based, 1:705 catch maximization, 1:702–703 crabs see Crabs, fisheries crayfish, 1:702 lobster, 1:702 management adaptive approach, 1:705 precautionary approach, 1:701 techniques, 1:705–706 marine landings, 1:699, 2:90F optimum yield, 1:705 shrimps/prawns see Shrimps/prawns stock assessment methods, 1:706–707 see also Bioluminescence, plankton; Lagoon(s); Mangrove(s) Crustal chemistry, hydrothermal circulation and, 3:46 Crustal dust, land-sea transfers, 3:402F Crustal magma chambers, 3:843 Crustal rebound phenomena, anatomy of sea level function, 3:52F, 3:54, 3:55F Cryopreservation, 3:565 Cryptic coloration, sea horses, 3:528 Cryptosporidium, sewage contamination, indicator/use, 6:274T C-SALT see Caribbean Sheets and Layers Transects CSIRO modified SeaSoar, 6:68F, 6:73F, 6:74F CSIRO multi-frequency vehicle, 6:70F CTD profilers see Conductivitytemperature-depth (CTD) profilers CTD recorders, towed vehicles, 6:68F, 6:72–73, 6:73F Ctenophores, 2:342, 3:12 Beroida, 3:13F, 3:14 bioluminescence, 1:377T, 1:378 Cestida, 3:14 Cydippida, 3:12, 3:13F Lobata, 3:12–14, 3:13F Platyctenida, 3:12 Thalassocalycida, 3:12 Cuba hurricanes, 6:192–193 water, microbiological quality, 6:272T Cubomedusae medusas, 3:10, 3:11F CUFES (continuous underway fish egg sampling system), 6:368 Cumaceans (Crustacea), 2:59F Cunene (Angola)
Index dissolved loads, 4:759T river discharge, 4:755T, 4:757 Cup anemometers, 5:375, 5:376F Curie (Ci), 4:82–83 Curl of surface wind stress, Ekman pumping velocity, 6:351 Current(s) abyssal see Abyssal currents AUV navigation and, 4:478 bottom see Bottom currents boundary see Boundary currents buoyancy see Buoyancy currents coastal see Coastal currents contour see Bottom currents effects on migration, 2:407–408 forcing, 6:312 as geomorphic processes, 3:33 geostrophic see Geostrophic currents gravity see Non-rotating gravity currents; Rotating gravity currents hydrothermal vents, dispersion from, 2:132–133, 2:133–134 inertial see Inertial currents internal tides see Internal tides internal waves see Internal wave(s) Labrador Sea, 3:65F longshore see Longshore currents non-rotating gravity see Non-rotating gravity currents overflows and, 4:267 radial density, 4:62 rips, 6:313–314 rotating gravity see Rotating gravity currents satellite remote sensing, 5:105–106 sediment transport, instrumentation for measuring, 1:42, 1:43F seiches, 5:344, 5:344F, 5:345F small-scale patchiness and, 5:474 speed, hurricane Frances, 6:207F surface, gravity and capillary waves energy exchange with, 5:577 generation, 5:577, 5:580 tidal see Tidal currents turbidity see Turbidity currents wave-current interactions, 4:772, 4:772F waves on, 5:577–578 Doppler relationship, 5:577 energy exchange, 5:577 refraction, 5:577 wave action conservation, 5:577 wave crests, conservation of, 5:577 wave property prediction, 5:577–578 wind-forced, upper ocean, 6:214–215 wind-induced, Baltic Sea circulation, 1:288, 1:292F see also Waves on beaches; individual currents and related topics Current meters Aanderaa RCM9/RCM8, 5:429F, 5:430T acoustic, 4:116–117, 4:116F definition, 4:116–117 acoustic travel time see Acoustic travel time (ATT) current meters
electromagnetic see Electromagnetic current meters (ECMs) moored see Moored current meters moorings, 4:116–117, 4:116F rotary, 4:116–117, 4:116F definition, 4:116–117 single point see Single point current meters vector averaging, 5:429–431, 5:429F, 5:430T, 5:432 Current profiler, expendable, see also Expendable sensors Current rings Deep Western Boundary Current (DWBC), 2:562–563 Gulf Loop Current (GLC), 2:561, 3:289, 3:290F, 3:291, 3:293F self-propagation, 3:290 T-S characteristics, 3:289–290, 3:290 Gulf Stream System, 2:557, 2:559F North Brazil Current (NBC), 2:561 ‘Curve-fitting’ form, 3:314 see also Least-squares solution Cuttlefish (Sepia spp.) buoyancy, 1:526 spawning, 1:527 Cuvier’s beaked whale (Ziphius cavirostris), 3:646, 3:647F, 3:648–649 CV (wireline reentry system), 6:260, 6:260T, 6:262F Cyanide fishing coral impact, 1:652–653, 1:672 quinaldine use, 1:672 Cyanobacteria, 1:270–271, 4:586–587 blooms, 4:739F definition, 3:574 in epipelic biofilms, 3:807 iron requirement, 4:588 lipid biomarkers, 5:422F Synechococcus spp., 3:799–800 viruses, 4:467 see also Microphytobenthos; Phytobenthos Cyanophora paradoxa alga, 3:553 Cyanophytes, fluorescence, 2:582 Cyclodienes, seabirds as indicators of pollution, 5:275 Cyclohexane, structure, 1:552F Cyclones, extratropical, heat flux affecting development, 1:579 Cyclonic eddies, 3:345–346 Cyclonic lenses, 3:708 Cyclopoida copepods, 1:640, 1:642F Cyclorhynchus, 1:171T see also Alcidae (auks) Cyclostratigraphy see Orbital tuning Cyclothone spp. fish, 2:467, 2:472 Cydippida ctenophores, 3:12, 3:13F Cylindrical spreading (sound), 1:114, 1:114F loss, 1:103 see also Geometrical spreading Cynoscion nebulosus (spotted sea trout), stock enhancement/ocean ranching programs, 4:147T, 4:150
(c) 2011 Elsevier Inc. All Rights Reserved.
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Cypraea moneta (money cowry), currency use, 3:899 Cyprinus carpio (carp), 2:471F Cystonectae siphonophores, 3:12, 3:13F CytoBuoy, 4:248 Cytochrome b6/f complex, definition, 6:85 Cytochrome oxidase, 6:83 Cyttopsis rosea (rosy Dory), 2:483, 2:483F CZCS see Coastal Zone Color Scanner
D D (diffusion coefficient), definition, 6:242 Dactylopteridae (flying gurnads), 2:395–396F Daily vertical migration, 2:216 see also Diurnal vertical migration Dalatias licha see Kitefin shark (Dalatias licha) Dall’s porpoise (Phocoenoides dalli), 2:154, 2:158, 2:159 Dam(s) hydrodynamics, 2:564 river discharge and habitat modification, 3:103–104 Dam building, 4:760 in sea level rise reduction, 5:183 upriver, 1:588 Damsel fish (Eupomacentrus planifrons), 2:378 Damselfishes (Pomocentridae), 1:656 Danish seines, 2:537, 2:537F Danish Straits, 1:288, 1:290F Baltic Sea circulation bidirectional flow, 1:291–292 currents, 1:290–291, 1:294–296 Fehmarnbelt, 1:288, 1:290F, 1:291–292 Great Belt, 1:288, 1:290F, 1:291–292, 1:294 Little Belt, 1:288, 1:290F mass transport, 1:294, 1:295F ¨ resund, 1:288, 1:291–292 O outflow rates, 1:294, 1:295T sea-level differences, 1:294, 1:295 Dansgaard–Oeschger (D/O) cycles Heinrich events and, 3:130F Holocene, 3:126F, 3:128, 3:130–131, 3:130F rapid warming at end of, 3:786, 3:787F Dansgaard–Oeschger (D/O) events, 1:1–2 cyclicity, 1:4 drivers, 1:3 periodicity, 3:886–887 warming distribution, 1:4 Danube, Black Sea input, 1:211, 1:402 Daption capense (Cape petrel), 4:591F Darcy percolation flux, mantle melt, 3:873 Darcy’s law burrows and, 1:398 saline groundwater quantification, 3:90 Dark matter, definition, 2:613
468
Index
Dark mixing, definition, 2:613 D’Arsonval, J.A., 4:168 Darss sill, Baltic Sea circulation, 1:288, 1:290F, 1:294, 1:295F Darters see Anhingidae (darters) Darwin, Charles, 3:191 atoll formation theory, 1:666–667, 1:666F coral reefs, 3:34, 3:34F, 3:37 Darwin (Australia), atmospheric pressure anomaly time series, 2:231F D’Asaro, Eric, Eric, 2:177 Dasyatis sayi (stingray), 2:446F Data acquisition, in oceans, 2:1 assimilation see Data assimilation collection, satellite remote sensing see Satellite remote sensing recording and handling, expendable sensors, see also Expendable sensors storage, solid-state, CTD profilers, 1:716 transmission, moorings, 3:926 Data assimilation biogeochemical see Biogeochemical data assimilation data requirements, 1:364 definition/description, 2:1 global vs local, via nudging, 2:8–10 history, 1:364 methods, 1:365–366 scheme for, 2:2, 2:2F components, 2:2 small-scale convection and, 2:10–11 tomography, 6:47 see also Data insertion Data assimilation in models, 2:1–12 accuracy of data, 2:2 biogeochemical see Biogeochemical data assimilation concepts and methods, 2:5–7 control theory, 2:7 adjoint method, 2:7 generalized inverse problems, 2:7 representer method, 2:7, 2:11 direct minimization methods, 2:7–8 descent methods, 2:8 genetic algorithms, 2:8 simulated annealing schemes, 2:8 examples, 2:8 general circulation from inverse methods, 2:8 global vs local via nudging, 2:8–10 North Atlantic circulation, 2:8, 2:9F ocean time estimation from inverse methods, 2:11 small-scale convection and, 2:10–11 field and parameter estimation, 2:1–3 approximate dynamics, 2:1 complexities and consequences, 2:1 dynamical model, 2:1, 2:7 error estimation/models, 2:2 feedbacks, 2:2 from measurements, 2:1 physical state variables, 2:1 process of, 2:2, 2:2F
global time-space adjustment, 2:7 goals and purposes, 2:3 compensation for deficient dynamical model, 2:3 four-dimensional time series, 2:3 multipurpose management models, 2:3 parameter estimation via, 2:3 weather prediction/practical purposes, 2:3 optimal and suboptimal schemes, 2:5–7 estimation theory, 2:7 regional forecasting and dynamics, 2:3–5 adaptive sampling, 2:5 real-time predictions, 2:3–5 stochastic and hybrid methods, 2:8 hybrid methods, 2:8 stochastic methods, 2:8 types of estimates, 2:2–3 validation and calibration, 2:2 Data insertion, 1:365–366, 1:367F limiting factors, 1:367–368 nutrient, phytoplankton, zooplankton (NPZ) models, 1:367F, 1:368F Dating techniques, orbital tuning, 4:311–318 Davidson Current, 1:458–459, 1:459, 1:460F, 1:463 Davis, Russ, 3:59 Davis, William Morris, 3:34, 3:34F DDD (dichlorophenyldichloroethane), structure, 1:552F DDPS (Discrete Depth Plankton Sampler), 6:362–363, 6:363F DDT (dichloro-diphenyl-trichloroethane), 1:551 definition, 1:677 environmental concerns, 1:553 feminization of male gulls, 3:427–428 history, 1:553 Mussel Watch Stations, 1:559F, 1:560 seabirds as indicators of pollution, 5:225, 5:274, 5:275 structure, 1:552F surface seawater analysis, 1:554 time trends, 1:561F ‘Dead zone,’ definition, 3:172–173 Debris avalanche, 5:450 see also Mass transport Debris blocks, 5:448F Debris flows, turbidity currents and, 5:460 Debrites, 5:456, 5:456–459, 5:460F Amazon submarine channel, 5:459 characteristics, 5:449F, 5:449T, 5:457 definition, 5:456–459 dimensions, 5:455T mechanical classification, 5:447 other gravity-based mass transport/ sediment flow processes and, 5:447–467 Decadal climatic oscillations, 6:215 Decapod shrimps (Caridea), bioluminescence, 1:380 Decay per minute, definition, 5:557
(c) 2011 Elsevier Inc. All Rights Reserved.
Decay time, internal waves, 3:271 Decibel, 1:101–102, 1:113 De´collement, definition, 5:464 Decollement Zone, 2:49 Decommissioning, rigs and offshore structures, 4:751 DECORANA (detrended correspondence analysis), 4:536 Deep basins anoxia, 3:173–174 hypoxia, 3:173–174 Deep boundary current, 4:127 Deep chlorophyll maximum (DCM), 5:477–478, 5:477F Deep convection, 2:13–21 boundary currents, 2:20, 2:21 buoyancy flux, 2:13, 2:15 carbon dioxide, 2:15 see also Carbon cycle float measurements, 2:16, 2:21 gas transport, 2:15 Greenland Sea, 2:13, 2:19–20 ice, influence of, 2:13–15, 2:19–20 Labrador Sea see Labrador Sea Labrador Sea Water see Labrador Sea Water Mediterranean Sea, 2:13, 2:19–20 Mediterranean Sea circulation, 3:716–717 meridional overturning circulation, 2:20, 2:21 mixed layer see Surface mixed layer model studies, 2:20–21 oxygen, 2:15 plumes see Ocean convection plumes regional differences, 2:19–20 restratification see Restratification Rossby wave, 2:20–21 salinity variability see Salinity sinking, 2:20–21 surface heat loss, 2:13 calculation, 2:13 temperature variability, 2:16–17 thermal boundary layer, 2:15, 2:16F tracer observations, 2:20, 2:21 ventilation, 2:15 water mass conversion, 2:20–21 Weddell Gyre, 6:324 wind, influence of, 2:19–20 see also Mediterranean Sea; Mediterranean Sea circulation; Rossby waves; Sub-sea permafrost; Thermohaline circulation ‘Deep dark mixing paradox’, 2:617 Deep Flight (high speed submersible), 3:508 Deep Jeep (USN submersible), 3:513–514 Deep marine, definition, 5:447 Deep ocean acoustic noise, 1:55 biological research, deep submergence science, 2:29, 2:32F, 2:33F carbon exchange efficiency with latitude, 4:96–97 cosmogenic isotope concentrations, 1:681T
Index dispersion and diffusion, 2:122–129 mixing, observations, 2:122–128, 2:124F, 2:127F thermohaline circulation, 2:122 magnetic anomalies, 3:483 storm surges, dissipation, 5:532 temperatures, 4:124–125, 4:124F Deep-Ocean Assessment and reporting of Tsunamis (DART), 6:137F Deep ocean passages, 2:564–571, 2:565F Atlantic Ocean, 2:566–569 flow physics, 2:564–566 comparison with theory, 2:569, 2:569F Indian Ocean, 2:569 long-term measurement, 2:569–570 mixing, 2:570 Pacific Ocean, 2:569 volume flux and free surface height, 2:565 see also Trenches Deep ocean work boat, 3:513 Deep scattering layer (DSL), 1:107 organisms, 4:134 Deep sea, definition, 2:55–56 Deep seabed mining threat to cold-water coral reefs, 1:624 see also Deep-sea drilling Deep-sea delta fan, 4:143F Deep-sea drilling, 2:45–54, 3:122–123 advisory structure, 2:53 advisory panels, 2:53, 2:53F logistics/infrastructure, 2:53 scientific guidance, 2:53 scientific programs determination, 2:53 dynamics of Earth’s environment, 2:47–49 expeditions (scientific), 2:52 facilities, 2:51–52 JOIDES Resolution, R/V, 2:51, 2:51T ODP core repositories, 2:51–52 state-of-the-art laboratory structure, 2:51 future directions, 2:53–54 Integrated Ocean Drilling Program (IODP), 2:54 new program planned, 2:53–54 historical perspective on Earth’s environment, 2:47–48 international partnership, 2:52 see also Ocean Drilling Program (ODP) laboratory equipment, Multisensor Track see Multisensor Track (MST) methodology, 2:37–44 in situ measurement tools, 2:41–44 sampling tools, 2:39–41 seafloor observatories, 2:44 technology, 2:37–39 see also specific techniquessee specific tools programs, 2:45–46 Deep Sea Drilling Project (DSDP), 2:45, 2:45–46, 2:46F, 2:48F
Glomar Challenger, RV, 2:45–46, 2:45F JOIDES, 2:45 JOIDES Resolution, R/V, 2:46, 2:47F Ocean Drilling Program (ODP), 2:46 Project Mohole, 2:45 results, 2:45–54 science initiatives, 2:46–47 scientific expeditions see Scientific expeditions sediments and crust exploration, 2:46–47 state-of-the-art laboratories, 2:51 technological advances, 2:49–50 coring and logging tools see Coring and logging tools new tools, 2:50 reentry cone seal (CORK), 2:50, 2:50F seafloor observatories, 2:50 Deep Sea Drilling Project (DSDP), 2:37, 2:45, 4:297 drilling sites, 2:38F, 2:45–46, 2:46F, 2:48F mid-ocean ridge seismic structure, seismic layer 2A, 3:827, 3:827F Deep-sea environment, 1:354 Deep-sea exploration vehicles, 6:255–266 see also Autonomous underwater vehicles (AUVs); Human-operated vehicles (HOV); Remotely operated vehicles (ROVs) Deep-sea fan system, 4:143F Deep-sea fauna, 2:55–66 anthropogenic threats, 2:64–65 fishing, trawling and dredging, 2:64–65 mining, 2:65 pollutants, 2:64–65 precautionary approach, 2:65 reasons for concern, 2:65 vulnerability of fauna, 2:65 waste disposal, 2:65 changing perceptions about biodiversity, 2:55 about stability, 2:55 comparison of benthic communities by depth, 2:62F defining the organisms, 2:58–59 feeding modes, 2:59 size groupings, 2:58–59, 2:59F depth, biomass and density relations, 2:59, 2:60F diversity, 2:55 diversity, theories about, 2:64 areal relationship theory, 2:64 current research, 2:64 intermediate disturbance theory, 2:64 patch mosaic model, 2:64 predator theory, 2:64 stability-time hypothesis, 2:64 diversity patterns, 2:61–62 depth patterns, 2:61–62 discovery, 2:61 latitudinal patterns, 2:62 environmental characteristics, 2:55 habitats, 2:55–57, 2:56F
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‘deep-sea’ defined, 2:55–56 environmental characteristics, 2:56–57 seasonality, 2:57 small-scale heterogeneity, 2:57 hydrothermal vents, 2:57–58 biodiversity, 2:57, 2:58F causes and characteristics, 2:57 chemoautotrophic bacteria, 2:57–58 see also Hydrothermal vent(s) low diversity environments, 2:63–64 areas of regular disturbance, 2:63 deep-sea trenches, 2:63 hydrothermal vents, 2:63 hypoxic areas, 2:63 young areas, 2:63–64 new questions, 2:55 numbers of species, 2:62–63 estimates, 2:62, 2:63F number of marine animal phyla, 2:62 small size of sampled area, 2:62–63 studies required, 2:63 sampling, 2:59–61 ALVIN corers, 2:60, 2:61F box corers, 2:60, 2:61F epibenthic sled, 2:59–60, 2:61F gear for specialist research, 2:60–61 multicorer, 2:60 quantitative samplers, 2:59–60 submersibles, 2:60, 2:61F trawls, 2:59–60 visual surveys, 2:60 seamounts, 2:57 habitat characteristics, 2:57 typical landscape, 2:56F see also Benthic foraminifera; Demersal fish(es); Macrobenthos; Meiobenthos; Ocean margin sediments; Pelagic biogeography Deep-sea fish(es), 2:67–72 benthic/benthopelagic species, 2:67 buoyancy, 2:71 methods employed, 2:71 categories, 2:67 definition, 2:67 depth-related abundances, 2:67–70 faunal provinces, 2:67–69 food sources, 2:69–70, 2:69F relation to food supply, 2:67 diet, 2:70 feeding strategies, 2:70 research methods, 2:70 evolution, 2:67 life histories, 2:72 ‘bigger-deeper’ phenomenon, 2:72 incomplete information, 2:72 longevity, 2:71–72 aging methods, 2:71, 2:71F morphologies, 2:68F regional differences/similarities, 2:67 reproduction, 2:72 early life stages, 2:71–72 hermaphroditism, 2:71 spawning, 2:71 sampling techniques, 2:67 sensory systems, 2:70
470
Index
Deep-sea fish(es) (continued) olfaction, 2:70 sight, 2:70 sound production, 2:70 touch, 2:70 see also Bioluminescence; Demersal fish(es); Demersal fisheries Deep-sea observatories, 2:50 long-term, deep submergence science studies, 2:24–26, 2:30–33, 2:33F, 2:34 Deep-sea red clay, 1:566–567 Deep-sea ridges endosymbionts see Endosymbionts, deep-sea ridges epibionts see Epibionts, deep-sea ridge microbiology internal tides, 3:263, 3:264F, 3:265 Deep-sea ridges, microbiology, 2:73–79 16S rRNA phylogenetic analysis, 2:75, 2:76–77 archaea see Archaea bacteria see Bacteria Beggiatoa, 2:77 biogenic flocculent material (floc), 2:77, 2:78, 2:78F chemolithotrophs, definition, 2:73 chemosynthesis, 2:73, 2:76 diversity at deep-sea vents, 2:75 endosymbionts, 2:75–76 epibionts, 2:76–77 free-living microbes, 2:77 measurement methods, 2:75 microscopic observations, 2:76–77 molecular phylogenetics, 2:75, 2:76–77, 2:77 in situ growth chamber, 2:78 mesophilic microbes, 2:77 thermophilic microbes, 2:77–78 see also Endosymbionts, deep-sea ridges; Epibionts, deep-sea ridge microbiology epsilon proteobacteria, 2:77, 2:78 geological setting, 2:73 back-arc spreading centers, 2:73 hot spots, 2:73 hydrothermal fluid chemistry, 2:73, 2:74F hydrothermal fluid flow, 2:73, 2:74F seamounts, 2:73 spreading centers, 2:73 habitats (microbial), 2:73–75 chemical diversity, 2:73–75, 2:74F high-temperature venting aerobic zone, 2:73–75 hydrothermal plume, 2:73–75, 2:77 hydrothermal vent deposits, 2:73–75, 2:75F, 2:78 invertebrate symbiontic hosts, 2:73–75, 2:76 microbial mats, 2:73–75 heterotrophic microbes, definition, 2:73 hyperthermophilic microbes, 2:73–75, 2:77–78 mesophilic bacteria see Mesophilic microbes
Mid-Atlantic Ridge (MAR), 2:76 origins of life, 2:78–79 psychrophilic microbes, definition, 2:73–75 subsurface biosphere, 2:78 exploration, 2:78 floc production, 2:77, 2:78F thermoacidophiles, definition, 2:78 thermophilic bacteria see Thermophilic microbes Thiothrix, 2:77 Universal Tree of Life, definition, 2:75 see also Endosymbionts; Epibionts; Hydrothermal vent biota; Hydrothermal vent deposits; Hydrothermal vent ecology; Hydrothermal vent fauna, physiology of; Mid-ocean ridge seismic structure Deep-sea sediment drifts, 2:80–89 bottom currents affecting see Bottom currents channel-related drifts, 2:83 channel floor deposits, 2:83 contourite fans, 2:83 deep passageways or gateways, 2:83 patch drifts, 2:83 confined drifts, 2:83–84 tectonically active areas, 2:83–84 contourite drifts, 2:81–82 five main classes, 2:81, 2:83T, 2:84F models, 2:81, 2:83T, 2:84F see also Contourite(s) contourite facies see Contourite sediment facies contourite sheet drifts, 2:81–82 abyssal sheets or slope sheets, 2:82, 2:83T accumulation rates, 2:82 large area of constant thickness, 2:81–82 elongate mounded drifts, 2:82–83 elongation trend, 2:83 progradation direction, 2:83 sedimentation rate and type, 2:83 variable dimensions, 2:82–83 erosional discontinuities, 2:84–85 architecture of deposits, 2:85, 2:85F historical background to studies, 2:80 modified drift-turbidite systems, 2:84 downslope and alongslope processes, 2:84 examples at margins, 2:84 seismic profiles, 2:84F, 2:85 Deep-sea sounding experiments, 3:121–122 Deep-sea trenches, 2:63 Deep-sea vehicles see Manned submersibles (deep water); Vehicles, deep-sea Deep-sea vents, microbial diversity, see also Deep-sea ridges Deep-sea water sinking flux of particles see Particle flux, temporal variability
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temperature, surface sea water vs., 4:167F topographic eddies, 6:63 see also entries beginning deep water Deep sound channel, 1:101, 1:102–103, 1:102F floats and, 2:176 noise directionality, 1:110F ray paths, 6:42F tomography, 6:41–42 Deep submergence science, 2:22–36 achievements/topics studied, 2:24–34 biodiversity of marine communities, 2:29 CORK, 2:24–26, 2:31F deep ocean biological research, 2:29, 2:32F, 2:33F deep ocean processes research, 2:26–28, 2:30–33 geochemical studies, 2:29–30 global MOR discoveries, 2:24–26 hydrothermal communities, 2:24–26, 2:28–29, 2:32F long-term deep seafloor observatories, 2:24–26, 2:30–33, 2:33F, 2:34 Ocean Drilling Program, 2:24–26, 2:29F, 2:30–33, 2:31F provision of deep submergence vehicles, 2:33–34 Scripps Institution’s re-entry vehicle, 2:24–26, 2:29F seafloor bathymetric surveys, 2:34, 2:35F subduction zone processes, 2:29–30 time-series observations, 2:24–26, 2:32F, 2:34 ocean phenomena and processes discoveries, 2:34 technologies enabling, 2:22–24 ABE Autonomous Benthic Explorer, 2:26F, 2:34, 2:35F Alvin, 2:22–23, 2:23F, 2:24F, 2:27F, 2:30–33 Argo II optical/acoustic mapping systems, 2:22–23, 2:27F AUVs, 2:26F DSL-120 towed multibeam sonar, 2:27F Jason ROV, 2:22–23, 2:24F, 2:25F, 2:27F, 2:30–33, 2:33F key discoveries by Alvin, 2:23–24, 2:32F manned submersibles, 2:22, 2:24F oceanographic technology and instrumentation, 2:22 ROVs, 2:22, 2:24F, 2:26F, 2:27F R/V Atlantis, support ship, 2:24F, 2:27F Tiburon remotely operated vessel, 2:26F time-series and observatory-based research, 2:22 Ventana remotely operated vessel, 2:26F
Index see also Autonomous underwater vehicles (AUVs); Manned submersibles (deep water); Remotely operated vehicles (ROVs) utilization of ODP boreholes, 2:24–26, 2:29F, 2:31F, 2:32F see also Deep-sea ridges; Hydrothermal vent fluids, chemistry of; Mid-ocean ridge geochemistry and petrology; Seamounts and off-ridge volcanism Deep submergence vehicles, 2:22–24, 2:33–34 see also Deep submergence science, technologies enabling Deep Tow 4KC, 6:256F, 6:256T Deep Tow 4KS, 6:256F, 6:256T Deep Tow 6KC, 6:255, 6:256F, 6:256T Deep-towed vehicle systems, 6:256F, 6:256T Deep-Tow survey System, 6:256T Deep water, 6:296–297, 6:296F formation, 1:481, 1:482F investigations difficulties, 3:505 severe environment, 3:505 see also Deep submergence science; Manned submersibles (deep water) mixing, 3:447–449 see also Energetics of Ocean Mixing see also entries beginning deep-sea Deep-water archaeology, 3:699 advanced technology for site mapping, 3:699, 3:700F advantages over shallow-water sites, 3:699 deep-waters disregarded, 3:699 deep-water sites favour preservation, 3:699 deep-water trade route from Carthage found, 3:699 Phoenician ships discovered, 3:699 trade routes shown by debris trails, 3:699 see also Archaeology (maritime) Deep-water fisheries see Demersal fisheries Deep-water gravity waves, see also Surface, gravity and capillary waves Deepwater redfish (Sebastes mentella), open ocean demersal fisheries, 4:228–229 Deep-water sediments, chlorinated hydrocarbons, 1:554–555 Deep-water species see Demersal fish Deep-water submersibles see Manned submersibles (deep water) Deep-water surface waves grouping, 1:431–432 processes affecting, 1:431 see also Waves Deep Western Boundary Current (DWBC), 1:16, 1:20F, 1:26F, 1:29–30, 1:726, 2:554, 2:562–563, 3:300, 3:301F, 4:88, 5:202
current rings, 2:562–563 generating forces, 2:555–556 Intra-Americas Sea (IAS), 3:292 observations, 1:24F, 1:25F, 1:26, 1:29 early, 1:16 long-term, 1:24F, 1:26, 1:27F, 1:28F recirculating gyre, 2:562–563 subpolar gyre, 2:562–563 transport, 2:561F, 2:562 velocity, 2:562, 2:563F see also Abyssal currents; Antarctic Bottom Water (AABW); North Atlantic Deep Water (NADW) Defant, A, 5:345 Defense Meteorological Space Program (DMSP) satellites, 5:206, 5:207 Deforestation, carbon emission and, 4:105 Deformation radius see Rossby radius of deformation Degassing flux (FVOL), 1:515 Deglaciations glaciations vs., atmospheric carbon dioxide and methane, 3:786 hydrate dissociation and, 3:785–786, 3:786, 3:787 Delayed oscillator, 4:715 ‘Delayed oscillator’ modes, 2:244–245 Del Buoy, 6:300–301 Delft Hydraulics, 1:154T Delphinapterus leucas (beluga whale), 3:629–630 Delphinidae see Oceanic dolphins Delphinus spp. (common dolphins), 2:154F Delta(s) definition, 3:38 geomorphology, 3:38, 3:38F river processes, 3:38 sea level change, 3:38 tidal processes, 3:38 wave processes, 3:38 D14C see also Carbon Delta Flume, 1:41F, 1:46, 1:46F Delta Plan, 5:532 De Magnete, 3:478–479 Demersal fish(es), 2:458–466 appearance and behavior, 2:460–461 activity patterns, 2:461 adaptations to benthic habitat, 2:460 adaptations to specific habitats, 2:461 camouflage, 2:461 modes of life, 2:461 sizes, 2:460–461 body shapes, 2:459F continental shelves, 2:458 high productivity, 2:458 patterns, 2:458 definition, 2:458 distribution and diversity, 2:458–460 distribution, 2:458, 2:460F environments/habitats, 2:458–460 influence of shelf width, 2:458–460 latitudinal patterns, 2:458 taxonomic diversity, 2:458
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fecundity, 4:226 feeding/diet, 2:462–464, 2:505 carnivorous categories, 2:462 benthophages, 2:463 piscivores, 2:462–463 zooplanktivores, 2:463 co-occurring species, 2:463–464 dietary flexibility, 2:463–464 ontogenetic changes, 2:463 partitioning of resources, 2:463 flatfish, 2:463 habitat, 2:505 harvesting, 2:501 migration, 2:461–462 diurnal vertical migrations, 2:461 horizontal migrations, 2:461 Northeast Atlantic cod, 2:461–462, 2:462F reproduction and life history, 2:464–465 habitats for hatchlings and young, 2:465 larvae, 2:465 longevity, 2:465 sharks, 2:464 somatic growth patterns, 2:465 spawning seasons, 2:464–465 teleost postlarvae, 2:465 teleosts, 2:464 sensory systems, 2:464 roles of different systems, 2:464 sharks and rays, 2:464 species, by FAO statistical areas, 4:231T, 4:232–233 see also Deep-sea fauna; Lagoon(s); Large marine ecosystems (LMEs); specific species Demersal fisheries, 2:90–97 environmental effects, 2:93–94 salinity, 2:93–94 water temperature, 2:93, 2:93F exploitation levels, 2:94, 2:95F, 4:226 impact, 2:92–93 FAO statistical areas, 4:226, 4:227F, 4:231T, 4:232–233 fishing intensity/effort, 2:91, 2:92T landings, 2:90, 2:90F, 2:91T limits, 2:94 per continental shelf unit area, 2:94, 2:94F principal species caught, 2:91 management, 2:94–96 biological, 2:95 economic, 2:94–95, 2:95 performance monitoring, 2:95 precautionary approach, 2:95–96 methods/gears, 2:90, 2:91–92 mortality rates, limitation, 2:95 New England, 2:96 north-west Atlantic, 2:96, 2:97T open ocean, 4:226–233 ecosystem effects, 4:233 fishing effort, 4:228 historical development, 4:226 Total Allowable Catch, 4:227–228 regional variation, 2:96 see also Groundfish fisheries
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Demersal organisms, 2:160 Denatant migration, 2:216 Dendrogram, 4:536, 4:537F Denitrification, 4:685–686, 4:686F, 6:227, 6:231 aerobic, 4:34–35 bacteria, 3:813–814 definition, 3:7 dinitrogen (N2) fixation and, 4:35 estuaries, 4:253–254 gas exchange in, 3:4 free energy yield, 4:686T isotope ratios and, 4:43, 4:43T, 4:46 ‘leaky pipe’ flow diagram, 1:164F nitrification and, pore water profile, 4:569F nitrous oxide, 1:164 role of microphytobenthos, 3:813–814 salt marshes and mud flats, 5:45 sedimentary, 4:43 upwelling zones, 6:227 water-column, 4:43 see also Nitrification; Nitrogen cycle Denitrification zone, 4:49F Denmark, trout farming, 5:23 Denmark Strait, 2:572, 4:126–127, 4:130 NADW formation, 4:306 overflow, 4:266, 4:267F, 4:791F, 4:793–794 eddies, 4:270–271 paleoceanography climate models in, 4:307 global ocean circulation and, 4:306–307 opening, 4:304F see also Straits Denmark Strait Overflow Waters, 1:21F, 1:24, 1:537 see also Denmark Strait Dense surface waters, 5:127 Dense water formation, 4:55 Density currents see Non-rotating gravity currents; Rotating gravity currents distribution measurement, ocean circulation, 4:119 hydrothermal plumes, 2:130, 2:131F neutral, vs potential surfaces, 4:27–29 of seawater, 6:379 calculation, 1:713 depth variation, 2:13 quantities related to, 6:379–381 turbulent flux, 2:295–296 see also Double-diffusive convection; Potential density; Stratification stratification see Stratification surface mixed layer see Surface mixed layer surface water, 6:163 evaporation and, 6:339–340 heat flux and, 6:339–340 hurricane Frances, 6:207F precipitation and, 6:339–340 Density-driven circulation, 4:126, 4:130
Density profile Black Sea, 1:216F, 1:405F Southern Ocean, 1:180F Dentition dolphins and porpoises, 2:149–153, 2:153F killer whale (Orcinus orca), 2:149–153 polar bear, 3:616F sea otter, 5:194–195, 5:196F Deposit feeders, 3:468 Deposit feeding, 1:395 Deposition, 2:328 aerosols, 1:250, 1:252 see also Dry deposition; ‘Wet’ deposition Depth current strength and, 3:62 effect on fish, 2:368–369 gradient, seabird abundance and, 5:228–229 measurement, by hydrowire casts, 1:709 range for towed vehicles/cable system, 6:70F, 6:71, 6:71F for shallow vs deep-water manned submersibles, 3:513, 3:515 Depth of no motion definition, 2:195 East Australian Current, 2:187–189 Depth sensors, remotely operated vehicles (ROVs), 4:743 Depuration facilities, molluskan fisheries, 3:903 Derbyshire, 4:770F Deregulation, liner trade, 5:406 Dermochelyids, 5:212, 5:214–215 see also Leatherback turtle (Dermochelys coriacea) Dermochelys coriacea see Leatherback turtle (Dermochelys coriacea) Desalination plants, effluent, coral impact, 1:674 Descent methods, direct minimization methods, in data assimilation, 2:8 Desulfurobacterium (bacteria), 2:78 Detergents, sewage contamination, indicator/use, 6:274T Deterministic simulation models, 4:722–723 Detrainment, non-rotating gravity currents, 4:63–64 Detrended correspondence analysis (DECORANA), 4:536 Detrital, definition, 1:268 Detrital minerals, 3:890 Detrital (depositional) remanent magnetization (DRM), 3:26 sediments, 3:26–27, 3:27F Detritus, 1:356, 2:56–57, 2:216, 3:468, 4:21 definition, 4:337 as optical constituents of sea water, 4:624 spectral absorption, 3:245 Detritus feeders, coral reef aquaria, 3:530T Detrivores, 1:351–352, 1:352, 1:356 Deuterium levels, 4:511F
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Developing countries, fishery management, 1:653, 2:515 Deviations from axial linearity (DEVAL), 3:875–876 De Voorst Laboratory, 1:46 Dewakang sill, 3:237 Dew point hygrometers, 5:379 Dew point temperature, definition, 2:325T Diagenesis, 4:563, 4:565–567 calcium carbonates, 1:451–453 definition, 1:268, 3:774 pore water and, 4:565–567 pyrite, 4:563 see also Biogeochemical zonation Diagenetic potential, 1:451–453 Diagenetic reactions, 1:266T Diapause, copepods, 1:649, 1:649F eggs, 1:647 Diapycnal flow ‘upward’, 2:128 Diapycnal mixing buoyancy frequency and, 6:88–89, 6:89F fiord basins, 2:357 Munk model, 6:88 open ocean, 6:88–89 radiocarbon age and, 5:421 total diffusivity, 6:88 tracer release experiments, 6:87–88 Diatom(s), 3:683–684, 6:231 cadmium in, 6:83 cell wall, 4:679 Chaetoceros spp., 4:434–436 chloroplasts, 2:552F common surf-zone species, 5:54F epipelic biofilms, 3:807 epipsammic assemblages, 3:807–808 extracellular polysaccharide production, 3:811 frustules, 1:371–372, 3:573 genomics, 3:554–555 giant see Giant diatoms influence of NH+4 concentrations, 3:813 large diatom/large grazer food path, 6:229 lipid biomarkers, 5:422F nitrogen assimilation, 4:44 opal as productivity proxy, 5:336, 5:341F, 5:342 paleothermometric transfer functions and, 2:111 polar regions, 4:516 reliance on turbulence, 5:492 skeletons, as biogenic silica in marine sediments, 3:681, 3:683–684, 3:684F Southern Ocean food web, 4:518 upwelling ecosystems, 6:228–229 blooms, 6:229 primary production efficiency, 6:228 sedimentation, 6:229 size, 6:228 see also Microphytobenthos; Phytoplankton Diatom mats ecological significance, 3:651–653
Index mass sinking, causes of, 3:653 ‘fall dump’, 3:652F, 3:653 ocean frontal systems, 3:653 Diazotrophy, 4:586 DIC see Dissolved inorganic carbon Dicentrarchus labrax (sea bass) mariculture marketing problems, 3:536 production systems, 3:534, 3:535 stock acquisition, 3:532 vaccination, 3:523 thermal discharges and pollution, 6:15–16, 6:16F Dichlorobiphenyls, structure, 1:552F Dichlorodifluoromethane, Schmidt number, 1:149T Dichlorodiphenyltrichloroethane (DDT) see DDT (dichloro-diphenyltrichloroethane) Dichlorophenyldichloroethane (DDD), structure, 1:552F Dieldrin seabirds as indicators of pollution, 5:275 structure, 1:552F Diel vertical migration biodiversity and, 2:143 reasons for, 4:358–359 Diet analysis, fishery multispecies dynamics quantification, 2:506–507 aquarium fish mariculture, 3:528–529 benthic organisms, 1:351–352 copepods, 1:645 demersal fishes, 2:462–464 dolphins and porpoises, 2:157 fish larvae, 2:383–385 intertidal fishes, 3:284 macrobenthos, 3:468–469 micronekton, 4:5–6 radiolarians, 4:614 salmonids, 5:33–34 seabirds, 5:281–282, 5:282, 5:282T sperm and beaked whales, 3:646 suspension feeders, 1:331–332, 1:332T see also Fish feeding and foraging Differential diffusion, 2:114–121 double diffusion and, 2:119–120 eddies and, 2:114–115 effect on large-scale ocean processes, 2:120–121 evidence for, 2:118–119, 2:119F importance, 2:119–121 laboratory studies, 2:115 Lagrangian schematic, 2:117F numerical simulation, 2:115–117, 2:116F process overview, 2:114–115, 2:114F real-world values, 2:117–118 small-scale restratification, 2:116 see also Double-diffusive convection Differential Global Positioning System (DGPS), manned submersibles (deep water), 3:509 Differential mixing see Differential diffusion
Differential pulse anodic stripping voltammetry (DPASV), 6:104T Diffuse attenuation coefficient, 4:623 Diffuse flow, Juan de Fuca ridge, 1:72F, 1:73F Diffuse reflection, 1:8 Diffusion, 4:103 definition, 6:58 differential see Differential diffusion double see Double diffusion gases across mass boundaries, 1:147–149 mixing and, 4:732 ocean climate models and, 5:137 pore water, 4:568 scalar mixing, 6:21, 6:23 in sediments, 4:491 temperature vs. salinity diffusivity, 2:114 turbulent diffusion and, 2:289 vertical, fiords, 2:357 see also Double-diffusive convection; Mixing; Turbulent diffusion; Turbulent mixing Diffusion coefficients, dissolved gases, 1:147T Diffusion-reaction equation, 6:239 Diffusive convection, 2:166–168 Antarctic, 2:167–168 Arctic, 2:167 basic mechanism, 2:166 necessary conditions, 2:166 oceanic spreading centers, 2:167 salt and heat flux, 2:166–167 under sea ice, 2:166 see also Double-diffusive convection Dikes, mid-ocean ridge tectonics, volcanism and geomorphology, 3:862 Diking, 3:845F Mid-Atlantic Ridge, 3:846 Dimethylgermanic acid (DMGe), 3:780, 3:780F Dimethyl mercury (DMHg), pollution, 3:768–769 Dimethylsulfide (DMS), 3:401–403 air–sea transfer, 1:157, 1:158–159 biogeochemical cycle, 1:158–159, 1:158F concentrations, 1:158 diffusion coefficients in water, 1:147T estuaries, gas exchange in, 3:5–6 fate in seawater, 1:159 photochemical oxidation, 1:159 photochemical processes/production, 4:417, 4:419 Schmidt number, 1:149T troposphere, 1:159 Dimethylsulfoniopropionate (DMSP), 1:612 b-Dimethylsulfoniopropionate (DMSP), features, 1:158–159 3-Dimethylsulfonium-propionate (DMSP), estuaries, gas exchange in, 3:5–6 Dinav, 4:770F Dinitrogen (N2), 4:32 fixation, 3:332, 4:33F, 4:33T, 4:35
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denitrification and, 4:35 fertilizers and, 4:35 iron availability and, 3:340, 4:35 measurement, 4:32 see also Nitrogen (N); Nitrogen cycle Dinoflagellates, 3:446 Alexandrium spp., 4:440, 4:441F bioluminescence, 1:376, 1:377T, 5:492 definition, 1:677 effects of turbulence, 5:492–493 genomics, 3:556–557 lipid biomarkers, 5:422F paleothermometric transfer functions and, 2:111–112 red tides, fossil turbulence, 2:619, 2:619F symbiotic relationship with radiolarians, 3:9 zooxanthellae, 1:665 see also Microphytobenthos Diomedea cauta (shy albatross), 4:593, 5:240 Diomedea chlororhynchos (yellow-nosed albatross), 4:594, 4:596 Diomedea chrysostoma (gray-headed albatrosses), 4:594–595, 4:596, 5:240, 5:252 Diomedea epomophora (royal albatross), 4:590 Diomedea exulans (wandering albatross), 4:590, 4:591F, 4:594, 4:596, 5:240 Diomedea immutabilis (Laysan albatross), expansion of geographical range, 4:593, 5:260 Diomedea melanophrys, 4:596 Diomedeidae see Albatrosses; see specific species Direct contact condenser (DCC), 4:170 Direct deposit feeders, 1:351–352, 1:356 Direct insertion, forecast data, 2:7 Direct numerical simulation (DNS), 5:134 differential diffusion, 2:115–116 Discarding ecosystem effects, 2:201–204, 2:546, 4:233 fishery management, 2:516, 2:518, 2:519, 2:523 fishing methods/gears, 2:544–546 problem solutions, 2:203–204 regional distribution, 2:202, 2:202F Discharge contaminants, coral disturbance/destruction, 1:671, 1:673–674 Discontinuous regime shifts, 4:702 Baltic Sea, 4:704 Discosphaera tubifera coccolithophore, 1:606F Discovery, HMS (1794-5), 5:410 Discovery Expedition, Continuous Plankton Recorder, 1:630, 1:631F Discovery Gap, 2:565F, 2:569 Discrete Depth Plankton Sampler (DDPS), 6:362–363, 6:363F Discretization, 4:92
474
Index
Diseases oyster farming, risk to, 4:283–284 see also Mariculture diseases Dish structures, 5:463 Dispersal, exploited fish, population dynamics, 2:179F, 2:180 Dispersants, oil pollution, 4:193–194 Dispersion bubbles, 1:440–442 deep ocean see Deep ocean from hydrothermal vents see Hydrothermal vent dispersion (from) shallow water, 1:118 Dispersion diagram, interface waves, 1:89, 1:89F Dispersion relationship, surface, gravity and capillary waves, 5:578 Dispersive waves, 5:575–576 Dissimilatory nitrate reduction to ammonium, 4:43–44 Dissipation, turbulence see Turbulence, dissipation Dissipation profiling, 6:146–147 Dissolved carbon dioxide see Carbon dioxide (CO2), dissolved Dissolved gases, diffusion coefficients, 1:147T Dissolved inorganic carbon (DIC), 4:89–90, 4:96–97 ariation of d-carbon-13, 5:529, 5:529F atmospheric carbon and, 4:105 carbon dioxide solubility and, 1:479 components, 1:610 nitrate vs., 4:682, 4:683F oceanic carbon cycle, 1:479, 1:480, 1:483, 1:483F, 1:484F vertical gradient, 1:480–481, 1:481F phytoplankton growth impact on concentration, 4:680–681, 4:681F, 4:682F radiocarbon and, 4:111–112 river fluxes, 3:397 vertical profile, 4:680, 4:682F Dissolved inorganic nitrogen (DIN), eutrophication, 2:307, 2:308T Dissolved inorganic phosphorus (DIP) eutrophication, 2:308T total,, river water, 3:395T turnover rate in surface waters, 4:409–410, 4:411T see also Phosphorus cycle Dissolved nitrogen inorganic, eutrophication, 2:307, 2:308T isotope analysis, 4:40–41 isotope ratios, 4:50 total see Total dissolved nitrogen (TDN) see also Dissolved organic nitrogen Dissolved organic carbon (DOC), 1:168 biological pump contribution, 1:481–483, 1:483F, 1:484F particulate organic carbon vs., 1:484–485 fluorometry, 2:593, 2:593T river fluxes, 3:397
Dissolved organic matter (DOM), 3:805 colored see Colored dissolved organic matter (CDOM) definition, 4:337, 4:684 depth profile, 5:427F fluorometry, 2:593, 2:593T high-molecular-weight (HMW) compounds, 5:426 microbial food web, 3:800–801 nutrient transport and, 4:684 as optical constituents of sea water, 4:624 radiocarbon tracing, 5:426 as source of primary particles, 4:331F, 4:332 transient accumulations in upper ocean, 1:271–272 use by bacterioplankton, 1:269, 1:271 Dissolved organic nitrogen (DON), 1:123, 4:32, 4:40–41, 4:46–47 depth distribution, 4:35–36, 4:37F determination, 4:32 isotope levels, 4:50 remineralization, 4:45 see also Nitrogen cycle Dissolved organic phosphorus (DOP) research, 4:409 turnover rate in surface waters, 4:409–410, 4:411T see also Phosphorus cycle Dissolved oxygen see Oxygen (O2), dissolved Dissolved reactive phosphate (TRP), redox cycling and, 1:542 Dissostichus eleginoides (Patagonian toothfish) habitat, 4:226, 5:517 open ocean demersal fisheries, 4:230F, 4:232 FAO statistical areas, 4:231T, 4:232 Dissostichus mawsoni (Antarctic toothfish), habitat, 5:517 Distant water fisheries, Salmo salar (Atlantic salmon), 5:2, 5:5–6, 5:6F Distributed observation systems, 4:483F Distribution algae, 5:325F Anguilla eels, 2:208, 2:209T beaked whales, 3:645–646 cephalopods, 1:524 coastal lagoons, 3:377, 3:378F, 3:378T coccolithophores, 1:607 cold-water corals, 1:615–616, 1:616–618 copepods, 1:642–644 coral reef fishes, 1:655 coral reefs, 1:667 dolphins and porpoises, 2:156 fiordic ecosystems, 2:359 fish, 2:472–473 fish tolerances/limits, 2:368 gelatinous zooplankton, 3:18 herring, 4:364 intertidal fishes, 3:280, 3:281T mackerels, 4:368 macrobenthos, 3:467
(c) 2011 Elsevier Inc. All Rights Reserved.
mangroves, 3:498–499, 3:499, 3:499T, 3:500F meiobenthos, 3:729 mesopelagic fishes, 3:748–749 micronekton, 4:1 microphytobenthos, 3:811–812 plankton, 4:454 planktonic foraminifera, 4:606 primary production, 4:572–577 radiolarians, 4:613–614 salmonids, 5:30 sardines, 4:366–367 seabirds, 5:279 seaweeds, 5:325F sperm whales, 3:645–646 sprats, 4:366 Distributional techniques, pollution, effects on marine communities, 4:533, 4:535–536 Diurnal jet, 4:224 Diurnal tides equilibrium tide, 6:34 internal tides, 3:259 tidal currents, 1:596–597 Diurnal vertical migration, 2:216, 4:134 copepods, 1:647–648, 1:648F deep-sea fishes, 2:70 fish larvae, 2:387 mesopelagic fishes, 3:750–751 micronekton, 4:3 plankton, 4:453 zooplankton, 2:363 Dive cycles, gliders (subaquatic), 3:62–63 Divergent continental margins, 4:139, 4:140F Diversity of marine species see Marine biodiversity Diving Alcidae (auks), 1:172 beaked whales (Ziphiidae), 3:646, 3:647F bottlenose whale, 3:583T elephant seals see Elephant seals gliders, 3:62 mammals (marine) see Marine mammals pinnipeds (seals) see Pinnipeds (seals) relationship with archaeologists, 3:700 scuba, corals, human disturbance/ destruction, 1:675 seabirds, 5:230, 5:265, 5:266 flying vs, 5:520–521 sea otter, 5:197–198, 5:198F sperm whales (Physeteriidae and Kogiidae), 3:583T, 3:646 Diving bell, Halley, Dr Edmund, 3:513 Diving petrels, 4:590 migration, 5:240–242, 5:241T see also Procellariiformes (petrels); specific species Diving tourism, corals, human disturbance/destruction, 1:675 DMSP (United States Defense Meteorological Satellite Program), 5:80, 5:81–82, 5:84F, 5:85F, 5:88–89, 5:88F DNA, fluorescent tagging, 2:583
Index DNRA see Dissimilatory nitrate reduction to ammonium DNS see Direct numerical simulation D/O see Dansgaard–Oeschger (D/O) events DOC see Dissolved organic carbon (DOC) Docking, autonomous underwater vehicles (AUV), 4:477, 6:263–265 Doliolum nationalis, North Sea, 1:638–639 Dolomite, 5:552 Dolphin 3K ROV, 4:746T Dolphinfish (Coryphaena hippurus) annual catch, 4:240 utilization, 4:241 ‘Dolphin-free’ tuna stamp, 1:652 Dolphins (Delphinidae), 2:149–154 acoustic scattering, 1:69 beak and teeth, 2:149–153, 2:153F body shape, 2:153F classification, 2:154 color patterns, 2:153, 2:154F dorsal fin, 2:153, 2:153F feeding in ocean gyre ecosystems, 4:135 mortality, tuna fishing-related, 4:241–242 oceanic see Oceanic dolphins river, 3:606–607T river dolphins, 2:154, 2:154F distribution, 2:156 trophic level, 3:623F size ranges, 2:153, 2:153F see also Dolphins and porpoises; Odontocetes (toothed whales) Dolphins and porpoises, 2:149–161 behavior and social organization, 2:158–159 feeding, 2:158 leaping and bowriding, 2:158, 2:158F multi-species feeding frenzy, 2:158F socializing, 2:158–159 conservation status/concerns, 2:159–160 contaminants, 2:160 directed fisheries, 2:159 incidental mortality, 2:159–160 live captures, 2:160 noise pollution, 2:160 statistics, 2:159 distribution, ranging patterns and habitats, 2:156–157 diving ability, 2:156 global distribution, 2:156 habitats, 2:156 ranging patterns, 2:156–157 dolphins see Dolphins (Delphinidae) evolution, 2:155 archaeocetes, 2:155 rise of modern families, 2:155 feeding ecology, 2:157 influence of prey distribution, 2:157 specialization within groups, 2:157 specialization within water column, 2:157 tooth size and prey, 2:157
life history, 2:155–156 density-dependent responses, 2:155–156 development pace, 2:155 gestation period and calf numbers, 2:155 life spans, 2:155 threats, 2:155 physical descriptions and systematics, 2:149–154 appendages, 2:149 body shape, 2:149 countershading, 2:149 cranial features, 2:149 genital and anal openings, 2:149 peduncles, 2:160 rostrums, 2:160 sexual dimorphism, 2:149 species diversity, 2:149 vertebral column, 2:149 porpoises see Porpoises sensory systems and communication, 2:157–158 echolocation, 2:157 smell, vision and touch, 2:157 whistles, 2:157–158 species diversity, 2:150–152T vernacular names confusion, 2:154–155 DOM see Dissolved organic matter (DOM) Doomed rift, 4:599F definition, 4:597 DOP see Dissolved organic phosphorus (DOP) Doppler current meters see Acoustic Doppler current meters Doppler current profiler, island wakes, 3:344–345 Doppler principle, marine animals and, 1:62 Doppler relationship, waves on currents, 5:577 Doppler shift/shifting and float tracking, 2:178 vortical modes, 6:287, 6:288–289 Doppler velocity log (DVL), 4:478 Dorado-class AUVs, 4:476F, 6:262, 6:263T Double diffusion, 3:202 fine-scale vortical mode generation mechanism, 6:287–288 Double-diffusive convection, 2:162–170, 5:353–354 global importance, 2:168–170 horizontal, 2:168 intrusions, 2:168, 3:295–297, 3:296F, 3:298 laboratory experiments, 2:579, 3:376 salt fingers, 2:162–166, 2:165F see also Salt fingers see also Differential diffusion; Diffusive convection; Intrusions; Mixing; Turbulence Dovekie (Alle alle), 1:171, 1:173F Dover, Straits see Strait of Dover DOWB (deep ocean work boat), 3:513
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Downward irradiance diffuse attenuation coefficient, 4:381 shortwave, spectrum of, 4:380–381, 4:381F Downwelling, 4:129F Baltic Sea circulation, 1:293–294, 1:294F irradiance, 1:391–393, 3:246–247, 5:114 Langmuir circulation, 3:405, 3:411 submesoscale, plankton distribution, 5:481, 5:482F tidal mixing fronts, 5:395–396 DPASV see Differential pulse anodic stripping voltammetry Dpm, definition, 4:651 Drag flowing water on seabed, 6:143, 6:145–146 gliders, 3:63 and endurance, 3:62 of towed cables see Tow cable drag wind at sea surface, 5:536–537, 6:352 see also Drag coefficient; Wind stress Drag coefficient, 3:107T, 3:200–201, 6:194 flowing water on seabed, 6:143, 6:145–146 hurricanes, 6:208 induced, towed vehicles, 6:69 normal, tow cable drag, 6:66, 6:66F, 6:71, 6:71F tangential, tow cable drag, 6:66–67, 6:66F tow cables see Tow cable drag wind on sea surface, 1:150, 3:107, 3:107T, 5:202–203, 5:530–531, 5:536–537, 6:192–193, 6:193, 6:194, 6:208, 6:341, 6:350, 6:352 see also Wind stress wind speed and, 6:194F Dragonfishes (Pachystomias spp.), 2:453 Drainage basin, sediment discharge to rivers, 4:755 Drake Passage, 1:178, 4:127, 4:127F Antarctic Circumpolar Current, 1:739–740, 1:740F ferromanganese deposits, 1:259 paleoceanography climate and, 4:304 climate models in, 4:305 closure, opening of Central American Passage and, 4:305–306, 4:306F opening, 1:511–512, 4:304, 4:304F Drake Passage effect, 4:325 Draupner platform New Year wave, 4:777–778 rogue wave, 4:771F Drebel, Cornelius van, manned shallowwater submersibles, 3:513 Dredged depressions, environmental impact, 4:187 Dredges/dredging, 2:538–539, 4:519 boat, 2:539, 2:539F, 3:901–902, 3:901F, 3:902F
476
Index
Dredges/dredging (continued) dredged material, pollution see Pollution solids habitat modification effects, 2:204–205 hand, 2:539 mechanized, 2:542, 2:543F molluskan fisheries, harvesting methods, 3:901–902, 3:901F, 3:902F regulations, 3:903 seabed effects, 2:204–205 see also Pollution solids Dreissena bugensis (quagga mussel), population increases, ecological effects, 3:908 Dreissena polymorpha (zebra mussel) population increases, ecological effects, 3:908 transport in bilge water, 5:407 Drift bottles, 3:445–446 Drifter Data Assembly Center, 2:173 Drifters, 2:171–178, 2:171–172, 4:117F, 6:261–262 Black Sea, 1:411F data interpretation, 2:171 drogues, depth, 2:173–174 flotsam and jetsam, 2:172 other, 2:172 position, determining, 4:117 problems, 2:173 sea bottom, 2:172 ships, 2:172 tracking, 2:172–173 see also Float(s) Drift ice, 5:159 conservation law, 5:162–163 equation of motion, 5:164–165 drift in presence of internal friction, 5:166–167, 5:166F drift problem, 5:165–166, 5:166–167 free drift, 5:165–166, 5:166–167, 5:166F stationary, 5:165 landscape features, 5:159 modeling, 5:167 rheology, 5:163–164 Drifts, sediment see Deep-sea sediment drifts Drilling, 2:37 closed hole system see Riser drilling deep-sea technology see Deep-sea drilling; Deep-sea drilling, methodology open hole system see Nonriser drilling Drilling programs, 2:45–46 deep-sea see Deep-sea drilling new, future developments, 2:53–54 Drill pipe, 2:37 Drive fisheries, 2:160 Drizzle, 6:165 DRM see Detrital (depositional) remanent magnetization (DRM) Drogues, 2:171–172, 2:172F depth, 2:173–174 RAFOS float, 2:177 WOCE drifter, 2:173 Dropwindsonde observations, 6:306
Droughts, El Nin˜o Southern Oscillation (ENSO) and, 2:238–239 Drowned river valleys, 2:299 Dry bulk carriers, 5:403–404 Capesize bulkers, 5:402, 5:403–404, 5:403T charter rates, 5:404T charters, 5:403, 5:404T dry bulk fleets, 5:403T, 5:404T, 5:406T Panamax bulkers, 5:402–403, 5:403T see also World fleet Dry deposition, 1:250, 1:252 parametrization, 1:252 DSDP see Deep Sea Drilling Project (DSDP) DSL-120A, 6:256F, 6:256T DSL-120 towed multibeam sonar, 2:27F Dual tracer release experiments, 6:89–90 tracer concentration ratio, 6:89–90 ‘Dual tracer technique’, 1:153 Ducted waves, acoustics in marine sediments, 1:79, 1:79F Du/dt, 6:158 Duelling propagator system definition, 4:602F microplate formation, 4:601, 4:603 Dugong (Dugong dugon), 3:594–595, 5:437, 5:437F conservation status, 3:608T cultivation grazing, 3:603 ecology, 5:442 exploitation, 3:640, 5:442–443 future outlook, 5:445–446 home ranges, 3:603 mating behavior, 5:441–442 morphology, 5:439–440 movement patterns, 3:603 population biology, 5:442 trophic level, 3:622 see also Sirenians Dugongidae, 3:595, 3:608T classification, 5:436 extinct species, 3:595 Steller’s sea cow, 3:594–595, 3:595, 5:436–437, 5:437F living species see Dugong (Dugong dugon) see also Sirenians Dumping at sea see Ocean dumping Duncan Basin, Cape Town, seiches, 5:349 Dunes, 3:37–38 building, coastal engineering, 1:587 gaps, plugging, 1:583 modification, 1:587–588 notching, 1:583 removal, 1:581 Dunite, 5:363–364 Durban, Agulhas Current, 1:129F, 1:131–132, 1:131F, 1:133, 1:133–134 Dust, 1:249–250, 1:249T atmospheric concentration, 1:249T deposition rates, 1:253F, 1:254T Dust pulses, 1:121–122
(c) 2011 Elsevier Inc. All Rights Reserved.
Dust storms, particle flux variability, 6:1–2 Dutch western Wadden Sea, eutrophication, 2:308T DVL (Doppler velocity log), 4:478 Dwarf spinner dolphin (Stenella longirostris roseiventris), 2:153 DWBC see Deep Western Boundary Current (DWBC) Dynamics, of Earth’s environment, 2:47–49 Dynamic sea surface topography, see also Satellite altimetry Dynamic topography see Geopotential anomaly measurements Dynamic tracers see Potential vorticity Dynamite fishing, coral impact, 1:652–653, 1:672
E EAC see East Australian Current (EAC) EACC see East African Coastal Current (EACC) Early diagenetic ferromanganese nodules, 1:258 Early Eocene Climatic Optimum (EECO), 4:323 EARP 99Tc pulse study, Sellafield, UK, 4:83, 4:87 Earth climatic system, 2:47, 2:48F early history, 4:261 elastic deformation, 3:53 environment, dynamics, 2:47–49 history, ocean floor record see Ocean floor interior, dynamics, 2:49 loss of water from surface see Origin of oceans magnetic field see Geomagnetic field; Magnetic field mantle see Mantle orbit, glacial cycles and, 4:505–507, 4:505F see also Milankovitch variability origins of life on, 2:34 oxidation, 4:263 radiation budget, 3:114, 3:114F tectonic cycle, 2:49, 2:49F viscosity, sea level changes and, 3:49 Earth models of intermediate complexity (EMIC), 4:512 Earth Observing System (EOS), 5:82, 5:97 Earthquakes accretionary prisms, 1:34–35 acoustic noise, 1:99 Alaska (1964), seafloor displacement, 6:131–132 centroid depth, 3:844F Gorda ridge, 3:844F interplate fault ruptures, seafloor displacement, 6:131 Juan de Fuca ridge, 3:844F
Index magnitude and ridge spreading rate, 3:841–843 ocean ridges, spreading rate and magnitude, 3:841–843 plate boundary transforms, 3:840 sediment transport process initiation, 5:450 seismometer detection, 3:838 spreading-center, 3:841–843 tsunamis and, 6:127, 6:129–132, 6:130F see also Seismicity Earth Radiation Budget Experiment, 3:119 Earth Summit, Agenda 21, 1:600 Earth System Models (ESM), 4:102, 5:133 EASIW, temperature-salinity characteristics, 6:294T, 6:297F East African Coastal Current (EACC), 1:730, 1:731, 3:234, 5:495 current measurements, 5:495, 5:496F flow, 5:495, 5:496F during NE monsoon, 5:495 under onset of SW monsoon, 5:495 East Antarctic Ice Sheet disintegration, 5:184 see also Antarctic Ice Sheet East Australian Current (EAC), 2:187–196, 3:449, 5:312–313 characteristics, 2:187 continental shelf effects, 2:194–195, 2:196F Cook, Captain James on, 2:187 depth of no motion, 2:187–189, 2:195 eddies, 2:187F, 2:191–194, 2:191F, 2:192F anticyclonic, 2:190F, 2:191, 2:195 coalescence, 2:193–194 current measurements, 2:191F encirclement, 2:191–192, 2:192F formation process, 2:191–192, 2:191F rotation period, 2:192, 2:195F cyclonic, 2:193, 2:195 effects, 2:193, 2:196F Lort Stokes, J on, 2:191 flow, 2:189, 2:195, 4:287F mesoscale eddy, 3:758–759, 3:759F, 3:760F overshooting of Tasmania, 2:191–192, 2:193F Rossby wave propagation, 2:187–189, 2:191–192, 2:195 sea surface topography, 2:187–189, 2:188F ridge, 2:187–189, 2:195 sources, 2:187, 2:187F, 2:188F, 2:189, 2:189F, 2:195 steric height, 2:187–189, 2:188F, 2:195 volume transport, 2:189–191 see also Pacific Ocean equatorial currents East China Sea ERS-1 SAR image, 5:111–112, 5:112F Kuroshio Current, 3:359–360, 3:360F density front, 3:360
frontal meanders, 3:360 geostrophic volume transport, 3:359–360 seasonal cycle, 3:359–360 time-series, 3:359–360, 3:361F see also Kuroshio Current Easter microplate, 4:601, 4:602F, 4:604F deformed core, 4:601, 4:603 evolution, 4:602–603, 4:603 geometry, 4:602, 4:603 origin, 4:603 Pito Deep, 4:602, 4:602F rotation velocity, 4:602–603 Eastern Arctic, mean ice draft, 5:152F Eastern Atlantic Subarctic Intermediate Water (EASIW), temperature–salinity characteristics, 6:294T, 6:297F Eastern Australia, continental shelf, effects of East Australian Current, 2:194–195, 2:196F Eastern boundary current(s) Ekman transport, 6:342 sea-air heat flux, 6:339 Eastern boundary current ecosystems continental margin area, 4:257F, 4:258T continental margins, primary production, 4:259T Eastern Equatorial Pacific, mixed layer seasonal variation, 6:342–343 Eastern Galapagos Spreading Center, MORB composition, 3:819F, 3:820F, 3:821, 3:822F Eastern Indian Ocean currents, 1:730–731 see also Indian Ocean Eastern Lau Spreading center, spreading rate, 3:878 Eastern Mediterranean, 1:748–751 morphology, 1:744, 1:745F thermohaline circulation, 1:748 deep, 1:750F, 1:751 intermediate layer, 1:749F, 1:751 upper, 1:748, 1:748F see also Thermohaline circulation see also Mediterranean Sea Eastern Mediterranean basin, Mediterranean Sea circulation bottom topography, 3:710, 3:711F geography, 3:710, 3:711F jets and gyres, 3:718–720, 3:719F salinity, 3:715F thermohaline circulation, 3:714–715 see also Eastern Mediterranean Transient (EMT) Eastern Mediterranean Deep Water (EMDW), 1:745–746, 3:713F, 3:717 formation, 3:712–714 salinity, 3:715F Eastern Mediterranean Transient (EMT), 3:716, 3:720, 3:724 Eastern North Atlantic Central Water (ENACW), temperature–salinity characteristics, 6:294T, 6:297F
(c) 2011 Elsevier Inc. All Rights Reserved.
477
Eastern North Pacific Central Water (ENPCW), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F Eastern North Pacific Transition Water (ENPTW), temperature–salinity characteristics, 6:294T, 6:297F, 6:298 Eastern oyster (Crassostrea virginica), 2:489 mariculture, environmental impact, 3:908 Eastern Pacific buoyancy profile, 6:196F salinity profile, 6:196F temperature, 6:196F Eastern South Pacific Central Water (ESPCW), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F Eastern South Pacific Intermediate Water (ESPIW), temperature–salinity characteristics, 6:294T Eastern South Pacific Transition Water (ESPTW), temperature–salinity characteristics, 6:294T Eastern tropical Pacific Ocean, see also Pacific Ocean East Greenland Current (EGC), 1:724, 4:122, 4:793 nuclear fuel reprocessing, 4:86 transport, 1:724T see also Atlantic Ocean current systems East Kamchatka Current, 3:359F, 3:365, 4:202F, 4:204 Oyashio Current vs., 3:365–366 East Madagascar Current (EMC), 1:128, 1:128–129, 1:130, 1:130F, 1:730 see also Agulhas Current East Pacific Rise (EPR), 3:852F, 3:867–868 abyssal hills, 3:865–866 axial depth profile, 3:858F axial magma chamber (AMC), 3:854–855, 3:856, 3:858F seismic structure, 3:829–830, 3:829F, 3:834F, 3:835F axial summit trough, 3:860 cross sectional area, 3:858F crust thickness, 3:856 diking, 3:846–847 faulting, 3:864 Chipperton transform fault, 3:856, 3:858F hydrothermal seismicity, 3:847 hydrothermal vent biota, 3:133–134, 3:133F, 3:134F, 3:141F community development, 3:141F, 3:142F, 3:154–155 crustaceans, 3:136–138, 3:139F fish, 3:139–140, 3:140F zoarcids, 3:133F, 3:135, 3:135F, 3:140 tubeworms, 3:134–135, 3:135F, 3:137F, 3:139, 3:139F, 3:140F vesicomyid clams, 3:137F
478
Index
East Pacific Rise (EPR) (continued) hydrothermal vent chimneys, 3:134F black smokers, 3:134F, 3:165F Tubeworm Pillar, 3:134–135, 3:135F magma supply, 3:166–167, 3:858F MORB composition, 3:818T, 3:821–822, 3:822–823, 3:823F near-ridge seamounts, 5:294, 5:295F chain formation and plate motion, 5:294F, 5:295F, 5:296 propagating rifts and microplates, 4:602F, 4:604F see also Easter microplate; Juan Fernandez microplate seafloor and mantle structure, 3:874F seismicity, 3:843F, 3:848F seismic structure axial magma chamber, 3:829–830, 3:829F, 3:834F, 3:835F layer 2A, 3:827, 3:827F, 3:828F, 3:829F, 3:831F, 3:832F, 3:834F Moho, 3:832, 3:832–833, 3:834F topography, 3:853F volcanic activity, 3:860, 3:861–862, 3:862 Alvin observations, 3:168 floc, 2:78F, 3:860 lava flows, 3:816F Venture Hydrothermal Field 1991 eruption, vent community development, 3:154–155 volcanic helium, 6:280, 6:281F East Sakhalin Current, 4:202–203, 4:202F, 4:203 East Siberian Coastal Current, 1:220 East Siberian Sea, 1:211 sea ice cover, 5:141–142 Ebb cycle, 6:26 EBDW see Eurasian Basin Deep Water Ebullition definition, 3:7 estuaries, methane emission, 3:4 Eccentricity (orbital), 4:311–312, 4:505–506 glacial cycles and, 4:508 Echinoderms bioluminescence, 1:377T, 1:378–379 sea urchins, 4:431 Echolocation, 2:160, 3:650 dolphin see Oceanic dolphins Echo sounders bathymetry, 1:298, 1:300 resolution and beam width, 1:300 history, 3:122 see also Sonar ECMWF see European Center for Medium Range Weather Forecasts (ECMWF) Ecological models future update sources, 4:731 plankton competition, 4:722 see also Biogeochemical and ecological modeling Ecological processes domains within hierarchy of coupled models, 4:722, 4:722T
one-dimensional modeling, 4:211 Ecological research, rigs and offshore structures, 4:752 Ecology, 3:565 baleen whales (Mysticeti), 1:278–279 benthic communities, bioturbation and, 1:400 benthic foraminifera see Benthic foraminifera cephalopods, 1:528 cold-water coral reefs, 1:618–619, 1:619F coral reef fish see Coral reef fish(es) dolphins and porpoises, 2:157 see also Dolphins and porpoises fish horizontal migration, 2:403 gelatinous zooplankton see Gelatinous zooplankton hydrothermal vents see Hydrothermal vent ecology key questions, 4:92 lagoons see Lagoon(s) manatees, 5:442 marine, modeling, 4:89–104 Phaethontidae (tropic birds), 4:371, 4:376T phytobenthos see Phytobenthos planktonic foraminifera see Planktonic foraminifera Procellariiformes (petrels) see Procellariiformes (petrels) seabirds see Seabird(s) sirenians, 5:442 sperm whales (Physeteriidae and Kogiidae) see Sperm whales (Physeteriidae and Kogiidae) Economic issues demersal fishery management, 2:94–95, 2:95 marine policy analysis, 3:669 marine protected areas, 3:673–674, 3:674 pelagic fisheries, 5:472 Salmo salar (Atlantic salmon) fisheries, 5:4–5 Economic optimization model, marine policy analysis, 3:669 Economic rationality, fishery management, 2:525 Economics fisheries see Fishery economics sea level rises see Economics of sea level rise Economics of sea level rise, 2:197–200 adaptation costs, 2:198–199 economy-wide implications, 2:199 failure to adapt, 2:198 methods of adaptation, 2:198 protection and accommodation, 2:198–199 retreat, 2:199 scale, 2:199 adaptation methods/problems, 2:199 coast protection as public good, 2:199 decision analysis of coastal protection, 2:199
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‘false security’ problems, 2:199 ignoring non-immediate threats, 2:199 uniqueness of each case, 2:199 climate change concerns and, 2:197 adaptations costs, 2:197 adaptations methods, 2:197 costs of sea level rise, 2:197 see also Climate change, economics costs, 2:197–198 episodic flooding, 2:198 erosion and permanent flooding, 2:197 impacts, 2:197 indirect costs, 2:198 salt water intrusion, 2:198 wetlands loss, 2:198 distribution of impacts, 2:199–200 greenhouse gas emissions, 2:197 thermal expansion, 2:197 uncertainties, 2:200 see also Coastal topography impacted by humans; Coastal zone management Ecopath model, ecosystem-based fisheries management, 1:652 Ecophenotypes, 2:216 EcoSCOPE, 6:368 Ecosystem(s), 6:231 balance, fishery stock manipulation effects, 2:528, 2:532 biological diversity, 3:567 coastal see Coastal ecosystems coral reef/tropical fisheries, 1:652 definition, 5:519, 6:225 eastern boundary current see Eastern boundary current ecosystems enclosed experimental see Enclosed experimental ecosystems fiordic see Fiordic ecosystems fishery management, 1:652, 2:519 fishing effects, 2:201–207, 2:546–547 by-catch, 2:201–204 competitor removal, 2:205–206 degradation, ’fishing down the food web’, 1:652 direct, 2:201 discarding, 2:201–204, 2:546, 4:233 global primary production requirements, 2:201, 2:201T indirect, 2:201 open ocean demersal fisheries, 4:233 predator removal, 2:205 prey removal, 2:205 species interactions, 2:205 species replacements, 2:206, 2:206F large marine see Large marine ecosystems (LMEs) management, environmental protection and Law of the Sea, 3:441 marine protected areas impact, 3:674–675, 3:675 monsoonal see Monsoonal ecosystems oceanic gyre see Ocean gyre ecosystems planktonic see Planktonic ecosystem polar see Polar ecosystems
Index protection, environmental protection and Law of the Sea, 3:441 subpolar see Subpolar ecosystems tropical see Tropical ecosystems upwelling see Upwelling ecosystems western boundary current see Western boundary current ecosystems Ecosystem Monitoring Program (CEMP), Commission for the Conservation of Antarctic Marine Living Resources, 5:519 Ecuador, water, microbiological quality, 6:272T Eddies Agulhas Current northern, 1:133 southern, 1:133, 1:133F, 1:133T Alaska Current, 1:457–458, 1:458F Antarctic Circumpolar Current, 1:187 Arctic Ocean, 1:220–221, 1:221F benthic flux and, 4:493 Black Sea, 1:407–409, 1:409, 1:412F, 1:413F vertical oxygen penetration and, 1:412F coastal currents, 4:791F, 4:795 differential diffusion and, 2:114–115 diffusion, 2:324–325 East Australian Current see East Australian Current (EAC) energy transfer (large to small eddies), 5:476 gliders and, 3:59 impinging, Kuroshio Current, 3:359, 3:361F importance, 3:756 laboratory generation, 3:371–372, 3:372F Mediterranean see Meddies mesoscale see Mesoscale eddies modeling resolution and, 4:102 nutrient injection event driven by, 5:481, 5:483F oceanic, one-dimensional models and, 4:215–217 in overflows, 4:268, 4:270–271 scaling, 4:268–269 overturning circulation and, 1:189 satellite remote sensing application, 5:107F, 5:108 shedding, effects of see Island wake(s) Southern Ocean energy dissipation and, 2:267–268 Soya Current, 4:203, 4:203F sub-surface, 3:702–709 discovery, 3:708 lens, aging effects, 3:708 other subsurface lenses, 3:707–708 see also specific subsurface lenses topographic see Topographic eddies turbulence and small-scale patchiness, 5:476 turbulent see Turbulent eddies upper ocean, 6:213–214 see also entries beginning eddy
Eddy coefficient, internal tidal mixing, 3:254 Eddy correlation, 2:291–292, 3:106 Eddy correlation flux measurements, 1:153 Eddy diffusion, 2:324–325 Eddy diffusivity, 2:17, 3:271 under-ice boundary layer, 6:160–161 vertical profile, models, 4:208, 4:209–210 Eddy-driven subduction, 4:163–164 bolus velocity, definition, 4:164, 4:164F stirring, 4:160–162 subduction rate, 4:164, 4:165F tracer distributions, 4:161–162, 4:162F, 4:164 transport, 4:164, 4:164F, 4:165 Eddy fluxes, 3:447 Eddy kinetic energy (EKE), 4:118F definition, 4:117–118 Gulf Stream System, 2:557, 2:560F Eddy mixing, 2:17, 2:18–19 Eddy turnover timescale, Langmuir circulation, 3:406 Eddy viscosity, 5:576–577 under-ice boundary layer, 6:156, 6:160–161 vertical profile, models, 4:209–210 Edge waves, 6:314, 6:314–315 coastal trapped waves, 1:591, 1:592, 1:593 atmospheric pressure forcing, 1:596 dispersion, 1:593F storm surges, 5:532 cross-shore structure, 6:315F dispersion, 6:314, 6:316F kinematics, 6:315T see also Infragravity waves; Waves on beaches EECO see Early Eocene Climatic Optimum Eel pouts see Zoarcid fish Eels (Anguilla), 2:208–217, 2:395–396F catadromous species, 2:208 diversity/distribution, 2:208, 2:209T reproduction requirements, 2:208 evolution/paleoceanography, 2:214–215 evolution, 2:215 separation, 2:215 fisheries/aquaculture, 2:215 culture operations, 2:215 glass eel fisheries, 2:215 world catches, 2:215 genetics/panmixia, 2:214 geographic structuring American, Japanese, Australian and New Zealandic eels, 2:214 European, African and Icelandic eels, 2:214 relationships debates, 2:214 Tucker’s hypothesis, 2:214 failure on genetic grounds, 2:214 failure on oceanographic grounds, 2:214 growth rate, 2:211 age determination, 2:211
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479
influencing factors, 2:211 variations, 2:211 life cycle, 2:208–210, 2:210F eggs, 2:210 elvers and yellow eels, 2:210–211 pigmentation development, 2:210–211 glass eels, 2:210 metamorphosis, 2:210, 2:214 knowledge base, 2:208 leptocephali, 2:210, 2:216 larval duration, 2:210 mode of nutrition, 2:210 morphology, 2:210 overview, 2:208 silver eels, 2:212 fecundity, 2:212, 2:212T spawning areas/times, 2:208–210 American/European eels, 2:209 Japanese/Australian/ New Zealandic/tropical eels, 2:210 lack of observation in nature, 2:208–209 migration, 2:403–404 morphology of life stages, 2:208 oceanic migration, 2:212–213, 2:403–404 glass eels, 2:214 metamorphosis, 2:214 selective tidal transport, 2:214 leptocephali, 2:213–214 daily vertical migration, 2:213 European, 2:214 horizontal migration, 2:213–214 vertical distribution, 2:213 silver eels, 2:212, 2:212–213 migration lengths, 2:213, 2:213T research technology, 2:213 selective tidal transport, 2:212 swimming ability, 2:212–213 travel routes/rates, 2:213 orders, 2:208 plasticity/adaptation, 2:211 diet, 2:211 habitat selection, 2:211 metamorphosis, 2:210, 2:211–212, 2:214 size at, 2:211 yellow eels to silver eels, 2:211–212 sex determination/differentiation, 2:211 sexual dimorphism, 2:211 size and age at maturity, 2:211, 2:212T status of populations, 2:215–216 downward trend, 2:215 recruitment, 2:215 EEZ see Exclusive economic zone (EEZ) Effluent layer, hydrothermal plumes, 2:132, 2:133F EGC see East Greenland Current (EGC) Eggs Alcidae (auks), 1:176 cephalopods, 1:527–528 copepods, 1:647
480
Index
Eggs (continued) eels (Anguilla), 2:210 fish, see also Fish reproduction EIA (environmental impact assessment), 4:530 EIC see Equatorial Intermediate Current (EIC) Eider duck, fisheries interactions, 5:270–271 EKE see Eddy kinetic energy (EKE) Ekman, V.W., 6:155 Ekman bottom boundary layer, 3:451–454 see also Ekman pumping; Ekman transport Ekman depth, 2:224 definition, 6:350 Ekman dynamics, 6:350–351 Coriolis parameter, 6:350 Fick’s Law, 6:350 Ekman equation, 6:141–142 Ekman height, 6:143 Ekman layer, 2:216, 6:226–227, 6:231 balance of forces, 6:142F continental shelf effects of East Australian Current, 2:194–195 currents, 2:222 definition, 2:195, 4:120 thickness d, 6:59 turbulence, 6:141–143 under-ice boundary layer (UBL), 6:155–157 see also Ekman transport Ekman number, island wakes, 3:344 Ekman pumping, 2:222–227, 4:121F, 6:350–351, 6:351, 6:352, 6:353 Baltic Sea circulation, 1:292 coastal downwelling, 2:226 coastal upwelling, 2:226, 2:226F columnar geostrophic flow, 6:351 definition, 4:120, 6:350–351 heat transfer, 4:124 Intra-Americas Sea (IAS), 3:293–294 North Atlantic subduction rates, 4:159F of ocean current gyres, 2:225–226, 2:225F tritium, 6:121 velocity, 6:351 curl of surface wind stress, 6:351 equation, 6:351 factors affecting, 6:351 see also Ekman transport; Sverdrup relation Ekman spiral, 2:223–224, 2:224, 2:224F, 4:209, 6:143, 6:214, 6:350 Ekman suction, 6:351 definition, 6:350–351 Ekman theory, of wind-driven currents, 2:222–224 Ekman transport, 2:222–227, 4:120–121, 4:121F, 4:715, 6:142F, 6:214, 6:341–342 Baltic Sea circulation, 1:292 coastal downwelling, 2:226 coastal upwelling, 2:226, 2:226F
definition, 6:350 governing equations, 6:141–142 Intra-Americas Sea (IAS), 3:293–294 island wakes, 3:346 North Pacific Current, 1970s, 4:710–711 pumping and see Ekman pumping relation, 2:224–226 sea surface temperature and, 6:342 spatial variation, 2:222 velocity profile, 6:142F see also Ekman layer; Ekman pumping Ekman transport relation, equation, 2:223, 2:224 Ekofisk oil rig, MDS plot, 4:537–538, 4:537F Elasmobranchs, 2:471–472, 2:472F, 4:234 biomass, north-west Atlantic, 2:505–506, 2:506F, 2:509, 2:509F body fluids and osmoregulation, 2:474 buoyancy, 2:473 differences from teleosts, 2:471–472 fins, 2:393 fishing effects, 2:206 main features, 2:472F osmoregulation, 2:474 paucity of habitats, 2:472 skeleton, 2:472 Elastic flexure, 3:85 Electrical components, remotely operated vehicles (ROVs), 4:745 Electrical conductance (G), 2:247 Electrical conductivity see Conductivity Electrically scanning microwave radiometer (ESMR), 5:81, 5:82, 5:84 Electrically scanning thinned array radiometer (ESTAR), 5:129 Electrical properties of sea water, 2:247– 254 conductivity see Conductivity electromagnetic wave propagation, 2:251–252 Maxwell equations, 2:251–252 galvanic couples, 2:247, 2:252 permittivity see Permittivity polarization, 2:248, 2:251 permittivity and, 2:251 velocity measurement, 2:252–253 with artificial magnetic fields, 2:253 in Earth’s magnetic field, 2:253 see also Inherent optical properties (IOPs); Irradiance; Single Point Current Meters Electrodes for benthic flux measurement, 4:489–490, 4:492 electric field creation in electrolytes, 2:248, 2:248F galvanic couples, 2:247, 2:252 sacrificial, 2:252 Electrolytic dissociation, sodium chloride, 2:247–248 Electromagnetic Autonomous Profiling Explorer (EM-APEX) floats, 6:207–208
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Electromagnetic current meters (ECMs), 1:46, 5:429F, 5:430T, 5:431–432, 5:432F Faraday effect as basis of, 2:253, 5:432, 5:432F Electromagnetic radiation, absorption, 1:7–8 Electromagnetic velocity sensors measurements in Earth’s magnetic field, 2:253 measurements with artificial magnetic fields, 2:253 Electromagnetic wave propagation, sea water see Electrical properties of sea water Electromechanical (EM) cable, in moorings, 3:927 Electron affinity, 1:540–542 Electronic profiling systems, 6:291, 6:299 Electrowinning, 3:897 Elemental distribution, 2:255–260, 2:256T historical review, 2:255 oceanic profiles, 2:258 concentrations, 2:256T vertical, 2:258, 2:259F particle association, 2:258–260 speciation, 2:256T, 2:260 technical challenge, 2:255, 2:260 contamination problems, 2:255, 2:260 see also Conservative elements (sea water); Rare earth elements (REEs); Refractory metals; Trace element(s); Transition metals Elemental mercury (Hgo) estuaries, gas exchange in, 3:6 see also Mercury (Hg) Element ratios tracer applications, 3:455–456 see also Cadmium/calcium ratio; Protactinium/thorium ratio Elephant seals adaptation to light extremes, 3:587–588 diving, 3:615 ability, 3:583T adaptations, 3:583, 3:583F, 3:584T profile, 1:362F, 1:363 mating strategies, 3:617 myoglobin concentration, 3:584T Northern (Mirounga angustirostris), 3:629–630, 4:135 Southern (Mirounga leonina), 5:513 telemetry, 1:362F, 1:363 see also Phocidae (earless/‘true’ seals) Elminius modestus, thermal discharges and pollution, 6:14 El Nin˜o, 2:241, 2:243F changes during late 1970s, 2:245 as consequence of change in winds, 2:243–244 global sea level variability, contribution to, 5:61–62, 5:62F intense, in 1997, 2:245 La Nin˜a change to, 2:242, 2:244 limited predictability, 2:245
Index satellite remote sensing of SST, 5:97–99 coupled ocean-atmosphere system perturbations, 5:97 normal Pacific SST distribution, 5:97–98 seasonal predictions of disturbed patterns, 5:98–99, 5:98F Warm Pool movement, 5:97–98 sea surface temperatures, 2:241, 2:241F thermocline and, 2:242, 2:243F tools for predicting, 2:241–242 see also El Nin˜o Southern Oscillation (ENSO) models warming of eastern tropical Pacific, 2:242 see also El Nin˜o Southern Oscillation (ENSO) El Nin˜o and Beyond Conference, 3:276 El Nin˜o forecasting, 5:129–130 benefits, 2:239 see also El Nin˜o Southern Oscillation (ENSO) El Nin˜o periods, 6:215 mesoscale eddies, 3:764–765 sea– air partial pressure of CO2, 1:489–491 temporal variability of particle flux, 6:6 El Nin˜o Southern Oscillation (ENSO), 1:465F, 2:228–240, 2:271–272, 2:272F, 2:279F, 3:110, 3:444–445, 4:699, 5:97 1997-1998 event human impact, 2:239 jet stream flow patterns, 2:236F precipitation and, 2:233F prediction, 2:239 sea level variability measured by satellite altimetry, 5:62–63, 5:62F sea surface temperatures, 2:229F sea temperature depth profiles, 2:234F, 2:235–237 surface winds, 2:232F Alaska Current system variability and, 1:464–465 Atlantic counterpart, 1:234, 1:236–237 California Current system variability and, 1:464–465 chlorophyll a concentrations, 5:123F coral-based paleoclimate records, 4:341–343, 4:343F, 4:344F, 4:345, 4:346 cycle, 2:228 ecological impact, 2:238 effect on primary productivity, 4:461 effect on upwelling ecosystems catch of Peruvian anchovy (Engraulis ringens), 6:230 chemical changes, 6:229–230 fish populations and, 4:704 heat flux, 2:235 human impact, 2:238–239 impact on seabirds, 5:256, 5:257 penguins, 5:527 see also Climate change, seabird responses
Indonesian Throughflow and, 3:239, 5:315 interannual variations, 2:235–238 Intra-Americas Sea (IAS), 3:287 krill distribution link to events, 5:519 mechanisms, 2:235 models see El Nin˜o Southern Oscillation (ENSO) models observations, 2:284–285 ocean-atmosphere interactions, 2:228–235 ocean color and, 5:125 ocean dynamics models, 2:280–282 delayed oscillator, 2:279F, 2:280F, 2:281–282 recharge oscillator, 2:282–283 origin of term, 2:228 oscillation, 2:235 Pacific Ocean equatorial current system variability and, 4:292–293, 4:293–294, 4:293F Pacific salmon catch impact, 5:14, 5:15 periodicity, 2:273 Peru-Chile Current System and, 4:391 prediction, 2:239 recharge-discharge mechanism, 2:281F recharge oscillator model, 2:282–283 regime shifts and, 4:699, 4:713 satellite remote sensing, 5:208–209, 5:209F, 5:210F sea level variation and, 5:181 sea surface temperatures, interannual variation, 2:237, 2:237F temperature-depth profiles, 2:273F temperature variability and, 6:167–168 thermocline depth, 2:231–234 time scale, 2:235 upwelling and, 2:235, 2:238 see also Climate change El Nin˜o Southern Oscillation (ENSO) models, 2:241–246 atmosphere circulation and, 2:242 general circulation models, 2:242 oceans and atmosphere interactions, 2:244–245 see also Ocean–atmosphere interactions oceans and thermoclines, 2:242–244 purpose, 2:243–244 Elongate mounded drifts see Deep-sea sediment drifts El Viejo, 4:709 EM-APEX see Electromagnetic Autonomous Profiling Explorer Embayments, anthropogenic trace metal enhancements, 1:200 Embiotica jacksoni (black surf perch), 2:376–377 EMDW see Eastern Mediterranean Deep Water (EMDW) Emergence, 3:33 Emerita spp. (mole-crabs), 5:52F EMIC (earth models of intermediate complexity), 4:512 Emiliani, Cesare, 2:101–103 Emiliani, Cesare´, 1:505–506
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Emiliania (coccolithophores), 3:555–556 Emiliania huxleyi coccolithophore, 1:606F, 2:105–106, 2:105F, 5:125F blooms, 1:607, 1:608F, 1:611 coccolith numbers, 1:609 genome, 1:610 research, 1:611 Emissivity, calculation, 3:320–322, 3:321F Emittance black body, 3:320 definition, 3:319, 3:320F Emperor penguin, 5:522T, 5:526, 5:527 see also Aptenodytes Empirical orthogonal functions (EOF) analysis, 4:719–720 thermocline depth, 2:285, 2:285F Ems estuary, Germany dissolved loads, 4:759T eutrophication, 2:308T EMT see Eastern Mediterranean Transient (EMT) ENACW (Eastern North Atlantic Central Water), temperature–salinity characteristics, 6:294T, 6:297F Enallopsammia profunda coral, 1:615–616 Enclosed experimental ecosystems, 3:732–747 challenges/opportunities, 3:734–740 importance of scale, 3:732 problems of scale, 3:736–737, 3:738–739, 3:740F scaling concerns, 3:737–738 size and design, 3:739F size and replicates, 3:739F types of effects, 3:739–740 control-realism trade-off, 3:732, 3:734F defined, 3:732 effective design, 3:740–741 abstraction, 3:740–741, 3:741F appropriateness, 3:741 ecosystem-specific mesocosms, 3:741 generic mesocosms, 3:741 mixing/exchange, 3:741–744 defined, 3:741–742 engineering approaches, 3:742, 3:743F intermediate scales, 3:742 rate of exchange, 3:743 residence time, 3:743–744 small scales, 3:742, 3:743F, 3:743T variations in rate of exchange, 3:744, 3:744F water-surfaces interfaces, 3:742 physical characteristics, 3:741 factors to consider, 3:741, 3:742T research objectives, 3:740 scaling considerations, 3:744–745 changes of scale, 3:744, 3:745F dimensional analysis, 3:745 numerical models, 3:745 simulation models, 3:745 spatial scaling relationships, 3:744, 3:745F
482
Index
Enclosed experimental ecosystems (continued) temporal scaling relationships, 3:746F history and applications, 3:732–734 composition/organization of communities, 3:734 history of use, 3:733–734 research difficulties, 3:734 research examples, 3:734, 3:735F, 3:736F, 3:737F styles and applications, 3:734 scale, 3:732 effects, 3:732 tools for aquatic research, 3:732 distinguishing environments, 3:732 trends in scale studies, 3:738F trends in use of field experiments and mesocosms, 3:738F useful characteristics, 3:732 Enclosed seas, hypoxia, 3:173–174 Endangered species, Pacific salmon fisheries, 5:22 Endangered Species Act (1973), USA, 5:22 ‘Endeavor Hot Vents’ marine protected area, boundary proposals, 3:675–676 Endosymbionts, deep-sea ridges, 2:75–76 coevolution and cospeciation, 2:76 invertebrate hosts bivalves, 2:76 giant tubeworms, 2:76 methane-oxidizing, 2:76 sulfur-oxidizing, 2:76 vertical transfer from adult host to offspring, 2:76 Endrin, structure, 1:552F Endurance, gliders, 3:62 En echelon volcanic ridges, 5:292, 5:299–300, 5:300F Energetically optimum speed, autonomous underwater vehicles (AUV), 4:475 Energetics of ocean mixing, 2:261–270 abyssal waters, 2:263–266 biogenic, 2:265 tidal forces, 2:265 energy dissipation pathways, 2:264–265 energy sources, 2:263–266 Energy conservation, ocean, 3:115 consumptions, mixing estimates from (Osborn method), 2:294–296 global cycling, 2:49 Energy Balance Models (EBM), 4:509 annual mean atmospheric, 4:509–512 climate/ice sheet, 4:512 Northern Hemisphere ice sheet, 4:512 seasonal atmospheric/mixed-layer ocean, 4:512 Energy budget fishery multispecies dynamics, 2:507–508 global, 2:262–263
history, network analysis see Network analysis of food webs internal, 2:262 and geothermal energy, 2:262–263 kinetic, 2:262 and advection, 2:263 potential energy, 2:262 tides and see Tidal energy; Tide(s) Energy carriers, ocean thermal energy conversion, 4:172–173 Enforcement, fishery management, 2:514, 2:524 Engine(s), gliders, efficiency, 3:63 Engineering coastal see Coastal engineering coastal circulation model applications, 1:575–576 Engineering Committee on Oceanic Resources (ECOR), 6:300 Engineering timescales, geomorphology, 3:35, 3:36F English Channel eutrophication, 2:308T metal pollution, 3:771T plankton, regime shifts, 4:713 sound propagation losses, 1:117F Engraulis (anchovies), 4:368 Engraulis japonicus (Japanese sardine), 2:486–487 multispecies dynamics, 2:505, 2:506F response to changes in production, 2:486–487 Engraulis ringens (Peruvian anchoveta), 2:375, 4:368 effects of El Nin˜o, 6:230, 6:230F see also Fisheries, and climate pelagic fishery landings, 5:469T, 5:472, 5:473F pelagic fishery management, stock fluctuations, 5:471–472, 5:472F Enhanced Actinide Removal Plant (EARP), 4:83 99 Tc pulse study see EARP 99Tc pulse study Enhancement programs see Fishery stock manipulation Enhydra lutris see Sea otter ENPCW (Eastern North Pacific Central Water), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F ENPTW (Eastern North Pacific Transition Water), temperature–salinity characteristics, 6:294T, 6:297F, 6:298 Enrichment factor (EF), 3:772–773 ENSO see El Nin˜o Southern Oscillation (ENSO) ‘Enstrophy’, 3:22 Entangling gear, 2:539–540, 2:540F fishing methods, 2:539–540, 2:540F Enteric redmouth, vaccination, mariculture, 3:523 Enteroptneusts (spaghetti worms), 3:140–141, 3:141F
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Entrainment, 2:300, 4:128 deep convection plumes, 2:15 hydrothermal plumes, 2:130, 2:131, 2:131–132, 2:131F, 2:132–133, 2:136–137 non-rotating gravity currents, 4:63–64, 4:63 coefficient, 4:63 Environmental assessments, pollution see Pollution control approaches Environmental conservation Law of the Sea, underlying principles, 3:433 duty of states, 3:433 see also Conservation Environmental gradients, seabird abundance and, 5:227–228 Environmental impact assessment, 4:530 Environmental issues affecting salmonids/salmon, see also Salmonids legal issues, shipping and ports, 5:406–407 pollution see Metal pollution; Pollution rigs and offshore structures, see also Rigs and offshore structures Environmental monitoring, by satellite remote sensing, 5:112 Environmental protection, from pollution see Global marine pollution; Pollution Environmental protection, Law of the Sea and, 3:439–440 airborne marine pollutants, 3:440–441 convention for prevention of pollution from ships (MARPOL), 3:440 enumerates pollution sources, 3:439–440 habitat and ecosystem protection, 3:441 land-based marine pollution, 3:440 movement of hazardous wastes, 3:440 ocean dumping, 3:440 persistent organic pollutants, 3:441 requires measures against pollution, 3:439 UNCLOS clarifies rights and duties, 3:439 vessel discharges, 3:440 Environmental stewardship, bathymetric maps and, 1:297 Envisat-1, 5:103 Envisat-1 MERIS, 5:118T Eocene, 4:319 Early Climatic Optimum, 4:323 ocean circulation, 4:307 d18O records, 1:508F, 1:510, 1:510F paleo-ocean modeling, 4:303 see also Cenozoic; Paleoceanography Eocene/Oligocene boundary, oxygen isotope evidence, 1:510F EOF see Empirical orthogonal functions (EOF) EOLE satellite tracking, 2:173 Eolian dust, 3:912 Eolian iron, deposition, 1:252–254 Eo¨tvo¨s correction, 3:82, 3:83
Index Eo¨tvo¨s unit, 3:80 Epibenthic predators, burrowing, 1:395 Epibenthos see Epifauna Epibionts, deep-sea ridge microbiology, 2:76–77 16S rRNA phylogenetic analysis, 2:76–77 epsilon proteobacteria, 2:76–77, 2:77, 2:78 genetic variation, environmentally induced, 2:76–77 invertebrate hosts polychaete, 2:76–77, 2:76F vent shrimp, 2:76–77 microscopic observations, 2:76–77, 2:76F Epifauna, 1:349, 1:351F, 1:356, 3:467, 3:471 see also Benthic boundary layer (BBL) Epifluorescence microscopy tool in microbial studies, 3:799 discovery of mixotrophs, 3:800 discovery of Synechococcus, 3:799–800 identifying/quantifying trophic connections, 3:799–800 problems, 3:800 use in bacterioplankton studies, 1:269, 1:272–273 Epipelagic zone, 2:160, 2:216, 4:356 see also Pelagic biogeography Epistominella exigua foraminifera, 1:346F, 1:347 EPR see East Pacific Rise (EPR) Epsilon proteobacteria, 2:76–77, 2:77, 2:78 Epstein, Sam, 1:502–503 ‘Equation of state’ (of sea water), 4:29–30, 6:379 general circulation models, 3:20 Gibbs function, 4:30 summary, 4:25 Equator ocean temperature, 2:271F thermocline depth, response to wind forcing, 2:278F wind stress by zone, 2:271F ‘Equatorial bulges,’ manganese nodules, 3:490 Equatorial currents Atlantic Ocean see Atlantic Ocean equatorial currents Pacific Ocean see Pacific Ocean equatorial currents Equatorial Intermediate Current (EIC) flow, 1:721–723, 1:723F, 4:290F, 4:291F see also Pacific Ocean equatorial currents Equatorial ocean, wind driven circulation, 6:354 Equatorial Pacific, temporal variability of particle flux, 6:4F Equatorial Undercurrent (EUC), 1:234–235, 3:230–232, 3:232F, 4:224, 6:182
flow, 1:723F, 4:287F, 4:289, 4:290F, 4:291F seasonal variation, 1:235, 3:230–232, 3:231F transport, 1:724T see also Atlantic Ocean current systems; Atlantic Ocean equatorial currents; Pacific Ocean equatorial currents Equatorial upwelling, productivity reconstruction, 5:339–340, 5:339F Equatorial waves, 2:271–287 baroclinic flow, 2:274 boundary reflection, 2:278–279 dispersion relation, 2:276F models of ENSO based on, 2:280–282 ocean response to wind perturbations, 2:276–279 shallow-water equations, 2:273–274, 2:274F free-wave solutions, 2:274–275 slowly varying winds, response, 2:279–280 wave dynamics, 2:273–274 long-wavelength approximation, 2:276 oscillatory wind forcing, 2:278 slowly varying winds, 2:279–280 see also Kelvin waves; Rossby waves Equilibrium line, definition, 3:190 Equilibrium tide, 6:33–34 constituents, 6:35 definition, 6:34 diurnal, 6:34 groups, 6:35 neap, 6:34 observed tides, comparison to, 6:34 response analysis, 6:35 semidiurnal, 6:34, 6:35 species, 6:35 spring, 6:34 Equinoxes, precession, 4:504, 4:508 Equity, fishery management goals, 2:513 Erect-crested penguin see Eudyptes sclateri (erect-crested penguin) Eretmochelys imbricata (hawksbill turtle), 5:217F, 5:218 see also Sea turtles Erignatus barbatus (bearded seal) song, 3:618–619, 3:619F see also Phocidae (earless/‘true’ seals) Eriocheir sinensis (Chinese mitten crab), 2:340 Erosion geographical cycle of, 3:34, 3:34F geomorphology rocky coasts, 3:36 sandy coasts, 3:37 see also Coastal erosion; Coastal topography impacted by humans Erosional discontinuities, 2:84–85 Error analysis, inverse modeling, 3:310 Error estimation/models, data assimilation in models, 2:2 Error subspace statistical estimation (ESSE) schemes, 2:8
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ERS-1 satellite, 5:203, 5:204T see also European Remote Sensing (ERS) satellites ERS-2 satellite, 5:203, 5:204T global sea level variability detection, 5:61–62, 5:62F see also European Remote Sensing (ERS) satellites Ertel, H, 6:285 ESA (European Space Agency), 5:74 Escherichia coli, sewage contamination, indicator/use, 6:274T Eschrichtiids see Gray whale (Eschrichtius robustus) Eschrichtius robustus see Gray whale (Eschrichtius robustus) Eskimos, polar bear hunting, 3:640 ESM (Earth System Models), 4:102, 5:133 ESMR (electrically scanning microwave radiometer), 5:81, 5:82, 5:84 Esox spp. (pike), 2:395–396F ESPCW (Eastern South Pacific Central Water), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F ESPIW (Eastern South Pacific Intermediate Water), temperature–salinity characteristics, 6:294T ESPTW (Eastern South Pacific Transition Water), temperature–salinity characteristics, 6:294T ESTAR (electrically scanning thinned array radiometer), 5:129 Estimation theory, 2:7 blending estimate, 2:7 direct insertion, 2:7 Estuaries ammonium isotope levels, 4:50 anoxia, 3:174 atmospheric deposition, 1:239–240 metals, 1:239–240 nitrogen species, 1:240–241 synthetic organic compounds, 1:241–242 biodiversity, 2:141 biogenic silica burial, 3:681T, 3:683 carbon cycling, 4:253 carbon monoxide, 1:168 circulation see Estuarine circulation colored dissolved organic matter influence, 4:415 definition, 2:299, 3:1, 3:7, 3:38, 4:253, 5:557 denitrification, 3:4, 4:253–254 equilibrium, concept of, 2:300 eutrophication, 2:307, 2:309F, 2:310F, 2:322F see also Eutrophication formation, 2:299 gas exchange, 3:1–8 across air/water interface, 3:1 gas solubility, 3:1 individual gases, 3:3–4 measurements, 3:2–3
484
Index
Estuaries (continued) models of, 3:1–2 see also specific gases geomorphology, 3:38, 3:39F barrier estuaries, 3:38 river processes, 3:38 tidal processes, 3:38 human influence, 4:254 hypoxia, 3:174–175 metal pollution processes affecting, 3:768F, 3:769 suspended particulate matter, 3:771F plankton communities, 3:658 primary production, 4:254T sediments see Estuarine sediments subterranean see Subterranean estuary tides, 2:299–300 uranium-thorium series isotopes, 6:245 zones, 2:299 Estuarine circulation, 2:299–305, 2:355–356 Baltic Sea circulation, 1:289–292 definition, 2:299 fiords, 2:356 flushing, 2:303 models, 2:304 patterns, 4:253 turbidity maximum, 2:303–304, 2:303F types, 2:300 partially mixed, 2:300–301, 2:301F salt wedge, 2:300, 2:301F well-mixed, 2:301–303, 2:302F Estuarine lagoons, formation, 3:379–380, 3:382F Estuarine sediments anthropogenic metals and, 1:549 chemical processes, 1:539–550, 1:549F elemental cycling, 1:546–547, 1:547F oxidation processes, 1:539, 1:543 structure, 1:539 types, 1:539–540 Estuary definition, 5:557 see also Estuaries Ethics, archaeology see Archaeology (maritime) Ethmodiscus rex, 3:653 Eubalaena glacialis see North Atlantic right whale EUC see Equatorial Undercurrent (EUC) Eucheuma denticulatum (red seaweed), 5:321F Eudyptes (crested penguins), 5:524–525 breeding patterns, 5:525 characteristics, 5:522T, 5:524, 5:524F distribution, 5:522T, 5:524–525 egg-size dimorphism, 5:525, 5:525F feeding patterns, 5:522T migration, 5:239 species, 5:522T, 5:524 see also Sphenisciformes (penguins); specific species Eudyptes chrysolophus (marconi penguin), 5:522T, 5:524–525 Eudyptes robustus (Snares penguin), 5:522T, 5:524–525
Eudyptes sclateri (erect-crested penguin), 5:522T, 5:524–525, 5:524F, 5:525 egg-size dimorphism, 5:525, 5:525F see also Eudyptes (crested penguins) Eudyptula, 5:523 migration, 5:239 species, 5:523 see also Sphenisciformes (penguins); specific species Eudyptula albosignata albosignata, 5:523 Eudyptula minor see Little penguin Eukaryotes, photosynthesis, 3:552–553 Euler, Leonhard, 3:389 Eulerian flow formulation, Lagrangian formulation vs., 3:389, 3:389–391, 3:390–391F, 3:393 ocean circulation, 4:115–116, 4:116–117, 4:116F Eulerian models, one-dimensional, marine ecosystems, 4:208 Eulerian reference frame, 6:157–158 Euler-Lagrange equations, 2:7 control theory in data assimilation, 2:7 Eunice norvegica worm, 1:620–621 Euphausia see Krill (Euphausiacea) Euphausiacea (krill) see Krill (Euphausiacea) Euphausia crystallarophias (ice krill), 3:353, 4:518, 5:514 Euphausia eximia, 4:389–390 Euphausia mucronata, 4:389–390 Euphausia pacifica (Pacific krill), 3:353, 3:356 Euphausia superba (Antarctic krill), 3:349, 3:350F, 4:460, 5:514 acoustic scattering, 1:67–68 aggregations, 3:354F, 3:355 see also Krill diurnal vertical migration, 3:351, 3:355 fisheries, 3:356 food sources, 3:353 life span, 3:352 Southern Ocean food web, 4:518 winter survival, 3:353 see also Krill (Euphausiacea) Euphausiids, 4:1, 4:3F acoustic scattering, 1:67–68 distribution patterns, 4:360, 4:361–362 see also Krill (Euphausiacea) Euphotic zone, 4:578, 6:231 biogeochemical processes, 4:90F mass budgets, 6:93 tracer constraints, 6:94F Eupomacentrus planifrons (damsel fish), 2:378 Eurasian Basin, 1:211 mean ice drafts, 5:153F Eurasian Basin Deep Water, 1:219 Europe see Europe/European Union (EU) European Center for Medium Range Weather Forecasts (ECMWF), 1:696, 2:328–329, 3:108, 6:51–52 European eel (Anguilla anguilla), 2:214 mariculture, stock acquisition, 3:532 see also Eels (Anguilla)
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European flat oyster (Ostrea edulis ), mariculture disease agents, 3:520T stock acquisition, 3:532 European Geophysical Society, 3:278–279 European green crab (Carcinus maenas), 2:342 European lobster (Homarus gammarus), stock enhancement/ocean ranching, 2:530 European oyster, production, 4:275T European Remote Sensing (ERS) satellites, 5:203 meteorological measurements, 5:380 revisit times, 4:739–740 see also ERS-1 satellite; ERS-2 satellite European shelf cascades, 4:265–266 internal tides, 3:263 European Space Agency (ESA), 5:74, 5:129 Europe/European Union (EU) anthropogenic reactive nitrogen, 1:245T artificial reefs, 1:227 fishing fleet vessels, decline, 2:543 maritime archaeology growth, 3:697 paleo shorelines, migration and sea level change, 3:56–58, 3:57F regional ICM initiatives, coastal zone management, 1:602 river water, composition, 3:395T water, microbiological quality, 6:272T Europium, 4:653, 4:654 dissolved, vertical profile, 4:658F see also Rare earth elements (REEs) Eurytemora affinis, Acartia tonsa and, population interaction models, 4:554 Eustigmatophytes, lipid biomarkers, 5:422F Euterpina acutifrons, stage-structured population model, 4:551F Euthecosomes, 3:15F Eutrophication, 2:306–323, 4:406, 4:685 anthropogenic, Black Sea, 4:704–705 areas, indications of importance to, 2:306, 2:306F case studies, 2:311–313 changing ratios, 2:314–315 hydrographic regime, 2:317–319 nutrients, concentrations of, 2:311–313, 2:313F, 2:314F peak loadings, 2:314–315 receiving area, size of, 2:313–314 river basin alterations, 2:315–317 riverine inputs, 2:311–313, 2:312F stratification, 2:317 coastal ecosystems, 3:173, 3:174 coastal region/seas, 2:309F conceptual model of effects, 2:319, 2:322F definition, 1:677, 2:306 harmful algal blooms (red tides), 4:459–460 historical background, 2:307 ‘hot spots’, 2:319–323
Index impact on biodiversity, 2:146 Mediterranean mariculture problems, 3:533 ‘point sources’, 2:306 processes, 2:307 output, 2:307–311 transformation, 2:307 remedial measures, 2:319–323 structuring elements, 2:307, 2:309F symptoms, 2:307 see also specific bays/estuaries/seas Eutrophic water, penetrating shortwave radiation, 4:382 Evanescent waves chemical sensors, 1:11–12, 1:12F optical fibers, 1:9, 1:9F, 1:11–12 Evaporation, 2:324–331, 3:449, 4:126, 4:131, 5:128F, 5:130 bulk formula, 2:326, 2:329 definitions, 2:324–326 eddy correlation equation, 2:325 effect on d18O values, 1:503, 1:503F estimation by satellite data, 2:329 global distribution, 6:171F, 6:340–341, 6:340F global maxima, 6:170–171 history, 2:324–326 inertial dissipation vs. eddy correlation, 2:325–326 latitudinal variations, 2:328 measuring, methods of, 2:325 Mediterranean Sea circulation, 3:710, 3:712–714 nomenclature, 2:324–326 North Atlantic Oscillation and, 4:69 open ocean convection, 4:219, 4:220 precipitation and, 6:340–341 Red Sea circulation, 4:666, 4:667 regional variations, 2:328 research directions, 2:329–330 satellite remote sensing, 5:207 sources of data, 2:328–329 Southeast Asian seas, 5:310F see also Humidity; Precipitation Event timescales, geomorphology, 3:35 beach states, 3:37, 3:37F coral reefs, 3:37 Evolution algae see Algal genomics and evolution beaked whales, 3:643 coccolithophores, 1:612–613 coral reefs, 1:665–666 deep-sea fishes, 2:67 dolphins and porpoises, 2:155 eels, 2:215 fish, 2:367, 2:467–468 intertidal fishes, 3:280–281 krill, 3:349 mangroves, 3:501 planktonic foraminifera, 4:606 salmonids, 5:29 Evolutive spectral analysis, orbital tuning and, 4:313–314 Ewing heat flow probe, 3:42–43, 3:42F
Excess fishing capacity fish stocks, effects on, 2:544 maximum sustainable yield, 2:544 Excess helium-3, 4:113 Excess radioactivity, 5:329 ‘Excess volatiles,’ ocean origin, 4:261 Excitation–emission matrix spectroscopy, 2:590, 2:591F Exclusive economic zone (EEZ), 3:494, 3:892, 5:417 200 nautical miles, Law of the Sea jurisdiction, 3:434–435 continental shelf extending beyond, Law of the Sea jurisdiction, 3:435 customary international law, Law of the Sea jurisdiction, 3:435 Law of the Sea jurisdictions, 3:434–435 oceanographic research vessel operations, 5:417 sovereignty over resources, 3:433 survey vessels, 5:415 see also Coastal zone management Exocoetidae (flying fish) see Flying fish (Exocoetidae) Exotic species, 3:18 introduction see Exotic species introductions salt marshes and mud flats, 5:47 thermal discharges and pollution, 6:16 see also Non-native species Exotic species introductions, 2:332–344, 3:68 biocontrol, 2:342 Asterias amurensis, 2:342 Carcinus maenas, 2:342 Caulerpa taxifolia, 2:342 definition, 2:342 Mnemiopsis leidyi, 2:342 species-specific control, 2:342 examples, 2:335F ‘exotic species’ defined, 2:332 fishery stock manipulation, 2:531–532 history, 2:332–333 antifouling methods, 2:332–333 Mya arenaria, 2:332 Oculina patagonica, 2:332–333 transportations of mariculture organisms, 2:333 wooden ships’ hulls, 2:332–333 impacts on society, 2:339–340 disease-carrying invertebrates, 2:340 diseases, 2:340 mariculture, 2:339–340 proximity of shipping to mariculture, 2:340 toxins, 2:340 limiting risk antifouling materials, 2:343 aquaculture management, 2:343 movement of aquarium species, 2:343 trading networks management, 2:343 treatment of ships’ ballast, 2:343 management, 2:340–341, 2:342–343 aquaculture, 2:340–341 ICES Code of Practice, 2:340, 2:341T
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non-beneficial species, 2:341 successful cultivation, 2:341 ecomorphology, 2:341 rapid assessment and action, 2:342–343 ships’ ballast water, 2:341 treatment techniques, 2:341, 2:341T ships’ hulls, 2:341–342 antifouling methods, 2:341–342 mode of life, 2:339 reproductive capability, 2:339 speed of range expansion, 2:339 possible effects, 2:332 possible vectors, 2:332 unexplained events, 2:338 natural pathogen eruptions, 2:338 vectors, 2:333–334 aquaculture, 2:333–334 best-adapted species, 2:333–334 crustaceans, 2:334 fishes, 2:334 mollusks, 2:334 aquarium species, 2:337 ballast water, 2:334–336 biota in ballast, 2:336 importance of correct procedures, 2:336 sediments and biota in ballast, 2:336 types, 2:336, 2:336F deliberate introductions, 2:333 inoculation to establishment, 2:333 primary inoculations, 2:333F shipping, 2:334–336 ballast water and ships’ hulls, 2:334 ships’ hulls, 2:336–337 defouling process, 2:336–337 disease-carrying organisms, 2:337 secondary surfaces, 2:337 small vessels, 2:334 spawning, 2:337 trade agreements, 2:337–338 organisms spread by trade, 2:337 toxins, 2:337–338 variety of vectors, 2:333 vulnerable regions, 2:338–339 port regions, 2:338–339, 2:338F survival factors for introduced species, 2:339 temperate regions, 2:339 see also Mariculture Expandable current profiler (XCP), 2:253 Expendable bathythermograph (XBT), 1:710, 1:711F, 2:345, 2:345–346, 3:450F, 3:452F air-launched, 2:348–349 JJYY data exchange format, 2:349–350 launch procedure, 2:347 limited depth capability, and extrapolation from data, 2:346 operational effects of finite depth, 2:346 probe accuracy, 2:346 probe design, 2:346–347 connecting wire, 2:346 electrical contacts, 2:346
486
Index
Expendable bathythermograph (XBT) (continued) probe body, 2:346–347 protective shell, 2:346 thermistor element, 2:346 two-strand wire, 2:346 probe operation, 2:347 role/use for ocean surveying, 2:350 submarine-launched, 2:349 vertical temperature profile, 2:345–346 Expendable bottom penetrometer probe (XBP), 2:348 accelerometer, 2:348 seabed properties, 2:348 see also Acoustics, shallow water Expendable conductivity-temperaturedepth probe (XCTD), 2:347 pre-calibrated with two-wire connection, 2:347 see also CTD Expendable conductivity-temperaturedepth profilers (XCTD), 6:220 Expendable current profiler (XCP), 2:347–348, 2:348 capability and resolution, 2:347–348 measures current velocity and direction, 2:347 Expendable optical irradiance probe (XKT), 2:348 optical diffuse attenuation K, 2:348 see also Inherent optical properties (IOPs); Irradiance suspended particle measurement, 2:348 Expendable sensors, 2:345–351, 2:345 data recording and handling, 2:349–350 data exchange format JJYY, 2:349–350 PC with dedicated electronic interface, 2:349 deployment variations, 2:348–349 air-launched or submarine-launched options, 2:348 air-launched XBT and XSV, 2:348–349 buoyant electronics package with rf transmitter, 2:348–349 large-area surveys of dynamic regions, 2:349 resolution and accuracy, 2:349 simultaneous monitoring of several probes, 2:349 submarine-launched XBT and ASV, 2:349 assesses sonar propagation, 2:349 needs expensive technology, 2:349 XCTD equivalent is imminent, 2:349 depth variation of temperature, 2:345 see also Acoustics, deep ocean expendable bathythermograph see Expendable bathythermograph (XBT) expendable bottom penetrometer probe see Expendable bottom penetrometer probe (XBP)
expendable CTD probe see Expendable conductivity-temperature-depth probe (XCTD) expendable current profiler see Expendable current profiler (XCP) expendable optical irradiance probe see Expendable optical irradiance probe (XKT) expendable probe capabilities, 2:345 expendable sound velocity probe see Expendable sound velocity probe (XSV) measurement precision, 2:350 calibration affects climate change data, 2:350 depth data checking, 2:350 fall-rate equation errors, 2:350 within specified tolerances, 2:350 temperature errors, 2:350 mechanical bathythermograph (MBT), 2:345 normal (surface ship) deployment, 2:348 limited if towing equipment, 2:348 reducing wind effects, 2:348 removal of data from top 3-5 m, 2:348 standard ship launchers, 2:348 requirements of physical oceanography, 2:345 survey with small spatial scales, 2:345 types, 2:345–346 see also individual types use at speed, 2:345 use for ocean surveying, 2:350 budget-dependence, 2:350 deductions made from data archives, 2:350 only when rapidity is essential, 2:350 uses in support of surveys, 2:350 XBT role in ocean science, 2:350 Expendable sound velocity probe (XSV), 2:347 air-launched, 2:348–349 precision and depth options, 2:347 sing around speed sensor, 2:347 submarine-launched, 2:349 use by operational submarines, 2:347 Experiment, US Coast Survey (1831), 5:410 Exploitation see Human exploitation Exploitation rights, fishery stock manipulation, 2:533 Exploited fish, population dynamics, 2:179–185 assessment, 2:180–181 cohorts, 2:179, 2:181 definitions, 2:179 demersal fisheries, 2:94, 2:95F environmental variations, 2:183–184, 2:184F focus, 2:179, 2:185 management targets/limits, 2:182–183 mortality rates, 2:182, 2:183F precautionary approach, 2:184 production, 2:179–180 components, 2:179, 2:179F
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dispersal, 2:179F, 2:180 recruitment, 2:179, 2:179–180, 2:179F sustainability, 2:180, 2:180F risk specifications, 2:184 status assessment, 2:180–182 mathematical models, 2:181 recruitment, 2:181–182, 2:182F uncertainty, 2:184 see also Overfishing; specific species/ fisheries Explorer 5000, 6:263T Export production, 3:678, 4:103, 6:93 definition, 4:113 diatoms and, 3:678 see also Silica cycle impacts on nutrient concentrations, 4:680–681, 4:681F Sargasso Sea, 6:100T total production vs., 4:680 see also Carbon cycle Export ratio, 4:100 Extended core barrel, 2:40, 2:41F Extent (of sea ice) see Sea ice, geographical extent Extracellular polysaccharide production, 3:807 Extraterrestrial material, in marine sediments, platinum group elements as tracers, 4:499–502, 4:501F Extreme environments, operation of remotely operated vehicles, 4:745 Exxon Production Research Company, 4:138
F F230, definition, 6:242 0 F230, definition, 6:242 Factory trawlers see Trawlers FADs (fish-aggregating devices), 4:237–239 Fairy penguin, 5:523 see also Little penguin (Eudyptula minor) Falklands (Malvinas) Current circulation, 1:425–427, 1:427–428 deep water, 1:425 flow, 1:724 transport, 1:724, 1:724T upper ocean, 1:422–423 see also Atlantic Ocean current systems; Brazil and Falklands (Malvinas) Currents Falling gear, 2:539, 2:540F fishing methods, 2:539, 2:540F False killer whale (Pseudorca crassidens), 2:149 Falsifiability, general circulation models/ theory, 3:21 FAMOUS (French–American Mid-Ocean Undersea Study), 3:511 FAO see Food and Agriculture Organization (FAO)
Index Faraday rotation, 5:131 Faraday’s Law of Electromagnetic Induction, as basis of electromagnetic current meters, 2:253, 5:432, 5:432F Far infragravity waves, 6:315 Faroe Bank Channel, 2:572, 4:126–127, 4:130 see also Straits Faroes salmon fishery, 5:7–8 regulatory measures, 5:7–8, 5:7T Fast field program model (acoustic), 1:105 Fast ice see Land ice Fast repetition rate (FRR) fluorometry, 2:583, 2:584F Fast-spreading ridges, 3:854 abyssal hills, 3:865–866, 3:865F axial high, 3:852 axial neovolcanic zone, 3:860 crustal thinning, 3:856 eruption rates, 3:862 lava morphology, 3:815–816, 3:816F, 3:862 layer 2A, 3:834, 3:834F MORB chemical variability, 3:821 seamounts, 5:294–295 segmentation, fourth-order, 3:862 seismic structure axial magma chamber (AMC), 3:832, 3:833F, 3:834, 3:835, 3:835F crustal formation, 3:833–834 layer 2A, 3:834, 3:834F vent fauna biodiversity, 3:157 see also East Pacific Rise (EPR); Midocean ridge geochemistry and petrology; Mid-ocean ridge tectonics; Propagating rifts and microplates; Slow-spreading ridges; Spreading centers Fatalities, tsunami (2004), 6:129 Fathogram, 3:191, 3:192F Fathometers, 3:191 history, 5:504 Fatigue, moorings, 3:925 Faulting accretionary prisms see Accretionary prisms mid-ocean ridge see Mid-ocean ridge tectonics, volcanism and geomorphology Fault plane, tsunamis, rupture speed, 6:133 Fauna, marine, 3:121 FCM see Flow cytometry Feather assays, mercury levels, 5:275 Feather dusters (serpulid polychaetes), 3:139, 3:140F Fecal contamination recreational waters, 6:269 sources, 6:269 Fecal enterococci, sewage contamination, indicator/use, 6:274T Fecal pellets, 4:330, 4:331F, 4:333 benthic infauna, 1:395–396 sediment particle size and, 1:398
zooplankton, 1:371 see also Particle aggregation dynamics Fecal pollution beaches, 6:267 microbial/nonmicrobial indicator use, 6:275 Fecal sterols, sewage contamination, indicator/use, 6:274T Fecal streptococci, sewage contamination, indicator/use, 6:274T Feeding baleen whales (Mysticeti), 1:280–282, 1:281T, 3:611–612, 3:611F cephalopods see Cephalopods cold-water coral reefs see Cold-water coral reefs conveyor-belt, 1:395 copepods see Copepod(s) corals, 1:671 crustaceans, 1:699 deep-sea fauna, 2:59 demersal fish see Demersal fish(es) deposit, 1:395 filter, right whales (balaenids), 1:278F fish see Fish feeding and foraging gray whale (Eschrichtius robustus), 1:282 interior, 1:395 krill (Euphausiacea), 3:355 macrobenthos see Macrobenthos marine mammals see Marine mammals Mediterranean species, mariculture, 3:532 mollusks, 3:532 oceanic dolphins, 4:135 odontocetes (toothed whales), 3:616, 3:616F, 4:135 pelagic fish, 2:505 pinnipeds (seals), 3:600, 3:611 plankton, 1:576–577, 1:576F, 1:577F planktonic foraminifera, 4:609 polar bear, 3:611 radiolarians, 4:614 seabirds see Seabird(s) subductive, 1:395 suction beaked whales (Ziphiidae), 3:646 sperm whales (Physeteriidae and Kogiidae), 3:646 surface-tension red-necked phalarope, 4:395, 4:396F Wilson’s phalarope, 4:395 suspension-, benthic boundary layer (BBL) see Benthic boundary layer (BBL) Thunnus thynnus (Atlantic bluefin tuna), 3:532 see also Animal feeding; individual species/groups Feeding behavior bottlenose dolphins (Tursiops truncatus), 2:157, 2:158 killer whale (Orcinus orca), 2:157, 2:158 Odobenidae (walruses), 3:615 Phalaropes see Phalaropes
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Feeding ecology dolphins and porpoises see Dolphins and porpoises intertidal fishes see Intertidal fish(es) Feeding guilds, coral reef fishes, 1:658 Feeding habits, benthic organisms see Benthic organisms Feeding patterns Anhingidae (darters), 4:375, 4:376T Aptenodytes (penguins), 5:522T, 5:526 Brachyramphus, 1:174 Eudyptes (crested penguins), 5:522T Fregatidae (frigatebirds), 4:371, 4:376T little penguin (Eudyptula minor), 5:522T, 5:523 Pelecanidae (pelicans), 4:371–373, 4:376T Pelecaniformes, 4:375–376, 4:376T Phalacrocoracidae, 4:376T Pygoscelis, 5:522T, 5:525–526 Spheniscus, 5:522T, 5:523 Sulidae (gannets/boobies), 4:373, 4:376T, 5:234 yellow-eyed penguin, 5:522T, 5:524, 5:527 Feeding shifts Atlantic cod (Gadus morhua), 2:379 Atlantic herring (Clupea harengus), 2:376, 2:376F herring (Clupea harengus), 2:376, 2:376F Feeding systems, automatic, salmonid farming, 5:26 Fehmarnbelt, Baltic Sea circulation, 1:288, 1:290F, 1:291–292 Fe(II)/(III), definition, 6:85 Fermat’s principle, 6:41 Ferredoxin, definition, 6:85 Ferrel Cell, 4:121F Ferric hydrolysis species, definition, 6:85 Ferrochrome lignosulfate, coral impact, 1:673 Ferromagnetic rocks, 3:481 Ferromanganese deposits, 1:258–260 barite crystals, 1:265F composition, 1:258–259 crusts, 1:261–262, 1:263F composition, 1:261–262 distribution, 1:258, 1:261F types, 1:259F growth rates, 1:259–260 metal sources, 1:259–260 nodules, 1:258, 1:258–260 distribution, 1:258, 1:260F manganese/iron ratios, 1:262F types, 1:258, 1:259F trace metal sources, 1:260–261 Ferromanganese oxide deposits, 3:488 elements, average abundance of, 3:488T historical formation controversy, 3:488–489 triangular representation, 3:489F see also Manganese nodules Ferry fleet, 5:404
488
Index
Fertilizers application levels, 3:398F dinitrogen (N2) fixation and, 4:35 pelagic fishery products, 5:471, 5:471T FGVR (free vehicle grab respirometer), 4:486, 4:487F FIA see Flow injection analysis (FIA) Fiber optics see Optical fibers Fickian diffusion, 4:732 Fick’s First Law of Diffusion, 3:1–2 benthic flux and, 4:491 Fieberling Guyot, Pacific Ocean, internal waves, 3:270–271 Figure of merit, sonar, 1:109–110 Filchner Depression, overflow, 4:266 Filchner ice shelf, 3:215, 5:541 climate change, effects of, 5:550 Filchner-Ronne Ice Shelf, 5:548–549 see also Ronne Ice Shelf Film droplets, 6:333–334 Films, surface see Surface films Filtering (datasets), mixing data, 2:292, 2:293F Filtration, coral reef aquaria, 3:528F, 3:530 Finfish, Southern Ocean fisheries, 5:514–515 Finite difference acoustic modeling, shallow-water, 1:119, 1:119F Finite difference modeling methods, storm surges, 5:535–536 Finite element modeling methods, storm surges, 5:536, 5:537F Finland, Gulf of see Gulf of Finland Finland, Salmo salar (Atlantic salmon) fisheries, 5:1, 5:2T Finlater jet, 1:728–730 Finless porpoise (Neophocaena phocaenoides), 2:154, 2:156, 2:159 Fiord(s), 2:300 barotropic pressure gradient, 2:354 basin, 2:357 circulation, 2:359–360 estuarine, 2:360 origins/general characteristics, 2:359 separation of water layers, 2:359–360, 2:360F sill depth types, 2:360 sill impacts, 2:360 wind-induced water exchange, 2:360, 2:360F circulation patterns, 2:353–358, 2:353F major processes, 2:354–355 concepts/descriptions, 2:353–354 definition, 2:353 distribution, 2:359 freshwater runoff, 2:360–361 nutrient cycling, 2:361 hypoxia, 3:173–174 intermediary layer, 2:357 water exchange rate, 2:357 mixing, 2:355 narrow mouthed, 2:356–357 physical/abiotic factors, 2:359 simple quantitative models basin water, 2:357
deep sills, stationary circulation, 2:356 intermediary layers, 2:357 surface layer, 2:355–356 water exchange, shallow/narrow mouths, 2:356–357 slides, 5:451 stagnation periods, 2:353–354 surface layer, 2:355–356 Fiordic ecosystems, 2:359–366 circulation, 2:359–360 see also Fiord(s), circulation energy input seasonality, 2:361 organic material in sediment, 2:361 primary production, 2:361 production ranges, 2:361, 2:361T fisheries, 2:359 food web structure/functioning, 2:364, 2:364F higher trophic animals, 2:364–365 apex predators, 2:365 mammalian predators, 2:365 ocean/coastal fish, 2:364–365 other structural forces, 2:365 light, 2:365 visibility, 2:365 zooplankton community, 2:364 general features, 2:359–360 scaling of exchange processes, 2:361–362 advection, 2:361 advective vs. biological processes, 2:362 growth rate/advective rate ratio, 2:362 magnitude of advective influence, 2:362 planktonic growth, 2:362, 2:362F sill boundary conditions, 2:361–362, 2:362T temporal/spatial variability, 2:361–362 tidal currents, 2:362–363 organisms exchange, 2:362 zooplankton transport, 2:363, 2:363T trophic relationships, 2:359 use in research, 2:359 vertical environmental gradients, 2:359 zooplanktonic vertical behavior, 2:363–364 aggregation mechanisms, 2:363F, 2:364 diurnal vertical migration, 2:363 spatial patterns, 2:363 species abundances, 2:363 see also Coastal circulation models Fiordland penguin, 5:522T, 5:524–525 see also Eudyptes (crested penguins) Fire shrimp see Lysmata debelius (fire shrimp) Firn, definition, 3:190 First-year (FY) ice, 5:172 Fish(es), 2:467–475 abundance, 2:467 diversity and numbers, 2:467 species, 2:467 acoustic scattering, 1:64–65, 1:107, 1:116
(c) 2011 Elsevier Inc. All Rights Reserved.
high frequency, 1:65 low frequency, 1:65 medium frequency, 1:65 swimbladder-bearing, 1:65 swimbladderless, 1:65–67 adaptations, 2:473 body fluids and osmoregulation, 2:473–474 buoyancy, 2:473 elasmobranchs vs. teleosts, 2:473 electroreception, magnetic fields and navigation, 2:474–475 electroreceptors, 2:474–475 generation of pulses, 2:474 navigation via electroreceptors, 2:475 navigation via magnetoreceptors, 2:475 locomotion see Fish locomotion vision see Fish vision warm blood, 2:474 body areas warmed, 2:474 purposes for warming, 2:474 benthic see Benthic fish(es) bioluminescence, 1:377T, 1:380–381 counterillumination camouflage, 1:381–382 luciferin/luciferase system, 1:381 see also Luciferin/luciferase system photophores, 1:381–382 symbiotic bacteria, 1:380–381 cartilaginous, acoustic scattering, 1:65–67 catch, drivers of variation, 4:713 coral reef see Coral reef fish(es) deep-sea see Deep-sea fish(es) demersal see Demersal fish(es) densities, ‘rigs to reefs’ program, 4:751 distribution, 2:472–473 bathypelagic zone, 2:472 benthopelagic zone, 2:472 coral reefs, 2:472–473 euphotic/epipelagic zone, 2:472 mesopelagic zone, 2:472 diversity and origins, 2:467–468 agnathans and gnathostomes, 2:468 common ancestor, 2:468 earliest ray-finned fishes, 2:468 fossil record, 2:467–468 species numbers, 2:467 ecophysiology see Fish ecophysiology exploited see Exploited fish, population dynamics farming see Aquaculture feeding/foraging see Fish feeding and foraging food sources copepods, 1:650 krill, 3:355–356 freshwater diversity, 2:467 growth/feeding, coastal circulation models, 1:576–577, 1:576F, 1:577F habitats and adaptations, 2:467 hearing see Fish hearing and lateral lines
Index human value, 2:475 advances in endocrinology, 2:475 contributions to/from other disciplines, 2:475 hydrothermal vent biota Galapagos Rift, 3:139–140, 3:140F see also Bythitid fish (Bythites hollisi); Zoarcid fish hypoxia, 3:177, 3:178F intertidal see Intertidal fish(es) lagoons, 3:386, 3:386T larvae see Fish larvae larval, analytical flow cytometry, 4:247–248 lateral lines see Fish hearing and lateral lines locomotion see Fish locomotion mesopelagic see Mesopelagic fish(es) migration horizontal see Fish horizontal migration vertical see Fish vertical migration nitrogen cycle and, 4:33T ocean ranching programs see Stock enhancement/ocean ranching programs oil pollution, 4:196 out of water, 2:467 pelagic see Pelagic fish(es) polar midwater regions, 4:516–517 populations, exploited see Exploited fish, population dynamics predation and mortality see Fish predation and mortality reproduction see Fish reproduction safe haven, ‘rigs to reefs’ program, 4:750 salt marshes and mud flats, 5:44 satellite remote sensing, 4:739 schooling see Fish schooling small pelagic, wasp-waist control, 4:700–702 species composition, ‘rigs to reefs’ program, 4:751 species numbers fossil species, 2:467–468 living species, 2:467 stock enhancement see Stock enhancement/ocean ranching programs stocks see Fish stocks straddling and high seas stocks, Law of the Sea and, 3:437 thermal discharges and pollution, 6:15–16 threats, 2:467 types, 2:468–471 comparisons, 2:468–470 elasmobranchs, 2:471–472 see also Elasmobranchs teleosts, 2:470–471 see also Teleosts types and relationships, 2:468 ancient relationships, 2:469F cladistic models of taxonomy, 2:468 example, 2:468, 2:469F
classification by morphology, 2:468 classification difficulties, 2:468 vision see Fish vision see also Antarctic fish(es); Flatfish; Salmonids; individual types of fish FISH (fluorescence in situ hybridization), 2:583 Fish-aggregating devices (FADs), 4:237–239 FishBase, 1:652 Fish ecophysiology, 2:367–373 basic features, 2:367, 2:368F biotic/abiotic distribution factors, 2:367–368 examples, 2:367–368 distribution tolerances/limits, 2:368 oxygen tension, 2:371–372 avoidance of hypoxic areas, 2:371–372 pH, 2:372 control of acid-base balance, 2:372 presence of water, 2:368 necessity of water for most fish, 2:368 problems of immersion, 2:368 salinity, 2:370–371 acclimation, 2:371 elasmobranch fish, 2:370 fresh/saltwater species differences, 2:370 marine teleost fish, 2:370–371, 2:371F osmorespiratory compromise, 2:371 temperature, 2:369–370 adaptations to avoid freezing, 2:370 adaptations to different temperatures, 2:370 ectothermic nature of fish, 2:369 factors determining thermal niche, 2:369 susceptibility to freezing, 2:370 warm-water specialist example, 2:369–370 water depth, 2:368–369 depth-related constraints, 2:368–369 diversity of fish, 2:367, 2:367T optimal abiotic conditions, 2:372 aquaculture perspective, 2:372 biogeographical perspective, 2:372, 2:372F origins/evolution of fish, 2:367 plasma and hemolymph osmolarity, 2:368F see also Antarctic fish(es); Deep-sea fish(es); Eels; Intertidal fish(es); Salmonids Fisheries, 2:499–504 calculating fish yields, 4:21 capture see Capture fisheries, economics cephalopods, 1:524, 1:529 climate affecting see Fisheries, and climate coastal environment changes affecting, 1:572
(c) 2011 Elsevier Inc. All Rights Reserved.
489
cold-water coral reefs, 1:622, 1:624F as threat to, 1:622, 1:624F copepod pests, 1:649 copepods, 1:650 coral reef fishes, 1:655 coral reefs, 1:669 current state of stocks, 2:500 dolphins and porpoises, 2:159 early exploitation study, 2:499 economics see Fishery economics eels, 2:215 emerging issues, 2:503–504 climate change, 2:503–504 ecosystem approach, 2:503 holistic view of human impacts, 2:503 humans in ecosystem, 2:504 multispecies considerations, 2:503 use of closed areas, 2:503 factors influencing harvesting behavior, 2:500 anadromous fish, 2:501 benthic fish, 2:501 demersal fish, 2:501 large-bodied fish, 2:500–501 shellfish, 2:501 small-bodied fish, 2:500–501 special habitats/environments, 2:501 fiordic ecosystems, 2:359 fish schooling, 2:437–443, 2:438F see also Fish schooling food webs and see Food webs habitat modification, 3:100–102 herring, 4:365 human population pressures, 2:500 impacts marine biodiversity, 2:145 marine habitats, 2:145 ocean gyre ecosystems, 4:137 studies, 2:145 importance of pelagic fishes, 4:369 importance to humans, 2:499 inexhaustibility concept, 2:499 krill, 3:349, 3:356, 3:356–357 lagoons, 3:386, 3:386T landings total marine production, 2:90, 2:90F trophic levels, 2:206F, 2:207 mackerels, 4:368 management see Fishery management Mediterranean mariculture dependence, 3:533 multispecies dynamics see Fishery multispecies dynamics pelagic see Pelagic fisheries realization of finite resources, 2:499 recruitment to, SAR images and, 5:107F, 5:108 regional management, Law of the Sea and see Fishery management resources, 2:500–501 see also Fishery resources sardines, 4:367 science supporting management, 2:499 institutions, 2:499–500 seabird interactions see Seabird(s), fisheries interactions
490
Index
Fisheries (continued) stock see Fishery economics stock manipulation see Fishery stock manipulation threat to cold-water coral reefs, 1:622, 1:624F tunas, 4:368 see also Ecosystem(s), fishing effects; Large marine ecosystems (LMEs); Mariculture; Ocean zoning; Southern Ocean fisheries; Whaling industry; specific types of fisheries/ fishing Fisheries, and climate, 2:483–490 anthropogenic climate change, 2:483 changes attributed to climate, 2:483 effects of climate change, 2:483, 2:484–486 bioclimate envelope, 2:485–486 effects on individuals, 2:484–485 effects on populations, 2:486 identifying processes, 2:485 recruitment, 2:485, 2:486F relation to fishing stresses, 2:486 temperature effects, 2:485, 2:485F history, 2:484 distribution shifts, 2:484 historical patterns vs. current change, 2:484 lessons to be learned, 2:484 climate influence on stocks, 2:484 risk of stock collapse, 2:484 stock recovery, 2:484 Norwegian spring spawning herring, 2:484 distribution shifts, 2:484, 2:485F expansion of summer migration, 2:484 historical account, 2:484 impacts on human societies, 2:489–490 economic consequences, 2:489 examples, 2:489 Greenland, 2:489 projections of impacts, 2:489 indirect effects and interactions, 2:488–489 changing primary production, 2:489 spread of pathogens, 2:489 North Pacific regime shifts (1998), 2:487 California Current System, 2:487 central North Pacific, 2:487 Gulf of Alaska and Bering Sea, 2:487 North Pacific regime shifts, history, 2:487 northward spread of species, 2:483, 2:483F regional effects of climate, 2:486–487 Baltic Sea, 2:488 coral reef fisheries, 2:488 Greenland cod stocks, 2:487–488 North Atlantic, 2:487–488 North Pacific, 2:487 species favored by climate trends, 2:488, 2:488F
tropical Pacific, 2:486–487 tuna example, 2:486–487 timescales and terminology, 2:483–484 Fisheries research vessels, 5:415–416 design characteristics, 5:416 fisheries research, 5:415–416 government agencies, 5:416 see also Fishing fleets; Fishing methods/ gears Fisher information index, 4:720 Fishermen, rigs and offshore structures relationship, 4:750 Fishery conservation zones, 3:436–437 management of migratory species, 3:436–437 total allowable catch, 3:436 Fishery economics, 2:491–498 capture fisheries see Capture fisheries fish as renewable resource, 2:491 Gordon-Schaefer bioeconomic model, 2:492F illegal fishing, 2:496 intertemporal allocation, 2:491 marine protected areas, 2:496–497 ‘insurance’ policies, 2:496 management tool, 2:496 protection variability, 2:496 spatially heterogeneous models, 2:496–497 rate of biomass adjustment, 2:491 renewable natural resource, 2:491 ‘rights-based’ management, 2:497 dedicated access privileges, 2:497 quotas and total allowable catch, 2:497 self-generation, 2:491 subsidies and overexploitation, 2:495–496 buyback subsidies, 2:495–496 impact on sustainability, 2:495, 2:496F two categories of world fisheries, 2:491 Fishery management, 2:501–503, 2:513–521, 2:522–527 allocation, 2:517 competitive vs. rights-based, 2:517–518 assessment research, 1:702–705 biological reference points, 2:502, 2:502F control systems, 2:515–516 area closures, 2:516, 2:546 effort, 2:515, 2:515–516, 2:546, 2:547 human dimension, 2:523–524 Individual Fishery Quota, 2:517, 2:520 Individual Transferable Quota, 1:706, 2:517, 2:520, 2:525, 2:526 input, 2:515, 2:516 output, 2:516 prohibited species catch limits, 2:516 quota-based, 1:705, 2:523 size limits, 2:516 time closure, 2:516, 2:546
(c) 2011 Elsevier Inc. All Rights Reserved.
costs externalities, 2:518 inefficiencies, 2:515–516 debates, 2:501–502 definition, 2:513, 2:517, 2:522 discarding, 2:516, 2:518, 2:519, 2:523 economic rationality, 2:525 see also Fishery economics economic reference points, 2:502 ecosystem perspective, 1:652, 2:519 enforcement, 2:514, 2:524 factors to consider, 2:501–502 failures, 2:503 fairness, 2:526 feedback mechanisms, 2:519, 2:520F fishing methods/gears and, 2:546 future issues, 2:519–520 goals, 2:513, 2:514 governance issues, 2:516–517, 2:519–520, 2:527 high-grading, 2:523 historical aspects, 2:523 human dimensions, 2:523–524 cooperation, 2:524 participation, 2:526–527 rules, 2:522, 2:523–524 social impacts, 2:522 traditional ecological knowledge, 2:526 traditional practices, 2:523 tragedies of the commons, 2:527 infrastructure supporting, 2:514 institutional arrangements, 2:513–515 international collaboration, Pacific salmon fisheries, 5:12–13, 5:19–22 legitimacy issues, 2:522, 2:524, 2:525, 2:527 marine protected areas see Marine protected areas (MPAs) maximum sustainable yield, 2:513, 2:518–519 modern, 2:523 open-access problems, 2:502 optimum yield, 2:513 performance issues, 2:516–517 access, 2:518 effectiveness, 2:517, 2:518 enforcement, 2:518 input vs. output controls, 2:516–517 problems, 2:518 ratchet effect, 2:518–519 political aspects, 2:522, 2:525–526, 2:526 precautionary approach, 2:520 crustacean fisheries, 1:701 definition, 2:520 demersal fisheries, 2:95–96 fairness issues, 2:526 marine policy, 3:670 principles, 3:675 Salmo salar (Atlantic salmon) fisheries, 5:9–10, 5:9F, 5:10F stock manipulation, 2:533–534 problems inherent, 2:519–520, 2:520F Reflagging Agreement, 2:524 regime shifts and, 4:707–708
Index regional, Law of the Sea and, 3:436 active management of stocks, 3:436 fisheries conflicts, 3:436 Fishing and Conservation of Living Resources Convention, 3:436 research trends, 1:652 resource rents, 3:674 rights-based, 2:526–527 rules, human dimensions, 2:522, 2:523–524 science supporting, 2:499 institutions, 2:499–500 scientific basis, 2:525–526 stock manipulation see Fishery stock manipulation strategies, ideal, 4:707–708 surveillance, 2:524, 2:524–525 tools (management), 2:502–503 see also specific fishery types Fishery Management Plans (FMPs), 2:515 Fishery multispecies dynamics, 2:505–512 area closures, 2:508 energy budgets, 2:507–508 ‘fishing down the food web’, 2:511 interaction hypotheses, 2:508–509, 2:511 bottom-up control, 2:508–509, 2:509F, 2:511 top-down control, 2:509–511, 2:510F interaction quantification tools, 2:506–508 diet analysis, 2:506–507 management implications, 2:511 models, 2:505, 2:507 virtual population analysis see Multispecies Virtual Population Analysis (MSVPA) predation, 2:506–507, 2:507F, 2:509–510 terminology, 2:505 variability patterns, exploited communities, 2:505–506, 2:506F, 2:507F time scales, 2:511 Fishery resources, 2:500–501 eutrophication, habitat effects, 3:179–180 global state see Global state of marine fishery resources hypoxia, effects of, 3:179F Law of the Sea and, 3:435–436 fishery conservation zones, 3:436–437 need for management measures, 3:436 regional fishery management, 3:436 straddling and high seas stocks, 3:437 yields approach limit, 3:435–436 see also Fishery conservation zones; Fishery management; Mariculture Fishery stock manipulation, 2:528–534 artificial reef deployments, 2:532 assessment research, 1:702–705 benefits, 2:528, 2:529T biomass measurement, 2:532 carrying capacity, 2:532 ecological balance effects, 2:528, 2:532 efficacy, 2:533–534
enhancement programs see Stock enhancement/ocean ranching programs exotics, introduction, 2:531–532 exploitation rights, 2:533 funding, 2:533 future approaches, 2:533–534 genetic considerations, 2:531–532 global perspective, 2:528–530 investment sources, 2:533 ocean ranching see Stock enhancement/ ocean ranching programs operational controls, 2:533 ownership rights, 2:533 performance monitoring, 2:532–533 precautionary approach, 2:533–534 quality considerations, 2:530–531 restoration programs, 2:528, 2:529T funding, 2:533 stock enhancement see Stock enhancement/ocean ranching programs types, 2:528, 2:529T Fish eyes see Fish vision Fish farming see Aquaculture Fish feeding and foraging, 2:374–380 complex interactions, 2:379–380 effects of climate change, 2:379–380 ontogenetic feeding shifts, 2:379 food chains, 2:379 critical links, 2:379 prey species, 2:379 foraging strategies, 2:377–379 optimization of behavior, 2:377 bluefin tuna example, 2:377–378 game theory, 2:378–379 sharing of resources, 2:378 modes of feeding, 2:374, 2:374–377, 2:374T adaptations, 2:374 ambushers, 2:377 carnivores, 2:376 benthic feeders, 2:376 tactics used to catch prey, 2:377 carrion feeders, 2:375 competition, 2:378 defence of territory, 2:378 hierarchy development, 2:378 scramble competition, 2:378 detrivores, 2:375 feeding guilds, 2:374 fluidity of tactics, 2:377 food type classifications, 2:374 herbivores, 2:375 non-exclusive categories, 2:375 optimization of behavior, 2:377 planktivores, 2:375 basking sharks, 2:375–376 herring, 2:376 migrations, 2:375 proportions of feeding modes, 2:375T specialist exploitation, 2:377 stalkers, 2:377 use of camouflage, 2:377 use of lures, 2:377 use of speed, 2:377
(c) 2011 Elsevier Inc. All Rights Reserved.
491
see also Coral reef(s); Ocean gyre ecosystems Fish hearing and lateral lines, 2:476–482 acoustic signals, 2:476 ear-lateral line interactions, 2:481 complementary systems, 2:481 ears, 2:478 mechanics, 2:478 mechanoreceptive hair cells, 2:478, 2:478F hearing, 2:476–477 mechanics, 2:477–478 inner ear, 2:477–478, 2:477F purposes, 2:478–479 behavioral situations, 2:479 communication, 2:478 sound production mechanisms, 2:478–479 sounds heard, 2:476–477 discrimination/understanding, 2:477 hearing ranges, 2:476, 2:477F specialist/generalist hearing, 2:476–477 testing fish hearing, 2:476 hearing adaptations, 2:479 air bubbles, 2:479 hearing specialists, 2:479 sound production and hearing, 2:479 swim bladder, 2:479 human-generated sound, 2:476, 2:479–480 conflicting evidence, 2:480 few data, 2:480 growing concern, 2:479–480 lateral line, 2:480–481, 2:480F description, 2:480 hydrodynamic stimulation, 2:480 pattern variations, 2:481 purposes, 2:480 sensory hair cells, 2:480–481 octavolateralis system, 2:476 structure and habitat, 2:481 evolution of specialized structures, 2:481 habitat and hearing importance, 2:481 Fish horizontal migration, 2:402–410 ecology, 2:403 regional production cycles, 2:403 spawning and homing, 2:403 life histories, 2:403 amphidromous species, 2:404 Japanese ayu, 2:404 anadromous species, 2:403 families included, 2:403 salmon, 2:403 catadromous species, 2:403–404 anguillid eels, 2:403–404 European/American eels, 2:404 families included, 2:403 oceanodromous species, 2:404–407 Arcto-Norwegian cod, 2:406 cod, 2:406 herring, 2:405, 2:405F plaice, 2:406–407 scombrids, 2:404–405, 2:405F
492
Index
Fish horizontal migration (continued) tuna, 2:404–405, 2:404F walleye pollock, 2:405–406 migration circuits, 2:402 migration mechanisms, 2:407 movement and navigation, 2:407 ocean currents, 2:407–408 oceanic gyres, 2:407 orientation and navigation, 2:409 tidal streams, 2:408–409, 2:408F, 2:409F migration speed, 2:407–408, 2:408F vertical movements, 2:407–408, 2:408F migration occurrence, 2:402 importance to world fisheries, 2:402, 2:402T numbers of migrating species, 2:402 tag data, 2:409 terminology, 2:402–403 categories of migrating fish, 2:402–403 see also Eels; Fish locomotion; Fish vertical migration; Pelagic fish(es); Salmonids; Tide(s) Fishing Benguela upwelling, regime shifts and, 4:705–707 Black Sea, regime shifts and, 4:704–705 by-catch, definition, 2:202 ecosystem effects see Ecosystem(s) effort see Fishing effort fronts and, 5:391 illegal, sanctions, 2:524 principles, 2:535 problems, 2:544 recreational see Recreational fishing regime shifts, 4:704–705, 4:705–707 target catch, definition, 2:202 unsustainable see Overfishing Fishing and Conservation of Living Resources Convention, 3:436 ‘Fishing down the food web’ ecosystem degradation, 1:652 fishery multispecies dynamics, 2:511 Fishing effort control systems, fishery management, 2:515, 2:515–516, 2:546, 2:547 crustacean fisheries, 1:705 definition, 2:517 demersal fisheries, 2:91, 2:92T, 4:228 distribution, marine protected areas, 3:674 exploited fish, population dynamics assessment, 2:181 reduction, global requirements, 2:522 Fishing fleets, 2:542–544 decked, tonnage by continent, 2:542, 2:544F by type, 2:544, 2:545F efficiency, 2:535, 2:544, 2:546T excess fishing capacity, 2:544 renewal rates, 2:543–544
undecked, number by continent, 2:542, 2:543F see also Trawlers Fishing methods/gears, 2:535–547 benthic species, disturbance, 2:204 by-catch, 2:544–546, 4:237 capture mechanisms, 2:535 classification, 2:535–536 coral impact, 1:672–673 demersal fisheries, 2:90, 2:91–92 discarding, 2:544–546 dredging see Dredges/dredging efficiency, 2:535, 2:544, 2:546T fish-aggregating devices, 4:237–239 fishery management and, 2:546 gill nets see Gill net(s) grappling gear, 2:542 harpoons, 4:235 harvesting gear see Harvesting gear hooks and lines, 2:541, 2:542F, 2:544, 2:545F, 4:235 mortality associated, unreported catches, 5:3 Pacific salmon fisheries, 5:12, 5:13 pelagic fisheries, 4:234–235 principles, 2:535 problems, 2:544 seine nets see Seine nets traps see Traps trawl nets see Trawls/trawl nets wounding, 2:542 Fishing quotas, 2:516, 2:516–517 management see Fishery management see also Total Allowable Catch (TAC) Fish larvae, 2:381–391, 2:425–426, 2:426F analytical flow cytometry, 4:247–248 behavior, 2:387 diurnal vertical migration, 2:387 selective tidal stream transport, 2:387 swimming behaviors, 2:387 development see Fish reproduction examples, 2:382–383F factors controlling survival, 2:381 foods/feeding, 2:383–385 common prey, 2:383–384 evaluation of nutritional condition, 2:384 feeding behaviors, 2:384–385, 2:384F growth, 2:384 prey size, 2:383–384 general description, 2:381 integration, 2:387–389 age determination, 2:388–389 cohort biomass, 2:387, 2:388F density-dependent processes, 2:388 density-independent processes, 2:388 larval stage dynamics models, 2:389 recruitment, 2:388F interactions with other plankton, 2:381 distributions within nurseries, 2:381 ichthyoplankton, 2:381 sampling methods, 2:381 mesocosms use in research, 3:655 predation, 2:385, 2:386F effect of larval growth rate, 2:385
(c) 2011 Elsevier Inc. All Rights Reserved.
predator types, 2:385 vulnerability, 2:385 see also Fish predation and mortality properties, 2:390T qualities of survivors, 2:390 recruitment, 2:390 research needs, 2:389–390 better abundance estimates, 2:389 better knowledge of trophic relationships, 2:389 new technologies, 2:389–390 time series of abundances, 2:389 size and survival, 2:390 survival and recruitment, 2:381, 2:390 survival hypotheses, 2:381–383 critical period, 2:381–382 lottery, 2:383 match-mismatch, 2:382–383 retention, 2:383 stable ocean, 2:382–383 temperature and salinity, 2:385–387 effects of salinity levels, 2:387 importance, 2:385–386 optimum salinity-temperature levels, 2:387 temperature effects on bioenergetics, 2:387 temperature effects on growth rates, 2:386–387 see also Fiordic ecosystems; Fish feeding and foraging; Fish predation and mortality; Fish reproduction; Large marine ecosystems (LMEs); Plankton; Salt marsh(es) and mud flats; Zooplankton sampling Fish-line problem, 5:579–580 Fish locomotion, 2:392–401 adaptations, 2:394, 2:395–396F, 2:473 generalists vs specialists, 2:394 stream-lining, 2:473 swim muscles, 2:473 apparatus, 2:392–394 body curvature waves, 2:392 body shape, 2:393 fins, 2:393 mucus, 2:394 muscles/myotomes/myosepts, 2:392–393, 2:392F scales, 2:393 skin, 2:393 vertebrae, 2:392 basic principles, 2:392 energy cost, 2:398–399 cost of swimming, 2:398–399, 2:398F optimum speed and mass, 2:399, 2:399F overcoming drag, 2:398–399 energy-saving behaviors, 2:399–400 burst-and-coast swimming, 2:399, 2:399F schooling behavior, 2:399–400 fish wakes, 2:394–398 creation of vortex rings, 2:394–397, 2:397F
Index quantitative flow visualization techniques, 2:397–398, 2:397F, 2:398F methods, 2:394 body curvature waves, 2:394 dorsal/anal fin propulsion, 2:394 pectoral/median fin propulsion, 2:394 speed and endurance, 2:400–401 maximum burst speeds, 2:400 maximum sustained speeds, 2:400 muscle groups, 2:400–401 oxygen limitations, 2:400 relationships, 2:400, 2:400F styles, 2:394 Fishmeal demand, 5:472 pelagic fishery products, 5:470–471, 5:471T Fish mortality see Fish predation and mortality Fish offal, pelagic fishery products, 5:471 Fish oil, pelagic fishery products, 5:470–471, 5:471T Fish predation and mortality, 2:417–424 community structure, 2:422 influencing factors, 2:422 diversity of predators, 2:417–418, 2:419T fish, 2:418 invertebrates, 2:418 types and sizes, 2:417–418 evolution, 2:422–423 avoidance tactics, 2:422–423, 2:423F feeding-predator avoidance trade-off, 2:423 life stages and predation, 2:418F, 2:420, 2:421F predators of adults, 2:420 predators of eggs, 2:420 predators of juveniles, 2:420 predators of larvae, 2:420 life transitions and predation, 2:420–421 highest predation rates, 2:420–421 metamorphosis, 2:421 mortality fishing, 2:417 natural, 2:417, 2:418F predation equation, 2:419–420, 2:420F changes in behavior, 2:420 escape, 2:420 factors affecting predation rates, 2:419–420 sequence of predation, 2:419 predators, phytoplankton competition model, 4:723–724, 4:724F recruitment, 2:421–422 density-dependent predation, 2:422 early life stage predation, 2:422 effects on population levels, 2:421–422 time in life stage, 2:422 removal of fish by predator type, 2:417F studying predation, 2:418–419 assessing impact, 2:418, 2:419T modelling, 2:418–419
see also Fish feeding and foraging; Fish schooling; Seabird foraging ecology Fish reproduction, 2:425–431 behavior, 2:430–431 antipredator mechanisms, 2:430 food acquisition, 2:430 high mortality rates, 2:431 light, 2:430 characteristics of most fish, 2:425 deep-sea fish see Deep-sea fish(es) demersal fish see Demersal fish(es) egg and larval development, 2:429–430 description/development of eggs, 2:429, 2:429F flexion, 2:429 larval feeding, 2:429 larval physiology, 2:429 larval stages and metamorphosis, 2:430F metamorphosis, 2:429–430 sensory systems, 2:429 see also Fish larvae eggs, 2:425–426, 2:425F effect of temperature on development, 2:426F intertidal fishes, 3:284 parental care, 3:285 factors affecting reproductive ability, 2:425 fecundity and egg size, 2:427, 2:427F relationship, 2:427 reproductive strategies, 2:427 intertidal fish see Intertidal fish(es) larvae, 2:425–426, 2:426F see also Fish larvae life histories (general), 2:425–426, 2:430F exceptions, 2:426 spawning behavior and parental care, 2:427–429 egg cases, 2:428F oviparity, 2:428 parental care, 2:428–429 seasonal migrations, 2:428 viviparity, 2:428 spawning season, 2:426–427 high latitudes, 2:426–427 low latitudes, 2:427 see also Fish larvae; Life histories (and reproduction) Fish schooling, 2:432–444 behavior, 2:433F decisions, 2:441F definitions, 2:432 social group types, 2:432 dynamics of decisions mature fish, 2:441 young fish, 2:440–441 fisheries applications, 2:437–443, 2:438F adjustment models, 2:438, 2:440F catchability/catch rate, 2:438 distribution dynamics, 2:442T fidelity to shoal, 2:439, 2:443 fishing technologies, 2:437 genetic relatedness, 2:439–440, 2:443
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human response to population collapse, 2:437 metapopulation model, 2:438–439 models, 2:439F patterns, 2:442 population collapse/range reduction, 2:437 predation minimizing, 2:441–442 retention zones, 2:439 schooling decisions, 2:440–441 shoaling behavior, 2:442–443 stock collapse/range collapse, 2:437–438, 2:439F food and predators, 2:434–436 anti-predator tactics, 2:435 competition strategies, 2:434 feeding methods, 2:434 food location, 2:434 grouping advantages, 2:434–435 predator avoidance, 2:434 predator behavior herding, 2:436 pack hunting, 2:436 splitting off individuals, 2:436 ‘twilight hypothesis’, 2:436 predator inspection behavior, 2:435–436 ‘tit-for-tat’ altruistic behavior, 2:436 shoal detection by predators, 2:434 shoaling behavior key factors, 2:434 shoal size and success, 2:435 genetic basis for behavior, 2:436–437 British minnows experiment, 2:436–437 ‘how’ and ‘why’ questions, 2:432, 2:433T inter-fish/inter-school distances, 2:443F learned behavior vs genetic basis, 2:436 other functions, 2:437 direction correction, 2:437 energy efficiency, 2:437 parasite reduction, 2:437 school rules and size, 2:432–433 effects of individual size, 2:432–433 influence of food/predation regime, 2:432 join, leave or stay (JLS) decisions, 2:432 spatial relationships, 2:432 sensory system, 2:433–434 lateral line system, 2:433–434 senses used, 2:433 vision, 2:433 see also Fish feeding and foraging; Fish locomotion; Fish predation and mortality Fish silage, pelagic fishery products, 5:471 Fish species biology, 3:122 Fish stocks determining factors, 2:519 distribution, marine protected areas, 3:674 excess fishing capacity effects, 2:544 management see Fishery management manipulation see Fishery stock manipulation
494
Index
Fish swimming see Fish locomotion Fish vertical migration, 2:411–416 multiple controls model, 2:415–416, 2:416F pattern examples, 2:411 type I, 2:411, 2:414 type II, 2:411, 2:411F, 2:412F, 2:414 pattern variations, 2:411–412 changes between types I and II, 2:412 genus/species, 2:412, 2:413F individual patterns, 2:411–412 influence of environmental conditions, 2:412 influence of size, 2:412 population/site, 2:412 seasonal patterns, 2:412 periodicities, 2:411 potential factors influencing, 2:412–413 commensal species, 2:414 endogenous circadian rhythm, 2:412 estuarine fish, 2:413–414 food, 2:414 intertidal fish, 2:413 jellyfish associations, 2:414 light, 2:412–413 migration of prey, 2:414 sensor mechanisms, 2:414 tides, 2:413–414 reasons for study, 2:411 survey difficulties, 2:416 theoretical explanations, 2:414–415 bioenergetics, 2:414–415 feeding-predator avoidance balance, 2:415 optimization models, 2:415 predation, 2:415 predator avoidance, 2:415, 2:415F see also Demersal fish(es); Fish feeding and foraging; Fish horizontal migration; Fish locomotion Fish vision, 2:445–457 adaptations, 2:474 optimal visual pigment, 2:474 use of light as camouflage, 2:474 use of photophores, 2:474 varied visual environments, 2:474 diversity of environments, 2:446F environmental adaptations, 2:445 image formation, 2:445–446 asymmetrical/odd-shaped eyes, 2:445, 2:446F, 2:447F focusing, 2:445–446, 2:447F lens, 2:447F resting eye, 2:445 light/dark adaptation, 2:450 structural changes, 2:450, 2:454F ocular filters, 2:446–448 deep-sea fishes, 2:448 overcoming drawbacks, 2:447–448, 2:449F reflective corneal layers, 2:446–447 short-wave absorbing, 2:446–447 pupils, 2:446 constriction/dilation, 2:446, 2:448F retinal structure, 2:448–450 basic structure, 2:448, 2:450F
regional variations, 2:449–450, 2:453F rods/cones, 2:451F, 2:452F species variation, 2:448–450 cone arrangement, 2:449, 2:453F multiple cones, 2:449 reflective tapeta, 2:449, 2:452F rods/cones, 2:448–449 typical teleost eye, 2:446F visual abilities, 2:454 absolute sensitivity, 2:454 contrast, 2:454–455 measuring, 2:455 detection, 2:454 distance perception, 2:456–457 visual angle, 2:456–457 importance, 2:454 polarization, 2:457 polarization sensitivity, 2:457 spatial resolution, 2:455–456 acuity, 2:455–456 minimum resolving angle, 2:455–456 neural processing, 2:456 spectral responses, 2:456 limits, 2:456 proving color vision, 2:456 visual pigments, 2:450–451 spectral absorption, 2:451–454, 2:454F bioluminescence detection, 2:453, 2:455F cone visual pigment, 2:453–454, 2:456F fresh/saltwater species differences, 2:452–453 optical environment, 2:453, 2:455F optimization, 2:454 range, 2:451–452 structure, 2:450–451 chromophore and opsin, 2:450–451 factors affecting absorption spectrum, 2:451 see also Bioluminescence; Inherent optical properties Fissurella spp. (giant keyhole limpets), 4:768 Fistulariidae (cornet fishes), 2:395–396F Fitzroy-East (Australia), sediment load/ yield, 4:757T Fixed nitrogen assimilation, 4:44–45 estuarine sediments and, 1:548 see also Nitrogen (N) Fixed point observations, internal waves, 3:268 Fixed-potential amperometry (FPA), 6:104, 6:104T Fjords see Fiord(s) Flags of convenience, National Control and Admiralty Law, 5:405, 5:406T Flag state responsibility, fishery management enforcement, 2:524 Flakes, as primary particles, 4:331F, 4:332 see also Particle aggregation dynamics
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Flash evaporation, ocean thermal energy conversion, 4:169–170 Flatback turtle (Natator depressus), 5:218–219 see also Sea turtles Flatfish (Pleuronectiformes), 2:395–396F biomass, north-west Atlantic, 2:505–506, 2:506F population density, body size and, 4:704 Flat oysters, 4:277 Fleet see Fishing fleets; Shipping; World fleet Fletcher’s Ice Island, 1:92 FLIM (fluorescence lifetime imaging), 2:583–584 FLM (fluorescence line height), 2:587 Float(s), 2:171–178, 2:174–176 acoustic, 2:174, 2:176–177 data interpretation, 2:175 instrumentation, 2:174–175 modification to glider, 2:176 position, determining, 4:117 sampling schemes, 2:174 schematic, 2:175F vertical water velocity measurement, 2:177 see also Drifters Floating mud clasts, 5:463 Floating tidal plant, 6:29–30 turbine power, calculation of, 6:30 Float measurements deep convection, 2:21 deep convection plumes, 2:16 Floc deep-sea ridges, microbiology, 2:77, 2:78, 2:78F eruption indicator, 3:853–854 hydrothermal vent ecology, 3:154–155, 3:154F Floc layers, 2:548–553 benthic environment, significance of, 2:550–553 characteristics, 2:549–550 composition, 2:549–550 methods of examination, 2:548 phytodetrital layer see Phytodetrital layer regional variations, 2:548–549 seabed as an interface, 2:548 temporal variations, 2:548–549 Flooding/floods coastal see Coastal flooding rivers, impact to, 4:755 Flood warning systems, storm surges, 5:532, 5:536 Florida Bay, eutrophication, 2:315–317, 2:320F Florida Current, 1:720–721, 2:554, 2:556, 2:561, 3:293F Guldberg-Mohn friction coefficient, 3:291 transport, 1:721, 1:724T, 2:556, 2:557–558, 3:291 see also Atlantic Ocean current systems
Index Florida Current, Gulf Stream and Labrador Currents, 2:554–563 current rings see Current rings Deep Western Boundary Current (DWBC) see Deep Western Boundary Current (DWBC) Florida Current see Florida Current Franklin-Folger chart, 2:554, 2:555F generating forces, 2:554–556 wind driven circulation, 2:555–556 Gulf Stream System see Gulf Stream System interannual variations, 2:557–558 Labrador Current see Labrador Current measurement and observation, 2:554, 2:557 history of, 2:554 see also Satellite remote sensing of sea surface temperatures meridionial overturning circulation (MOC), 2:554–555, 2:556F North Brazil Current (NBC) see North Brazil Current (NBC) recirculating gyres, 2:558–560, 2:561F, 2:562–563 Slope Water gyre, 2:562–563 seasonal variations, 2:557–558 South Atlantic Water, 2:561 transport, 2:556 see also Benguela Current; Brazil and Falklands (Malvinas) Currents; Intra-Americas Sea (IAS); Mesoscale eddies; Thermohaline circulation; Wind-driven circulation Florida manatee (Trichechus manatus latirostris), 5:437, 5:438F, 5:441F, 5:443F see also Manatees Floridan aquifer, 5:553 Florida Strait, 3:286F, 3:287 Florisphaera profunda coccolithophore, 1:606F, 1:609 Flotsam, as Langmuir circulation tracers, 3:404–405 Flounders (Platichthyes americanus) fishing effects, 2:206 thermal discharges and pollution, 6:13 Flow, 5:463 Eulerian, ocean circulation, 4:115–116, 4:116–117, 4:116F Eulerian description, formulation, Lagrangian formulation vs., 3:389, 3:389–391, 3:390–391F, 3:393 Reynolds decomposition, 4:732 Flow cytometers underwater, development of, 6:117–118 see also Analytical flow cytometry (AFC) Flow cytometry (FCM), 1:272–273, 2:582–583, 2:586T Flow injection analysis (FIA), 6:327–329 advantages, 6:327, 6:328, 6:329 air-segmented continuous flow analysis vs., 6:327 applications, 6:327 water industry, 6:327
in-situ, 6:329 submersible sensors, 6:329–330 manifold arrangement, 6:328F principles, 6:328, 6:328–329 simultaneous nitrate and nitrite determinations, 6:327 system, 6:328, 6:328F periodic mixing, 6:327 Flow slide, 5:450 see also Mass transport Fluid(s) accretionary prisms see Accretionary prisms definition, 5:463 microscopic/macroscopic laws for interactions, 3:21 Fluid dynamics coordinate transformation, 5:136 definition, 5:463 laboratory experiments, 2:578–580 advantages, 2:579, 2:580 to ascertain parameters, 2:578 beyond current theory, 2:578–579 influence on ocean observation, 2:579–580 purposes, 2:578 to test theoretical predictions, 2:578 unexpected discoveries, 2:579 modeling and, 5:135–136, 5:136 see also Fluid parcels Fluid mechanics, definition, 5:463 Fluid parcels definition, 5:136 mass, 5:136 mass conservation, 5:136 meddies, 3:705 momentum, 5:137 time-stepping, 5:138 tracers, 5:136–137 velocity, 5:138 see also ‘Equation of state’ (of sea water) Fluorescence, 2:589–590, 3:245 accessory pigments, 2:582 chlorophyll, 4:245, 4:246F, 4:734 colored dissolved organic matter, 4:417 coral-based paleoclimate research, 4:339T, 4:341 decay times, 2:589, 2:592–593 definition, 2:581 emission spectra, 2:589 absorption spectrum and, 2:589, 2:589F compared with absorption spectra, 2:582F gelbstoff, 4:734–735 phycobiliproteins, 4:245 polarization, 2:590 measurement, 2:591 quenching, 2:592 dynamic, 2:592 static, 2:592 Stern–Volmer equation, 2:592, 2:592F reflectance (optical) spectra and, 4:734 variable induction, 2:583 water-column, Massachusetts Bay, 4:481F
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yield, 2:581 see also Fluorometry Fluorescence in situ hybridization (FISH), 2:583 Fluorescence lifetime imaging (FLIM), 2:583–584 Fluorescence line height (FLM), 2:587 Fluorescent dyes, near00727infrared, 2:583 Fluoride (F-) concentration in sea water, 1:627T determination, 1:626 concentrations in krill, 5:515 Fluorocarbon refrigerants, ocean thermal energy conversion, 4:169 Fluorometers, biological sensing, 2:581, 2:582, 2:582F scales of sampling, 2:586T Fluorometry biological sensing, 2:581–588 advantages, 2:581 algal and aquatic plant productivity, 2:583–584 estimating abundance, 2:581–582 fluorescence defined, 2:581 phylogenetic discrimination, 2:582–583 physiological applications, 2:583–584 scales of productivity measurements, 2:583–584 chemical sensing, 2:589–595 applications, 2:591–593, 2:593–594, 2:594T direct sensing, 2:590–591 applications, 2:593–594, 2:593T excitation–emission matrix spectroscopy, 2:590, 2:591F Raman standard, 2:590, 2:590F time-resolved, 2:590–591, 2:592F X-ray, 2:593T, 2:594 indicators and sensors, 2:590–591, 2:594T applications, 2:593–594, 2:594T device components, 2:591 measurement of fluorescent species in sea water, 2:593–594, 2:593T techniques, 2:589–590, 2:594 see also Carbon cycle FRR, 2:583 iron fertilization experiments, 3:336 pump and probe, aircraft for remote sensing, 1:141 see also Fluorescence Flushing, definition, 2:303 Flushing time, 2:303 definition, 3:774 eutrophication, 2:309, 2:310F Fluvial inputs, 1:120 trace metals, 1:126, 1:126T Flux definition, 5:382 measurements see Micrometeorological flux measurements see also specific fluxes Flux chamber, 3:2–3 Flux estimation, bulk formulae, 3:107
496
Index
Fluxgate magnetometers, 3:479 Flyaway mode, remotely-operated vehicles (ROV), 6:259 Flying fish (Exocoetidae), 2:369–370, 2:395–396F topographic eddies, 6:57 Flying gurnads (Dactylopteridae), 2:395–396F FMPs (Fishery Management Plans), 2:515 Foams, 6:306 syntactic, 3:920 Focal plane array (FPA) detector technology, 3:329 problems with, 3:329 Focusing (surface waves) dispersive, 4:772 spatial, 4:772 Fokker-Planck equation, behavior affecting small-scale patchiness, 5:485 Follows’ marine ecosystem model, 2:598 Food additives, marine organisms, 3:568–571 Food and Agriculture Organization (FAO), 3:748 assessments of fishery resources, 2:491–492 reviews of fishery resources see Global state of marine fishery resources statistical areas, 4:226, 4:227F, 4:231T, 4:232–233 Food webs, 2:379, 2:596–603 Arctic Ocean, 4:518 bacterioplankton, 1:274, 1:274–275 see also Bacterioplankton basic theory, 2:596–598 carbon cycle, 2:597 community stability, 2:597–598 Follows’ marine ecosystem model, 2:598 Lotka-Volterra model of predator–prey dynamics, 2:596, 2:597F NPZ models, 2:597 research needs, 2:598 cephalopods, 1:528–529 copepods, 1:650 descriptions, 2:596 ecological complex, coupled to water circulation model, 4:723–724, 4:724F exponential population growth, 4:723–724, 4:724F fiordic ecosystems, 2:364, 2:364F fisheries and, 2:598–600 impacts of species removal, 2:599–600 monitoring changes, 2:598–599 overfishing, 2:600–602 function and stability, 2:598 aggregated species models, 2:598 Bering Sea food web, 2:598, 2:599F link to food web dynamics, 2:598 future research applications, 2:602 general structure properties, 2:600
habitat comparisons, 2:600 network structures, 2:600, 2:600F investigations gaining prominence, 3:124 krill, 3:355 lagoons, 3:385F large marine ecosystems, 3:418–419 meiobenthos, 3:726, 3:730 microbial loops, 3:800–802, 3:801F see also Microbial loops micronekton, 4:2F Mid-Atlantic Bight, biomass (observed/ simulated), 4:727, 4:728F network analysis see Network analysis of food webs ocean gyre ecosystems, 4:136–137 open ocean, 4:132 overfishing and biodiversity, 2:600–602 network structure and interaction, 2:601–602, 2:601F subwebs approach, 2:602 trophic cascades, 2:600–601 plankton, 4:457–458, 4:459 plankton viruses, 4:469–470 polar ecosystems, 4:514–516, 4:516F population models and, 4:554 predicting ecosystem responses to perturbations structure approach, 2:600 structure-dynamics approach, 2:600–601 structure-strength approach, 2:601–602 subwebs approach, 2:602 research uses, 2:596 allometry and scaling laws, 2:596 biodiversity and genetic diversity, 2:596 ecological network structure/ dynamics, 2:596 energy flow and balance, 2:596 marine macroecology, 2:596 predator–prey relationships, 2:596 rocky shores, 4:766–767 sandy beaches, 5:52–54, 5:54F Southern Ocean, 4:518 structure, diversity and function, 2:596 upwelling ecosystems see Upwelling ecosystems see also Network analysis of food webs; Upwelling ecosystems ‘Footprints of turbulence’, 2:612 Foraging definition, 3:603 fish see Fish feeding and foraging marine mammals see Marine mammals seabirds see Seabird(s) see also specific species Foraging ecology, beaked whales (Ziphiidae), 3:646 see also Beaked whales (Ziphiidae) Foraminifera, 3:912, 3:915F abundance, sea surface temperature and, 2:109F benthic see Benthic foraminifera
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calcium carbonate content, paleological series, 1:452F calcium carbonate production, 1:445 carbonate oozes, 1:446F carbon isotype profile, Arabian Sea, 3:916F effects of global warming, 4:459, 4:459F fossilized, 3:911 fragmentation, 1:449F paleological record, 1:452F hypoxia, 3:177 oxygen isotope variability, glacial cycles and, 4:505 oxygen isotype profiles, Arabian Sea, 3:915F paleothermometric transfer functions and, 2:110–111 planktonic see Planktonic foraminifera shells, 2:102F dissolution, 1:449–450 see also Planktonic foraminifera Foraminifers benthic see Benthic foraminifera planktonic see Planktonic foraminifera Forcing atmospheric see Atmospheric forcing habitat modification see Habitat modification Forecasting/forecasts climate change, 5:99–101 El Nin˜o see El Nin˜o loss of predictability and, 2:3 regional, data assimilation for see Data assimilation in models weather, for coastal regions, satellite remote sensing, 5:112–113 Forecast systems application of coastal circulation models, 1:574F, 1:577–578, 1:578F, 1:579 see also individual systems (e.g. Coastal Ocean Forecast System) Foreign policy, marine policy overlap, 3:664T Forel, F A, 5:345 Formaldehyde, oxidation, 1:542–543 Formation Microscanner (FMS), 2:50–51 Form drag, 6:145–146, 6:146F Forward models, 4:93, 4:103 disadvantages, 3:302 Forward numerical models, 2:604–611, 3:312 advantages, 2:604 application, 2:604 configuring, 2:604 data discrepancies, 2:604 discretization issues, 2:606–607 error types, 2:606 isopycnal coordinates, 2:607, 2:607F level coordinates, 2:606, 2:607F spectral discretization, 2:606 stretched coordinate models (terrain-following), 2:606–607, 2:607F surface intensity density gradients, 2:606
Index truncation errors, 2:606 vertical discretization, 2:606 equations of motion, 2:604–606 advantage of primitive equations, 2:605 analytic solutions, 2:604 Boussinesq approximations, 2:604–605 continuity equation, fluid incompressible, 2:605 disadvantage of primitive equations, 2:605 dissipative processes, 2:605 horizontal momentum balance, 2:605 Navier–Stokes equations, 2:604–605 quasigeostrophic equations, 2:605–606 vertical momentum balance, 2:605 equations of motions, 2:605–606 initial and boundary conditions, 2:607–609 boundary conditions, 2:608 diapycnal turbulent mixing and, 2:610 heat flux components, 2:608–609 initial conditions, 2:607–608 lateral boundary conditions, 2:608 no-slip/free-slip momentum equations, 2:608 planetary boundary layer model, 2:609 regional models, variables from ‘observations’, 2:608 salinity, conservation equations, 2:609 short-term simulations/integrations, 2:607–608 surface fluxes for heat/salt and momentum, 2:608 mean and time-dependent characteristics, 2:604 mesoscale eddies, 2:610 primitive equation models, 2:605, 2:608 subgridscale parameterizations, 2:609–611 bulk models and local closure models, 2:610 downgradient diffusion, 2:610 mesoscale eddies, 2:610 scales/classes of motion, 2:609 temporal variations, 2:609 turbulent mixing properties, 2:609–610, 2:610 see also Regional models Forward problem, in numerical models, 2:604–611 see also Forward numerical models ‘Forward solution,’ inverse method vs, 3:312 Fossil(s) Alcidae, 1:171 pelecaniform birds, 4:370 penguins modern penguins and, 5:521–522 size, 5:521 Waipara (New Zealand), 5:520
plankton, 3:911, 3:912 sea turtles, 5:213 sirenians, 5:436 Fossil assemblages, SST transfer functions, 2:108–110 Fossil layers, 6:221–222 Fossil record, hydrothermal vent organisms, 3:149–150 evolution of vent communities, 3:149–150 fossilization processes, 3:149 Fossil ridge volcanoes, 5:300, 5:301F Fossil-scalar-turbulence, 2:614 Fossil spreading centers, 5:300, 5:301F Fossil-temperature-turbulence, 2:613–614 Fossil turbulence, 2:612–619 dark matter paradox, 2:617 dark mixing, 2:613 definition, 2:617–618 dropsonde Cox number samples, probalility plot, 2:613, 2:613F formation, 2:614, 2:618 gravitational structure formation, theory of, 2:612 history, 2:612, 2:614–616 mixing and, 2:616–617 oceanic turbulence, intermittency of, 2:616–617 patches, 2:612, 2:613 quantification methods, 2:618–619 rotating fossils, 2:614 stratified fossils see Stratified fossil turbulence Fossil-vorticity-turbulence, 2:612, 2:614 Fossil water, 4:564 Fouling organisms, oyster farming, risk to, 4:284 Four-eyed fish (Anableps anableps), 2:447F Fourier analysis, current flow variability, 4:118–119, 4:118F Fourier transform infrared spectrometers (FTIR), 3:327–328, 3:328F, 3:329–330 FPA (fixed-potential amperometry), 6:104, 6:104T Fractal geometry, definition, 4:337 Fraction modern carbon, 5:420 Fracture, ice shelves, 3:213–214 Fracture zones definition, 2:123 seismic structure, 5:364–365 Fram, 3:207, 5:159, 6:155 FRAM II ice camp, 1:95F Fram Strait, 1:92, 6:171 nuclear fuel reprocessing tracers, 4:87–88 transport, 1:223 water column profiles, 1:214F France aquaculture development levels, 3:535 see also Mediterranean species, mariculture water, microbiological quality, 6:272T
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Franciscana dolphin (Pontoporia blainvillei), 2:153, 2:153F, 2:155–156 Franklin-Folger chart, 2:554, 2:555F Fraser’s dolphin myoglobin concentration, 3:584T see also Oceanic dolphins Fratercula, 1:171T diet, 1:174 see also Alcidae (auks) Fratercula arctica (Atlantic puffin), 1:171, 1:173F F-ratio, 6:93 Frauenhofer laser diffraction instruments, 3:246 FRAZ displays, passive sonar beamforming, 5:512 Frazil ice, 5:173, 6:161–162 formation, transmissometers in study of, 6:117T ‘Freedom of the sea,’ marine policy, 3:666 Free vehicle grab respirometer (FVGR), 4:486, 4:487F Freezing point, seawater, 6:382–383 Fregata minor (great frigatebird), 4:372F Fregatidae (frigatebirds), 4:370, 4:371 breeding patterns, 4:371 characteristics, 4:371, 4:376T distribution, 4:371 feeding patterns, 4:371, 4:376T migration, 5:242–244 species, 4:371, 4:372F see also Pelecaniformes; specific species French Research Institute for Exploitation of the Sea (IFREMER), 5:76 French Research Institute for Exploration of the Sea (IFREMER) autonomous underwater vehicles, 6:263T deep-towed vehicles, 6:256T human-operated vehicles (HOV), 6:257T remotely-operated vehicles (ROV), 6:260T Frequency-azimuth (FRAZ) displays, passive sonar beamforming, 5:512 Frequency spectrum, current flow variability, 4:118–119, 4:118F Fresh submarine groundwater discharge, 3:88 drivers, 3:89–90 Fresh water added in polar regions, 4:130–131 balance, ocean circulation, 4:122–124, 4:123F flow from rivers, 4:126 glacial meltwater, 4:127–128 mixed-layer buoyancy and, 6:341 ocean thermal energy conversion, 4:172 outflows, rotating gravity currents, 4:790, 4:792, 4:794F transport, Weddell Sea circulation, 6:318 upper ocean mixing, 6:190, 6:190F Fresh water-brackish water interface (FBI), 3:769
498
Index
Freshwater flux, 5:129–130, 5:130, 6:170–171 barrier layer formation and, 6:222 Mediterranean Sea circulation, 3:710, 3:712–714 Red Sea circulation, 4:666, 4:675–676 satellite remote sensing, 5:207–208, 5:210F upper ocean, 6:165 see also Precipitation; Salinity; Upper Ocean Freshwater fronts, 5:391–392, 5:391F creation, 5:392 mixing, 5:392 position, 5:391–392 Freshwater trout, farming, 5:23 Fresnel reflection, 5:128 incidence angle, 5:128, 5:130, 5:131, 5:131F Friction Ekman transport and, 6:142F ocean models, 5:137 Friction velocity, 6:142–143 Friedmann-Keller series, 4:210 Frigg oil field, wave data, 4:777 Friis, Peder Claussøn, 2:484 Frillfin goby (Bathygobius soporator), 3:282 Fringing reefs, geomorphology, 3:34, 3:34F, 3:37 Friza Strait, 4:201 Frontal regions definition, 3:295 salinity, 3:295, 3:296F temperature, 3:295 Frontal zone, 2:216 Fronts definition, 5:391 oceanic, one-dimensional models and, 4:215–217 positions, satellite remote sensing of SST, 5:99 satellite remote sensing application, 5:108–109, 5:108F, 5:109F seabird abundance and, 5:228, 5:228F shelf sea, 5:391–400 upper ocean, 6:213–214 see also Freshwater fronts; Shelf break; Shelf slope fronts; Tidal mixing fronts Froth flotation, 3:896 Froude number, 3:374, 6:61 hurricane Katrina, 6:195T hurricane Lili, 6:195T FRR fluorometry (fast repetition rate fluorometry), 2:583, 2:584F Fs, definition, 6:242 FSI 3D ACM acoustic travel time, 5:430T F-specific RNA phages, sewage contamination, indicator/use, 6:274T Fucus, 3:773, 3:773T Fuel rods, 4:83 Fuels, marine organisms, 3:572–573 Fuglister, Fritz, 3:758
Fulmar(s), 4:590 breeding success, 5:255 migration, 5:240–242, 5:241T northern see Northern fulmar (Fulmaris glacialis) see also Procellariiformes (petrels) Fulton, Robert, copper submarines, 3:513 Fundulus heteroclitus (killifish), 2:371, 5:45 Fundy, Bay see Bay of Fundy, Gulf of Maine Fungi, lipid biomarkers, 5:422F Fur seal see Arctocephalinae (fur seals); Arctocephalus gazella (Antarctic fur seal) Furunculosis, mariculture disease, 3:520T, 3:521 Fw, definition, 6:242 Fye, Paul, 3:665 Fyke nets, traps, fishing methods/gears, 2:540–541, 2:541F
G Gadfly petrels, 4:590 migration, 5:240, 5:241T see also Procellariiformes (petrels) Gadiformes, 2:395–396F Gadoids acoustic scattering, 1:65 biomass, north-west Atlantic, 2:505–506, 2:506F, 2:509, 2:509F North Sea outburst, 2:508 Gadus see Cod (Gadus) Gadus macrocephalus (Pacific cod), population, El Nin˜o and, 4:704 Gadus morhua (Atlantic cod) see Atlantic cod (Gadus morhua) Gakkel Ridge, 1:211, 3:846, 3:846F, 3:870F Galactic radiation, 5:130 Galapagos 95.51W propagating rift system, 4:597–600, 4:599F lava composition, 4:600, 4:600F Galapagos hot spot, rift propagation, 4:597–600, 4:600–601 Galapagos Islands chlorophyll a concentrations, 5:124F coral records, 4:341–342, 4:343F, 4:344F global sea level variability, satellite altimetry, 5:62–63, 5:62F Galapagos Mounds Field, clay mineral profile, smectite composition, 1:567T Galapagos penguin (Spheniscus mendiculus), 5:522, 5:522T, 5:523, 5:527 climate change responses, 5:263, 5:263F see also Spheniscus Galapagos Rift hydrothermal vent biota, 3:133–134 Alvin exploration, 3:133 fish, 3:139–140, 3:140F
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tubeworms, 3:139, 3:141–142 vesicomyid clams, 3:137F survey of hydrothermal venting, 6:265 Galapagos Spreading Center, 3:873F clay mineral formation, 1:566 clay mineral profile, 1:566F smectite composition, 1:567T geophysical heat flow, 3:46 hydrothermal vent fluids, temperature and venting style, 3:167–168 seismicity, 3:843F see also Cocos-Nazca spreading center; Eastern Galapagos Spreading Center Galatheid crab (Munidopsis subsquamosa), 3:136F, 3:138, 3:138F, 3:139F Gallegos, A, Yucatan Current, 3:289 Gallium concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:690–691 depth profile, 4:692F properties in seawater, 4:688T surface distribution, 4:690F Gallium triple point cell, 1:710 Galvanic couples, 2:247, 2:252 gn labels, 4:28, 4:29F deviation from neutral tangent planes, 4:29, 4:30F Gamov concept, 2:612 Ganges/Bramaputra dissolved loads, 4:759T river discharge, 4:755T sediment load/yield, 4:757T Gannets see Sulidae (gannets/boobies) Garrett-Munk spectrum, 3:269F, 5:358–359 Gas(es) atmospheric contaminant deposition, 1:238 chemical sensors, absorptiometric, 1:13 ice solubility, 4:56 solubility, 1:157 definition, 3:7 estuaries, gas exchange in, 3:1 transport, deep convection, 2:15 see also entries beginning gassee individual gases Gas carriers, 5:404 Gas chromatography nitrogen isotope analysis, 4:40–41 sulfur hexafluoride and, 6:90–91 see also Preparative capillary gas chromatography Gas exchange air–sea transfer see Air–sea gas exchange estuaries see Estuaries investigated by uranium-thorium decay series, 6:242T open ocean convection, 4:218, 4:222–223 Gas flux, 1:157–158 Gas hydrates, 2:41, 5:559 clathrates, 3:792
Index formation of, 2:49 see also Methane hydrate(s) Gasoline, leaded see Leaded gasoline Gaspe current, 4:793 Gasteropelecidae (hatchet fishes), 2:395–396F Gasterosteus aculeatus (three-spined stickleback), 2:378 Gas transfer bubbles, 1:442 surface films, 5:571 Gas transfer velocity, k, 1:169 Gastrodemal, definition, 1:677 Gastrointestinal infection, beaches, microbial contamination, 6:268 Gastropods habitat, 3:899 production, global, 3:905–906, 3:906F Gastrosaccus spp. (mysid shrimp), 5:52F Gauss–Markov estimation, 6:44–45 Gauss–Markov method, 3:314–315, 3:314F, 3:316 Gauss’ theorem, 4:94–96 Gaviiformes, 5:266T see also Seabird(s) Gaviota slide, 5:453F Gazami crab see Swimming crab (Portunus trituberculatus) GCM see General circulation models (GCM) Gdansk Basin, Baltic Sea circulation, 1:288, 1:289F GDH1 heat flow model, 3:45 GEF see Global Environment Facility (GEF) GEK (geomagnetic electrokinetograph), 2:253 Gelatinous animals, observed using human-operated vehicle, 6:257 Gelatinous zooplankton, 3:9–19 body form evolution adaptations, 3:9 common form, 3:9 environmental impact, 3:9 ecology, 3:18–19 fragility, 3:18 see also Zooplankton sampling geographical and depth distribution, 3:18 outcompeting other animals, 3:18 research method advances, 3:18 seasonal blooms, 3:18 trophic niche distribution, 3:18 observed using human-operated vehicle, 6:257 polar midwater regions, 4:516–517 taxonomic groups, 3:9 cephalopods, 3:14–16 crustaceans, 3:16 ctenophores, 3:12 see also Ctenophores heteropods, 3:14 holothurians, 3:16 medusae, 3:9–10 see also Medusae
pelagic tunicates, 3:16 Doliolida, 3:16–17 Larvacea/Appendicularia, 3:18 Pyrodomida, 3:16 Salpida, 3:17–18 polychaete worms, 3:16 pteropods, 3:14 see also Pteropods Radiolaria, 3:9 siphonophores, 3:10–12 see also Siphonophores vertical migration, 2:414 see also Bioluminescence, plankton Gelbstoff absorption spectra, 4:734, 5:116F coastal areas, 4:734 fluorescence, 4:734–735 spectral absorption, 3:245 spectral range for remote sensing, 4:735T see also Colored dissolved organic matter (CDOM) Gelendzhik, 1:407 Gel particles, 4:331F, 4:332–333, 4:333F see also Particle aggregation dynamics General cargo/container ships, see also World fleet General circulation models (GCM), 3:20–24 aims of large-scale models, 3:20 biogeochemical state variables, 4:725–726 carbon cycle, 4:111–112 computing power, 3:21 correction by data assimilation, 3:20 definition, 3:20 heat equation, 3:20 momentum equation, 3:20 ecological realism limited, 4:725–726 elements of, 3:20 El Nin˜o Southern Oscillation, 2:242 glacial cycle modeling, 4:509 lateral boundary conditions, 4:727 limits/errors, 3:22–23 conservation properties, 3:22 convection, 3:22 dissipation, 3:22 numerical viscosity, 3:22 momentum (vorticity) equation, 3:22 numerical methods, 2:606 reality link (causal), 3:22 robustness, 3:20 sensitivity, 3:21 suggestive not predictive nature of, 3:21 theory and practice, 3:21–22 backward compatibility, 3:21 classical modes/physical laws, 3:21 confinement of form, 3:21 expression in quantity/extent and duration, 3:21 falsifiability, 3:21, 3:22 violation of principles, 3:22 see also Coastal circulation models
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Generalized inverse problems, control theory, in data assimilation, 2:7 Generalized Yield Model, Southern Ocean fisheries management regime, 5:518 General Ocean Turbulence Model (GOTM), 4:210, 4:211F General purpose vessels, 5:415 coastal vessels, 5:415 flexible scientific facilities, 5:415 increased size, 5:415 multidiscipline vessels, 5:415 Genetic algorithms, direct minimization methods, in data assimilation, 2:8 Genetic considerations, stock enhancement/ocean ranching programs, 2:531–532, 4:153 Genetic diversity within species, 4:557 see also Population genetics of marine organisms Genetic modification, salmonid farming, 5:25 Genetics see Population genetics of marine organisms Genomics see Algal genomics and evolution Genomic techniques, 1:269 Genotoxins, 3:565 Gentoo penguin (Pygoscelis papua), 5:522T, 5:525 see also Pygoscelis Geoacoustic models, 1:115 Geoacoustic parameters marine sediments see Acoustics, marine sediments measurement see Acoustic remote sensing; In situ measurement techniques; Sediment core samples Geochemical cycling, bubbles, 1:441–442, 1:441F Geochemical Ocean Sections Study (GEOSECS), 1:488, 2:255, 3:123, 3:302, 6:278 carbon isotopes, 5:529 initiation and role, 2:255 oxygen isotope ratios, 4:272 radioactive wastes, 2:255, 4:633–634 radiocarbon, 4:640–641, 4:644, 4:645F uranium-thorium decay series, 6:240 Geochemical Ocean Sections Study (GEOSECS) nephelometer, 4:8 Geochemical sections, radioisotope tracers and, 1:684 Geochemical studies, deep submergence science studies, 2:29–30 Geochemical tracer techniques, 1:153 Geographical cycle of erosion, 3:34, 3:34F Geographic Information Systems (GIS), mariculture, location determination, 3:908 Geohazards, 5:463 Geoid, 3:80, 3:756, 5:58–59 definition, 4:119 long-wavelength anomalies, 3:85–86
500
Index
Geoid (continued) models, extraordinary gravity field data, 5:61 see also Gravitational potential energy Geological Long Range Inclined Asdic (GLORIA), 5:464 Geological timescales geomorphology, 3:35, 3:36F coral reefs, 3:37 sandy coasts, 3:37–38 sea level change, 3:35 Geology, symmetrical resolution requirements, 1:299T Geomagnetic electrokinetograph (GEK), 2:253 Geomagnetic field ancient see Paleomagnetism polarity, 3:25 intervals, 3:25 calibrated ‘standard’ see Geomagnetic polarity timescale (GPTS) normal, 3:25, 3:25F reversals, 3:25, 3:25F, 3:26 see also Magnetic field, Earth Geomagnetic polarity timescale (GPTS), 3:25–32, 3:25, 3:27–30, 3:484F, 4:314 astronomical polarity timescale vs., 3:30 chrons, 3:28–30 standard nomenclature, development of, 3:30 CK95, 3:30 development, 3:28–30, 3:29F Cande and Kent, 3:30 Heirtzler J R, 3:28, 3:29F remnant magnetization of oceanic crust, 3:27–28, 3:28F subchrons, 3:28–30 standard nomenclature, development of, 3:30 see also Astronomical polarity timescale (APTS); Magnetics; Paleoceanography GEOMAR-SP ocean bottom seismometer, 5:368T, 5:371F Geometric acoustic spreading, power loss, 1:103 Geometrical spreading, see also Cylindrical spreading (sound) Geometrical spreading (acoustic), 1:118 see also Spherical spreading Geometric dispersion, 1:118 Geomorphology, 3:33–39 boundary conditions, 3:33 climate, 3:33 geophysical and geological, 3:33 oceanographic, 3:33 sea level change, 3:33 coral reefs see Coral reef(s) definition, 3:33 deltas see Delta(s) estuaries see Estuaries history, 3:34–35 Darwin, Charles, 3:34, 3:34F Davis, William Morris, 3:34, 3:34F
geographical cycle of erosion, 3:34, 3:34F Johnson, Douglas, 3:34, 3:34F see also Darwin, Charles mid-ocean ridge see Mid-ocean ridge tectonics, volcanism and geomorphology models of coastal evolution, 3:35–36 coastal systems, 3:35–36 conceptual, 3:34, 3:34F, 3:35 nonlinear dynamical systems, 3:35–36 paleoenvironmental reconstruction, 3:35 sediments and sedimentary evidence, 3:35 simulation modelling, 3:36 morphodynamics, definition, 3:33 muddy coasts see Muddy coasts processes and dynamic equilibrium, 3:34–35 rocky coasts see Rocky coasts sandy coasts see Sandy coasts scales of study, 3:35 spatial, 3:35, 3:35F timescales engineering, 3:35, 3:36F instantaneous, 3:35 see also Event timescales; Geological timescales uniformitarianism, 3:34 Geophone arrays, 1:87–88, 1:87F, 1:88F Geophysical flows, turbulence in, 6:21–22 boundary effects, 6:23 buoyancy effects, 6:22–23 energy transfer, 6:22 large-scale currents, 6:22 shear effects, 6:22, 6:23, 6:24F Geophysical heat flow, 3:40–48 anomalies, 3:45 Hawaiian Swell, 3:47F lithospheric processes, 3:45–46 hot spots, 3:46–47 hydrothermal circulation, 3:45–46 measurements and techniques, 3:40–43, 3:42F environmental corrections, 3:43 instrumentation, 3:40–43 location of measurements, 3:40, 3:41F probe spacing, 3:42–43 models, 3:44 data, 3:44 halfspace and plate models, 3:44–45 reference models, 3:45 ocean depth and, 3:44F ocean margins, 3:47 gas hydrates, 3:48 passive margins, 3:47–48 subduction zones, 3:47 parameter ranges, 3:43–44 hydrothermal circulation, 3:43 sediment thermal conductivity, 3:43–44 temperature gradients, 3:43 seafloor topography, 3:43 sealing age, 3:46
(c) 2011 Elsevier Inc. All Rights Reserved.
Geophysical measurement systems, deep-towed, 6:255 Geophysical research vessels, 5:416 MCS (multichannel seismic surveys), 5:416 purpose, 5:416 specialized design, 5:416 Geopotential anomaly measurements, Weddell Sea circulation, 6:319 George VI Ice Shelf, 5:548 temperature and salinity trajectories, 5:545F Georges Bank, North Atlantic, 2:458–460, 2:460F depth/circulation, effect on coastal ecosystem, 1:576–577, 1:576F, 1:577F Georges Bank frontal system, 5:396 Georgia, Black Sea coast, 1:211, 1:401 Geos-3 satellite, 3:83, 5:68 Geosat, 5:67F, 5:73–74 gravimetry, 3:83 GEOSECS see Geochemical Ocean Sections Study (GEOSECS) GEOSS (Global Earth Observation System of Systems), 5:77 Geostationary orbit, ocean color sensing and, 5:118 Geostrophic balance, definition, 4:119 Geostrophic circulation, global, dynamic sea surface topography, 5:59–61, 5:61F Geostrophic currents, 2:216 shelf slope fronts and, 5:398 wind driven circulation, 6:349, 6:349F Geostrophic flow columnar, 6:351, 6:352, 6:353–354 Rossby waves, 4:782, 4:783F Geostrophic principle, 3:302–303 Geostrophic turbulence, 5:134 potential enstrophy cascade, 6:287 fine-scale vortical mode generation mechanism, 6:287–288 Geostrophic velocity, 3:302–303 Geostrophy, 1:179 Geosynchronous orbit measurements of SST, GOES Imager, 5:97 Geothermal energy, internal energy budget and, 2:262–263 Geothermal heating, subterranean water flow and, 5:554F Gephyrocapsa oceanica coccolithophore, 1:606F Gerard barrel, radiocarbon, 4:640 Germanium (Ge), 3:776, 3:780 concentrations in ocean waters, 6:101T depth profile, 3:780, 3:780F methylated forms, 3:780, 3:780F, 3:783 Germanium:silicon ratio, as weathering vs. hydrothermal input tracer, 3:780 GESAMP (Group of Experts on Marine Environmental Protection), UN, 4:526 GFP (green fluorescence like proteins), 2:582
Index Ghost crabs (Ocypode spp.), 5:53F Ghost fishing pelagic fisheries, 4:237 Salmo salar (Atlantic salmon) fisheries, 5:3–4 Ghyben-Herzberg relation, 5:553 Giant clam (Tridacna squamosa), 3:141–142 Giant diatoms distribution, 3:651–653 ecological significance, 3:651–653 mass sinking, causes of, 3:653 ‘fall dump’, 3:652F, 3:653 ocean frontal systems, 3:653 Giant keyhole limpets (Fissurella spp.), 4:768 Giant petrels, 4:593 see also Procellariiformes (petrels) Giant tubeworm (Riftia pachyptila) see Riftia pachyptila Gibbs function, 4:30 Gibraltar, Straits see Strait of Gibraltar Gibraltar inflow, 3:710, 3:711F Gibraltar outflow, 3:710, 3:711F, 3:712–714, 3:717–718 Gigatons, 1:487 Gilbert, William, 3:478–479 Gill net(s), 2:539–540, 2:540, 2:540F drifting, 2:540 encircling, 2:540 fixed, 2:540 Pacific salmon fisheries, 5:12, 5:13 pelagic fisheries, 4:237, 5:468–469 Salmo salar (Atlantic salmon) fisheries, 5:1, 5:6 set, 2:540 vessel numbers, 2:544, 2:545F Gill-net fisheries, seabird by-catches, 5:265, 5:268–270, 5:268T, 5:272–273 Gilthead sea bream see Sparus aurata (gilthead sea bream) Gilvin see Colored dissolved organic matter (CDOM); Gelbstoff Gimbals, 3:105–106 Gippsland lakes, Victoria, Australia, 3:381, 3:383F GIS (Geographic Information Systems), mariculture, location determination, 3:908 Glacial crustal rebound, 3:49–58 Australia, Northwest Shelf, 3:58 Europe, 3:56–58, 3:57F Scandinavia, 3:56–58, 3:57F South East Asia, 3:57F, 3:58 Glacial cycles ice extent, 4:508F, 4:510F Milankovich variability and, 4:504–513 history, 4:504–505 orbital parameters and insolation, 4:504 Plio-Pleistocene, 4:507–509 modeling, 4:509–512 monsoon abundance relative to interglacials, 3:914 periodicity, 4:507F, 4:509F, 4:512
sea level changes, 3:50–51 from maximum levels, 3:51–53 Glacial-interglacial cycles, iron and, 6:82 Glacial maxima, 5:550 Glacial transitions, nitrogen isotope ratios, 4:53F Glaciation period, sub-sea permafrost, 5:560, 5:560F Glaciations climate change within, 1:4 see also Dansgaard–Oeschger (D/O) events; Heinrich events cyclicity, 1:1 deglaciations vs., atmospheric carbon dioxide and methane, 3:786 sea level variations and, 5:179, 5:185, 5:186, 5:186F Glaciers nonpolar, sea level variations and, 5:182, 5:182F, 5:183 ocean margin sediments and, 4:141 see also Land ice Glacio-hydro-isostatic models, 3:53–54 elastic deformation of Earth, 3:53 eustatic sea level, 3:54 formulation of planetary deformation, 3:53–54 gravitational pull of ice-sheet, 3:53 ice-volume equivalent sea level, 3:51F, 3:53 isostatic contribution to relative sea level, 3:53 isostatic contribution to sea level change, 3:54 response parameters of Earth, 3:53–54 see also Geomorphology Glass, in optical fibers, 1:8 Glass-bead thermistor, 2:294F Glass catfish (Kryptopterus bicirrhis), 2:451F, 2:456F Glass eels see Eels Glass spheres, on benthic flux landers, 4:489–491 Glauconite, hypoxia, 3:177 Glaucony, 1:567 formation, 1:568F GLC see Gulf Loop Current (GLC) Gliders (subaquatic), 3:59–66, 3:61F, 3:930, 6:261–262 advantages, 3:59 cost, 3:59 design, 3:60–62 disadvantages, 3:59 dive cycles, 3:62–63 diving and ascent, 3:62 history, 3:59–60 hydrodynamics, 3:63, 3:64F instrumentation, 3:63–64 longest deployment, 3:60 missions, 3:64–66 size, 3:60 specialized versions, 3:60 speed, 3:62, 3:63 thermal stratification engine, 3:62 volume displacement, 3:60
(c) 2011 Elsevier Inc. All Rights Reserved.
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wings, 3:60 WOCE floats as, 2:176 Gliding, 3:60 Global atmosphere metals, emission of, 1:242T see also Atmosphere Global-average sea level rise see Sea level rise Global-average temperature, predicted rise, 5:181 Global Boundary Stratotype Section and Point (GSSP), 3:30, 3:31F Global carbon cycle see Carbon cycle Global climate models (GCMs), 4:129–130 advantages, 4:113 carbon cycle, 4:111–112 chemical tracers and, 4:111 sea ice extent and global warming, 5:146 subgrid-scale parametrization, 4:111 see also Climate models Global climate system, Asian monsoon and, 3:917 Global conveyor belt, 1:16, 1:17F Global conveyor circulation see Thermohaline circulation Global cycling, of mass and energy, 2:49 Global Drifter Program, 2:173 Global Earth Observation System of Systems (GEOSS), 5:77 Global Environment Facility (GEF), 3:419 World Bank, 3:275 Global geostrophic circulation, dynamic sea surface topography, 5:59–61, 5:61F Global heat transport, 4:129 Global institutional frameworks, marine policy, 3:666–667, 3:667T Globalization, coral reef/tropical fisheries, impact, 1:651, 1:653 Global marine pollution, 3:67–69 changing priorities, 3:68 global attention to problem, 3:67–68 invasive species, 3:68 oil and human sewage, 3:67 perception of ocean dumping capacity, 3:67 ‘pollution’ defined, 3:68 radioactive waste and metals, 3:67 synthetic organics and plastics, 3:67 see also Pollution Global Maritime Distress and Safety System (GMDSS), 5:405 Global mean surface salinity, 5:127, 5:128F Global mid-ocean ridge (MOR) discoveries, deep submergence science studies, 2:24–26 observation using human-operated vehicles (HOV), 6:257 Global ocean atmospheric deposition, 1:242–244 circulation Mediterranean Sea circulation, 3:710 Weddell Gyre see Weddell Gyre
502
Index
Global ocean (continued) energy budget, 2:262–263, 2:268F sea–air flux of carbon dioxide, 1:493T tides, estimation from inverse methods, data assimilation, 2:11 Global Ocean Data Assimilation Experiment, 3:275, 5:381 Global Ocean Ecosystem Dynamics (GLOBEC) program, 3:124, 3:278 Global Ocean Observing System (GOOS), 3:275, 5:381 Global Positioning System (GPS), 3:891, 4:478 determining data measurement locations, 4:115, 4:116–117 drifter tracking, 2:173 oceanographic research vessels, 5:412 shallow-water manned submersibles using, 3:516–517 Global Precipitation Measurement (GPM) mission, 5:208 Global Programme of Action, land-based marine pollution, 3:440 Global sea level rise see Sea level changes/variations; Sea level rise variability, satellite altimetry, 5:61–62, 5:62F see also Sea level changes/variations; Sea level rise Global state of marine fishery resources, 3:576–581 analysis considerations, 3:576 exploitation levels, 3:576–578 compliance with UNCLOS requirements, 3:577 conflicting viewpoints, 3:577–578 management required, 3:577 situation of oceanic fish, 3:578, 3:578F UN-FAO definition of ‘full exploitation’, 3:576 UN-FAO stock classifications, 3:576 fully exploited, 3:576 overexploited and depleted, 3:576 percentages in each class, 3:576–577, 3:577F recovering, 3:576 underexploited and moderately exploited, 3:576 global trends, 3:578 changes in stocks since 1951, 3:580F changes in stocks since 1974, 3:578, 3:579F no evidence of improvements, 3:580 relative production levels, 3:576 compared to historical levels, 3:576, 3:577T state of stocks by region, 3:578 exploitation levels, 3:578, 3:579F UN-FAO data questioned, 3:579 data confirmation, 3:579 ‘new’ stocks included, 3:579–580 ‘overfished’ classification, 3:580 UN-FAO reviews, 3:576 see also Fishery resources
‘Global thermometer,’ satellite remote sensing of SST, 5:101 climate change forecast models, 5:99–101 global climate change problems, 5:99 thermal inertia of the ocean, 5:99–101 Global warming, 4:89, 4:105, 4:126, 4:128, 4:130–131 anthropogenic, 1:1, 1:5 sea ice coverage and, 5:146 see also Carbon dioxide (CO2) coral impact, 1:676 economics, 2:197 effect on ocean pH, 1:624 effects on phenology, 4:456–457, 4:458F effects on plankton, 4:455–456, 4:457F, 4:463F effects on stratification, 4:459 land-sea fluxes and, coastal zones, 3:399–401 threat to penguins, 5:527 see also Carbon sequestration by direct injection; Climate, warming; Climate change; Economics of sea level rise; Greenhouse climates GLOBEC (Global Ocean Ecosystem Dynamics), 3:124, 3:278 Globicephala (pilot whales), 2:149, 2:158–159, 2:159 Globicephala melas (long-finned pilot whale), 2:156 Globigerina bulloides foraminifera, 1:347, 3:913 Globigerinoroides bulloides, 2:104 Globigerinoroides ruber, 2:104, 2:109F Globigerinoroides sacculifer, 2:104 Glomar Challenger, RV, deep-sea drilling, 2:45–46, 2:45F GLORIA (Geological Long Range Inclined Asdic), 5:464 Glycerol dialkyl glycerol tetraethers (GDGT), 2:106–107, 2:107F see also TEX86 Gobies (Gobiidae), 1:656 Gobiidae (gobies), 1:656 Goddard Institute for Space Studies Level2 closure, 6:198–199 GOES Imager, 5:97 Go-Flo bottles, 2:255–257 Gold, concentrations in ocean waters, 6:101T Golden Pine, 4:770F Goldfish (Carassius auratus), 2:456F hearing range, 2:476–477 Goleta slide, 5:453F Goleta slide complex, 5:451, 5:453F Goniocorella dumosa coral, 1:615–616 Gonostomatidae (bristlemouths), 4:1–3 Gonyualax, 3:574F GOOS (Global Ocean Observing System), 3:275, 5:381 Gorda Ridge earthquakes, 3:844F volcanic helium, 6:280 Gorgonacea (sea whips), 2:56F
(c) 2011 Elsevier Inc. All Rights Reserved.
Gorm oilfield empirical wave height distribution, 4:777F rogue wave, 4:771F, 4:777 Gosse, Philip Henry, 1:615, 1:615F Gotland Basin, Baltic Sea circulation, 1:288, 1:289, 1:289F, 1:290F, 1:292–293 GOTM (general ocean turbulence model), 4:210, 4:211F Gouging, seafloor see Ice-gouged seafloor Governance, fishery management, 2:516–517, 2:519–520, 2:527 GPS see Global Positioning System (GPS) GPTS see Geomagnetic polarity timescale (GPTS) Grabens abyssal hills, 3:866F horst/graben model, 3:858, 3:865–866 mid-ocean ridge tectonics, volcanism and geomorphology, 3:862–863, 3:865–866, 3:865F, 3:866F Grab samplers see Grabs for shelf benthic sampling Grab sampling, 4:184 Grabs for shelf benthic sampling, 3:70–79 alternatives to grabs, 3:75–76 chemical sampling, 3:77 ideal sediment sample, 3:75 Knudsen sampler, 3:75–76, 3:76F precision corers, 3:77 Reineck sampler, 3:76–77, 3:76F spade box samplers, 3:76–77, 3:77F suction samplers, 3:75–76 conventional grabs, 3:70–71 Baird grab, 3:71, 3:72F Day grab, 3:71, 3:71F digging profiles, 3:72F Hunter grab, 3:71, 3:71F Petersen grab, 3:70, 3:70F Smith-McIntyre grab, 3:71, 3:71F van Veen grab, 3:70–71, 3:70F present technology, 3:77–78 disadvantages of box corers, 3:78 disadvantages of warp activation, 3:78 popularity of grabs, 3:78 problems, requirements and future developments, 3:78 chemical studies, 3:78 macrobenthic studies, 3:78–79 cost of analysis, 3:79 need for new instrument, 3:79 precision required, 3:79 spatial/temporal population variations, 3:79 meiofauna studies, 3:78–79 sample volume and capture numbers, 3:74F sampling different sediments, 3:77 Hamon grab, 3:77, 3:78F Holme grab, 3:77, 3:77F self-activated bottom samplers, 3:74 Bedford Institute of Oceanography’s sampler, 3:75
Index compressed-air-powered samplers, 3:74–75 Heriot-Watt University’s grab, 3:75, 3:75F history of hydrostatic machines, 3:75 hydraulically-powered samplers, 3:75 hydrostatically-powered samplers, 3:75 modified Petersen grab, 3:74–75 Shipek grab, 3:74, 3:74F solution to warp-activation problems, 3:74 spring-powered samplers, 3:74 uses, 3:70 warp activation problems, 3:71–72 contact with vessel, 3:72 drift, 3:73 effects of wind/current conditions, 3:73 grab bounce, 3:72–73 effect of ship’s roll, 3:72–73 effect of weather conditions, 3:73, 3:73F initial penetration, 3:73–74 final sample volume, 3:73, 3:73F influence of sampler weight, 3:73 minimal penetration required, 3:73–74 pressure wave effect, 3:74 effects of downwash, 3:74 warp heave, 3:72 effect of rigging, 3:71, 3:72 effect on bite depth, 3:72 Gracilaria chilensis algae, 5:321F Gradients, physical, seabird abundance and, 5:227–228 Gram-negative bacteria, 3:565 Grampus griseus (Risso’s dolphin), 2:149–153 Gran Canaria, anticyclonic eddy, 3:346, 3:346F Grand Banks earthquake, 3:793 Grand Banks Newfoundland, turbidity currents, 4:791 Granular flow, turbidity currents and, 5:460 Grappling gear, 2:542 Gravel extraction, pollution, see also Pollution solids geoacoustic properties, 1:116T offshore mining see Offshore gravel mining sand vs., 4:182 Gravel lags and pavements, 2:85–86 Gravel-rich contourites, 2:85–86 Gravimeters, 3:81 absolute, 3:81 platforms, 3:81 relative, 3:81 see also Gravity gradiometers Gravimetry, 3:80 bathymetric features and, 3:85F, 3:86F data interpretation, 3:83–84 long-wavelength anomalies, 3:85–86
mid-wavelength anomalies, 3:84–85 short-wavelength anomalies, 3:84–85 data reduction, 3:81–82 free air gravity correction, 3:82 latitude correction, 3:82 vehicular motion, 3:82 field gradient, 3:80, 3:81 measurement, 3:80–81 auxiliary measurements, 3:80 history, 3:82–83 instrumentation, 3:81 platforms, 3:81 mid-ocean ridges, 3:873F North Pacific, 3:84F observations, applications, 3:80 South Pacific, 3:85F uncertainty, 3:83 units, 3:80 Gravitational potential energy, 5:58–59, 6:33 Gravitational sea surface topography see Satellite altimetry Gravitational tides see Tide(s) Gravity, 5:58–59 anomalies, gravitational sea surface topography, 5:58–59, 5:60F Gravity-capillary waves, 5:575F, 5:579 resonant interactions, 5:578 see also Surface, gravity and capillary waves Gravity currents laboratory experiments, 2:578 non-rotating see Non-rotating gravity currents rotating see Rotating gravity currents see also Cascades; Overflows; Radial density currents; Surface gravity currents Gravity-derived processes, 5:447 mechanics-based terms, 5:447–450 velocity-based terms, 5:450 see also Debris flows; Mass transport; Slides; Slumps; Turbidity currents Gravity gradiometers, 3:81 see also Gravimeters Gravity-inertial waves, 2:275 Gravity models, extraordinary gravity field data, 5:61 Gravity unit, 3:80 Gravity waves evolution, 5:579F group velocity, 5:576 internal, phytoplankton interactions, 4:482F nonlinear effects, 5:578 resonant interactions, 5:578–579 surface, and one-dimensional models, 4:214–215 see also Surface, gravity and capillary waves Gray-headed albatross (Diomedea chrysostoma), 4:594–595, 4:596, 5:240, 5:252 see also Albatrosses Gray whale (Eschrichtius robustus), 1:276, 1:277T, 1:395, 3:594, 3:628
(c) 2011 Elsevier Inc. All Rights Reserved.
503
exploitation, 3:642F feeding, 1:282 habitat, 1:279 lateral profile, 1:278F migration, 1:283 trophic level, 3:623F see also Baleen whales Grazing benthic organisms, 1:352 by domestic animals, salt marsh vegetation, 5:41 phytoplankton blooms see Phytoplankton blooms Grazing angle, 1:75, 1:84–86, 1:84F, 1:85F Grease ice, 4:542 Great auk (Pinguinis impennis), 1:171 overexploitation, 1:171, 1:176–177, 5:265 remains, 1:175–176 see also Alcidae (auks) Great Australian Bight, 3:444, 3:447, 3:451F Great Barrier Reef Marine Park, Australia, size, 3:672 Great Barrier Reef Undercurrent (GBRUC) flow, 4:287F, 4:290 see also Pacific Ocean equatorial currents Great Belt, Baltic Sea circulation, 1:288, 1:290F, 1:291–292, 1:294 Great Biogeochemical Loop, 4:89–92, 4:90F, 4:102–103 and modeling, 4:92 Great black-backed gull (Larus marinus), 3:423F ‘Great Conveyor’ definition, 4:303 see also Paleoceanography; Thermohaline circulation Great cormorant (Phalacrocorax carbo), 4:372F, 4:374, 4:374F see also Cormorants Great frigatebird (Fregata minor), 4:372F see also Fregatidae (frigatebirds) Great Lakes Program, 3:668T Great Salinity Anomaly, 4:70, 4:72 Great scallop (Pecten maximus), stock enhancement/ocean ranching programs, 4:147T, 4:151–152, 4:152F Great South Channel, Calanus finmarchicus distribution, 4:354F Great whales see Baleen whales ‘Great Whirl’, 1:732, 5:496–497, 5:499–501, 5:500F, 5:501F see also Somali Current Greece, mariculture production, 3:535 Greek government, archaeology treasures recovered, 3:696 Green algae see Algae; Microphytobenthos Green fluorescence like proteins (GFP), 2:582
504
Index
Greenhouse climates, 4:319–329 Cretaceous, 4:320–321 key features, 4:319 modeling problems, 4:324F, 4:326–328, 4:327T Paleogene, 4:321–325 temperature gradient, 4:319 transition to current climate, 4:325–326 see also Climate change; Global warming Greenhouse gas, 1:477, 3:786 emissions, 2:197 see also Carbon sequestration by direct injection release during early Cenozoic, 1:511 SST modulates exchanges of heat and, 5:101 see also Climate change; Sulfur hexafluoride; specific greenhouse gases ‘Greenhouse world’ oxygen isotope evidence, 1:509 sea level variations, 5:187 Greenland bottom water, export of, 1:416 climate effects on fisheries, 2:489 Holocene climatic variability ice core records, 3:126–127, 3:128 Little Ice Age, 3:127–128, 3:128F icebergs, 3:181, 3:184–185, 3:188 paleoclimatic data, 1:1 salmon fishery regulations, North Atlantic Salmon Conservation Organization, 5:6, 5:7T Salmo salar (Atlantic salmon) fisheries, 5:4 management, 5:6, 5:7T sea ice cover, 5:141 Greenland Ice Sheet formation, oxygen isotope ratio and, 5:185–186, 5:186F sea level variations and, 5:182–183, 5:183 surface melting, 5:184 projections, 5:183 see also Ice sheets Greenland Sea, 4:126–127 deep convection, 2:13, 2:19–20 mixed layer depth profile, 6:50F sea ice cover, interannual trend, 5:146 North Atlantic Oscillation and, 4:70 thickness, 5:151 tomographic experiments, 6:49–50, 6:49F tracer release experiments, 6:92 water column profiles, 1:214F Greenland Sea Bottom Water, diffusive convection and, 2:168 Greenland Sea gyre, sea ice cover, 5:146 Green seaweeds (Chlorophyta spp.), 4:427 Green turtle (Chelonia mydas), 2:408–409, 5:216–217, 5:216F see also Sea turtles Grey, Harold, 2:101
Grey phalarope see Red phalarope Grice, Dr George, memorial, 3:279 Grid stirring, 3:372–373 Groins/jetties, 1:586 descriptions and purposes, 1:586 downdrift beach loss, 1:586, 1:586F effect on deltas, 1:586 groin failure, 1:586 Gross growth efficiency, 3:805 Groundfish fisheries, 2:91 New England resources, 2:96 quota management scheme, 2:96 see also Demersal fisheries Groundwater cycle, 3:89F definition, 3:88, 5:557 flow to ocean, 3:88–97 at coastal margins, 3:89–90 governing equations, 3:88–89 freshwater–saltwater interface, 3:90, 5:553 recharge, sewage disposal, 6:271 Groupers, tropical fisheries development, impact, 1:651–652 Group of Experts on Marine Environmental Protection (GESAMP), UN, 4:526 Growler, definition, 3:190 GSA (Great Salinity Anomaly), 4:70, 4:72 GSNW (Gulf Stream North Wall), index, copepod numbers and, 1:636, 1:637F GSSP (Global Boundary Stratotype Section and Point), 3:30, 3:31F Guanine (C5H5N5O), 2:216 Guano, phosphorite deposit formation, 1:264 Guiana Current, 1:721–723, 2:555–556, 3:288, 3:293F Guidelines for Safe Recreational Water Environment (WHO), 6:267 Guild, definition, 2:505 Guildline Inc., 1:715–716 Guillemot(s) black, 1:171, 5:258–259, 5:259F Brunnich’s, 1:171, 1:173F migration, 5:244–246 see also Alcidae (auks) Guldberg-Mohn friction coefficient, Florida Current, 3:291 Gulf Loop Current (GLC), 3:289, 3:293F current rings see Current rings Mississippi River water, 3:290–291 Gulf of Aden, Red Sea circulation water exchange, 4:673–675, 4:675–676 coastal trapped waves, 4:675 current speeds, 4:675 hydraulic control, 4:675 inflow, 4:667, 4:674 outflow, 4:667, 4:673, 4:674, 4:675F salinity, 4:667, 4:669F seasonal variability, 4:667, 4:674, 4:675 Strait of Bab El Mandeb see Strait of Bab El Mandeb total exchange, 4:674–675 wind-driven circulation, 4:674
(c) 2011 Elsevier Inc. All Rights Reserved.
see also Red Sea circulation Gulf of Alaska atmosphere–ocean interactions, 1:456–457, 1:457F coastal discharge, 1:456–457, 1:457F downwelling, 1:456, 1:457F seabird responses to climate change, 5:263 sea surface temperature, image, 1:458F storm tracks, 1:456 upwelling, 1:456, 1:457F see also Alaska Current; Alaska Gyre Gulf of Aqaba, 4:666, 4:666F outflow, 4:670–671, 4:673 Gulf of Bengal, western boundary currents, 1:732 Gulf of Bothnia, Baltic Sea circulation, 1:288, 1:290–291, 1:296 Gulf of Cadiz, subsurface eddy, 3:708 Gulf of California, sedimentary records of Holocene climate variability, 3:126 Gulf of Finland Baltic Sea circulation, 1:288, 1:289, 1:289F, 1:290F, 1:296 oscillatory currents, 1:296 Gulf of Mexico (GOM) buoyancy frequency profiles, 6:195–196 buoyancy profile, 6:192 crustacean fishery, 4:750 fish species composition, 4:751 fronts, satellite remote sensing and, 5:108–109, 5:108F habitat modification, 3:103 hook and line fishery, 4:750–751 hurricanes, 6:192–193, 6:193F, 6:197–198, 6:208F methane hydrate, 3:784F northern region see Northern Gulf of Mexico offshore structures, 4:748–749, 4:751, 4:752T salinity profile, 6:196F seabird responses to prehistoric climate change, 5:258 seiches, 5:348–349 storm surges, 5:532–535, 5:537F temperature profile, 6:196F Gulf of St. Lawrence, 5:141–142 chlorophyll, spatial variability, 5:477, 5:477F sea ice cover, 5:141 Gulf of Suez, 4:666, 4:666F outflow, 4:670–671, 4:672–673 sea surface salinity, 4:666 Gulf of Thailand, fisheries development impact, 1:651 ‘Gulf’ series of high-speed samplers, 6:359, 6:360F Gulf Stream, 1:720–721, 2:243–244, 4:121–122, 4:126, 6:347F awareness of (historical), 3:123 coupled model, 3D-dynamical of meandering jets, 5:481, 5:482F
Index Ekman transport, 2:225 flow measurement, telephone cable, 3:116–117 heat transport, 3:117 hydrographic problem, salt/mass conservation and, 3:316, 3:316F identification, satellite remote sensing of SST, 5:99 mesoscale eddy, 3:758, 3:758F ‘rings’, 3:758 transport, 1:721, 1:724T wave propagation, 5:577 see also Atlantic Ocean current systems; Florida Current, Gulf Stream and Labrador Currents; Gulf Stream System Gulf Stream North Wall (GSNW), index, copepod numbers and, 1:636, 1:637F Gulf stream rings, 2:171 Gulf Stream System, 2:554, 2:556–557 Azores Current, 2:556 current rings see Current rings current structure, 2:556–557 current velocity, 2:556, 2:556–557, 2:557F, 2:560 eddy kinetic energy (EKE), 2:557, 2:560F formation, 3:293F, 3:294 mesoscale eddies, 2:557, 2:559F North Atlantic Current, 2:556, 2:560 recirculating gyres, 2:558–560, 2:561F salinity distribution, 2:558F sea surface slope, 2:557 Stommel, Henry, 2:554 temperature distribution, 2:557, 2:558F sea surface, 2:557, 2:559F thermohaline circulation, 2:555–556 topographic control, 3:291 transport, 2:556F, 2:558–560, 2:561F variability, 2:557–558 see also Florida Current, Gulf Stream and Labrador Currents; Gulf Stream Gulls see Laridae (gulls) Gulper shark (Centrophorus granulosus), over-exploitation vulnerability, 4:232 Gurvich numbers, 2:617 Guyana Current, 1:721–723, 2:555–556, 3:288, 3:293F Gymnodinium breve phytoplankton competition model, 4:723–724, 4:724F West Florida Shelf, 4:729–730, 4:730F Gymnoptera pteropods, 3:14 Gymnosomata pteropods, 3:14, 3:15F Gymnosperms, lipid biomarkers, 5:422F Gyre ecosystems see Ocean gyre(s); Ocean gyre ecosystems Gyre models, 4:110, 4:110F Gyres Black Sea, 1:404–407 see also Ocean gyre(s); individual gyres
H H-0 event, dates, 3:883 H-1 event, dates, 3:883 H-2 event, dates, 3:883 H-3 event, dates, 3:883 H-4 event, dates, 3:883 H-5 event, dates, 3:883 H-6 event, dates, 3:883 H230, definition, 6:242 H231, definition, 6:242 Habitat(s) aquarium fish mariculture, 3:528 biodiversity and, 2:139, 2:139F, 2:144, 2:147 bivalves, 3:899 cephalopods, 3:899 demersal fish, 2:505 features, tropical fisheries development, 2:511 gastropods, 3:899 modification see Habitat modification pelagic fish, 2:505 pollution, molluskan fisheries, 3:899–901 protection, environmental protection and Law of the Sea, 3:441 threats, 2:145–146 types (marine), 2:139, 2:139F see also Coral reef(s); Fiordic ecosystems; Lagoon(s); Mangrove(s); Rocky shores; Salt marsh(es) and mud flats; Sandy beach biology Habitat modification, 3:99–104 ecological process, 3:100 ecosystem maintenance, 3:100 human forcing, 3:99, 3:100 aggregate extraction and mining, 3:102–103 aquaculture, 3:102 deforestation, 3:102 laying stock on seabed, 3:102, 3:103F overdevelopment, 3:102 pollution, 3:102 direct and indirect effects, 3:100 direct removal of habitat, 3:103 dredging effects, 2:204–205 fishing, 3:100–102 deep-sea, 3:101 diffuse predation phenomenon, 3:102 trawling, 2:204–205, 3:100–101, 3:101F trophic interactions, 3:101–102 petroleum exploration and production, 3:104 effects and habitat, 3:104 river discharge, 3:103–104 contaminants, 3:103 dams, 3:103–104 example of Gulf of Mexico, 3:103 increased nutrient loads, 3:103 phytoplankton blooms, 3:103
(c) 2011 Elsevier Inc. All Rights Reserved.
505
large-scale natural forcing, 3:99 North Atlantic Oscillation, 3:99, 3:100F natural processes, 3:99 types of processes, 3:99 small-scale natural forcing, 3:99–100 examples, 3:99–100 HABs (harmful algal blooms) see Algal blooms; Phytoplankton blooms Hadal zone, 1:351T, 1:354, 1:356 Haddock, biomass, north-west Atlantic, 2:505–506, 2:506F Hadley Cell, 4:121F, 4:124 Haeckelia rubra, 3:12 Hafnium concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:693–694 depth profile, 4:694F properties in seawater, 4:688T surface distribution, 4:690F zirconium atom ratio, 4:694F long-term tracer properties, 3:456T global distribution, 3:459F source materials, 3:457–458 isotope ratios, 3:457T Hagfish (Myxinidae), 2:375 Haida Coastal Current, 1:455, 1:456F, 1:458–459 Hake (Merluccidae), 2:458–460 catch Namibia, 4:705–707 South Africa, 4:705 open ocean demersal fisheries, FAO statistical areas, 4:231T population, Benguela upwelling, 4:706F Halfspace heat flow models, 3:44–45 Half-space seafloor, 1:84–86, 1:84F Halibut (Hippoglossus hippoglossus) discarding solutions, 2:203 fisheries, economic rationality, 2:525 fishery stock manipulation, quality issues, 2:530–531 mariculture disease, 3:519, 3:520T, 3:521 Halice hesmonectes (amphipod), 3:139 Haline buoyancy flux, 6:339–341 Haline convection, 4:218, 4:220F Haliotis spp. see Abalone (Haliotis spp.) Halley, Dr Edmund, diving bell, 3:513 Halmahera Eddy, 4:287F, 4:290–291 Halocline, 6:166, 6:218 Arctic Ocean, 1:212–213 Baltic Sea, 1:288, 1:290F Halocline catastrophe, 5:171 Halocyptena microsoma (least storm petrel), 4:590 see also Procellariiformes (petrels) Halodule wrightii, 2:315–317 Haloperoxidases, 3:571–572 Halophiles, lipid biomarkers, 5:422F Halophytes, 5:39, 5:40 osmotic pressure in roots, 5:40 succulent growth form, 5:40 Halowax, 1:553 Hand line fishing, 4:235
506
Index
Hanford complex, 4:632 Hanish sill, Red Sea circulation, 4:666, 4:666F, 4:674 Haplosporidium nelsoni pathogen, 2:489 Haptophyte algae genomics, 3:555–556 long-chain alkenones, 2:105 Harbor Branch Oceanographic Institution, human-operated vehicles (HOV), 6:257T Harbor paradox, 5:347 Harbor porpoise (Phocoena phocoena), 2:159 hunting, 3:635, 3:636F see also Dolphins and porpoises; Porpoises Harbors see Port(s); Seiches; see specific harbors Harbor seals (Phoca vitulina) lactation, 3:600 movement patterns during breeding season, 3:600, 3:601F see also Phocidae (earless/‘true’ seals) Hard clam (Mercenaria mercenaria), 3:899 Hard Rock Guide Base (HRGB), 2:51 Hard shell clam fishery, thermal discharge and pollution, 6:16 Hardware (computer), autonomous underwater vehicles (AUV), 4:477 Hardy, Sir Alister, 2:376 Continuous Plankton Recorder, 1:630, 1:631F, 3:122, 6:359–361, 6:360F plankton indicator, 6:359, 6:360F Hardy Continuous Plankton Recorder, 6:72 Harmful algal blooms (HABs) see Algal blooms; Phytoplankton blooms Harpacticoida copepods, 1:640 Harpoon fishing, open ocean pelagic fisheries, 4:235 Harp seal (Phoca groenlandica) migration and movement patterns, 3:602–603, 3:602F see also Phocidae (earless/‘true’ seals) Harvard Ocean Prediction System (HOPS), 2:3–5 Harvesting gear fishing methods, 2:542, 2:543F pumps, 2:542 Harvey estuary, phosphorus, release of, 2:321F Hatcheries isolation, mariculture disease management, 3:519 oyster farming, 4:276–278, 4:279F see also Mariculture Hatchet fishes (Gasteropelecidae), 2:395–396F Hatshepsut, Queen of Egypt, 5:409 Hatteras Abyssal Plain, 5:461 Haul-out site(s) definition, 3:603 pinnipeds (seals), 3:600–603, 3:601F
Hawaii El Nin˜o events and, 2:228 tsunami (1946), 6:127–128, 6:128, 6:128F tsunami (1975), 6:132 Hawaii-2 Observatory, deployment, 2:33F Hawaiian archipelago island wakes, 3:347, 3:347F lee of islands, 3:347 Hawaiian Islands, volcanic helium, 6:282–283 Hawaiian Ridge, internal tides, 3:263, 3:264F, 6:52F Hawaiian Swell, geophysical heat flow, 3:47F Hawaii-Emperor chain, mantle plume, 5:296, 5:297F Hawaii Lee Counter Current, 3:347 Hawaii Mapping Research Group, deeptowed vehicles, 6:256T Hawaii submarine ridge, internal tides, 3:256, 3:256F Hawaii Undersea Research Laboratory, human-operated vehicles (HOV), 6:257T Hawksbill turtle (Eretmochelys imbricata), 5:217F, 5:218 see also Sea turtles Hazardous wastes, movement, environmental protection and Law of the Sea, 3:440 HBOI (Harbor Branch Oceanographic Institution), 6:257T Head wave, acoustics in marine sediments, 1:80, 1:80F, 1:88 Health and safety, bathymetric maps and, 1:297 Health management aquarium fish mariculture, 3:529 see also Mariculture Hearing fish see Fish hearing and lateral lines marine mammals, 1:359–360, 1:360F, 3:610 terrestrial mammals, 1:359–360, 1:360 Heat diffusivity relative to salinity, 2:114 fluid packets, 5:136 Heat dissipation ocean, 5:135 rates, mixing depth and, 6:219 Heat distribution, upper ocean, 6:166 Heat equation, general circulation models, 3:20 Heat flux air–sea see Air–sea heat flux components, primitive equation models, forward numerical, 2:608–609 development of extratropical cyclones, 1:579 El Nin˜o Southern Oscillation, 2:235 estimates, Indonesian Throughflow, 3:239–240 hydrothermal vents, dispersion from, 2:131, 2:132 latent, 5:383
(c) 2011 Elsevier Inc. All Rights Reserved.
measurement, 5:384, 5:389–390 resistance wires, 5:387 sensor mounts, 5:387–388, 5:387F sonic thermometry, 5:388 thermistors, 5:387 thermocouples, 5:387, 5:387F megaplumes, 2:132 between ocean layers, turbulent, 2:289 open ocean convection, 4:220, 4:222 sea surface, 3:105–113 accuracy of estimates, 3:110–112 data, sources of, 3:107–108 measuring, 3:105–107 Mediterranean Sea circulation, 3:710, 3:716–717 North Atlantic sites, 3:110, 3:112F Red Sea circulation, 4:666, 4:667, 4:675–676 regional variation, 3:110 seasonal variation, 3:110, 3:111F transfer coefficients, typical values, 3:107, 3:107T Weddell Sea circulation, 6:318 sensible, 5:383 Heating coastal circulation models, 1:572 oceanographic research vessels, 5:412 Heat transfer coefficient, 1:696 Heat transfer processes, sea surface, 5:202 Heat transport, 3:114–120, 4:126, 4:129, 6:168–170 air–sea heat exchange, 3:116 atmospheric, 3:114–115, 3:115F, 3:119 Bjerkenes compensation mechanism, 3:120 convergence, 3:115 definition, 3:115 direction, 3:114 eddies, 3:118–119 future prospects, 3:119–120 global distribution, 3:116–118, 3:116F, 3:118F global heat budget, 3:114–116 Indo-Pacific Ocean, 3:118–119 latitude and, 3:114F models, 3:119–120 North Atlantic, 3:117 North Pacific, 3:117 ocean warming and, 3:119 power, 3:117 residual method of calculation, 3:119–120 Heavy metals analytical techniques, 6:102 concentrations, 6:100 conservative type, 6:101, 6:102F discharges, coral impact, 1:674 distribution maps, 6:102 fluorometry, 2:593T, 2:594 micronutrient aspects, 6:107 mixed type, 6:102 nutrient type, 6:101–102, 6:102F scavenged type, 6:101, 6:102F seabirds as indicators of pollution, 5:274, 5:275–276
Index speciation, 6:100–108, 6:102–103 inorganic, 6:103 organic, 6:103 see also Refractory metals Hector’s dolphin (Cephalorhynchus hectori), 2:153, 2:159 Heinrich (H) events, 1:1–2, 3:883–885 correlating with other climate records, 3:885 Dansgaard–Oeschger cycle and, 3:130F drivers, 1:3 periodicity, 3:886–887 see also H-0 event; H-1 event Heirtzler J R, geomagnetic polarity timescale development, 3:28, 3:29F Helical Turbine, 6:29–30, 6:30F Helium, 5:544 3 He vs.4He, 6:279, 6:280F atmospheric, 6:277 atmospheric abundance, 4:55T cosmogenic isotopes, 1:679T extraction, 6:277 ice solubility, 4:56 ideal gas and, 1:710 isotope ratio anomaly Bermuda, 6:97F nitrate correlation, 6:98F isotopes, 6:277 origin of oceans, 4:261, 4:262F mantle see Mantle helium phase partitioning, 4:56T ‘primordial’, 6:277 radiogenic, 6:277 saturation responses, 4:57–58, 4:58F Schmidt number, 1:149T seawater concentration, 4:55T terrestrial helium budget, 6:278, 6:278F tritiogenic, 6:277 units, 6:277 volcanic see Volcanic helium see also Helium-3 Helium-3 3 He vs.4He, 6:279, 6:280F air–sea flux, 6:98 nitrate flux and, 6:100 seasonal variation, 6:98 cosmogenic isotopes, production rates, 1:680T diffusion coefficient in water, 1:147T long-term variations, production estimates and, 6:100 Sargasso Sea, 6:98 Schmidt number, 1:149T sulfur hexafluoride dual tracer release, 6:89–90 tracer applications, 1:683T see also Helium Helium-4 3 He vs.4He, 6:279, 6:280F diffusion coefficients in water, 1:147T Hellenic Trench, clay mineral composition, 1:570–571 Hell Gate, 1:223 Helsinki Commission, 3:277 Hemiemblemaria simulus (wrasse blenny), 2:423
Hemipelagic, definition, 1:268 Henry’s Law, 1:479, 3:1 Henry’s Law constant, 3:1 definition, 3:7 Henry the Navigator, Prince, 5:410 Hensen net, 6:355, 6:356F Henyey-Gregg parameterization, 6:211 Heptachlor seabirds as indicators of pollution, 5:275 structure, 1:552F Herbivores, fish feeding/foraging, 2:375 Herglotz-Bateman-Wieckert integration, 1:88–89, 1:89F Hermatypic, definition, 1:677 Hermatypic corals sea surface temperature paleothermometry, 2:100–101, 2:101T, 2:104–105 strontium/calcium ratio, 2:104–105 Hermite functions, equatorial wave flow and, 2:276, 2:277F Herring (Clupea), 1:63, 1:65F, 4:364, 4:364–366 biomass, north-west Atlantic, 2:505–506, 2:506F description and life histories, 4:364–365 distribution, 4:364 fisheries history, 4:365 fishery locations, 4:365 migration, 4:364–365, 4:365F, 4:366F Northeast Atlantic spawning stocks, 4:365 North Sea abundance, time-series, 1:633–634, 1:635F Northwest Atlantic spawning stocks, 4:365 overexploitation, 4:366 Pacific spawning stocks, 4:365, 4:367F relationship between fecundity and egg size, 2:427, 2:428F spawning biomass, Baltic Sea, 2:505–506, 2:507F see also Atlantic herring (Clupea harengus) Herring gull (Larus argentatus), 3:423F see also Laridae (gulls) Hess deep, submersible observation, 3:826–827, 3:827F Hessler, Robert, 2:61 Heterocyclic molecules, marine environment, 3:572 Heterolithic facies, definition, 5:463 Heteropods, 3:14 Heterotrophic microbes, definition, 2:73 Heterotrophic nitrification, 4:34 Heterotrophic organisms, 4:103 Heterotrophic respiration, 1:546 Heterotrophs, 3:805 Heterotrophy, corals, 4:338–339, 4:340–341 H events see Heinrich (H) events Hexachlorobenzene, structure, 1:552F Hexachlorobiphenyls, structure, 1:552F HEXMAX (HEXOS Main Experiment), 1:142–143, 5:380
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HEXOS (Humidity Exchange Over the Sea) experiment, 1:142–143, 2:326, 2:326F, 5:380 HF see High frequency band (HF) Hf radar, North Sea measurements, 4:76, 4:78–80 Hibler model, 5:164 High-frequency acoustics, zooplankton sampling, 6:368 High frequency band (HF), 1:60 definition, 1:52 High-grading, fishery management, 2:523 High Himalayan Crystalline Series, silicate minerals, strontium isotopic ratios, 1:517 High inside corner, 3:864, 3:864F High-molecular-weight compounds, 5:426 High natural dispersing areas (HNDA), 2:307 High-nitrate, high-chlorophyll (HNHC) regions, 3:332–333, 3:332T High-nitrate, low-chlorophyll (HNLC) regions, 3:332–333, 3:332T, 3:333–334, 3:333F, 3:334F, 4:213 iron deficiency, 3:331F, 3:333–334, 3:334 see also Iron fertilization High-nitrogen, low-chlorophyll (HNLC) regions, 4:213 High-nitrogen, low-productivity (HNLP), 1:124 High-nutrient, low-chlorophyll (HNLC) regimes, 4:133, 4:573–574, 4:575, 4:587–588, 4:588 High-nutrient, low chlorophyll (HNLC) waters, 1:252 High-performance liquid chromatography (HPLC), radiocarbon analysis, 5:424 sample contamination, 5:424 High Resolution Profiler, 2:122, 2:123 High Salinity Shelf Water (HSSW), 3:215, 5:542 Antarctic continental shelf, 5:544–545 High seas, Law of the Sea jurisdiction, 3:435 High-speed plankton samplers, 6:355–356, 6:357T, 6:360F Hikino submersible, 3:514–515 Hilbert space, 3:312–313 Hilo tsunami (1947), 6:127–128, 6:128F tsunami (1960), 6:129F Himalayan uplift, carbon cycle changes and associated processes, 1:516–517, 1:517, 1:518 Himalayas (mountains), 3:911 Hindcasts coastal trapped waves, 1:597F storm surges, 5:539 Hingham Bay, pore water vs. depth concentration profiles, 1:544F Hinze scale, 1:434–435 Hippa spp. (mole-crabs), 5:52F
508
Index
Hippocampus (sea horse), 2:395–396F aquarium mariculture, 3:525, 3:525T cryptic coloration, 3:528 Hippocampus abdominalis (pot-bellied sea horse), aquarium mariculture, 3:525–526, 3:525T, 3:526 behavior, 3:528 breeding, 3:529 diet, 3:529 habitat, 3:528 life span, 3:529 salinity tolerance, 3:526 water quality guidelines, 3:526, 3:527 water temperature range, 3:526 Hippocampus zosterae (pygmy sea horse), aquarium mariculture, life span, 3:529 Hippoglossus hippoglossus (halibut), discarding solutions, 2:203 Hippoglossus stenolepis (Pacific halibut), population density, body size and, 4:704 HiROS optical system, 3:249F see also Ocean optics History maritime archaeology see Archaeology (maritime) of ocean sciences, 3:121–124 scientific observations, 3:121 shallow-water manned submersibles, 3:513–515 see also Satellite oceanography; individual topics Histrio histrio (sargassum fish), aquarium mariculture, 3:528 HMRG (Hawaii Mapping Research Group), 6:256T HMW (high-molecular-weight compounds), 5:426 HNDA (high natural dispersing areas), 2:307 HNLC regimes, 4:133, 4:573–574, 4:575, 4:587–588, 4:588 Hoki, acoustic scattering, 1:66 Hokkaido Island, tsunami, 6:128–129 Holocene climate variability, 3:125–132, 3:126–127, 3:127F build up to, 3:125 current understanding, 3:130–131, 3:131F decadal-scale, 3:125 Greenland see Greenland knowledge gaps, 3:130–131, 3:131F millennial-scale, 3:125, 3:126F, 3:130–131 causes, 3:128–130, 3:129F, 3:130–131, 3:130F Northwest Africa vs. North Atlantic, 3:126–127, 3:127F sedimentary records, 3:126 vegetation effects, 3:127 Dansgaard–Oeschger cycles, 3:126F, 3:128, 3:130–131, 3:130F
land-sea carbon flux, 3:399 Little Ice Age, 3:126F, 3:127–128, 3:127F, 3:128F, 3:130–131 millennial-scale climate variability, 3:886 paleoceanography, importance of, 3:125–126 see also Cenozoic; Paleoceanography Holothuroidea (sea cucumbers), 1:332, 1:355, 3:16 Homarus americanus (American lobster), fisheries, 1:702 Homarus gammarus (European lobster), stock enhancement/ocean ranching, 2:530, 4:146, 4:152 Home range definition, 3:596, 3:603 see also specific marine mammals Home water fisheries, Salmo salar (Atlantic salmon), 5:2, 5:2T, 5:8–9 Homogeneous turbulence see Stationary, homogeneous, isotropic turbulence Homogenization, meddies, 3:705 Honda, K, 5:345 Hooke’s law, gravimetry and, 3:81 Hooks and lines, 2:541, 2:542F, 2:544, 2:545F, 4:235 Hopfinger scale, 2:617–618 fossil turbulence, 2:612 HOPLASA (Horizontal Plankton Sampler), 6:361, 6:362F Hoplostethus atlanticus see Orange roughy (Hoplostethus atlanticus) Horizontal advection, inversion formation and, 6:223–224 Horizontal discretization, coastal circulation models, 1:573 Horizontal eddy diffusivity, 6:58 Horizontal migration see Fish horizontal migration Horizontal mixing, definition, 2:290 Horizontal Plankton Sampler (HOPLASA), 6:361, 6:362F Horizontal structure barrier layer, 6:180–181, 6:180F mesoscale eddies, 3:763 upper ocean see Upper ocean Horned puffins, 5:258–259, 5:259F see also Alcidae (auks) Horse mackerel (Trachurus trachurus), 4:368, 4:368–369 fishing, management, 4:707 Horst/graben model, abyssal hills development model, 3:865–866, 3:865F Hotel load, 4:475 Hot film sensor, 6:152 disadvantages, 6:152 Hot spots, 3:218 geophysical heat flow, 3:46–47 see also Galapagos hot spot; Large igneous provinces (LIPs); Mantle plumes Hot vents see Hydrothermal vent(s) HOV see Human-operated vehicles
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Hovmo¨ller diagram, Rossby waves, 4:783, 4:784F limitations, 4:783 ocean spinup, 4:787F HOZ (hydrate occurrence zone), 3:793–794 HROV (hybrid remotely-operated vehicle), 6:260 HSSW see High Salinity Shelf Water (HSSW) HSZ see Hydrate stability zone Huanghe (Yellow River), hypoxia, 3:175 Huchen (Hucho spp.), 5:29 Hucho spp. (huchen), 5:29 Hudson Bay, sea ice cover, 5:141 Hudson Strait Heinrich events, 1:1–2, 3:883–885 ice core data, 3:884F sea ice cover, 5:141 Hugin AUV, 4:474F Hulk vent, 1:72F Human activities, adverse effects on global phosphorus cycle, 4:406 increased atmospheric carbon dioxide concentrations, 1:477–478, 1:479F management see Conservation on marine biodiversity, 2:145–146 on marine habitats, 2:145–146 release of platinum group elements, 4:502–503, 4:502F on seabirds, 5:221F, 5:222, 5:223F, 5:225 immediate, 5:223F long-term, 5:223F see also specific genera/species see also Anthropogenic impacts; Climate change; entries beginning anthropogenic; specific activities Human exploitation management of see Conservation marine mammals history of, 3:635–642 live-capture, 3:640–642, 3:641F as objects of tourism, 3:642, 3:642F see also specific species seabirds, 5:221F, 5:222, 5:266, 5:267–268 culling, 5:267–268 management see Conservation see also specific genera/species Human health harmful algal blooms, 4:432, 4:435T impact of phytoplankton, 4:455 Human-operated vehicles (HOV), 6:255–257 advantages, 6:255–257 dive duration, 6:255–257 equipment, 6:259F, 6:265 future prospects, 6:265–266 Human population, land-sea fluxes and, 3:401 Humber estuary, UK enrichment factor, 3:773T metal pollution, 3:771, 3:772F Humboldt Current see Peru Current
Index Humboldt current system, catch, anchovy and sardine, 4:701F Humboldt penguin (Spheniscus humboldti), 5:522, 5:522T, 5:523, 5:527–528 see also Spheniscus Humic acid(s), fluorometry, 2:593T, 2:594 Humics, 1:168 Humic substances see Colored dissolved organic matter (CDOM) Humidity, 2:324–331 definitions, 2:324–326 history, 2:324–326 latitudinal variations, 2:328 measurement see Humidity measurement nomenclature, 2:324–326 regional variations, 2:328 satellite remote sensing, 5:206–207 sources of data, 2:328–329 tropical conditions of, 2:327–328 vertical structure of, 2:328 see also Evaporation Humidity Exchange Over the Sea (HEXOS) experiment, 1:142–143, 2:326, 2:326F, 5:380 Humidity measurement, 5:377–378 capacitance sensors, 5:378–379 capacitance change hygrometers, 5:379 classical sling psychrometer, 5:377–378 psychrometric method, 5:377–378, 5:378F see also Evaporation; Humidity exposure to salt, 5:379 dew point hygrometers, 5:379 protective devices, 5:379 resistance thermometer psychrometer, 5:378 error due to salt build-up, 5:378 housing arrangements, 5:378 spray-removal devices, 5:379–380 device performance, 5:379–380 quantitative effectiveness, 5:380 spray flinger, 5:379, 5:379F Humpback dolphins (Sousa spp.), 2:153 Humpback whale (Megaptera novaeangliae), 3:631–632 defense from predators, 3:617 habitat, 1:279–280 lateral profile, 1:278F migration, 1:283, 3:597, 3:597F sound production, 1:283 see also Baleen whales Hungarian Academy of Sciences, 4:504–505 Hunter Channel, 2:565F, 2:566 Hunterston power station, UK, thermal discharges, effects of, 6:16 Hurricane(s), modeling see hurricane models 1999 season (Atlantic), 5:99 Caribbean Sea, 6:193F development, surface temperature, 6:171–172
frequency, 6:208–209 future research direction, 6:208–209 geographical variability, 6:195–196 Gulf of Mexico, 6:208F intensification prediction of development of storms, SST, 5:99 satellite remote sensing of SST application, 5:99 see also Heat flux; Momentum fluxes Intra-Americas Sea (IAS), 3:287, 3:293 mixed layer and, 6:192–210, 6:193F air–sea parameters, 6:194–195 atmospheric forcing, 6:193–194 basin-to-basin variability, 6:195–197 ocean structure and, 6:194–195 models, 6:198 mixing parameters, 6:198–199 oceanic response, 6:199–202 predictions, offshore structures, 4:752 spray and, 6:306 storm surges, 5:532, 5:532–535 temperature and, 6:171–172 Hurricane Allen, 6:209 Hurricane Bertha, sea level changes, 1:575F Hurricane Camille, 5:532–535 Hurricane Edouard, 3:248, 3:250F Hurricane Frances, current, salinity, density profiles, 6:207F Hurricane Gilbert, 6:199F Hurricane Hugo, sediment transport, 5:463 Hurricane Isidore, 6:200 mixed layer depth, 6:201F sea surface temperatures, 6:201F Hurricane Ivan air–sea parameters, 6:195T current profiles, 6:202–203, 6:203F warm core ring interactions, 6:202–203, 6:202F Hurricane Juliette, 6:196–197 Hurricane Katrina, 5:450 air–sea parameters, 6:195T sea surface temperatures, 6:203F Hurricane Lili air–sea parameters, 6:195T Loop Current interactions, 6:200, 6:200F mixed layer depth, 6:201–202, 6:201F sea surface temperatures, 6:201–202, 6:201F Hurricane Opal, 6:192 Hurricane Rita oceanic heat content, 6:206F ocean temperature profile, 6:203F temperature profile, 6:204F Hutton’s shearwater (Puffinus huttoni), 5:253, 5:254F see also Procellariiformes (petrels) Huxley, Thomas Henry, 2:499 Hybrid coordinate ocean model (HYCOM), 6:198 Hybrid remotely-operated vehicle (HROV), 6:260
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Hydrate occurrence zone (HOZ), 3:793–794 Hydrates, 1:167 see also Methane hydrate(s) Hydrate stability zone (HSZ), 3:790F, 3:792 base (BHSZ), 3:792–793 depth and, 3:796 hydrate distribution, 3:793–794 Norwegian margin, 3:796 Hydratization, 2:247–248 Hydraulically controlled flows, turbulence, 6:24, 6:24F Hydraulic control, 2:564–565 Hydraulic jumps three-dimensional (3D) turbulence, 6:23, 6:24F topographic eddies, 6:61, 6:62F Hydroacoustics, pelagic fish shoaling detection, 5:468, 5:472 Hydrobatidae, 4:590 see also Procellariiformes (petrels); specific species Hydrocarbon formation, accretionary prisms, 1:32, 1:34 Hydrocasts, 1:708–709, 1:709F Hydrodamalis gigas (Steller’s sea cow), 3:639, 5:436–437, 5:437F, 5:443–444 see also Dugongidae Hydrodynamic forcing, tracer release and, 6:88 Hydrodynamic phase diagrams, fossil turbulence, 2:618–619, 2:619F Hydrodynamics definition, 5:463 gliders, 3:63, 3:64F planktonic/fish population changes, 1:576–577 Hydroelectric power generation application of coastal circulation model, 1:575–576 Bay of Fundy, Gulf of Maine, 1:575–576 Hydrogen (H2) absorption band, 5:127, 5:128 cosmogenic isotopes oceanic sources, 1:680T production rates, 1:680T reservoir concentrations, 1:681T specific radioactivity, 1:682T diffusion coefficients in water, 1:147T estuaries, gas exchange in, 3:6 Schmidt number, 1:149T tidal energy, 6:30 see also Deuterium; Tritium Hydrogen carbonate, in river water, 1:627, 1:627T Hydrogenetic ferromanganese nodules, 1:258 Hydrogenous environments, clay minerals, 1:565–567 Hydrogen sulfide, 1:13 accretionary prisms, 1:34 chemosynthesis, 3:159–160, 3:160F, 3:161, 3:162 detoxification, 3:161, 3:162
510
Index
Hydrogen sulfide (continued) transport, 3:161, 3:161F, 3:162 enrichment, Baltic Sea circulation, 1:294–295 enrichment in hydrothermal vent fluid, 3:159 profile, Black Sea, 1:216F, 1:405F Hydrographic cast (hydrocast), 1:708–709, 1:709F Hydrographic departments, history, 5:410 Hydrographic problems, inverse method application, 3:315–316, 3:316F Hydrographic sections, 3:303F mixing estimations, 2:291 Hydro-isostatic effect, anatomy of sea level function, 3:54–56, 3:55F Hydrolight, 4:625 simulations, 4:625, 4:625–628, 4:625F, 4:626F, 4:627F, 4:628F Hydrolight model, 4:381 Hydrologic budget, 5:130 Hydrologic cycle, 4:130–131 sublimation–deposition, 2:328 Hydrology, submarine groundwater discharge (SGD), 3:90–91, 5:557 Hydrophone arrays, bioacoustic research, 1:358F, 1:362, 1:363 Hydrophone flow noise, 1:55 Hydrophones, 3:838–839 moorings, 3:930, 3:930F Hydropower plant, principal parameters, 6:29 Hydrostatic approximations, 5:133–134, 5:137 in forward numerical models, 2:604–605 Hydrothermal circulation crustal chemistry and, 3:46 geophysical heat flow, 3:45–46 Hydrothermal communities, deep submergence science studies, 2:24–26, 2:28–29, 2:32F Hydrothermal environments, 1:565–566 clay minerals, 1:565–567 Hydrothermal flow cell, hydrothermal vent fluids, chemistry of, 3:166–167, 3:167F, 3:170 Hydrothermal fluid chemistry, 2:73, 2:74F Hydrothermal fluid flow, 2:73, 2:74F Hydrothermal plumes ambient flow, effect of, 2:131 basic plume model, 2:131 b-plume, 2:134–135 buoyancy, 2:130, 2:131, 2:131F, 2:136–137 buoyant rise, 2:130–132, 2:131F, 2:136–137 density, 2:130, 2:131F effluent layer, 2:132, 2:133F entrainment, 2:130, 2:131, 2:131–132, 2:131F, 2:132–133, 2:136–137 megaplumes see Megaplumes microbial habitats, 2:73–75, 2:77
observations light attenuation anomalies, 2:130–131, 2:132F temperature, 2:130–131, 2:132F radial outflow, 2:131, 2:131F, 2:132–133 ridge topography, effect of, 2:131, 2:134–135 rotation, effect of, 2:132–133, 2:134–135, 2:134F, 2:135F baroclinic vortex pair, 2:132–133, 2:133–134, 2:134F eddy propagation, 2:133, 2:134, 2:134F, 2:136F laboratory experiments, 2:133, 2:135F spreading level, 2:130, 2:131, 2:131F anticyclonic rotation, 2:132–133, 2:134F, 2:136–137 salinity, 2:132, 2:133F temperature, 2:132, 2:133F see also Hydrothermal vent dispersion (from) Hydrothermal systems biological communities, seismicity and, 3:850 diffuse flow mapping, 1:71 seismicity and, 3:849–850 Hydrothermal vent(s) biodiversity, 2:57, 2:58F, 2:63 biota see Hydrothermal vent biota; Hydrothermal vent fauna, physiology of causes and characteristics, 2:57, 2:58F chemoautotrophic bacteria, 2:57–58 conservative element concentrations in sea water and, 1:628, 1:628F deep manned submersibles for study, 3:123, 3:511 deep-sea fauna see Deep-sea fauna deposits see Hydrothermal vent deposits discovery, 2:55, 2:57 dispersion from see Hydrothermal vent dispersion (from) diversity of marine species and, 2:144 ecology see Hydrothermal vent ecology energy in benthic environment, 1:355 geophysical heat flow and, 3:46 microbes see Deep-sea ridges, microbiology mid-ocean ridge (MOR) crest, discovery, 2:22 radionuclide output, 6:245 salinity and, 1:711 scattering sensors in monitoring of, 6:117T sites, 2:73, 2:74F transient nature, 2:57–58 Hydrothermal vent biota, 3:133–143 chemosynthesis, 3:133–134 chemosynthetic symbionts, 3:133–134, 3:141–142 community development, 3:141F, 3:142F crustaceans amphipods, 3:139
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brachyuran crabs, 3:133F, 3:135F, 3:136–138, 3:136F crab nurseries, 3:136–138 food sources, 3:136–138, 3:139F galatheid crabs, 3:136F, 3:138, 3:138F, 3:139F shrimp, 3:139, 3:139F East Pacific Rise see East Pacific Rise (EPR) enteroptneusts (spaghetti worms), 3:140–141, 3:141F fish bythitids, 3:139–140, 3:140F global distribution, 3:139–140 zoarcids (eel pouts), 3:133F, 3:135, 3:135F, 3:136F, 3:138F, 3:140 food chains, 3:133–134, 3:135, 3:136–138, 3:139F, 3:140 Galapagos Rift see Galapagos Rift hydrogen sulfide, 3:133–134 megafauna, 3:133–134 microbes Archaea, 3:134 bacteria, 3:138, 3:138F chemosynthetic, 3:133–134, 3:141–142 eukaryotes, 3:134 free-living, 3:133–134, 3:135 mollusks archeogastropod limpets, 3:135, 3:136F, 3:138F giant clam, 3:141–142 mussels, 3:133–134, 3:135, 3:136F, 3:138F vesicomyid clams see Vesicomyid clams peripheral vent environments, 3:138, 3:138F, 3:139, 3:140–141, 3:140F, 3:141F planktonic larval stage, 3:135–136 sulfide edifices, 3:139 black smokers, 3:134–135, 3:134F, 3:137F Tubeworm Pillar, 3:134–135, 3:135F symbiotic relationships, 3:133–134, 3:141–142 tubeworms see Polychaetes/polychaete worms vent sites, 3:134F vestimentiferan tubeworms see Vestimentiferan tubeworms see also Deep-sea ridges, microbiology; Hydrothermal vent ecology; Hydrothermal vent fauna, physiology of Hydrothermal vent chimneys, 3:145–146, 3:145F black smokers, 3:134F, 3:144 evolution to white smokers, 3:146 fauna, 3:134–135, 3:137F, 3:153–154 fluid temperature, 3:164, 3:165F elemental and mineral compositions, 3:148–149F, 3:149 mineral precipitation, 3:149 fluid temperature, 3:167–168
Index growth model, 3:146–147, 3:146–149, 3:146F, 3:148–149F as habitats, 3:146, 3:149 chemosynthesis, 3:149 microbial habitat, 2:73–75, 2:75F, 2:78 morphology, 3:145–146, 3:148–149F venting style, 3:167–168 white smokers, 3:145F, 3:146 see also ‘Black smokers’; Deep-sea ridges, microbiology; Hydrothermal vent biota; Hydrothermal vent deposits; Hydrothermal vent ecology; Hydrothermal vent fauna, physiology of Hydrothermal vent deposits, 3:144–150 anhydrite precipitation and chimney growth, 3:146–147, 3:146F axial summit troughs, 3:144–145 deposition process, 3:144 diffuse fluid seepage, 3:145–146 mineral precipitation, 3:145–146, 3:145F, 3:146–147, 3:146F, 3:149 distribution, geologic controls on, 3:144 axial zone distribution, 3:144–145 fast-spreading ridges, 3:144, 3:144–145 faulting, 3:144–145 intermediate-spreading ridges, 3:145 lava burial of deposits, 3:144–145 magmatic sources, 3:144 ridge segmentation, 3:144 rift valley distribution, 3:145 slow-spreading ridges, 3:145 see also Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge seismic structure; Propagating rifts and microplates; Seamounts and off-ridge volcanism elemental/mineral composition, 3:147T, 3:149 chimneys, 3:148–149F, 3:149 mineral precipitation processes, 3:149 mineral zoning, 3:145F, 3:146F, 3:149 fossil record of hydrothermal vent organisms, 3:149–150 evolution of vent communities, 3:149–150 fossilization processes, 3:149 habitats, 3:144, 3:146, 3:148–149F, 3:149 see also Deep-sea ridges, microbiology; Hydrothermal vent biota; Hydrothermal vent fauna, physiology of hydrothermal sediments, 3:145–146 particulate debris, 3:145–146 plume particles, 3:144, 3:145–146 Juan de Fuca Ridge, Endeavour Segment, 3:146 lava flow burial, 3:146, 3:149 metal sulfide minerals precipitation and chimney growth, 3:146–147, 3:146F microbial habitats, 2:73–75, 2:75F, 2:78 mining, 3:144, 3:149
ophiolites, 3:144, 3:149, 3:149–150 seafloor sediments, 3:145, 3:146 seafloor weathering, 3:149 structures, 3:145–146 chimneys see Hydrothermal vent chimneys debris piles, 3:145–146 development, 3:145 edifices, 3:145–146, 3:145F encrustations, 3:145–146 flanges, 3:145–146, 3:145F morphology, 3:145–146 mounds of accumulated mineral precipitates, 3:145–146, 3:145F, 3:149 size, 3:146 stockwork, 3:145 see also Hydrothermal vent fluids, chemistry of; Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge seismic structure; Propagating rifts and microplates; Seamounts and off-ridge volcanism Hydrothermal vent dispersion (from), 2:130–138 advection, 2:132–133, 2:133–134, 2:136–137 ambient fluid currents, 2:132–133, 2:133–134 cyclonic circulation, 2:132–133, 2:133–134, 2:134F density, 2:130, 2:131F atmospheric comparison, 2:137 Coriolis effect, 2:132–133, 2:134–135 diffuse venting, flow characteristics, 2:130 heat flux, 2:131, 2:132 hydrothermal plumes see Hydrothermal plumes large-scale flow, 2:134–135, 2:137F b-plume, 2:134–135 larvae of vent organisms, 2:131–132, 2:134 mass balance, 2:134–135 megaplumes see Megaplumes mesoscale flow, 2:132–134 timescales, 2:130 vortices, 2:132–134 see also Hydrothermal vent biota; Hydrothermal vent ecology; Hydrothermal vent fluids, chemistry of; Meddies; Mesoscale eddies Hydrothermal vent ecology, 3:151–158 biodiversity of vent fauna, 3:155–157 spreading rate, effect of, 3:157 biogeography of vent fauna, 3:155–157 isolation/differentiation mechanisms, 3:156–157, 3:156F ocean basin variations, 3:157 chemosynthetic processes, 3:151–152, 3:152F Calvin-Benson cycle, 3:151–152 chemosynthetic bacteria, 3:151–152, 3:152F energy yields, 3:151–152
511
community dynamics, 3:154–155 eruptive event monitoring, 3:155 mussels, 3:154–155 stability in species composition, 3:155 swarming shrimp, 3:153F, 3:155 TAG vent site (Mid-Atlantic Ridge), 3:155 Venture Hydrothermal Field 1991 eruption, 3:154–155 vesicomyid clams, 3:154–155 vestimentiferan tubeworms, 3:154–155 floc, 3:154–155, 3:154F food web, 3:151 free-living chemosynthetic bacteria, 3:153 origin of life, 3:151, 3:157 acellular precursor, pyrite supported, 3:157 chemosynthetic basis, 3:157 origins of vent fauna, 3:155–157 fossil vent communities, 3:156 invasion, 3:155 relict taxa, 3:155–156 specialized taxa, 3:155–156 photosynthesis, 3:151, 3:152F phytoplankton, 3:151 shrimp, swarming, 3:153F symbiosis and the host-symbiont relationship, 3:152–153 bathymodiolid mussels, 3:153 endosymbiotic bacteria, 3:152–153, 3:153 metabolic requirements, 3:153 shrimp, 3:153, 3:153F vesicomyid clams, 3:153 vestimentiferan tubeworms see Vestimentiferan tubeworms thermal adaptations, 3:153–154 alvinellid polychaete (Alvinella caudata), 3:153–154, 3:154F high temperature tolerance, 3:153–154 shrimp (Rimivaris exoculata), 3:154 vent environment, 3:151 vent exploration, 3:151 vent invertebrate food web free-living chemosynthetic bacteria, 3:153 heterotrophic bacteria, definition, 3:153 see also Hydrothermal vent biota; Hydrothermal vent deposits; Hydrothermal vent fauna, physiology of; Hydrothermal vent fluids, chemistry of; Mid-ocean ridge tectonics, volcanism and geomorphology Hydrothermal vent fauna, physiology of, 3:159–163 chemosynthesis, 3:159–160 Calvin-Benson cycle, 3:160 carbon dioxide, 3:160, 3:160F food chain, 3:160, 3:162 free-living bacteria, 3:159–160
(c) 2011 Elsevier Inc. All Rights Reserved.
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Index
Hydrothermal vent fauna, physiology of (continued) hydrogen sulfide, 3:159–160, 3:160F, 3:161, 3:162 symbiotic bacteria, 3:159–160 environmental conditions, 3:159 fluid flow rate, 3:159 hydrogen sulfide enrichment, 3:159, 3:161–162 temperature, 3:159 volcanic activity, 3:159 photosynthesis, 3:159 see also Deep-sea ridges, microbiology; Hydrothermal vent biota; Hydrothermal vent deposits; Hydrothermal vent ecology; Hydrothermal vent fluids, chemistry of Hydrothermal vent fluids, chemistry of, 3:164–171 black smokers, 3:164, 3:165F chemical flux, 3:164, 3:170 chimney construction, fluid temperature and venting style, 3:167–168 fluid composition controls, 3:166–168 biological uptake/removal, 3:166–167 magmatic degassing, 3:166–167 phase separation, 3:166–167, 3:167F, 3:169–170 water-rock reaction, 3:166–167, 3:167F, 3:169–170 fluid composition observations, 3:169–170, 3:169T acidity, 3:169–170 chlorinity, 3:135–136, 3:169–170, 3:170 enrichment, 3:169–170 low-temperature diffuse flow, 3:169–170 seafloor physical parameters, noncorrelation to, 3:170 sea water comparison, 3:169–170, 3:169T steady-state venting, 3:170 tectonic/cracking events, influences of, 3:168, 3:170 time, variations with, 3:170 fluid temperature and venting style, 3:167–168 chimney construction, 3:167–168 high-temperature focused flow, 3:167–168 low-temperature diffuse flow, 3:167–168, 3:169–170 global distribution, 3:164, 3:166F back arc spreading centers, 3:164, 3:166F mid-ocean ridge system, 3:134F, 3:164 heat flux, 3:164, 3:168–169, 3:170 off-axis vents, 3:168–169 hydrothermal flow cell, 3:166–167, 3:167F, 3:170 oceanic crust interaction, 3:166–167, 3:167F, 3:169–170 off-axis vents, 3:168–169
data collection difficulties, 3:168–169 Juan de Fuca Ridge, 3:168–169 plumes, 3:164–166 lack of, 3:168–169 observations, 3:168 see also Hydrothermal plumes sea water, properties of, 3:164, 3:166–167, 3:167F survey and discovery methods, 3:164, 3:164–166 Alvin, 3:165F, 3:168 dredging, 3:164–166 nested survey strategy, 3:164–166 Ocean Drilling Program, 3:168–169 ROV (remotely operated vehicle), 3:164–166 SOSUS (Sound Surveillance System), 3:168 surface ship surveys, 3:164–166, 3:168 tectonic/cracking events, influences of, 3:168 fluid composition, 3:168, 3:170 fluid temperature, 3:168 spreading rates, variations with, 3:168 volcanic events, influences of, 3:168, 3:170 Alvin observations, 3:168 see also Hydrothermal vent deposits; Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge seismic structure; Mid-ocean ridge tectonics, volcanism and geomorphology; Seamounts and off-ridge volcanism Hydrothermal venting, 6:277, 6:283 Hydroxyl radical (OH), 4:416–417, 4:417 Hygrometers, 5:388 capacitance change, 5:379 dew point, 5:379 infrared, 5:388–389, 5:388F, 5:389F krypton, 5:388 Lyman a, 5:388 Hyperbenthos (suprabenthos), 1:328, 2:55, 3:468 see also Benthic boundary layer (BBL) Hyper Dolphin, 6:260T HYPER-DOLPHIN ROV, 4:746T Hyperoodon ampullatus (northern bottlenose whale), 3:643, 3:646, 3:647–648, 3:647F, 3:649 Hypersaline, definition, 1:268 Hyperspectral sensors, 4:737–738 Hyper-spectral systems AVIRIS see Airborne Visible/Infrared Imaging Spectrometer (AVIRIS); Infrared (IR) radiometers; Optical particle characterization used by aircraft for remote sensing see Aircraft for remote sensing Hyperthermophilic microbes, 2:77–78 definition, 2:73–75 Hypertidal estuaries, 2:299–300 Hypoxia, 3:172–180 anthropogenic zones, 3:174 causes, 3:173
(c) 2011 Elsevier Inc. All Rights Reserved.
consequences, 3:177–179 direct effects, 3:177–179 secondary production, 3:179–180 ‘dead zone’, 3:172–173 definitions, 3:172–173 geographic distribution, 3:172, 3:172F marine organisms, affects to, 3:172 outlook, 3:180 oxygen, historical change in, 3:176–177 oxygen-minimum zones see Oxygen minimum zone (OMZ) systems, 3:173 see also specific systems/environment see also Anoxia
I IA (Ionian anticyclones), 1:748–751, 1:748F IABO (International Association of Biological Oceanography), 5:513 IAEA (International Atomic Energy Agency), 4:629 IAPSO standard seawater, 1:712 IAS see Intra-Americas Sea (IAS) IBM see Lagrangian biological models ICCAT (International Commission for the Conservation of Tuna), fishery management, 2:513–514 Ice categories, 1:689–690, 1:692F classes, 1:689, 1:692F deep convection, 2:13–15, 2:19–20 drift see Drift ice formation dense water and, 4:55 noble gases and, 4:55–58 physical properties relevant, 4:55–56 tracer applications, 4:56–58 noble gas saturation and, 4:57, 4:57–58 phase partitioning of dissolved gases, 4:56 marine, 5:545–546, 5:547 pinniped (seal) haul-out sites, 3:602 sea see Sea ice strengthening, oceanographic research vessels, 5:412 temperature, 3:188–189, 3:188F upper ocean mixing, 6:190–191 see also Sea ice; entries beginning ice Ice, Cloud and land Elevation Satellite (ICE-SAT), 5:84 Ice ages astronomical theory (Milankovitch, Milutin), 4:504–505 climate transitions within, 1:1–2 end, 1:1 Ice-bearing permafrost, 5:560, 5:560F Iceberg(s), 3:181–190 blocky form, 3:186T calving, 3:211 destruction of, 3:190
Index deterioration, 3:187–188 cliff faces, calving of, 3:188 melting, 3:187–188 ram loss, 3:188 splitting, 3:188 domed form, 3:186F, 3:186T drydock form, 3:186F, 3:186T economic importance, 3:189 hazard to shipping, 3:189 seabed damage, 3:189 usage of icebergs, 3:189–190 gouging, 3:191 Greenland vs. Antarctica, 3:181 ice properties, 3:188 ice shelf stability, 3:209 northern regions numbers, 3:184–185 size distribution, 3:184–185 sizes, 3:186–187 numbers, 3:182–185 origins, 3:181 pinnacle form, 3:186F, 3:186T satellite imagery, 3:183 scours, 3:189 shapes, 3:185–187, 3:186T, 3:187F size distribution, 3:182–185 sizes, 3:185–187, 3:185T southern regions numbers, 3:185 size distribution, 3:185 sizes, 3:187 spatial distribution, 3:182 spatial distribution, 3:181 tabular form, 3:185F, 3:186T wedge form, 3:186F, 3:186T see also specific geographic regions Iceberg-rafted detrital (IRD) peaks, 3:883 see also Heinrich events Ice biota, 5:171–172 Ice-bonded permafrost conduction model, 5:560 definition, 5:559–560 ice-bearing permafrost, separation effects, 5:562 Icebreakers, acoustic noise, 1:99 Icebreaking, polar research vessels’ capability, 5:416 Ice caps, sea level variations and, 5:182 Ice cores, paleoclimatic data, 1:1 Ice cover internal wave field affects, 3:207 particle flux variability, 6:1–2 Ice draft, mean see Mean ice draft Icefishes (Channichthyidae), 1:193 Ice floes, 5:159, 5:172 see also Drift ice Ice-gouged seafloor, 3:191–197 historical aspects, 3:191 locations, 3:196 see also specific locations observational techniques, 3:191 offshore wells, 3:191 results, 3:191–195 stochastic models, 3:194–195 water depth maximum, 3:193
‘Ice house world,’ oxygen isotope evidence, 1:509–511 Ice islands, 3:194 Ice krill (Euphausia crystallarophias), 3:353, 4:518, 5:514 Iceland, 4:126–127, 4:127F, 4:130 crustal thickness, 3:877, 3:878F Laki, 3:224–225 magmatism, 3:874, 3:877 North Atlantic Oscillation, variability, 4:67 Salmo salar (Atlantic salmon) fisheries, 5:1–2, 5:2T Iceland-Faroes front, 2:585F Icelandic cod see Atlantic cod (Gadus morhua) Iceland Low see North Atlantic Oscillation Iceland–Scotland Overflow Water, 1:24 Ice–ocean interaction, 3:198–208 horizontal inhomogeneity summertime buoyancy flux, 3:205–207 wintertime buoyancy flux, 3:203–205 internal waves, ice cover, interaction effects, 3:207–208 outstanding issues, 3:208 under-ice boundary layer see Under-ice boundary layer Weddell Sea circulation, 6:318 freshwater fluxes, 6:318, 6:324 momentum transfer, 6:318 wintertime convection heat balance, 3:201–203 mass balance, 3:201–203 Ice-rafted detritus (IRD) deposition, 1:509, 1:511 distribution, 1:509–510, 1:511 Ice-rich permafrost definition, 5:559–560 location, 5:562 ICES see International Council for the Exploration of the Sea (ICES) Ice sheets, 3:888F decay over geological time, 5:180F, 5:185 formation, 1:509–510 glaciological modeling, 3:49 gravitational pull, glacio-hydro-isostatic models, 3:53 maximum glaciation, glacial cycles and sea level change, 3:50–51, 3:51F ocean d18O values and, 1:505, 1:505–506, 1:506F sea levels and, 5:182–183 see also Antarctic Ice Sheet; Greenland Ice Sheet Ice shelf water (ISW), 5:544–545 Ice shelves, 1:417–418, 3:182, 3:209–211 bay illustration with ice streams, 3:210F definition, 3:209 features, 5:541 locations, 5:541 map, 5:542F stability, 3:209–217 break-up, reasons for, 3:213–214
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case studies, 3:212–213, 3:213 disintegration, 3:212–213 geographical setting, 3:209–211 grounding lines, 3:215–217 historical alterations, 3:211–212 importance, 3:211 physical setting, 3:209–211 vulnerability of, 3:215–217 see also specific ice shelves Ice states, 5:159 Ice Station Weddell, 6:156–157, 6:156F under-ice boundary layer, 6:156F, 6:159 Ice-volume equivalent sea level function, 3:56, 3:56F ICJ see International Court of Justice (ICJ) ICM see Integrated coastal management (ICM) ICNAF see International Commission for Northwest Atlantic Fisheries (ICNAF) ICP see International Conference of Paleoceanography (ICP) ICP-MS (inductively coupled plasma mass spectrometry), 2:103–104 ICSU (International Council of Scientific Unions), 3:277 Ictaluridae (catfish), 2:481 ICZM (integrated coastal zone management) marine policy, 3:668 see also Integrated coastal management (ICM) Ideal gas law, and temperature scale, 1:710 Idealized ocean general circulation model (OGCM), 4:304 Identical twin experiments, 1:366–368, 1:366F advantages, 1:364 Idronaut,S.r.l, 1:715–716 Ierapetra Anticyclone, 3:719F, 3:720, 3:720T IEW (Indian Equatorial Water), temperature-salinity characteristics, 6:294T, 6:298, 6:298F IFQ (Individual Fishery Quota) system, fishery management, 2:517, 2:520 IFREMER see French Research Institute for Exploration of the Sea (IFREMER) IGBP (International Geosphere-Biosphere Program), 3:277 Igneous provinces, 4:320–321 see also Large igneous provinces (LIPs) IGOS (Integrated Global Observing Strategy), 5:77 IGW (internal gravity waves), phytoplankton interactions, 4:482F IIW see Indonesian Intermediate Water (IIW) IKMT (Isaacs–Kidd midwater trawl), 6:355 Illite, 1:563, 3:912 distribution Atlantic ocean, 1:563–564
514
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Illite (continued) global, 1:564F Indian Ocean, 1:564–565, 1:565F IMAGES (International Marine Global Change Study), 4:301 Imaging systems, deep-towed, 6:255 IMI-30, 6:256T IMO see International Maritime Organization (IMO) Imperial shag, 4:372F see also Shag(s) Incongruent release (of trace metals from rocks), 3:464–465, 3:465T INDEX (Indian ocean experiment), 5:494, 5:495, 5:497F India, artificial reefs, 1:226–227, 1:227 Indian boats (archaeology), in Central American sinkholes, 3:697 Indian Central Water (ICW), 6:182–183 Indian Equatorial Water (IEW), temperature–salinity characteristics, 6:294T, 6:298, 6:298F Indian mackerel (Rasterlliger kanagurta), 4:368 Indian Ocean, 1:728, 3:444, 3:446, 3:449, 3:451 abyssal circulation, 1:27–28, 1:28F see also Abyssal currents atmospheric circulation, 1:728–730, 1:729F see also Monsoon barrier layer, 6:181 basin, characteristics, 1:728, 1:729F, 1:734 benthic foraminifera, 1:339T bioluminescent phenomena, 1:383 carbonate compensation depth, 1:453F carbonate saturation, 1:450–451 depth profile, 1:449F climatological mean temperature, 6:183F continental margins, 4:256T primary production, 4:259T coral records, 4:344F current systems see Indian Ocean current systems dust deposition rates, 1:122T ferromanganese oxide deposits, 3:488T heat transport, 3:117–118 illite, 1:564–565, 1:565F krill species, 3:350 magnetic anomalies (linear), 3:485F manganese nodules, 3:491–492, 3:493–494, 3:495 monsoons nanofossil species diversity, 3:916F seasonal variability, 3:910 sedimentary record, 3:910 nepheloid zone turbidity, 4:13F organochlorine compounds, 1:123T, 1:246T osmium concentration, 4:496–497, 4:497T, 4:498F oxygen concentration, 6:183F platinum profiles, 4:497, 4:500F radiocarbon, 4:641F, 4:643F
rare earth elements, associated with particulate matter in sea water, 4:658T river inputs, 4:759T salinity, 6:183F sea–air flux of carbon dioxide, 1:493T sea ice cover, 5:146–147 smectite distribution, 1:565F Southeast Asian seas and, 5:314–315 subsurface passages, 1:15–16, 1:15F trace metal isotope ratios, 3:457 tsunami (2004), 6:129 linear shallow water equations and, 6:134 volcanic helium, 6:279 water masses deep and abyssal waters, 6:296–297, 6:296F temperature–salinity characteristics, 6:293F, 6:294T, 6:298, 6:298F upper waters, 6:293–295, 6:295F western, 6:4F Indian Ocean current systems, 1:728–734 deep circulation, 1:734 eastern part, 1:730–731 equatorial see Indian Ocean equatorial currents northern part, response to wind variability, 1:728, 1:731–732 eastern boundary, affected by monsoons, 1:733–734 northern interior, 1:732–733 western boundary, 1:731–732, 5:495, 5:503 see also Monsoon southern part, 1:128, 1:728, 1:730–731, 1:731F see also specific currents Indian Ocean equatorial currents, 3:226–236 Atlantic Ocean equatorial current system vs., 3:226, 3:236 drifting buoy observations, 3:228–229, 3:229F, 3:230F, 3:235F, 3:236 at equator, 3:227 along Somali Coast, 3:227, 3:228F, 5:494 see also Somali Current at depth, 3:230–232, 3:232F measurements, 3:230–232, 3:231F, 3:232, 3:233F surface, east of 521E, 3:227–230, 3:228F measurements, 3:228–229, 3:228F, 3:229F, 3:230F, 3:231F future studies, 3:236 monsoon circulation and, 1:732–733, 3:226–227, 3:226F see also Monsoon north of equator, 3:232–233 south of Sri Lanka, 3:229F, 3:231F, 3:232–233, 3:234F Pacific Ocean equatorial current system vs., 3:226, 3:236 south of equator, 3:233–234
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South Equatorial Countercurrent see South Equatorial Countercurrent (SECC) South Equatorial Current see South Equatorial Current (SEC) Wyrtki jet, 1:732–733, 3:227–228, 3:228F, 3:230–232 see also specific currents Indian ocean experiment (INDEX), 5:494, 5:495, 5:497F Indian Ocean Standard net, 6:355, 6:356F Indian Ocean Tuna Commission, 4:242 Indicator organisms beaches, microbial contamination, 6:268 climate change krill as, 3:356–357 planktonic indicators, 4:455–456, 4:463F seabirds as indicators of pollution see Seabird(s) sewage contamination, 6:274T, 6:275 Indium concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:691–692 depth profile, 4:692F properties in seawater, 4:688T Individual-based models (IBMs), 3:389, 4:97–98, 4:103, 4:208, 4:212, 4:547, 4:550 i-state, 4:550 marine ecosystems, low-diffusivity regions, 4:212 physiologically structured population models vs., 4:547 representation of population interactions, 4:554 spatially explicit, 4:553 see also Population dynamic models Individual Fishery Quota (IFQ) system, fishery management, 2:517, 2:520 Individual Transferable Effort (ITE), fishery management, 2:518 Individual Transferable Quota (ITQ) system, fishery management, 1:706, 2:517, 2:520, 2:525, 2:526 Individual water parcels, 4:126 Indonesia earthquake (1992), 6:137F El Nin˜o events and, 2:228, 2:239 inundation maps, 6:136F tsunami (2004), 6:129 Indonesian Intermediate Water (IIW), 3:237–238 Indian Ocean, 3:238–239 temperature–salinity characteristics, 6:294T, 6:298, 6:298F Indonesian-Malaysian Passages NADW formation, 4:306 paleoceanography climate models in, 4:303 gateway and global ocean circulation, 1:512, 4:306 Indonesian Sea Water (ISW), 5:306
Index Indonesian Throughflow, 1:733–734, 3:237–243 bathymetric map, 3:238F currents, 3:237 ENSO and, 3:239 heat transport, 3:239–240 mass transport, 3:239 mean throughflow mass and heat flux estimates, 3:239–240 mixing, 3:237–238 monsoons, 3:241F overview, 3:237 salt transport, 3:239–240 seasonal winds and, 5:315 Southeastern Asian sea and, 5:315 variability, 5:315 annual, 3:240–242 interannual, 3:242–243 of properties and transport, 3:240–242 semiannual, 3:242 water masses, 3:237–239, 3:238F Indonesian Throughflow Water (ITW), 3:237–238 Indian Ocean, 3:238–239 Indonesian Upper Water (IUW), temperature–salinity characteristics, 6:294T, 6:298, 6:298F Indo-Pacific Ocean, heat transport, 3:118 Inductively coupled plasma mass spectrometry (ICP-MS), 2:103–104 Indus, sediment load/yield, 4:757T Industrial enzymes, marine biotechnology see Marine biotechnology Industrial inflows, impact on water quality, monitoring with scattering sensors, 6:117T Industrial solids, 4:522–523 see also Pollution solids Industry, pollutants from see Pollution solids Inelastic optical scattering, 4:734–735 Inertial circulation, 6:212–213 Inertial currents Baltic Sea circulation, 1:296 Intra-Americas Sea (IAS), 3:293 North Sea, 4:80–81 Inertial dissipation method, 3:106–107 evaporation, 2:325–326 Inertial frequency, 6:212–213 Inertial navigation system, 4:476F, 4:478 Inertial period, 6:194 Inertial recirculations, 3:764 Infauna, 1:349, 1:356, 3:467, 3:471 burrows, 1:395, 1:398, 2:56F communities, 1:350 latitudinal differences, 1:350, 1:351F Petersen’s, 1:350, 1:351T Thorson’s, 1:352T, 3:471 size groups, 1:350F Infectious disease(s) mariculture management, 3:521 see also Mariculture diseases Infectious pancreatic necrosis virus (IPNV), mariculture disease, 3:519, 3:520T, 3:521, 3:523
Infectious salmon anemia virus (ISAV), mariculture disease, 3:520T, 3:521 Inferred water trajectories, 3:453F Inflows see see specific inflows/seas Information theory, regime shift analysis and, 4:720 Infragravity waves, 6:314, 6:314–315 far, 6:315 magnitude, 6:314–315, 6:315T seiche generating mechanism, 5:349 see also Edge waves; Waves on beaches Infrared atmospheric algorithms, satellite remote sensing of sea surface temperatures, 5:91–93 Infrared budget, 6:164 Infrared hygrometers, 5:388–389, 5:388F, 5:389, 5:389F Infrared (IR) radiation, 3:244, 3:249F, 3:319 measurement theory, 3:319–322 emittance, 3:319, 3:320F Planck’s law, 3:320 radiance, 3:319, 3:320F radiant energy, 3:319 radiant flux, 3:319 radiant intensity, 3:319, 3:320F spectral radiance, 3:320, 3:320F seawater absorption depth, 6:164 see also Solar radiation Infrared (IR) radiometers, 3:319–330, 3:322F application, 3:324 broadband pyrgeometers, 3:324, 3:324F multichannel radiometers see Multichannel radiometers narrow beam filter see Narrow beam filter radiometers spectroradiometers, 3:327–328, 3:328F thermal imagers see Thermal imagers cooled detectors, 5:94 design, 3:322 calibration system to quantify output, 3:323–324 detector and electronics system, 3:322 environmental system, 3:323 antireflection coatings, 3:323 thermal shock considerations, 3:323 window materials, 3:323, 3:323F fore-optics system, 3:322–323 mirrors, 3:322 spectral filter windows, 3:323, 3:323F detector types, 3:322 future directions, 3:329–330 microwave radiometers vs, satellite remote sensing of SST, 5:93 new generation/future improvements, 5:101 satellite-borne, 3:329–330, 5:92F, 5:94, 5:94T see also Air–sea gas exchange; Radiative transfer; Satellite remote sensing of sea surface temperatures
(c) 2011 Elsevier Inc. All Rights Reserved.
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Infrared thermography, 3:91F saline groundwater detection, 3:90 Inherent optical properties (IOPs), 3:244–253, 3:244–245, 4:621–623, 4:733, 6:109 apparent optical properties and, 3:247 chlorophyll concentration and, 1:388, 1:389–390, 1:389F, 1:390T, 1:391F coefficients, 3:244–245, 6:109 see also specific coefficients definition, 4:619, 4:622F irradiance, and fish vision see Fish vision mathematical operations, 3:245 measurement beam attenuation coefficient see Transmissometry new technologies, 6:116 volume scattering function see Nephelometry models, 1:385 see also Bio-optical models penetrating shortwave radiation, 4:379 quantities, 4:620T see also Apparent optical properties (AOPs); Infrared (IR) radiometers; Ocean color; Ocean optics; Optical particle characterization Inia (South American river dolphins), 2:156, 2:159 Inia geoffrensis (boto), 2:157 Injectite, 5:454F, 5:463 INL (intermediate nepheloid layers), 4:8, 4:16–17 Inland seas, continental shelf and, 4:256–257 Inlets modification, 1:588 seiches see Seiches see also specific inlets Innocent passage, Law of the Sea jurisdictions, 3:434 Inorganic carbon dissolved see Dissolved inorganic carbon (DIC) particulate see Particulate inorganic carbon (PIC) pump, 4:682 total see Total inorganic carbon (TIC) see also Carbon Inorganic particles, 4:331F, 4:333 as optical constituents of sea water, 4:624–625 Inorganic side-reaction coefficient, 6:103, 6:103T INPFC (International North Pacific Commission), 5:20 INS (inertial navigation system), 4:476F, 4:478 Insecticides, organochlorines, seabirds as indicators of pollution, 5:274, 5:274–275, 5:275 Inside corners, 3:840 In situ chemical analysis see Wet chemical analyzers In situ measurements, 5:84, 5:85
516
Index
In situ measurement techniques, geoacoustic parameters, 1:81–82, 1:83T cross-hole method, 1:82–83, 1:83F ISSAMS (in situ Sediment Acoustic Measurement System), 1:82, 1:82F near-surface method, 1:82 In situ zooplankton detecting device, 6:367F, 6:368 Insolation, 3:449, 4:506F caloric summer half-year, 4:509F glacial cycles and, 4:504 methods of calculation, 4:508 mixed layer stratification and, 6:218 orbital parameters affecting, 4:311–312, 4:505–507, 4:507F, 4:508 range, 6:164 surface layer stability and, 6:166 Instabilities of MOC, 4:130–131 in Pacific Ocean, 5:99, 5:101F INSTANT (International Nusantara Stratification and Transport program), 3:239, 5:316 Instantaneous timescales, geomorphology, 3:35 Institute of Marine Research, Norway, 4:633 Institutional frameworks, marine policy see Marine policy Instrumentation acoustic measurement, sediments see Sediment transport aircraft for remote sensing, 1:138 benthic flux landers, 4:490 borehole logging, 2:52 Continuous Plankton Recorder (CPR) survey, 1:631F, 1:633, 6:357T, 6:359–361, 6:360F floats, 2:174–175 geophysical heat flow measurements, 3:40–43 gliders (subaquatic), 3:63–64 gravimetry, 3:81 oceanographic, deep submergence science, 2:22 ocean optics see Ocean optics wet chemical analyzers, 6:329–330 Insurance marine protected areas, 3:675 shipping and ports, 5:407 Integrated coastal management (ICM), 1:600–601 consequences of choices, 1:604 coordination mechanisms, 1:601 Earth Summit, Agenda 21, 1:600 EC’s definitions and aims, 1:601 environment-development interdependence, 1:600–601, 1:600F future directions, 1:603–604 initiatives, growth of, 1:603 national program differences, 1:601 regional initiatives, see also Coastal zone management successful programs, 1:601
types of action taken, 1:601 see also Coastal zone management Integrated coastal zone management (ICZM), marine policy, 3:668 Integrated Global Observing Strategy (IGOS), 5:77 Integrated Ocean Drilling Program (IODP), 2:37, 2:54, 4:297–298 drilling sites, 2:38F IODP Site 302, 4:322F logging tools, 2:41–42 methodologies see Deep-sea drilling, methodology Integrated water vapor (IWV), 5:206–207 Inter-American Tropical Tuna Commission, 4:242 Interface displacements, equations of motion, forward numerical models, 2:605–606 Interface waves, seismo-acoustic, 1:79–80, 1:84F, 1:87–88 acoustic remote sensing, 1:84F, 1:89 arrival times, 1:80, 1:80F, 1:89 dispersion diagram, 1:89, 1:89F Rayleigh wave, 1:79–80 Scholte wave, 1:78T, 1:79–80, 1:79F Stoneley wave, 1:79–80 see also Acoustics, marine sediments; Seismo-acoustic waves Interfacial waves, 3:266–268 continental shelf, 3:271–272 generation, 3:267 layer thickness, 3:266–267 shoreline behavior, 3:267–268 solitons, 3:266–267, 3:267F speed, 3:266 vertical motion, 3:268 Interglacials, monsoon abundance relative to glacials, 3:914 Intergovernmental Oceanographic Commission (IOC), 3:274 composition, 3:274 marine scientific investigations, 3:276 regional subsidiary bodies, 3:274 technical subsidiary bodies, 3:274 work of the Secretariat, 3:274 Intergovernmental organizations (global), 3:274 see also Intergovernmental Oceanographic Commission (IOC); World Meteorological Organization (WMO) Intergovernmental organizations (regional), 3:275–276 ICES see International Council for the Exploration of the Sea (ICES) other regional commissions, 3:277 Helsinki Commission, 3:277 OSPAR Commission, 3:277 PICES see North Pacific Marine Science Organization (PICES) Intergovernmental Panel on Climate Change, 3:275 Interior continental shelf see Proximal continental shelf Interior feeding, 1:395
(c) 2011 Elsevier Inc. All Rights Reserved.
Interleaving Antarctic Intermediate Water (AAIW), 1:424 Brazil and Falklands (Malvinas) Currents, 1:422–423, 1:427 Brazil/Malvinas confluence (BMC), 1:427 Intermediary layer, fiords, 2:353, 2:357 Intermediate Atlantic Water, 3:887 Intermediate beaches, 1:306–309, 1:307F, 1:308F control of, 1:307 longshore bar and trough system, 1:309–310 low tide terrace, 1:307–309, 1:309F rhythmic bar and beach state, 1:309, 1:310F transverse bar and rip state, 1:309, 1:309F Intermediate complexity models, carbon cycle, 4:109–110 Intermediate disturbance hypothesis, 4:534–535 Intermediate nepheloid layers, 4:8, 4:16–17 Intermediate-spreading ridges, hydrothermal vent deposits, 3:145 Intermediate waters, 6:292, 6:295, 6:296F Internal energy budget, 2:262 Internal gravity waves, phytoplankton interactions, 4:482F Internal solitary waves see Solitons Internal tidal mixing, 3:254–257, 3:258, 3:264–265 boundary layer dissipation vs. scatter, 3:255–256 down gradient flux equation, 3:254 satellite altimetry, 3:256–257 spatial resolution, battle for, 3:254 stirring, 3:254 stratification, maintaining, 3:254–255 tidal dissipation, astronomic evidence, 3:255 Internal tides, 3:255, 3:258–265, 6:50, 6:213 analysis, 3:258–259 beams, 3:259–261 definition, 3:259–260 dissipation, 3:261 energy propagation, 3:260, 3:261F reflection, 3:260 shelf breaks, 3:260, 3:260F coherence, 3:263 current velocities, 3:258 definition, 3:258 dissipation, 3:261, 3:264–265 diurnal, 3:259 energy energy budget, 3:265 mixing and, 3:258, 3:264–265 open ocean, 3:264–265 propagation, 3:260, 3:261F generation, 3:258, 3:260 deep-sea ridges, 3:263, 3:264F, 3:265 point, 3:258, 3:259, 3:259–260
Index seamounts, 3:265 shelf breaks, 3:260F, 3:261, 3:265 Hawaiian Ridge, 6:52F higher harmonics, 3:258 incoherence, 3:258, 3:263 internal displacements, 3:258, 3:261–263 latitudinal variations, 3:259 mixing see Internal tidal mixing modes, 3:259, 3:261 continental shelf, 3:259 deep-ocean, 3:259, 3:259F nutrient concentrations, 3:264 observations, 3:261 acoustic methods, 3:263–264 moored current meters see Moored current meters satellite altimetry see Satellite altimetry vertical profilers, 3:261 properties, 3:258 Puerto Rico, 6:53F seafloor topography, 3:260, 3:263, 3:264F canyons, 3:260–261 continental shelf, 3:259, 3:263 deep-sea ridges, 3:263, 3:264F, 3:265 seamounts, 3:265 shelf breaks, 3:260, 3:260F, 3:265 semidiurnal, 3:259, 3:261, 3:262F solitons, 3:258, 3:261, 3:262F, 3:264 stratification, 3:258, 3:261 surface tides, decoupling from, 3:261 tidal energy, proposed flux, 3:257, 3:257F variability, 3:258 wave breaking, 3:258, 3:264–265 see also Acoustics, marine sediments; Internal tidal mixing; Internal wave(s); Satellite altimetry; Tide(s) Internal wave(s), 3:266–273 amplitude, 3:266–267, 3:267–268 Antarctic Circumpolar Current, 2:127–128 atmospheric, 3:272 bottom reflection and scattering, 3:270–271, 3:271F amplification, 3:270–271 buoyancy frequency, 3:270 energy redistribution, 3:271 mixing, 3:271 breaking, 3:270, 3:271, 3:272, 6:23 characteristics, 3:266 continental shelf, 3:271–272 currents, 3:266, 4:60–61 eddy diffusivity, 3:271 energetics and mixing, 3:270, 3:271, 3:272F energy propagation, 3:268, 3:269, 3:269F topography, 3:271 turbulent energy dissipation and, 2:296–297 energy spectra, 5:358–359, 5:359F see also Garrett-Munk spectrum
evolution, 3:270, 3:272F decay time, 3:271 resonance, 3:270 field, ice cover, 3:207 fine-structure contamination, 6:287, 6:288 frequency, 3:268, 3:269F, 3:270 spectra, 3:268, 3:269F, 3:270 generation, 3:270, 3:272F, 5:350 storms, 3:270 tides, 3:267, 3:270, 5:349–350, 5:349F see also Internal tides topography, 3:270 wind, 3:270, 3:271 horizontal divergence, 6:288–289 inertial peak, 3:269–270, 3:270 interfacial waves see Interfacial waves Kelvin waves see Kelvin waves lee waves, 3:270, 3:272 mixing, 3:266, 3:271, 3:272F models, 3:272 North Sea, 4:81 nutrient fluxes, 3:266 observations, 3:268–270 fixed point, 3:268 inertial cusp, 3:268 vertical profiles, 3:268–269 physics, 3:268 buoyancy frequency, 3:268 Coriolis force, 3:268 group velocity, 3:268, 3:269F restoring forces, 3:268 propagation, laboratory experiments, 2:578 seafloor topography, 3:271, 3:272F energetics and mixing, 3:271 generation, 3:270 reflection, 3:270–271, 3:271F seiches, 5:349, 5:349F seismic reflection profiling and, 5:358–359 stratification, 3:266 submarine detection, 3:266 surface mixed layer deepening, 3:272 three-dimensional turbulence, 6:22, 6:22–23, 6:23F tidal frequency, satellite remote sensing application, 5:110–111, 5:111F tomography, 6:50 turbulent energy dissipation and, 2:296–297 upper ocean, 6:212–213 water transport, 3:267–268 wavelength, 3:266–267, 3:270–271 wavenumber, 3:268, 3:268–269, 3:269, 3:270 wind, effect of, 3:270, 3:271 wind forcing and, 2:265 see also Breaking waves; Internal tidal mixing; Internal tides; Surface, gravity and capillary waves; Wave generation Internal Wave Experiment (IWEX), 6:287 ‘Internal weather of sea’, 5:479–481
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517
International Antarctic Treaty (1959), 5:416 International Association of Biological Oceanography (IABO), 5:513 International Association for the Physical Sciences of the Oceans (IAPSO), salinity definitions, 4:29–30 International Atomic Energy Agency (IAEA), 4:629 International Bathymetric Charts project, 1:302–303 International Commission for the Conservation of Atlantic Tunas (ICCAT), 4:242 fishery management, 2:513–514 International Commission for Northwest Atlantic Fisheries (ICNAF), 5:6 groundfish resources, quota management scheme, 2:96 International Commission on Radiological Protection (ICRP), 4:527–528 International Conference of Paleoceanography (ICP), 4:295 meetings, 4:296T International conflicts, ocean resource use, 3:666 International Convention for the Conservation of Atlantic Tunas, 3:668T International Convention for the HighSeas Fisheries of the North Pacific Ocean, 5:20 International Convention for the Safety of Life at Sea (SOLAS), 5:405 International cooperation, need to conserve the seas, Law of the Sea, 3:433–434 International Council for Science (ICSU), 3:277–278 IGBP (International GeosphereBiosphere Program, 3:277 interdisciplinary bodies created, 3:277 International Council of Scientific Unions (ICSU), 3:277 international multidisciplinary programs, 3:277 Scientific Committee on Oceanic Research (SCOR) see Scientific Committee on Oceanic Research (SCOR) sources of finance, 3:277 International Council for the Exploration of the Sea (ICES), 2:525, 3:122, 3:123, 3:275–276, 4:226–227, 4:284–285, 5:3 Annual Science Conference, 3:276 Code of Practice on Introductions and Transfers of Marine Organisms, 2:340, 2:341T History Symposium and publications, 3:276 membership, 3:276 oceanographic investigations, 3:275–276 peer-reviewed advice, 3:276
518
Index
International Council for the Exploration of the Sea (ICES) (continued) Secretariat databanks, 3:276 structure and operations, 3:276 International Council of Scientific Unions (ICSU), 3:277 International Court of Justice (ICJ), 3:442 Law of the Sea jurisdictions over boundaries, 3:435 UN Charter recognised by UNCLOS, 3:442 International Decade of Ocean Exploration, 1:488 International Geomagnetic Reference Field, 3:480–481 International Geophysical Year, 5:411 International Geosphere-Biosphere Program (IGBP), 3:277 International Indian Ocean Expedition, Red Sea circulation, 4:670–671 International Indian Ocean Experiment, 3:277–278 International Law of the Sea, 5:405 International Law of Treaty of the Sea, offshore drilling and oil spills, 4:749–750 International Marine Global Change Study (IMAGES), 4:301 International Maritime Organization (IMO), 5:405, 5:412 compensation for pollution, 5:405 offshore drilling and oil spills, 4:749–750, 4:751 port state control, 5:405 International North Pacific Commission (INPFC), 5:20 International Nusantara Stratification and Transport (INSTANT), 3:239, 5:316 International Ocean Institute, 3:665 International Oceanographic Commission (IOC), 1:302–303 International organizations, 3:274–279 see also individual organizations International Pacific Salmon Fisheries Commission (IPSFC), 5:21 International Satellite Cloud Climatology Project, 5:205 International Seabed Area deep seabed minerals, 3:438 defined, Law of the Sea jurisdiction, 3:435 International Seabed Authority ‘area’ defined, Law of the Sea jurisdiction, 3:435 payments, mineral resources, 3:437–438 International Ship Operators Meeting, 5:418 International trade, 5:401 deep-water trade route from Carthage, 3:699 maritime transportation, 5:408 routes shown by debris trails (archaeology), 3:699 shipping industry, 5:401 total cargo movements, 5:401
units, 5:401 ship size, 5:401 TEU (twenty-foot equivalent unit), 5:401 see also World seaborne trade International Tribunal of the Law of the Sea, 3:441–442 decisions are final and binding, 3:441 jurisdiction and types of claims, 3:441–442 specimen dispute, 3:442 International Union for Conservation of Nature (IUCN), ‘Red List’ categories for baleen whales, 1:285, 1:286T International Whaling Commission (IWC) moratorium on commercial whaling, 3:638 Scientific Committee, baleen whale population status, 1:285–286 Interocean gateways, see also Paleoceanography InterOcean S4 electromagnetic current meter, 5:429F, 5:430T Interplate fault, 6:129–131 fault plane parameters, 6:131, 6:131F seafloor displacement, 6:131 Interrogation Recording and Locating System (IRLS), 2:173 Intertidal fish(es), 3:280–285 classification, 3:280 feeding ecology and predation impact, 3:284 diet, 3:284 impact on prey abundance, 3:284 habitats, abundance and systematics, 3:280 abundances by habitat, 3:280 diversity/distribution, 3:280, 3:281T life histories and reproduction, 3:284–285 eggs, 3:284 larval development, 3:285 distribution of larvae, 3:285F life spans, 3:284 mating behavior, 3:284 parental care of eggs, 3:285 spawning, 3:284, 3:284–285 traits and adaptations, 3:280–281 behavior, 3:281–283 circatidal rhythms, 3:282–283, 3:283F homing, 3:282 intertidal movements, 3:282 locomotion, 3:281–282 movement, 3:282 resident/visitor differences, 3:282 thigmotaxis, 3:281–282 tidal synchronization, 3:282–283 combating intertidal stresses, 3:280 evolution, 3:280–281 morphology, 3:281, 3:281F physiology, 3:283–284 gas exchange, 3:283 respiration, 3:283–284 water loss, 3:283, 3:283F
(c) 2011 Elsevier Inc. All Rights Reserved.
see also Mangrove(s); Rocky shores; Salt marsh(es) and mud flats; Salt marsh vegetation; Sandy beach biology Intertidal habitats, biodiversity, 2:141 Intertropical Convergence Zone (ITCZ), 2:242, 2:560–561, 3:108–109, 4:121F, 6:165, 6:342 Atlantic Ocean, 1:721–723 El Nin˜o and, 2:242 El Nin˜o Southern Oscillation and, 2:230 North Atlantic winds, regional model case study, 4:729, 4:729F Peru-Chile Current system and, 4:387 salinity, 6:170 seasonal migration, 6:343 seasonal variations of winds and, 1:234F Intra-Americas Sea (IAS), 3:286–294 American Mediterranean, 3:286 bottom topography, 3:287, 3:288F current flow, 3:291 storm surges, 3:293 currents, 3:292–294 atmospheric forcing, 3:287 Ekman transport and pumping, 3:293–294 inertial, 3:293 longshore, 3:293 rip, 3:293 storm surge, 3:293 subsurface, 3:291–292 Deep Western Boundary Current (DWBC), 3:292 inflows, 3:291–292 level-of-no-motion, 3:291 outflows, 3:291–292 T-S characteristics, 3:292 ventilation, 3:292 surface see below tidal, 3:292–293 tsunami, 3:294 upwelling, 3:293–294 von Karman vortices, 3:292F, 3:293 geography, 3:286, 3:286F geology, 3:287 Gulf Stream System formation, 3:293F, 3:294 indigenous peoples, 3:287 inflows, 3:291–292 meteorology, 3:287 climate classifications, 3:287 ENSO, 3:287 hurricanes, 3:287, 3:293 Trade Winds, 3:287, 3:293–294 Panama-Columbia Bight, 3:288 riverine systems, 3:290–291 Amazon River, 3:288 Magdalena River, 3:288, 3:293F Mississippi River, 3:290–291, 3:292–293, 3:293F Orinoco River, 3:288, 3:293F salt balance, 3:290 sea surface heights, 3:290F, 3:293F sea surface temperatures, 3:293–294 sills, 3:287, 3:291–292
Index surface currents, 3:287–291, 3:294 Amazon River water, 3:288 Antilles Current, 3:291, 3:293F biota transport, 3:288, 3:289F Caribbean Current, 3:288, 3:288–289, 3:293F current rings see Current rings Florida Current see Florida Current Guiana Current, 3:288, 3:293F Gulf Loop Current (GLC) see Gulf Loop Current (GLC) Gulf Stream System see Florida Current North Brazil Current retroflection, 3:288 North Equatorial Current, 3:293F Orinoco River water, 3:288 Panama-Columbia Gyre (PCG), 3:288, 3:293F sediment transport, 3:288, 3:289F Yucatan Current, 3:288–289, 3:293F see also Gulf Stream; Labrador Current (LC) tsunami, 3:287, 3:294 see also Brazil and Falklands (Malvinas) Currents; Sphenisciformes; Storm surges; Tide(s) Intraplate volcanism see Seamounts and off-ridge volcanism Intraslope basin, 5:448F Introductions, of species see Exotic species introductions Intrusions, 2:168, 3:295–299, 4:59 Arctic Ocean, 1:221 cross-frontal fluxes, 3:297–298, 3:298–299 double-diffusive mixing, 3:295–297, 3:296F, 3:298 frontal regions, 3:295, 3:295F interleaving layers, 3:295–297, 3:296F North Atlantic Current, 2:169F North Atlantic Front, 5:353–354 observational studies, 3:297–298 salt-fingering interface, 3:295–297, 3:296F theoretical studies, 3:298–299 Inuits, chlorinated hydrocarbons, 1:561 Inundation maps, 6:139 Indonesia, 6:136F Newport, Oregon, 6:139F tsunamis, 6:133 Invasive species see Non-native species Inverse barometer effect, storm surges, 5:531 Inverse catenary moorings, 3:924–925, 3:924F, 3:925T Inverse grading, 5:463 Inverse methods, 3:312–318 advection/diffusion/decay equation example, 3:312 application in oceanography, 3:315–316, 3:316F background to, 3:312 definition, 3:312 difficulties and misconceptions, 3:317 example, 3:313–314
first use in oceanography, 3:312 ‘forward solution’ vs, 3:312 functional analysis method (Backus and Gilbert), 3:312, 3:312–313, 3:316–317 inverse model use with, 3:312 least-squares solution, 3:313, 3:314, 3:314F by singular value decomposition (SVD), 3:315, 3:316 mathematical usage, 3:312 noise component, 3:312, 3:313 solution methods, 3:314–315 extensions to, 3:316 Gauss–Markov method, 3:314–315, 3:314F, 3:316 hydrographic example, 3:315–316, 3:316F time-dependent problems, 3:316–317 tracer budgets, 2:290–291 see also Inverse models/modeling Inverse models/modeling, 3:300–311, 3:312–318, 4:93, 4:103 absolute velocities and nutrient fluxes, 3:302–304 adjoint method, 3:304–305 advantages, 3:302 basic concepts, 3:302 carbon cycle, 4:110 carbon export fluxes by adjoint method, 3:304–310 comparison with measurements, 3:306 difficulties and misconceptions, 3:317 error analysis, 3:310 error sources, 3:302 optimization, 3:306, 3:307–310, 3:307F particulate organic carbon (POC), 3:309F, 3:310 radiocarbon, 3:307–310, 3:308F reference-level velocity, hydrographic sections, 3:316, 3:316F section inverse approach, 3:302–304 time-dependent problems, 3:316–317 tomography see Tomography tracer fluxes, 3:303–304 see also Inverse methods Inverse theory, background to, 3:312 Inversions, 6:223F horizontal advection and, 6:223–224 intermediate nepheloid layers and, 4:8, 4:16–17 seasonal heating and, 6:222–223 Invertebrates hypoxia, 3:177, 3:178F lagoons, 3:386, 3:386–387 salt marshes and mud flats, 5:44 species diversity, 2:140 stock enhancement/ocean ranching programs, 4:147T, 4:151–152, 4:152F see also specific invertebrates Investigations at sea, history, 3:121–122 Investigator (survey vessel 1801), 3:445 IOC (International Oceanographic Commission), 1:302–303
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519
Iodine (I), cosmogenic isotopes, 1:679T Iodine-129 (129I), nuclear fuel reprocessing, 4:82, 4:84T, 4:85 IODP see Integrated Ocean Drilling Program (IODP) IODP Site 302, 4:322F Ion-exchange beads, 3:897 Ionian anticyclones (IA), 1:748–751, 1:748F Ionian Shelfbreak Vortex (ISV), 2:5 Ionic conductivity see Conductivity (sea water) Ionic equilibrium, 2:216 Ionosphere activity, 5:131 Ion-selective electrodes (ISE), 6:104, 6:104T IOP see Inherent optical properties (IOPs) IP see Inertial period IPNV (infectious pancreatic necrosis virus), mariculture disease, 3:519, 3:520T, 3:521, 3:523 IPSFC (International Pacific Salmon Fisheries Commission), 5:21 IRD see Ice-rafted detritus (IRD) Iribarren number, 6:312, 6:314–315, 6:316–317 Iridium (Ir), 4:494 concentrations deep earth, 4:494T N. Atlantic and N. Pacific waters, 6:101T sea water, 4:494T, 4:497 vertical profiles, 4:497, 4:499F see also Platinum group elements (PGEs) Irish Sea storm surge modeling, 5:538 tidal dissipation, 3:255 IRLS (Interrogation Recording and Location System), 2:173 Irminger Current (IC), 1:724 transport, 1:724T see also Atlantic Ocean current systems Iron (Fe) atmospheric deposition, 1:252–254, 1:254T availability, dinitrogen (N2) fixation and, 3:340, 4:35 biological uptake, phytoplankton, 6:80–81 chemical speciation in seawater, 6:79 coastal waters, 6:76 concentration N. Atlantic and N. Pacific waters, 6:101T phytoplankton, 6:76T seawater, 3:334, 6:76, 6:76T, 6:79 vertical distribution in seawater, 3:334, 3:335F cosmogenic isotopes, 1:679T crustal abundance, 4:688T cycle, 6:227 cycling, 4:567F estuarine sediments, 1:546–547, 1:547F sediments, 4:566–567, 4:567F
520
Index
Iron (Fe) (continued) depth profiles, estuarine sediments, 1:544F, 1:545F dissolved, 4:694–695 depth profile, 4:696F properties in seawater, 4:688T effect on N:p ratio, 4:588 effect on primary production, 4:573–574 in ferromanganese deposits, 1:259–260 manganese and, 1:262F fertilization see Iron fertilization inorganic speciation, 6:103 ligands, biogenic, 6:84 in limitation of phytoplankton growth, 3:333–334, 3:333F, 3:334, 3:335 metabolic roles, 6:82 nitrogen fixation and, 6:75 organic complexes, 6:105 oxidation, 1:545 particle flux variability, 6:1–2 particulate scavenging, 4:685 photochemical reaction, effects of, 4:420 phytoplankton, 1:124 precipitation, 3:334 primary production and, 4:89–90 redox chemistry in seawater, 6:79 reduction, 1:543–545 reduction of oxides, 1:545–546 requirement for primary productivity, 4:586, 4:588 riverine flux, 1:254T role, 3:331, 3:334–335 sediment oxidation processes, 1:543 see also Trace element(s) Iron enrichment studies, 6:91–92, 6:92 sulfur hexafluoride marking, 6:91 IRONEX experiments, 3:335, 3:336F, 3:337–338, 3:339, 3:340, 4:588, 6:87 definition, 4:588 results, 6:91, 6:91F see also Iron fertilization Iron fertilization, 3:331–342, 3:331, 3:335 carbon cycle and, 3:331, 3:339–340, 3:339F, 3:340, 3:340F experimental measurements, 3:336–337 experimental strategy, 3:335 fluorometry, 3:336 form of iron, 3:335, 3:336F inert tracer, 3:335–336, 3:336F Lagrangian point of reference, 3:336 remote sensing, 3:336 shipboard iron analysis, 3:336 findings to date, 3:337 biophysical response, 3:337 carbon flux, 3:339–340, 3:339F, 3:340F growth response, 3:337–338, 3:338F heterotrophic community, 3:331–332 nitrate uptake, 3:337 nutrient uptake ratios, 3:338, 3:338F organic ligands, 3:338–339 questions remaining, 3:340 societal challenge, 3:340–341
see also Nitrogen cycle; Phosphorus cycle Iron-limitation hypothesis, 1:124 Iron oxides, subterranean estuaries, 3:96 Iron–phosphorus–oxygen coupling, 4:411–412, 4:412 see also Phosphorus cycle Iron sulfate, 1:543–544 ‘Iron theory’, 3:333–334, 3:333F Irradiance, 3:244–253 angular distribution, 5:115 definition, 3:246–247 downwelling, 1:391–393, 3:246–247 measurements, 3:246–247, 3:247–248, 4:620–621 scalar, 3:246–247 solar spectrum, 5:116F upwelling, 1:391, 3:246–247 see also Infrared (IR) radiometers; Ocean color; Ocean optics; Radiative transfer Irradiance reflectance, 3:246–247 bio-optical modeling, 1:393–394, 1:393F definition, 1:391–392, 4:623 Irrawaddy dissolved loads, 4:759T sediment load/yield, 4:757T Irrawaddy dolphin (Orcaella brevirostris), 2:156, 2:157 Irrigation bioturbation and, 4:568–570 pore water profile, 4:568–570, 4:569F Is, definition, 6:242 Isaacs–Kidd midwater trawl (IKMT), 6:355 ISAV (infectious salmon anemia virus), mariculture disease, 3:520T, 3:521 ISCCP (International Satellite Cloud Climatology Project), 5:205 ISE (ion-selective electrode), 6:104, 6:104T Iselin, Columbus, 2:266–269 Isis, 6:260T Isitani, D, 5:345 Island arcs, 3:33 Island chains, 5:300–301 off-ridge plume related volcanism, 5:292, 5:296, 5:298F ‘Island mass effect’, 3:343 Islands coastal trapped waves, 1:592–593 continental margins, 4:257–258 magnetic anomalies, 3:486–487 see also specific islands Island wake(s), 3:343–348 eddies, 3:345 observations, 3:344–348 parameter, 3:344, 6:60 theory, 3:343–344 bottom friction, effect of, 3:344 nonrotating case, 3:343–344 rotation, effect of, 3:344 see also specific islands Island Wake of Tobi, topographic eddies, 6:57, 6:57F
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Island wake parameter, 3:344, 6:60 Isobaths, bathymetry, 1:297 Isolated seamounts, 5:292, 5:294, 5:300 Vesteris, 5:300, 5:303F Isoprenoids, radiocarbon analysis, 5:426 Isopycnal coordinate systems, 5:139 Isopycnal flow ‘downward’, 2:128 Isopycnal mixing, tritium-helium-3 tracing and, 6:94–95 Isopycnal models, overflows and, 4:270 Isopycnals (density isolines), 3:703, 3:708, 4:128, 4:129, 4:130F definition, 4:120–121 vortical modes, 6:286F, 6:287–288 Isosmotic conditions, 2:216 Isostasy, dynamic height calculation, 6:347–349 Isostatic basal melt rate, 3:201 Isostatic compensation, 3:85 Isotopes argon see Argon beryllium see Beryllium carbon see Carbon (C); Carbon isotope ratios; Carbon isotope ratios (d13C); Radiocarbon cosmogenic see Cosmogenic isotopes fractionation, 4:40, 4:45F helium see Helium lead see Lead (Pb) nitrogen, 4:32 see also Nitrogen isotope ratios oxygen see Oxygen isotope ratio (d18O) phosphorus see Phosphorus (P) strontium see Strontium see also individual isotopes Isotope tracers, long-term, 3:456T Isotopic budget equation, 1:521 Isotopic ratios in carbon cycle models, 1:518F, 1:521–522 in coral-based paleoclimate research, 4:339–340, 4:339T see also specific isotope ratios Isotropic points, ice shelf stability, 3:215 Isotropic turbulence see Stationary, homogeneous, isotropic turbulence Israel, water, microbiological quality, 6:272T ISSAMS (in situ Sediment Acoustic Measurement System), 1:82, 1:82F Isthmus of Panama, paleoceanography climate models in, 4:305 passage closure, 1:512, 4:304F, 4:305 climate and, 4:304–305 passage opening, closed Drake Passage and, 4:305–306, 4:306F Istiophoridae see Billfishes (Istiophotidae) Istiophorous albicans (larger sailfish), 2:377 Istiophorus platypterus (sailfish), utilization, 4:240 ISW (ice shelf water), 5:544–545 Italy aquaculture markets, 3:535 markets, sea bass, 3:535
Index ITCZ see Intertropical convergence zone (ITCZ) ITE (Individual Transferable Effort), fishery management, 2:518 ITQ (Individual Transferable Quota) system, fishery management, 1:706, 2:517, 2:520, 2:525, 2:526 ITW see Indonesian Throughflow Water (ITW) IUCN (International Union for Conservation of Nature), ‘Red List’ categories for baleen whales, 1:285 IUW see Indonesian Upper Water (IUW) Iw, definition, 6:242 IWEX see Internal Wave Experiment (IWEX) IWV (integrated water vapor), 5:206–207 Izu Ridge, Kuroshio Current, 3:360–362, 3:362F
J J (sedimentation rate), definition, 6:242 Jaguar/Puma, 6:263T Jamaica, coral reef systems, regime shifts, 4:702 James, USA, river discharge, 4:755T JAMSTEC see Japan Marine Science and Technology Center (JAMSTEC) JAMSTEC-ORI ocean bottom seismometer, 5:368T, 5:369 Jan Mayen Current, 5:146 sea ice cover and, 5:141 Japan anthropogenic reactive nitrogen, 1:245T artificial reefs, 1:227, 1:227F mariculture, bluefin tuna, 4:241 Pacific salmon fisheries, 5:12 catch, 5:14F, 5:15F, 5:17F, 5:19F, 5:20F, 5:21F international management issues, 5:19–20 sashimi market, 4:239, 4:240, 4:241 stock enhancement/ocean ranching, 2:528–530, 4:146, 5:19 salmonids, 4:147–148, 4:154, 4:154F subduction zones, geophysical heat flow, 3:47 tsunami (1993), 6:128–129 tsunami early warning system, 6:138–139 water, microbiological quality, 6:272T Japanese amberjack (Seriola quinqueradiata), 3:539 Japanese ayu (Plecoglossus altivelis), 2:404 Japanese cupped oyster (Crassostrea gigas) mariculture environmental impact, 3:908 production systems, 3:534 stock acquisition, 3:532 see also Pacific oyster (Crassostrea gigas)
Japanese flounder (Paralichthys olivaceus), 2:334 stock enhancement/ocean ranching programs, 4:147T, 4:149 albinism-related mortality, 4:149, 4:149F catch impact, 4:149, 4:149F Japanese kelp (Laminaria japonica), 3:538, 5:319–321 Japanese Marine Observation satellites, 5:81–82 Japanese National Space Development Agency, 5:82 Japanese sardine see Engraulis japonicus (Japanese sardine) Japanese scallop (Patinopecten yessoensis), stock enhancement/ ocean ranching programs, 2:528–530, 4:147T, 4:151, 4:152F Japan Marine Science and Technology Center (JAMSTEC), 6:300 autonomous underwater vehicles, 6:263T deep-towed vehicles, 6:256T human-operated vehicles (HOV), 6:257T remotely-operated vehicles (ROV), 6:260T Japan Sea monsoons historical variability, 3:915 indicators, 3:914 long-term evolution of, 3:917 Okhotsk Sea and, 4:201, 4:203, 4:204 sea ice cover, interannual trend, 5:146 Jason-1 satellite, 5:75, 6:134, 6:135F measurements compared with models, 6:136F Jason II, 6:260T, 6:261F, 6:262F Jason and the Argonauts, 5:409 Jason/Medea ROV, 4:746T Jason remotely operated vessel (ROV), deep submergence studies, 2:22–23, 2:24F, 2:25F, 2:27F, 2:30–33, 2:33F Jasper seamount, off-ridge non-plume related volcanism, 5:300, 5:302F Jasus (lobster) chlorobiphenyl congeners, 1:557–558 fisheries, 1:702 management techniques, 1:706 see also Crustacean fisheries see also specific species Java-Australia Dynamics Experiment (JADE), 5:316 JCOMM (Joint Technical Commission for Oceanography and Marine Meteorology), 5:74 Jeffreys wave growth theory, 6:305 Jellyfish see Cnidarians; Ctenophores Jerlov water types, 4:382T, 4:383 JERS-1 satellite, 5:103 Jet droplets, 6:333–334 Jets coastal, Baltic Sea circulation, 1:292, 1:292–293 mesoscale see Mesoscale jets
(c) 2011 Elsevier Inc. All Rights Reserved.
521
Jet stream flow patterns El Nin˜o event 1996-1997, 2:236F El Nin˜o Southern Oscillation and, 2:235 Jetties see Groins/jetties J-flux, radiocarbon levels and, 1:686 JGOFS see Joint Global Ocean Flux Study (JGOFS) Jiangxia tidal power plant, 6:27, 6:28T Johnson, Douglas, 3:34, 3:34F Johnson-Sea-Link, 3:515, 3:516 corrosion immunity, 3:516 diver operations, 3:516 multi-science dives, 3:517 search and recovery operation, 3:517 state of the art vehicles, 3:516–517 thicker plexiglas, 3:515, 3:516, 3:516F unique features, 3:516 Johnson Sea-Link submersibles, 6:257T JOIDES (Joint Oceanographic Institutions for Deep Earth Sampling), 2:45 JOIDES Resolution, R/V, 4:301 deep-sea drilling, 2:46, 2:47F, 2:51, 2:51T facts, 2:39T Joint Global Ocean Flux Study (JGOFS), 1:686, 3:278 marine mats, 3:653 Joint North Sea Wave Observation Project (JONSWAP), 4:778, 4:778F Joint Oceanographic Institutions for Deep Earth Sampling (JOIDES), 2:45 Joint Oceanographic Institutions Incorporated (JOI), 5:70 Ocean Drilling Project (ODP), 2:52–53 Joint Panel on Oceanographic Tables and Standards, seawater equation of state, 6:379 Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), 5:74 Journals, marine policy, 3:665 Juan de Fuca Ridge clay minerals formation, 1:566 profile, 1:566F CoAxial Segment, 3:845 diffuse flow, 1:72F, 1:73F earthquakes, 3:844F, 3:845, 3:848F Endeavour Segment, hydrothermal vent deposits, 3:146 geophysical heat flow, 3:45F hydrothermal plume, 2:130–131, 2:132F megaplume observations, 2:133–134, 2:136F salinity profile, 2:132, 2:133F temperature profile, 2:132, 2:133F hydrothermal vent fluids, chemistry of off-axis vents, 3:168–169 volcanic events, influence of, 3:168 magnetic anomalies, 3:483F MORB composition, 3:823F near-ridge seamounts, 5:294, 5:296
522
Index
Juan de Fuca Ridge (continued) seismic structure axial magma chamber (AMC), 3:830, 3:834F, 3:835F layer 2A, 3:828–829, 3:834F volcanic helium, 6:280, 6:281F Juan Fernandez microplate, 4:601, 4:602F, 4:604F deformed core, 4:601, 4:603 Endeavor Deep, 4:602, 4:602F evolution, 4:602–603, 4:603 geometry, 4:602, 4:603 rotation velocity, 4:602–603 Juday net, 6:355, 6:356F Juncus roemerianus, 4:254 Junge distribution, 1:386 Jungfern-Anegada Passage, 3:286F, 3:287 Jurisdictions, affected by Law of the Sea see Law of the Sea
K K, definition, 6:242 k1, definition, 6:242 k-1, definition, 6:242 k2, definition, 6:242 k-2, definition, 6:242 Kaiko (Japanese ROV), 3:508, 4:746T Kaiko 7000, 6:260T, 6:261F Kaimei wave energy conversion system, 6:300F, 6:301F Kalina cycle, 4:169 Kalix River, uranium, 6:245 Kalman filter, 2:7 Kalman smoother, 2:7 Kanon der Erdbestrahlung, 4:505, 4:510F ‘Kansas’ experiment, 2:324 Kara Sea, 1:211 radioactive wastes, disposal, 4:629 sea ice cover, interannual trend, 5:144–146 sub-sea permafrost, 5:566 Karenis brevis dinoflagellate, 3:557–558, 3:558F Karimata Strait, 5:314F Von Karman constant see Von Karman constant Kashevarov Bank, 4:200F, 4:201, 4:201F, 4:203, 4:206 polynyas, 4:540 see also Okhotsk Sea Katsuobushi, tuna utilization, 4:240 Katsuwonus pelamis see Skipjack tuna (Katsuwonus pelamis) Kattegat Baltic Sea circulation, 1:288, 1:289, 1:289F, 1:290F, 1:294 salinity, 1:289, 1:290F Kattegat front, 1:295 Katzev, Michael, Kyrenia wreck raised by, 3:697 Kaula report, 5:66–67
Kd, definition, 6:242 K-dominance curves, pollution, effects on marine communities, 4:535, 4:536F Keels definition, 3:190 of pressure ridges, 3:191–193, 3:193 Kelp(s), 2:142 as habitat, 2:142 Japanese, 3:538, 5:319–321 Macrocystis pyrifera, use of artificial reefs, 1:228 species, 2:142 see also Macrocystis (giant kelps); Phytobenthos Kelp forests, 5:199F sea otters and, 3:625, 5:198–199 Kelvin–Helmholtz instability (KHI), 4:224, 6:189, 6:211 Kelvin–Helmholtz shear instabilities, 2:579 differential diffusion and, 2:117, 2:118F mixed layer base, 6:341 modeling, 4:732, 4:733F see also Shear instability Kelvin–Helmholtz wave analysis, 6:304–305 Kelvin waves, 1:591, 1:592, 2:271, 2:276F, 2:282F, 6:36–37 atmospheric pressure forcing, 1:596 boundary reflection, 2:278–279 delayed oscillator ENSO model and, 2:282 dispersion, 1:593F double, 1:593 energy transmission, 1:596 Indonesian Throughflow, 3:242 internal, 1:593, 1:593–594, 1:595, 1:596, 1:597 latitudinal variation, 1:596 observations, 2:284–285, 2:284F reflected, 6:37, 6:37F, 6:38 steepening, 1:595 storm surges, 5:532 stratification, 1:593–594 tides, 1:596–597, 6:37 transit time, 2:273 wave dynamics, 2:274–275 wave phase speed, 2:275 wave speeds, 1:592 Kelvin wave solution, 2:275 KEM see Mean kinetic energy (KEM) Kemp’s ridley turtle (Lepidochelys kempii), 5:217–218, 5:217F see also Sea turtles Kennedy, R M, acoustic noise, 1:59, 1:59F Kennett, James, 1:506–507 Kent, D V, geomagnetic polarity timescale development, 3:29F, 3:30 K-[epsilon] models, 4:210 Kerguelen-Heard Plateau, seismic structure, 5:365 Kermadec Arc, volcanic helium, 6:282F, 6:283
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Kerman, B R, 1:59 Kewley, D J, 1:59 Keystone predators, rocky shores, 4:764 K-Gill anemometer, 5:385–386, 5:385F KHI (Kelvin–Helmholtz instability), 4:224, 6:189, 6:211 Killer whale (Orcinus orca), 2:153F distribution, 2:156, 3:599 dorsal fin, 2:153 effects of anthropogenic noise, 3:628 exploitation, 3:640–642, 3:641F feeding behaviors, 2:157, 2:158 group recognition calls, 3:620–621, 3:621F home ranges, 3:599 migration and movement patterns, 3:599 prey movements and, 3:599 predation by sperm whales, 3:617 resident form, 3:599 sexual dimorphism, 2:149 social interactions, 2:158–159 teeth, 2:149–153 transient form, 3:599 see also Odontocetes (toothed whales) Killifish (Fundulus heteroclitus), 2:371 Kilopascal, 1:356 Kinetic energy (KE), 6:26–27 budget, 2:262 advection, 2:263 meddies, 3:706–707 Kinetic energy/unit volume (current flow), definition, 4:117 Kinetic isotope effect, nitrogen, 4:40 King penguin (Aptenodytes patagonicus), 5:522T, 5:526, 5:526F see also Aptenodytes King salmon (Oncorhynchus tshawytscha), 2:392F Kirchoff approximation, marine organisms, 1:66 Kislaya Guba tidal power plant, 6:27, 6:28T ‘KISS’ model, small-scale patchiness, 5:476 Kitefin shark (Dalatias licha) open ocean demersal fisheries, FAO statistical areas, 4:231T, 4:232 over-exploitation vulnerability, 4:232 Kittiwake (Rissa tridactyla), 3:423F Bering Sea, 5:263 breeding success, 5:255 time-series, 1:633–634, 1:635F see also Laridae (gulls) Kitty Hawk, North Carolina, USA, coastal erosion, 1:581–582 Kleptoparasitism, in seabird foraging, 5:230, 5:233, 5:255 Knight Inlet, British Columbia, 2:576, 2:576F internal waves, 3:267F Knipovich spectacles, 1:218F, 1:404–407, 1:407F Knudsen formula, 2:249 Knudsen Sea State, 1:98
Index Kogiidae (dwarf and pygmy sperm whales) trophic level, 3:623F see also Odontocetes (toothed whales); Sperm whales (Physeteriidae and Kogiidae) Kohout cycle, 5:553 Kolgomerov inertial subrange hypothesis, 1:433 Kolmogoroff microscale, 5:476 Kolmogoroff scale, 6:211 Kolmogorov, A N, 6:20, 6:24 Kolmogorov hypothesis, for wavenumbers, 2:616 Kolmogorov length, 5:133 Kolmogorov length scale, 2:617 fossil turbulence, 2:612 Kolmogorov scale, 6:23–24 Komsomolets, radioactive wastes, 4:633, 4:634–635 Korea, artificial reefs, 1:227–228 Kosi Lakes, South Africa, 3:379, 3:380F K-profile parametrization, 4:209–210 hurricane modeling, 6:198–199 Kraus-Turner turbulence balance modeling, 6:198–199 Krill (Euphausiacea), 3:349–357, 3:350F, 4:1, 4:3F, 4:460 acoustic scattering, 1:67–68 age determination techniques, 3:351–352 aggregations, 3:354, 3:354–355, 3:354F biological influences, 3:354 densities, 3:354–355 percentage of regional biomass, 3:355 physical influences, 3:354–355 in baleen whale diet, 1:281 bioluminescence, 1:380 definition, 1:287 distribution, ENSO events, 5:519 distribution patterns, 4:360, 4:361–362 diversity, 3:349 evolutionary development, 3:349 fisheries, 3:349, 3:356–357 management, 3:356 recent catch levels, 3:356 fluoride concentrations, 5:515 general characteristics, 3:349 growth, development and physiology, 3:354–355 Euphausia crystallorophias, 3:353 Euphausia pacifica, 3:353 Euphausia superba, 3:352 food sources, 3:353 habitat-dependent strategies, 3:351–352 latitude-dependent strategies, 3:354 life spans, 3:352 lipid utilization, 3:353 Meganyctiphanes norvegica, 3:353 potential for rapid growth, 3:353 sex-related differences, 3:353 Thysanoessa inermis, 3:352–353, 3:353 Thysanoessa macrura, 3:353
Thysanoessa raschii, 3:352–353 winter survival, 3:353 influence of ocean currents, 3:349 see also Antarctic Circumpolar Current place in food webs, 3:349 role in food web, 3:355 food consumption, 3:355–356 feeding strategies, 3:355 food sources, 3:355 nutrient cycling, 3:355 see also Copepod(s) predators, 3:356 baleen whales, 3:355 fishes, 3:355–356 impact of krill distribution patterns, 3:356 seabirds, 3:356 seals, 3:355 in seal diet, 5:290 Southern Ocean fisheries, 5:513, 5:513–514 harvesting methods, 5:515 production, 5:515, 5:516T surplus, 2:510–511 spatial distribution, 3:355 aggregations see Krill (Euphausiacea), aggregations diurnal vertical migration, 3:354, 3:355 dynamism, 3:355 species separation and distribution, 3:349–351, 3:351F aggregations, 3:355 Arctic Ocean, 3:351 Atlantic and Pacific Oceans, 3:350–351 northern limits, 3:351 distribution in water column, 3:350 diurnal vertical migration, 3:351, 3:355 effect of ocean currents, 3:350 evolutionary separation, 3:349–350 Indian Ocean, 3:350 latitudinal distribution, 3:350 Southern Ocean, 3:350, 3:352F variability, 3:356–357 competition with salps, 3:356 impact of ocean currents, 3:356 impact of physical environment, 3:356 importance of sea ice, 3:356 see also Sea ice indicator species for climate change, 3:356–357 see also Fiordic ecosystems; specific species Krill Yield Model (KYM) formula, 5:518 Southern Ocean fisheries management regime, 5:518 Kruzenshtern Strait, 4:200F, 4:201 see also Straits Krypton cosmogenic isotopes, 1:679T oceanic sources, 1:680T production rates, 1:680T
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523
reservoir concentrations, 1:681, 1:681T specific radioactivity, 1:682T tracer applications, 1:683T diffusion coefficients in water, 1:147T Schmidt number, 1:149T Krypton hygrometers, 5:388 Kryptopterus bicirrhis (glass catfish), 2:451F, 2:456F Kstratification, internal tides, 3:257 K/T boundary see Cretaceous/Tertiary boundary Kubelka-Munk function, 1:8 Kumukahi, acrylic plastic sphere, 3:515 Kuril Basin, 4:200F, 4:201, 4:203, 4:206 see also Okhotsk Sea Kuril-Japan trench, 4:17 Kuroshio (submersible observation chamber), 3:687, 3:687F Kuroshio Current, 3:358, 3:358–360, 3:359F, 5:312–313 ‘blackness’, 3:358 catch, anchovy and sardine, 4:701F downstream extension region see Kuroshio Extension flow, 4:287F frontal position, satellite remote sensing of SST, 5:99 origins, 3:358 region south of Japan, 3:360–363 bimodal path variability, 3:358, 3:362, 3:362F future studies, 3:363 proposed mechanisms, 3:363 Izu Ridge, 3:362F path index, 3:362 time-series, 3:362, 3:363F Shikoku Basin, 3:360–362 region upstream of Tokra Strait, 3:358–360 East China Sea see East China Sea impinging eddies, 3:359, 3:361F Luzon Strait loop current, 3:358–359, 3:360F volume transport, 3:358 seasonal cycles, 3:358 sea surface temperature anomalies and, 3:368–369, 3:368F seismic reflection water-column profiling, 5:354, 5:355F western boundary current, heat transport, 3:117 World Ocean Circulation Experiment (WOCE) observational program, 3:369 see also Abyssal currents; East China Sea; Okhotsk Sea, circulation; Pacific Ocean equatorial currents; Wind-driven circulation Kuroshio Extension, 3:359F, 3:363–365 eddy variability, 3:361F, 3:364 front, seismic reflection profiling, 5:356F interannual variability, 3:364–365, 3:366F mean temperature map at 300m depth, 3:363, 3:364F
524
Index
Kuroshio Extension (continued) potential vorticity anomalies and, 3:364 quasi-stationary meanders, 3:363 recirculation gyre, 3:364, 3:365F volume transport, 3:364 Shatsky Rise bifurcation, 3:364 Subarctic Current and, 3:364 Kuroshio-Oyashio Extension, 4:713–714 Kursk, radioactive content, 4:633 Kuruma prawn see Penaeus japonicus (kuruma prawn) Kw ocean model, 1:686 KYM see Krill Yield Model (KYM) Kyoto Protocol, sulfur hexafluoride and, 6:87
L L1 ligand (copper), 6:105F LAA (large amorphous aggregates) camera, 6:368 Laboratories air–sea gas exchange studies, 1:153 equipment see see specific equipment/ instruments oceanographic research vessels, 5:412 heating, ventilation and air conditioning, 5:412 Laboratory experiments non-rotating gravity currents, 4:59–60, 4:60, 4:60F, 4:61F, 4:63F open ocean convection, 4:219, 4:221 seafloor sediments see Sediment core samples Laboratory turbulence studies, 3:371–376 continuous stratification, 3:374–376, 3:375F, 3:376F mixing efficiencies, 3:375F dynamics parameters, 3:372 eddies, 3:371–372 entrainment velocity, 3:372–373, 3:373F, 3:374F experiment types, 3:371–374 flow generation, 3:372 fluids, 3:372 gravity currents, 3:374 turbulence generation, 3:372 see also Wave tank experiments Labrador Current (LC), 2:554, 2:561–562, 4:122, 4:793, 5:353–354 formation, 2:561–562 generating forces, 2:555–556 Labrador Current Water, 2:562 path, 2:561–562 salinity gradients, 2:562 sea ice cover and, 5:141 subpolar gyre, 2:561–562, 2:562F temperature gradients, 2:562 transport, 1:724T see also Atlantic Ocean current systems; Florida Current, Gulf Stream and Labrador Currents Labrador Current Water, 2:562
Labrador Sea, 4:127 circulation, global warming and, 1:5 deep convection, 2:13, 2:14F boundary currents, 2:21 float measurements, 2:16 restratification, 2:17–18, 2:19, 2:19F, 2:20F temperature variance, 2:16–17, 2:17F iceberg size categories, 3:185T ice-induced gouging, 3:195 neodymium supply, 3:463 North Atlantic Oscillation, 4:70 salinity distribution, 2:13–15, 2:14F variance, 2:17, 2:18F Seaglider mission, 3:65F sea ice, 5:171 North Atlantic Oscillation and, 4:70 tomography, 6:49 trace metal isotope ratios, 3:457 Labrador Sea Water, 1:725–726, 2:13–15, 2:14F flow rate, 2:15 generation, interannual variability, 1:22F, 1:25 outward transport, 2:20, 2:21 volume variation, 2:19 Labridae (wrasses), 1:656, 1:657, 2:395–396F Labroides (wrasse), 2:377 Labroides dimidiatus (cleaner wrasse), aquarium mariculture, 3:528 Lack, David, 5:249, 5:251, 5:252 Lagenodelphis hose (Fraser’s dolphin) myoglobin concentration, 3:584T see also Oceanic dolphins Lagoon(s), 3:377–388 biota and ecology, 3:382–387 birds and invertebrates, 3:386 estuarine environment similarities, 3:382–384 fish yields, 3:386, 3:386T food web, 3:385F human threats, 3:387, 3:387T invertebrate yields, 3:386–387 nursery and feeding grounds, 3:386 primary production, 3:384 species categories, 3:386 zonation, 3:386 definition, 3:377 environment (lagoonal), 3:381–382 connectivity to sea, 3:381 formation, 3:378–381 bahira lagoons, 3:381 estuarine lagoons, 3:379–380, 3:382F human impacts, 3:380–381 influence of sea level, 3:378 longevity of lagoons, 3:381, 3:383F longshore movement of sediment, 3:380 river delta lagoons, 3:379 sequence barrier next to/against mainland, 3:379–380
(c) 2011 Elsevier Inc. All Rights Reserved.
landward movement, 3:378–379 offshore barrier, 3:378, 3:381F types/characteristics, 3:377–378 atoll lagoons, 3:377–378 choked lagoons, 3:381F, 3:382, 3:384F, 3:385F closed lagoons, 3:379F, 3:382 coastal lagoons, 3:377 distribution, 3:377, 3:378F, 3:378T formation factors, 3:377, 3:379F salinity, 3:377 leaky lagoons, 3:381, 3:381F, 3:384F restricted lagoons, 3:382, 3:384F see also Mangrove(s); Salt marsh(es) and mud flats Lagrange, Joseph, 3:389 Lagrange constrained model optimization, 3:306–307, 3:307F Lagrangian biological models, 3:389–393 Eularian vs. Lagrangian formulations, 3:389, 3:389–391, 3:390–391F, 3:393 fluid dynamics, 5:136 see also Fluid parcels marine ecosystem see Individual-based models (IBMs) simple, 3:391, 3:392F, 3:393 simulations of populations with demographic structure, 3:391–393, 3:393 example, 3:392–393, 3:392F historical parameters, 3:391–392 Hoffman et al, 3:391–392 Wolf and Woods, 3:391–392 see also Population dynamic models Lagrangian flow, ocean circulation, 4:115–116, 4:116F, 4:117 Lake(s) ferromanganese oxide deposits, 3:488T gas exchange experiments, 6:89 seiches see Seiches Lake, Simon, Argonaut I, 3:513 Lake George Langmuir circulation, 3:408 wave growth experiment, 6:307 Lake Ontario, water-air momentum transfer, 6:308 Lake St Lucia lagoon, South Africa, 3:379, 3:380F Laki, 3:224–225 l, definition, 6:242 l (decay constant), definition, 4:651 l230, definition, 6:242 l231, definition, 6:242 Lambert’s scattering law, 1:106 Lamb wave, 5:138 Laminar flow, 5:455–456 Laminaria hyperborea algae, 4:430–431 Laminaria japonica (Japanese kelp), 3:538, 5:319–321 mariculture, 5:319F Laminaria saccarina, acoustic scattering, 1:69 Lamna ditropis (salmon shark), 2:474 Lamniformes (mackerel sharks), 2:393
Index Lamont Doherty Earth Observatory (LDEO), 2:53 Lamont nephelometer, 4:8 Lampara nets, 2:536, 2:536F, 5:470 fishing methods/gears, 2:536, 2:536F, 5:470 Lampris (opah), 2:395–396F Lams fuscus (lesser black-backed gulls), 5:253 Land components of global climate system, 2:48F erosion, river inputs, 4:759 surface see Land surface(s) Land-based marine pollution, environmental protection and Law of the Sea, 3:440 Landfilling, coral disturbance/destruction, 1:675 Land ice, 5:159 melting, 6:173 see also Glaciers Land-locked boats, early maritime archaeology, 3:695 Land-Ocean Interaction in the Coastal Zone (LOICZ) project, 3:94 Land–ocean interface, 3:394 river inputs, 4:754 see also Land–sea global transfers Land–sea global transfers, 3:394–403 of aeolian materials, 1:120–122 distribution, 1:120–122 major components, 1:120–122 marine aerosols, 1:120–122, 1:121F mineral dust aerosol see Mineral dust aerosol nutrients, 1:123–124 organic compounds, 1:122–123 organic matter, 1:122–123 sources, 1:120–122 sulfate aerosol, 1:120–121 trace metals see Trace metals coastal zones, 3:396–399 bioessential elements, 3:397–399 global warming and, 3:399–401 direction, 3:394 human influence, 3:394, 3:398F Asia, 3:401–403 mechanisms, 3:394–396 trace elements, 3:396 Landslides marine see Slides submarine see Slides Land surface(s) changes, relative to sea level changes, 3:49 cosmogenic isotope concentrations, 1:681T instability, sea level changes, 3:49 sediment volumes, 4:138T temperatures, North Atlantic Oscillation, 4:68F Langmuir cells, 6:189, 6:211–212 Langmuir circulation, 1:436, 3:404–412, 4:214–215, 6:341 bubbles, 1:441
conditions affecting, 3:407 dynamics, 3:405–406 Boussinesq equations, 3:406–407 heat flux, 3:406–407 instability, 3:408–410, 3:410F momentum divergence, 3:406–407 velocity, 3:408 vorticity, 3:408, 3:410F eddy turnover timescale, 3:406 features, 3:404–405, 3:404F, 3:405F field observations, 3:410–412, 3:410F, 3:411F computer simulation of surface tracers, 3:411F Pacific mixed layer, 3:410F, 3:411 instability, 3:408–410, 3:409F Langmuir force, 3:406–407 large eddy simulations, 3:407 polynyas, 4:542–543, 4:544 scaling, 3:405, 3:407–408 sea foam, 6:334–335, 6:335F thermocline and, 3:405 tracers, 3:404–405, 3:405, 3:410–411, 3:411 upper ocean see Upper ocean waves and mass drift, 3:406 Langmuir force, 3:406–407 Lanice conchilega polychaete worm, 1:333, 1:333F La Nin˜a, 2:228, 2:241, 2:242, 2:243F, 2:272, 3:444, 4:699 change to El Nin˜o, 2:242, 2:244 chlorophyll a concentrations, 5:124F, 5:125 mesoscale eddies, 3:764–765, 3:765F sea surface temperatures, 2:241, 2:241F temperature-depth profiles, 2:273F wave response to wind forcing, 2:279F see also El Nin˜o Southern Oscillation (ENSO) Lanternfishes (Myctophidae), 2:412, 2:413F, 4:1–3 bioluminescence, 1:381–382 Lantern nets, fishing methods/gears, 2:539 Lanthanides see Rare earth elements (REEs) Laplace, P-S, tides, 6:35–36 Laplace pressure, 5:574–575, 5:579 Laplace’s equation, surface, gravity and capillary waves, 5:573–574 Laptev Sea, 1:211 polynyas, 4:540 sea ice cover, 5:141–142 sub-sea permafrost, 5:566 La Rance tidal power plant, 6:27, 6:28F, 6:28T Large amorphous aggregates (LAA) camera, 6:368 Large-bodied fishes, harvesting, 2:500–501 Large eddy simulation (LES), 5:134 Large igneous provinces (LIPs), 3:218– 225, 4:320–321 ages, 3:222, 3:223F composition, 3:218–219 coring of, 2:49
(c) 2011 Elsevier Inc. All Rights Reserved.
525
crustal structure, 3:218–219, 3:219F extrusive layer, 3:218–219, 3:219F intrusive layer, 3:218–219, 3:219F lower crustal body, 3:218–219, 3:219F definition, 3:218 distribution, 3:218, 3:218F, 3:219–222, 3:220T in time, 3:222, 3:223F environmental effects, 3:223–225, 3:223F latitude and, 3:223–224 temporal correlations, 3:224–225, 3:224F volatile release, 3:223, 3:223F felsic eruptions, 3:224 mantle dynamics and, 3:218, 3:222, 3:222–223, 3:222F, 3:225 mantle roots, 3:219 mid-ocean ridge basalts vs., 3:218, 3:225 physical volcanology, 3:218–219 sea level rise and, 5:186F, 5:189 seamounts and off-ridge volcanism, 5:292 seismic structure, 5:365 tectonic setting, 3:219–222, 3:219F types, 3:218, 3:219–222, 3:220T, 3:225 see also Geomorphology; Magnetics; Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge seismic structure; Mid-ocean ridge tectonics; Seismic structure; Volcanism Large marine ecosystems (LMEs), 3:413–419, 3:668T biomass yields and food webs, 3:413, 3:418–419 east China Sea LME, 3:413–416, 3:416, 3:416F south China Sea LME, 3:413 application of ECOPATH model, 3:413, 3:415F estimates of combined prey consumption, 3:413 open-ocean food web, 3:415F shallow-water food web, 3:415F Yellow Sea LME, 3:416, 3:417F decline in demersal species, 3:416 effect of overfishing, 3:416 boundaries, 3:414F definition, 3:413 dynamic nature, 3:419 ECOPATH-type models, 3:413, 3:415F, 3:418–419 ‘fish down foodweb’, 3:416, 3:416F, 3:418 food web dynamics and yields, 3:418–419 changes in top predators, 3:418 ECOPATH-type models, 3:413, 3:418–419 ecosystem based management, 3:418 impact of fisheries, 3:418 impact of fish predation, 3:418 recovery of fish stocks, 3:418–419
526
Index
Large marine ecosystems (LMEs) (continued) food webs and, 3:413 importance to fisheries, 3:413 management and food webs, 3:419 global participation, 3:419 oceanographic and biotic components, 3:419 planktonic foraminifera, 4:609 recent degradation of coastal waters, 3:413 regime shifts, food webs and biomass yields, 3:416 California Current LME, 3:416 Gulf of Alaska LME, 3:416 large-scale oceanographic regime shifts, 3:416 US north-east Shelf LME, 3:416–418 effects of overfishing, 3:416–417 influence of lower food web, 3:417–418 recovery of stocks, 3:417 role of copepods, 1:650 see also Demersal fish(es); Ecosystem(s), fishing effects; Exploited fish, population dynamics; Fishery multispecies dynamics; Fishery mutispecies dynamics; Fishery resources; Network analysis of food webs; Ocean gyre ecosystems; Pelagic fish(es); Plankton; Population dynamic models Large Opening Closing High Speed Net and Environmental Sampling System (LOCHNESS), 6:364 Larger sailfish (Istiophorous albicans), 2:377 Large-scale salinity events and thermohaline convection, 5:130 Large-scale sediment transport, 5:447–467 canyons and, 5:462–463 initiation, 5:450 recognition, 5:464 see also Debris flows; Slides; Slumps; Turbidity currents Large waves see Rogue waves Laridae (gulls), 3:420–431, 3:421T body size colony size and, 3:425, 3:426F territory size and, 3:425, 3:426F breeding ecology/behavior, 3:420, 3:425, 3:426–428 age of first breeding, 3:427 chick-rearing, 3:427 clutch size, 3:425–426, 3:427 egg incubation, 3:427 male vs. female investment, 3:428 mobbing, 3:425 nesting, 3:426–427 pairing, 3:427 phenology, 3:426 range, 3:421T studies, 3:427–428 conservation, 3:430–431
measures, 3:431 status, 3:430, 3:430T distribution, 3:420, 3:421T foraging, 3:429–430 habitat, 3:420, 3:424, 3:424–425, 3:426–427 foraging, 3:429–430 nesting, 3:424–425, 3:426 winter, 3:425 migration, 3:425, 5:244, 5:245T physical appearance, 3:422–424, 3:423F, 3:424 plumage, 3:424 Sternidae (terns) vs., 3:424 species, 3:420, 3:421T taxonomy, 3:420 threats, 3:430–431 see also Seabird(s); specific species LARS (launch and recovery system), 4:744 Larsen Ice Shelf, 3:209–211, 3:213 breakup, 3:214F Larsen A, 3:213 Larsen B, 3:213 modeled strain-rate trajectories, 3:216F Larus argentatus (herring gull), 3:423F Larus marinus (great black-backed gull), 3:423F Larvacean(s), 3:16, 3:17F, 3:18 ‘houses’, 2:216, 4:334, 4:334F Larvae adaptive strategies, 1:331T fish see Fish larvae lecithotrophic, 1:331, 1:353, 1:356 pelagic, 1:356 benthic organisms, 1:353 settlement process, 1:353–354, 3:475–476 planktotrophic, 1:331, 1:356, 3:468 benthic organisms, 1:353, 1:354 settlement process, 1:331, 1:353–354, 3:475–476 time in plankton, 1:331 Larval fish analytical flow cytometry, 4:247–248 see also Fish larvae Laser diffraction instruments, 3:246 Laser-induced fluorescence, aircraft remote sensing, 1:139 Laser in situ scattering transmissometry (LISST), 1:48–50, 1:50F Last glacial maximum (LGM), 3:882F, 4:758 d18O values, 1:505, 1:506F Late Cretaceous ocean circulation, 4:307–308 heat transport, 4:307–308 models, 4:308, 4:308F surface, 4:308 thermohaline, 4:308 see also Paleoceanography Late Mesozoic paleo-ocean modeling, 4:303 see also Paleoceanography Latent heat flux, 2:324, 2:329 global distribution, 2:329, 2:330F
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satellite remote sensing, 5:206–207 upper ocean mixing, 6:191 Latent sea–air heat flux, 6:164–165, 6:339 global distribution, 6:169F see also Turbulent heat flux Latimeria spp., 2:468 Latitude heat radiation from Earth and, 3:114, 3:114F heat transport and, 3:115–116 hurricane vorticity and, 6:194 midocean ridge magnetic anomalies and, 3:484–485 mixed layer depth and, 6:218 sea ice depth and, 5:154T species diversity and, 2:142, 4:356, 4:357T thermocline steepness and, 2:272F Launch and recovery system (LARS), 4:744 Launchers, normal (surface ship) deployment of expendable sensors, 2:348 Laurentide Ice Sheet, H events, 1:1–2 Lava composition, 4:600, 4:600F, 5:296, 5:299–300 Lava fields, 5:292, 5:300 Lava flows abyssal hills elongate pillows, 3:865F syntectonic, 3:865–866, 3:865F lobate flows, 3:816F, 3:817 mid-ocean ridges effusion rates, 3:862 morphology, 3:815–816, 3:816F, 3:862 syntectonic, 3:865–866, 3:865F pillow lava, 3:815–816, 3:816F, 3:817, 3:819F seamounts and off-ridge volcanism, composition, 5:296 sheet flows, 3:816F, 3:817 Law and regulation see Law of the Sea; Legal regimes; Shipping Law of the Sea, 3:432–443 dispute settlement, 3:441–442 Annex VII arbitration and tribunals, 3:442 Annex VIII arbitration and tribunals, 3:442 International Court of Justice, 3:442 International Tribunal of the Law of the Sea, 3:441–442 UNCLOS provides a binding framework, 3:441 see also International Tribunal of the Law of the Sea distinguished from maritime/admiralty law, 3:432 environmental conservation, 3:433 environmental protection, 3:439–440 fishery conservation zones, 3:436–437 fishery resources see Fishery resources
Index future prospects, 3:442 evolution in response to pressure, 3:442 historical development, 3:432 jurisdictions, 3:434 ‘area,’ the, 3:435 baselines, 3:434 boundary determinations, 3:435 contiguous zone, 3:434 continental shelf, 3:435 EEZ (exclusive economic zone), 3:434–435 high seas, 3:435 six basic zones, 3:434 territorial sea, 3:434 marine science and technology, 3:438–439 mineral resources, 3:437–438 see also Mineral resources sovereignty over resources, 3:432–433 in EEZ and territorial sea, 3:433 right to exploit, 3:433 without damage to others, 3:433 underlying principles, 3:432–433 articulated by UNCLOS, 3:432 common heritage, 3:433 duty of states on environment, 3:433 environmental conservation, 3:433 international cooperation, 3:433–434 need to conserve the seas, 3:433–434 precautionary action, 3:433 precautionary action prior to environmental damage, 3:433 Rio Declaration, 3:433 sustainable development, 3:433 see also Archaeology (maritime); International organizations Law of the Sea Conference, 3:494 Law of the Sea Convention, sought, protection of archaeological sites, 3:701 Law of the Sea Institute, 3:665 Law of the wall, 6:144 Layered seafloor, acoustic remote sensing, 1:86F, 1:87, 1:87F Laysan albatross (Diomedea immutabilis) expansion of geographical range, 4:593, 5:260 see also Albatrosses LBL (long-baseline navigation), 6:265 LBMP (land-based marine pollution), environmental protection and Law of the Sea, 3:440 LC see Loop Current (LC) LCDW see Lower Circumpolar Deep Water (LCDW) LDEO-BB ocean bottom seismometer, 5:369T, 5:372F LDW see Levantine Deep Water (LDW) Leaching, 3:895–896 Lead (Pb) anthropogenic, 1:549 atmospheric deposition, 1:254T bioturbation tracer as, 1:396–397 in coastal waters/sediments, 1:200
concentration, N. Atlantic and N. Pacific waters, 6:101T in corals, 1:197 dissolved, 6:105 fluxes to world ocean, 1:122F global atmosphere, emissions to, 1:242T isotope ratios Cenozoic, 3:463–464, 3:463F global distribution, 3:459F incongruent release, 3:465T over time, 3:463–464, 3:463F long-term tracer properties, 3:456T North Sea, direct atmospheric deposition, 1:240F in open-ocean, 1:195, 1:195–198, 1:197F, 1:198F, 1:199F evidence presented by Patterson and co-workers, 1:195, 1:196F flux from atmosphere, 1:196 North Atlantic see North Atlantic North Pacific, 1:195, 1:196F, 2:255 South Pacific, 1:195, 1:196F organic complexation, 6:105 pollution, 3:768–769 anthropogenic and natural sources, 3:769T distribution, 3:771T enrichment factor, 3:773T Humber estuary, 3:771, 3:772F riverine flux, 1:254T sampling/analysis difficulties, 1:195 seabirds as indicators of pollution, 5:275, 5:276 source materials, isotope ratios, 3:457T stable isotope ratios, 1:197–198 see also Lead-210 (210Pb) Lead-210 (210Pb), 6:238–239 dissolved, distribution, 6:248–250 polonium-210 ratio, 6:249F radium-226 ratio, 6:249–250, 6:249F removal mechanisms, 6:249–250 sediment chronology, 5:327, 5:328T sediment profile, 5:329F see also Lead (Pb) Lead convection modes of, 3:204F summertime studies, Surface Heat Budget, 3:207 Leaded gasoline phasing-out of, 1:195 impacts, 1:197, 1:198F, 1:199F utilization, 1:195 changing patterns, 1:196, 1:197F Lead Experiment (LeadEx; 1992), 3:204–205 salinity profile, 3:204–205, 3:205F salt flux, 3:205, 3:206F under-ice boundary layer, 6:160 Leads (long linear cracks, ice), 3:203 definition, 4:540 Leafscale gulper shark (Centrophorus squamosus), open ocean demersal fisheries, FAO statistical areas, 4:231T, 4:232 Leaky modes, 6:314
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527
Least auklet, 1:171, 1:173F see also Alcidae (auks) Least-squares solution inverse methods, 3:313, 3:314, 3:314F by singular value decomposition, 3:315 Least storm petrel, 4:590 see also Procellariiformes (petrels) Leatherback turtle (Dermochelys coriacea), 5:212 characteristics, 5:213F, 5:215–216, 5:215F distribution, 5:214–215 migration corridors, 5:215, 5:215F physiology, 5:214, 5:214F reproduction, 5:215 see also Sea turtles Leavitt net, 6:356–357, 6:358F Leeuwin (VOC vesel 1622), 3:447 Leeuwin Current (LC), 1:730–731, 3:444–454, 3:444, 3:444F, 3:445F, 3:446, 3:446F annual cycle, 3:444, 3:445–446 anticyclonic eddies, 3:444, 3:445F, 3:446, 3:446F, 3:447, 3:449, 3:451, 3:451F, 3:452F bottom temperatures, 3:451–454, 3:453F on the Continental Shelf, 3:451–454 cyclonic eddies, 3:446, 3:446F, 3:447, 3:449, 3:451 eddies, 3:449–451 history, 3:445–447 low-salinity tropical water, 3:445–446, 3:447, 3:448F, 3:449F offshoots, 3:447, 3:449–451, 3:452F southward meanders, 3:447 see also Meddies; Mesoscale eddies Leeuwin Undercurrent (LUC), 3:447, 3:449F Lee waves, 3:270, 3:272 Legal regimes, affecting shipping, 5:405 Global Maritime Distress and Safety System (GMDSS), 5:405 International Law of the Sea, 5:405 International Maritime Organization (IMO), 5:405 see also International Maritime Organization (IMO) Marine Pollution Treaty (MARPOL), 5:405, 5:406 National Control and Admiralty Law, 5:405 see also National Control and Admiralty Law Safety of Life at Sea (SOLAS), 5:405 Standards of Training, Certification and Watchkeeping (STCW), 5:405 see also International organizations; Marine policy Legal studies, marine policy analysis, 3:669–670 Legitimacy issues, fishery management, 2:522, 2:524, 2:525, 2:527 Lemon sole (Microstomus kitt), 2:376
528
Index
Lena estuary, Russia enrichment factor, 3:772–773, 3:773T river discharge, 4:755T Lepeophtheirus salmonis (salmon louse), 1:650 Lepetodrilus elevatus (archeogastropod limpet), 3:136F, 3:138F Lepidochelys kempii (Kemp’s ridley turtle), 5:217–218, 5:217F see also Sea turtles Lepidochelys olivacea (olive ridley turtle), 5:214F, 5:217–218 see also Sea turtles Lepidorhombus wiffiagonis (megrim), 2:377 Leptocephali, 2:210, 2:216 see also Eels Leptomedusae medusas, 3:10, 3:11F Leptonychotes weddellii see Weddell seal (Leptonychotes weddellii) Lernaeocera spp. copepods, 1:650 Lerwick, tide-surge interaction, 5:534F Leslie matrix, 4:548 equations, 4:548 modification, 4:548 Lesser black-backed gulls (Lams fuscus), 5:253 Leucocarboninae see Shag(s) Levantine Deep Water (LDW), 3:713F formation, 1:745–746, 1:746, 3:712–714 Levantine Intermediate Water (LIW), 2:4F, 2:5, 3:713F formation, 1:744, 1:745–746, 3:712–714 Gibraltar outflow, 3:717–718 mesoscale eddy interaction, 3:721 path, 1:746, 1:749F, 1:751, 3:711F, 3:718F, 3:720 preconditioning deep-water formation, 3:724 Levees, 5:448F Level-of-no-motion problem, inverse method, 3:312 Levitus atlas, 3:20 LF see Low frequency band (LF) LGM see Last glacial maximum (LGM) LHPR see Longhurst–Hardy Plankton Recorder (LHPR) Liability and insurance, shipping and ports, 5:407 Libby half-life, 5:420 LIDAR see Light detection and ranging Lifamatola Strait, 3:237 Life cycle, population dynamic models and, 4:547, 4:548F Life histories (and reproduction) cephalopods, 1:527 coccolithophores, 1:609–610 cold-water corals, 1:618–619 copepods, 1:647, 1:648–649 coral reef fishes, 1:657 deep-sea fishes, 2:72 demersal fishes, 2:464–465 dolphins and porpoises, 2:155–156 eels, 2:208–210, 2:210F
herring, 4:364–365 intertidal fishes, 3:284–285 krill, 3:354–355 mackerels, 4:368 mesopelagic fishes, 3:749–750 micronekton, 4:5 plankton, effects of turbulence, 5:491–492 planktonic foraminifera, 4:606, 4:608 radiolarians, 4:616 salmonids, 5:30T, 5:31T sardines, 4:367 seabirds, 5:281 sprats, 4:366 toxic phytoplankton, 4:439–441 tunas, 4:368 viruses, 4:465–466, 4:466F see also Fish larvae; Fish reproduction; Reproduction Life span, aquarium fish mariculture, 3:529 Life support, manned submersibles see Manned submersibles (deep water) Lift nets, 2:539, 2:539F, 5:468–469 boat-operated, 2:539, 2:539F fishing methods/gears, 2:539, 2:539F, 5:468–469 portable, 2:539 shore-operated, 2:539, 2:539F Light, 3:244 effects of water depth, 1:348 effects on fish behavior, 2:430 impact on vertical migration, 2:412–413 influence on primary production, 4:573 optimal light conditions, 6:226 penetration into sediments cohesive sediments, 3:807 impact on photosynthesis, 3:810 noncohesive sediments, 3:807–808 penetration through water column, 4:574 requirements, coral reef aquaria, 3:530 sources, absorptiometric chemical sensors, 1:9–10 see also Ocean optics; Solar radiation Light attenuation anomalies, hydrothermal plumes, 2:130–131, 2:132F megaplumes, 2:133–134, 2:136F Light attenuation coefficient, Black Sea, 4:738F Light detection and ranging (LIDAR), 2:586–587, 2:586T bathymetry, 1:299 Light-mantled sooty albatross, 4:596 see also Albatrosses Light rare earth elements (LREE), midocean ridge basalt composition, 3:819–820, 3:820F Ligurian Sea acoustics in marine sediments, 1:83, 1:83F, 1:84F summer desert dust transport, 1:123–124 Liguro-Provenco-Catalan Current, 3:717 Limacina retroversa, 1:67–68
(c) 2011 Elsevier Inc. All Rights Reserved.
Limanda ferruginea (yellowtail flounder), biomass, north-west Atlantic, 2:505–506, 2:506F Limestone formation, 1:451–453 geoacoustic properties, 1:116T Limited domain models, 4:102 Limnomedusae medusas, 3:10 Limpopo (Mozambique), river discharge, 4:755T Lindane, North Sea, direct atmospheric deposition, 1:240F Linear seamount chains, 5:293F, 5:294 off-ridge plume related volcanism, 5:292, 5:296, 5:298F Linear shallow water equations, tsunamis, 6:134 Linear waves kinematic properties, 6:311T surface, gravity and capillary waves, 5:574–576 deep water, 5:575–576 dispersion relations, 5:575 frequency, 5:574 group velocity, 5:576 phase speed, 5:575, 5:575F shallow water, 5:575 velocity, 5:575 wavelength, 5:574 wavenumber, 5:574 wind-generated, 5:578 Linear wave theory, 6:301, 6:301F ‘Liner’ carriers, 5:404 Liner conferences, 5:406 liner companies, 5:406 open conferences, 5:406 price competition, 5:406 Liner trade, deregulation, 5:406 Link, Edwin, 3:516 LIP see Large igneous provinces (LIPs) Lipariid fish, 4:518 Lipid biomarkers radiocarbon tracing, 5:422–423, 5:422F, 5:426F Santa Monica Basin, 5:426F structures, 5:423F vascular plants, applications, 5:422 Lipophrys pholis (shanny), 3:282–283, 3:283F Lipotes vexillifer (Yangtze river dolphin), 2:154F, 2:155, 2:156, 2:159 Liquid bulk charter tankers, 5:404, 5:404T Liquid chromatography see Highperformance liquid chromatography Liquid laminar thickness, definition, 3:7 Liss-Merlivat air–sea gas transfer parametrization, 1:152, 1:153F, 6:89 dual tracer results and, 6:90, 6:90F Lissodelphis spp. (right whale dolphins), 2:153, 2:156 LISST (laser in situ scattering transmissometry), 1:48–50, 1:50F Lister heat flow probe, 3:42–43, 3:42F
Index Lithofacies, 5:464 Lithosphere carbon dioxide cycle, 1:487 deformation, 2:49 formation rates, 3:867–868 thickness, 3:868F Litter, pollution see Pollution solids Little auk, 1:171, 1:173F see also Alcidae (auks) Little Ice Age (LIA), 3:126F, 3:127–128, 3:127F, 3:128F, 3:130–131 coral records, 4:343–345, 4:344F see also Holocene Little penguin (Eudyptula minor), 5:522T, 5:523 breeding patterns, 5:255, 5:523, 5:527 characteristics, 5:522T, 5:523, 5:524F feeding patterns, 5:522T, 5:523 nests, 5:522T, 5:523 see also Eudyptula Little skate, biomass, north-west Atlantic, 2:505–506, 2:506F Littoral Ocean Observing and Prediction System (LOOPS) project, 2:3–5 Littoral zone, 1:351T Living rock coral reef aquaria, 3:530–531 definition, 3:530–531 LIW see Levantine Intermediate Water (LIW) Lloyd mirror effect, 1:102, 1:102F Lloyd’s Maritime Information Services (LMIS), fishing fleet tonnage, 2:543 LMEs see Large marine ecosystems (LMEs) LNHS (low-nitrate, high-chlorophyll) regions, 3:332–333, 3:332T, 3:333F LNLC (low-nitrate, low-chlorophyll) regions, 3:332–333, 3:332T Lobata ctenophores, 3:12–14, 3:13F Lobe, 5:448F, 5:464 Lobster see Jasus (lobster) LOCHNESS (Large Opening Closing High Speed Net and Environmental Sampling System), 6:364 Loco (Concholepas concholepas), 4:768 Locomotion fish see Fish locomotion macrofauna adaptations, sandy beach, 5:54–55 marine mammals, 3:596, 3:608 sea otter, 5:196 LOFAR (Low Frequency Acoustic Recording and Analysis), passive sonar beamforming, 5:511–512 Logarithmic layer, 6:141, 6:141F, 6:144, 6:145 Loggerhead turtle (Caretta caretta), 4:136, 5:214F, 5:218–219, 5:218F see also Sea turtles Logging definition, 2:42 tools, 2:41–42
Logging-while-drilling (LWD), 2:43–44 Log-layer solution, 3:198 Lohmann, Hans, 3:686–687 Loihi Seamount, volcanic helium, 6:281F, 6:282–283 Loligo opalescens, acoustic scattering, 1:68–69 Loligo vulgaris reynardii, acoustic scattering, 1:68–69 Lombok Strait, 3:237 mass transport, 3:239 El Nin˜o and, 3:242 Lomonosov Ridge, 1:211 acoustic reflection, 1:97 London Convention (1972) on dumping of wastes, 3:440, 4:630 London Dumping Convention (LDC), 4:630 London Metal Exchange, 3:897 Lonely, Alaska, sub-sea permafrost, 5:564 Long-baseline (LBL) navigation, 6:265 Long-finned pilot whale (Globicephala melas), 2:156 Longhurst–Hardy Plankton Recorder (LHPR), 6:357T, 6:363–364, 6:363F Optical Plankton Counter vs., 4:249–250 Long Island Sound eutrophication, 2:308T nitrogen, atmospheric input, 1:241T Longitude of perihelion, 4:506 Longline fisheries, 5:265, 5:267T, 5:272–273 Longline fishing, 2:541–542 drifting, 2:542 pelagic species, 4:236–237, 4:238F seabird by-catches, 4:596, 5:249, 5:267T, 5:268 set, 2:541–542 trolling, 2:542 Longman’s beaked whale, 3:643 Long-sea outfalls, 6:270–271 Longshore currents, 6:313, 6:313–314, 6:316F Intra-Americas Sea (IAS), 3:293 sand bars, 6:315 shear, 6:315–316, 6:316 storm surges, 5:531 Longshore wind stress, coastal trapped waves, 1:596 Long-term tracer changes, 3:455–466 definitions and concepts, 3:455–456 information recorded, 3:455 leaching variability and, 3:464–465, 3:465T materials and methods, 3:457–458 results, 3:458–462 beryllium, 3:464 lead, 3:463–464 neodymium, 3:463 osmium, 3:462–463 strontium, 3:458–462 sediment concentrations, factors affecting, 3:455–456 time resolution, 3:465
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tracers used, 3:455, 3:456–457 see also Tracer(s) Long water wave, definition, 5:344–345 Long-wave heat flux, global distribution, 6:169F Long waves, 6:127 Loop Current (LC), 6:192, 6:205F buoyancy profile, 6:196F Gulf see Gulf Loop Current (GLC) hurricane intensity and, 6:209 hurricane interactions, 6:200–202, 6:200F hurricane ocean response, 6:198 salinity profile, 6:196F temperature profile, 6:196F Lophelia pertusa coral, 1:615–616, 1:615F, 1:616F, 1:617F, 1:618 associated with Eunice norvegica worm, 1:620–621 growth on oil platforms, 1:623 molecular research, 1:619–620 parasites, 1:621 reproductive ecology, 1:618–619, 1:619F Lophiiformes (angler fishes), 2:377, 2:472 Lophius piscatorius (monkfish), 2:461 Loran (LOng RAnge Navigation), 5:411 Lord Howe Island, 6:302–303 Loricifera, 5:50 Lort Stokes, J, on East Australian Current eddies, 2:191 Los Angeles, offshore topography, 5:448F Lotka-Volterra model of predator–prey dynamics, 2:596, 2:597F Louisiana coast, hypoxia, 3:175–176, 3:175F Louisiana shelf, hypoxia, 3:175, 3:176F Louvar (Luvarus imperialis), 2:395–396F Love waves, 1:78T, 1:79, 1:79F arrival times, 1:80, 1:80F mantle, 3:869 Lower atmospheric adsorption, 5:130 Lower Circumpolar Deep Water (LCDW), 1:425, 1:426F upwelling, 1:189F water properties, 1:180F see also Circumpolar Deep Water (CDW); Upper Circumpolar Deep Water (UCDW) Lowestoft sampler, 6:359, 6:360F Low frequency band (LF), 1:55–56 definition, 1:52 distant shipping noise see Ship(s) Low molecular weight (LMW) organic compounds, photochemical production, 4:416–417 Low-nitrate, high-chlorophyll (LNHC) regions, 3:332–333, 3:332T, 3:333F Low-nitrate, low-chlorophyll (LNLC) regions, 3:332–333, 3:332T Low-noise microwave radiometers, 5:127 LREE (light rare earth elements), 3:819–820, 3:820F LSW (linear shallow water equations), 6:134
530
Index
LUC (Leeuwin Undercurrent), 3:447, 3:449F Luciferin/luciferase system, 1:376, 1:376–378 dietary requirement for luciferin, 1:381 synthesis of luciferin, 1:381–382 Lucky Strike segment, Mid-Atlantic Ridge, 3:846 Ludwig, 6:270–271 Lulu, R/V (support vessel), 3:505–506, 3:509 Lumpenus lampetraeformis, eutrophication, 2:313 Lutein, structure, 3:570F Lutjanus campechanus (red snapper), marine protected area economics, 3:673–674 Lutra marina (marine otter) conservation status, 3:608T see also Sea otter Lutrinae see Sea otter Luvarus imperialis (louvar), 2:395–396F Luzon Strait, 5:306 Kuroshio loop current, 3:358–359, 3:360F upper layer velocity, 5:314F Lvitsa, 1:211, 1:402 LWD (logging-while-drilling), 2:43–44 Lyman a hygrometers, 5:388 Lyon, Waldo, 1:93–94 Lysmata debelius (fire shrimp), aquarium mariculture, 3:525 Lysocline, 1:448 see also Chemical lysocline
M MAAs (mycosporine-like amino acids), 3:571 Maastrichtian, climate proxy records, 4:322F Macaroni penguin, 5:522T, 5:524–525 see also Eudyptes (crested penguins) McCabe wave pump, 6:300–301, 6:301F Mace Head, aerosol concentrations, 1:249T McKendrick–von Foerster equation, 4:548 Mackenzie River Delta region dissolved loads, 4:759T sub-sea permafrost, 5:562, 5:564F, 5:567 geological model, 5:567, 5:568F salt transport, 5:565 Mackerel (Scomber scombrus), 2:375, 4:368, 4:368–369, 4:368 acoustic scattering, 1:65–67 biomass, north-west Atlantic, 2:505–506, 2:506F description and life histories, 4:368 distribution and catches, 4:368 fishing, management, 4:707 Mackerel icefish (Champsocephalus gunnari) diet, 5:517 Southern Ocean fisheries, 5:515–517
Mackerels (Scombridae), 4:368, 4:368–369 see also Mackerel (Scomber scombrus) Mackerel sharks (Lamniformes), 2:393 Mackinawite, 1:544F Macroalgae, definition, 3:574 Macrobenthos, 3:467–477 composition and succession, 3:470–471, 3:472F global similarity of patterns, 3:471 rich diversity, 3:470–471 description, 3:467 epifauna, 3:467 food sources and feeding methods, 3:468, 3:468–469 environmental factors, 3:468–469, 3:469F influence of body size, 3:469 functional importance, 3:474–476 large-scale disturbances, 3:475 larval settlement process, 3:475–476 macrofauna actions on sediments, 3:475, 3:476T global biomass pattern, 3:467 food availability and depth, 3:467, 3:468F latitudinal differences, 3:467 trenches, 3:467 importance in environmental assessment, 3:476–477 establishing baseline, 3:476–477 impact of trawling, 3:476–477 monitoring changes, 3:476 infauna, 3:467 large-scale diversity patterns, 3:471–473 communities, 3:471 deep-sea vs. shallow water, 3:473 depth-related patterns, 3:473 see also Demersal fish(es) epifauna vs. infauna, 3:471 see also Fiordic ecosystems macrofauna sensu lato, 3:470 macrofauna sensu stricto, 3:470 pollution, effects of, 4:533 relationship between diversity and depth, 3:467 research history and size limits, 3:467–468 benthos categories, 3:468 size limits, 3:468 size spectra, 3:469–470 peaks pattern, 3:469–470, 3:470F size vs. function differentiation, 3:470 small-scale diversity patterns, 3:473–474 disruption problems, 3:474 three-dimensional spatial patterns, 3:474, 3:474F species numbers, 3:471 discoveries of new species, 3:471 research difficulties, 3:471 size of unexplored area, 3:471 substrate differences, 3:467 see also Benthic boundary layer (BBL); Benthic foraminifera; Coral reef(s); Grabs for shelf benthic sampling;
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Meiobenthos; Microphytobenthos; Phytobenthos Macrocystis (giant kelps), 4:430–431 Macrocystis pyrifera (kelp), use of artificial reefs, 1:228 Macrofauna, 1:350, 1:350F, 1:356, 2:58–59, 2:59F definition, 2:140 examples, 2:140 sampling, 2:140 species diversity, 2:144–145 see also Macrobenthos; specific macrofauna Macro Flow Planktometer, 4:247–248 Macro-invertebrates, thermal discharges and pollution, 6:14–15, 6:15F Macronectes giganteus, 4:593 see also Procellariiformes (petrels) Macronectes halli, 4:593 see also Procellariiformes (petrels) Macrotidal estuaries, 2:299–300, 2:300–301 Macrouridae (rattail fish), 2:59F Mad, USA, sediment load/yield, 4:757T Madden-Julian Oscillation, 3:242 Southeast Asian seas and, 5:306 Madeiran storm petrel, 4:594 see also Procellariiformes (petrels) MAD (Magnetic Airborne Detector) program, 3:479 Madrepora oculata coral, 1:615–616, 1:618, 1:619–620, 1:620–621 Maelstrom, 6:57 Magdalena River Intra-Americas Sea (IAS), 3:288, 3:293F sediment load/yield, 4:757T sediment transport process initiation, 5:450 Magellan, Ferdinand, 5:410 Magellanic penguin, 5:522, 5:522T, 5:523, 5:523F see also Spheniscus Magma, 3:843 composition, liquid line of descent (LLD), 3:821, 3:821F mid-ocean ridge see Mid-ocean ridge geochemistry and petrology Magma lens see Axial magma chamber (AMC) Magma supply, mid-ocean ridges, 3:857F, 3:861F abyssal hills, 3:864–865 axial depth profile, 3:854 axial magma chamber (AMC), 3:854–855 axial neovolcanic zone, 3:862 East Pacific Rise, 3:858F fast-spreading ridges, 3:856 magma supply model, 3:858, 3:861F slow-spreading ridges, 3:855–856, 3:858, 3:861F subaxial flow, 3:856–857 Magmatism, 3:843–847 Magnesium (Mg2+), concentrations in river water, 1:627T, 3:395T
Index in sea water, 1:627T determination, 1:626 Magnesium/calcium ratio, 4:323F calcification temperature and, 2:103F measurement in benthic foraminifers, 1:509 sea surface temperature paleothermometry and, 2:101T, 2:103–104 standard error, 2:104 Magnesium carbonate chemical weathering, 1:515 see also Carbonate Magnetic Airborne Detector (MAD) program, 3:479 Magnetic anomalies see Magnetics, anomalies observed Magnetic compasses, 4:478 Magnetic declination, 3:479 Magnetic field, Earth, 3:479–480 core and, 3:479 intensity, 3:480F nondipole component, 3:479 reversal, 3:478F, 3:483, 4:507 magnetic anomalies and, 3:483 past 160 million years, 3:484F see also Geomagnetic field Magnetic poles, 3:479 Magnetics, 3:478–487 anomalies observed, 3:482–484 Juan de Fuca Ridge, 3:483F latitude and, 3:487F major oceans, 3:485F north-east Pacific, 3:482F orientational anisotropy, 3:487F phase shift, 3:484–485 Cape Verde Islands profile, 3:481F data reduction, 3:480–481 anomalies, 3:480 diurnal correction, 3:480 history, 3:478–479 ocean floor rocks, 3:481–482 paleomagnetic information, 3:484–487 latitude, 3:484–485 units, 3:478 Magnetic sensors, archaeology (maritime), 3:698 Magnetic susceptibility, sediments, and origin of material, 3:912 Magnetic variation, 3:479 Magnetometers, 3:479 Magnetostratigraphy, 3:25 Magnuson–Stevens Fishery Conservation Management Act (MSFCMA), (1976) fishery management councils, 2:515 optimum yield definition, 2:182 Main thermocline see Permanent thermocline; Thermocline, main Makaira (marlins), 4:135 Makaira indica (black marlin), hook and line fishing, 4:235 Makaira nigricans (blue marlin), utilization, 4:240 Makakai submersible, 3:515
Makarov Basin, deep water, 1:219–220, 1:220 Makassar Strait, 3:237 interannual variation, 3:242 throughflow, 3:240 upper layer velocity, 5:314F Makharov Basin, temperature and salinity profiles, 1:213F, 1:214F Malacca Strait, 5:306 Malacosteus spp. (stoplight loosejaws), 2:453, 2:455F Mallotus villosus see Capelin (Mallotus villosus) Maltese Channel Crest (MCC), 2:5 ‘Malthusian’ overfishing, 1:653 Malvinas Current see Brazil and Falklands (Malvinas) Currents; Falklands (Malvinas) Current Malvinas Return Current, 1:427 Mammals marine see Marine mammals ocean gyre ecosystems, 4:135 oil pollution, 4:197–198 salt marshes and mud flats, 5:45 terrestrial see Terrestrial mammals Man and the Biosphere Program, 3:668T Manatees, 3:595, 3:608T behavior, 5:440–441 mating, 5:441–442 conservation status, 3:608T ecology, 5:442 exploitation, 3:639–640, 5:442–443, 5:444F future outlook, 5:444–445, 5:446 morphology, 5:439–440, 5:441F physiology, 5:440 myoglobin concentrations, 3:584T population biology, 5:442 skeleton, 3:595F threats, 5:442–443 destruction of seagrass habitat, 5:444 hunting, 5:442–443, 5:444F, 5:446 watercraft collisions, 5:443–444, 5:443F, 5:444–445, 5:445F trophic level, 3:622 see also Sirenians; specific species Mandibles, 3:650 Manganary, E.P., 1:211, 1:402 Manganese (Mn) biological uptake, phytoplankton, 6:80 Black Sea profile, 1:216F, 1:405F concentration N. Atlantic and N. Pacific waters, 6:101T phytoplankton, 6:76T seawater, 6:76T cosmogenic isotopes, 1:679T cycling in estuarine sediments, 1:546–547, 1:547F depth profiles, 6:77F estuarine sediments, 1:544F, 1:545F in ferromanganese deposits, 1:259–260 inorganic speciation, 6:103 metabolic functions, 6:83 nodules see Manganese nodules photosystem II, 6:84–85
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planktonic growth limitation, 6:107 reduction of oxides, 1:545 in sediment oxidation processes, 1:542–543, 1:543 solubility in seawater, 6:79 see also Trace element(s) Manganese crusts, 3:890 mining, cutter head design, 3:894F proposed mining system, 3:893F robotic miner, 3:894F Manganese nodules, 2:65, 3:494, 3:495 abundance, 3:490 characteristics, 3:488 compositional variability, 3:492–493 regional, 3:492–493 diagenetic deposits, 3:489 distribution, 3:490–491, 3:491F worldwide patterns, 3:491 economic potential, 3:494 growth rates, 3:490 hydrogenous deposits, 3:489 internal structure, 3:489–490 concentric banding, 3:489, 3:489F ore-grade, 3:492 Manganese oxides, photochemical production, 4:420 Manganese tailings, 3:898 Manganiferous contourites, 2:86 Mangrove(s), 3:496–504 adaptations, 3:498F to anaerobic soils, 3:496–497 to salinity, 3:496 to salt exclusion, 3:496 aerial roots buttress roots, 3:497 pneumatophores, 3:496–497 root knees, 3:497 stilt roots, 3:496 structure, 3:497 biodiversity, 2:141 definition, 3:496 distribution/biogeography, 3:498–501 distribution, 3:498–499, 3:499, 3:499T, 3:500F diversity anomaly, 3:501 east-west diversity differences, 3:501 east/west floras, 3:501 global diversity, 3:500F latitudinal patterns, 3:499–501 number of countries, 3:499 subregions divisions, 3:499 temperature requirements, 3:499–501 east/west floras, 3:501 evolution and separation, 3:501 species level, 3:501 factors affecting growth patterns, 3:501–502 salinity, 3:502 terrestrial advancement, 3:502 tides, 3:502 humans and, 3:502–503 ancient associations, 3:502 overexploitation/loss, 3:502, 3:503–504 proximity/usefulness, 3:502 types of exploitation, 3:503
532
Index
Mangrove(s) (continued) oil pollution, 4:195–196, 4:196F protection/plantation, 3:502, 3:504 management, 3:504 plantations, 3:504 protected areas, 3:504 sustainability efforts, 3:504 sea-level rise effect, 3:503–504 seeds/seedlings, 3:497–498 dispersal, 3:497–498 longevity, 3:498 species, 3:496, 3:497T adaptations, 3:496 core group, 3:496 definition, 3:496 utilization, 3:502–503 coastal protection, 3:503 fisheries, 3:503 other products, 3:503, 3:503T timber products, 3:502–503 zonation and succession, 3:501–502 see also Coastal topography impacted by humans; Coastal zone management; Intertidal fish(es); Lagoon(s); Salt marsh(es) and mud flats; Salt marsh vegetation; Sea level changes/ variations Mangrove forests, 3:38, 4:254 primary production, 4:254T Mangrove oyster, production, 4:275T Mangrove swamp, oil pollution, sample analysis, 4:193F Manipulators manned submersibles, 3:508–509 master–slave system, 3:508–509 remotely operated vehicles (ROVs), 4:743 Man-made reservoirs, 4:760 Manned submersibles (deep water), 3:505–512 advantages of ROVs as scientific research vehicles, 4:745–746 buoyancy, 3:507–508 extra buoyancy, 3:507 syntactic foam, 3:508 cameras, 3:508, 3:509F deep submergence science, 2:22, 2:24F energy, 3:508 batteries, 3:508 examples of deep submersibles Alvin, US submersible, 3:505–506, 3:509, 3:510F, 3:511 Deep Flight (high speed submersible), 3:506 Lulu, R/V (support vessel), 3:505–506, 3:509 Mir I and Mir II (Russian submersibles), 3:505–506, 3:509–511, 3:510–511, 3:510F Nautile (French submersible), 3:505–506, 3:509, 3:510F Sea Cliff (US Navy submersible), 3:505–506, 3:509 Shinkai (Japanese submersible), 3:505–506, 3:508, 3:511, 3:511F world-wide, 3:509
history, 3:505–506 instrumentation, 3:508 cameras, 3:508, 3:509F manned submersibles (deep water), 3:508 pressure resistant housing, 3:508F life support, 3:508 extra life support, 3:508 pressure hull, 3:508, 3:508F major contributions, 3:511–512 manipulators, 3:508–509 master–slave system, 3:508–509 navigation, 3:509 acoustic navigation systems, 3:509 Differential Global Positioning System (DGPS), 3:509 pressure resistant housing, 3:508F principles, 3:506–507 Deep Flight (high speed submersible), 3:508 descent and ascent, 3:506, 3:506F negative buoyancy, 3:507 neutral buoyancy, 3:507 surfacing, 3:507 second generation, 3:505–506 shallow-water submersibles vs, 3:513, 3:515 surface support, 3:509 support ships, 3:509, 3:510–511, 3:511 third generation, 3:506 typical components, 3:505 water pressure, 3:507 ambient pressure, 3:507, 3:507F pressure compensated housings, 3:507, 3:508F pressure hull material, 3:507 size and shape, 3:507 Manned submersibles (shallow water), 3:513–518 achievements, 3:517 acrylic plastic pressure hulls, 3:514–515 acrylic sphere limits, 3:515 diver ‘lock-out’ capability, 3:514, 3:516 drop weight methods, 3:515 enabling underwater activity, 3:513 examples see Johnson-Sea-Link history, 3:513–515 marine science in situ, 3:517 new smaller vehicles, 3:517 operations, 3:517 multi-science dives, 3:517 search and recovery operation, 3:517 Space Shuttle Challenger disaster, 3:517 present day, 3:515–517 replacement by ROVs, 3:517 scientific uses, 3:516 support vessel, 3:517 transition point (1000m), 3:513, 3:515 underwater missions, 3:513 unique sample collection, 3:517 variable ballast systems, 3:515 viewing windows, 3:515 Man-of-war birds see Fregatidae (frigatebirds)
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Mantle, 4:275 composition melting at subduction zones and, 3:879F spreading behavior and, 3:870F Darcy percolation flux, 3:873 flow see Mantle flow gravimetric anomalies, 3:85–86 loss of water, 4:262 melting beneath mid-ocean ridges, 3:869–872 transport to ridge axes, 3:872–874, 3:872F oxidation, 4:263 plumes see Mantle plumes Rayleigh waves, 3:869 shear wave velocity structure, East Pacific Rise, 3:871F, 3:872 spreading rate composition and, 3:870F melt flux and, 3:869–871 upper, anisotropic structure, 5:366 upwelling, 3:868–869 see also Mantle flow; Melt Mantle flow, 3:868–869 equation of motion, 3:868 model predictions, 3:871F, 3:877F numerical model, 3:869, 3:869F Mantle helium, 6:277 history, 6:278 see also specific types Mantle plumes, 5:296 large igneous provinces and, 3:218, 3:222, 3:222–223, 3:222F, 3:225 Pacific, 5:300–301 plume-ridge interaction, 5:296–297 propagating rifts and microplates, plume-related asthenospheric flow, 4:600, 4:601, 4:604 starting plumes, 5:292 well-behaved plume, definition, 5:296 see also Galapagos hot spot; Seamounts and off-ridge volcanism Manx shearwater (Puffinus puffinus) expansion of geographical range, 4:593 see also Shearwater(s) Mapping AUVs, 6:262–263 early protocol established by Bass, 3:696 undersea see Bathymetry Mapping and charting vessels, 5:415 hydrographic survey ships, 5:415 MAR see Mid-Atlantic Ridge (MAR) Marangoni waves, 5:571 Marbled murrelet, 1:173F see also Alcidae (auks) Marchetti, Cesare, 1:498 Marchwood power station, thermal discharges, effects of, 6:16 Mare, Molly, 3:468 Margalef’s species richness index, 4:534 Marginal ice zone (MIZ), 5:159 acoustic propagation, 1:99 sea ice deformation rate, 5:160–162 Marginal Ice Zone Experiments (MIZEX), 3:202
Index Margins, ocean, geophysical heat flow, 3:47 Margin sediments, ocean see Ocean margin sediments Marianas subduction zone, accretionary prisms, 1:31–32 Marianas Trench, sea surface topography, 5:58–59, 5:60F Mariculture, 3:537–544 aquarium fishes see Aquarium fish mariculture bluefin tuna, 4:241 see also Thunnus thynnus (Atlantic bluefin tuna) commodity/system descriptions, 3:537–538 organisms produced, 3:537 containment facilities, 3:537 crustaceans, 3:539–540 development needs, 3:539–540 lobster aquaculture, 3:539 diseases see Mariculture diseases economic/social impact see Mariculture economic and social impacts environmental challenges, 3:540–541 environmental impacts, 3:540–541 challenges, 3:541 complex interactions, 3:540 economics, 3:541 environment effect on, 3:540 interactions, 3:540 mariculture on environment, 3:540 mariculture on itself, 3:540 political environment, 3:541 positive mariculture impacts, 3:540 siting of farms, 3:541 sociocultural aspects, 3:541 technology/farming methods, 3:540 environmental management, 3:541–542 future, 3:543 growing industry, 3:537 mariculture regions, 3:537, 3:538T statistics, 3:537, 3:537F habitat modification, 3:102 integrated coastal area management, 3:542 planning, 3:542 introduction of exotic species, 2:333–334 marine finfish, 3:539 Americas and Europe, 3:539 Asia, 3:539 environmental concerns, 3:539 global status, 3:539 hatchery technologies, 3:539 Mediterranean species see Mediterranean species, mariculture miscellaneous invertebrates, 3:540 mollusks (bivalve), 3:537–538 bottom methods, 3:538 culturing methods, 3:537 human health concerns, 3:538 management and production, 3:538 siting of farms, 3:537 surface or suspended methods, 3:538
within-particulate substrates method, 3:537 see also Oyster farming ocean thermal energy conversion, 4:172 other miscellaneous invertebrates, sponges, 3:540 pelagic fish, 4:241 policy and legal issues, 3:542–543 environmental impact assessment, 3:543 government involvement, 3:542–543 government regulations, 3:543 important issues, 3:542–543 international issues, 3:543 salmonids see Salmonid farming seaweed see Seaweed mariculture technology and systems management, 3:541–542 animal health management, 3:542 economic/sociocultural aspects, 3:542 farm construction/design, 3:541 farm siting, 3:541 feeds/feed management, 3:542 food safety, 3:542 suitability of species/seed, 3:541–542 water/sediment management, 3:541 see also Exotic species introductions; Mariculture economic and social impacts Mariculture diseases, 3:519–523 aquarium fish, 3:529 bacterial, 3:520T, 3:521–522 treatments, 3:521–522 vaccination, 3:522, 3:522T management, 3:519, 3:521 facility design, 3:519 handling, 3:520 hatchery isolation, 3:519 husbandry issues, 3:519, 3:519–520 hygiene practice, 3:519 infected stock avoidance, 3:521 infected stock eradication, 3:521 infection control, 3:521 stress minimization, 3:519, 3:519–520, 3:520, 3:520–521 vertical transmission elimination, 3:521 parasitic, 3:520T, 3:522 treatments, 3:522 treatments, 3:520T, 3:521 vaccination, 3:522, 3:522T methods, 3:522–523 status, 3:522 use, 3:522 viral, 3:520T, 3:521 treatments, 3:521 vaccination, 3:522, 3:522T see also specific diseases Mariculture economic and social impacts, 3:545–551 economic impacts, 3:545–547 direct and indirect effects, 3:545 economic development, 3:548 economic growth, 3:548 economic multiplier effects, 3:548–549
(c) 2011 Elsevier Inc. All Rights Reserved.
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mariculture’s multiplier effects, 3:549 effects on lives of the poor, 3:545–546 employment, 3:547 depressed areas, 3:547 displaced fishermen, 3:547 at farm, 3:547 percentage, 3:547 throughout distribution chain, 3:547 throughout supply chain, 3:547 export revenue/foreign exchange, 3:548 importance to poor countries, 3:548 income from sales revenue, 3:546–547 cash income benefits, 3:547 exceeding capture fisheries, 3:547 factors affecting growth, 3:546–547 growth from 1950 to 2005, 3:546, 3:546F macroeconomic effects, 3:545 negative impacts, 3:549 externalities, 3:549 impact on wild fish stocks, 3:549 loss of mangrove forests, 3:549 predator control, 3:549 primary sources, 3:549 tax revenue, 3:547–548 importance to poor countries, 3:548, 3:549–550 interconnections, 3:545 social impacts, 3:549–550 enhancement of capture fisheries, 3:550 food security, 3:549–550 food reserves, 3:550 health benefits, 3:550 negative impacts, 3:550–551 conflicts in Asia, 3:550–551 conflicts in the Mediterranean, 3:551 conflicts over use of resources, 3:550–551 displacement of local people, 3:550 nutritional benefits, 3:550 poverty alleviation, 3:550 top mariculture-producing countries, 3:545T top mariculture species cultured, 3:546T types of impacts, 3:545 Mariculture of seaweeds see Seaweed mariculture Marina development, coral disturbance/ destruction, 1:675 Marina di Equa, 4:770F Marine aerosols see Aerosols Marine aggregates see Aggregates, marine Marine algal genomics and evolution see Algal genomics and evolution Marine-Atmospheric Emitted Radiance Interferometer (M-AERI), 3:327–328 Marine biodiversity, 2:139–148 coastal environments, 2:140–142 importance of, 2:147 concerns, 2:147
534
Index
Marine biodiversity (continued) deep submergence science studies, 2:29 estimates of total species numbers, 2:144–145, 2:147 habitats and, 2:139, 2:139F, 2:144, 2:147 see also specific habitats importance of, 2:146–147 late Eocene, 4:325 latitude and, 2:142, 4:356, 4:357T open ocean, 2:142–144 depth-related patterns, 2:143 work by Grassle and Maciolek, 2:143 work by Hessler and Sanders, 2:143 hydrothermal vents and, 2:144 importance of, 2:147 low, 2:143, 2:144 productivity and, 2:143 organisms, 2:140 see also specific organisms patchiness and, 2:144 sampling, 2:140, 2:143–144, 2:144–145 threats, 2:145–146 zooplankton, 1:636–637, 1:637F see also specific species Marine biotechnology, 3:560–566 academic research discipline, 3:560 applications to aquaculture, 3:562–563 disease control, 3:563 bacteria, 3:563 chemotherapeutics, 3:563, 3:565 viruses and fungi, 3:563 genetically modified crops, 3:563 genetic management/engineering, 3:563 biological contaminants, 3:563 cloning of wild genotypes, 3:563 ‘genetic management’ defined, 3:565 marker-assisted techniques, 3:563 transgenic organisms, 3:563 improved feed and nutrition, 3:563 larval nutrition, 3:563 reproduction, 3:562–563 definitions, 3:560 future perspectives, 3:565 international conferences, 3:560 marine conservation, 3:560–561 data collection methods, 3:561 monitoring/assessing ocean health, 3:560 research tools, 3:560–561 tools for the study of marine ecology, sensors, 3:561 understanding life histories, 3:561 marine-derived bioprocesses, 3:562 bioremediation, 3:562 oceans and human health, 3:563–564 biomarkers, 3:564, 3:565 diagnostic tools/assessments, 3:564 global perspective, 3:564 rising concern, 3:564 organism uses, 3:560 pelagic fishery product resources, 5:471
policy issues, 3:564 funding, 3:564 intellectual property protection, 3:564–565 marketing, 3:564 national policy initiatives, 3:565 regulatory framework, 3:564 resource competition, 3:564 role of government/public agencies, 3:564 United States, 3:565 use conflicts, 3:565 products of interest, 3:561 biomaterials and nutraceuticals, 3:561–562 antifreeze glycoproteins, 3:562 antioxidant peptides, 3:562 chitin polymers, 3:562 deep-sea hydrothermal vents, 3:562 eelgrass, 3:562 invertebrates, 3:562 seaweeds, 3:561–562 industrial enzymes, 3:562 bioluminescence, 3:562 thermostable-DNA-modifying enzymes, 3:562 medicines, 3:561 horseshoe crabs, 3:561 invertebrates, 3:561 new genes, 3:561 seaweeds, 3:561 sponges, 3:561 professional associations, 3:560 professional journals, 3:560 Marine birds see Seabird(s) Marine ecology, 3:565 see also Ecology Marine Ecosystem Research Laboratory (MERL), 3:734, 3:735F, 3:737F Marine ecosystems see Ecosystem(s) Marine fauna, 3:121 Marine finfish mariculture see Mariculture Marine habitat(s) biodiversity and, 2:139, 2:139F, 2:144, 2:147 threats, 2:145–146 types, 2:139, 2:139F see also Habitat(s); specific habitats Marine Hydrophysical Institute of Sevastopol, 1:154T Marine ice, 5:545–546, 5:547 see also Ice; Sea ice Marine invertebrates stock enhancement/ocean ranching programs, 4:147T, 4:151–152, 4:152F see also Invertebrates; specific invertebrates Marine Mammal Protection Act (1972), USA, 3:667 Marine mammals, 3:605–614 adaptations, 3:605–608, 3:615 for diving see Marine mammals, diving physiology amphibious, 3:608–610
(c) 2011 Elsevier Inc. All Rights Reserved.
bioacoustics, 1:357–363, 1:359–360 basics of, 1:357–358 recognition calls, 3:619–620 group recognition, 3:620–621 individual recognition, 3:620 mother–infant, 3:619–620 social organization and, 3:621 research methods, 1:362–363, 1:362F acoustic location, 1:358F, 1:362 telemetry, 1:362F, 1:363 sound production mechanisms, 1:359F, 1:361–362, 1:361F structure and biological function of calls, 1:358–359, 1:358F, 1:359F vocalizations, 1:357, 1:360–361 songs, 1:360–361, 3:618, 3:618F, 3:619F see also Marine mammals and ocean noise conservation, 3:613–614 defense from predators, 3:616–617 diving physiology, 3:582–588 adaptations for locomotion, 3:587 adaptations for ventilation, 3:586–587, 3:587F adaptations to anoxia, 3:582–583 cardiovascular adjustments, 3:583–584 metabolic responses, 3:584–585, 3:585F myoglobin concentrations, 3:583, 3:584T oxygen stores, 3:583, 3:583F, 3:588 adaptations to light extremes, 3:587–588 adaptations to pressure, 3:585–586, 3:586F, 3:587F aerobic diving limit, 3:585, 3:585F gliding, 3:584–585 obstacles to overcome, 3:582, 3:582–583, 3:585–586, 3:586–587, 3:587–588 research, 3:588 evolution, 3:582, 3:589–595 exploitation see Human exploitation feeding, 3:610 annual cycles, 3:610–611 behavior, 3:615–616 mechanisms, 3:615–616, 3:616F importance of Alaska Gyre coastal currents, 1:459 locomotion, 3:596, 3:608 lungs, 3:586, 3:586F, 3:587F migration and movement patterns, 3:596–604, 3:613 see also individual types of mammals navigation, 3:613 ocean gyre ecosystems, 4:135 oil pollution, 4:197–198 prohibited species protection, fishery management, 2:516 reproduction annual breeding cycles, 3:610–611 mating strategies, 3:617–619 advertisement displays, 3:618, 3:618F, 3:619F
Index female, 3:617 male, 3:617 sensory systems, 3:610 hearing, 1:359–360, 1:360F, 3:610 vision, 3:587–588 social organization and communication, 3:615–621 taxonomy, 3:589–595, 3:605 Order Carnivora see Carnivores Order Cetacea see Cetaceans Order Sirenia see Sirenians trophic level(s), 3:622–627 estimation, 3:626 dietary analysis, 3:622–623, 3:623F, 3:626 equation, 3:622 stable isotope analysis, 3:623–625, 3:626 interactions, 3:624F, 3:625–626 prey–predator, 3:625, 3:626 variation, 3:623 see also Climate change, effect on marine mammalssee specific genera/ species Marine mammals and ocean noise, 3:628–634 acoustic disturbance, model of population consequences, 3:633F acoustic results of human activity, 3:628 ambient noise increased, 3:628 effects of noise on mammals, 3:628 hearing loss permanent, 3:631 temporary, 3:630–631 interference with natural sound reception, 3:628 masking, 3:630 critical frequency band, 3:630 directional hearing, 3:630 interference with natural sound, 3:630 passive listening for acoustic cues, 3:630 passive sonar equation, 3:630 possible effects on baleen whales, 3:630 masking, adaptations to captive animals, 3:630 wild animals, 3:630 natural sounds, 3:628 naval sonar, 3:628 noise role in population declines, 3:628–629 nonauditory effects, 3:631 acoustic resonance, 3:631 blast injuries, 3:631–632 bubble growth effect, 3:631 effects in humans, 3:631 humpback whales and blast injuries, 3:631–632 rectified diffusion and activation of microbubbles, 3:631 stress, 3:632 permanent threshold shift, 3:631 problem magnitude, 3:632–633 mortality, 3:632 seismic exploration, 3:628
shipping, 3:628, 3:632 temporary threshold shift, 3:630–631 exposure and sound intensity, 3:631 recovery time, 3:631 zones of influence, 3:629–630, 3:629F behavioral responses, 3:629–630 beluga whales, 3:629–630 sound characteristics and intensities, 3:629 see also Marine mammals, bioacoustics Marine mats, 3:651–653 biological pump, 3:651 diatom mats see Diatom mats giant diatoms see Giant diatoms see also Microphytobenthos Marine methodologies see Remotely operated vehicles (ROVs); Sonar systems Marine natural history, 3:121–122 Marine Optical Buoy (MOBY), 5:119 Marine organisms bacterial isolates, 3:569F as chemical and medicine resources, 3:567–575 biocatalysis, 3:571–572 bioremediation, 3:572 drug discovery, 3:567–568 food additives, 3:568–571 marine-derived nutraceuticals, 3:568–571 novel metabolites, 3:567–568 research directions, 3:573–574 uses, 3:568F habitats, 3:567 pollution, effects of see Pollution see also individual types of organisms, species Marine otter see Sea otter Marine Oxygen Isotope Stage, 3:127 Marine parks see Marine protected areas (MPAs) Marine phenomena, history of study of, 3:121 Marine policy, 3:664–671 analytical approaches, 3:668–669 economic, 3:669 goals, 3:664–665 legal studies, 3:669–670 lesson-drawing, 3:670 organizational studies, 3:669 collective action, 3:664–665 ‘freedom of the sea’, 3:666 future prospects, 3:670 general public policy vs., 3:664, 3:664T historical emergence, 3:665 institutional frameworks, 3:666 effectiveness, 3:670 global, 3:666–667, 3:667T integration, 3:667–668 multiple-use management regimes, 3:667–668 national, 3:667 ocean space enclosure, 3:666 regional, 3:667, 3:668T integrated coastal zone management, 3:668
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journals, 3:665 marine protected areas, 3:670 multidisciplinarity, 3:665–666 ocean resources, 3:666 ocean uses, 3:666, 3:666T precautionary approach, 3:670 social science disciplines, research foci, 3:665–666, 3:665T Marine Policy and Ocean Management program, 3:665 Marine Policy Center, Woods Hole Oceanographic Institution marine policy emergence role, 3:665 purpose, 3:665 Marine pollution definition, 3:768 see also Pollution Marine Pollution Treaty (MARPOL), 5:405, 5:406 Marine protected areas (MPAs), 3:672– 677, 4:178 administrative costs, 3:676, 3:676F coral reef/tropical fisheries, 1:653–654 definition, 3:672 ecosystem effects, 3:674–675, 3:675 expansion, 2:205, 3:673 fishing effort, distribution, 3:674 fish stocks, distribution, 3:674 focus, 3:672 impact on fishermen, 4:178 implementation, dynamic responses, 3:674 insurance, 3:675 irreversibilities, 3:675–676 management objectives, 3:673 biological, 3:673, 3:675 economic, 3:673–674, 3:674 multiple-use management regimes, 3:667–668 networks, 4:179 ‘no-take’ fisheries reserves, 4:178 number, 3:672–673, 3:673F ocean area inclusion estimates, 3:675 optimal spatial distribution, 4:178 policy issues, 3:670 refuge effect, 3:673, 3:674 size, 3:672, 3:672F size and location, 4:178 social impacts, 2:523–524 stock effect, 3:673, 3:674 tropical fisheries, 1:653–654, 3:673 Marine recreational waters beaches see Beach(es) fecal contamination, 6:269 microbiological quality guidelines, 6:270T sewage disposal methods, 6:270–271 Marine salvagers, archaeological expertise sought by, 3:700 Marine science and technology, 3:438–439 consent regime, 3:439 rights of coastal states, 3:439 right to withhold consent, 3:439 Law of the Sea and, 3:438–439 legal right to conduct research, 3:439
536
Index
Marine science and technology (continued) marine scientific research regime, 3:438–439 technology transfer, 3:439 Marine sediments see Seafloor sediments; Sediment(s) Marine silica cycle, 4:615 Marine snow, 1:371, 3:686–694, 3:686F characteristics, 3:689 adsorption, 3:690 biological processes, 3:689–690 chemical composition, 3:689 density, 3:689 enrichment factors, 3:690–691 grazers, food source for, 3:690–691 microenvironments, 3:690 microscopic composition, 3:689 porosity, 3:689, 3:690F scavenging, 3:690 sinking rate, 3:689, 3:690F definition, 3:686, 4:330, 4:337 destruction, 3:692–693 distribution, 3:691–692 features, 3:686 formation, 4:330, 4:331–332, 4:331F, 4:332F, 4:335 historical developments, 3:686–687 methods of examination, 3:687–689 holographic techniques, 3:687 insitu pumping systems, 3:687–688, 3:688F laboratory production, 3:689, 3:689F photography systems, 3:687 sediment traps, 3:688–689, 3:688F subaqua diver, 3:688F water bottle, 3:688F production, 3:692–693 sedimentation of calcite, 4:610–611 underwater video profiling, 6:368 see also Particle aggregation dynamics Marine species diversity see Marine biodiversity Marion Dufresne, 4:301 Maritime archaeology see Archaeology (maritime) Maritime law, 3:432 Market issues, Mediterranean mariculture, 3:533, 3:536 Marlin (instrument), 2:292F Marlins (Makaira spp., Tetrapturus spp.), 4:135 utilization, 4:240 MARPOL, convention for prevention of pollution from ships, 3:440 Marquesas Island hot-spot, seismic structure, 5:365 Marrobbio, 5:349 Marsigli, Luigi, 2:572 Martialia hyadesi (seven star flying squid), Southern Ocean fisheries, 5:518 MARVOR floats, 2:177 Mary Rose, recovery by Margaret Rule, 3:697 Masked booby, 4:373 see also Sulidae (gannets/boobies)
Mass fluid packets, 5:136 global cycling, 2:49 Massachusetts Bay circulation variability, 2:5 forecasting and data assimilation, 2:3–5, 2:5, 2:6F ocean zoning, 4:175F water-column profiles, 4:481F Mass balance approach, subterranean groundwater discharge estimation, 3:91 Mass boundary layer, 1:148F dissolved gas diffusion, 1:148 Mass-destruction weapons, radioactive wastes, 4:629 Mass median diameter (MMD), 1:124, 1:249 Mass movement see Slide Mass spectrometry (MS), 3:881–883 inductively-coupled, 2:103–104 nitrogen isotope ratio determination, 4:40 see also Accelerator mass spectrometry (AMS); Thermal ionization mass spectrometry Mass transport characteristics, 5:449T definition, 5:447 initiation, 5:450 recognition, 5:450–451 runout distances, 5:452T sediment flow and, 5:447–467 velocity-based terms, 5:450 Master–slave system, manipulators, manned submersibles, 3:508–509 Masuda, Yoshio, 6:300 Masu salmon (Oncorhynchus masou), 5:32, 5:33 MASZP (moored, automated, serial zooplankton pump), 6:364, 6:366F MAT (modern analog technique), 2:109–110 Mathematical models, exploited fish, population dynamics assessment, 2:181 Matlab, 1:708 Matrilineal (social unit), definition, 3:603 Matrilines, 3:650 Matrix models, 4:548 applications, 4:548 equations, 4:548 Leslie, 4:548 variations, 4:548 see also Population dynamic models Matuyama Diatom Maximum, productivity reconstruction, 5:341F, 5:342 Maud polynya, 4:543 Maud Rise, 6:321–322 Maumere, 6:128–129 Maurolicus muelleri (pearlsides), 2:415 Maury, Matthew Fontaine, 3:122 MAW see Modified Atlantic Water (MAW) Mawson, aerosol concentrations, 1:249T
(c) 2011 Elsevier Inc. All Rights Reserved.
Maximum sustainable yield (MSY) excess fishing capacity, 2:544 exploited fish, population dynamics, 2:182 fishery management, 2:513, 2:518–519 see also Sustainability Maxwell equations, electromagnetic wave propagation, 2:251–252 MBARI see Monterey Bay Aquarium Research Institute MBES (multibeam echo sounders), 1:299, 1:300 MBT (mechanical bathythermograph), 2:345 MC see Mindanao Current (MC); Mozambique Current McCabe wave pump, 6:300–301, 6:301F McKendrick–von Foerster equation, 4:548 MCP (Medieval Cold Period), 3:127–128 MCS (multichannel seismic surveys), 5:412, 5:416 MDS (multidimensional scaling), pollution, effects on marine communities, 4:536–537, 4:538F Meander systems, mesoscale jets, 5:481, 5:482F Mean ice draft Beaufort Sea, 5:152F Canada Basin, 5:152F Chukchi Cap, 5:152F Eastern Arctic, 5:152F Eurasian Basin, 5:153F Nansen Basin, 5:152F North Pole, 5:152F Mean kinetic energy (KEM), 4:118F definition, 4:117–118 Mean life l–ı (decay), 4:651 Mean meteorological variables measurement methods by land and sea, 5:375 sensors for measurement see Sensors for mean meteorology Mean oceanic residence time, definition, 3:678 Mean sea level (MSL), storm surges, 5:539 Mechanical bathythermograph (MBT), 2:345 Meddies, 2:171, 3:295F, 3:702–709 anticyclonic, 3:702 cyclonic, 3:702 decay of, 3:705–706 definitions, 3:702–703 discovery, 3:702 discussion, 3:708–709 energetics, 3:706–707 fluid parcels, 3:705 formation, 3:705, 3:706F historical observations, 3:707F history, 3:703 homogenization, 3:705 intrusions, 3:295, 3:295F observational study, 3:297, 3:297F kinetic energy/available potential energy, ratio of, 3:706–707
Index salinity of, 3:295, 3:296F structure, 3:703–705 sudden death, 3:707 vortical modes, 6:287 vorticity, 3:702 see also Mesoscale eddies Meddy ‘Sharon’, 3:703, 3:704F, 3:705F, 3:706F potential vorticity distribution, 3:705, 3:705F structure, 3:708 Medicines, from marine sources see Marine biotechnology; Marine organisms Medieval Cold Period (MCP), 3:127–128 see also Holocene Medieval Warm Period (MWP), 3:127–128, 3:128F see also Holocene Mediterranean Action Plan (1975), 1:602 evaluation, 1:602 impacts, 1:602–603 Mediterranean Intermediate Water, 1:473 Mediterranean maritime archaeology, 3:697 Mediterranean mussel see Mytilus galloprovincialis (Mediterranean mussel) Mediterranean outflow, 3:705 diffusive convection, 2:167 salty, 4:126, 4:128 thermohaline staircases, 2:163F Mediterranean Ridge, sedimentary records of Holocene climate variability, 3:126 Mediterranean Salt Tongue (MST), 3:703, 3:707 Mediterranean Sea acoustic time dispersion, 1:118, 1:118F Atlantic overflow, 4:265, 4:266F Atlantic Water entry, 1:745–746, 1:746 basin, 1:744, 1:745F open thermohaline cell, 1:746, 1:746F bathymetry, 1:744, 1:745F bottom layering, 1:113F bottom topography, 3:710, 3:711F carbon sequestration, 1:498 circulation, 4:123 climatology, 1:745–746 current systems, 1:744–751 deep convection, 2:13, 2:19–20 eastern see Eastern Mediterranean geography, 3:710, 3:711F gravity currents, 4:792–793 morphology, 1:744–746, 1:745F phosphate, atmospheric input, 1:123–124 research programs, 1:744 salinity, 4:125 distribution, 1:23F, 1:25–26 salty outflow, 4:126, 4:128 sapropels, diatom flux and, 3:653 sediment sequences, orbital tuning, 4:315 sound speed profile, shallow water, 1:112–113
source of warm, saline intermediate water, 2:81 tomography, 6:49, 6:51–52, 6:54F western see Western Mediterranean Sea see also Mediterranean Sea circulation Mediterranean Sea circulation, 3:710–725 Adriatic, 3:714–715 Aegean, 3:714–715 salinity, 3:716–717, 3:724 basin scale circulation, 3:712–717 Aegean Deep Water see Aegean Deep Water (AGDW) Atlantic Water jet, 3:710–712 Cretan Deep Water see Cretan Deep Water (CDW) Cretan Intermediate Water see Cretan Intermediate Water (CIW) Eastern Mediterranean Deep Water see Eastern Mediterranean Deep Water (EMDW) Levantine Deep Water see Levantine Deep Water (LDW) Levantine Intermediate Water see Levantine Intermediate Water (LIW) Transitional Mediterranean Waters (TMW), 3:717 water mass formation, 3:712–714 Western Mediterranean Deep Water see Western Mediterranean Deep Water (WMDW) Black Sea input, 3:710, 3:716 bottom water formation, 3:712–714, 3:714–715 deep convection, 3:716–717 deep water temperature, 3:714 eastern Mediterranean basin see Eastern Mediterranean basin Eastern Mediterranean Transient (EMT), 3:716, 3:720, 3:724 evaporation, 3:710, 3:712–714 freshwater flux, 3:710, 3:712–714 global ocean circulation, 3:710 heat flux, 3:710, 3:716–717 history of study, 3:714 interannual variability, 3:723 mesoscale circulation, 3:720–722 Algerian eddies, 3:717, 3:721 Corsican eddies, 3:721 current characteristics, 3:721 horizontal scale, 3:720–721 measurements, 3:721, 3:722F seasonal variability, 3:717 sub-basin/mesoscale interaction, 3:722 temperature cross-section, 3:722, 3:722F western basin, 3:721 modeling, 3:722–724 baroclinic eddies, 3:723–724 deep- and intermediate-water formation, 3:723–724 Eastern Mediterranean Transient (EMT), 3:724 eddy resolving, 3:723, 3:724F interannual variability, 3:723
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Levantine Intermediate Water (LIW), 3:724 seasonal variability, 3:723 Modified Atlantic Water (MAW), 3:717, 3:718F multiscale interaction and variabilities, 3:710–712, 3:712F eastern basin, 3:710–712, 3:712F sub-basin/mesoscale interaction, 3:722 western basin, 3:710–712, 3:712F nonlinear system, 3:710 nutrient flux, 3:717 outflows see Outflows precipitation, 3:710, 3:716–717 preconditioning, 3:714, 3:715F, 3:716–717, 3:723, 3:724 salinity, 3:714, 3:715F, 3:716–717, 3:724 measurements, 3:714 preconditioning, 3:712–714, 3:716–717, 3:724 salt flux, 3:710 seasonal variability, 3:723 sea surface temperature, satellite imagery, 3:720, 3:721F straits, 3:710, 3:711F sub-basin scale circulation, 3:717–720 Algerian Current, 3:717, 3:721 Almeria-Oran Jet, 3:717 anticyclonic eddies, 3:720, 3:721F Atlantic Ionian Stream (AIS), 3:719F, 3:720, 3:720T eastern basin, 3:718–720 Ierapetra Anticyclone, 3:719F, 3:720, 3:720T Liguro-Provenco-Catalan Current, 3:717 Mersa Matruh anticyclonic gyre, 3:718–720, 3:719F, 3:720 Mid-Mediterranean Jet, 3:718–720, 3:719F modeling, 3:722–723, 3:723F Rhodes cyclonic gyre, 3:718–720, 3:719F, 3:720T seasonal variability, 3:720 Shikmona eddy, 3:718–720, 3:719F, 3:720T sub-basin/mesoscale interaction, 3:722 surface waters’ pathways, 3:719F Winter Intermediate Water (WIW), 3:717–718, 3:718F thermohaline circulation see Thermohaline circulation water budget, 3:710 water exchange, 3:710 water masses see Water mass(es) western Mediterranean basin see Western Mediterranean basin wind stress, 3:710 see also Coastal circulation models; Upper ocean, time and space variability; Wind-driven circulation
538
Index
Mediterranean species, mariculture, 3:532–536 capital investment, 3:533 favorable aspects, 3:533 sheltered waters, 3:533 feeding, 3:532 manpower requirements, 3:532–533 market issues, 3:533, 3:536 Italy, 3:535 problems, 3:533, 3:535 eutrophication, 3:533 fisheries, dependence on, 3:533 pollution-related, 3:535–536 site shortages, 3:535 space, competition for, 3:533 temperature extremes, 3:533 tourism, 3:533 urbanization, 3:533 production systems, 3:533–534 regional specialization, 3:535 stock acquisition, 3:532 hatcheries, controlled reproduction, 3:532 wild origins, 3:532 technology access, 3:532, 3:536 transport, 3:532 see also specific species Mediterranean Water (MW), 2:20, 6:295, 6:296F temperature–salinity characteristics, 6:294T, 6:297, 6:297F Medium resolution imaging spectrometer (MERIS), 5:117–118 Medusae, 3:10 Anthomedusae, 3:10, 3:11F Coronatae, 3:10, 3:11F Cubomedusae, 3:10, 3:11F Leptomedusae, 3:10, 3:11F Limnomedusae, 3:10 Narcomedusae, 3:10, 3:11F Rhizostomae, 3:10 Semaeostomae, 3:10, 3:11F Trachymedusae, 3:10, 3:11F Megadyptes, 5:523–524 see also Sphenisciformes (penguins); Yellow-eyed penguin Megadyptes antipodes see Yellow-eyed penguin Megafauna, 2:58–59, 2:59F definition, 2:140 examples, 2:140 sampling, 2:140 see also specific megafauna Megamullions, definition, 3:864 Meganyctiphanes norvegica see North Atlantic krill (Meganyctiphanes norvegica) Megaplumes, 2:130 anticyclonic plume eddy, 2:133–134, 2:136F heat flux, 2:132 light attenuation anomalies, 2:133–134, 2:136F rise characteristics, 2:132 temperature anomalies, 2:133–134, 2:136F
see also Hydrothermal plumes; Hydrothermal vent dispersion (from) Megaptera novaeangliae see Humpback whale (Megaptera novaeangliae) Megrim (Lepidorhombus wiffiagonis), 2:377 Meinesz, Vening, 3:83 Meiobenthos, 3:726–731 abundance and diversity, 3:730 collection and extraction, 3:728–729 qualitative samples, 3:729 quantitative samples, 3:728–729 sample types and methods, 3:728 definitions and taxa, 3:726, 3:728F taxa diversity, 3:726, 3:727T distribution, 3:729 geographic distribution, 3:729 large-scale spatial distribution, 3:729 small-scale spatial distribution, 3:729–730 functional roles, 3:730 food for higher trophic levels, 3:730 general roles, 3:730 importance in food web, 3:730 mineralization and nutrient regeneration, 3:730–731 pollution monitoring, 3:730 see also Carbon sequestration by direct injection; Microbial loops habitats, 3:726–727 epibenthic and interstitial meiofauna, 3:726–727 non-sediment habitats, 3:727–728 sediment habitats, 3:726–727 types of meiofauna, 3:727T ubiquitous nature, 3:726 see also Salt marsh(es) and mud flats; Sandy beach biology identification, 3:726 meiofauna and pollution, 3:731 assessment approaches, 3:731 see also Pollution role in food web, 3:726 see also Fish feeding and foraging use in pollution monitoring, 3:726 see also Benthic foraminifera; Copepod(s); Deep-sea fauna; Macrobenthos; Microphytobenthos Meiofauna, 1:350, 1:350F, 1:356, 2:58–59, 2:59F definition, 2:140 examples, 2:140 sampling, 2:140 see also specific meiofauna Mekong River, discharge, 4:755T Melanges, accretionary prisms, 1:31, 1:33, 1:33F Melanitta fusca (velvet scoter) fisheries interactions, 5:270–271 see also Seabird(s) Melanitta nigra (common scoter) fisheries interactions, 5:270–271 see also Seabird(s) Melding scheme, data see Data assimilation, scheme for
(c) 2011 Elsevier Inc. All Rights Reserved.
Mellor-Yamada level-2.5 turbulence closure scheme, 6:198–199 Mellor-Yamada model, 4:210 Ocean Station Papa, 4:215F Melon butterfish (Chaetodon trifasciatus), aquarium mariculture, 3:528–529 Melt ponds, 5:88, 5:172 Meltwater events, bipolar seesaw model and, 3:129–130, 3:130F Member–vagrant hypothesis, in pelagic biogeography, 4:358–359, 4:362 Memorial, Grice, Dr George, 3:279 Mendeleyev Ridge, 1:211 Mentor Current see Peru Current Mercenaria mercenaria (hard clam), currency use, 3:899 Mercury (Hg) anthropogenic, 1:549 in bird feathers, 5:275 emission into atmosphere, 1:198 Northern Hemisphere vs. Southern Hemisphere, 1:198–200 oceanic, 1:195, 1:198–200 oceanic concentrations, 1:198–200 N. Atlantic and N. Pacific waters, 6:101T pollution, 3:768–769 anthropogenic and natural sources, 3:769T distribution, 3:771T environmental impact, 3:773 Humber estuary, 3:771, 3:772F Minimata Bay (Japan), 1:200 sampling/analysis difficulties, 1:198 seabirds as indicators of pollution, 5:225, 5:275 Merian’s formula, 5:344–345 Meridional distribution, 2:216 Meridional exchange, Weddell Gyre, 6:324 Meridional overturning circulation (MOC), 1:16, 1:17F, 2:20, 2:21, 4:126 Florida Current, Gulf Stream and Labrador Current, 2:554–555, 2:556F general theory for, 4:129–130 instability of, 4:130–131 Merluccidae (hakes), 2:458–460 Merluccius hubbsi see Argentine hake (Merluccius hubbsi) Merluccius merluccius (hake) see Hake (Merluccidae) Merluccius productus (Pacific hake), population, El Nin˜o and, 4:704 Mersa Matruh anticyclonic gyre, 3:718–720, 3:719F, 3:720 Mertz Ice Tongue polynya, 4:540–541 Mesocosms, 3:654–655, 3:654F advantages/disadvantages, 3:655 current experiments, 3:655 limitations, 3:655 placement, 3:655 possible length of study, 3:655
Index reasons for development difficulties of executing controlled experiments, 3:654 possible length of study, 3:654–655 sampling method, 3:655 uses, 3:655 see also Enclosed experimental ecosystems Mesodinium rubrum, 2:318–319 Mesopelagic fish(es), 3:748–754 adaptations, 3:751–754 camouflage, 3:751 diurnal migration, 3:753 eye morphologies, 3:751 see also Fish vision influence of light stimuli, 3:751 metabolic rates, 3:753–754 mouth morphologies, 3:751 muscles, 3:752–753, 3:753F ventral light organs, 3:752 behavior, 3:750–754 diurnal migration, 3:750–751 daytime depths, 3:751 influence of light, 3:751 orientation in water column, 3:750 research difficulties, 3:750 definition, 3:748 distribution, 3:748–749 diversity, 3:748, 3:748T, 3:749F general morphologies, 3:748–749, 3:749F history of scientific interest, 3:748 life histories, 3:749–750 early life stages, 3:749–750 fecundity and mortality, 3:749 geographical variations, 3:750 growth and age composition, 3:750 growth patterns, 3:750 protandry, 3:750 sexual dimorphism, 3:750 size, 3:749 spawning seasons, 3:749–750 major groups, 3:751, 3:752T see also Fiordic ecosystems; Pelagic fish(es) Mesopelagic zone, 2:160, 2:216 Mesophilic microbes Archaea, 3:134 Beggiatoa, 2:77 definition, 2:73–75 diversity, 2:77 habitats, 2:73–75, 2:77 microbial mat communities, 2:77, 2:77F sulfur filament production, 2:77 Mesoplodon densirostris (Blainville’s beaked whale), 3:646, 3:647F, 3:648–649 Mesoscale, oceanic, 2:610 Mesoscale eddies, 3:755–767, 3:755F baroclinic state, 3:759–760 barotropic state, 3:759–760 Brazil/Malvinas confluence (BMC), 1:427–428, 1:428F circulation, 3:756 cold, appearance of, 3:760 fluid packet tracer mixing, 5:137
formation, 3:760–763, 3:762F forward numerical models, 2:610 geography of, 3:756–759 Gulf Stream System, 2:557, 2:559F heat transport, 3:118–119, 3:119 importance, 3:756 Mediterranean Sea circulation Algerian eddies, 3:717, 3:721 Corsican eddies, 3:721 modeling, 5:134–135 modelling techniques, 3:763, 3:766F nutrient transport, Sargasso Sea, 5:481, 5:483F orbiting satellites, 3:756, 3:756–757, 3:757F physical properties, 3:762 horizontal structure, 3:763 potential vorticity, 3:763 size, 3:763 vertical structure, 3:763 research direction, 3:767 turbulent dynamics, 2:610 warm, appearance of, 3:760 Mesoscale jets, 5:481 meandering, simulation, 5:481, 5:482F 3D dynamical models, 5:481, 5:482F Mesoscale patchiness, 5:481 implications, 5:481 Mesoscale processes physical–biological interactions, 5:481 small-scale patchiness models, 5:479–481 Mesoscale weather models, application of coastal circulation models, 1:579 Mesotidal estuaries, 2:299–300, 2:300–301 Mesotrophic water, penetrating shortwave radiation, 4:382 Mesozoic, 4:319 carbon releases, 3:792 Late, paleo-ocean modeling, 4:303 temperature gradients, 4:319 see also Paleoceanography Messian Rise Vortex (MRV), 2:5 Metadata, bathymetric, 1:301–302 Metal(s) atmospheric deposition, 1:239–240, 1:239T benthic exchange, 4:492–493 chemical sensors, 1:13 electrodes see Electrodes heavy see Heavy metals pollution see Metal pollution transition see Transition metals Metal complexes inorganic, 6:103 organic, 6:103 Metalliferous, definition, 1:268 Metalliferous muds, 3:890 Metalloenzyme, definition, 6:85 Metalloid elements antimony see Antimony arsenic see Arsenic germanium see Germanium as oxyanions, 3:776–783 chemical speciation, 3:776
(c) 2011 Elsevier Inc. All Rights Reserved.
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selenium see Selenium tellurium see Tellurium see also Trace element(s) Metal pollution, 3:768–775 anthropogenic inputs, 3:769–770, 3:769T distributions, 3:770–771 in coasts, 3:771 in estuaries, 3:771 local hydrodynamics, 3:770 in North Atlantic Ocean, 3:771–772 particle–water interactions, 3:770–771 environmental impact, 3:772–773 human health, 3:773–774 natural inputs, 3:769–770, 3:769T particulate metals, 3:768F, 3:770 see also specific metals Metamorphic rocks, magnetism, 3:481 Metastable, definition, 1:268 METEOR Expedition, 1:488 Meteor Expedition, 4:296, 5:411, 5:417 sediment core collection, 4:296, 4:297F Meteoric ice, 5:157 Meteoric water, definition, 5:557 Meteorite impacts, abrupt climate change and, 1:5 Meteorological measurements by satellite see Satellite measurements by sensors see Sensors for mean meteorology Meteorological models, use in satellite altimetry, 5:58 Meteorological satellites, 5:75 Meteorological sensors, moorings, 3:922–923 Meteorological tides see Radiational tides Meteorological tsunamis, 5:349 Meteorological variables, 5:375 Methane (CH4), 1:147T absorptiometric sensor, 1:13 accretionary prisms, 1:34 air–sea transfer, 1:163T, 1:166–167 atmospheric concentration, historical, 3:797 atmospheric sources and sinks, 1:167F, 3:4, 3:7, 3:110 estuaries, gas exchange in, 3:3–4, 3:3T as greenhouse gas, 3:786 historical emissions, 3:796–797 drivers, 3:797 oxidation, estuaries, 3:4 reduction in pore water, 4:566T released from hydrates see Methane hydrate(s) surface water supersaturation, 1:165T see also Methane hydrate Methane hydrate(s), 3:784F Blake Ridge, 3:784, 3:785 composition, 3:784 deposit stability, 3:790F, 3:792, 3:792–793 detection, 3:784 bottom simulating reflectors (BSR), 3:784
540
Index
Methane hydrate(s) (continued) dissociation (methane release), 3:784, 3:787F climatic effects, 1:511, 1:518, 3:784–789 deglaciations, 3:785–786, 3:786, 3:787 feedback loop model and, 3:786–787, 3:787F long-term record of, 3:787–788 rapid climate change, 3:785–787 global warming models and, 3:785 from methane hydrate reservoirs, 3:796–797 mode of, 3:785 from permafrost, 3:785–786, 3:786, 3:787F slumping and, 3:785, 3:787F distribution in reservoirs, 3:793–794 quantification, 3:794 geophysical heat flow and, 3:48 global carbon cycle and, 3:788, 3:789 mechanical strength behavior, 3:785 methane trapped in, estimation of, 3:784–785 paleoceanographic research, 4:299 Paleocene-Eocene Thermal Maximum and, 4:323 shallow-water reserves, 3:793 sites of occurrence, 3:784 slide headwall and excess pore pressure, 3:796 slope instability regions, 3:795–796 stability, 3:784–785, 3:788 deposits, 3:790F, 3:792, 3:792–793 pressure dependency, 3:785, 3:788 temperature dependency, 3:785, 3:788 submarine slides and, 3:790–798 evidence for causal relationship, 3:795–796 extent on continental margins (largest), 3:791F triggering mechanism, 3:795–796 timing of development, 3:788–789 see also Hydrate stability zone; Methane (CH4); Paleoceanography, climate models Methanococcus jannaschii, (archaea), 2:77–78 Methanogenesis, 1:166 Methanogens, 1:166 lipid biomarkers, 5:422F Methanopyrus (archaea), 2:77–78 Methanotrophs, 1:166 Methyl bromide circulation of, 1:162F diffusion coefficients in water, 1:147T Methylgermanium compounds, 3:780, 3:780F, 3:783 Methyl iodide, photochemical production, 4:419–420 Methyl mercury in bird feathers, 5:275–276 feather assays, 5:275 Methyl metallates, 6:103
Methyl nitrate, photochemical production, 4:419–420 METOP satellites, 5:203 Mexico, 6:192–193 water, microbiological quality, 6:272T Mexico, Gulf of see Gulf of Mexico (GOM) Mezada, 4:770F MF see Midfrequency band (MF) Mg/Ca see Magnesium/calcium ratio Michaelis-Menten kinetics, 6:80 Microalga(e), definition, 3:574 Microbead thermistors, 5:387 Microbes definition, 2:140 sampling, 2:140 species diversity, 2:140, 2:144–145 see also Bacteria; specific microbes Microbial decomposition, large particles, 4:336 Microbial loops, 3:799–806, 3:800–802, 3:801F definition, 3:799 effect on plankton communities, 3:656, 3:662 food web transfers, 3:802–803 early understanding, 3:802 microbes as prey, 3:803 microbial contributions to plankton energy flows, 3:802–803 future research, 3:805 importance in pelagic food webs, 4:21 nutrient cycling, 3:803–804 bacteria–phytoplankton competition, 3:803, 3:803F primary function of microbial food web, 3:803 organization of microbial food webs, 3:800–802, 3:801F dissolved organic matter (DOM), 3:800–801 planktonic organisms included, 3:802 predator–prey size relationships, 3:801–802 regional patterns and variations, 3:804–805 average concentrations, 3:804 bacterial abundance and biomass variability, 3:804, 3:805T bacterial production estimates, 3:804–805 effects of plankton blooms, 3:804 see also Phytoplankton blooms latitudinal variations, 3:804 research discoveries misclassification of organisms, 3:800 mixotrophy, 3:800 Prochlorococcus spp., 3:800 Synechococcus spp., 3:799–800 research history, 3:799–800 importance of viruses, 3:800 inadequacy of early methods, 3:799 underestimates of primary production, 3:799 research methods analysis of ATP, 3:799
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autoradiography, 3:799 electron microscopy, 3:800 epifluorescence microscopy, 3:799 flow cytometers, 3:800 fluorescent staining methods, 3:800 respiration measurements, 3:799 role of meiobenthos, 3:730–731 see also Bacterioplankton; Primary production distribution; Primary production measurement methods; Primary production processes Microbial mats, 2:73–75, 4:390 see also Bacterial mats Microbreaking, 1:431 Microbubbles, 1:442 Microconductivity probe, 2:294, 2:294F Microcosms see Enclosed experimental ecosystems Microcrustacea, thermal discharges and pollution, 6:14, 6:14–15 Microelectrodes, sensor landers, 4:489, 4:490F Microfauna, 1:350, 1:350F, 1:356 Microfossil assemblages, as productivity proxies, 5:333, 5:337–338, 5:338F Micromesistius poutassou (blue whiting) see Blue whiting (Micromesistius poutassou) Micrometeorological flux measurements, 5:382–384, 5:383F heat see Heat flux moisture, 5:382, 5:388 see also Hygrometers momentum see Momentum flux measurements sensors, 5:382–390, 5:384–386 frequency response, 5:384, 5:389 performance degradation, 5:384, 5:384F state-of-the-art, 5:389, 5:389F see also Sensors for mean meteorology; Turbulence sensors see also Air–sea gas exchange Micromonas pusilla alga, 3:558–559 Micronekton, 4:1–7 bioluminescence, 4:3–5 adaptations, 4:5 methods of production, 4:4–5 uses, 4:5 distributions, 4:1 biology and morphology, 4:1 species variations, 4:1 diurnal vertical migrations, 4:3 adaptive significance, 4:3 biological pump, 4:3 migration theories, 4:3 biomass extent, 4:3 role of sunlight, 4:3 sound-scattering layers, 4:3, 4:5F species variations, 4:3, 4:5F food habits, 4:5–6 deep-water food paucity, 4:5–6 midwater vs. deep-water nekton, 4:5–6 predator avoidance, 4:6
Index life history, 4:5 finding a mate, 4:5 life cycle, 4:5 reproductive patterns, 4:5 mesopelagic examples, 4:4F midwater micronekton, 4:1–3 distribution, 4:1–3 diurnal vertical migration, 4:3 position in food webs, 4:2F taxonomic groups included, 4:1 Microorganisms, 2:58–59 Micropaleontology, 4:298 Microphytobenthos, 3:807–814 common genera, 3:807T depth, oxygen and production, 3:810F description, 3:807 distribution and biomass, 3:811–812 large-scale heterogeneity, 3:812 influence of sediment properties, 3:812 intertidal mudflats, 3:812 subtidal habitats, 3:812 seasonal variations, 3:812 small-scale heterogeneity, 3:811–812 temporal variation, 3:812 EPS production and sediment biostabilization, 3:811 extracellular polysaccharide production, 3:811 sediment biostabilization, 3:811 functions, 3:807 light penetration and photosynthesis, 3:809–811 diurnal vertical migration, 3:810–811 irradiance gradients, 3:810 light sensitivity, 3:810 nutrient cycling, 3:813–814, 3:813F denitrification, 3:813–814 effect of biofilms, 3:813 see also Microbial loops; Nitrogen cycle nutrient limitation, 3:812–813 effect on photosynthesis, 3:812–813 effect on species composition, 3:813 influence of sediment properties, 3:812 photosynthesis, 3:808–809 diurnal vertical migration, 3:810–811 impact of light penetration, 3:810 production rates, 3:808, 3:808T photosynthesis measurement techniques, 3:808, 3:808F bicarbonate uptake, 3:808–809 chlorophyll a fluorescence, 3:809, 3:809F oxygen exchange, 3:808–809 oxygen production, 3:809 primary production, 3:808–809 effects of temperature, 3:811 tidal differences in temperature, 3:811 variability by biomass and irradiance, 3:810 see also Primary production measurement methods response to nutrients, 3:812–813
types, 3:807 epipelic biofilms, 3:807 see also Salt marsh(es) and mud flats epipsammic assemblages, 3:807–808 see also Sandy beach biology influence of sediment properties, 3:807 see also Benthic boundary layer (BBL); Marine mats; Phytobenthos Microplankton, 3:805 Microplates, 4:601–603 definition, 4:601–602 evolution, 4:602–603, 4:603 deformation, 4:603 lithospheric transfer, 4:603 formation, 4:601, 4:603, 4:603–604 duelling propagator system, 4:601, 4:603 plate motion, 4:604, 4:604F plume-related forces, 4:604 rift propagation, 4:603, 4:604F superfast seafloor spreading rates, 4:604 transform faults, 4:603, 4:604F geometry, 4:602–603 circular shape, 4:603 dual spreading centers, 4:602 pseudofaults, 4:603F roller-bearing model, 4:603, 4:603F location, triple-junctions, 4:601–602 rotation, 4:602–603, 4:603F Euler pole, 4:603, 4:603F stable growing, 4:601–602 see also Easter microplate; Juan Fernandez microplate; Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge tectonics, volcanism and geomorphology; Propagating rifts and microplates; Spreading centers Microscale data, from Marlin, 2:293, 2:294F Microscale wave breaking, 1:151 Microseismicity hydrothermal systems and, 3:849–850 tidal forces and, 3:848–849 Microseism noise, 1:54 Microstomus kitt (lemon sole), 2:376 Microstructure data from Marlin, 2:293, 2:294F salinity, 1:712F temperature, 1:711 thermohaline staircase, 2:164 Microstructure profilers, 1:434, 2:296 Microtag injections, fishery stock manipulation, performance monitoring, 2:533 Microtidal estuary, 2:299–300, 2:300 Microwave backscattering, 5:202–203 see also Scatterometry Microwave data, atmospheric interference, 5:81, 5:83 Microwave humidity sounder (MHS), 5:207
(c) 2011 Elsevier Inc. All Rights Reserved.
541
Microwave measurements, satellite remote sensing of SST, 5:93 Microwave optical depth, 5:128, 5:130 Microwave radar, 5:58 Microwave radiometers, 1:144, 5:93 infrared radiometers vs, satellite remote sensing of SST, 5:93 low-noise, 5:127 Microwave radiometry, 5:70, 5:127, 5:129 Microwave salinometers, 1:145–146 proposed space instrument for SSS, 1:145–146 sea surface salinity measures, 1:145 tracer of water mass movement, 1:145, 1:145F see also River inputs; Salinity, satellite remote sensing Microwave scanning radiometer, 4:543, 5:82, 5:206 Microwave scattering, sea surface, 5:202–203 Microwave sensing, freshwater flux, 5:207–208 Mid-Arctic Ridge, earthquakes and acoustic noise, 1:99 Mid-Atlantic Bight biomass (observed/simulated), 4:727, 4:728F coupled biophysical models, 4:727 first version, 4:727 front structures, 5:398 physical-biogeochemical model, curvilinear grid, 4:726, 4:726F plankton regional circulation model, 4:726, 4:726F regional models, 4:727 Mid-Atlantic Ridge (MAR), 3:841F, 3:852F, 3:867–868 axial morphology, 3:855–856 crustal thickness, 3:858, 3:877, 3:878F deep-sea ridges, microbiology, 2:76 diking, 3:846 faulting, 3:864 ‘hot spots’, 3:877 hydrothermal vent locations, 3:134F, 3:166F internal tidal mixing, 3:256–257 lead-210 profile, 5:329–330, 5:329F magma composition, fractional crystallization, 3:821–822 see also Mid-ocean ridge geochemistry and petrology manganese nodules, 3:488–489 MORB composition, 3:818T, 3:822–823, 3:823F near-ridge seamounts, 5:295–296, 5:295F radiocarbon profile, 5:329F seafloor and magmatic system, 3:875F seismicity, 3:842–843, 3:843F seismic structure axial magma chamber (AMC), 3:830–832 layer 2A, 3:828–829, 3:834F Moho, 3:832
542
Index
Mid-Atlantic Ridge (MAR) (continued) shrimp, 3:139 topography, 3:853F, 3:877, 3:878F tracer release experiment, 2:123, 2:125F, 2:126F turbulent mixing, observations of, 2:123, 2:124F see also Mid-ocean ridge(s) (MOR) Middle East, North Atlantic Oscillation, temperature, 4:67 Middle Ice, 5:141–142 Midfrequency band (MF), 1:57–59 definition, 1:52 wind driven sea surface noise see Winddriven sea surface processes Mid-Ionian Jet (MIJ), 1:748–751, 1:748F Mid-latitude storms, storm surges, 5:532 areas affected, 5:532 North Sea 1953 storm, 5:532, 5:536F prediction, 5:536–537 Mid-Mediterranean Jet (MMJ), 1:748–751, 1:748F, 3:718–720, 3:719F Mid-Ocean Dynamics Experiment (MODE), 3:261 floats, 2:176–177 Mid-ocean ridge(s) (MOR), 3:867–868 crest, hydrothermal vents, discovery, 2:22 degassing, 1:515, 1:520F carbon dioxide, 1:519–520 deviations from axial linearity (DEVAL), 3:875–876 diking, 3:843–847 earthquakes, 3:841–843 geochemistry see Mid-ocean ridge geochemistry and petrology magnetic anomalies, 3:481 asymmetry, 3:484–485 mantle convection and lithosphere formation, 3:867–880 mantle flow, 3:868–869 mantle melting, 3:869–872 mapping, data resolution requirements, 1:299T melt transport to ridge axes, 3:872–874 morphological variability, 3:872–874, 3:874–879 morphology, 3:870F overlapping spreading centers, 3:875 petrology see Mid-ocean ridge geochemistry and petrology sea level fall and, 5:187, 5:188F, 5:189 seismicity, 3:837–851 technology to measure, 3:838, 3:838F TIDAL FORCES AND, 3:845F tidal forces and, 3:845F seismic structure see Mid-ocean ridge seismic structure spreading rate and earthquake magnitude, 3:841 tectonics/volcanism see Mid-ocean ridge tectonics, volcanism and geomorphology trace metal isotope ratios, 3:457T
Mid-ocean ridge basalt (MORB) composition, 3:817–820 D-MORB (depleted MORB), 3:819–820 elemental abundance, 3:819–820, 3:820F E-MORB (enriched MORB), 3:818T, 3:819–820, 3:819F, 3:822–823 fractional crystallization, 3:817, 3:819F, 3:820F light rare earth elements (LREE), 3:819–820, 3:820F low potassium tholeiites, 3:817, 3:818T N-MORB (normal MORB), 3:818T, 3:819–820, 3:819F, 3:820F, 3:822–823, 3:823F oceanic island basalts (OIB), comparison with, 3:819–820 subaxial magma chamber, 3:817, 3:819F T-MORB (transitional MORB), 3:819–820 large igneous provinces vs., 3:218, 3:225 mineralogy, 3:820–821 chemical alteration, 3:820–821 cooling rates, 3:820 fractional crystallization, 3:820 holocrystalline gabbros, 3:820 melt composition, effect of, 3:820 metamorphism, 3:820–821 mid-ocean ridge lava, 3:820 texture variations, 3:820 see also Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge seismic structure; Mid-ocean ridge tectonics, volcanism and geomorphology; Propagating rifts and microplates; Seamounts and off-ridge volcanism Mid-ocean ridge crest, hydrothermal vents, discovery, 2:22 Mid-ocean ridge geochemistry and petrology, 3:815–825 chemical variability, 3:821–822 fast-spreading ridges, 3:821 fractional crystallization, 3:821 ridge depth and crustal thickness, 3:823, 3:824F slow-spreading ridges, 3:821 composition see Mid-ocean ridge basalt (MORB) global variability, 3:822–824 chemical characteristics, 3:823, 3:824F E-MORB composition, 3:818T, 3:822–823 global array, 3:823 local trend, 3:823, 3:824F N-MORB composition, 3:818T, 3:822–823, 3:823F primary melts, 3:823 spreading rates, 3:822–823, 3:823F local variability, 3:821–822 enrichment, 3:822, 3:822F fast-spreading ridges, 3:821–822
(c) 2011 Elsevier Inc. All Rights Reserved.
fractional crystallization, 3:821 liquid line of descent (LLD), 3:821, 3:821F slow-spreading ridges, 3:821–822 magma generation, 3:816–817 differentiation, 3:817 magma flow mechanisms, 3:816–817, 3:822 mantle melting, 3:816–817, 3:822, 3:823 modification processes, 3:817 primary melts, 3:816–817, 3:818T spreading rate, 3:822 mineralogy of MORB see Mid-ocean ridge basalt (MORB) ocean floor volcanism and crustal construction, 3:817 axial summit trough, 3:819F cooling rates, 3:817 intrusive magma formations, 3:817, 3:819F lava formations, 3:816F, 3:817, 3:819F mush zone, 3:819F, 3:820 near-axis seamount formation, 3:817 oceanic crust, 3:817 off-axis volcanism, 3:817, 3:819F seismic layers, 3:817, 3:819F transform faults, 3:817 see also Mid-ocean ridge tectonics, volcanism and geomorphology; Seamounts and off-ridge volcanism see also Mid-ocean ridge seismic structure; Mid-ocean ridge tectonics, volcanism and geomorphology; Propagating rifts and microplates; Seamounts and off-ridge volcanism Mid-ocean ridge seismic structure, 3:826– 836 axial magma chamber see Axial magma chamber (AMC) East Pacific Rise see East Pacific Rise (EPR) Juan de Fuca Ridge see Juan de Fuca Ridge Mid-Atlantic Ridge (MAR) see MidAtlantic Ridge (MAR) Moho, 3:832–833 characteristics, 3:832, 3:832–833 P-wave velocities, 3:832 ridge axis discontinuity (RAD), 3:827, 3:829F, 3:830, 3:832 seismicity, see also Mid-ocean ridge(s) (MOR) seismic layer 2A see Seismic layer 2A seismic techniques, definition, 3:826 spreading rate, variation with, 3:833–836 axial magma chamber see Axial magma chamber (AMC) crustal formation, 3:833–834 layer 2A, 3:834, 3:834F see also Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge tectonics, volcanism and
Index geomorphology; Seamounts and off-ridge volcanism; Seismic structure Mid-ocean ridge tectonics, volcanism and geomorphology, 3:852–866 abyssal hills see Abyssal hills axial high, definition, 3:852 axial morphology, large-scale variations in, 3:854–858, 3:854F, 3:857F axial depth profile, 3:854, 3:854F, 3:857F axial magma chamber (AMC), 3:854–855 cross-sectional area (axial volume), 3:854, 3:855 crust thickness, 3:855–856 East Pacific Rise, 3:856 hydrothermal vents, 3:855 magma supply, 3:852, 3:854, 3:854–858, 3:854F, 3:857F mantle upwelling, 3:855–856, 3:857F, 3:858 measurement methods, 3:855–856 Mid-Atlantic Ridge (MAR), 3:855–856 segmentation, 3:854, 3:854–858, 3:854F, 3:855T, 3:856F, 3:857F, 3:858, 3:859F definition, 3:852–853 slow-spreading ridges, 3:855–856 volcano distribution, 3:854 see also Ridge axis discontinuity (RAD) axial neovolcanic zone, ridge morphology, 3:858–862 axial summit trough, 3:860 axial volcanic ridges, 3:860–861 definition, 3:853F, 3:859–860 dikes, 3:862 eruption frequency, 3:862 fast-spreading ridges, 3:860 fissures, 3:862 magma supply, 3:862 slow-spreading ridges, 3:860–861 faulting, 3:862–866 along-axis variations, 3:863F, 3:864 causes, 3:862–863 crustal extension, 3:862–863, 3:864, 3:864F East Pacific Rise, 3:864 fast-spreading ridges, 3:862F, 3:865F fault trends, 3:863 grabens, 3:862–863, 3:865–866, 3:865F, 3:866F high inside corner, 3:864, 3:864F lithosphere thickness, 3:862–863, 3:863–864 magma supply, 3:864 mantle coupling, 3:864 megamullions, definition, 3:864 Mid-Atlantic Ridge, 3:864 plate motion indicator, 3:863 ridge axis discontinuities, 3:864 seismicity, 3:864 slow-spreading ridges, 3:855–856, 3:862F, 3:863–864, 3:863F, 3:864F
transform faults, 3:853F, 3:854, 3:864 volcanic growth faults, 3:865–866, 3:865F see also Ridge axis discontinuity (RAD) hydrothermal vents see Hydrothermal vent chimneys; Hydrothermal vent deposits; Hydrothermal vent fluids; Hydrothermal vent fluids, lava, 3:862 magma supply see Magma supply; Midocean ridge geochemistry and petrology magnetization, 3:854, 3:856 mantle plumes, 5:296–297 see also Mid-ocean ridge seismic structure; Propagating rifts and microplates Midwater otter trawl nets, 2:538, 2:538F Midwater pair trawl nets, 2:538 Midwater trawl nets, 2:538, 2:538F, 5:515, 5:517 Midway, aerosol concentrations, 1:249T Mie scattering, 4:9–10 Mie theory, spectral scattering, 6:110–111 Migrating overlapping spreading centers, 4:601 Migration, 2:428 cod, 2:406, 2:406F crustaceans, 1:703 definition, 3:596, 3:603 demersal fishes, 2:461–462 eels, 2:212–213 green turtles, 2:408–409 herring, 2:405, 2:405F, 4:364–365, 4:365F, 4:366F Japanese ayu, 2:404 marine mammals, 3:596–604, 3:613 plaice, 2:406–407, 2:408F, 2:409F salmon, 2:403 salmonids, 5:32, 5:33F, 5:34F, 5:35F, 5:36F seabird see Seabird migration seabirds, 5:279 tunas, 2:404–405 walleye pollock, 2:405–406 see also Circatidal vertical migration; Contranatant migration; Daily vertical migration; Denatant migration; Diurnal vertical migration; Fish horizontal migration; Fish vertical migration; Horizontal migration; specific species MIJ (Mid-Ionian Jet), 1:748–751, 1:748F Milankovich cycles, 1:1 Milankovitch, Milutin, 4:504–505 ice ages theory, 4:504–505 Milankovitch scale sea level variations, 5:187 see also Sea level changes/variations Milankovitch variability, 3:886–887, 4:504–513 summer solstice insolation, 4:509, 4:511F Miles theory (MT), 6:305, 6:305F
(c) 2011 Elsevier Inc. All Rights Reserved.
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Millenium Ecosystem Assessment, 1:604 Millennial-scale climate variability, 3:881–889, 3:881F Heinrich events, 3:883–885 history, 3:881–883 Holocene, 3:886 mechanisms, 3:886–888 other proxies, 3:885–886 proxy agreement, 3:887 proxy record examples, 3:883 Milligal (mGal) (unit for gravity anomaly), 3:80 Million year scale sea level variations, 5:179, 5:192F, 5:193 estimation, 5:192, 5:192F research, 5:193 see also Sea level changes/variations Minamata Bay (Japan) mercury pollution, 1:200 metal pollution, 3:773–774 Mindanao Current (MC), 5:312–313 flow, 4:287F, 4:289–290 see also Pacific Ocean equatorial currents Mindanao Eddy, 4:287F Mindanao Undercurrent (MUC), flow, 4:287F, 4:290–291 Mineral(s) clay see Clay minerals detrital, 3:890 extraction of authigenic minerals see Authigenic minerals extraction see also Mineral resources; Trace element(s); specific minerals Mineral dust aerosol, 1:120–121 deposition, 1:252–254 global distribution, 1:121–122, 1:122T Mineral resources, 3:437–438 continental shelf minerals, 3:437–438 Convention on the Continental Shelf, 3:437 International Seabed Authority payments, 3:437–438 territorial sea production, 3:437 deep seabed minerals, 3:437, 3:438 International Seabed Area, 3:438 parallel system of mining, 3:438 polymetallic nodules, 3:438 revised mining regime, 3:438 Law of the Sea and, 3:437–438 offshore deposits, 3:437 see also Manganese nodules; Oil Mining, seabed, see also Mineral resources Minke whales habitat, 1:280 lateral profile, 1:278F see also Baleen whales Minnows (Phoxinus spp.), 2:436–437 Miocene d18O records, 1:508F, 1:510F, 1:511, 1:512 see also Cenozoic Mirounga angustirostris (Northern elephant seal), 3:629–630, 4:135
544
Index
Mirounga leonina (Southern elephant seal), harvesting history, 5:513 MIR submersibles, 6:257T dive duration, 6:265 Mir I and Mir II (Russian submersibles), 3:505–506, 3:509–511, 3:510–511, 3:510F Mississippi River debris flows, 5:458F dissolved loads, 4:759T Intra-Americas Sea (IAS), 3:290–291, 3:292–293, 3:293F river discharge, 4:755T sediment load/yield, 4:757T Mississippi River delta, USA, coastal erosion, 1:588 Mitochondrial DNA, 2:216 Mixed later modeling, 5:130 Mixed layer Arctic, acoustics, 1:95 buoyancy flux gradient, 4:214 cosmogenic isotope concentrations, 1:681T depth definition, 6:219–221 hurricane Lili, 6:195T hurricanes Isidore and Lili, 6:201F North Pacific, regime shifts, 4:711–712 thermal expansion coefficient and, 6:219–220, 6:220F Ocean Station Papa, 4:213F one-dimensional models analytical, 4:209 bulk models, 4:209 K-profile parametrization, 4:209–210 Ocean Station Papa, 4:213F upper, 2:98, 6:217–218 see also Euphotic zone; Surface mixed layer Mixed layer temperature, 6:217F, 6:337– 345 barrier layers and thermocline heat flux, 6:222 deepening, 6:192 depth, 6:164, 6:341 global distribution, 6:168F seasonal variation, 6:342 drag coefficient, 6:341 hurricane Gilbert, 6:199F Loop Current, hurricane response, 6:200 mixing and, 6:217–218 drivers, 6:337 momentum flux, 6:341 Coriolis force and, 6:341 range, 6:163 seasonal variation, 6:342 Eastern Equatorial Pacific, 6:342–343 surface heat flux, 6:337 surface layer and, 6:220–221 thermal and haline buoyancy fluxes and, 6:341–342 wind and buoyancy-forced processes, 6:337, 6:338F wind forcing, 6:341–342 see also Upper Ocean
Mixing dark, definition of, 2:613 deep ocean passages, 2:570 dominant processes, 2:288 estimation, 2:288–298 direct eddy correlation, 2:291–292 energy quantification, 2:294–296, 2:296–297 Gregg-Henyey method, 2:296–297 heat fluxes in/out, 2:290, 2:291F large-scale, 2:290, 2:297 microscalars, 2:292–294 microscale, 2:291–292 small-scale, 2:291–292 Thorpe scales, 2:296 fiords, 2:355 internal tides, 3:258, 3:264–265 internal waves, 3:266, 3:271, 3:272F nepheloid layers, 4:12 non-rotating gravity currents, 4:59–60, 4:61, 4:62, 4:63 ocean, energetics see Energetics of ocean mixing quantification, 2:289 advection-diffusion, 2:289 turbulent temperature gradient variance, 2:289–290 turbulent see Turbulence; Turbulent mixing upper ocean, 4:208, 6:23, 6:24 vortical mode generation mechanism, 6:287–288 see also Deep convection; Differential diffusion; Diffusion; Doublediffusive convection; Mixed layer; Open ocean convection; Surface mixed layer; Tidal mixing fronts; Turbulent mixing; Turbulent temperature gradient variance ‘Mixing efficiency’, 3:255 Mixing-length definition, 6:158 hypothesis, 6:158 Mixing ratio, definition, 2:325T Mixing time, global, 3:456 Mixotrophs, 3:805 MIZ see Marginal ice zone MIZEX (Marginal Ice Zone Experiments), 3:202 MLP (multilayer perceptron neural networks), 4:736F MMD (mass median diameter), 1:124, 1:249 MMJ (Mid-Mediterranean Jet), 1:748–751, 1:748F, 3:718–720, 3:719F Mnemiopsis leidyi (a comb jelly), 2:342, 3:18 acoustic scattering, 1:68–69 Black Sea, 4:705 Mn(II)/(III)/(IV), definition, 6:85 MNLS (modified nonlinear Schro¨dinger equation), 4:778 Mobile silica see Opal MOBY (Marine Optical Buoy), 5:119
(c) 2011 Elsevier Inc. All Rights Reserved.
MOC see Atlantic meridional overturning circulation (MOC); Meridional overturning circulation (MOC) MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System), 6:357T, 6:364, 6:365F, 6:366T dual-beam acoustic system, 6:369, 6:370F MOCS (Multichannel Ocean Color Sensor), 1:141–142 MODE see Mid-Ocean Dynamics Experiment (MODE) Models/modeling basin, 4:722T biogeochemical see Biogeochemical and ecological modeling; Biogeochemical models chemical tracers as calibrants, 4:106–107 coastal circulation see Coastal circulation models complexity, 4:113 coupled see Coupled models; Coupled sea ice-ocean models data assimilation see Biogeochemical data assimilation; Data assimilation in models deterministic simulation, 4:722–723 El Nin˜o Southern Oscillation see El Nin˜o Southern Oscillation (ENSO) models forward numerical see Forward numerical models geological, 4:722T global, 4:722T inverse see Inverse models/modeling local, 4:722T matrix see Matrix models N-P-Z (nutrient–phytoplankton–zooplankton), 4:722 one-dimensional see One-dimensional models reference points, circulation, mean and time-dependent characteristics, 2:604 regional see Regional models small scale, 4:722T statistical, 4:722–723 turbulent, 4:722T wind driven circulation, 6:353–354 see also Ocean models/modeling; individual models Moderate Resolution Imaging Spectroradiometer (MODIS), 5:97, 5:205–206 36-band imaging radiometer, 5:97 narrower swath width than AVHRR, 5:97 ocean color sensing, 5:117–118 ocean color sensor, 5:118T polarization errors, 5:121 Modern, definition, 5:464 Modern analog technique (MAT), 2:109–110
Index Modified Atlantic Water (MAW), 1:745–746, 1:746, 3:717, 3:718F pathways, 1:746, 1:748F Modified drift-turbidite systems see Deepsea sediment drifts; Ocean margin sediments Modified nonlinear Schro¨dinger equation (MNLS), 4:778 Modified warm deep water (MWDW), 5:542–543 MODIS see Moderate Resolution Imaging Spectroradiometer (MODIS) Moho (Mohorovic discontinuity), 3:80, 3:869–871, 5:361 definition, 3:819F gradient-change models, 5:362 mid-ocean ridge seismic structure, 3:832–833 characteristics, 3:832, 3:832–833 East Pacific Rise (EPR), 3:832, 3:832–833, 3:834F Mid-Atlantic Ridge (MAR), 3:832 P-wave velocities, 3:832 Mohovia¸iS˙ seismic boundary see Moho Mola mola (sunfish), 2:395–396F Mole-crabs (Emerita spp., Hippa spp.), 5:52F Molecular diffusion scalar mixing, 6:21, 6:23 see also Diffusion Molecular diffusivity (D), definition, 3:7 Molecular noise, 1:53F, 1:60 Molecular phylogeny, 2:216 Molecular recognition element, absorptiometric chemical sensors, 1:10–11 Molecular viscosity, turbulence, 6:20 Moles of carbon, 1:487 Molluscs see Mollusks Molluskan fisheries, 3:899–909 cephalopods, 1:529 depuration facilities, 3:903 detrimental effects, 3:907–908 exploitation history, 3:899, 3:901–903 habitat pollution, 3:899–901 harvesting, 3:899–901, 3:901–903, 3:907–908 mariculture vs., 3:905–907, 3:906F, 3:906T methods/gears, 2:542, 2:543F, 3:901 production, global, 3:905–906, 3:906F management problems, 3:903 regulatory mechanisms, 3:903 processing, 3:903 size selectivity, 3:903 see also Lagoon(s); Phytoplankton blooms Mollusks aggregation, 1:334T bioluminescence, 1:377T, 1:380 bivalve see Bivalves heteropods, 3:14, 3:15F mariculture, 3:536, 3:903–905 feeding, 3:532
fisheries, dependence on, 3:533 location determination, Geographic Information Systems, 3:908 predators, 3:904 problems/risks, 3:536, 3:904, 3:908 production, global, 3:905–906, 3:906F production systems, 3:534 wild harvesting vs., 3:905–907, 3:906F, 3:906T pteropods, 3:14 euthecosomes, 3:15F Gymnoptera, 3:14 Gymnosomata, 3:14, 3:15F Pseudothecosomata, 3:14, 3:15F Thecosomata, 3:14 shells, radiocarbon, 4:638–639 see also Bivalves; specific species Molting process, crustaceans, 1:699, 1:703 Molva dypterygia (blue ling) see Blue ling (Molva dypterygia) Molybdenum (Mo), 3:776, 3:778–779, 3:783 concentration N. Atlantic and N. Pacific waters, 6:101T phytoplankton, 6:76T salinity and, 6:78 seawater, 6:76, 6:76T depth profile, 3:777F metabolic functions, 6:83 oxic vs. anoxic waters, 3:778–779 requirement for primary productivity, 4:586 see also Trace element(s) Momentum conservation/dissipation features in equations, 3:22 upper ocean, general circulation model, 3:20 Momentum equation, general circulation models, 3:20 Momentum fluxes forward numerical models, 2:608 measurements see Momentum flux measurements at sea surface, 3:105–113 accuracy of estimates, 3:110–112 data, sources of, 3:107–108 measuring, 3:105–107 Mediterranean Sea circulation, 3:710, 3:716–717 Red Sea circulation, 4:666, 4:667, 4:675–676 regional variation, 3:108–110 seasonal variation, 3:108–110 transfer coefficients, typical values, 3:107T Weddell Sea circulation, 6:318 Momentum flux measurements, 5:382, 5:385F, 5:386–387, 5:386F direct covariance method, 5:383 eddy correlation, 5:383 longitudinal velocity fluctuations, 5:383, 5:383F, 5:384F
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sensors, 5:386–387 cone anemometers, 5:385 gyro-stabilized systems, 5:387 hot-film anemometers, 5:385 hot-wire anemometers, 5:384 K-Gill anemometer, 5:385–386, 5:385F motion correction, 5:384, 5:387–389 sonic anemometers, 5:386, 5:386F strapped-down systems, 5:387 vertical velocity fluctuations, 5:382–383, 5:383F see also Turbulence sensors Momentum imbalance paradox theory, 6:198 Monachinae (southern phocids), 3:609T, 5:286T see also Phocidae (earless/‘true’ seals); specific species Monachus monachus (monk seal), 2:218 Money cowry see Cypraea moneta (money cowry) Monin-Obukhov depth scale, 6:341 Monin-Obukhov length, 2:356 Monin-Obukhov theory, 4:221–222 Monitoring Bathing Waters (Bartram and Rees, 2000), 6:267 Monkfish (Lophius piscatorius), 2:461 Monk seal (Monachus monachus), 2:218 Monochlorobiphenyls, structure, 1:552F Monodontidae, 3:606–607T Monodon monoceros see Narwhal trophic level, 3:623F see also Odontocetes (toothed whales) Monomethylgermanic acid (MMGe), 3:780, 3:780F Monosaccharides, radiocarbon analysis, 5:426–427 depth profile, 5:427F Monostroma algae, 4:428 Monostroma nitidum algae, 5:322F Monsanto, 1:553 Monsoon(s), 1:728, 1:729F, 3:226, 5:494–495 Asian see Asia astronomical polarity timescale application, 3:30–31 causes and generation, 3:910 effect of continental topography, 3:911 cyclicity, 3:917–918 derivation of word, 1:728, 5:494 equatorial upwelling, 3:917 geologic records, 3:910–911 historical variability, 3:914 history of, 3:910–918 Indian Ocean see Indian Ocean indicators China Sea, 3:914 present, 3:912–913 in sediments, 3:911–912 Indonesian archipelago, 3:237 Indonesian Throughflow and, 3:240–242 surface response, 3:240 transport effect, 3:240
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Index
Monsoon(s) (continued) particle flux variability, 6:1–2 periods, 1:728, 5:494 salinity and, 6:170 seasonal variability Northern Hemisphere, 3:910F and sedimentary record, 3:910 Southeast Asian Seas, 5:306–308 summer (SW), 1:728–730, 1:729F, 3:226, 3:226F, 5:494 teleconnections, 3:917 transition periods, 1:728, 1:730, 3:226–227, 3:227F, 5:494 winter (NE), 1:728, 1:729F, 3:226, 3:226F, 5:494 see also Indian Ocean current systems; Indian Ocean equatorial currents; Somali Current; Wind-driven circulation Monsoonal ecosystems continental margin area, 4:257F, 4:258T continental margins, primary production, 4:259T Monsoon winds, Red Sea circulation, 4:667, 4:667–668, 4:674 Montastrea annularis (boulder star coral), growth rates, ferrochrome lignosulfate effects, 1:673 Monterey Bay autonomous underwater vehicles (AUV) observations, 4:482F ocean field decorrelation, 4:482–483 Monterey Bay Aquarium Research Institute autonomous underwater vehicles, 6:263T remotely-operated vehicles (ROV), 6:260T Montmorillonite formation, 1:266–268 global distribution, 1:267F Moon, tidal energy, 6:26 Moon-Earth system gravity and, 6:33, 6:33F, 6:34F energy loss, 6:38 tides energy fluxes and budgets, 6:38 gravitational, 6:33, 6:33F, 6:34F Moored, automated, serial zooplankton pump (MASZP), 6:364, 6:366F Moored current meters, internal tide observation, 3:261, 3:263F limitations, 3:261 Moored instruments, Weddell Sea circulation, 6:319, 6:321F Moorings, 3:919–931, 4:116–117, 4:116F anchor release, 3:920 buoys, 3:920, 3:923 compliance, 3:923 components, 3:919–922 data transmission, 3:926, 3:928 deployment, 3:928–930 anchor-first, 3:929–930 anchor-last, 3:928, 3:929F designs, comparison of shapes, 3:926F early designs, 3:919
fatigue, 3:925, 3:927 hybrid, 3:925–926, 3:926F hydrophone array, 3:930, 3:930F instrumentation, 3:921 inverse catenary, 3:924–925, 3:924F, 3:925T, 3:926F combination with subsurface design, 3:926F lines bite damage, 3:919 breakage, 3:920 compliance, 3:923 telemetry via, 3:927 termination, 3:920 weight, 3:919 meteorological sensors, 3:922–923 modeling of performance, 3:930–931 observational disadvantages, 3:59 plankton sampling systems, 6:361–364, 6:366F recovery, 3:919, 3:920, 3:921 remote repair, 3:926 sea ice thickness determination, 5:154 semi-taut, 3:923–924, 3:924F, 3:925F, 3:925T subsurface advantages and disadvantages, 3:919, 3:920 design, 3:919–922, 3:921F, 3:922F surface advantages and disadvantages, 3:919 applications, 3:922–923 depth-measurement problems, 3:925 design, 3:922–928 two-dimensional array, 3:931F U-shaped, 3:930, 3:930F see also Current meters MOR see Mid-ocean ridge(s) (MOR) Moraine, geoacoustic properties, 1:116T MORB see Mid-ocean ridge basalt (MORB) Morlaix, Bay of, multidimensional scaling diagram, 4:538, 4:538F Morone saxatilis (striped bass), 2:333 Morris Island, South Carolina, USA, coastal erosion, 1:582, 1:582F MORS optical system, 3:249F see also Ocean optics Mortality exploited fish, population dynamics, 2:182, 2:183F fishing gear-related, unreported catches, 5:3 limitation, demersal fisheries, 2:95 stock enhancement/ocean ranching, 2:530 Mosses, lipid biomarkers, 5:422F MOSS optical system, 3:249F see also Ocean optics Mother-of-pearl (nacre), commercial value, 3:899 Motion, equations, in forward models see Forward numerical models Motors, autonomous underwater vehicles (AUV), 4:475
(c) 2011 Elsevier Inc. All Rights Reserved.
Mottled petrel (Pterodroma inexpectata), 4:591F see also Procellariiformes (petrels) Mountain building, sediment deposition and, 4:139–140 Moving Vessel Profiler towed vehicle, 6:65 Mozambique Current, 1:130F, 1:131, 1:730 MPAs see Marine protected areas (MPAs) MSFCMA see Magnuson–Stevens Fishery Conservation Management Act (MSFCMA), (1976) MSL (mean sea level), storm surges, 5:539 MSVPA see Multispecies Virtual Population Analysis (MSVPA); Multispecies Virtual Population Analysis (MSVPA), fisheries MSY see Maximum sustainable yield (MSY) MT (multiple turnover fluorescence induction), 2:583 Mucopolymers, 1:395–396 Mud acoustics in marine sediments, 1:83T flow, 5:460 Mud banks, 3:38 Muddy coasts, geomorphology, 3:38, 3:38–39 mud banks, 3:38 mud flats, 3:38 sedimentation, 3:38 vegetation, 3:38 Mud flats, 3:38 see also Salt marsh(es) and mud flats Mudstone, 5:454F Mud volcanoes, accretionary prisms, 1:32, 1:32F Mugil (mullet), mariculture, stock acquisition, 3:532 Mugilidae, 2:375 Mu¨ller P, productivity reconstruction, 5:334–335, 5:335F Mullet (Mugil), mariculture, stock acquisition, 3:532 Mullets (Mugilidae), 2:375 Multibeam bathymetric mapping, active sonar images, 5:509, 5:510F Multibeam echo sounders (MBES), 1:299, 1:300 Multibeam sonar, 4:479–480 Multichannel Ocean Color Sensor (MOCS), 1:141–142 Multichannel radiometers, 3:326–327, 3:327F in situ, 3:326 Multichannel seismics, oceanographic research vessels, 5:412 Multichannel seismic surveys (MCS), geophysical research vessels, 5:416 Multichannel streamers, 5:361 Multidimensional scaling (MDS), pollution, effects on marine communities, 4:536, 4:536–537, 4:538F
Index Multidisciplinarity, marine policy, 3:665–666 Multilayer perceptron (MLP) neural networks, 4:736F Multiple Opening/Closing Net and Environmental Sensing System see MOCNESS (Multiple Opening/ Closing Net and Environmental Sensing System) Multiple turnover (MT) fluorescence induction, 2:583 Multiple-use management regimes marine policy, 3:667–668 marine protected areas, 3:667–668 Multisensor Track (MST), 2:51 correlation of data from offset holes, 2:51 measurement of cores, 2:51 Multispecies dynamics, fisheries see Fishery multispecies dynamics Multispecies Virtual Population Analysis (MSVPA), fisheries management, ecosystem perspective, 1:652, 2:507 multispecies dynamics, 2:509–510, 2:510F predation, 2:509–510, 2:510F ‘Multisymplectic geometry’, 3:22 Multivariate methods, pollution, effects on marine communities, 4:533, 4:536–538 Multiyear (MY) ice, 3:191–193, 5:141, 5:170 Arctic, 5:143 thickness, factors affecting, 5:172 Munidopsis subsquamosa (galatheid crab), 3:136F, 3:138, 3:138F, 3:139F Munk, Walter, 2:263–264, 2:617, 4:208 wind driven circulation model, 6:352–353 Munk unit, 4:208 ‘Muro Ami’ fishing, coral destruction, 1:672 Murray, J, 3:488–489 Murre(s) common, 1:171, 5:260–261 climate change responses, 5:260–261, 5:261F migration, 5:244–246 thick-billed, 1:171, 1:173F see also Alcidae (auks) Murrelets migration, 5:244–246 see also Alcidae (auks) Musician seamounts, magnetic anomalies, 3:486–487 Musician seamounts chain, 5:296–297, 5:299F Mussel farms, seaduck interactions, 5:270–271 Mussels (Mytilus) bathymodiolid Bathymodiolus thermophilus, 3:133–134, 3:135, 3:136F, 3:138F symbiosis, 3:153
vent community dynamics, 3:154–155 culling method, 3:903 harvesting, 3:902 thermal discharges and pollution, 6:14 wave resistance, 1:332 see also specific species Mussel Watch Stations, chlorinated hydrocarbons, 1:559F, 1:560 Mustelids, 3:589, 3:605, 3:608T conservation status, 3:608T trophic level, 3:623F see also specific species Mutualism, in seabird foraging, 5:230, 5:233 MW see Mediterranean Water (MW) Mya arenaria (soft-shell clam), 2:332 Mycosporine-like amino acids (MAAs), 3:571 Myctophidae (lanternfishes), 4:1–3 bioluminescence, 1:381–382 polar midwater regions, 4:517 Myctophids (lanternfishes), 2:412, 2:413F MY ice see Multiyear (MY) ice Myoglobin concentrations, marine mammals, 3:583, 3:584T Myomeres, 2:216 Mysid shrimp (Gastrosaccus spp.), 5:52F Mystacocarida, 5:50 Mysticeti derivation of word, 1:276–277 see also Baleen whales (Mysticeti) Myticola intestinalis copepod, 1:650 Mytilid mussel see Bathymodiolus thermophilus (mussel); Mussels (Mytilus) Mytilus see Mussels (Mytilus) Mytilus edulis (blue mussel), 1:330F Mytilus galloprovincialis (Mediterranean mussel), mariculture health issues, 3:536 production systems, 3:534 stock acquisition, 3:532 Myxinidae, 2:375
N N (number of nucleons), definition, 6:242 NAC see North Atlantic Current Nacre (mother-of-pearl), commercial value, 3:899 NADPH, definition, 6:85 NADW see North Atlantic Deep Water (NADW) Nagasaki Harbor, abiki (catastrophic seiches), 5:349 Namibia, fishing policy, regime shifts and, 4:705 Nannacara anomala (cichlid), 2:456F Nanocalanus minor, Lagrangian population simulation, 3:392–393, 3:392F Nanofossil species diversity, Indian Ocean, 3:916F Nanoplankton, 3:805
(c) 2011 Elsevier Inc. All Rights Reserved.
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Nansen, Fridtjof, 1:712, 2:222, 3:207, 6:155 Nansen Basin, 1:211 deep water, 1:219 mean ice draft, 5:152F temperature and salinity profiles, 1:213F, 1:214F, 1:217F Nansen bottles, 1:712 salinity measurements from, 1:713 sampling method, 2:255 Nansen closing net, 6:356–357, 6:358F NAO see North Atlantic Oscillation (NAO) Narcomedusae medusas, 3:10, 3:11F Narragansett Bay, eutrophication, 2:307, 2:308T Narrow beam filter radiometers, 3:324–326 calibration, 3:325 ‘black-body’ strategy, 3:325, 3:325–326, 3:326F, 3:327F chopper systems, 3:324–325 advantages, 3:325 dynamic detector bias compensation, 3:325 rotary, 3:324–325, 3:325F tuning fork, 3:324–325, 3:325F polarization of sea surface reflection as function of view angle, 3:325, 3:326F Narwhal, 3:606–607T exploitation, 3:635, 3:635F movement patterns, 3:599 trophic level, 3:623F see also Odontocetes (toothed whales) NASA (United States National Aeronautics and Space Administration), 5:81 early data, 5:65–66, 5:65F, 5:66F Earth Observing System (EOS), 5:97 missions see Satellite oceanography; see specific missions partnership with field centers, 5:69 satellites see Satellite oceanography; see specific satellites SIR-B and SIR-C experiments, 5:104 Space Shuttle, 5:104 NASA Air-Sea Interaction Research Facility, 1:154T NASA scatterometer (NSCAT), 5:71, 5:203, 5:204T NASA Skylab, 5:129 NASA Team algorithm, 5:83, 5:88F NASCO see North Atlantic Salmon Conservation Organization (NASCO) NASF (North Atlantic Salmon Fund), 5:8 Natal Pulse, 1:132, 1:132F, 1:134, 1:137 see also Agulhas Current Natator depressus (flatback turtle), 5:218–219 see also Sea turtles National Aeronautics and Space Administration, US (NASA) see NASA
548
Index
National Center for Atmospheric Research, 1:696 National Center for Environmental Prediction (NCEP), 1:696, 2:328–329, 3:108 National Control and Admiralty Law, 5:405 admiralty law, 5:405 flags of convenience, 5:405, 5:406T National Deep Submergence Facility (NDSF), 2:22–23 autonomous underwater vehicles (AUV), 6:263T human-operated vehicles (HOV), 6:257T remotely-operated vehicles (ROV), 6:260T vehicles operated by, 2:22–23, 2:27F National Geophysical Data Center (NGDC), 1:300, 5:464 National Ice Center, 3:184 satellite remote sensing, 5:106–107 National Oceanographic and Atmospheric Administration (NOAA), 1:251F, 1:560, 2:173 Coastal Ocean Forecast System (COFS), 1:574F, 1:577–578, 1:578F hydrophone research, 3:839 satellites, 5:94 National Oceanographic Centre, Southampton autonomous underwater vehicles, 6:263T deep-towed vehicles, 6:256T remotely-operated vehicles (ROV), 6:260T National Ocean Sciences AMS facility, 4:642 National Office of Ocean Exploration, remotely-operated vehicles (ROV), 6:260T National Science Foundation, 3:122–123 National Space Development Agency of Japan (NASDA), 5:103 National Tsunami Hazard Mitigation Program, 6:133 NATO, data assimilation for forecasting for, 2:3–5 NATO Undersea Research Centre (SACLANTCEN), geoacoustic properties of seafloor sediments, measurement of, 1:81 sediment cores, 1:81, 1:82F NATRE see North Atlantic Tracer Release Experiment (NATRE) Natural Energy Laboratory of Hawaii Authority (NELHA), 4:172 Natural gas hydrates see Methane hydrate(s) Natural ground cover, river inputs, 4:759 Naturally occurring radioactive material (NORM), 4:629, 4:634 Natural remanent magnetization (NRM), 3:26, 3:26–27 chemical see Chemical remanent magnetization (CRM)
contamination with ‘viscous’ remanence components, 3:27 detrital see Detrital (depositional) remanent magnetization (DRM) thermal, 3:26 Natural resources, policy, marine policy overlap, 3:664T Nauplii, copepods, 1:644F, 1:646 Nautile (French submersible), 3:505–506, 3:509, 3:510F, 6:257T, 6:258F Nautilus (Nautilidae), 1:524 Naval Electronics Laboratory (NEL), 1:93–94 Naval research, optical sensor development and, 6:115 Navicula planamembranacea, 1:633 Navier–Stokes equation, 2:604–605, 3:22, 4:208, 4:723 modified, coastal circulation models, 1:572 surface, gravity and capillary waves, 5:573 turbulence, 6:148 Navigation, 3:509 acoustic, autonomous underwater vehicles (AUV), 4:478 acoustic systems, 3:509 autonomous underwater vehicles (AUV), 4:477–479 using geophysical parameters, 4:478–479 dead-reckoning, 4:478 deep-sea vehicles, 6:265 Differential Global Positioning System (DGPS), 3:509 hyperbolic, 4:478 inertial system, 4:476F, 4:478 spherical, 4:478 Navigation charts, 1:298 Navy Layered Ocean Model, Southeast Asian Seas, 5:313F Navy Remote Ocean Observing Satellite (NROSS), 5:67F, 5:71 NBC see North Brazil Current (NBC) NCC see Norwegian Coastal Current (NCC) NCEP (National Center for Environmental Prediction), 1:696, 2:328–329, 3:108 NDSF see National Deep Submergence Facility NEAFC (North-East Atlantic Fisheries Commission), 5:6 Neap tide, 6:26, 6:34 definition, 6:32 front position and, 5:395F mixing in regions of freshwater influence and, 5:392 Near Cape Farewell, Greenland, mesoscale eddy, 3:759–760 Near-inertial waves, 5:478–479, 6:213 impact on small-scale patchiness, 5:478–479 Near-ridge seamounts, East Pacific Rise (EPR), 5:294, 5:295F
(c) 2011 Elsevier Inc. All Rights Reserved.
Nearshore waters, chlorinated hydrocarbons, 1:557 Nearshore zone, 1:306, 1:311 NEC see North Equatorial Current (NEC) NECC see North Equatorial Countercurrent (NECC) Necho II, Pharaoh of Egypt, 5:409–410 Neil Brown Instrument Systems, Mark III CTD Profiler, 1:714–715 operating conditions, 1:715 Nekton, 4:1–7 definition, 4:1 habitats, 4:1 problems, 4:1 taxonomic groups included, 4:1 see also Micronekton Nekton submersibles, 3:514 Nematodes, 2:59F species diversity, 2:144–145 Nemo, plexiglas hull, 3:515, 3:516 Neobalaenids see Pygmy right whales (neobalaenids) Neocalanus plumchrus copepods, 3:661, 4:458 Neodymium (Nd), 4:655T isotope ratios Cenozoic, 3:462F global distribution, 3:459F, 3:463 incongruent release, 3:465T isotopic composition, 4:654, 4:659–660, 4:660–661 applications, 4:664 distribution in surface waters, 4:660–661, 4:664F long-term tracer properties, 3:456T, 3:463 mean oceanic residence time, 4:659, 4:661, 4:662T river flux, 4:659, 4:662T sea water concentrations surface, 4:654–655, 4:656F vertical profile, 4:658F source materials, 3:457–458 isotope ratios, 3:457T see also Rare earth elements (REEs) Neogloboquadrina pachyderma foraminifer, 1:347 Neolepas zevinae (stalked barnacle), vent fauna origins, 3:156, 3:156F Neomphalus fretterae (archaeogastropod limpet), vent fauna origins, 3:155–156 Neon atmospheric abundance, 4:55T cosmogenic isotopes, 1:679T diffusion coefficients in water, 1:147T ice solubility, 4:56 isotopes, origin of oceans, 4:263, 4:263F phase partitioning, 4:56T Schmidt number, 1:149T seawater concentration, 4:55T Neophocaena phocaenoides (finless porpoise), 2:154, 2:156, 2:159 Neoproterozoic, benthic ecosystems, 1:399
Index Neovolcanic zone, 3:815 see also Axial summit trough Nepers, 1:104 Nepheloid layers, 2:549, 3:690, 4:8–18 Atlantic Ocean, 4:14F benthic, 6:236 bottom, thickness, 4:11 bottom mixed, 4:8, 4:11–12 chemical scavenging, 4:13–15 features, 4:11–12 intermediate, 4:8, 4:16–17 mixing, 4:12 particle concentration decay, 4:12–13 separated mixed-layer model, 4:12 settling, 4:13 sources, 4:15 surface, 4:8 trenches and, 4:17 Nephelometers, 4:8–11 Nephelometric turbidity units (NTU), 6:111 Nephelometry, 6:109–118 definition, 6:109 depth profiles, Rockall Trough, 4:10F new technologies, 6:116–118 scattering sensors, 6:113–115, 6:113F angular configurations, 6:114, 6:114F applications, 6:109, 6:115, 6:115–116, 6:117T naval, 6:115 backscatter, 3:246, 6:115 calibration, 6:114–115, 6:115 deployment, 6:116 measurements, 6:109–110, 6:110 optical rejection, 6:113–114 principles, 6:114 transmissometry vs., 6:109, 6:118 see also Inherent optical properties (IOPs); Ocean optics; Optical particle characterization; Turbulence sensors; Volume scattering function (VSF) Nereus (ROV), 6:260T, 6:263F Nested survey strategy, 6:265 Net(s) gill see Gill net(s) pelagic fisheries, 4:237 see also specific types Net environmental benefit analysis, oil spill response, 4:194, 4:194–195 Net fisheries, rigs and offshore structures effect, 4:750 Netherlands storm surges, 5:532, 5:536F Wadden Sea, seaduck–fisheries interactions, 5:270–271 see also Rhine estuary, The Netherlands Net irradiance (E), 4:381–382 depth vs., 4:382F Net production measurements, 6:93 Sargasso Sea, 6:100T Net systems, zooplankton sampling see Zooplankton sampling Network analysis of food webs, 4:19–24 attention to all parts of web, 4:22
carbon tracers, 4:19 check on productivity estimates, 4:24 C:n:p ratio, 4:19 description of food web, 4:19 estimating long-term changes, 4:22–24 estimating sustainable harvests, 4:21–22 examples of carbon and biomass networks, 4:21 English Channel - Celtic Sea, 4:21, 4:22F Gulf of Mexico, 4:21, 4:23F role of detritus, 4:21 see also Marine snow focus on lower trophic levels, 4:21 history of energy budgets, 4:19–20 division of ecosystems, 4:19–20, 4:20T freshwater lakes, 4:19 North Sea, 4:19, 4:20F number of trophic levels, 4:20 sustainable fish yield estimate, 4:19–20 limitations, 4:22 path of food energy, 4:19 predator–prey interactions, 4:22 quantitative methods, 4:20–21 calculating fish yields, 4:21 carbon balancing, 4:20–21 steady state assumption, 4:20–21 unknown parameters, 4:21 research required, 4:24 size and trophic level, 4:19 units, 4:19 conversion of units, 4:19 see also Carbon cycle; Large marine ecosystems (LMEs); Primary production measurement methods; Upwelling ecosystems Neural networks algorithm optimization for coastal water remote sensing, 4:736, 4:736F paleothermometric transfer functions, 2:111F regime shift analysis and, 4:719–720 Neuse River estuary, nitrogen, atmospheric input, 1:241T Neuston, net samplers, 6:356–359, 6:361F Neutral buoyancy surfaces, 4:25 approximate, 4:29F geometry, 4:26–27 see also Potential density surfaces ‘false’ diffusivities and, 4:29–30 helical nature of trajectories, 4:26–27, 4:27F necessary conditions, 4:26 requirements for existence, 4:26, 4:26F Neutral density, 4:28 Neutral density surfaces, potential density surfaces vs, 4:27–29 Neutral helicity, 4:26 Neutral surfaces and equations of state, 4:25–31 see also ‘Equation of state’ (of sea water); Neutral buoyancy surfaces Neutral tangent planes, 4:25
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549
Neutral trajectories, helical nature, 4:26–27, 4:27F New Bern (North Carolina), sea level changes with Hurricane Bertha, 1:575F New England demersal fisheries, 2:96 New England seamounts, 3:486–487 Newfoundland, 4:127 east, ice-induced gouging, 3:195 sea ice cover and, 5:141 Newfoundland Basin Eddy, 2:560 New Guinea Coastal Current (NGCC) flow, 4:287F, 4:290 see also Pacific Ocean equatorial currents New Guinea Coastal Undercurrent (NGCUC), 5:312–313 flow, 4:287F, 4:290, 4:290–291 see also Pacific Ocean equatorial currents New Jersey continental margin, clay sediments, 1:569, 1:570F Newly formed water masses, 4:127 Newport (Oregon), inundation maps, 6:139F New production, 6:93 Sargasso Sea, 6:100T Newton, Isaac, 6:26 Newtonian fluids, 5:455 Newtonian momentum conservation equations, 2:617 Newtonian relaxation scheme, 2:7 Newton’s Laws second law of motion, 4:723 tides, 6:32 New York Bight, nitrogen, atmospheric input, 1:241T New York Mercantile Exchange, 3:897 New Zealand chinook salmon farming, 5:24 fossil layers, 6:222 Hoplostethus atlanticus (orange roughy) fishery, 4:230 marine protected areas, 1:654 NGCC see New Guinea Coastal Current (NGCC) NGCUC see New Guinea Coastal Undercurrent (NGCUC) NGDC (National Geophysical Data Center), 1:300, 5:464 Nichols, R H, 1:55 Nickel (Ni) atmospheric deposition, 1:254T chemical speciation in seawater, 6:79 concentration N. Atlantic and N. Pacific waters, 6:101T in phytoplankton, 6:76T in seawater, 6:76, 6:76T cosmogenic isotopes, 1:679T depth profiles, 6:77F ferromanganese deposits, 1:260–261, 1:262F global atmosphere, emissions to, 1:242T inorganic speciation, 6:103
550
Index
Nickel (Ni) (continued) manganese nodules, 3:492, 3:493F, 3:494, 3:495 metabolic functions, 6:83 organic complexation, 6:106 riverine flux, 1:254T see also Trace element(s) Niger River delta, Nigeria, coastal erosion, 1:588 Nile River delta, Egypt, coastal erosion, 1:588 Nimbus 3 satellite, 2:173 Nimbus 5 satellite, 5:80, 5:81 Nimbus 6 satellite, 2:173, 5:81–82 Nimbus 7 satellite, 5:67F, 5:68, 5:80, 5:81–82, 5:85F, 5:141 Arctic ice cover, 5:142F Coastal Zone Color Scanner (CZCS), 5:114, 5:118T Niobium (Nb) concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:694 depth profile, 4:695F properties in seawater, 4:688T Nisken bottles, 1:715F Niskin bottles, 2:255 X-type, 2:255–257 Nitrate (NO-3), 5:45 assimilation, 4:44–45 isotope ratios and, 4:43T, 4:46, 4:49F atmospheric, 1:248–249 concentration, 1:249T, 1:250 benthic flux, 4:486–487, 4:488F depth profiles, 4:47F, 6:77F dissolved inorganic carbon and, 4:96–97 global distribution, 4:91F helium isotope ratio anomaly correlation, 6:98F high-nitrate, high-chlorophyll (HNHC) regimes, 3:332–333, 3:332T high-nitrate, low-chlorophyll regimes see High-nitrate, low-chlorophyll (HNLC) regions isotope analysis, 4:40–41 low-nitrate, high-chlorophyll (LNHC) regimes, 3:332–333, 3:332T, 3:333F low-nitrate, low-chlorophyll (LNLC) regimes, 3:332–333, 3:332T nitrite and, simultaneous determination by flow injection analysis, 6:327 photolysis, 4:419 phytoplankton growth reaction, 4:579 profiles, 1:216F Black Sea, 1:405F reduction in pore water, 4:566T sea water concentrations determination, 4:32 impact of phytoplankton growth, 4:680–681, 4:681F phosphate vs., 3:332, 3:332F, 4:681, 4:682–684, 4:683F, 4:686F silicate vs., 3:679F, 4:682, 4:683F, 4:684
surface, 4:35, 4:36F, 4:677, 4:677F deeper water vs., 3:335F, 4:37F, 4:682F Southern California Bight, 4:102 transport, global, 3:305F upwelling zones, 6:227 see also Denitrification; Fertilizers; Nitrification; Nitrogen; Nitrogen cycle Nitrate reductase, 6:82–83, 6:83–84 Nitric oxide (NO) air–sea transfer, 1:163T, 1:165–166 atmospheric sources and sinks, 1:166, 1:166F measurement, 4:32 photochemical production, 4:419 see also Nitrogen cycle Nitrification, 4:33–34, 4:33F, 4:33T, 4:34, 4:34F definition, 3:7 denitrification and, pore water profile, 4:569F estuaries, gas exchange in, 3:4 isotopic effect, 4:43T, 4:45 ‘leaky pipe’ flow diagram, 1:164F nitrous oxide, 1:164 see also Nitrogen cycle Nitrite (NO-2), 1:255–256 accumulation in sea water, 4:37–38 assimilation, 4:44–45 isotope analysis, 4:40–41 isotope ratios, 4:47 nitrate and, simultaneous determination by flow injection analysis, 6:327 oxidation, isotope ratios and, 4:43T primary nitrite maximum (PNM), 4:36–37, 4:38F sea water concentrations, determination, 4:32 see also Nitrogen cycle Nitrite reductase, 6:82–83, 6:83, 6:83–84 Nitrogen (N) anthropogenic emission perturbations, 3:398F atmospheric deposition, 1:240–241 input to oceans, 1:123 see also Dinitrogen (N2) biogeochemical role, 4:40 C:n:p ratios, 4:587 coastal fluxes, 3:399F cycle see Nitrogen cycle denitrification, 3:813–814 see also Denitrification depth profiles, estuarine sediments, 1:544F dissolved see Dissolved nitrogen; Dissolved organic nitrogen (DON); Total dissolved nitrogen (TDN) estuaries, 4:253–254 eutrophication, 2:308, 4:19, 4:459–460 conversion processes, 2:310F fertilizers, application levels, 3:398F fixation see Nitrogen fixation flow, four-compartment planktonic ecosystem model, 5:478, 5:478F
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isotope ratio see Nitrogen isotope ratios isotopes, 4:32 kinetic isotope effect, 4:40 limitation, phosphorus vs., 3:332, 3:332F, 4:408 limiting factor to photosynthesis, 4:19, 4:586, 4:588 ocean gyres, 4:132–133 phytoplankton, chlorophyll prediction, 5:478 as radioisotope source, 1:679 reservoirs see Nitrogen reservoirs river fluxes, 3:397 role in harmful algal blooms, 4:441–442 salt marshes and mud flats, 5:45 sea distributions, 4:32, 4:35–37, 4:36F, 4:37F total organic, 4:50 total oxidised see Total oxidised nitrogen (TON) see also Nitrogen cycle; Nitrogen fixation; Nitrogen isotope ratios; Particulate nitrogen; specific forms of nitrogen Nitrogenase, 6:83–84 definition, 6:85 Nitrogen cycle, 4:32–39, 4:90F analytical methods, 4:32 inputs, 4:42 internal, 4:44–45, 4:44F isotope ratios and, 4:41F, 4:42F, 4:46F see also Nitrogen isotope ratios marine, 4:32, 4:32–34, 4:33F, 4:33T ammonification, 4:33–34, 4:33F, 4:34F denitrification see Denitrification dinitrogen fixation, see also Dinitrogen (N2) ‘new’ vs. ‘regenerated’ nitrogen dichotomy, 4:38, 4:39F nitrification, 4:33–34, 4:33F, 4:33T, 4:34, 4:34F nitrogen assimilation, 4:33F, 4:33T, 4:34 ocean productivity and, 4:38–39, 4:39F units, 4:32 see also Phosphorus cycle ocean processes, 4:44–45, 4:44F outputs, 4:42–44 role of copepods, 1:650 see also Primary production processes Nitrogen dioxide (NO2) absorptiometric sensor, 1:13 photochemical production, 4:419 Nitrogen fixation, 2:323, 4:42 atmospheric input to open ocean, 1:244–245 energy requirements, 6:82–83 estuaries, 4:253–254 isotope ratios and, 4:43T Nitrogen isotope ratios, 4:40–54, 4:40 d15N in organic matter, as productivity proxy, 5:333, 5:337 global budget, 4:49F
Index limitations in determining nitrogen cycling processes, 4:47 measurement procedure, 4:40–41 models, 4:41 process affecting, 4:41–42 sedimentary record, 4:52–53, 4:53F terms/units, 4:40 Nitrogen oxides, pollution, 5:225, 5:277 Nitrogen reservoirs, 4:45–47 ammonium, 4:47–50 dissolved gases, 4:50 dissolved nitrogen, 4:46–47 dissolved organic nitrogen, 4:50 isotopes, 4:52 nitrate, 4:46–47 nitrite, 4:47 particulate nitrogen, 4:50–51 see also specific forms of nitrogen Nitrous oxide (N2O) air–sea transfer, 1:163–165, 1:163T atmospheric sources and sinks, 1:164–165, 1:165F dissolved, 4:50–51 depth profile, 4:51F distribution, 1:164 estuaries, gas exchange in, 3:4–5, 3:5T measurement, 4:32 nitrate and nitrite isotopic analysis, 4:40–41 production, 4:36–37 surface water supersaturation, 1:165T see also Nitrogen cycle NLSW (nonlinear shallow water equations), 6:134–137 NMC (North-east Monsoon Current), 1:733, 3:232–233 NOAA see National Oceanographic and Atmospheric Administration (NOAA) NOAA satellites, 5:94 NOAA/TIROS, 5:67F Noble gases atmospheric abundance, 4:55T ice formation and, 4:55–58 phase partitioning, 4:55T, 4:56 physical properties relevant, 4:56–58 ice solubility, 4:56 phase partitioning, 4:56T seawater concentration, 4:55T tracer applications, 4:55, 4:56–58 see also Argon; Helium; Krypton; Neon; Xenon NOC see National Oceanographic Centre, Southampton Nodularia spumigena, 4:739F ‘Noether invariants’, 3:22 Noise (acoustic) acoustic scintillation thermography, 1:73 Arctic, 1:98–99 anthropogenic, 1:99 spectral profiles, 1:97F deep ocean, 1:107–109, 1:109F marine mammals and see Marine mammals and ocean noise microwave scatterometry, 5:203
ocean color data, 5:121–124 tomography and, 6:44 Noise (statistical), regime shift analysis, 4:718 Nonconservative tracers, 1:683 Nondimensional eddy coefficient, 3:200 Nondimensional surface layer thickness, 3:200 Non-enriched elements (NEEs), 1:124 Nongovernmental organizations (global), 3:277–278, 3:278–279 American Geophysical Union, 3:278–279 European Geophysical Society, 3:278–279 ICSU see International Council for Science (ICSU) see also Ocean Drilling Program (ODP) Nongovernmental organizations (regional), 3:278–279 Nonlinear shallow water (NLSW) equations, 6:134–137 Nonlinear SST (NLSST), 5:92–93 Non-local transport, 4:568–570 Nonmethane hydrocarbons (NMHC) air–sea transfer, 1:160 photochemical oxidation, 1:160 photochemical production, 4:419 production, 1:160F Nonmethyl mercury (NMHg), pollution, 3:768–769 Non-native species impacts on marine biodiversity, 2:146 on marine habitats, 2:146 see also Exotic species Non-opening/closing nets, zooplankton sampling, 6:355, 6:356F Nonpenetrative convection, open ocean convection, 4:220, 4:221F Non Polar Front (Antarctic), biogenic silica burial, 3:681T Nonpolar glaciers, sea level variations and, 5:182, 5:182F, 5:183 Nonriser drilling, 2:37–39, 2:37F Non-rotating gravity currents, 4:59–64 bottom currents see Bottom currents definition, 4:59 downslope, 4:62–63 detrainment, 4:63–64 entrainment, 4:63–64, 4:63 entrainment coefficient, 4:63 head behavior, 4:62–63 into stratified environments, 4:63–64 fronts see Shelf seas; Shelf slope fronts head, 4:59–60, 4:62 structure, 4:59–60, 4:62, 4:62–63 velocity, 4:60, 4:61, 4:62, 4:62–63, 4:63 vorticity, 4:59–60, 4:62 internal waves, 4:60–61 intrusion, 4:59 laboratory experiments, 4:59–60, 4:60, 4:60F, 4:61F, 4:63F mixing, 4:59–60, 4:61, 4:62, 4:63
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see also Upper ocean, mixing processes oil spills, 4:59 power station effluent, 4:59 radial see Radial density currents river surges, 4:59 sewage outfalls, 4:59 spreading inertia-buoyancy stage, 4:61, 4:62 slumping stage, 4:60–61, 4:61F, 4:62 viscous stage, 4:60–61, 4:61–62, 4:62 structure dense layer, 4:59–60, 4:60, 4:60F, 4:61F, 4:63–64, 4:63F head, 4:59–60, 4:62, 4:62–63 lobe and cleft structure, 4:60 mixed layer, 4:59–60, 4:60F, 4:61–62, 4:62, 4:63, 4:63–64, 4:63F overhanging nose, 4:60 surface currents see Surface gravity currents surface tension, 4:60 tidal causes, 4:59 turbidity currents see Turbidity currents unidirectional, 4:59–62 bottom current, 4:59–60, 4:60F dense fluid body collapse, 4:60–62 hydraulic jump see Cascades; Overflows idealized 2D model, 4:60 surface current, 4:60, 4:61F velocity, 4:60, 4:61, 4:62, 4:62–63, 4:63 vorticity, 4:59–60, 4:62 see also Internal wave(s); Rotating gravity currents; Shelf seas; Shelf slope fronts; Upper ocean, mixing processes; Upper ocean, vertical structure Nontronite, diagenetic reactions, 1:266T Nonuniform flow, definition, 5:464 Nonvolatile substances, bubbles, 1:442 NORM (naturally occurring radioactive material), 4:629, 4:634 Normal (surface ship) deployment, standard ship launchers, 2:348 Normal grading, definition, 5:464 Normal mode model (acoustic), 1:105 Normal modes see Seiches Normal oceanic crust definition, 5:361 seismic structure, 5:361–363 Normal reflectivity (p), pure water, 3:320–322, 3:321F Normal refractive index (n), electromagnetic wave propagation, 2:251–252 Norse Variant, 4:770F Norsk Polarinstitutt, Norway, icebergs, 3:184 Nortek Aquadopp current meter, 5:429F North Africa dust production, 1:253–254 North Atlantic Oscillation, temperature, 4:67
552
Index
North America river water, composition, 3:395T see also Canada; United States of America (USA) North Atlantic, 1:249T aphotic zone oxygen consumption, 6:94–95, 6:95F atmosphere, ocean coupling, 4:715 bottom water masses, 2:80, 2:82F breaking waves, 5:580F circulation, from inverse methods, data assimilation models, 2:8, 2:9F current see North Atlantic Current (NAC) current harmonic constants, 6:51F debris flows, 5:459F deep water formation, 4:126–127, 4:130, 4:131 dust deposition, 1:254T rates, 1:122T ecosystems, North Atlantic Oscillation and, 4:70 freshwater sources, 3:888F heat fluxes (mean), 3:110, 3:112F heat transport, 3:117 Holocene climate, 3:126–127, 3:127–128, 3:127F, 3:128 icebergs, 3:181 sources and drift paths, 3:182F intermediate waters, 6:295, 6:296F lead concentrations, 1:197, 1:198F, 1:199F vertical profile, 1:195, 1:196F mesoscale eddy, 3:759, 3:761F metal pollution, 3:771T distribution, 3:771–772, 3:773F mixing, importance of double-diffusive processes, 2:169 north-eastern see North-eastern Atlantic north-western see North-west Atlantic nuclear fuel reprocessing, 4:87–88 organochlorine compounds, 1:123T, 1:246T overflow from Arctic ocean, 4:266 Pacific Ocean vs., nitrate concentrations, 4:36, 4:37F particulate nitrogen, 4:52F polychlorinated biphenyls concentrations, 1:554, 1:557F potential vorticity, 4:161F radiocarbon, meridional sections, 4:643F radiocarbon levels, 3:307–310 rare earth elements, associated with particulate matter in sea water, 4:658T regime shifts, 4:704 atmosphere-ocean coupling, 4:715 see also North Atlantic Oscillation (NAO) river inputs, 4:759T seabird responses to climate change, 5:264 sills, 4:126–127, 4:130, 4:130F subduction rates, 4:158–159, 4:159F temperature changes, 4:124F
thermohaline circulation, 4:122 thermohaline staircases, 2:163F vertical salt flux and, 2:165–166 tidal currents, 6:51F tritium, 6:120, 6:120F, 6:121F tritium-helium dating, 6:125 variability, 4:67 ventilation, tritium-helium age, 4:159, 4:160F warm water, 4:129, 4:130 see also North Atlantic Deep Water (NADW) North Atlantic Current (NAC), 1:720–721, 1:724, 4:122, 5:353–354 fine structure, 2:169F Gulf Stream System, 2:556, 2:560 meddy, 3:708 transport, 1:724T see also Atlantic Ocean current systems North Atlantic Deep Water (NADW), 1:416, 2:569, 3:128–129, 4:127, 4:127F, 4:128, 4:131, 4:303, 6:297 Antarctic Bottom Water and abyssal circulation, 1:26, 1:26F alternating dominance, 3:129–130 areas of production, 3:888F Benguela region, 1:319–322, 1:322F, 1:324 Brazil Current, 1:425 Brazil/Malvinas confluence (BMC), 1:426F, 1:427 Denmark Strait, 4:306 flow, 1:725–726, 1:725F flow routes, 4:121F, 4:122, 4:127, 4:127F, 4:128 formation, 1:24, 4:121F, 4:122 formation rate, 1:420–421 formation region, 6:296F global warming and, 1:5 Heinrich events and, 1:1–2 Indonesian-Malaysian Passages, 4:306 neodymium isotope ratio, 3:458F, 3:463 observations, long-term, 1:24F, 1:26 paleoceanographic data, 4:303 radiocarbon, 4:643 reductions in intensity causes, 3:128–129, 3:129F Holocene, 3:127F, 3:128–129 salinity, 4:127, 4:131 Straits of Gibraltar, 4:303 temperature–salinity characteristics, 6:294T, 6:295, 6:297, 6:297F transport, 2:556F upwelling, Southern Ocean, 1:189F, 4:128 volume transport, 1:26 North Atlantic Front, seismic reflection profiling, 5:353–354 North Atlantic gannet see Northern gannet North Atlantic Intermediate Water, areas of production, 3:888F
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North Atlantic krill (Meganyctiphanes norvegica), 3:350F diurnal vertical migration, 3:351, 3:355 growth and development, 3:353 North Atlantic Oscillation (NAO), 3:99, 3:110, 4:65–72, 4:710F, 4:713, 5:88–89 anthropogenic warming and, 4:67–68, 4:71 Arctic Ocean, 5:141 Arctic Ocean Circulation and, 1:222 Arctic Oscillation and, 4:65 atmospheric pressure anomaly, 4:66F centers of action, 4:65 deep convection, 2:19–20 governing mechanisms, 4:70–71 atmospheric, 4:71 oceanic, 4:71–72 influence, 4:67–68 ecological impact, 4:70 ocean variability and, 4:69–70 precipitation, 4:68–69, 4:69F sea ice and, 4:70 temperature, 4:67–68, 4:68F interdecadal variability, 4:71 North Sea regime shifts and, 4:704 positive mode, 4:714 positive phase, 4:65, 4:68 principal features, 4:65–67 sea ice cover and, 5:146 North Atlantic Oscillation Index, 2:216, 4:65, 4:66F Calanus abundance and, 1:634–635, 1:636F increased, 1:635–636 North Atlantic right whale, 1:277T life cycle, typical, 1:280F as threatened species, 1:279, 1:286, 1:286T see also Baleen whales North Atlantic Salmon Conservation Organization (NASCO), 5:2, 5:5–6, 5:6–7 regulations Faroes salmon fishery, 5:7–8, 5:7T West Greenland salmon fishery, 5:6, 5:7T North Atlantic Salmon Fund (NASF), 5:8 North Atlantic Subpolar Gyre Deep Western Boundary Current (DWBC), 2:562–563 Labrador Current, 2:561–562, 2:562F North Atlantic Subtropical Gyre, eastern boundary, 1:467 large-scale circulation, 1:467–468, 1:467F see also Canary Current; Portugal Current North Atlantic Tracer Release Experiment (NATRE), 2:122–123, 2:164–165, 6:287 results, 6:88, 6:88F North Atlantic Western Boundary Current, velocity profile, 6:145, 6:145F
Index North Atlantic winds, Intertropical Convergence Zone, regional model case study, 4:729, 4:729F North Brazil Current (NBC), 1:234F, 1:235, 2:554, 2:560–561 Amazon River Water, 2:561 Antarctic Intermediate Water (AAIW), 2:560–561 current rings, 2:561 flow, 1:721–723, 1:723–724, 1:723F generating forces, 2:555–556 retroflection, 3:288 river influxes, 2:561 seasonal variation, 1:235, 2:560–561 transport, 1:724T, 2:560 see also Atlantic Ocean current systems North Brazil Undercurrent (NBUC), 1:720–721, 1:721–723 transport, 1:724T see also Atlantic Ocean current systems North Carolina, coastal zone management, 1:599–600 North-East Atlantic Fisheries Commission (NEAFC), 5:6 North-eastern Atlantic marine snow, 3:691, 3:692F phytodetrital layer quantity variation, 2:550F time-lapse photography, 2:551F, 2:552F temporal variability of particle flux, 6:4F see also North Atlantic North-east Monsoon Current (NMC), 1:733, 3:232–233 North-East Pacific magnetic anomalies, 3:482F radiocarbon concentrations, 3:307–310 radiocarbon profiles, 5:426–427, 5:427F temporal variability of particle flux, 6:4F see also North Pacific North-east Water (NEW), polynyas, 4:540 North Equatorial Countercurrent (NECC), 1:234, 1:234F, 5:312–313, 6:182 flow, 1:721–723, 4:287F, 4:288, 4:288F, 4:289, 4:291F seasonal variation, 1:235, 1:235F transport, 1:724T see also Atlantic Ocean current systems; Atlantic Ocean equatorial currents; Pacific Ocean equatorial currents North Equatorial Current (NEC), 1:234, 1:234F, 1:720–721, 3:293F, 5:312–313 bifurcation, 3:358, 3:359F flow, 4:287F, 4:288, 4:288F, 4:290F, 4:291F Hawaiian islands, eddy production, 3:347 transport, 1:724T see also Atlantic Ocean current systems; Atlantic Ocean equatorial currents; Pacific Ocean equatorial currents North Equatorial Undercurrent (NEUC) flow, 1:721–723, 1:723F
transport, 1:724T see also Atlantic Ocean current systems Northern anchovy, 4:700F Northern Basin, Baltic Sea circulation, 1:288, 1:289F Northern bluefin tuna see Thunnus thynnus (Atlantic bluefin tuna) Northern blue whiting, acoustic scattering, 1:66 Northern bottlenose whale (Hyperoodon ampullatus), 3:643, 3:646, 3:647–648, 3:647F, 3:649 Northern elephant seals (Mirounga angustirostris), 3:629–630, 4:135 Northern fulmar (Fulmaris glacialis) breeding, 5:251 changes in distribution, 4:592–593 food/foraging, 4:593 see also Procellariiformes (petrels) Northern fur seal (Callorhinus ursinus), 4:135 Northern gannet (Sula bassana), 4:372F human exploitation, 5:267 see also Sulidae (gannets/boobies) Northern Gulf of Mexico, hypoxia, 3:174, 3:175–176, 3:175F Northern hemisphere aerosol concentration, 1:250 atmospheric meridional section, 4:121F carbon dioxide sinks, 1:491 chlorofluorocarbons, 1:531–532, 1:532F current rotation, 6:192 Ekman divergence, 2:226 geostrophic circulation, dynamic sea surface topography, 5:59–61, 5:61F sea ice, 5:170 sea ice cover, interannual trend, 5:145F seasonal thermocline, 6:180T subtropical gyre, 4:121 summer wind stress, 3:109–110, 3:109F Northern Indian Ocean, oxygen distribution, 6:178 Northern Norwegian Sea Fishery, Salmo salar (Atlantic salmon), 5:6–7 Northern phocids see Phocinae (northern phocids) Northern Sea Route acoustics research and, 1:92 navigability, 5:141–142 Northern Subsurface Countercurrent (NSCC) flow, 4:287F, 4:289, 4:290F see also Pacific Ocean equatorial currents North Indian Ocean current systems see Indian Ocean dust deposition, 1:254 North Intermediate Countercurrent (NICC), 1:723F North Marquises Fracture Zone, clay mineral profile, smectite composition, 1:567T North Pacific aerosol concentrations, 1:249T antimony depth profile, 3:781–782, 3:781F
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553
arsenic depth profile, 3:780–781, 3:781F biogenic silica burial, 3:681T, 3:682 chromium depth profile, 3:778, 3:778F copper complexation, depth profiles, 6:105F deep and abyssal waters, 6:296–297, 6:296F depth profiles, trace nutrients, 6:77F dust deposition, 1:254T rates, 1:122T germanium depth profile, 3:780, 3:780F gravity field, 3:84F heat transport, 3:117, 6:168–170 lead depth profile, 1:195, 1:196F molybdenum depth profile, 3:777F, 3:778–779 Okhotsk Sea and, 4:201, 4:202, 4:204, 4:206–207, 4:206F organochlorine compounds, 1:123T, 1:246T osmium depth profile, 3:778F, 3:779–780, 4:496–497, 4:497T, 4:498F oxygen and radiocarbon profiles, 4:107, 4:108F rare earth elements associated with particulate matter in sea water, 4:658T vertical profiles, 4:655, 4:658F regime shifts, 4:699, 4:700, 4:702–704, 4:709–710, 4:710–713 1970s, 4:710 analysis, 4:718–719, 4:719F mechanisms, 4:714F rhenium depth profile, 3:777F, 3:779 river inputs, 4:759T seasonal cycles, mixed-layer properties, 6:342 sedimentary communities, sea otter effects on invertebrate populations, 5:199 selenium depth profile, 3:782, 3:782F silicate vertical profile, 3:678–679, 3:679F subtropical, nitrogen depth profiles, 4:51F tellurium depth profile, 3:782–783, 3:782F temporal variability of particle flux, 6:7 thorium-230 profile, 5:330F tungsten depth profile, 3:777F, 3:779 vanadium depth profile, 3:777, 3:777F volcanic helium, 6:278, 6:279F western boundary currents, 3:358 Kursoshio Current see Kuroshio Current Oyashio Current see Oyashio Current wind stress, 1966-1986, 4:711–712 see also North-East Pacific; Pacific Ocean North Pacific Anadromous Fisheries Commission (NPAFC), 5:20–21 North Pacific Current, formation, 3:364 North Pacific Intermediate Water (NPIW), 6:295 salinity distribution, 1:23F, 1:25–26
554
Index
North Pacific Intermediate Water (NPIW) (continued) temperature–salinity characteristics, 6:292, 6:292F North Pacific Marine Science Organization (PICES), 3:276–277 El Nin˜o and Beyond Conference, 3:276 established by Warren Wooster, 3:277 members and purposes, 3:276 multidisciplinary focus, 3:276 symposia and workshops, 3:276–277 North Pacific sea star (Asterias amurensis), 2:342 North Pacific Subarctic Gyre see Alaska Gyre North Pacific Subtropical Front, 4:136 North Pacific Subtropical Gyre, 1:455 see also California Current North Pole, mean ice draft, 5:152F North Queensland Current (NQC), 5:312–313 North Sea 1953 storm, 5:532, 5:536F areas with oxygen deficiency, 2:315F atmospheric deposition, 1:240F synthetic organic compounds, 1:242T bathymetry, 4:75F circulation, 4:73–81, 4:77F, 4:80 measurements, 4:76, 4:77F, 4:78 acoustic Doppler current profiler, 4:76, 4:78, 4:81 radionuclide tracers, 4:76 shore-based hf radar, 4:76 see also Drifters; Float(s); Moorings; Nuclear fuel reprocessing; Single Point Current Meters numerical models, 4:76–78 see also Regional models seasonal variation, 4:80 connections, 4:73 Doliolum nationalis, 1:638–639 ecosystem regime shift, 1:635–636 elevated nutrient levels, 2:314F eutrophication, 2:308T fish species composition, 4:751 gadoid outburst, 2:508 inputs, 4:80 river, 4:73–76, 4:76, 4:80 meteorology, 4:73 nitrogen, atmospheric input, 1:241T offshore structures, 4:749 outflow, 4:80 phytoplankton color, 1:635–636, 1:636F regime shifts, 4:704 seabird populations, 5:271–272, 5:272T consumption rates of fishery discards/ offal, 5:269T, 5:270 see also Seabird(s) shelf edge, 4:81 dynamical processes, 4:81 storm surges, 5:532, 5:534F model simulation, 5:533F prediction, 5:535
stratification, 4:76 due to freshwater river discharge, 4:76 due to solar heat input, 4:76 stratification, effects, 4:80 fronts, 4:80 see also Fronts inertial currents, 4:80–81 internal waves, 4:81 see also Internal wave(s) studies, 4:73, 4:76 tides, 4:78, 4:79F see also Tide(s) topography, 4:73, 4:74F, 4:75F wind forcing, 4:78–80 see also Storm surges North-west Africa, Holocene climate, 3:126–127, 3:127, 3:127F North-west Atlantic demersal fisheries, 2:96, 2:97T multispecies dynamics, 2:505–506, 2:506F, 2:509–510 seabird responses to prehistoric climate change, 5:258 Northwest Atlantic Fishery Organization (NAFO), fishery management, 2:513–514 North-west Atlantic shelf, coastal circulation model and, 1:574F North West Cape, 3:449, 3:449F Northwestern Europe, global warming and, 1:5 Northwest monsoon, Indonesian Throughflow, 3:241F Northwest Passage, sea ice cover, 5:141–142 Norway herring, 2:484, 2:485F North Atlantic Oscillation, ecological effects, 4:70 salmonid farming, 5:24 Salmo salar (Atlantic salmon) fisheries, 5:1–2, 5:2T catch, 5:8F, 5:9 stock enhancement/ocean ranching programs, 2:530 cod, 4:150–151, 4:151F Norwegian Atlantic Current, 1:213 Norwegian Coastal Current (NCC), 4:73–76, 4:77F, 4:80, 4:792, 4:794F, 4:795 nuclear fuel reprocessing, 4:85, 4:87–88 origins, 1:291–292 see also North Sea Norwegian Cod Study, stock enhancement/ocean ranching programs, evaluation, 4:150–151, 4:151F Norwegian Current, 4:126–127 Norwegian margin, slides, methane hydrate and, 3:796 Norwegian Sea, 4:126 bottom water, export of, 1:416 seismic reflection water-column profiling, 5:353F, 5:354, 5:358F NOSAMS (National Ocean Sciences AMS facility), 4:642
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NOSS (National Oceanographic Satellite system), 5:69 Notacanthus chemnitzii (spiny eel), 2:452F Notothenioidei, 1:191, 1:192F Notothenioid fish, 4:518 Nova Canton trough area, manganese nodules, 3:493 Novel metabolites, marine organisms, 3:567–568 Novorossiysk, 1:212, 1:403 NPAFC (North Pacific Anadromous Fisheries Commission), 5:20–21 NPIW see North Pacific Intermediate Water (NPIW) NPZ see Nutrient–phytoplankton– zooplankton NPZD-type models, small-scale patchiness, 5:478, 5:481 N-P-Z (nutrient–phytoplankton–zooplankton) models, 4:722, 4:724F, 4:725, 4:731 NRM see Natural remanent magnetization (NRM) NROSS (Navy Remote Ocean Observing Satellite), 5:67F, 5:71 NSCAT (NASA scatterometer), 5:71 NSE see Navier–Stokes equation NTU (nephelometric turbidity units), 6:111 Nuclear DNA, 2:217 Nuclear fuel reprocessing discharges, use in oceanography, 4:82, 4:86–87 coastal circulation, 4:87 deep-water formation, 4:87–88 history, 4:86–87 surface circulation, 4:87 plants Cap de la Hague see Cap de la Hague, France Sellafield see Sellafield, UK radionuclides, 4:82 see also specific radionuclides related discharges and, 4:82–88 sources, 4:85 tracer releases, 4:83, 4:84F applications, 4:84T description, 4:83 origin, 4:83 regional setting, 4:85–86 reprocessing discharges, circulation of, 4:85–86 source function, 4:83–85 units, 4:82–83 Nuclear power plants/stations thermal discharges effects of, 6:10 pollution due to see Pollution tidal energy, 6:27 see also specific nuclear power stations Nuclear reactors closed primary cooling systems, 4:632 construction, 4:630–632 Nuclear submarines, history, 5:504
Index Nuclear testing, coral disturbance/ destruction, 1:676 Nuclear weapons test fallout, 4:85 Nucleotide, 2:217 Nudging (Newtonian) relaxation scheme, 2:7 Numerical analysis, regime change data, 4:717–718 Numerical models, 2:604 coastal circulation, 1:573, 1:579 forward see Forward numerical models general circulation see General circulation models (GCM) limits/limitations, 3:22–23 see also Direct numerical simulation Numerical weather prediction (NWP) models, 3:108 storm surges, 5:536–537 Nusa Tenggara islands, monsoonal variations, 3:240 Nusselt number, 4:222 Nutraceuticals definition, 3:574 see also Marine biotechnology Nutrient(s), 6:231 abundance, in NP models, 4:98 availability, North Pacific, regime shifts, 4:711–712 biological pump and, 1:485–486 cycles see Nutrient cycles; Nutrient cycling definition, 4:677–678 eddy-driven injection event, 5:481, 5:483F effect on primary production, 4:573 fluxes see Nutrient fluxes land-sea global flux, 3:397–399 oceanic distribution, 3:332–334, 3:333F depletion in surface vs. deeper waters, 4:681, 4:682F high-nitrate, high-chlorophyll (HNHC) regions, 3:332–333, 3:332T high-nitrate, low-chlorophyll regions see High-nitrate, low-chlorophyll (HNLC) regions low-nitrate, low-chlorophyll (LNLC) regions, 3:332–333, 3:332T oceanic distribution implications, 4:680 impact of export production on concentrations, 4:680, 4:681F intercepts of scatter plots, 4:682–684, 4:683F spatial separation of photosynthesis and remineralization, 4:680 straight lines in some scatterplots, 4:681–682, 4:683F optimal conditions, 6:226 relationship to temperature, 6:230, 6:230F remineralization, 3:300–302 requirements for primary productivity, 4:586, 4:587 tidal mixing fronts, 5:396 trace element, 6:75–86 biological uptake, 6:80–82
chemical speciation, 6:78–80 distribution in seawater, 6:76–78 metabolic role, 6:82–84 seawater chemistry and, 6:84–85 see also Trace element(s) tracers as, 3:300–302 transport to upper ocean, mesoscale eddies in Sargasso Sea, 5:481, 5:483F units, 4:678 upwelling zones, 6:227 see also Redfield ratio; specific nutrients Nutrient cycles anoxia and, 4:685–686 estuarine sediments, redox chemistry and, 1:547–549 important processes, 4:684–685, 4:684F photosynthesis see Photosynthesis remineralization see Remineralization residence times, 4:685 salt marsh see Salt marsh(es) and mud flats Nutrient cycling bacterioplankton, 1:275 benthic foraminifera, 1:340, 1:347 copepods, 1:647, 1:650 coral reef aquaria, 3:530, 3:530F meiobenthos, 3:730–731 microbial loops, 3:803–804, 3:803F microphytobenthos, 3:813 plankton, 4:453 plankton communities, 3:656 salt marshes and mud flats, 5:45–46 upwelling zones, 6:227 see also Microbial loops; Phytoplankton blooms; Primary production distribution; Primary production measurement methods; Primary production processes Nutrient fluxes absolute velocity estimation (inverse modeling), 3:302–304 estimation (inverse modeling), 3:302–304 internal tides, 3:264 internal waves, 3:266 Mediterranean Sea circulation, 3:717 Nutrient–phytoplankton models, 4:98, 4:99F, 4:100F limitations, 4:98 Nutrient–phytoplankton–zooplankton (NPZ) models, 4:98, 4:98–100, 4:99F, 4:100F, 4:211, 4:722, 4:724F, 4:725, 4:731 adjoint data assimilation, 1:368F data insertion, 1:367–368, 1:367F Nutrient-rich waters, 3:451 deep water, 4:126 see also Inverse models/modeling NUVEL-1 (global plate tectonic model), astronomical polarity timescale and, 3:30 NWP see Numerical weather prediction (NWP) models Nyquist frequency, bathymetry, 1:300
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555
O OAE (ocean anoxic events), 4:320, 4:321F OASIS (Optical-Acoustical Submersible Imaging System), 6:368–369 Objectively Analyzed air–sea Fluxes (OAFlux) project, 5:207 Obliquity (orbital), 4:311–312 Oboukhov scale, open ocean convection, 4:222 OBS see Ocean bottom seismograph (OBS); Ocean bottom seismometer (OBS) Observational System Simulation Experiments (OSSEs), 1:578, 2:3 Observations at sea, history, 3:121 Observatories AUV docking stations, 6:263–265 AUVs and, 4:482–483 deep-sea, 6:265–266 and AUVs, 6:263–265 and benthic flux rovers, 4:493 seafloor, 2:50 undersea, AUV and, 4:475 Obukhov length, under-ice boundary layer, 6:158–159, 6:160 Ocean(s) circulation see Ocean circulation color see Ocean color components of global climate system, 2:48F oxygend18O values see Oxygen isotope ratio (d18O) deep see Deep ocean deposition of particulate material see Aerosols depth, tectonic plate ageing and, 3:867, 3:868F features SAR detection see Satellite remote sensing satellite remote sensing of SST application, 5:97 flows, Rossby waves, 4:788 history see Paleoceanography metal pollution, suspended particulate matter, 3:771F nutrient distributions see Nutrient(s), oceanic distribution open see Open ocean origin see Origin of oceans pollution, seabirds as indicators see Seabird(s) productivity see Productivity rainfall estimates and global hydrologic budget, 5:130 satellite remote sensing see Satellite remote sensing as single unit (global to estuarine scales), 1:579 statistical areas see Statistical areas thermal expansion, sea level variation and, 5:181–182, 5:182F, 5:183
556
Index
Ocean(s) (continued) trajectories, velocity measurement, 2:171, 2:173–174 upper see Upper ocean uses, marine policy, 3:666, 3:666T volume changes, sea level changes, 3:49 see also entries beginning ocean, oceanicsee specific oceans; specific topics Ocean–atmosphere interactions advection, 2:244 circulation system, 4:126, 4:129 coupled climate models, 4:131 El Nin˜o, 2:244–245 exchanges, 5:82 see also Air–sea gas exchange long time-scales and slow adjustment to winds, 2:244–245 stability properties, 2:245 Ocean basin changes, deep-sea drilling and, 2:47, 2:48F sediment volumes, 4:138T volume and sea level variations, 5:185–187, 5:186F changes over time, 5:187–189, 5:188F Ocean basin flood basalts, 3:219–222, 3:220T, 3:225 see also Large igneous provinces (LIPs) Ocean blueprint for the 21st century, A (US Commission on Ocean Policy), 1:603–604 Ocean bottom modeling, coordinate choice, 5:139 sound reflection and absorption, 1:104 topography, satellite altimetry, 5:59, 5:60F see also entries beginning bottomsee entries beginning seafloor Ocean bottom seismograph (OBS), 5:361, 5:367 broadband see Broadband (BB) ocean bottom seismometers pool (OBSIP), 5:367 short period see Short period (SP) ocean bottom seismometers synthetic pressure, 5:373F vertical motion, 5:373F Ocean bottom seismometer (OBS), 3:838 hydrothermal seismicity and, 3:847 Ocean Carbon-Cycle Model Intercomparison Project (OCMIP), 4:112F Ocean Carbon Model Intercomparison Project (OCMIP) -2 program, 4:648–650 participants, 4:649F, 4:650T Ocean circulation, 4:115–125, 4:126 biogeochemical models and, 4:98–100, 4:107–109 climate system, effect on, 4:124–125 deep ocean temperatures, 4:124–125, 4:124F heat capacity of the ocean, 4:124 poleward heat transfer, 4:123F, 4:124
salinity measurements, 4:125 sea surface temperatures, 4:125 thermohaline circulation stability, 4:125 timescale variations, 4:124 see also Climate change; Ocean climate models definition, 4:115 determination of, 4:115–119 chemical tracers, 4:119 coordinates of measurement position, 4:115, 4:116–117 density distribution measurement, 4:119 dynamic method, 4:119 Eulerian flow, 4:115–116, 4:116–117, 4:116F measurement techniques see Current meters flow variability, 4:117, 4:118F time series analysis, 4:118–119, 4:118F frequency spectrum, 4:118–119, 4:118F geostrophic balance, definition, 4:119 geostrophic current, 4:119 Lagrangian flow, 4:115–116, 4:116F, 4:117 measurement techniques see Drifters; Float(s) mariners’ observations, 4:117 mean flow, 4:117 sea surface slope measurement, 4:119 vertical circulation, 4:119 see also World Ocean Circulation Experiment (WOCE) ecological models and, 4:98–100 fresh water, role of, 4:122–124 Arctic Basin circulation, 4:123 buoyancy fluxes, 4:123 evaporation, 4:123 freshwater transfer, 4:123F Mediterranean Sea, 4:123 polar oceans, 4:123 precipitation, 4:123 sea ice, 4:123 subpolar oceans, 4:124 general circulation model see Ocean general circulation model (OGCM) mathematical methods see Elemental distribution meridional overturning, 4:126–131 models see Ocean climate models; Ocean models/modeling thermocline see Thermocline, main thermohaline see Thermohaline circulation wind driven see Wind-driven circulation World Ocean Circulation Experiment (WOCE), 4:119, 4:124–125 see also specific currents/circulations Ocean City, Maryland, USA, coastal erosion, 1:582 Ocean climate models acoustic waves, 5:138 boundary fluxes, 5:139
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climate, 5:139 eddies, 5:134–135 finite volume method, 5:138 fundamental budgets/methods, 5:136 gravity waves, 5:138 grid resolution, 5:133, 5:134 linear momentum budget, 5:137 mass conservation, 5:136 mesoscale eddies, modeling, 5:134–135 methods and budgets, 5:136 parameters, 5:135–136 problems, posing, 5:135–136 rounding errors, 5:139 scales of magnitude, 5:133 subgrid-scale parametrization, 5:133–134 time-stepping momentum, 5:137–138 tracer budgets, 5:136–137 truncation methods, 5:133–134 use/process, 5:139 vertical coordinates, 5:138–139 Ocean color atmospheric correction, 4:735, 5:119–120 coastal waters, 4:732–734 algorithms, 4:735 data validation, 4:736–737 data processing requirements, 5:117F definition, 5:114 instruments, 5:114 satellite remote sensing see Satellite remote sensing sensor design, 5:116–118, 5:118T theory, 5:114–116 see also Reflectance Ocean convection plumes deep convection, 2:15–16 entrainment, 2:15 float measurements, 2:16 penetrative, 2:15–16 rotation, 2:15 thermal boundary layer, 2:15, 2:16F vertical mass flux, 2:15–16 open ocean convection, 4:218–219 see also Open ocean convection Ocean currents see Current(s) Ocean Data Acquisition System (ODAS), 1:142 Ocean Drilling Program (ODP), 2:24–26, 2:29F, 2:30–33, 2:31F, 2:37, 2:46, 3:278, 4:297–298 advisory structure, 2:53, 2:53F Benguela upwelling system, 5:342 core repositories, 2:51–52 coring within subduction zones, 2:49 current specific studies, 3:278 drilling sites, 2:38F explores the earth’s crust, 3:278 funding, 2:52 management structure, 2:52–53 management team, 2:52–53, 2:52F members of the program, 2:52 scientific themes explored by, 2:49 sedimentary records of Holocene climate variability and, 3:126 sites, 2:48F, 2:51T
Index survey and discovery methods, hydrothermal vent fluid chemistry, 3:168–169 US National Science Foundation and partners, 3:278 Ocean Drilling Program Leg 175, 5:342 Ocean-driven climate change, 3:125, 3:128–129 see also Climate change Ocean dumping capacity, global marine pollution, 3:67 environmental protection and Law of the Sea, 3:440 prohibition in coastal state waters, environmental protection and Law of the Sea, 3:440 rigs and offshore structures, 4:751 solid waste, coral disturbance/ destruction, 1:674–675 Ocean floor Law of the Sea jurisdiction, ‘area,’ definition, 3:435 record of Earth’s history, 2:22 Earth and ocean history, 2:22, 2:23F hydrothermal vents, 2:22, 2:23–24, 2:23F, 2:25F study of seafloor terrain, 2:22 sediment charts, 3:122–123 see also Seafloor; entries beginning bottom Ocean general circulation model (OGCM), 1:364, 4:119, 4:128 definition, 4:119 forcing, 4:119, 4:120F model boxes, 4:119, 4:120F momentum equation, 4:119, 4:120F in paleoceanography, 4:304, 4:305 Denmark Strait, 4:307 Drake Passage, 4:304 Gibraltar, 4:306 Indonesian–Malaysian Passages, 4:306 Isthmus of Panama, 4:305 mid-Cretaceous, 4:308 variable results, 4:309 salinity equation, 4:119, 4:120F temperature equation, 4:119, 4:120F see also Atmosphere–ocean general circulation models (AOGCMs); General circulation models (GCM); Paleoceanography Ocean global climate models (OGCM), 4:129–130 see also Global climate models (GCMs) Ocean gyre(s) Alaskan Gyre, 3:661 Labrador-Irminger Sea Gyre, 3:661 North Atlantic Subtropical Gyre (NASG), 3:661, 3:661–662 North Pacific Central Gyre (NPCG), 3:661, 3:661–662 Norwegian Sea Gyre, 3:661 Ocean gyre ecosystems, 4:132–137 description, 4:132–133 enhanced feeding habitats, 4:135–136 frontal systems, 4:135
mesoscale variability, 4:136 seamounts, 4:136 food web dynamics, 4:136–137 effects of climatic change, 4:136–137 effects of fisheries, 4:137 higher trophic levels, 4:135 large pelagic fishes, 4:135 see also Mesopelagic fish(es); Pelagic fish(es) marine mammals, 4:135 see also Marine mammals organisms included, 4:135 seabirds, 4:135 see also Seabird foraging ecology see also Fish predation and mortality intermediate trophic levels, 4:133–135 deep scattering layer (DSL) organisms, 4:134 gelatinous zooplankton, 4:134 see also Gelatinous zooplankton organisms included, 4:134 pelagic forage fishes, 4:135 see also Mesopelagic fish(es); Pelagic fish(es) open-ocean food web, 4:132 characteristics, 4:132 food webs vs. food chains, 4:132 role of microbes, 4:132 see also Microbial loops role of winds, 4:132 seasonality, 4:132 subarctic north Atlantic, 4:133 north Pacific, 4:133, 4:133F subtropical gyres, 4:132–133 subtropical north Pacific, 4:134F Oceania El Nin˜o Southern Oscillation, precipitation, 2:230–231 river water, composition, 3:395T Oceanic anoxic events (OAE), 4:320, 4:321F Oceanic carbon cycle, 1:479–480 see also Carbon cycle Oceanic convection subpolar regions, 5:130 see also Convection; Deep convection Oceanic crust see Crust, oceanic Oceanic dolphins, 3:606–607T bioacoustics, 1:357 body outline and skeleton, 3:610F echolocation, 1:358–359, 1:359F, 3:615 mechanism, 1:361, 1:361F optimal frequency, 1:359 exploitation, 3:635–637, 3:641F drive fisheries, 3:636 live-capture, 3:640–642, 3:641F feeding in ocean gyre ecosystems, 4:135 hearing, 1:360, 1:360F home ranges, 3:598–599, 3:599 lungs, 3:586F migration and movement patterns, 3:598–599, 3:599 recognition calls individual recognition, 3:620 mother–infant, 3:619–620
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signature whistles, 3:619–620, 3:620, 3:620F trophic level, 3:623F see also Odontocetes (toothed whales); specific species Oceanic gyres see Ocean gyre(s) Oceanic heat content (OHC), 6:197F hurricane Katrina, 6:204, 6:204F hurricane Rita, 6:205 Oceanic island basalts (OIB), composition, 3:819–820 Oceanic islands magnetic anomalies, 3:486–487 see also Islands Oceanic Peru Current see Peru Current Oceanic plateaus, 5:292, 5:296, 5:297F Oceanic precipitation, 5:130 Oceanic processes remote sensing program, 5:129 Ocean interior, modeling, vertical coordinate choice, 5:139 Ocean Isle, North Carolina, USA, coastal erosion, 1:581 Oceanites oceanicus (Wilson’s storm petrel), 4:591F Oceanitidae see Storm petrels Ocean law dynamic nature, 3:669–670 see also Law of the Sea Ocean margins, geophysical heat flow, 3:47 Ocean margin sediments, 4:138–145 carbonate, 4:141 characteristics, 4:140–141 particle size, 4:140 composition, 4:138 cycling, 4:142 distribution, 4:139F evaporites, 4:141 margin structure, 4:139–140 mass movements, 4:142 research programs, 4:138–139 siliclastic, 4:140–141 stratigraphy, 4:141–143 formation, 4:143–144 geographical variation, 4:144 scaling, 4:144 sequences, 4:143–144 transport mechanisms, 4:141–142, 4:142F see also Deep-sea fauna Ocean mixed layer see Mixed layer Ocean mixing see Energetics of ocean mixing; Mixing Ocean models/modeling challenges, 1:686 radionuclide tracers and, 1:686 data resolution requirements, 1:299T tuning, radionuclide tracers and, 1:687 see also Coupled sea ice-ocean models; Models/modeling Ocean observing and prediction system (OOPS), 2:2 Oceanodroma castro (Madeiran storm petrel), 4:594
558
Index
Oceanographic campaigns, remote sensing data validation, 4:736–737 Oceanographic expeditions, history, 5:410 Oceanographic institutions, 3:122 history, 5:410–411 Oceanographic instrumentation, deep submergence science studies, 2:22 Oceanographic research vessels, 5:409 accommodation, 5:412 acoustical systems, 5:412 categories, 5:409 characteristics, 5:409 communications (internal/external), 5:412 control of ship, 5:412 deck working area, 5:412 definition, 5:412 design characteristics, 5:414–415 design factors, 5:415 design priorities, 5:415 endurance, 5:412 fisheries research vessels, 5:415–416 future ships, 5:418 growth in interest, 5:418 larger sizes, 5:418 new types, 5:418 SWATH (Small Waterplane-Area Twin Hull) ships, 5:418 general purpose vessels, 5:415 geophysical research vessels, 5:416 heating, ventilation and air conditioning, 5:412 history, 5:409–412 larger improved fleet, 5:411–412 ice strengthening, 5:412 laboratories, 5:412 mapping/charting vessels, 5:415 miscellaneous classes of vessels, 5:416–417 mission requirements, 5:412–414 multichannel seismics, 5:412 nature of, 5:412–414 acoustical systems, 5:412 equipment and facilities, 5:412 IMO category, 5:412 multi-disciplinary role, 5:412, 5:418 primary requirement, 5:412 science mission requirements, 5:412 scientific personnel, 5:412 specific purposes, 5:412 navigation/positioning, 5:412 operations, 5:417 cruise planning, 5:417 EEZ (exclusive economic zone), 5:417 international cooperation, 5:417 measurements and observations, 5:417, 5:417T Meteor, German Atlantic Expedition, 5:417 other classes, 5:417 commercial expediency, 5:417 occasional employment, 5:417 see also Archaeology (maritime) overside handling, 5:412 polar research vessels, 5:416 satellite monitoring, 5:412
seakeeping and station keeping, 5:412 shipbuilding boom, 5:411 size, 5:412 speed, 5:412 storage facilities, 5:412 support vessels, 5:416–417 towing, 5:412 vans (portable), 5:412 winches, 5:412 workboats, 5:412 world fleet, 5:417–418 International Ship Operators Meeting, 5:418 numbers, 5:418, 5:418T varying status and categories, 5:418 see also Fisheries research vessels; General purpose vessels; Geophysical research vessels; Mapping and charting vessels; Support vessels; individual types of vessels (e.g. polar research vessels) Oceanographic research voyages, history, 5:411 Oceanographic technology, deep submergence science studies, 2:22 Oceanography definition, 3:121 history, 3:121 Oceanography from Space (report), 5:66, 5:70 Ocean optics, 3:244 apparent optical properties see Apparent optical properties (AOPs) experiment data sets, 3:248–252 Bermuda Testbed Mooring, 3:251–252, 3:252F BIOPS system, 3:248, 3:250F sewage plume waters, 3:248–249, 3:251F ship-based profiling system, 3:248–249 fundamentals, 3:244–245 inherent optical properties see Inherent optical properties (IOPs) instrumentation, 3:245–248 absorption meter, 6:116 ac-meters, 3:246 antifouling methods, 3:246 beam transmissometers see Transmissometry, sensors biofouling issue, 3:246 future goals, 3:248, 3:252 laser (Frauenhofer) diffraction instruments, 3:246 mooring applications, 3:248, 3:249F novel, 6:116 photosynthetically available radiation (PAR) sensor, 3:247, 3:249F scattering sensors see Nephelometry measurements and fundamental values, 6:109–111 optical constituents of seawater see Sea water, optical constituents quantities, radiometric, 4:619–621, 4:620T commonly used, 4:620T
(c) 2011 Elsevier Inc. All Rights Reserved.
quasi-inherent optical property, 3:247 terminology, 4:619 see also Irradiance; Ocean color; Optical particle characterization; Radiance; Radiative transfer (oceanic) Ocean perch (Sebastes marinus), open ocean demersal fisheries, 4:228–229 Ocean plateaus, 3:218, 3:220T, 3:223F, 3:225 see also Large igneous provinces (LIPs) Ocean ranching programs see Stock enhancement/ocean ranching programs Ocean resource use international conflicts, 3:666 marine policy, 3:666 see also Fishery resources; Mineral resources Oceans and Coastal Areas Program, United Nations Environment Program, 3:668T Ocean sciences fundamental problem, 2:1 history of, 3:121–124 Ocean Sensors, Inc, 1:715–716 Ocean space enclosure, institutional frameworks, marine policy, 3:666 Ocean spinup, Rossby waves, 4:788 Hovmo¨ller diagram, 4:787F Sverdrup balance, 4:787–788, 4:787F Ocean Station Papa (OSP), 6:342 depth profiles, trace element nutrients, 6:77F one-dimensional models, 4:212–213 physical parameters, 4:212–213 planktonic ecosystem, 4:213–214 phytoplankton variability, 4:215F seasonal climate profiles, 6:343F Ocean subduction, 4:156–166 buoyancy fluxes, 4:156, 4:157F, 4:162–163 sea surface, 4:163, 4:163F, 4:165 convective chimneys, 4:164–165, 4:165, 4:165F definition, 4:165 density Lagrangian change in mixed layer, 4:162 outcrops, 4:156–157, 4:158F, 4:163F potential density surfaces, 4:160, 4:160–161, 4:161F diffusive fluxes, 4:163, 4:163–164, 4:163F dynamic tracer distribution see Potential vorticity eddy-driven see Eddy-driven subduction frontal-scale subduction, 4:164–165 gyre-scale subduction, 4:158–159, 4:160–162, 4:164 annual subduction rates, 4:158–159, 4:159F buoyancy input, 4:162–163 Ekman pumping, 4:158, 4:159, 4:159–160, 4:159F
Index tracer distributions, 4:160–161, 4:161F mixed layer, 4:156F, 4:157–158 density evolution, 4:162 seasonal cycle, 4:156, 4:157F mode waters, 4:157, 4:158 definition, 4:157 formation, 4:163 overflows and cascades see Cascades; Overflows process, 4:156–157 seasonal boundary layer, 4:156, 4:159, 4:165 definition, 4:165 seasonal rectification, 4:156–157, 4:158F spatial scales, 4:156 subduction rate, 4:157–158, 4:165 annual, 4:159F, 4:164 definition, 4:157–158, 4:165 eddy-driven, 4:164, 4:165F equations, 4:157–158, 4:162–163, 4:164 instantaneous, 4:156F, 4:157–158, 4:158F, 4:164 integral connections, 4:163 kinematic connections, 4:162–163 negative, 4:159 North Atlantic, 4:158–159, 4:159F thermocline see Seasonal thermocline; Thermocline, main thermohaline circulation see Thermohaline circulation transient tracers, 4:159, 4:162 tritium-helium age, 4:159, 4:160F ventilation, 4:156, 4:156F definition, 4:165 measures of, 4:159, 4:160F rates, 4:159, 4:165 tracer distribution, 4:162 water mass transformation, 4:163, 4:163F see also Deep convection; Ekman pumping; Ekman transport; Mesoscale eddies; Open ocean convection; Upper ocean, mixing processes; Upper ocean, vertical structure; Wind-driven circulation Ocean surface, 5:91, 6:217 atmosphere interactions, 5:91 current velocity data, 5:130 high-resolution global coverage of satellites, 5:91 see also Satellite oceanography ocean-atmosphere interactions, 5:91 waves see Surface, gravity and capillary waves; Surface waves see also Sea surface Ocean surveying, expendable sensor use see Expendable sensors Ocean thermal energy conversion (OTEC), 4:167–173 closed cycle, 4:168–169, 4:168F economics, 4:171–172 environmental considerations, 4:171 foam lift system, 4:170–171
hybrid cycle, 4:171 mist lift system, 4:170–171 open cycle, 4:169–171, 4:170F technology, state of, 4:167–168 thermal sink, 4:167–168 working fluids, importance of, 4:169 Ocean tides see Tide(s) Ocean warming, methane hydrate reservoirs and, 3:794, 3:794F Ocean Yearbook, 3:665 Ocean zoning, 4:174–181 appropriate scales, 4:178–179 marine protected areas, 4:178 physical and ecological features, 4:178 competition and conflict, 4:174 comprehensive zoning, 4:175–177 arguments for/against, 4:177 factor variations within schemes, 4:176T, 4:177 fisheries closures, 4:177 definition, 4:177 economic and distributional implications, 4:179 distributional effects, 4:179 legal decision rules, 4:179 optimal mix of uses, 4:179 public perceptions, 4:179 social preferences, 4:179 valuation complexities, 4:179 essential characteristics, 4:174 geographic positions, 4:175 institutional approaches, 4:179–180 decision-making agents, 4:180 limited nature of ocean space, 4:174 management challenges, 4:177–178 commons management, 4:177 nature of management, 4:177–178 marine protected areas, 4:178 impact on fishermen, 4:178 networks, 4:179 ‘no-take’ fisheries reserves, 4:178 optimal spatial distribution, 4:178 size and location, 4:178 see also Marine protected areas (MPAs) Massachusetts, 4:175F ocean space markets, 4:180 purposes, 4:175 regulation, 4:174 policy tool, 4:174 restriction duration variations, 4:174 restriction variations, 4:174 use variations, 4:174 value of ocean space, 4:174 Ochre sea star (Pisaster ochraceus), 4:763–764 OCMIP (Ocean Carbon-Cycle Model Intercomparison Project), 4:112F OCMIP-2 (Ocean Carbon Model Intercomparison Project -2) program, 4:648–650 participants, 4:649F, 4:650T Octopodidae (octopuses) bioluminescence, 1:380 brain functions, 1:526 spawning, 1:527
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Oculina patagonica (South American coral), 2:332–333 Oculina varicosa coral, 1:615–616 Ocypode spp. (ghost crabs), 5:53F ODAS (Ocean Data Acquisition System), 1:142 Odden, 5:141, 5:141–142, 5:146 Odobenidae (walruses), 1:395, 3:590–591, 3:605, 3:609T, 5:286T abundance, 5:286T trends, 5:286T acoustic advertisement displays, 3:618–619 conservation status, 5:286T diet, 5:290 distribution, 5:286T exploitation, 3:638 feeding behavior, 3:615 species, 3:609T, 5:286T trophic level, 3:623F see also Pinnipeds Odontocetes (toothed whales), 3:592F, 3:606–607T baleen whales vs., 1:276 defense from predators, 3:616–617 definition, 2:160 evolution, 3:593 exploitation, history of, 3:635–637 extant, 3:593 feeding, 3:616, 3:616F, 4:135 in ocean gyre ecosystems, 4:135 feeding mechanisms, 3:616, 3:616F growth and maturation, prolonged, 3:612–613, 3:612F migration and movement patterns, 3:598, 3:599 cetaceans vs., 3:596 sound production, 1:361, 1:361F taxonomy, 3:593, 3:606–607T family Delphinidae see Oceanic dolphins family Kogiidae see Kogiidae family Monodontidae see Monodontidae family Phocenidae see Porpoises family Physeteridae, 3:606–607T family Platanistidae, 3:606–607T family Ziphiidae see Beaked whales (Ziphiidae) trophic level, 3:622, 3:623F see also Marine mammals; specific species ODP see Ocean Drilling Program (ODP) Odum, H.T., 3:733–734 Odyssey AUV, data obtained, 4:481F, 4:482F Odyssey class AUVs, 6:263T OECD (Organization for Economic Cooperation and Development), shipbuilding support, 5:407 Off-axis volcanism, 3:817, 3:819F Office of Naval Research (ONR), 3:60 acoustics research, 1:92–93 Offshore breakwaters, 1:586–587
560
Index
Offshore gravel mining, 4:182–190 environmental impacts, 4:187–188 biological impacts, 4:188–189 physical impacts, 4:187–188 extraction process, 4:184–187 production, 4:183–184 UK, 4:182F prospecting surveys, 4:184 resource origin, 4:182–183 supply and demand outlook, 4:189 usage, 4:183–184 see also Pollution solids Offshore leasing, USA, 3:893 Offshore permafrost see Sub-sea permafrost Offshore sand mining, 4:182–190 environmental impacts, 4:187–188 biological impacts, 4:188–189 physical impacts, 4:187–188 extraction process, 4:184–187 sandy furrows, suction dredging, 4:185, 4:186F production, 4:183–184, 4:183F prospecting surveys, 4:184, 4:184F resource origin, 4:182–183 supply and demand outlook, 4:189 usage, 4:183–184 see also Pollution solids Offshore structures, 4:748–753 distribution, 4:748F environmental issues see Oil pollution see also Rigs and offshore structures OGCM see Ocean general circulation model (OGCM) O’Hara plankton sampler, 6:364, 6:366F OHC see Oceanic heat content Oi1 event, 4:325 OIB see Oceanic island basalts (OIB) Oil, 4:191 continental margins, 4:138 hydrocarbons, 4:191 spill see Oil pollution Oil exploration, threat to cold-water coral reefs, 1:622 Oil industry, surveying, 4:473–475 Oil platforms, Lophelia pertusa (coral) growth, 1:623 Oil pollution, 4:191–199 assessment, 4:198 after a spill, 4:198 prior to spill, 4:198 coral impact, 1:673 effects, 4:191, 4:195 biological damage, extent of, 4:195 geographical factors, 4:195 range of, 4:195 toxic damage, 4:195 vulnerable natural resources, 4:195 see also specific natural resources major inputs, 4:191F Prince William Sound, 1:459 recovery, 4:198 seabirds and, 5:224, 5:274, 5:276–277, 5:276F shore cleaning see Shore cleaning spill response, 4:193
aims, 4:193 booms, 4:193 dispersants, 4:193–194 in situ burning, 4:194 net environmental benefit analysis, 4:194, 4:194–195 shore cleaning methods, 4:194 skimmers, 4:193 tanker accidents vs. chronic inputs, 4:191–192 see also Oil spills Oil rigs see Rigs and offshore structures Oil slicks dampening effect on short surface waves, satellite remote sensing, 5:104F, 5:106 natural fate, 4:192–193 ‘weathering’, 4:192 remote sensing, 4:739–740 see also Oil spills Oil spills, 4:59 assessment after, 4:198 assessment before, 4:198 offshore drilling, Law of Treaty of the Sea, 4:749–750 response to, see also Oil pollution tanker accidents causing, 5:406 tracking, satellite remote sensing application, 5:104F, 5:107 see also Oil pollution; Oil slicks Oithona spp. copepods, 3:661, 3:662 Okhotsk Sea Amur River inflow, 4:201, 4:204–205, 4:205 basins, 4:200F, 4:201 Kuril Basin, 4:200F, 4:201, 4:203, 4:206 Bering Sea and, 4:201, 4:202, 4:204 biogenic silica burial, 3:681T, 3:682 chlorofluorocabon, 1:537 circulation, 4:200–207, 4:201–203, 4:202F prevailing winds, 4:202 convection, 4:206 mixing due to, 4:206 dichothermal layer, 4:204, 4:204F, 4:205 East Kamchatka Current, 3:359F, 3:365–366, 4:204 East Sakhalin Current, 4:202–203, 4:202F, 4:203 eddy fields, 4:203, 4:203F geography, 4:200–201, 4:200F Japan Sea and, 4:201, 4:203, 4:204 North Pacific and, 4:201, 4:202, 4:204, 4:206–207, 4:206F Pacific salmon fisheries, 5:13, 5:14, 5:19–20 polynya, 4:203, 4:540, 4:541, 4:543–544 sea ice, 4:203–204, 4:203F sea ice cover, 5:141, 5:142–143 interannual trend, 5:146 Soya Current see Soya Current straits, 4:201 see also specific straits
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tides, 4:200, 4:201, 4:201F water properties, 4:204–206, 4:204F, 4:205F bottom density, 4:205–206, 4:205F salinity, 4:204, 4:204F, 4:205 temperature, 4:204, 4:204F, 4:205 West Kamchatka Current, 4:202, 4:202F see also Kuroshio Current; Oyashio Current Okushiri Island, tsunami, 6:128–129 Olfaction deep-sea fishes, 2:70 dolphins and porpoises, 2:157 Oligocottus maculosus (tidepool sculpin), 3:282 Oligotrophic, definition, 4:337 Oligotrophic system, 3:805 Oligotrophic water, penetrating shortwave radiation, 4:382 Oligotrophs, 1:272 Olive ridley turtle (Lepidochelys olivacea), 5:214F, 5:217–218 see also Sea turtles OM (ocean mapping) see Mapping Ombai Strait, 3:238–239 mass transport, 3:239 El Nin˜o and, 3:242 OML see Mixed layer Ommastrephes spp. (squids), 4:135 Omori, F, 5:345 Omori’s law, 3:845–846 OMZ see Oxygen minimum zone (OMZ) ON see Organic nitrogen (ON) Oncorhynchus see Pacific salmon (Oncorhynchus) Oncorhynchus gorbuscha (pink salmon), 5:32, 5:33, 5:33F catch, 5:13F, 5:14, 5:16–17, 5:20F life span, 5:12 stock enhancement/ocean ranching, 4:147–148, 4:147T, 5:27 Oncorhynchus keta (chum salmon), 5:32, 5:33, 5:33F catch, 5:13F, 5:14, 5:17, 5:21F stock enhancement/ocean ranching, 4:147T, 4:148, 5:27 Japan, 2:528–530, 4:154, 4:154F, 5:19 Oncorhynchus kisutch (coho salmon), 5:32, 5:33 catch, 5:13F, 5:14, 5:15, 5:17F, 5:18F farming, 5:15 global production, 5:23, 5:24T population time series, 4:703F stock enhancement/ocean ranching, 4:147T, 4:149 Oncorhynchus masou (masu, cherry salmon), 5:32, 5:33 catch, 5:14 Oncorhynchus mykiss (rainbow trout), 2:453F farming, global production, 5:23, 5:24T stock enhancement/ocean ranching, 4:147T, 4:148, 4:153
Index Oncorhynchus nerka (sockeye salmon), 2:400F, 5:30–31, 5:33, 5:33F, 5:36 catch, 5:13F, 5:14, 5:15–16, 5:19F life history, 5:16 population fluctuations, 4:153 Oncorhynchus tshawytscha (chinook salmon), 5:32, 5:33 catch, 5:13F, 5:14, 5:14–15, 5:15F, 5:16F farming, 5:14–15 global production, 5:23, 5:24, 5:24T Pacific basin production, 5:15, 5:16F life span, 5:12 population time series, 4:703F Oncorhynchus tshawytscha (king salmon), 2:392F One-dimensional models, 4:208–217 case studies, 4:212–213 convective and internal wave mixing, 4:214 observed vs simulated SST, 4:213, 4:214F Ocean Station P, 4:212–213 physics, 4:212–213 definition, 4:208 estuary, 2:304 limitations and applications, 4:214–217 mixed-layer processed, 6:337–339, 6:344 numerical models of upper ocean mixed layer, 4:208–209 analytical near-surface layer models, 4:209 bulk models, 4:209 K-profile parametrization, 4:209–210 turbulence closure models, 4:210 oxygen and radiocarbon profiles, 4:107, 4:108F planktonic ecosystem, 4:210–212 Eulerian approach, 4:210–212 Lagrangian approach, 4:212 sediment entrainment, 1:47–48 Onomichi Maru, 4:770F Ontong Java Plateau, 5:186F, 5:189 Opah (Lampris spp.), 2:395–396F Opal (amorphous silica, SiO2), 4:90–91 biogenic, 1:371–372 flux, 1:374F diagenetic reactions, 1:266T in sediments, 5:335 origins, 5:335–336 productivity reconstruction, 5:335–336 diatoms, 5:336, 5:341F, 5:342 limitations, 5:336 organic carbon and, 5:335 OPC see Optical Plankton Counter (OPC) Open ocean atmospheric deposition, 1:242–244 metals, 1:242–244, 1:243T, 1:244F nitrogen species, 1:244–245, 1:244T, 1:246F synthetic organic compounds, 1:245–246, 1:246T chlorinated hydrocarbons, 1:554–555
Open ocean convection, 4:126–127, 4:218–225 buoyancy flux, 4:220, 4:223F buoyancy length scale, definition, 4:221–222 cascade process, 4:219–220, 4:220F convection cells, 4:218–219 cool skin see Cool skin diurnal cycles, 4:218, 4:223–224, 4:223F diurnal jet, 4:224 Kelvin-Helmholtz instability, 4:224 solar radiation, 4:223–224 thermal compensation depth, 4:223–224 turbulent boundary layer, 4:223F evaporation, 4:220 gas exchange, 4:218, 4:222–223 haline convection, 4:218, 4:220F heat exchange, 4:218 heat flux, 4:220, 4:222 laboratory experiments, 4:219, 4:221 mixed layer see Surface mixed layer Monin-Oboukhov theory, 4:221–222 nonpenetrative convection, 4:220, 4:221F Nusselt number, 4:222 ocean convection plumes, 4:218–219 see also Ocean convection plumes penetrative convection see Penetrative convection phenomenology, 4:218–220 turbulent convection, 4:219 plumes see Ocean convection plumes Priestly formula, 4:220–221 pycnocline, 4:220, 4:221F Rayleigh number, 4:218–219, 4:222 Red Sea circulation, 4:670–671 salinity, 4:220 seasonal cycles, 4:218, 4:224 stability parameter, definition, 4:221–222 surface cooling, 4:219F, 4:220 thermal boundary layer, 4:219 thermal convection see Thermal convection thermals, 4:219, 4:219F, 4:220 thermocapillary convection, 4:218 thermohaline convection, 4:218 turbulence, 4:220–222, 4:221–222 kinetic energy, 4:221–222, 4:224 wind stress, 4:221–222 velocity field, 4:218 vertical density gradient, 4:222 Weddell Gyre, 6:324 wind, effect of, 4:221–222, 4:223, 4:224 see also Air–sea gas exchange; Breaking waves; Deep convection; Nonrotating gravity currents; Photochemistry, processes; Rotating gravity currents; Small-scale patchiness models; Threedimensional (3D) turbulence; Upper ocean, mixing processes
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Open ocean fisheries deep-water species see Deep-sea fish(es); Demersal fisheries pelagic species see Pelagic fisheries Ophiolites, 5:363 definition, 3:817 hydrothermal vent deposits, 3:144, 3:149, 3:149–150 seismic structure profiling and, 5:364 Ophiuroidea (brittle stars), 1:353, 1:355 Opisthoproctus (barreleyes), 2:447F, 2:449F Opsanus tau (toadfish), 2:478–479 Optic(s), ocean see Ocean optics Optical absorption magnetometers, 3:479 Optical-Acoustical Submersible Imaging System (OASIS), 6:368–369 Optical backscatter, water-column, Massachusetts Bay, 4:481F Optical backscattering sensors, 3:246, 6:115 see also Nephelometry Optical coefficient, absorption see Absorption (optical) coefficient Optical constituents of seawater see Sea water, optical constituents Optical fibers advantages, 1:9 chemical sensors, 1:8–9 reflectometric, 1:12F typical instrumentation system, 1:10F construction, 1:8 evanescent waves, 1:9, 1:9F remotely-operated vehicles (ROV), 6:259 structure, 1:8, 1:8F transmission characteristics, 1:8–9, 1:9F types, 1:9 Optical irradiance probe, expendable, see also Expendable sensors Optically active components (AOC), 5:115 Optical oceanography see Ocean optics Optical particle characterization, 4:243–251 techniques, 4:243 analytical flow cytometry see Analytical flow cytometry (AFC) imaging, 4:250 photographic, 4:250 using remotely operated vehicle, 4:250 video, 4:250 optical plankton counting see Optical Plankton Counter (OPC) rapid, 4:243 see also Bio-optical models; Carbon cycle; Fluorometry; Inherent optical properties (IOPs); Irradiance; Ocean color; Ocean optics Optical Plankton Counter (OPC), 4:248, 4:353T, 6:357T, 6:367F, 6:368 applications, 4:248–249, 4:249F limitations, 4:250 Longhurst–Hardy Plankton Recorder vs., 4:249–250
562
Index
Optical Plankton Counter (OPC) (continued) operation calibration, 4:249 considerations, 4:249–250 technique, 4:248, 4:248F see also Zooplankton sampling Optical properties apparent see Apparent optical properties (AOPs) inherent see Inherent optical properties (IOPs) Optical scattering see Scattering (spectral) Optical systems, zooplankton sampling see Optical Plankton Counter (OPC); Zooplankton sampling Optics, ocean see Ocean optics Optimal interpolation (OI), estimation theory and, 2:7 Optimal Thermal Interpolation Scheme (OTIS), 2:9 Optimum yield crustacean fisheries, 1:705 definition, 2:182, 2:515 fishery management, 2:513 Optodes (optrodes), 1:7–14, 1:7F, 2:586, 2:586T absorptiometric see Chemical sensors Orange roughy (Hoplostethus atlanticus), 1:63, 4:226 acoustic scattering, 1:66 distribution, 4:226 open ocean demersal fisheries, 4:229–230, 4:229F FAO statistical areas, 4:230, 4:231T Orbit (Earth) aphelion, 4:505–506 clay mineral composition and, 1:569, 1:571T Earth, glacial cycles and, 4:505–507 long-term changes, uncertainty, 4:312 perihelion, 4:505–506 Orbit (satellites), ocean color sensing, 5:117–118 see also Geostationary orbit Orbital tuning, 4:311–318 accuracy limits, 4:312 error sources, 4:313 examples, 4:312F, 4:315–316 future prospects, 4:316–317 limitations, 4:314 mapping function, 4:311 methods, 4:313–314 visual mapping, 4:313 motivations, 4:316–317 multiple parameters, 4:316–317, 4:316F necessary conditions, 4:314–315 older sediments, 4:313 proxy response lags and, 4:316–317 verification, 4:314–315, 4:315 OrbView2 satellite see SeaWiFS Orcaella brevirostris (Irrawaddy dolphin), 2:156, 2:157 Orcinus orca see Killer whale (Orcinus orca)
Ordinary differential equations (ODEs), stage-structured population models, 4:549 Ore bodies, formation of, 2:49 Ore-carrying robotic submersible shuttles, 3:894–895 Oregon shelf bottom stress, 6:146–147, 6:146F NPZD-type ecosystem model, small-scale patchiness, 5:481 ¨ resund, Baltic Sea circulation, 1:288, O 1:291–292 Organic carbon (OC) atmospheric, 1:248–249 cycling in shore ecosystems, 4:254 deposition rates, 4:259T, 4:260 dissolved see Dissolved organic carbon (DOC) global reservoirs, 5:419F pump, 4:682 in sediments, 5:333 opal and, 5:335 in sediments, productivity reconstruction, 5:333–335, 5:335F equation, 5:333–334 estimation, 5:334–335, 5:335F Mu¨ller P, 5:334–335, 5:335F slope-dominated continental margins, 4:255 subcycle, Cenozoic, 1:517–519, 1:518F total, river water, 3:395T vapor-phase, land–sea exchange, 1:122 see also Carbon (C) Organic matter barite and, 1:264–265 dissolved see Dissolved organic matter (DOM) nitrogen isotope ratios (d15N), as productivity proxy, 5:333 oxidation pathways and free energy yields, 4:685, 4:686T transportation processes, 4:89–90 see also Organic carbon (OC); Sediment(s) Organic nitrogen (ON), 1:255 dissolved see Dissolved organic nitrogen (DON) nitrogen transport and, 1:257 total, 4:50 Organic particles as optical constituents of sea water, 4:624 see also Organic matter Organic phosphorus Black Sea profile, 1:216F, 1:405F dissolved see Dissolved organic phosphorus (DOP) Organisms discovery in volcanic crust, 2:48 see also Microbes; specific groups of organisms Organization for Economic Cooperation and Development (OECD), shipbuilding support, 5:407
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Organochlorines, 1:551 atmospheric input, 1:123T seabirds as indicators of pollution, 5:274, 5:274–275, 5:275 Organohalogens, air–sea transfer, 1:161–162 Organometallic compounds, 6:103 Organophosphate pesticides seabirds and, 5:274 sensors, 1:13 ORI-BB ocean bottom seismometer, 5:369T Origin of life, 2:34 hydrothermal vent ecology, 3:157 hydrothermal vent systems, 3:151, 3:157 acellular precursor, pyrite supported, 3:157 chemosynthetic basis, 3:157 Origin of oceans, 4:261–264 composition see Composition of oceans development/Earth’s acquisition of, 4:261–262 argon isotopes, 4:261, 4:262F established feature or degassing supply, 4:261 helium isotopes, 4:261, 4:262F initial presence of water, 4:262 meteoric origin of water, 4:261 planetary degassing, 4:261, 4:262F Rubey’s excess volatiles, 4:261, 4:261T slow growth with time, 4:261 water present at Earth’s formation, 4:263 future of the oceans, 4:264 decrease by photolysis of water vapor, 4:264 less subduction of hydrated crust, 4:264 steady state of water supply, 4:264 loss of water from Earth’s surface, 4:262–263 abundant oxygen inhibits dissociation, 4:262 oxidation of mantle, 4:263 oxidation of planet, 4:263 photolytic dissociation, 4:262 sources of water, 4:263 capture from solar nebula, 4:263, 4:263F claims of blocks of cometary ice, 4:263 cometary impacts, 4:263 neon isotopes, 4:263, 4:263F Orinoco River discharge, 4:755T Intra-Americas Sea (IAS), 3:288, 3:293F North Brazil Current (NBC), 2:561 sediment load/yield, 4:757T OS3 event, 3:886 Osborn–Cox method, microscalars, 2:292–294 Osborn method, 2:294–296 OSC see Overlapping spreading center (OSC)
Index Osmium (Os), 3:776, 3:779–780, 3:783, 4:494 concentration deep earth, 4:494T N. Atlantic and N. Pacific waters, 6:101T sea water, 4:494T, 4:497T vertical profiles, 3:778F, 3:779–780, 4:496–497, 4:498F isotope(s) geochemistry, 4:497–499, 4:501T ratio, in sea water, 4:498F, 4:499, 4:501T isotope ratios global distribution, 3:459F incongruent release, 3:465T time series, 3:461F long-term tracer properties, 3:456T, 3:462–463 in sewage, 1:200 source materials, isotope ratios, 3:457T see also Platinum group elements (PGEs) OSPAR Commission, 3:277 ¨ stlund, Go¨te, 4:645 O Ostracods, 1:376–378, 2:59F hypoxia, 3:177 Ostrea edulis (European flat oyster), mariculture disease agents, 3:520T stock acquisition, 3:532 Ostreococcus spp. alga, 3:558–559 Otariidae (eared seals), 3:590–591, 3:605, 3:609T, 3:610, 3:610F, 5:286T abundance, 5:286T trends, 5:286T conservation status, 3:609T, 5:286T distribution, 5:285, 5:286T lungs, 3:586F mother–infant recognition, 3:619 species, 3:609T, 5:286T subfamily Arctocephalinae see Arctocephalinae (fur seals) subfamily Otariinae see Otariinae (sea lions) trophic level, 3:623F see also Pinnipeds; specific species Otariinae (sea lions), 3:590, 3:609T, 5:286T hearing, 1:360F skeleton, 3:610F, 5:285F see also Otariidae (eared seals); specific species OTEC see Ocean thermal energy conversion (OTEC) Otoliths, 2:71F, 2:217 Otter, sea see Sea otter Otter multiple trawl nets, 2:537–538, 2:538F Otter multiple trawls, 2:537–538, 2:538F Outcrop, definition, 5:464 Outer Banks, North Carolina, USA, coastal erosion, 1:587–588 Outer Continental Shelf Lands Act, 3:893
Outflows Baltic Sea circulation, 1:288, 1:290–291, 1:294, 1:295T see also Danish Straits Intra-Americas Sea (IAS), 3:291–292 Mediterranean Sea circulation Cretan Arc Straits, 3:716–717 Gibraltar, 3:710, 3:711F, 3:712–714, 3:717–718 Red Sea circulation Gulf of Aqaba, 4:670–671, 4:673 Gulf of Suez, 4:670–671, 4:672–673 shallow, 4:674 Strait of Bab El Mandeb, 4:667, 4:673, 4:674, 4:675F see also specific outflows Ovalipes spp. (swimming crabs), 5:55F Overfishing causative factors, 1:651, 2:513, 2:522 definition, 2:522 effects on seabirds, 5:224, 5:271, 5:272–273 beneficial, 5:271–272, 5:272–273, 5:272T detrimental, 5:222, 5:271–272, 5:271, 5:272–273 stock depletion, 5:271 global exploitation state, 2:513, 2:514F ‘Malthusian’, 1:653 management, 5:224 see also Exploited fish, population dynamics; Fishery management Overflows, 4:265–271 along-slope flow, 4:267–268 ambient fluid columns, 4:268, 4:268–269 Coriolis force and, 4:267–268 currents and, 4:267 definition, 4:265 draining layer, 4:268–269 laboratory modeling, 4:269 Ekman layer and, 4:268–269 flow characteristics, 4:266–267, 4:267F basic behavior, 4:267–268 instability, 4:268, 4:270–271 inviscid along-slope flow, 4:268, 4:268F parameters, 4:266–267 speeds, 4:265 laboratory experiments, 4:269–270, 4:270F modeling, 4:269 numerical models, 4:270 streamtube models, 4:269, 4:269F Overlapping spreading center (OSC), 3:853F, 3:854, 3:875, 4:597, 4:601 Overshot, 2:40 Overside handling, oceanographic research vessels, 5:412 Overturning circulation, 1:188, 2:261–262 Antarctic Circumpolar Current and, 1:188–189 Black Sea, 1:412–413 Southern Ocean, 1:189F Oviparity, 1:356, 2:428, 2:428F
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563
Ovoviviparity, 2:428 Ownership rights, fishery stock manipulation, 2:533 Oxic layer, estuarine sediments, 1:539 Oxidants, estuarine sediments, 1:541T organic matter, 1:542–543 relative free energy yields, 1:542–543, 1:543F Oxidation FeOOH, 1:548F manganese, 6:79 organic matter, 1:542–543 see also Oxidants; Redox chemistry Oxidation ponds, 6:270 Oxidised nitrogen species, 1:255 deposition rates, 1:256T see also Nitrous oxide (N2O) Oxyanions, trace elements, 3:776–783 chemical speciation, 3:776 see also specific trace elements Oxygen (O2), 1:541T abundance, limiting loss of water from Earth’s surface, 4:262 availability in deep-sea, 2:56–57 benthic flux, 4:488F concentration, 4:127, 4:128, 4:129F, 6:183F concentration gradient, in sediments, 4:490 cycle, 4:90F phosphorus cycle and, 4:411–412 deep convection, 2:15 deep-sea-floor microelectrode results, 4:489, 4:490F demand in sediments, as productivity proxy, 5:339F depletion zones in upwelling ecosystems, 6:227 depth profiles, estuarine sediments, 1:545F dissolved Brazil and Falklands (Malvinas) Currents, 1:425, 1:426F, 1:427 Brazil/Malvinas confluence (BMC), 1:426F upper ocean structure and, 6:224 distribution, upper ocean, 6:178 estuaries, gas exchange in, 3:5 fluorescent sensing, 2:594, 2:594T influence on fish distribution, 2:371–372 isotope ratios see Oxygen isotope ratio isotopes, 4:272–273 isotope stage (OS) events, 3:885–886 from photosynthesis, productivity measures, 2:584–585 profile Atlantic Ocean, WOCE section 16, 3:301F Black Sea, 1:216F, 1:405F Southern Ocean, 1:180F as radioisotope source, 1:679 reduction in pore water, 4:566T saturation, 6:179F upper ocean, 6:178, 6:179F seasonal depth profile, Bermuda, 6:96F
564
Index
Oxygen (O2) (continued) stores, marine mammals, 3:583, 3:583F, 3:588 tracer applications, 4:56–57 transport, Baltic Sea circulation, 1:294–295 use by Antarctic fishes, 1:192–194 Oxygen isotope ratio (d18O), 4:272 calcium carbon content and, 1:452F Cenozoic records, 1:506–509, 1:510F, 5:185–186 caveats, 1:512 foraminiferal, 1:506–507, 1:507F, 1:508F ‘greenhouse world’, 1:509 ‘ice house world’, 1:509–511 clay mineral composition and, 1:570F clouds (values), 1:503, 1:503F, 1:504F coral-based paleoclimate records, 4:339–340, 4:339T, 4:341 climate trends, 4:343, 4:343–345, 4:344F El Nin˜o Southern Oscillation, 4:341–342 seasonal variation, 4:341 temperature and salinity reconstructions, 4:340 corals, 2:104 Cretaceous, 4:322F depth profile, 4:51F determination, 1:502 effects of evaporation, 1:503, 1:503F effects of precipitation, 1:503, 1:503F estimation of sea level variations, 5:185 glacial cycles and, 4:505, 4:507 ice cores, 1:1, 1:2F, 3:883 in marine sediment deposits, and monsoon activity, 3:911 marine sediments, 1:2F ocean values, 1:504–505, 1:505F deep, 1:502 ice sheet effects, 1:505–506 surface, 1:502 paleoclimate and, 4:319–320 paleothermometry, 1:502–503 equation, 1:502–503 planktonic–benthic foraminifera differences, 3:915F as present monsoon indicator, 3:913 rain (values), 1:503, 1:504F reporting standards, 1:502 salinity and, 1:504–505, 1:505F sea surface temperature paleothermometry and, 2:100, 2:101T snow (values), 1:503, 1:504F systematics, 1:502 variations glacial–interglacial, 1:505–506, 1:507F interspecific, 1:512 in natural environment, 1:503–504, 1:503F, 1:504F Pleistocene, 1:505–506, 1:507F spatial, in modern sea water, 1:504–505, 1:505F
between species, 1:512 temporal, 1:505, 1:506F Oxygen isotope stage (OS) events, 3:885–886 Oxygen minimum zone (OMZ), 3:173, 3:177, 6:227, 6:231 benthic fauna, 3:178–179 definition, 3:173 ferromanganese deposits and, 1:261 formation, 3:911–912 and sediment bioturbation, 3:911, 3:911–912 Oxystat benthic lander, 4:492–493 Oxystele variegata gastropods, 4:763 OY see Optimum yield Oyashio Current, 3:358, 3:359F, 3:365–368 East Kamchatka Current vs., 3:365–366 intrusions first, 3:367–368, 3:367F second, 3:367–368 origins, 3:365 paths, 3:367, 3:367F sea surface temperature anomalies and, 3:368–369, 3:368F Subarctic Current and, 3:367 volume transport, 3:366 annual cycle, 3:366 World Ocean Circulation Experiment (WOCE) observational program, 3:369 Oyashio Front, 3:367 Oyster(s) biology, 4:275–276 broodstock, 4:277 European flat see Ostrea edulis (European flat oyster) farming see Oyster farming as healthy food source, 4:274 Japanese cupped see Crassostrea gigas (Japanese cupped oyster) mariculture, 3:904, 3:905F see also Mollusks; Oyster farming measurement, 3:903 pearls see Pearls Portuguese see Crassostrea angulata (Portuguese oyster) see also Bivalves; Mollusks; specific species Oyster farming, 4:274–286 cultivation methods on-growing, 4:278–281, 4:280F seed supply, 4:276 site selection for on-growing, 4:282–283 spat collection, 4:276, 4:276F see also specific methods diseases, risk of, 4:283–284 fattening ponds (claires), 4:281, 4:282F food safety, 4:285, 4:285F history, 4:274 nonnative species, 4:284–285 production, 4:274–275, 4:275T risks, 4:283 see also specific risks steps and processes, 4:281F
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stock enhancement, 4:284 Oystershell middens, formation, 3:899 Oyster tongs, molluskan fisheries, harvesting methods, 3:900F, 3:901 Ozmidov scale, 2:616, 2:617–618 fossil turbulence, 2:612 three-dimensional (3D) turbulence, 6:22, 6:23–24 Ozone (O3) cycling, nitric oxide, 1:165 depletion, 4:128 North Atlantic Oscillation and, 4:71 ocean color sensing and, 5:120 UV-B radiation level, concentration effects to, 4:414 Ozone Monitoring Instrument (OMI), 5:120
P P230, definition, 6:242 P231, definition, 6:242 PA (Pelops anticyclone), 1:748–751, 1:748F Pachystomias spp. (dragonfishes), 2:453 Pacific see Pacific Ocean Pacific cod (Gadus macrocephalus), population, El Nin˜o and, 4:704 Pacific Decadal Oscillation (PDO), 4:461–462, 4:462F effects on Alaska Current, 1:465 index time series, 4:712F Peru-Chile Current System (PCCS) and, 4:390–392 Pacific Deep Water (PDW), 1:26 radiocarbon, 4:643–644 Pacific equatorial belt, carbon dioxide, 1:491 Pacific Equatorial Water (PEW), temperature–salinity characteristics, 6:294T, 6:298, 6:298F Pacific-Farallon ridge, causes of rift propagation, propagating rifts, 4:601 Pacific hake (Merluccius productus), population, El Nin˜o and, 4:704 Pacific halibut (Hippoglossus stenolepis), population density, body size and, 4:704 Pacific herring (Clupea pallasii), 4:364 Pacific-Indian throughflow, freshwater fluxes, 4:123F Pacific-(inter)Decadal Oscillation (PDO) regime shifts and, 4:702–703, 4:703F salmon populations and, 4:702–703, 4:703F Pacific krill (Euphausia pacifica), 3:353, 3:356 Pacific-Nazca-Antarctica triple junction see Juan Fernandez microplate Pacific-Nazca ridge, Easter microplate see Easter microplate Pacific Ocean abyssal circulation, 1:26, 1:27F, 1:28F see also Abyssal currents
Index actinium depth profile, 6:253F Atlantic Ocean vs., 1:234, 1:236–237 barium accumulation, 1:264F barrier layer, 6:181 benthic foraminifera, 1:339T calcite, depth profile, 1:448F calcite compensation depth, 1:447–448 carbonate compensation depth, 1:453F carbonate saturation, 1:450–451 climate effects on fisheries, 2:486–487 continental margins, 4:141–142, 4:256T primary production, 4:259T coral records, 4:343, 4:343F, 4:344F coral reefs, radiocarbon record, 4:638–639, 4:638F, 4:639F dust deposition rates, 1:122T eastern see Eastern Pacific eastern equatorial, thermocline, 2:242 eastern tropical atmosphere, 2:242 sea surface temperature, 2:241, 2:241F warming, El Nin˜o, 2:242 see also Intertropical Convergence Zone Ekman transport, 2:225 El Nin˜o-Southern Oscillation (ENSO), 4:461, 6:229–230 equatorial currents see Pacific Ocean equatorial currents ferromanganese oxide deposits, 3:488T food webs subarctic north Pacific, 4:133F subtropical north Pacific, 4:134F fossil layers, 6:222 frontal position instabilities, satellite remote sensing of SST, 5:99, 5:101F frontal systems, 4:136 krill species, 3:350–351, 3:350F lead-210/radium-226 ratio, 6:249F, 6:250F magnetic anomalies (linear), 3:485F manganese nodules, 3:490F, 3:491, 3:492–493 mantle plumes, 5:300–301 North see North Pacific North Atlantic vs., nitrate concentrations, 4:36, 4:37F North-eastern see North-East Pacific ocean gyre ecosystem, 4:133 opal flux, 5:336, 5:340 Pacific Decadal Oscillation (PDO), 4:461–462, 4:462F pelagic fisheries, 4:368 platinum profile, 4:497, 4:500F productivity reconstruction, 5:339–340, 5:339F radiocarbon, 4:641F, 4:642 GEOSECS and WOCE comparisons, 4:645F meridional sections, 4:643F, 4:648F radium isotope distribution, 6:251, 6:252F regime shifts, 2:487 salinity, meridional sections, 1:415F
sea–air flux of carbon dioxide, 1:493, 1:493T sea ice cover, 5:141–142 seamounts and off-ridge volcanism large igneous provinces(LIPs), 5:296, 5:297F non-plume related, 5:299–300, 5:300F, 5:301F, 5:302F sea surface temperatures, ENSO and, 2:230 South see South Pacific Ocean subsurface passages, 1:15–16, 1:15F temperature, meridional sections, 1:415, 1:415F thermal streaks, aerial photograph, 3:376F thorium-228 distribution, 6:247F trace element concentrations, 6:78 trace metal isotope ratios, 3:457 beryllium, 3:464F tropical, SST distribution, satellite remote sensing, 5:97–98 uranium isotope ratio depth profile, 6:246F vertical profiles, 6:217F volcanic helium, 6:124–125, 6:124F, 6:279 water masses intermediate waters, 6:295, 6:296F temperature–salinity characteristics, 6:291–292, 6:292–293, 6:292F, 6:293F, 6:294T, 6:297–298, 6:298F upper waters, 6:295, 6:295F western, mixing, indirect estimate, 2:297, 2:297F western equatorial, thermocline, 2:242 wind change, El Nin˜o and, 2:243–244 see also Eastern Pacific; North Pacific; South Pacific Pacific Ocean equatorial currents, 4:287– 294, 4:287F Indian Ocean equatorial currents vs., 3:226, 3:236 mean flow, 4:288–289 boundary flows, 4:287F, 4:289–290 subsurface, 4:290–291, 4:291F surface, 4:289–290, 4:291F interior flows, 4:287F, 4:288–289 subsurface, 4:289, 4:290F, 4:291F surface, 4:288–289, 4:288F, 4:289F South, as East Australian Current source, 2:187, 2:195 variability, 4:291–293 annual cycle, 4:291–293, 4:292F associated with El Nin˜o events, 4:292–293, 4:293–294, 4:293F high-frequency current, 4:294 meridional current, 4:291–292, 4:292F, 4:294, 4:294F zonal current, 4:291–292, 4:292F, 4:293F, 4:294 see also specific currents Pacific Ocean perch see Sebastes alutus (Pacific Ocean perch)
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Pacific Ocean South Equatorial Current, as East Australian Current source, 2:187, 2:195 Pacific oyster (Crassostrea gigas), 2:334, 2:341, 4:274F D-larva, 4:277, 4:278F methods of cultivation, 4:279, 4:280F production, 4:275, 4:275F, 4:275T see also Japanese cupped oyster (Crassostrea gigas); Oyster(s) Pacific ridley turtle, 5:214F see also Sea turtles Pacific salmon (Oncorhynchus), 2:501, 5:29, 5:33, 5:34 diet, 5:33 farming global production, 5:23, 5:24, 5:24T issues, 5:17–19 see also Pacific salmon fisheries predation, 5:34 stock enhancement/ocean ranching, 4:147–148, 4:147T, 5:27 taxonomy, 5:29 vertical movement, 5:33 see also specific species Pacific Salmon Commission (PSC), 5:21–22 Pacific salmon fisheries, 5:12–22 Canada see Canada catch, 5:13–15 ENSO events, impact, 5:14, 5:15 by fishing nations, 5:14, 5:14F, 5:15F, 5:17F, 5:19F, 5:20F, 5:21F by species, 5:13F, 5:14 endangered species, 5:22 historical aspects, 5:12–13 issues, 5:17–19 management, international collaboration, 5:12–13, 5:19–22 methods/gear types, 5:12, 5:13 research, 5:12–13 see also Pacific salmon (Oncorhynchus), farmingsee specific species Pacific Subarctic Intermediate Water (PSIW), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F Pacific Subarctic Upper Water (PSUW), temperature–salinity characteristics, 6:294T Pack ice Antarctic Ocean see Antarctic Ocean Arctic Ocean, 1:95F see also Arctic Ocean perennial, 6:158–159 Paedomorphosis, 2:160 Pagodroma nivea (snow petrels), 4:594 see also Procellariiformes (petrels) Pagrus major see Red sea bream (Pagrus major) Paine, Bob, 4:763–764 Paine Instruments, Inc., 1:713–714 Pakicetidae, 3:592 see also Cetaceans
566
Index
PALACE (profiling autonomous Lagrangian circulation explorer), 6:370 Palaemonetes varians, thermal discharges and pollution, 6:13 Palawan Island, Philippines, seiches, 5:349F Paleoceanography, 4:295–302 bathymetric resolution requirements, 1:299T climate models, 4:303–310 applications, 4:303 history, 4:303 OGCM see Ocean general circulation model (OGCM) seaways, 4:308–309 verification, 4:309 by incorporation of isotopic fractionation, 4:309 definition, 4:295–298 genetic diversity, 4:561 see also Population genetics of marine organisms history, 4:295–298 see also specific expeditions/projects Holocene, importance of, 3:125–126 interocean gateways and global climate systems, 4:303–304 Denmark Strait, 4:306–307 Drake Passage, 4:304, 4:305–306 implications, 4:307, 4:309 Indonesian–Malaysian Passages, 4:306 Isthmus of Panama, 4:304–305, 4:305–306 Straits of Gibraltar, 4:306 interocean gateways opened/closed during Cenozoic, 4:303, 4:304F models, 4:93 numerical dating techniques, 4:299 ocean circulation, Late Cretaceous see Late Cretaceous orbitally tuned timescales see Orbital tuning oxygen isotope analysis, 4:297 proxy data, 4:295 measurement of, 4:298, 4:298F relevance, 4:295 research directions, 4:301 sea surface temperature see Sea surface temperature paleothermography sediment core recovery, 4:296, 4:297F sediment records, correlation techniques, 4:299 studies, contributions to, 4:299–301 techniques, 4:298–299 see also specific techniquessee see also specific epochs/eras Paleoceanography, 4:295 Paleocene bottom-water warming, 3:788 climate, 4:321 see also Cenozoic Paleocene-Eocene Thermal Maximum (PETM), 4:321, 4:322F
Paleoclimate coral-based research see Coral-based paleoclimate research history of study, 3:123 Paleoclimatology, 1:1–3 Paleocurrent reconstructions, clay minerals, 1:570 Paleogene climate, modeling, 4:326 temperature gradients, 4:319 Paleoindian settlements, in North America, 3:697 Paleolatitude, 3:484–485 Paleomagnetism, 3:25–27, 3:484–487 marine sediments, 3:26–27, 3:27F polarity reversals, 3:26 frequency, 3:26 timescales, 3:26 Quaternary lavas, 3:26 remanent magnetization see Natural remanent magnetization (NRM) see also Geomagnetic polarity timescale (GPTS) Paleotemperature Mg/Ca and, 4:323F oxygen isotope ratio and, 4:319–320 Paleothermometers, sea surface temperature paleothermography, 2:101–103 Paleothermometry, SST see Sea surface temperature paleothermography PALK method, natural radiocarbon, 4:646, 4:647F Palladium (Pd), 4:494 anthropogenic release into environment, 4:502, 4:502F commercial demand/utilization, 4:502, 4:502F concentrations deep earth, 4:494T N. Atlantic and N. Pacific waters, 6:101T sea water, 4:494T vertical profile in sea water, 4:496 see also Platinum group elements (PGEs) Palladium-231 concentration depth profile, 6:248F dissolved, distribution, 6:248–250 uranium-235 activity ratio, 6:248–249 Palygorskite, 1:266–268 Pamlico Sound, North Carolina, USA, 3:381F Panama, Isthmus see Isthmus of Panama Panama Basin, coccolith flux, 6:7–8 Panama-Columbia Bight, 3:288 Panama-Columbia Gyre (PCG), 3:288, 3:293F Panamanian Isthmus see Isthmus of Panama Panamax bulkers, 5:402–403, 5:403T Panmixia, 2:217 Pantropical organisms, 2:160 Pantropical spotted dolphin (Stenella attenuata), 2:158F, 2:159–160
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Panulirus cygnus (western rock lobster), 3:444–445 fishery assessment research catch forecast, 1:703–704, 1:706F puerulus settlement, 1:704–705, 1:707F Panulirus ornatus (tropical spiny rock lobster), 3:539 Papahanaumokuakea Marine National Monument, Hawaii, USA, 4:180 Papua New Guinea earthquake (1998), 6:129 tsunami (1998), landslide and, 6:132–133 Parabolic equation acoustic modeling, shallow water, 1:119 Parabolic equation model (acoustic), 1:105, 1:106F Paralichthys olivaceus (Japanese flounder; bastard sole) see Japanese flounder (Paralichthys olivaceus) Paralomis formosa, Southern Ocean fisheries, 5:518 Paralomis spinosissima (Antarctic king crab), Southern Ocean fisheries, 5:518 Parameter estimation, 2:1–3 via data assimilation, 2:3 see also Data assimilation in models Parana/Uruguay dissolved loads, 4:759T river discharge, 4:755T Parasites, associated with baleen whales, 1:282 Parasitic capillary waves, 5:575F, 5:580 generation, 5:579, 5:579F see also Surface, gravity and capillary waves Parasitic disease, mariculture see Mariculture; Mariculture diseases Parental care of eggs, intertidal fish, 3:285 fish, 2:428–429 Parental investment theory, seabirds, 5:254 Pargo (USS), 1:93–94 Parrotfishes (Scaridae), 1:657 Partial differential equations, discretization, 4:92 Partial pressure of atmospheric carbon dioxide (PCO2), 1:479 Cenozoic decreased, 1:514, 1:515–516, 1:516 Raymo’s hypothesis, 1:516 reconstructions, 1:514, 1:514F Henry’s law, 1:479–480 response to changes in sea water properties, 1:479–480, 1:480F sea–air, 1:489–491, 1:490F see also Carbon dioxide (CO2) Partial pressure of CO2 of ocean water (pCO2)sw, 1:488 seasonal effects, 1:491 ‘skin’ temperature, 1:489
Index Partial pressures chlorofluorocarbons (pCFC), age calculations, 1:533–534 Partial Test Ban Treaty, 4:638 Particle(s) aggregation dynamics see Particle aggregation dynamics bio-optical models, 1:385–388, 1:387F characterization, 4:243 nonoptical techniques, 4:243 optical techniques see Optical particle characterization detection systems, zooplankton sampling, 6:364–365, 6:367F elemental distribution and, 2:258–260 flux definition, 4:337 investigated by uranium-thorium decay series, 6:242T see also Particle flux, temporal variability inorganic see Inorganic particles organic, as optical constituents of sea water, 4:624 properties, 4:243 size, distribution function, 1:386, 1:387F suspended see Suspended particles see also Particulate matter Particle aggregation dynamics, 4:330–337 destructive/transformative processes, 4:330, 4:336–337, 4:337 animal feeding, 4:336 microbial decomposition, 4:336 physical processes, 4:336 solubilization, 4:336 turbulence, 4:336 production processes, 4:330–333, 4:337 formation of aggregated particles, 4:331F, 4:333–335, 4:334F biologically mediated, 4:330, 4:331F, 4:333–335, 4:334F physically mediated see Coagulation, particle origins of primary particles, 4:330–333, 4:331F, 4:332F, 4:333F significance, 4:330, 4:337 see also Marine snow Particle flux, temporal variability, 6:1–9 causes, 6:1–2 reality of, 6:1 Sargasso Sea see Sargasso Sea sediment traps, 6:1 stationary traps, 6:1 timescales, 6:2–4 anomalies, 6:6–7, 6:7F decadal, 6:7 diurnal, 6:4 episodic, 6:7–8 interannual, 6:6–7 monthly, 6:4 seasonal, 6:4–6 ubiquity of, 6:1 see also Particle(s), flux
Particulate detrital matter (POM) absorption spectra, 4:415F definition, 4:415–416 photochemical processes, 4:414 Particulate inorganic carbon (PIC) concentrations, determination by underwater transmissometry, 6:117–118, 6:117T flux, Arabian Sea, 1:372–373 total flux, 1:372–373, 1:373F Particulate matter, 1:248 atmospheric transport and deposition see Aerosols coastal waters, absorption (optical) spectra, 4:734 concentration depth profile, 4:12F suspended, optical scattering, 4:8 volume transported by wind, 1:248 see also Particle(s); Particulate inorganic carbon (PIC); Particulate nitrogen (PN); Particulate organic carbon (POC); Suspended particles Particulate nitrogen (PN), 4:40–41 atmospheric deposition, 1:255–257 atmospheric emissions, 1:255T composition, 1:255 deposition rates, 1:256T global deposition, 1:256F isotope ratios, 4:50–51, 4:52F depth profile, 4:51–52 sinking, 4:51–52 Particulate organic carbon (POC), 1:371 aggregates, 1:372 ballast components, 1:371–372 biological pump contribution, 1:481–483 dissolved organic carbon vs., 1:484–485 composition, 1:371 depth profile, 5:427F flux measurement, 1:372 inverse modeling, 3:309F, 3:310 Land–sea exchange, 1:122 non-viable material, 1:122–123 viable material, 1:122 metabolism, 1:371 total flux, 1:372–373, 1:373F Particulate organic nitrogen (PON), 4:32 decomposition, 4:33–34, 4:34F depth distribution, 4:35–36, 4:37F see also Nitrogen cycle Passenger vessels, 5:404 cruise ships, 5:404 ferry fleet, 5:404 Passive margins, geophysical heat flow, 3:47–48 Passive sensors, 3:108 Passive sonars see Sonar systems, passive sonar Passive systems aircraft for remote sensing see Aircraft for remote sensing Multichannel Ocean Color Sensor (MOCS), 1:141–142 see also Ocean color
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567
Ocean Data Acquisition System (ODAS), 1:142 see also Phytoplankton blooms; Primary production distribution; Satellite remote sensing of sea surface temperatures Past climate research see Coral-based paleoclimate research; Paleoceanography, climate models Patagonian toothfish see Dissostichus eleginoides (Patagonian toothfish) Patch dynamics, 4:348–355 food web implications, 4:349, 4:353–355 flow patterns, 4:354 predator–prey interactions, 4:352, 4:353–354, 4:355 history, 4:348–352 observations and analysis techniques, 4:348, 4:348–349, 4:352–353, 4:355 direct, 4:353 role of turbulence, 4:348–349, 4:349, 4:352, 4:354–355 sensors, 4:353T, 4:354F acoustic sounding, 4:352–353, 4:353T fluorometer, 4:353T fractal analysis, 4:353 optical plankton counter, 4:353T satellite, 4:350F, 4:352–353, 4:353T towed nets, 4:353T video plankton recorders, 4:349, 4:353, 4:353T, 4:354F unknowns, 4:355 Patchiness definition and description, 5:474 plankton see Plankton patchiness role, 5:474 small-scale see Small-scale patchiness Pathfinder SST (PSST), 5:92–93 Patinopecten yessoensis (Japanese scallop), stock enhancement/ocean ranching programs, 2:528–530, 4:147T, 4:151, 4:152F Pawleys Island, South Carolina, USA, coastal erosion, 1:586F 231 Paxs, definition, 6:242 Payne, R.E., 4:379–380, 4:380 PCA (principal component analysis), 4:719–720 PCA (principle-component analysis), 4:719–720 PCBs (polychlorinated biphenyls) see Polychlorinated biphenyls (PCBs) PCG (Panama-Columbia Gyre), 3:288, 3:293F PCGC see Preparative capillary gas chromatography PD, definition, 6:242 PDO see Pacific-(inter)Decadal Oscillation Pe (electron affinity), 1:540–542 P/E (salinity effect), 2:102 Peale’s petrel, 4:591F see also Procellariiformes (petrels) Pearl Beach, Australia, 1:309F
568
Index
Pearl oysters, harvesting, 3:902–903 Pearls, 4:281–282 formation, 3:899 production, 4:282T Pearlsides (Maurolicus muelleri), 2:415 Pearly nautilus (Nautilus spp.), 1:524 PEAS (possible estuary-associated syndrome), 4:432, 4:434T, 4:435T Peat moss, 3:898 Pechora, sub-sea permafrost, 5:566 Peclet number, 1:396, 1:396T, 4:568 definition, 4:162 Pecten maximus (great scallop), stock enhancement/ocean ranching programs, 4:147T, 4:151–152, 4:152F Pectinidae (scallops), adaptations to resist shear stress, 1:332–333 Pedogenesis, definition, 1:268 Peedee formation, 5:529 Peel-Harvey estuarine system, 2:317 Peepers, 4:564 Pelagic, definition, 1:268 Pelagic biogeography, 4:356–363 concordance of patterns, 4:360–363 ‘bipolar’ species, 4:361 euphausiids, 4:360, 4:361–362 oceanic tuna, 4:362–363 diversity of biota, 4:356–358, 4:357T analyses, constraints, 4:356 latitude and, 4:356, 4:357T future directions, 4:363 historical aspects, 4:356 planktonic foraminifera, 4:606 population(s), 4:358–359 diel vertical migration, 4:358–359 disjunct, 4:361 expatriation and, 4:358 member–vagrant hypothesis, 4:358–359, 4:362 persistence, 4:358 persistence mechanism, 4:358 regional oceanography influence on biogeochemical provinces see Biogeochemical provinces distribution of organisms, 4:359–360 ecology, 4:359–360 Sverdrup’s model of seasonal cycle of phytoplankton, 4:359, 4:361T see also Coral reef(s); Marine biodiversity Pelagic fish(es), 4:364–369 benthopelagic, 2:67 biomass, north-west Atlantic, 2:505–506, 2:506F clupeoids, 4:364–366 herring, 4:364–366 sardines, 4:366–368 sprats see Sprat see also Herring (Clupea); Sardines (Sardina, Sardinops, Sardinella) exploited communities, variability patterns, 2:505, 2:506F feeding, 2:505 groups clupeoids, 4:364, 4:364–366
mackerels, 4:364, 4:368–369 tunas, 4:364, 4:368 see also Clupeoids; Mackerel (Scomber scombrus); Tuna habitat, 2:505 importance to fisheries, 4:369 mariculture, 4:241 oil content, 5:468 recreational fishing, 4:241 shoaling, 5:468, 5:472 fishing methods impact, 2:535, 5:468 location determination, 5:468, 5:472 sprats, 4:366 utilization, 4:240–241 wasp-waist control, 4:700–702 see also Fishery resources; Fish horizontal migration; Mesopelagic fish(es); specific species Pelagic fisheries, 5:468–473 economic importance, 5:472 ghost fishing, 4:237 landings, 5:468, 5:469F, 5:469T management issues, 4:232–233, 5:471–473 stock fluctuations, 5:472, 5:472F methods/gears, 2:90, 4:234–235, 5:468–469 shoaling behavior impact, 2:535, 5:468 open ocean, 4:234–242 landings, 4:239–240, 4:239F, 4:240F methods, 4:234–235 see also specific methods/gears resource conservation, 4:241–242 predator control, 2:205 products, 5:470–471, 5:471T biotechnology resources, 5:471 research directions, 5:472–473 Pelagic food web, 3:124 Pelagic habitat, 2:160 Pelagic organisms biodiversity, 2:143 depth-related patterns, 2:143 distributions, 2:139–140 water mass delineation, 2:142–143, 2:143 see also specific pelagic organisms Pelagic tunicates see Gelatinous zooplankton; Tunicates Pelagic zones, 2:217 Pelecanidae (pelicans), 4:370, 4:371–373 breeding patterns, 4:373 characteristics, 4:371–373, 4:376T feeding patterns, 4:371–373, 4:376T human disturbance, 4:373 migration, 5:242–244 species, 4:371–373, 4:372F threats, 4:373 see also Pelecaniformes; specific species Pelecaniformes, 4:370–378, 4:372F behavior, 4:376, 4:376T, 4:377F breeding patterns, 4:376 characteristics, 4:370 conservation, 4:376–378 distribution, 4:370–371 ecology, 4:375–376
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feeding patterns, 4:375–376, 4:376T fossils, 4:370 migration, 5:242–244 plumage, 4:375 population status, 4:378 taxonomy, 4:370, 4:370–371, 5:266T family Anhingidae see Anhingidae (darters) family Fregatidae see Fregatidae (frigatebirds) family Pelecanidae see Pelecanidae (pelicans) family Phaethontidae see Phaethontidae (tropic birds) family Phalacrocaracidae see Phalacrocoracidae family Sulidae see Sulidae (gannets/ boobies) see also Seabird(s); specific species Pelecanoididae see Diving petrels Pelecanus occidentalis see Brown pelican Pelicanoides urinatrix (common diving petrel), 4:591F, 5:252 Pelicans see Pelecanidae (pelicans) Pelops anticyclone (PA), 1:748–751, 1:748F Penaeus esculentus (tiger prawn), fishery assessment research, 1:703, 1:704F, 1:705F Penaeus japonicus (kuruma prawn), stock enhancement/ocean ranching, Japan, 2:528–530 Penaeus merguiensis (banana prawn), predator defense, 1:700 Penetrating shortwave radiation, 4:379–384 albedo see Albedo downward irradiance, spectrum of, 4:380–381, 4:381F modeled irradiance, 4:381–382 parameterized irradiance vs. depth, 4:382–383, 4:382F, 4:383F Penetrative convection deep convection, 2:15–16 open ocean convection, 4:220, 4:221F, 4:223–224 density jump, 4:220 thermals, 4:220 Penguins see Sphenisciformes (penguins) Penrhyn Basin, manganese nodules, 3:493 Pentachlorobiphenyls, structure, 1:552F Perca fluviatilis (perch), 2:454F Percent areal coverage see Sea ice, concentrations Perch (Perca fluviatilis), 2:454F Perennial pack ice, 6:158–159 Performance monitoring demersal fisheries management, 2:95 fishery stock manipulation, 2:532–533 Peridinium, 3:574F Peridotite, definition, 3:816–817 Perihelion, 4:505–506 Perim Narrows, 4:666F, 4:674 Perkinsus marinus pathogen, 2:489
Index Permafrost, 5:559–560 high sea levels, 5:559 hydrate dissociation, 3:785–786, 3:786, 3:787F see also Methane hydrate(s) low sea levels, 5:559 onshore, submergence effects, 5:562 sea level variation and, 5:183 Permanent pycnocline, 2:266–269 Permanent Service for Mean Sea Level (PSMSL), 5:179 see also Sea level changes/variations Permanent thermocline, 6:175, 6:181–182, 6:211 regional distribution, 6:182F see also Thermocline, main Permittivity, 2:247–248, 2:248–249, 2:251, 2:251–252 electronic polarization and, 2:251 Perrin’s beaked whale, 3:643 Perry Submarine Builders, 3:513 Clelia, 3:515F Deep Diver, 3:514F Persistent organic pollutants (POPs), 1:553 Personnel, research vessels see Oceanographic research vessels Personnel sphere, 6:255–257 Pertechnetate, 4:632 Peru, water, microbiological quality, 6:272T Peru Basin, manganese nodules, 3:492, 3:494 Peru–Chile Countercurrent (PCCC), 4:387 Peru–Chile Current (PCC), 4:387 Peru–Chile Current System (PCCS), 4:385–392 chlorophyll concentration, 4:386F, 4:389, 4:389F currents, 4:385–388, 4:385F coastal, 4:387 cross-section, 4:391F offshore, 4:387 see also Peru Current ecosystem, 4:388–390 El Nin˜o events and, 4:391 Ekman pumping velocity, 4:386F El Nin˜o Southern Oscillation (ENSO), 4:391 Intertropical Convergence Zone (ITCZ) and, 4:387 sea level, 4:387 sea surface temperature (SST), 4:386F anchoveta/sardine production and, 4:390F temperature anomaly, 4:385F upwelling, 4:387–388 variability, intensity, 4:391 variability, 4:390–392 El Nin˜o effect, 4:390F, 4:392 interannual and decadal, 4:391 winds, 4:386F, 4:387 zooplankton, 4:389–390 Peru–Chile Undercurrent (PCUC), 4:387–388 flow, 4:287F, 4:291
see also Pacific Ocean equatorial currents Peru Current, 4:385 catch, anchovy and sardine, 4:701F flow, 4:287F, 4:290 seabird responses to climate change, 5:262–263, 5:263F see also Pacific Ocean equatorial currents; Peru–Chile Current System (PCCS) Peru Margin, monsoon evolution, 3:917 Perumytilus purpuratus mussel, 4:768 Peru trench, nepheloid layers, 4:16F, 4:17 Peruvian anchoveta see Engraulis ringens (Peruvian anchoveta) Pesticides, 1:248 chlorinated see Chlorinated pesticides optical sensors, 1:13 PET (photosynthetic electron transfer), 2:584 Petagrams, 1:487 Petersen, C.G.J. classification of the benthos, 1:349, 1:350, 1:351T macrobenthos studies, 3:475 PETM see Paleocene-Eocene Thermal Maximum Petrels see Procellariiformes (petrels) Petroleum dominance of in cargo volume, 5:401, 5:402T see also Oil PEW (Pacific Equatorial Water), temperature–salinity characteristics, 6:294T, 6:298, 6:298F PFS Polarstern, 5:155 PGEs see Platinum group elements (PGEs) pH deep-sea-floor microelectrode results, 4:489, 4:490F effect of carbon, 1:495–496, 1:496F effects on dissolved inorganic carbon, 1:613 electron affinity and, 1:541 fluorescent sensing, 2:594, 2:594T gradient in sediments, 4:490 impacts on phytoplankton, 4:460, 4:461F impacts on zooplankton, 4:460 influence on fish distribution, 2:372 optical sensors, 1:13 of sea water, coral-based paleoclimate research, 4:339T, 4:341 Phaeocystis, CPR survey data, 1:638, 1:638F Phaeophyta (brown seaweeds), 4:427 Phaethon rubicauda, 4:372F Phaethontidae (tropic birds), 4:370, 4:371 characteristics, 4:371, 4:376T distribution, 4:371 ecology and behavior, 4:371, 4:376T migration, 5:242–244 species, 4:371, 4:372F see also Pelecaniformes; specific species Phages see Bacteriophage
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Phalacrocoracidae, 4:370, 4:373–374 breeding patterns, 4:374, 4:374F characteristics, 4:373–374, 4:376T feeding patterns, 4:376T Leucocarboninae sub-family see Shag(s) migration, 5:242–244 Phalacrororacinae sub-family see Cormorants species, 4:372F, 4:373–374 see also Pelecaniformes; specific species Phalacrocorax atriceps (imperial shag), 4:372F Phalacrocorax carbo (great cormorant), 4:372F, 4:374, 4:374F see also Cormorants Phalacrororacinae see Cormorants Phalaropes, 4:393–400 conservation, 4:399 definition, 4:393 diversity of names, 4:398, 4:399T females vs. males, 4:393, 4:393–394, 4:394F, 4:397 on land, 4:397 appearance, 4:394F, 4:397 breeding behavior, 4:397 male–female role reversal, 4:393, 4:397 diet, 4:398 distribution, 4:397 migration and movement patterns, 4:398, 5:244 population status, 4:393, 4:399 declines, 4:399 at sea, 4:393–394 appearance, 4:393–394, 4:394F aquatic adaptations, 4:394–395 lobed toes, 4:394, 4:394F diet, 4:395 distribution, 4:395 feeding behavior/mechanics, 4:395–396 spinning, 4:395 surface tension feeding, 4:395, 4:396F habitat, 4:396–397 systematics, 4:398–399, 4:399T threats, 4:399 see also Seabird(s); specific species Phalaropus fulicaria see Red phalarope Phalaropus lobatus see Red-necked phalarope Phalaropus tricolor see Wilson’s phalarope Phanerozoic benthic ecosystems, 1:399 rocks, phosphorite deposits, 1:263–264 strontium isotope ratio variation, 3:458–461, 3:460F Phase partitioning, noble gases, 4:56T Phase-resolvent wind models, 6:308 Phenology defined, 4:456–457 effect of global warming, 4:456–457 Phenol red, 1:13
570
Index
Philippines El Nin˜o events and, 2:228 marine protected areas, 1:653, 1:654 Phillipsite, 1:265–266 diagenetic reactions, 1:266T PHILLS (Portable Hyper-spectral Imager for Low-Light Spectroscopy), 1:144 Phoca groenlandica (harp seal) migration and movement patterns, 3:602–603, 3:602F see also Phocidae (earless/‘true’ seals) Phoca vitulina see Harbor seals (Phoca vitulina) Phocidae (earless/‘true’ seals), 3:590, 3:605, 3:609T, 5:286T abundance, 5:286T trends, 5:286T body outline and skeleton, 3:610F conservation status, 3:609T, 5:286T distribution, 5:285, 5:286T lungs, 3:586F species, 3:609T, 5:286T subfamily Monachinae see Monachinae (southern phocids) subfamily Phocinae see Phocinae (northern phocids) trophic level, 3:623F see also Pinnipeds; specific species Phocinae (northern phocids), 3:609T, 5:286T see also Phocidae (earless/‘true’ seals); specific species Phocoena dioptrica (spectacled porpoise), 2:154, 2:159 Phocoena phocoena (harbor porpoise), 2:159 hunting, 3:635, 3:636F see also Porpoises Phocoena sinus (vaquita), 2:154F, 2:159 Phocoenidae see Porpoises Phocoenoides dalli (Dall’s porpoise), 2:154, 2:158, 2:159 Phoebastria irrorata (waved albatross), 5:239–240, 5:240 see also Albatrosses Phoebetria palpebrata (light-mantled sooty albatross), 4:596 see also Albatrosses Phoenician ships, discovery, 3:699 Phosphate (PO43-) atmospheric input, 1:123–124 benthic flux, 4:488F concentration depth profiles, 6:77F in upwelling zones, 6:227 vs. zinc and cobalt, 6:82F profile Atlantic Ocean, WOCE section 16, 3:301F Black Sea, 1:216F, 1:405F proxy tracers, 3:455–456 see also Cadmium/calcium ratio in sea water nitrate vs., 3:332, 3:332F, 4:681–682, 4:682–684, 4:683F, 4:686F
subsurface, cadmium/calcium ratio as tracer, 5:333, 5:337, 5:337F vertical profile, 4:682F see also Phosphorus; Phosphorus cycle Phosphate oxygen isotopes (d18O–PO4), in marine phosphorus research, 4:407–409, 4:412 Phosphorescence, 1:376 see also Fluorescence Phosphorite, 3:890 Phosphorite deposits, 1:262–264 composition, 1:263 formation, 1:263 insular, 1:264 Phanerozoic rocks, 1:263–264 Phosphorus (P) accumulation in sediments through Cenozoic, 1:518–519, 1:519F biological role, 4:401 C:n:p ratios, 4:587 coastal fluxes, 3:399F cosmogenic isotopes, 1:679T biodynamic tracer applications, 1:684, 1:685 reservoir concentrations, 1:681T cycle see Phosphorus cycle dissolved inorganic see Dissolved inorganic phosphorus (DIP) eutrophication, 2:308 cause of, 4:459–460 conversion processes, 2:310F Sweden’s reduction policy, 2:320–323 fertilizers, application levels, 3:398F isotopes (32P and 33P) as tracers of phosphorus cycling in surface waters, 4:409–410, 4:411T, 4:412 see also Phosphorus-32; Phosphorus33 limitation nitrogen vs., 3:332, 3:332F, 4:407–408 research, 4:408F, 4:409–410, 4:409T limiting factor to photosynthesis, 4:19, 4:586, 4:588 oceanic residence time, research, 4:410–411, 4:412, 4:412T role in harmful algal blooms, 4:441–442 salt marshes and mud flats, 5:46 sediments see Sediment(s) solid-phase, estuarine depth profile, 1:548F subterranean estuaries, 3:96 see also specific forms of phosphorus Phosphorus-32 cosmogenic oceanic sources, 1:680T production rate, 1:680T as tracers of phosphorus cycling in surface waters, 4:409–410, 4:411T, 4:412 Phosphorus-33 cosmogenic, production rate, 1:680T as tracers of phosphorus cycling in surface waters, 4:409–410, 4:411T, 4:412
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Phosphorus cycle, 4:90F, 4:401–413, 4:402F, 4:684, 4:684F carbon cycle and, 4:411 human impacts, 4:406 marine, 4:402F, 4:406–407 marine, research, 4:401, 4:407, 4:412 cosmogenic 32P and 33P as tracers, 4:409–410, 4:411T, 4:412 links to other biogeochemical cycles, 4:411–412, 4:412 long time-scale cycling, 4:409–410 oceanic residence time of phosphorus, 4:410–411, 4:412, 4:412T phosphate oxygen isotopes in, 4:407–409, 4:412 reevaluation of phosphorus role as limiting nutrient, 4:408F, 4:409–410, 4:409T reservoirs, 4:403T associated residence times, 4:403T fluxes between, 4:404T, 4:406–407, 4:412T sizes, 4:403T terrestrial, 4:401–403, 4:402F, 4:403T, 4:406F chemical weathering in, 4:401, 4:402F transport of phosphorus from continents to ocean, 4:403–406, 4:404T riverine, 4:403–406 see also Carbon cycle; Nitrogen cycle; Redfield ratio Photoadaptation, mechanism for deep chlorophyll maximum, 5:477–478 Photoautotrophs see Microphytobenthos Photochemical efficiency, 2:583–584 Photochemistry consumption low molecular weight organic compounds, 4:416–417 trace gases, 4:416–417 oxidation, of trace gases see see specific gases photochemical fluxes, global estimation, 4:420–423 processes, 4:414–424 abiotic constituents, optical properties, 4:414 calculations, 4:420 CDOM see Colored dissolved organic matter (CDOM) microbial activity, 4:418 PDM see Particulate detrital matter (POM) see also Microbial loops; Network analysis of food webs production low molecular weight organic compounds, 4:416–417 reactive oxygen species, 4:414–416 trace gases, 4:416–417 trace metal, 4:417–420 see also specific gases/metals/processes Photodetector, absorptiometric chemical sensor, 1:9–10
Index Photographic systems particle imaging, 4:250 zooplankton sampling, 6:364 Photolithotrophs, 4:585 Photolithotrophy, 4:585 Photolysis, colored dissolved organic matter, effects of, 4:417–418 Photolytic dissociation, loss of water from Earth’s surface, 4:262, 4:264 Photons colored dissolved organic matter, 4:417 flux density, 4:588 Photo-oxidation, 4:416–417 Photophores, 1:379–380 effects of accessory optical structures, 1:379F effects of pigment and reflectors on light emission, 1:378F fishes, 1:380–381 occlusion, 1:380, 1:380F shrimps and krill, 1:380 squids, 1:380 Photoprotective pigments, 2:582 Photosynthesis, 3:159, 4:414, 4:680 algae, 4:425 carbon flux and, 6:95 corals, 4:338–339, 4:340–341 cyanobacteria, 4:425 effect on atmospheric carbon dioxide/ oxygen ratio, 4:91–92 equation, 1:481–483 hydrothermal vent ecology, 3:151, 3:152F importance of spatial separation from remineralization, 4:680 measuring, 4:578–579 microphytobenthos see Microphytobenthos phytoplankton see Phytoplankton restriction to upper waters of ocean, 4:680 terrestrial vs. marine, 4:678, 4:678T see also Network analysis of food webs; Primary production; Primary production distribution; Primary production measurement methods; Primary production processes Photosynthetically available radiation (PAR), 1:391, 3:246–247, 4:621 sensor, 3:247, 3:249F Photosynthetic electron transfer (PET), 2:584 Photosynthetic unit size, photosystem II, 2:584–585 Photosystem I, definition, 6:85 Photosystem II definition, 6:85 photosynthetic unit size, 2:584–585 physiological measurement conditions, 2:584 Phoxinus spp. (minnows), 2:436–437 Phragmites australis (common reed), 5:46–47 Phycobiliproteins, 3:569–570 autofluorescence, 4:245 Phycocyanin, 2:582F, 2:583–584
Phyllosilicate, 1:268 Phylogenetics, 4:561 Phylogeography, 4:561 Physalia physalis (Portuguese man-ofwar), 3:12 Physeteridae, 3:606–607T Physeter macrocephalus see Sperm whales (Physeteriidae and Kogiidae) see also Odontocetes (toothed whales) Physeter macrocephalus (sperm whale), 3:643, 3:648F Physical–biological–chemical interactions, plankton patchiness, 5:474, 5:481 Physical gradients, seabird abundance and, 5:227–228 Physical oceanography of the eastern Mediterranean, 1:744 Physical processes, domains within hierarchy of coupled models, 4:722, 4:722T Physiologically structured population models see Structured population models Physoclists, 1:63 Physonectae siphonophores, 3:12, 3:13F Physostomes, 1:63 Phytobenthos, 4:425–431 ‘algae’ defined, 4:425 cyanobacteria, 4:425 definitions, 4:425 descriptions, 4:425 diversity of algae see Algae, diversity (phytobenthos) ensuring commercial supplies, 4:430–431 biotic considerations, 4:431 manipulation of stocks, 4:431 sustainable harvesting, 4:430–431 value-dependent approaches, 4:430 human uses, 4:429–430 alginate, 4:430 fertilizers, 4:430 high value chemicals, 4:430 human consumption, 4:430 principle uses, 4:430 primary production, 4:425 seaweed ecology, 4:428–429 see also Seaweed ecology seaweed life cycles, 4:427–428 see also Seaweed(s), life cycles validity of laboratory cultures, 4:428 Asparagopsis armata and Falkenbergia rufulanosa, 4:428 Monostroma spp., 4:428 possibility of false results, 4:428 see also Algae; Primary production distribution; Primary production measurement methods; Primary production processes Phytodetrital layer, 2:548 features, 2:549–550, 2:552F material, autofluorescence photomicrographs, 2:549–550, 2:552F North-eastern Atlantic see Northeastern Atlantic
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regional variations, 2:548–549 temporal variations, 2:549 Phytoplankton, 4:453–454, 6:231 absorption spectra, 4:415F analytical flow cytometry, 4:245–246, 4:245T, 4:246F arsenic detoxification, 3:780–781 bacterioplankton comparison, 1:272–273 biomass Mid-Atlantic Bight, 4:727, 4:728F shelf sea fronts, 5:396 blooms see Phytoplankton blooms carbon fixation, 4:89–90 cellular composition, relative uniformity of, 4:678–679 cell wall variety, 4:679–680 chemical reaction for formation of, 4:679 CO2 sequestration, 4:445 Coastal Transition Zone (California), simulations, food web and biooptical model, 5:481–485, 5:485F color, 1:632–633, 1:635–636, 1:636F North Sea, 1:635–636, 1:636F see also Continuous Plankton Recorder survey competition see Phytoplankton competition Continuous Plankton Recorder survey, 1:633–634, 1:635F definition, 4:337 distribution, coastal upwellings affecting, 5:481, 5:484F ecology, turbulence and see Plankton and small-scale physical processes effect of iron enrichment see Iron fertilization elemental compositions see Redfield ratio fixed nitrogen assimilation, 4:44–45 fluorescence imaging, 2:585F fossil turbulence, effects of, 2:619 functional groups for modeling, 4:100 growth reactions, 4:579 harmful algal blooms (red tides), 4:455 high-nitrate, high-chlorophyll (HNHC) regimes, 3:332–333, 3:332T high-nitrate, low-chlorophyll regimes see High-nitrate, low-chlorophyll (HNLC) regions laboratory grown, 2:586 low-nitrate, high-chlorophyll (LNHC) regimes, 3:332–333, 3:332T, 3:333F low-nitrate, low-chlorophyll (LNLC) regimes, 3:332–333, 3:332T maximum biomass, vs deep chlorophyll maximum, 5:477–478 microphytoplankton, 4:448–449 nanophytoplankton, 4:448–449 nitrate assimilation, 4:46 nitrate uptake, 4:48F nitrogen, chlorophyll prediction, 5:478 nitrogen cycle and, 4:33T see also Nitrogen cycle
572
Index
Phytoplankton (continued) in NP models, 4:98 nutrient(s) macro-, 4:678 micro-, 4:678 requirements, 3:331–332, 4:677–678 see also Nutrient(s); Photosynthesis in nutrient-impoverished surface waters, recycled nutrients, 5:477F, 5:478–479 oceanic, trace elements and, 6:76 as optical constituents of sea water, 4:624 patchiness, 4:348, 4:350F sensors for observing, 4:353T see also Patch dynamics penetrating shortwave radiation, 4:379 Peru-Chile Current System, 4:389 photosynthesis, 4:445, 4:455 determination by pump and probe fluorometry, 1:141 importance to marine life, 4:455 picophytoplankton, 4:448–449 primary production, 4:578 Prochlorococcus, 4:449–450 production limitations, 6:75–76 size in upwelling ecosystems, 6:228 size structure see Phytoplankton size structure spatial variability, small-scale patchiness models and, 5:477, 5:477F species, 2:140 spectral absorption, 3:245 temperature-dependent growth in MidAtlantic Bight, 4:727, 4:728F trace element nutrients, 6:75, 6:75F uptake, 6:80–82, 6:81–82 see also Biomass; Coccolithophores; Diatom(s); Plankton and small-scale physical processes; Primary production distribution; Primary production processes Phytoplankton blooms, 3:556, 3:660, 3:804, 4:432–444, 4:576F caused by habitat changes, 3:103 control by copepods, 1:650 diatoms, 6:229 dinoflagellates, 5:492–493 ecology and population dynamics, 4:437–439 global warming, 4:459–460 grazing interactions, 4:441–443 grazers’ abilities, 4:439–440 grazing mechanisms, 4:440, 4:441F toxins’ role, 4:439–440 toxin vectoring, 4:440–441 harmful effects, 4:434T human causes, 4:441, 4:443 aquaculture, 4:443F pollution, 4:443F wastewater treatment plants, 4:443, 4:443F impacts, 4:432, 4:432–433, 4:433F influence of viruses, 4:470 life histories, 4:439–441 cyst dispersal, 4:439
cyst stages, 4:439 life cycle, 4:439, 4:440F mammalian responses, 2:218–219 management issues, 4:444 options, 4:443–444 mechanisms, 4:439 complex communities, 4:437 horizontal transport, 4:437–438, 4:438F hydrographic effects, 4:438–439, 4:439F influencing factors, 4:437 vertical transport, 4:437, 4:438F water stratification, 4:437 natural causes, 4:441 nomenclature, 4:432 nontoxic blooms, 4:436–437 Chaetoceros spp. diatoms, 4:434–436 light reduction, 4:434 macroalgae, 4:433F, 4:434 oxygen depletion, 4:433–434 nutrient enrichment, 4:441 nutrient-ratio hypothesis, 4:441–442 ocean gyre systems, 4:133 particle aggregation, 4:334F, 4:336 planktonic foraminifera, 4:609–610 research and management, 4:444 salmonid farming, 5:26 toxic algae, 4:433–436 accumulation in shellfish, 4:432 see also Molluskan fisheries direct toxic transfer, 4:432 human illnesses, 4:435T nonhuman deaths, 4:432–433, 4:435F toxin release, 4:432 toxins, 4:437–439 actions, 4:436, 4:436T binding/dissociation, 4:436 fish deaths, 4:436–437 human exposure, 4:436 metabolic role, 4:437 potency, 4:436 release, 4:432 trends, 4:443–444 expanding problem, 4:441, 4:442F improved detection, 4:441, 4:443 trophic cascade, 2:510 see also Algal blooms; Nutrient cycling; Primary production Phytoplankton competition N–P–Z model, 4:722, 4:725, 4:731 regional model, 4:722, 4:723–724, 4:724F Phytoplankton cycle productivity, passive sensors used by aircraft for remote sensing, 1:142, 1:143F Phytoplankton size structure, 4:445–452 controlling factors, 4:450 factors favoring large-celled organisms, 4:450 ecological/biogeochemical implications, 4:450–451, 4:451T CO2 sequestration, 4:450–451 ecosystem differences, 4:451 food web interactions, 4:450–451
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patterns, 4:448–449 size-abundance spectra, 4:449–450 ecosystem differences, 4:449–450, 4:450F size-fractionated chlorophyll a, 4:448–449, 4:449F range of cell sizes, 4:445 size, metabolism and growth, 4:445–447 size and growth rates, 4:448 influence of nutrients, 4:448 variable values, 4:448 size and loss processes, 4:447–448 large size, advantages/disadvantages, 4:448 respiration and exudation, 4:447 sinking velocity, 4:448 size and resource acquisition, 4:445–447 deviation from general allometric theory, 4:447 light absorption, 4:446 metabolic rates, 4:445–446 nutrient limitation, 4:445–446 nutrient uptake, 4:445, 4:446F optical absorption cross-section, 4:446 package effect, 4:446–447, 4:446F photosynthesis, 4:447, 4:447F Piccard, Jacques, 6:255 PICES see North Pacific Marine Science Organization (PICES) P&I (Protection and Insurance) clubs, 5:407 Picoeukaryotes, 3:558–559 Picoplankton, 3:805 Pielou’s evenness index, 4:534 Pigments accessory, 2:582 see also Visual pigments Pike (Esox spp.), 2:395–396F Pilchard (Sardina pilchardus), 2:375 Pilchard fisheries by-catch issues, 2:202 multispecies dynamics, 2:508 Pill bug (Tylos granulatus), 5:53F, 5:56F sheltering behavior Japan, 5:56 Mediterranean and South Africa, 5:56 Pillow lava, 3:815–816, 3:816F, 3:817, 3:819F elongate pillows, 3:865F Pilot whales (Globicephala spp.), 2:149, 2:158–159, 2:159 Pine Island Glacier, 5:548 Pinguinis impennis see Great auk (Pinguinis impennis) Pinguinus, 1:171T see also Alcidae (auks) Pink salmon (Oncorhynchus gorbuscha), 5:32, 5:33, 5:33F population time series, 4:703F Pinnipeds (seals), 3:605, 3:609T, 5:285–291 abundance, 5:285, 5:286T trends, 5:285, 5:286T
Index adaptations to aquatic life, 5:285–288 morphological, 5:285–288 physiological, 3:584, 5:288 annual feeding and reproductive cycle, 3:600, 3:611 conservation status, 3:609T, 5:286T constraints of aquatic life, 5:288–289 maternal body size, 5:288 diet, 5:289–290 fish, 5:289–290 krill, 5:290 seabirds, 5:290 distribution, 5:285, 5:286T diving, 5:288 cardiovascular adaptations, 3:584 for food, 3:615, 5:290 evolution, 3:590–591 exploitation see Sealing hearing, 1:360, 1:360F importance of krill, 3:355 lactation, 5:288 mating systems, 5:289 competitive, 5:289 postpartum estrus, 5:289 sexual dimorphism, 5:289 terrestrial, 5:289 migration and movement patterns, 3:599–600 breeding season, 3:600, 3:601F haul-out sites, 3:600–603, 3:601F, 3:603 nonbreeding season, 3:600, 3:602F phylogeny, 3:590, 5:285, 5:285F Southern Ocean populations, harvesting impact, 2:205–206, 5:513 taxonomy, 1:276–278, 3:590, 5:285, 5:286T family Odobenidae see Odobenidae (walruses) family Otariidae see Otariidae (eared seals) family Phocidae see Phocidae (earless/ ‘true’ seals) thermoregulation constraints, 5:288 newborn pups, 5:288, 5:288–289, 5:289 threats, 5:285 trophic level, 3:622, 3:623F see also Marine mammals; specific species Pintado petrel, 4:591F see also Procellariiformes (petrels) Pipefishes (Syngnathidae), 2:395–396F Pisaster ochraceus (ochre sea star), 4:763–764 Pisces IV, 6:257T Pisces V, 6:257T Piston corers advanced see Advanced piston corer historical use in paleoceanography, 4:296 Piston velocity, 1:489, 4:222–223 whitecaps, 6:332 Pitch attitude, gliders, 3:62–63 and speed, 3:63
Pitot tubes momentum flux measurements, 6:152 shear stress measurements, 5:385 Plaice (Pleuronectes platessa) larval stages and metamorphosis, 2:430F life history, 2:430F migration, 2:406–407, 2:408F, 2:409F Plaice fisheries, marine protected areas, 3:674 Plainfin midshipman (Porichthys notatus), 2:448F, 2:450F Planar clast fabric, definition, 5:464 Planck’s constant, 5:91 Planck’s equation, 5:91 Planck’s function, linearized, 5:92 Planetary boundary layer, 3:198, 3:198–199 under sea ice see Under-ice boundary layer Planetary boundary layer model, forward numerical models, 2:609 Planetary degassing, origin of oceans, 4:261 Planetary vorticity, wind driven circulation, 6:351 Planetary waves see Rossby waves Planktobenthos sampling nets, 6:359–361, 6:362F Plankton, 2:217, 4:453–454 abundance and productivity, 4:453–454 acoustic scattering, 1:107 anisotropic, vertical structure in smallscale patchiness models, 5:477–478 assemblages and communities, 4:454 factors limiting distribution, 4:454 transition zones, 4:454 behavior, affecting small-scale patchiness, 5:485–486 biogeography, Continuous Plankton Recorder survey, 1:633 bioluminescence, 1:376–380 ‘bottom up’-controlled food web, 4:459 carbon isotype profile, Arabian Sea, 3:916F climate and see Plankton and climate communities see Plankton communities competition, regional models, 4:722 concentration levels, 5:489 cooling waters, effects of, 6:12–13 definition, 4:453 dense aggregations see Plankton, swarms distribution, submesoscale upwellings/ downwellings effect, 5:481, 5:482F diurnal vertical migration, 4:453 ecosystem see Planktonic ecosystem factors limiting growth and production, 5:489 feeders, coral reef aquaria, 3:530T foraminifera see Planktonic foraminifera fossilised, 3:911 growth/feeding, application of coastal circulation models, 1:576–577, 1:576F, 1:577F holoplanktonic vs. meroplanktonic species, 4:453
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Hutchinson’s ‘paradox of plankton’, 4:470 krill see Krill (Euphausiacea) N-P-Z (nutrient–phytoplankton– zooplankton) models, 4:722 nutrient cycling, 4:453–454 oxygen isotype profile, Arabian Sea, 3:915F patchiness see Plankton patchiness phytoplankton, 4:453–454 see also Phytoplankton population dynamic models see Population dynamic models populations, hydrodynamics, application of coastal circulation models, 1:576–577, 1:576F, 1:577F production conservative element concentrations in sea water and, 1:626–627 stoichiometry, 1:626–627 recording see Continuous Plankton Recorder (CPR) survey regime changes and, environmental drivers, 4:700 roles in marine environment, 4:453 size, 4:453 small-scale physical processes see Plankton and small-scale physical processes subdivisions, 4:453 swarms behavior affecting small-scale patchiness, 5:485 see also Phytoplankton blooms trace element concentrations and, 6:84–85 uneven distributions, 4:454 vertical structure, 5:477–479 viruses see Plankton viruses zooplankton, 4:454 see also Gelatinous zooplankton; Zooplankton see also Bacterioplankton; Copepod(s); Demersal fish(es); Fish larvae; Primary production processes; specific types of plankton Plankton and climate, 4:455–464, 4:607, 4:611 beacons of climate change, 4:455–456 carbon cycle, 4:455 changes in abundance, 4:458–460 effects on fisheries, 4:459 changes in distribution, 4:456 responses to global warming, 4:456 changes in phenology, 4:456–458 effects on food web, 4:457–458 climate variability, 4:461–462 consequences for the future, 4:462–464 nutrient–phytoplankton–zooplankton (NPZ) models, 4:463, 4:463F plankton as models, 4:462–463 results, 4:463–464 global importance of plankton, 4:455 impact of acidification, 4:460–461 aragonite and calcite structures, 4:460
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Plankton and climate (continued) effects on calcification, 4:460 impacts of climate change, 4:456 reflection of solar radiation, 4:455 see also Upwelling ecosystems Plankton collectors, towed vehicles, 6:72 Plankton communities, 3:656–663 characteristics, 3:659T current research methodologies, 3:662 definition of ‘community’, 3:656 effects of microbial loops, 3:662 future research methodologies, 3:662 general features, 3:656–658 continuous operation/functioning, 3:656 microbial loop, 3:656 nutrient recycling, 3:656 place in water column, 3:656 quantitative assessments, 3:657–658 size groupings, 3:656 sizes and relationships, 3:656–657, 3:657F sun energy, 3:656 specific communities, 3:658–660 continental shelves, 3:660, 3:660–661 environmental characteristics, 3:660 episodic nature of nutrient availability, 3:660 interactions across thermoinclines, 3:660 short-lived plankton communities, 3:661 estuaries, 3:658–660 copepod species, 3:658 environmental characteristics, 3:658 open ocean, 3:661–662 gyres, 3:661 regional and seasonal variation, 3:661 subpolar gyres, 3:661 subtropical gyres, 3:661–662 temperate gyres, 3:661 types of environments, 3:658 Plankton feeders, coral reef aquaria, 3:530T Planktonic ecosystem model, four-compartment model (nitrogen flow), 5:478, 5:478F motile organisms, 4:212 Ocean Station Papa, 4:213–214, 4:215F one-dimensional models, 4:210–212 general conservation/transportation equation, 4:211 mass conservation equation, 4:211 Planktonic foraminifera, 4:606–612 applications of research, 4:611 climate change studies, 4:611 cellular structure, 4:607–608, 4:607F chamber formation, 4:607 cytoplasm and organelles, 4:607, 4:608F interaction with surrounding water, 4:607–608
inter-chamber connections, 4:607–608 spines, 4:607–608, 4:609F description and distribution, 4:606 ecology and distribution, 4:609–610 biomass distributions, 4:609–610 depth habitat, 4:609 faunal provinces, 4:609, 4:610F north Atlantic distribution, 4:610F evolutionary history, 4:606 general life history, 4:606 molecular biology research, 4:608–609 diversity studies, 4:608–609 d18O records, 1:505–506, 1:506–507, 1:509 benthic foraminifers vs., 1:507, 1:507F, 1:508F long-term patterns, 1:507F, 1:508–509, 1:508F as productivity proxies, 5:338 reproduction and ontogeny, 4:608 life cycle, 4:608 reproductive method, 4:608 research history, 4:606 uses in other studies, 4:606 research methods, 4:606–607 molecular biology, 4:607 reconstruction information from shells, 4:607 reconstruction studies, 4:607 sampling and observation, 4:606–607 sedimentation of calcite, 4:610–611 global calcite production, 4:610–611 preservation/remineralization of shells, 4:610–611 seasonality, 4:611F see also Calcium carbonate (CaCO3) sediment traps, lunar cyclicity, 6:4 symbionts, commensals and parasites, 4:608, 4:609F spinose vs. nonspinose species, 4:608 trophic demands, 4:609 food and feeding, 4:609 Plankton patchiness coastal upwelling and, 5:481 coupling models with sparse data, 5:474, 5:474–476 dynamics, 5:474 influence of internal weather of sea processes, 5:481 mesoscale eddies and, 5:481, 5:483F physical–biological–chemical interactions, 5:474, 5:481 phytoplankton vs. zooplankton, 4:348 scales, 5:474, 5:475F spectral modeling/analysis, 5:477, 5:477F study of see Patch dynamics Plankton and small-scale physical processes, 5:488–493 goals of plankton, 5:488 life in plankton, 5:488 research, 5:493 difficulties, 5:488 past assumptions, 5:488
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turbulence and phytoplankton ecology, 5:492–493 avoidance of sinking, 5:492 bioluminescence, 5:492 turbulence and predator–prey interactions, 5:489–491 contact rate, 5:489–490 different prey search methods, 5:490–491 field studies, 5:491, 5:491F gut fullness of predatory fish, 5:491F inhibition of dinoflagellate cell division, 5:492–493 laboratory experiments challenge, 5:490 limitations, 5:490 results, 5:490 locating a mate, 5:491–492 responses of visual predators, 5:491F search for prey by other methods, 5:490 by vision, 5:489–490 turbulence and reproductive ecology, 5:491–492 turbulence effects, 5:489 types of turbulence, 5:489 viscosity effects, 5:488–489 viscous vs. inertial forces, 5:488 Plankton viruses, 4:465–472 benefits of infection increase in production, 4:471 nutritional gains, 4:471 resistance to superinfection, 4:471 comparison to mortality from protists, 4:468–469 effects on host species, 4:470 control of algal blooms, 4:470 species composition, 4:470 vulnerability of dominant hosts, 4:470 food web and geochemical cycles, 4:469–470 enabling host to produce toxins, 4:469–470 prokaryote-viral loop, 4:469, 4:470F release of cell contents, 4:469 relevant features of viruses, 4:469 viral lysis, 4:469 general properties, 4:465–466 genetic transfer, 4:471 mechanisms, 4:471 history of knowledge, 4:465 host resistance, 4:470–471 laboratory vs. field systems, 4:470–471 importance to planktonic communities, 4:472 observation, 4:466–467 electron microscopy, 4:466–467 epifluorescence microscopy, 4:466–467, 4:467F preparation methods, 4:466–467 types of viruses, 4:467 bacteriophages, 4:467 molecular techniques, 4:467 viruses of cyanobacteria, 4:467
Index viral activities, 4:467–468 lysogeny and chronic infection, 4:468 lytic infection, 4:468 viral roles in system functions, 4:465 virus abundance, 4:467 environmental variations, 4:467 virus:prokaryote ratios, 4:467, 4:468F Plants aquatic, productivity measures, 2:584–586 particulate production, 1:248 upper temperature limits, 6:12T vascular see Vascular plants see also Vegetation Plastic(s) discarded, seabirds and, 5:270, 5:276F, 5:277 see also Pollution solids Plastic flow, 5:455 Plasticity, sea ice, 5:163–164 Plastic yield curves, sea ice, 5:164F Plastocyanin, 6:83 Platanista spp. (susus), 2:156, 2:157, 2:158, 2:159 Platanistidae, 3:606–607T see also Odontocetes (toothed whales) Plate boundaries, accretionary prisms see Accretionary prisms Plate boundary geometry, propagating rifts and microplates, 4:601, 4:602F, 4:604, 4:604F triple junctions, 4:601–602 Plate boundary transforms aseismic motions, 3:840 seismicity, 3:839–841, 3:839F location, 3:840 Plate heat flow models, 3:44–45 GDH1, 3:45 hot spots and, 3:46–47 PSM, 3:45 Platelet ice, 5:173 Plate subduction, crust formation and, 2:49 Plate tectonics, 3:839–840 deep manned submersibles for study, 3:123, 3:511 history of study, 3:123 long-term sea level change and, 5:187, 5:188F, 5:189 process overview, 3:867 sequence formation and, 4:144–145 tsunamis and, 6:129–131, 6:130F Vine and Matthews hypothesis, 3:123 see also Tectonics Platichthyes americanus see Flounders (Platichthyes americanus) Platinum (Pt), 4:494 anthropogenic release into environment, 4:502, 4:502F commercial demand/utilization, 4:502, 4:502F concentrations deep earth, 4:494T sea water, 4:494T, 4:497 vertical profiles in sea water, 4:497, 4:500F
Platinum group elements (PGEs), 4:494–503 anthropogenic release into marine environment, 4:502–503, 4:502F commercial demand, 4:502, 4:502F low concentrations in sea water, 4:494–495, 4:494T, 4:503 deep earth vs., 4:494–495, 4:494T, 4:495F osmium see Osmium (Os) palladium see Palladium (Pd) research, 4:497–499 tracing of extraterrestrial material in marine sediments, 4:499–502, 4:501F rhodium see Rhodium ruthenium see Ruthenium solubility, 4:495, 4:495F water column data, 4:495–496, 4:503 Platinum resistance thermometer, 1:709–710 Platyctenida ctenophores, 3:12 Plecoglossus altivelis (Japanese ayu), 2:404 Pleistocene glacial cycles, 4:507 ice shelves, 3:211 oxygen isotope variations, 1:505–506, 1:507F see also Cenozoic Pleuronectes platessa (plaice), 2:406–407, 2:408F, 2:409F Pleuronectiformes (flatfish), 2:395–396F Pliny the Elder, 5:410 Pliocene glacial cycles, 4:507 d18O records, 1:507F, 1:510F, 1:511 see also Cenozoic Plio-Pleistocene Ice Ages, paleoceanographic research, 4:300–301 Plough shells (Bullia spp.), 5:52F, 5:55, 5:56 Plume convection Red Sea circulation, 4:672–673 see also Ocean convection plumes Plumes see Hydrothermal plumes; Mantle plumes; Megaplumes; Ocean convection plumes Plunging breakers, 1:431, 6:312 Plutonium atomic weapons and, 5:327 isotopes, nuclear fuel reprocessing, 4:84T sediment profile, 5:330, 5:331F PML (polar mixed layer), 1:211, 1:212–213, 1:215T PMMA (poly(methyl methacrylate)), 1:8 PN see Particulate nitrogen (PN) PNM (primary NO2, maximum), 4:37–38, 4:38F POEM (physical oceanography of the eastern Mediterranean), 1:744 Pogo measurements, 3:40–42 spacing, 3:42–43
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Poincare´ waves, 2:276F equatorially trapped, 2:275 solution, 2:275–276 tides, 6:37 wave dynamics, 2:275 Poisson process, 3:193–194 Poland, water, microbiological quality, 6:272T Polar Basin, sea ice trends, 5:175 Polar bear (Ursus maritimus) annual feeding and reproductive cycle, 3:611 body outline and skeleton, 3:610F exploitation, 3:635, 3:640, 3:642 history of, 3:640 shearing teeth, 3:616F trophic level, 3:622, 3:623F see also Marine mammals Polar biome, 4:359, 4:361T boundary, 4:359 zooplankton community composition, 4:357T Polar ecosystems, 4:514–518 Arctic food web see Polar marine food webs challenges to organisms, 4:514 continental margin area, 4:258T continental margins, primary production, 4:259T copepod habitat, 1:645 distinguishing characteristics, 4:514 food webs see Polar marine food webs radiation seasonality, 4:514, 4:514F similarities and differences, 4:514 Southern Ocean food web see Polar marine food webs water temperatures, 4:514 see also Arctic Basin; Southern Ocean, current systems Polar esterlies, 2:225–226 Polar Experiment (POLEX), 1:92–93 Polar Front, 1:179F biogenic silica burial, 3:681–682 transport, 1:184 water properties, 1:180F Polar Frontal Zone, 1:181–182 Polar glaciation, paleoceanographic research, 4:300 Polarity, geomagnetic see Geomagnetic field; Geomagnetic polarity timescale (GPTS) Polarization, electric see Electrical properties of sea water Polar lows, satellite remote sensing application, 5:106F, 5:107–108 Polar marine food webs, 4:514–516, 4:516F Arctic food web, 4:518 description, 4:518 low-diversity benthos, 4:518 paucity of knowledge, 4:518 basic food webs, 4:514–515, 4:515F benthos, 4:517 importance, 4:517 organisms in polar benthos, 4:517 extra features of polar webs, 4:515
576
Index
Polar marine food webs (continued) human effects, 4:517–518 disturbance, 4:517 overfishing and overhunting, 4:517 unknown pristine condition, 4:517–518 see also Southern Ocean fisheries midwater, 4:516–517 characteristic organisms, 4:516–517 similarity to lower latitude regions, 4:516 primary production and microbial loops, 4:516 importance of diatoms, 4:516 see also Microbial loops; Primary production distribution; Primary production measurement methods; Primary production processes sea ice, 4:515–516 ice-associated primary production, 4:515 melting zone primary production, 4:515 microbial habitat, 4:515 primary production regulation, 4:515 reduction of turbulence, 4:515 seasonality, 4:517 limited primary production, 4:517 migration of top predators, 4:517 short linear food chains, 4:516 diatoms-krill-whales example, 4:516 nonlinear system, 4:516 see also Krill (Euphausiacea) Southern Ocean food web, 4:518 common organisms, 4:518 description, 4:518 top predators, 4:517 animals included, 4:517 prey, 4:517 see also Baleen whales (Mysticeti); Beaked whales (Ziphiidae); Seabird foraging ecology; Sperm whales (Physeteriidae and Kogiidae) vertical flux, 4:516 seasonality, 4:516 Polar mixed layer (PML), 1:211, 1:212–213, 1:215T Polar oceans ocean circulation, 4:123 see also Antarctic Ocean; Arctic Ocean Polar research vessels, 5:416 ice capability, 5:416 limited icebreaking capability, 5:416 special requirements, 5:416 Polar Water, acoustics, 1:94–95 POLDER ocean color sensor, 5:118T Pole and line fishing, 2:541 mechanized, 2:541 pelagic species, 4:235–236, 4:236F, 4:237F Poleward geostrophic transport, 3:444, 3:447 Poleward-propagating waves, coastal trapped waves, 1:596 POLEX (Polar Experiment), 1:92–93 Policy, marine see Marine policy
Poli’s stellate barnacle (Chthamalus stellatus), 4:763 Political issues, fishery management, 2:522, 2:525–526, 2:526 Pollachius pollachius see Pollack (Pollachius pollachius) Pollachius virens (saithe), open ocean demersal fisheries, 4:228 Pollack (Pollachius pollachius), 2:456F swimbladder, 1:66F Pollutants airborne marine, environmental protection and Law of the Sea, 3:440–441 atmospheric input, 1:238–247 estimation of, 1:238 fluorometry, 2:593–594, 2:593T metal see Metal pollution nutrients, 4:441 oil see Oil pollution oyster farming, risk to, 4:283 PCB see Polychlorinated biphenyls (PCBs) persistent organic, environmental protection and Law of the Sea, 3:441 solid see Pollution solids Pollution, 3:103 aquaculture, 3:102 benthic studies, 3:471, 3:473F compensation, International Maritime Organization (IMO), 5:405 control see Pollution control approaches coral reefs, 1:669 dredged material see Pollution solids effects on marine communities, 4:533–539 community data, analysis of, 4:533–535 indicator species, 4:535 global see Global marine pollution impacts on marine biodiversity, 2:146 on marine habitats, 2:146 industrial solids see Pollution solids land-based marine, environmental protection and Law of the Sea, 3:440 marine organisms, 3:572 metal affects in food web, 3:768–769 Mediterranean mariculture problems, 3:535–536 metals see Metal pollution ocean, seabirds as indicators see Seabird(s) oil spill see Oil pollution; Oil slicks; Oil spills salt marshes and mud flats, 5:46 sand/gravel see Pollution solids solids see Pollution solids thermal discharges and, 6:10–17 mixing zones, 6:11–12, 6:11F sources, 6:10 water temperatures, 6:10–11, 6:11F threat to deep-sea fauna, 2:64–65
(c) 2011 Elsevier Inc. All Rights Reserved.
see also Antifouling materials; Global marine pollution; Pollution solids Pollution control approaches, 4:526–532 changes in policy perspectives, 4:528 incorporating all human activity, 4:528 lack of holistic approach, 4:528 public’s distrust of science, 4:528 changes since 1960s, 4:526 changing concept of pollution, 4:526 ‘contaminant’ defined, 4:526 early agreements on prevention, 4:526–527 lists review and update, 4:527 Oslo and London conventions, 1972, 4:526 early approaches to protection, 4:527 environmental impact assessments, 4:530 assessing/controlling activities, 4:530 involvement, 4:530 making predictions, 4:530 monitoring programs, 4:530 testing predictions, 4:530 improving protection, 4:531–532 ‘pollution’ defined, 4:526 precautionary approach, 4:529 predicting chemical effects, 4:530–531 biomarkers, 4:530–531 hormone-disrupting chemicals, 4:530 toxicity tests, 4:530 public perception of threats, 4:531–532 recent protection approaches, 4:528–530 best available technology strategy, 4:528–529 revised precautionary approaches, 4:529 description, 4:529 extreme measures, 4:529 lack of science, 4:529–530 safety and risk, 4:529–530 scientific perspectives, 4:527–528 holistic approach to environmental protection, 4:527 radiological protection system, 4:527–528 uncertainties and risk assessments, 4:531 criticisms of monitoring, 4:531 feedback to management, 4:531 management frameworks, 4:531 risk-assessment process, 4:531 Pollution Prevention and Safety Panel, deep-sea drilling, 2:53 Pollution solids, 4:519–525 dredged material, 4:519, 4:519–520 beneficial uses, 4:521 biological impact assessment, 4:520 characterization, 4:520 disposal, 4:520 global quantities, 4:520 impacts, 4:520–521 navigation, 4:520 regulation, 4:520 regulatory guidelines, 4:520 dredging, 4:519 fine material, 4:519
Index material types, 4:519 see also Dredges/dredging impacts, 4:519 biological consequences, 4:519 contaminated sediments, 4:520–521 contamination amounts, 4:521 dredged material, 4:520–521 impacts and their effects, 4:519 natural vs. human contamination, 4:520 industrial solids, 4:522–523 beneficial uses, 4:523 biological impact assessments, 4:523 characterization, 4:523 fly ash, 4:523 impacts, 4:523 London Convention 1972, 4:523 material characteristics, 4:523 mining, 4:522 physical impacts, 4:523 regulation, 4:523 surplus munitions, 4:523 main materials involved, 4:519 plastics and litter, 4:523 fishing gear/equipment, 4:524 growing concern, 4:523 impacts, 4:524 international regulations, 4:524 other debris, 4:524 regulation, 4:523–524 strapping bands/synthetic ropes, 4:524 threat to organisms, 4:524 regulation, 4:519 London Convention 1972, 4:519 regional and national conventions, 4:519 sand/gravel extraction, 4:521 biological impacts, 4:522 benthic biota, 4:522 modification of topography, 4:522 redeposition and transport, 4:522 turbidity plumes, 4:522 chemical impacts, 4:522 impacts, 4:521–522 land reclamation examples, 4:521 physical impacts, 4:521–522 modification of topography, 4:521–522 redeposition and sediment transport, 4:522 turbidity plumes, 4:522 purposes and producers, 4:521 reclamation, 4:521 regulation, 4:521 Polonium-210 (210Po), 6:239 chlorophyll concentration and, 6:249, 6:249F dissolved, distribution, 6:248–250 lead-210 ratio, 6:249, 6:249F Polovina, Jeffrey, 1:652 Poly(methyl methacrylate), in optical fibers, 1:8 Polyaniline, 1:13
Polychaetes/polychaete worms, 2:58F, 2:59F, 3:15F, 3:16, 3:134–135, 3:137F aggregation, 1:334T Alvinella caudata, 3:154F temperature tolerance, 3:153–154 Alvinella pompejana, 3:134–135, 3:137F epibionts, 2:76–77, 2:76F bioluminescence, 1:377T, 1:378–379 deep-sea communities, 1:355 epibionts, 2:76–77, 2:76F serpulid polychaetes (feather dusters), 3:139, 3:140F Polychlorinated biphenyls (PCBs), 1:551 contamination, marine organisms, 1:557, 1:557T environmental concerns, 1:551 history, 1:553 human health concerns, 1:551, 1:553 Mussel Watch Stations, 1:559F, 1:560 seabirds as indicators of pollution, 5:225, 5:275 structure, 1:552F surface seawater, 1:554, 1:555F, 1:557F time trends, 1:561F Polycyclic aromatic hydrocarbons (PAHs), fluorometry, 2:593–594, 2:593T Polydora, oyster farming, 4:280 Polymetallic sulfides, 3:890, 3:893 mining, cutter head design, 3:894F Polynomial form equation, inverse method, 3:312–313 Polynyas, 1:218, 4:540–545, 5:147–148 biological importance, 4:544 coastal, 4:541–543, 4:542F, 6:324 formation, 4:540 physical properties, 4:541–543 definition, 4:540 geographic distribution, 4:540, 4:541F ocean, 6:324 Okhotsk Sea, 4:203 open-ocean, 4:543, 4:543F characteristics, 4:540 physical properties, 4:541–543 physical importance, 4:543–544 remote sensing observations, 4:543 Weddell Sea circulation, 6:324 Polypterus spp. (bichir), 2:468, 2:469F Pomacanthidae (angelfish), 2:395–396F Pomacentridae (anemonefishes), 1:656, 1:657 Pomacentrus coelestris (blue damsel), aquarium mariculture, 3:528 Ponds, oyster farming, risk to, 4:278 Pontoporia blainvillei (Franciscana dolphin), 2:153, 2:153F, 2:155–156 Pop-down nets, 6:358–359 POPs Treaty, on persistent organic pollutants, 3:441 Population(s) components, 4:546 definition, 4:546 growth, exponential (Malthus’s), food web and, 4:723–724, 4:724F
(c) 2011 Elsevier Inc. All Rights Reserved.
577
Population dynamic(s) definition, 2:179 Eularian vs. Lagrangian formulations, 3:389–391 exploited fish see Exploited fish, population dynamics models see Population dynamic models Population dynamic models, 4:546–555 interactions between populations, 4:554 food webs and, 4:554 plankton, 4:554 mesocosms use in research, 3:655 objectives, 4:546 plankton, approaches/considerations, 4:546 individual and demographic processes, 4:546 development, 4:546 growth, 4:546 mortality, 4:546 reproduction, 4:546 plankton characteristics, 4:546–547 plankton population models, 4:547 population structure, 4:546 units, 4:546 single species, 4:547 calibration of parameters, 4:550–552 individual-based models see Individual-based models (IBMs) life cycle description, 4:547, 4:548F stage-structured models see Stagestructured population models structured models see Structured population models total density description, 4:547, 4:547F spatial distribution of single plankton populations, 4:552–553 advection–diffusion–reaction equations, 4:552–553 aggregations, 4:553–554 behavior mechanisms in, 4:553–554 coupling IBMs and spatially explicit models, 4:553 patches, 4:553–554 schooling, 4:553–554 see also Lagrangian biological models Population genetics of marine organisms, 4:556–562 aims, 4:556 applications, 4:556–557 definitions and historical approaches, 4:556 genetic change factors, 4:556 genetic diversity within species, 4:557 determining factors, 4:558 real/ideal populations, 4:559 Hardy-Weinberg (H-W) principle, 4:556 historic analyses, 4:560–561 use of molecular techniques, 4:561 molecular technologies, 4:557 morphologically cryptic, sibling species, 4:556–557 diversity estimates, 4:557 early life stages, 4:557
578
Index
Population genetics of marine organisms (continued) sympatric/allopatric cryptic species, 4:557 phylogenetics, phylogeography and paleoceanography, 4:561 constructing phylogenies, 4:561 new insights, 4:561–562 phylogeographic patterns, 4:561–562 questions addressed, 4:557 random genetic drift, 4:558 calculation of allelic distribution, 4:558 decline of heterozygosity, 4:558–559 evolution, 4:558T features, 4:558 randomly mating populations, 4:556 spatial structure, genetic diversity within species, 4:559 baseline descriptions, 4:560 gene flow, 4:560 ‘island’ model, 4:560 isolation and heterozygosity, 4:559–560 limitations of dispersal biology, 4:560 partitioning, 4:559 processes time scales, 4:560 recruitment sources, 4:560 temporal genetic change, 4:557–560 dynamism of planktonic larvae, 4:560–561 recruitment research, 4:561 reproductive success, 4:561 Porcupine Abyssal Plain, thorium flux, 4:13–15 Pore pressure, sediments, slides and, 3:795 Pore water bioirrigation, 1:398–400, 1:399F exchange, sandy sediments, 5:554–555, 5:554F flow, geophysical heat flow and, 3:43 Pore water chemistry, 4:563–571 applications, 4:563 benthic exchange rate estimation, 4:564 fossil water recovery, 4:564 mineral stability assessment, 4:563 reaction site identification, 4:563–564 sedimentary record interpretation, 4:564 data interpretation, 4:570 assumptions, 4:570 example profiles, 4:569F diagenetic processes, 4:565–567 adsorption/desorption, 4:568 advection, 4:568 biogeochemical zonation and, 4:565–567 boundary conditions, 4:570 chemical reactions, 4:567–568 diffusion, 4:568 irrigation, 4:565, 4:568–570 modeling, 4:563–564, 4:567–568 limitations, 4:564–565 artifacts, 4:564, 4:565, 4:565T
assumptions, 4:565 sampling resolution, 4:565 stoichiometry, 4:565 redox reactions, 4:566T sampling techniques, 4:564 in situ, 4:564 sensitivity, 4:563 Porichthys notatus (plainfin midshipman), 2:448F, 2:450F Porites (stony coral), heavy metal exposure effects, 1:674 Porosity, 4:490 Porphyra seaweeds, 4:428, 4:430, 4:431 Porphyra yezoensis (red seaweed), 5:320F Porpoises, 2:154–155, 3:606–607T appendages, 2:154 body shape, 2:154F color patterns, 2:154 cranial features, 2:154 exploitation, history of, 3:635–637, 3:636F hearing, 1:360, 1:360F prohibited species protection, fishery management, 2:516 trophic level, 3:623F see also Dolphins and porpoises; Odontocetes (toothed whales); specific species Port(s), 5:407–408 activities, coral disturbance/destruction, 1:675, 1:675–676 container terminal development, 5:407 major cargo ports, 5:407 publicly controlled entities, 5:407–408 top container ports (by volume), 5:407, 5:408T see also Shipping Portable Hyper-spectral Imager for LowLight Spectroscopy (PHILLS), 1:144 Port Elizabeth (South Africa), Agulhas Current, 1:129F, 1:131, 1:133T Portugal Current, 1:467–476 coastal upwelling, 1:467, 1:468–472 annual cycle, 1:469–470, 1:470F cross-shelf flow profiles, 1:472, 1:472F filaments, 1:472, 1:473F Trade Winds and, 1:467, 1:469, 1:471F geostrophic flow, 1:468F seasonal variation, 1:467, 1:469F origins, 1:467 spatial variability, 1:474, 1:475F see also Canary Current; North Atlantic Subtropical Gyre Portuguese dogfish (Centroscymnus coelolepis), open ocean demersal fisheries, FAO statistical areas, 4:231T, 4:232 Portuguese man-of-war (Physalia physalis), 3:12 Portuguese oyster, mariculture, stock reduction, disease-related, 3:534 Portunus trituberculatus see Swimming crab (Portunus trituberculatus)
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Posidonia spp. (seagrasses), use of artificial reefs, 1:228 Possible estuary associated syndrome (PEAS), 4:432, 4:434T, 4:435T Potassium (K+) concentrations river water, 1:627T, 3:395T sea water, 1:627T determination, 1:626 sediment profiles, 5:331 Potassium-argon ratio, 5:331 Potassium chromate, 1:711–712 Pot-bellied sea horse see Hippocampus abdominalis (pot-bellied sea horse) Potential density, definition, 4:28 Potential density surfaces neutral density surfaces vs, 4:27–29 ‘patched’, 4:28 Potential energy, 6:26–27 budget, 2:262 Potential enstrophy cascade of geostrophic turbulence, 6:287 fine-scale vortical mode generation mechanism, 6:287–288 Potential field maps/surfaces, bathymetric maps and, 1:297 Potential temperature, 3:115, 4:25 Brazil/Malvinas confluence (BMC), 1:424F, 1:426F seawater, 6:380T, 6:382 Potential vorticity (PV) anomalies, Kuroshio Extension and, 3:364 Baltic Sea circulation, 1:292 conservation, 4:782, 4:782F, 6:285, 6:287, 6:287–288 definition, 4:165, 6:285 dynamic tracer, 6:287 equations, 4:160, 4:162 main thermocline distribution, 4:160 climatological maps, 4:160, 4:161F ideal thermocline models, 4:160–161, 4:161–162, 4:161F, 4:162F mixed layer density evolution, 4:162 tracer contours, 4:160, 4:160–161, 4:161F seamounts, 6:288, 6:288F vertical shears, 6:286F vortical modes, 6:285–286, 6:286F, 6:288–289 Potential vorticity (PV) eddies, 4:270–271 Pots, traps, fishing methods/gears, 2:540, 2:541F Pound nets, stationary uncovered, traps, fishing methods/gears, 2:540, 2:541F Poverty, coral reef/tropical fisheries, impact, 1:653 Power consumption autonomous underwater vehicles (AUV), 4:475, 4:482–483 sonar and, 4:479–480 speed and, 4:475 gliders, 3:62 torpedo AUVs, 4:473
Index Power station effluent, 4:59 see also Nuclear power plants/stations; Pollution P.P. Shirshov Institute of Oceanology, human-operated vehicles (HOV), 6:257T Practical salinity, 6:379 Practical Salinity Scale (PSS-78), 5:127, 5:127–128 definition, 3:7 Practical salinity units (psu), 5:127 Prandtl (Schmidt) numbers see Schmidt (Prandtl) numbers Pratt isostasy, 3:86 Prawns see Shrimps/prawns Precautionary approach exploited fish, population dynamics, 2:184 fishery management see Fishery management fishery stock manipulation, 2:533–534 marine policy, 3:670 Precession (orbital), 4:311–312 equinoxes, 4:504, 4:508 Precipitation, 4:126, 4:127–128 effect on d18O values, 1:503, 1:503F El Nin˜o Southern Oscillation and, 2:230–231, 2:233F estimates, satellite measurements, 5:380 freshwater flux and, 6:165 global, 6:340–341, 6:340F global distributions, 6:170–171, 6:171F measurement, 1:138 Mediterranean Sea circulation, 3:710, 3:716–717 monsoonal oxygen isotope ratio and, 3:911 seawater density and, 3:910 North Atlantic Oscillation and, 4:68–69, 4:69F Southeast Asian Seas, 5:307, 5:309F tropics, sea surface temperature and, 2:230–231 upper ocean mixing, 6:190 see also Evaporation; Rain; Snow Precipitation collectors, aerosol deposition measurement, 1:250 Precipitation radar (PR), 5:207–208 Precision, of measurements, expendable sensors see Expendable sensors Preconditioning, Mediterranean Sea circulation, 3:723, 3:724 salinity, 3:712–714, 3:716–717, 3:724 Predation Alcidae (auks), 1:176–177 aquarium fish mariculture, 3:528 Atlantic cod (Gadus morhua), 2:509, 2:509F, 2:510, 2:510F Atlantic salmon (Salmo salar), 5:35 beaked whales (Ziphiidae), 3:649 copepods, by higher trophic animals, 3:730 fish see Fish predation and mortality fishery multispecies dynamics, 2:506–507, 2:507F, 2:509–510, 2:510F
Multispecies Virtual Population Analysis, 2:509–510, 2:510F fish larvae see Fish larvae killer whale (Orcinus orca) by sperm whales, 3:617 molluskan mariculture, 3:904 Pacific salmon (Oncorhynchus), 5:34 Procellariiformes (petrels), 4:595–596 salmonid farming, 5:26 salmonids, 5:34–35 seabirds, 5:222 sperm whales see Sperm whales (Physeteriidae and Kogiidae) Sphenisciformes (penguins), 5:527–528 stock enhancement/ocean ranching programs, 4:153–154 Predation behaviors herding, 2:436 pack hunting, 2:436 splitting off individuals, 2:436 ‘twilight hypothesis’, 2:436 see also Fish predation and mortality Predator avoidance coral reef fishes, 1:656–657 fish larvae, 2:430 juvenile fish, 2:430–431 micronekton, 4:6 schooling behavior, 2:434 vertical migration, 2:415 see also Fish predation and mortality Predator–prey interactions influence of turbulence, 5:489–491 Lotka-Volterra model, 2:596, 2:597F network analysis of food webs, 4:22 plankton see Plankton and small-scale physical processes sperm and beaked whales, 3:649 Predators oyster farming, risks to, 4:283 planktonovoric, regime shifts and, 4:700 polar ecosystems, 4:517 removal ecosystems, fishing effects, 2:205 pelagic fish, 2:205 top, regime shifts and, 4:700–702 Prehistoric climate change, seabird responses see Seabird(s) Preparative capillary gas chromatography, 5:425F example series, 5:425F radiocarbon analysis and, 5:423–424 Preservation stratigraphy, 1:451 Pressure buoyancy frequency and, 6:382F marine mammals adaptations, 3:585–586, 3:586F, 3:587F sea, measurement, 1:713–714 Pressure-compensated housings, remotely operated vehicles (ROVs), 4:745 Pressure Core Sampler (PCS), 2:50 Pressure differentials, internal energy and, 2:262–263 Pressure measurements, 5:375 atmospheric pressure and altitude, 5:375 barometer types, 5:375
(c) 2011 Elsevier Inc. All Rights Reserved.
579
Pressure-proof housings, remotely operated vehicles (ROVs), 4:745 Pressure ridges, sea ice, 5:174 Pressure sensors, strain gauges, 1:714F Pressure surfaces, floats and, 2:174 Pressure transducer (PT), 1:50F Prevailing noise, definition, 1:52 Prevailing westerlies, 2:225–226 Prey cephalopods, 1:524 consumption, south China Sea LME, 3:413 fish larvae, 2:383–384 foraging seabirds and, 5:231 killer whale migration and, 3:599 microbes as, food web transfers, 3:803 migration, fish vertical migration, 2:414 predator interactions see Predator–prey interactions removal, ecosystems, fishing effects, 2:205 seabirds, 5:281–282 top predators in polar marine food webs, 4:517 Price-Weller-Pinkel dynamic instability modeling, 6:198–199 Priestly formula, 4:220–221 Primary basal glide plane, definition, 5:464 Primary nitrite maximum (PNM), 4:36–37, 4:38F see also Nitrogen cycle Primary NO2, maximum, 4:37–38, 4:38F Primary particles origins, 4:330–333, 4:331F see also Particle(s); Particle aggregation dynamics; specific types Primary production, 4:89–90, 4:97–98, 4:103 attributable to marine organisms, 2:147 carbon cycle and see Carbon cycle, biological pump continental shelves, 4:256 definition, 4:573, 4:578, 6:93 distribution see Primary production distribution estimation/measurement see Primary production measurement methods fiordic ecosystems, 2:361 global, marine contribution to, 4:588 microphytobenthos, 3:808–809 nitrogen cycle and, 4:38–39, 4:39F processes see Primary production processes see also Photosynthesis; Phytoplankton; Phytoplankton size structure; Primary production processes Primary production distribution, 4:572–577 different quantities measured, 4:572 estimation methods, 4:572, 4:572T factors influencing variations, 4:573–574 light, 4:573 micronutrient availability, 4:573–574 nutrient availability, 4:573
580
Index
Primary production distribution (continued) phytoplankton biomass, 4:573 species composition/succession, 4:574 temperature, 4:573 horizontal distribution, 4:575 areas of high productivity, 4:575 HNLC regimes, 4:575 regional/seasonal variations, 4:575 influencing factors, 4:573 mathematical modeling techniques, 4:574 measurement compilations, 4:575 measuring by remote sensing, 4:575–577, 4:576F advantages, 4:576 improvements expected, 4:576–577 methodology, 4:575 problems, 4:576–577 successful models, 4:575–576 requirement for extrapolation schemes, 4:572–573 research difficulties, 4:572 space-timescale links, 4:572 vertical distribution, 4:574–575 critical depth, 4:574–575 euphotic zone, 4:574 mixed vs. stratified layers, 4:575 see also Primary production measurement methods; Primary production processes Primary production measurement methods, 4:578–584 approaches, 4:579 13 C method, 4:580T, 4:581 14 C method, 4:580–581, 4:580T 18 O method, 4:580T, 4:581 change in O2 concentration, 4:579, 4:580T change in total CO2, 4:579–580, 4:580T remote sensing, for distribution, see also Primary production distribution technical objectives, 4:579 see also Productivity tracer techniques definitions, 4:578 distribution, see also Primary production distribution methodological considerations, 4:581 containers, 4:582, 4:583T filtration or acidification, 4:583 incubation, 4:581–582 artificial incubators, 4:580T, 4:582 in situ, 4:580T, 4:581–582 simulated in situ, 4:580T, 4:582 types, 4:581 incubation duration, 4:582–583, 4:584T interpretation of carbon uptake, 4:583–584 photosynthesis and phytoplankton growth, 4:578–579 photosynthesis reaction, 4:578–579 photosynthetic quotient, 4:579
phytoplankton growth reaction, 4:579 quantifying photosynthesis, 4:578–579 planktonic primary production, 4:578 sampling, 4:581 contamination avoidance, 4:581 light exposure avoidance, 4:581 trace metal-clean procedures, 4:581 turbulence avoidance, 4:581 significance of uncertainties, 4:584 uncertainty of interpretations, 4:584 uncertainty of measurements, 4:584 see also Network analysis of food webs Primary production processes, 4:585–589 benthic primary productivity, 4:585 cell processes, 4:586–587 cell size, 4:587 diversity of photosynthesizers, 4:586–587 phylogenetic differences, 4:587 pigmentation and photon absorption, 4:587 characteristics of primary producers, 4:585 mineral dependencies, 4:587 movement, 4:587 pigmentation, 4:587 chemolithotrophy, 4:585 determinants of productivity, 4:587–588 C:n:p ratios, 4:587 geophysical and ecological factors, 4:587–588 limiting nutrients, 4:588 marine contribution to global primary production, 4:588 net primary productivity by habitat, 4:586T ocean habitat, 4:585–586 absorption of solar radiation, 4:585 nutrients, 4:586 stratification, 4:586 see also Carbon cycle; Carbon dioxide (CO2) cycle; Nitrogen cycle photolithotrophy, 4:585 bacteriochlorophyll-based, 4:585 O2-evolvers, 4:585 rhodopsin-based, 4:585 see also Primary production distribution; Primary production measurement methods Primary productivity, 6:231 PRIMER, 4:536 Primeval oceans, redox chemistry, 6:84–85 ‘Primordial’ helium, 6:277 Prince William Sound coastal current, 1:459 oil pollution and, 1:459 earthquake, 6:128 Principle-component analysis (PCA), 4:536, 4:719–720 Principle-co-ordinates analysis (PCoA), 4:536, 4:719–720 Prionace glauca (blue shark), 4:135, 4:240
(c) 2011 Elsevier Inc. All Rights Reserved.
Prions, 4:590 migration, 5:240–242, 5:241T see also Procellariiformes (petrels) Probability density function (PDF), rogue waves, 4:773–774, 4:774F Procellariidae, 4:590 migration, 5:240–242, 5:241T see also Procellariiformes (petrels); specific species Procellariiformes (petrels), 4:135, 4:590–596, 5:266T breeding ecology, 4:590, 4:593–595, 5:248 chick-rearing, 4:594–595, 4:595, 4:595F, 5:248 copulation, 4:593–594 displays, 4:593 egg incubation, 4:594, 4:594F characteristics, 4:590, 4:591F conservation, 4:595–596 food/foraging, 4:593 nocturnal, 5:230 stomach oil, 4:593, 4:595 see also Seabird foraging ecology life spans, 4:590, 5:249 migration, 5:239–240 population ecology, 4:590 demography, 4:590, 4:592F distribution, 4:590, 4:592–593 changes in, 4:592–593, 4:592F regulation of population size, 4:590–592 reproductive effort, 4:595 species, 4:590, 4:591F richness by latitude, 4:590, 4:592T threats, 4:595–596 human activities, 4:595–596 longline fishing, 4:596, 5:249 predation, 4:595–596 see also Seabird(s); specific families/ genera Prochlorophytes, 2:582–583 Productivity biodiversity and, 2:143 nitrogen cycle and, 4:38–39, 4:39F primary see Primary production reconstruction from sedimentary records see Sedimentary records, productivity reconstructions Productivity tracer techniques, 6:93–99 aphotic zone oxygen consumption, 6:94–95 comparison, 6:100, 6:100T euphotic zone mass budgets, 6:95–97 overview of techniques, 6:93–94 tracer flux-gauge determinations, 6:97–99 see also Tracer(s) Profilers, moorings, 3:921–922 Profiling autonomous Lagrangian circulation explorer (PALACE), 6:370 Progressive vector diagrams, 3:453F Prohibited species catch limits, control systems, fishery management, 2:516
Index Projected clasts definition, 5:464 Project Mohole, 2:45 Prokaryotic microorganisms, upper temperature limits, 6:12T Propagating rifts and microplates, 4:597–605, 4:597–600 bookshelf faulting, 4:597–600 causes of rift propagation, 4:600–601 plate motion changes, 4:601 plume-related asthenospheric flow, 4:600, 4:601 subduction related stresses, 4:601 topographic gradient, 4:600–601 definition, 4:597 doomed rift, 4:599F definition, 4:597 duelling propagator system, 4:602F definition, 4:597 microplate formation, 4:601, 4:603 evolution, 4:597 failed rift, 4:597, 4:598F Galapagos 95.51W system see Galapagos 95.51W propagating rift system geometry, 4:597–600, 4:599F continuous propagation model, 4:597, 4:598F discontinuous propagation model, 4:597, 4:598F equations, 4:597–600 non-transform zone model, 4:597, 4:598F overlapping spreading center geometry, resemblance to, 4:597 overlap zone, 4:597, 4:598F, 4:599F pseudofaults, 4:597, 4:598F, 4:599F transform fault fossil, 4:597, 4:598F instantaneous, 4:597, 4:598F lithospheric transfer, 4:597, 4:598F, 4:599F microplates see Microplates migrating overlapping spreading centers, 4:601 plate boundary geometry, 4:601, 4:602F, 4:604, 4:604F propagation rates, 4:597, 4:600–601 scales of rift propagation, 4:601, 4:604 large scale, 4:601, 4:602F small scale, 4:601 seafloor spreading see Spreading centers shear deformation, 4:597, 4:597–600 thermal and mechanical consequences, 4:600 basalt glasses, 4:600, 4:600F ferrobasalts, 4:600 lava compositional diversity, 4:600, 4:600F magnetic anomalies, 4:600 see also Cocos-Nazca spreading center; Easter microplate; Galapagos Rift; Juan Fernandez microplate; Midocean ridge geochemistry and petrology; Mid-ocean ridge tectonics; Spreading centers Propellor anemometers, 5:375, 5:376F
Propellor-driven AUVs see Torpedo AUVs Propulsion efficiency, autonomous underwater vehicles (AUV), 4:475 remotely operated vehicles (ROVs), 4:742 Protactinium-231 (231Pa), 6:237–238 Protactinium-234, sediment chronology, 5:328T Protactinium/thorium ratio, 3:455–456 Protection see Pollution control approaches Protection and Insurance (P&I) clubs, 5:407 Protectionism/subsidies, shipping, 5:405–406 cabotage system, 5:406 domestic flag fleet, 5:405 operating cost subsidies, 5:406 shipbuilding subsidies, 5:406, 5:407 Proteinaceous material, fluorometry, 2:593, 2:593T Protista, 4:613–614 Protocetidae, 3:592 see also Cetaceans Proton affinity see pH Proton-precession magnetometers, 3:479 Protozoa analytical flow cytometry, 4:247, 4:247F see also Planktonic foraminifera; Radiolarians Proximal continental shelf, 3:397 Proxy tracers, 3:455 necessary characteristics, 3:455 Prudhoe Bay, Alaska gouging, 3:191 sub-sea permafrost, 5:562, 5:563F, 5:567, 5:567F mean annual seabed temperature, 5:564, 5:565F pore fluid pressure profiles, 5:565, 5:566F salt transport, 5:565 Prymnesiophytes, 6:83 lipid biomarkers, 5:422F PSC (Pacific Salmon Commission), 5:21–22 Pseudofaults, 4:597, 4:598F, 4:599F, 4:603F Pseudorca crassidens (false killer whale), 2:149 Pseudothecosomata pteropods, 3:14, 3:15F Pseudotuberculosis, vaccination, mariculture, 3:523 PSIW (Pacific Subarctic Intermediate Water), temperature-salinity characteristics, 6:294T, 6:297–298, 6:298F C (focusing factor), definition, 6:242 PSM geophysical heat flow model, 3:45 PSUW (Pacific Subarctic Upper Water), temperature-salinity characteristics, 6:294T
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Psychrometer classical sling, 5:377–378 resistance thermometer, 5:378 Psychrometric method, classical sling psychrometer, 5:377–378, 5:378F Psychrophilic microbes, definition, 2:73–75 PT (pressure transducer), 1:50F Pteriomorpha (mussels), 1:332 Pterodroma inexpectata (mottled petrel), 4:591F see also Procellariiformes (petrels) Pteropods, 3:14, 4:460 calcium carbonate formation, 1:445–446 Gymnosomata, 3:14 Thecosomata, 3:14 Ptolemy, ship reports used for world map compilation, 5:410 Ptychoramphus, 1:171T see also Alcidae (auks) Ptychoramphus aleuticus (Cassin’s auklet), 4:458 Public law of the sea, 3:432 admiralty law, 3:432 Convention on the Law of the Sea (UNCLOS), 3:432 historical development, 3:432 maritime law, 3:432 see also Law of the Sea Public policy, marine policy vs., 3:664, 3:664T Puerto Rico internal tides, 6:53F internal waves, 6:50 sand mining, 1:588, 1:588F, 1:589 effects, 1:589 water, microbiological quality, 6:272T Puerto Rico Trench anomaly, 5:68 Puerulus settlement, Panulirus cygnus (western rock lobster), 1:704–705, 1:707F Puffins, 1:171, 1:173F horned, 5:258–259, 5:259F migration, 5:244–246 see also Alcidae Puffinus griseus see Sooty shearwater Puffinus huttoni (Hutton’s shearwater), 5:253, 5:254F Puffinus Iherminieri (Audubon’s shearwaters), 4:590, 5:252 Puffinus puffinus (Manx shearwater), expansion of geographical range, 4:593 Puffinus tenuirostris (short-tailed shearwater), 4:593 Puka Puka Ridges, 5:299–300, 5:300F Pulse repetition frequency (PRF), active sonars, 5:505 Pumped tunnels, 3:372 Pumps, harvesting gear, 2:542 Punctuated equilibrium, 4:709 see also Regime shifts Purposeful tracer experiment, 1:687 Purse lines, fishing methods/gears, 2:536
582
Index
Purse seines, 2:536, 2:536F, 5:470 Pacific salmon fisheries, 5:12 pelagic fisheries, 4:237–239, 4:238F vessel tonnage, 4:237–239, 4:239F PV see Potential vorticity (PV) PV (potential vorticity) eddies, 4:270–271 P-waves, 5:361 propagation anisotropy, 5:366 Pycnocline, 3:207, 6:163, 6:218 diapycnal diffusivity, 6:88 open ocean convection, 4:220, 4:221F thermocline and, 6:218 under-ice boundary layer, 6:158–159, 6:161 vortical modes, 6:287, 6:288 see also Permanent pycnocline Pycnogonids (sea spiders), 1:377T, 2:59F Pygmy right whales (neobalaenids), 1:276, 1:277T, 3:594 habitat, 1:279 lateral profile, 1:278F trophic level, 3:623F see also Baleen whales Pygoplites diacanthus (regal angelfish), aquarium mariculture, diet, 3:528–529 Pygoscelis, 5:525–526 breeding patterns, 5:525, 5:525–526 characteristics, 5:522T, 5:525, 5:526F distribution, 5:522T, 5:525 feeding patterns, 5:522T, 5:525–526 migration, 5:239 nests, 5:522T, 5:525–526 species, 5:522T, 5:525 see also Sphenisciformes (penguins); specific species Pygoscelis adeliae see Ade´lie penguin Pygoscelis antarctica see Chinstrap penguin Pygoscelis papua (gentoo penguin), 5:522T, 5:525 Pygoscelis pygoscelis ellsworthii, 5:525 Pygoscelis pygoscelis papua, 5:525, 5:525–526 Pynocline, 6:225, 6:231 Pyranometer, 3:106F Pyrgeometer, 3:105–106 broadband, 3:324, 3:324F Pyrite, 1:543–544 diagenesis, 4:563 Pyrogallol red, 1:13 Pyrogens, 3:565 Pyrolobus fumarii (archaea), 2:77–78 Pyrosoma spp. tunicates, 1:379–380
Q Quagga mussel (Dreissena bugensis), 3:908 Quantum yield of fluorescence, 2:581 Quartz ocean boundary sediments, 4:140–141 in optical fibers, 1:8 sediment cores, 3:886
Quasigeostrophic equations, 2:605–606 drawbacks, 2:606 Quasigeostrophic potential vorticity, 2:606 Quasigeostrophy, 3:21 Quasi-inherent optical property, 3:247 see also Ocean optics Quaternary lavas, paleomagnetism, 3:26 Quaternary sediments, clay minerals, 1:569 degradation, 1:568F Queensland (Australia), El Nin˜o Southern Oscillation (ENSO), economic impact, 2:238–239 Quenching, fluorescence see Fluorescence Quest, 6:260T QUICKBIRD satellite, 6:136F QuikSCAT satellite, 5:75, 5:203, 5:204T Quinaldine cyanide fishing use, 1:672 definition, 1:677
R RAD see Ridge axis discontinuity (RAD) Radar drifter tracking, 2:172–173 synthetic aperture see Synthetic aperture radar (SAR) Radar altimetry, 1:144 basic measurements, 5:58 ocean applications of airborne systems, 1:144 Topex/Poseidon satellite altimeter system, 5:58, 5:59F Radar backscatter black patches, 5:572, 5:572F mineral oil films, 5:572, 5:572F surface films, 5:571–572 Radar measurements, rogue waves, 4:778 Radarsat-1 and Radarsat-2, 5:103 Gulf of Mexico image, 5:108–109, 5:108F oil spills off Point Barrow (Alaska), 5:104F South China Sea image, 5:110–111, 5:111F Radial density currents, 4:62 steady flow input, 4:62 Radial erosion, meddies, 3:706–707 Radiance, 3:320, 5:114 black-body, 3:114, 3:114F, 3:320, 3:320F, 6:339 definition, 3:246–247, 3:319, 3:320F, 4:619–620, 4:620F Hydrolight simulation, 4:626–627, 4:626F, 4:627F measurement, 3:322, 4:620–621 see also Infrared (IR) radiometers reflectance, 3:247 upwelling, diffuse attenuation coefficient, 5:115 water-leaving, 3:251–252, 3:252F, 5:114, 5:115, 6:115 see also Ocean optics
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Radiant energy, definition, 3:319 Radiant flux, definition, 3:319 Radiant intensity, definition, 3:319, 3:320F Radiated shanny (Ulvaria subbifurcata), 5:491 Radiation absorption, 1:7–8, 1:8F black-body, 3:114, 3:114F, 3:320, 3:320F, 6:339 cosmic see Cosmic radiation Earth’s budget, 3:114, 3:114F electromagnetic, absorption, 1:7–8 galactic, 5:130 infrared see Infrared (IR) radiation penetrating shortwave see Penetrating shortwave radiation solar see Solar radiation transmittance, Beer’s law, 5:388–389 ultraviolet, 3:244 see also Solar radiation Radiational tides, definition, 6:32 Radiation shields, for temperature sensors, 5:376F, 5:377 Radiation stress definition, 6:312 waves on beaches, 6:312–313, 6:314 mean flow forcing, 6:312, 6:313 set-up, 6:312–313 Radiative fluxes, 5:205–206 global budget, 5:205T see also Air–sea heat flux Radiative transfer (oceanic), 4:619–628 studies, 1:392, 4:625, 6:117T see also Hydrolight theory, 3:247, 4:619 see also Bio-optical models; Infrared (IR) radiometers; Ocean color; Ocean optics Radiative transfer equation (RTE), 1:385, 1:392, 4:623 Radioactive wastes, 4:629–636 accidental releases, 4:632–633 anthropogenic radioactivity, inputs, 4:634–635, 4:635 discharges to sea, 4:630–632 disposal at sea, 4:629–630, 4:629T, 4:630F examples of, 4:631F sources, 4:629–630 nuclear accidents, 4:633–634 nuclear weapon tests, fallout from, 4:633–634 Radioactivity discovery, 4:629 fluid packets and, 5:136 see also Radionuclides; specific isotopes Radiocarbon (carbon-14, 14C), 4:637–652 activity ratio relative, 4:638 air–sea gas exchange, 4:650–651 experiments, 1:153 allochthonous, 5:420 anthropogenic, 4:638 application, 4:640
Index atmospheric, 4:637 historical recordings, 4:639, 4:639F history, 4:637, 4:637F production rate, 4:637 testing, 4:638 bomb produced, 4:638 bottom waters, 3:308F circulation tracer, 4:106–107, 4:107 cosmogenic, 1:678 production rates, 1:680T date tuning, 4:311 decay rate, 4:637, 4:638 deep ocean mixing, 4:646–647 definition, 4:113 D14C, coral-based paleoclimate records, 4:339T, 4:345, 4:346 decadal variability, 4:343 upwelling, 4:340–341 dissolved inorganic carbon and, 4:111–112, 4:111F distribution for large-scale circulation, 4:642–645 features, 4:637 fractionation, 4:638 Global Climate Models and, 4:111–112, 4:111F implications for large-scale circulation, 4:642–645 incubation, 6:93 inverse modeling, 3:307–310 measurements, 4:126 measurement techniques, 4:639–640 natural, 4:637 and bomb components, separation of, 4:645–646, 4:646F ocean models, calibration, 4:647–650 oceanographic applications, 4:646 oxygen utilization rate, 4:647, 4:648F primary application, 4:637 residence time, 4:646–647 sampling history, 4:640–642 techniques, 4:639–640 sediment chronology, 5:327, 5:328T, 5:329–330 sediment depth and, 5:329–330, 5:329F sediments, sources, 5:419–420 single compound measurements see Single compound radiocarbon measurements thermocline ventilation rate, 4:650–651, 4:651F tracer applications, 1:683T advantages, 1:685 tracer as, 3:300 tracing applications, 5:419 ventilation rate, 4:646–647 see also Bomb carbon; Carbon (C), isotopes; Carbon isotope ratios (d13C); Radiocarbon age; Single compound radiocarbon measurements Radiocarbon age, 5:420–421 reservoir age, 5:421 Radiocarbon carbon dioxide (14CO2), 4:637
Radio direction finding, drifter tracking, 2:172–173 Radioisotopes advantages as tracers, 1:682 see also specific isotopes/elementssee specific radionuclides Radioisotope tracers geochemical sections and, 1:684 techniques, 1:269 Radiolarians, 4:613–617 algal symbionts, 4:613–614 location within cell body, 4:614 role, 4:617 bioluminescence, 1:376, 1:377T biomineralization, 4:615–616 definition and process, 4:615 deposition rate, 4:616 growth forms, 4:615–616 sedimentation rate, 4:616 cellular morphology, 4:614 cell parts and organization, 4:614 parts and organization, 4:614F distribution, 4:613–614 feeding, 4:614 gelatinous colonies, 3:9 morphology, 4:613–614, 4:613F opal as productivity proxy, 5:336 paleothermometric transfer functions and, 2:111 reproduction, 4:616 asexual/sexual, 4:616 siliceous skeleton, 4:614 skeletons, as biogenic silica in marine sediments, 3:683–684 symbiotic relationship with dinoflagellates, 3:9 taxonomy, 4:614–615 diversity, 4:615 groups and subgroups, 4:615 zoogeography, 4:616–617 effect of temperature, 4:616–617 factors influencing abundance, 4:616–617 food, 4:617 growth requirements, 4:617 role of algal symbionts, 4:617 shallow-water species zones, 4:616–617 Radiometer antennas, 5:127, 5:129 beam width, 5:128–129 footprint, 5:128–129 Radiometers, 5:91 fixed platform, 4:737, 4:737F infrared see Infrared (IR) radiometers in-water, 4:737 mesoscale eddies, 3:757 microwave see Microwave radiometers multichannel see Multichannel radiometers narrow beam filter see Narrow beam filter radiometers reflected sunlight measurement, 1:141–142 satellite, 5:205 Radiometric dating, 3:25 techniques, manganese nodules, 3:490
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Radiometric quantities, 4:619–621, 4:620T Radionuclides anthropogenic, sources of, 4:85 excess activity, 5:329 naturally occurring, activity of, 4:83 seabirds as indicators of pollution, 5:277 sediment profiles, 5:329–331 see also Sediment chronologies tracers bioirrigation, 1:399 long-term changes see Long-term tracer changes submarine groundwater discharge, 5:555–557 see also Cosmogenic isotopes; Nuclear fuel reprocessing; Radioisotopes; Radionuclides; specific isotopes/ radionuclides Radium, 4:634, 6:240–241 223 Ra, 6:241 226 Ra, 6:240 228 Ra, 6:240, 6:241F barium ratio, 6:253F concentration depth profile, 6:252F deep water of Pacific and Atlantic, 6:252F depth profile, 6:252F distance from coast and, 6:252F distribution, seawater, 6:251–252 off Carolina coast, 6:251F fluvial transport, 6:245 groundwater flux and, 3:92–94, 3:93F isotopes, 6:251–252 submarine groundwater discharge (SGD), 5:556 South Atlantic Bight, 5:556F surface water, distribution in, 6:239, 6:240F tracer applications, 6:251 Radon (Rn) air–sea gas diffusion experiments, 1:153 bioirrigation tracing, 1:399 bottom water, distribution in, 6:239–240, 6:240F diffusion coefficients in water, 1:147T gas exchange in estuaries, 3:3 groundwater flux and, 3:93, 3:94 vs. seepage meter, 3:94F Schmidt number, 1:149T submarine groundwater discharge (SGD), 5:557 Radon-222 (222Rn), 6:241–242 bottom water profile, 6:250F radium-226 ratio, 6:250–251 Radon transform, 4:783 RAFOS (Ranging and Fixing of Sound), 1:92, 3:702–703 RAFOS floats, 2:176–177, 2:177–178 ballasting, 2:177 diagram of structure, 2:177F operating depth, 2:177 Raia batis (common skate), demersal fishing impact, 2:92 Raia laevis (barndoor skate), demersal fishing impact, 2:92
584
Index
Rain acid, seabirds and, 5:277 attenuation, 5:128, 5:131 bubble formation, 1:440 d18O values, 1:503, 1:504F see also Precipitation; Rainfall Rainbow trout see Oncorhynchus mykiss (rainbow trout) Rainbow trout (Oncorhynchus mykiss), 2:453F Rainfall global, 6:165 heavy, eastern tropical Pacific Ocean and El Nin˜o, 5:97–98 sewage contamination, indicator/use, 6:274T tropics, 6:171 patterns, El Nin˜o and, 2:241 see also Precipitation; Rain Rain ratio, 1:371 Ram(s), 3:185 definition, 3:190 Raman scattering, fluorescence and, 2:590, 2:590F RAMS (Random Access Measurement System), 2:173 Random Access Measurement System (RAMS), 2:173 Range autonomous underwater vehicles (AUV), 4:475 gliders, 3:62 Ranging and Fixing of Sound (RAFOS), 1:92, 3:702–703 Ranging and Fixing of Sound (RAFOS) floats see RAFOS floats Ranked species abundance (dominance) curves, 4:535 Rankine cycle, 4:168–169, 6:10 Raoult laws, 2:248 Rapana venosa (veined rapa whelk), environmental impact, 3:908 Rapid backscatter ripple profiler (BSARP), 1:39, 1:39F Rare earth elements (REEs), 4:653–665, 4:653F history, 4:654 inputs into ocean, 4:659–661, 4:662T atmospheric flux, 4:660–661, 4:662T remineralization flux, 4:661, 4:662T, 4:664 riverine flux, 4:659, 4:662T ionic radii, 4:653, 4:655T isotopes, 4:654 mean oceanic residence times, 4:661–664, 4:662T equation, 4:663 normalization, 4:654, 4:655T North Pacific Deep Water (NPDW), 4:654, 4:655T Post-Arcean Australian Sedimentary rocks (PAAS), 4:654, 4:655T oceanic distributions, 4:654–655, 4:656F, 4:658T vertical profiles, 4:655, 4:658F, 4:662
particle reactivity, 4:654–655, 4:658T, 4:660F, 4:661–664, 4:664 patterns, 4:655–656, 4:659F fractionation between particles and sea water, 4:656, 4:660F North Pacific Deep Water (NPDW)normalized, 4:656, 4:659F, 4:660F surface water comparisons, 4:660–661, 4:663F, 4:664 Post-Arcean Australian Sedimentary rocks (PAAS)-normalized, 4:656, 4:659F sea water concentrations, 4:654, 4:655T shale concentrations, 4:654, 4:655T see also specific rare earth elements Rarefaction curves, 4:535 Rasterlliger kanagurta (Indian mackerel), 4:368 Ratchet effect, performance issues, fishery management, 2:518–519 Rattail fish (Macrouridae), 2:59F Ray-finned fishes (Actinopterygii), 2:468 Rayleigh Distillation Model, 1:503, 1:503F, 1:504F Rayleigh models, nitrogen isotopes, 4:41, 4:41F Rayleigh number, 4:218–219, 4:222 Rayleigh region, active sonars, 5:507 Rayleigh roughness parameter, 1:116 Rayleigh scattering, 6:110–111 solar irradiance, 5:120 Rayleigh waves acoustics in marine sediments, 1:79–80 mantle, 3:869 Raymo, M E, 1:516 Rays (Batoidea), 2:395–396F, 2:474 tropical fisheries development, impact, 1:651–652 Ray theory (acoustic), 1:105, 1:106F shallow water, 1:119 see also Acoustic rays Razorbill (Alca torda), 1:173F, 1:175 see also Alcidae (auks) Razor clam, acoustic scattering, 1:69 Reaction-diffusion, pore water profile, 4:569F Reactive odd nitrogen, 1:250 Reactive oxygen species (ROS), 4:414–416 iron and, 6:76–78 Real estate development, impacts on marine biodiversity, 2:146 on marine habitats, 2:146 Recherche Archipelago, 3:444F, 3:445, 3:447, 3:449, 3:451 Recirculating flows see Topographic eddies Recirculating gyres Deep Western Boundary Current (DWBC), 2:562–563 Gulf Stream System, 2:558–560, 2:561F Recirculation cells, abyssal, 1:16–18, 1:20F, 1:29–30 Recovery benthic flux landers, 4:486 moorings, 3:919
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Recreation corals, human disturbance/destruction, 1:675 see also Beach(es); Marine recreational waters Recreational fishing, 2:523–524 pelagic fish, 4:241 Salmo salar (Atlantic salmon), 5:1, 5:4, 5:4–5, 5:9 Recreational waters, marine see Marine recreational waters Recruitment, 2:217 exploited fish, population dynamics production, 2:179, 2:179–180, 2:179F status assessment, 2:181–182, 2:182F Rectangular mouth opening trawl (RMT), 6:357T, 6:364, 6:365F Red algae (Rhodophyta spp.), 4:427 Red clays thermal conductivity, 3:43–44 see also Clay minerals Red drum (Sciaenops ocellatus), stock enhancement/ocean ranching programs, 4:147T, 4:150 Redfield, Alfred C, 4:681–682 Redfield ratio, 3:331, 4:106, 4:408, 4:408F, 4:677–686 definition, 4:678 laboratory grown phytoplankton, 4:679 phytoplankton in sea, 4:679 cell wall contributions, 4:679 problems, 4:679 reporting of, 4:679 useful properties, 4:679, 4:686 see also Carbon cycle; Nutrient(s); Phosphorus cycle; Silica cycle, marine Redfield stoichiometry, definition, 3:7 Redfish see Sebastes (redfish) Red-necked phalarope, 4:393 appearance, 4:393 diet, 4:398 distribution, 4:395, 4:397 habitat, 4:396–397 migration, 4:398 names, 4:398, 4:399T population declines, 4:399 surface-tension feeding, 4:395, 4:396F see also Phalaropes Red noise, 4:715 ocean variability, 4:714 Redondo Canyon, 5:448F, 5:462 Redox, definition, 1:268, 6:85 Redox chemistry equilibrium constant, 1:541 estuarine sediments, 1:540 measurement, 1:546 nutrient cycles and, 1:547–549 particulates and, 1:546 principal reactions, 1:542T pore water, 4:566T, 4:567–568 primeval oceans, 6:84–85 trace metals in oxygenated seawater, 6:78–80 see also Oxidation; Reduction
Index Red phalarope, 4:393 appearance, 4:393, 4:394F distribution, 4:395 habitat, 4:397 migration, 4:398 names, 4:398, 4:399T see also Phalaropes Red Sea circulation see Red Sea circulation oil pollution, coral impact, 1:673 salinity, 5:127 salty outflow, 4:128 sewage discharges, coral impact, 1:673 Red Sea Atlantis II Deep, hydrothermal reactions and conservative elements in sea water, 1:628, 1:628F Red sea bream (Pagrus major) stock enhancement/ocean ranching, 4:147T, 4:149 stock enhancement/ocean ranching programs Japan, 2:528–530 size-dependent survival, 4:149, 4:150F Red Sea circulation, 4:666–676 deep circulation, 4:667, 4:669–673 deep water sources, 4:670–671 interannual variability, 4:673 open ocean convection, 4:670–671 plume convection, 4:672–673 renewal times, 4:670–671, 4:675–676 slope convection, 4:671, 4:673 see also Deep convection evaporation, 4:666, 4:667 freshwater fluxes, 4:666, 4:675–676 Gulf of Aden exchanges see Gulf of Aden, Red Sea circulation water exchange Hanish sill, 4:666, 4:666F, 4:674 heat fluxes, 4:667, 4:675–676 hydrographic structure, 4:667 convection, 4:667 deep layer, 4:667 oxygen content, 4:667, 4:669F, 4:672–673 salinity, 4:666, 4:667, 4:669F, 4:670, 4:672–673, 4:675, 4:675T seasonal variations, 4:667, 4:669F, 4:675, 4:675T surface temperatures, 4:667, 4:668F, 4:669F temperature distribution, 4:667, 4:668F, 4:669F, 4:670, 4:672–673, 4:675, 4:675T upper layer, 4:667 vertical mixing, 4:667 inflows, 4:667, 4:674 International Indian Ocean Expedition, 4:670–671 modeling and measurement, 4:667, 4:674 chemical tracer data, 4:670–671 current measurements, 4:667–668, 4:674
high resolution 3D circulation models, 4:668–669 linear 2D box models, 4:671 linear inverse box models, 4:667–668 vertical advection-diffusion model, 4:670–671 momentum fluxes, 4:666 monsoon winds, 4:667, 4:667–668, 4:674 Perim Narrows, 4:666F, 4:674 Red Sea Deep Water, 4:669–673, 4:674F Red Sea Water, 4:666, 4:673, 4:675, 4:675F seasonal variations, 4:666 upper layer circulation, 4:667–669 anticyclonic gyres, 4:668–669 boundary currents, 4:668–669 seasonal variation, 4:667–668 thermohaline circulation, 4:667 wind driven circulation, 4:667–668 vertical distribution of temperature, 4:673F wind field, 4:666–667, 4:674 wind stress, 4:666–667 see also Indian Ocean current systems; Thermohaline circulation; Winddriven circulation Red Sea Deep Water, 4:669–673, 4:674F Red Sea-Persian Gulf Intermediate Water (RSPGIW), temperature–salinity characteristics, 6:294T, 6:298, 6:298F Red Sea Water, 4:666, 4:673, 4:675, 4:675F Red seaweeds, mariculture, 5:320F, 5:321F Red snapper (Lutjanus campechanus), marine protected area economics, 3:673–674 Red-tailed tropic bird (Phaeton rubricauda), 3:444–445, 4:372F see also Phaethontidae (tropic birds) Red tides spectral range for remote sensing, 4:735T see also Algal blooms; Phytoplankton blooms; Red tides Reduced nitrogen species, deposition rates, 1:256T Reduction electron affinity, 1:542F sulfate and, 1:543–545 see also Redox chemistry Redundancy bathymetric data, 1:299 mooring instrumentation, 3:922 Reef(s) artificial see Artificial reefs coastal, 3:444–445 coral see Coral reef(s) rigs to, program see ‘Rigs to reefs’ program small-scale, 6:57–58 turbulence, 6:62–63 Reef nets, Pacific salmon fisheries, 5:13 Reentry cone, 2:40–41, 2:42F
(c) 2011 Elsevier Inc. All Rights Reserved.
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Reentry cone seal (CORK), deep-sea drilling, 2:50, 2:50F REEs see Rare earth elements (REEs) Reeve net, 6:355 Reflagging Agreement, fishery management, 2:524 Reflectance, 1:8, 4:733 definition, 5:114 irradiance, 5:114 remote sensing, 5:114, 5:115 sea bottom, 4:734 substance concentrations and, 5:115 total surface, 5:115 Reflectance spectra, water types, 4:733F Reflectance spectroscopy, 1:8 chemical sensors, sensor design, 1:11 see also Absorbance spectroscopy Reflection (of electromagnetic radiation), 1:8 Reflection coefficient, acoustic remote sensing, 1:84–86, 1:86–87, 1:86F Reflection loss, acoustic remote sensing, 1:86F, 1:87, 1:87F Reflection of sunlight, surface films, 5:571 Reflectivity (acoustic) critical angle, 1:115 sea bottom, 1:114–115 Refracted-refracted (RR) rays, 6:42 Refracted-surface-reflected (RSR) rays, 6:42 Refractive focusing, 6:313–314 Refractive index, electromagnetic wave propagation, 2:251–252 Refractory metals, 4:687–698 concentration in seawater, 4:688T, 4:689F crustal abundance, 4:688T crustal abundance vs. oceanic concentration, 4:689F distribution, 4:687–690 aluminum, 4:687, 4:689–690 bismuth, 4:695–696 gallium, 4:690–691 hafnium, 4:693–694 indium, 4:691–692 iron, 4:694–695 niobium, 4:694 scandium, 4:692 tantalum, 4:694 thorium, 4:696 titanium, 4:692–693 zirconium, 4:693–694 history, 4:687 residence times, 4:688T see also Heavy metals; Trace element(s), nutrients Refrigeration, ocean thermal energy conversion, 4:172 Refuge effect definition, 3:673 marine protected areas, 3:673, 3:674 Regal angelfish (Pygoplites diacanthus), aquarium mariculture, diet, 3:528–529 Regime shifts, 2:217 abrupt shifts, 4:702
586
Index
Regime shifts (continued) analysis, 4:717–721 approaches, 4:718–720 artifacts, 4:717–718, 4:718 curve fitting, 4:717–718, 4:718F, 4:720 data interpretation, 4:717–718, 4:718F drivers and responses, 4:717–718 independence of variables, 4:719–720 information theory approach, 4:720 nonlinear techniques, 4:719–720 numerical analysis techniques, 4:717–718 STARS algorithm, 4:719, 4:720 timescale, 4:717 variable selection, 4:717, 4:718 classification, 4:702 climate change and, 3:792 cyclicity, 4:713 definition, 4:699, 4:709, 4:717 drivers, 4:717 physical, 4:699–700, 4:700, 4:709–716, 4:713–715 ecological impact, 4:699–708 case studies, 4:702 management implications, 4:707–708 equatorial symmetry, 4:714 history, 4:709–710 mechanisms underlying, 4:699–702 observations, 4:710–713 prediction, 4:707 responses, 4:717 smooth transitions, 4:702 sustaining factors ecological, 4:700–702 physical, 4:699–700 Regional institutional frameworks, marine policy, 3:667, 3:668T Regional models, 4:722–731, 4:722T baroclinical circulation, Southern Caribbean Sea, 4:727–729, 4:729F boundary conditions, 4:727 case studies, 4:727 Mid-Atlantic Bight, 4:727 Southern Caribbean Sea, 4:727–729, 4:729F West Florida Shelf, 4:729–730, 4:730F circulation, plankton, 4:726, 4:726F coupled models ecological/physical process, 4:722T food web and water circulation model, 4:723–724, 4:724F ecological, 4:722 future prospects, 4:731 hierarchies, 4:725–727 N-P-Z (nutrient–phytoplankton–zooplankton) models, 4:722, 4:724F, 4:725, 4:731 see also Nutrient–phytoplankton–zooplankton (NPZ) models plankton competition, 4:722 time-dependent distributions temperature/salinity, 4:723
wind and bottom friction stresses, 4:723 sources of updates for ecological models, 4:731 see also Forward numerical models; Inverse models/modeling; Lagrangian biological models Regions of freshwater influence (ROFI), mixing and front creation, 5:392, 5:392F Relative humidity (RH), definition, 2:325T Relative sea level, isostatic contribution, 3:53 Relative tide range (RTR), 1:305, 1:311 tide-dominated beaches, 1:313 wave-dominated beaches, 1:312F Relative variability of flow Agulhas Current, 4:118F definition, 4:117–118 Relict deposits, 4:182–183 Relict margins, 4:141 Remineralization, 4:680 importance of spatial separation from photosynthesis, 4:680 occurrence in deep and surface waters, 4:680 of rare earth elements, 4:661, 4:662T, 4:664 see also Nutrient(s) Remingtonocetidae, 3:592 see also Cetaceans Remote environmental measuring units (REMUS), 6:370 Remotely operated vehicles (ROVs), 3:511–512, 4:630, 4:742–747, 6:257–260, 6:261F advantages and disadvantages, 6:259–260 archaeology (maritime), 3:699, 3:700F basic design characteristics, 4:742 common designs, 4:742 buoyancy, 4:742 challenges and solutions, 4:745 corrosion-resistant materials, 4:745 electrical components, 4:745 extreme operating environment, 4:745 human operators, 4:745 pressure-compensated housings, 4:745 pressure-proof housings, 4:745 surface components on deck, 4:745 components, 4:742 control, 4:743 computer control, 4:743, 4:744–745 hardwire control, 4:743, 4:744–745 deep submergence science studies, 2:22, 2:24F, 2:26F, 2:27F depth sensors, 4:743 description, 4:742 development, 4:742 flyaway mode, 6:259 frame, 4:742 future improvement efficiency, 4:745 intervention technology, 4:746–747
(c) 2011 Elsevier Inc. All Rights Reserved.
Jason see Jason remotely operated vessel (ROV) Kaiko (Japanese ROV), 3:508 manipulators, 4:743 operated by Scripps Institute of Oceanography, 2:24–26, 2:29F operated by UNOLS NDSF, 2:22–23, 2:27F in particle imaging, 4:250 portable design, 4:745 propulsion, 4:742 scanning sonars, 4:743 scientific research see Scientific research vehicles seafloor diffuse flow mapping, 1:72 sensors, 4:743 shallow-water manned submersibles replaced by, 3:517 size range, 4:742 support ships, 6:259 survey and discovery methods, hydrothermal vent fluids, chemistry of, 3:164–166 tether management see Tether management system (TMS) types, 4:742 see also Towed vehicles video cameras, 4:743 vision, 4:742–743 zooplankton sampling, 6:369, 6:370F see also Manned submersibles (deep water); Manned submersibles (shallow water) Remote repair, moorings, 3:926 Remote sensing acoustics in marine sediments see Acoustic remote sensing aircraft for see Aircraft for remote sensing chlorophyll, 5:396 fluorescence, 2:587 iron fertilization experiments, 3:336 salinity see Salinity, satellite remote sensing satellite see Satellite remote sensing single point current meters, 5:429F, 5:433 validation, application of transmissometry and nephelometry, 6:117T see also Satellite remote sensing Remote-sensing reflectance, 3:246, 5:115 definition, 4:623 Hydrolight simulation, 4:628, 4:628F Remote sensing theory, 5:127–128 REMUS (remote environmental measuring units), 6:370 REMUS (Remote Environmental Monitoring Unit S), 6:262, 6:263T Renard, A, 3:488–489 Representer method, control theory, in data assimilation, 2:7, 2:11 Reproduction Alcidae (auks) see Alcidae (auks) balaenopterids (rorquals), 1:284 baleen whales (Mysticeti), 1:284
Index benthic organisms see Benthic organisms bowhead whale (Balaena mysticetus), 1:284 Brachyramphus, 1:174 cephalopods, 1:527 Cerorhinca, 1:174–175 coccolithophores, 1:609–610 cold-water coral reefs see Cold-water coral reefs copepod(s) see Copepod(s) corals, 4:338 deep-sea fish see Deep-sea fish(es) demersal fish see Demersal fish(es) eels (Anguilla), 2:208 fish see Fish reproduction leatherback turtle (Dermochelys coriacea), 5:215 marine mammals see Marine mammals planktonic foraminifera see Planktonic foraminifera radiolarians, 4:616 sea otter (Lutrinae), 5:195–196, 5:198, 5:198F, 5:200–201 sea turtles see Sea turtles see also Life histories (and reproduction); specific organisms/species Research stations, rigs and offshore structures, 4:752 Research submersibles, history, 3:123 Research vehicles, scientific see Scientific research vehicles Research vessels geophysical see Geophysical research vessels oceanographic see Oceanographic research vessels polar see Polar research vessels Reserves see Marine protected areas (MPAs) Residence time, 3:455 definition, 2:303, 3:456 nutrients, 4:685 Resistance thermometer psychrometer, 5:378 Resistance wires, heat flux measurement, 5:387 Resistivity, deep-sea-floor microelectrode results, 4:489, 4:490F Resonant focusing, 6:302 Resource management, bathymetric maps and, 1:297 Resource partitioning coral reef fishes, 1:658 seabirds see Seabird(s) Resource rents, fishery management, 3:674 Resources fishery see Fishery resources; Global state of marine fishery resources mineral see Mineral resources natural, policy, marine policy overlap, 3:664T ocean resource use see Ocean resource use
sovereignty over, see also Law of the Sea Response time, absorptiometric chemical sensors, 1:10–11 Restonguet Creek, Uk, enrichment factor, 3:772–773, 3:773T Restoration programs see Fishery stock manipulation Restratification deep convection, 2:17–19 eddy mixing, 2:17, 2:18–19 numerical model, 2:18–19 observations, 2:17–18, 2:19, 2:19F, 2:20F see also Stratification Reverberation, 1:105–107, 1:115–116 sea ice, 1:97 Reversible reactions, in chemical sensors, 1:10–11 Revised analog method (RAM), 2:110 Reykjanes Ridge, 3:852 Reynolds, Osborne, 2:579, 5:455–456 Reynolds decomposition, 2:289, 4:209–210 eddy correlation and, 2:292 Reynolds flux, under-ice boundary layer, 6:157–158 Reynolds number, 1:328, 3:202, 3:372, 5:134 calculation, 5:488–489 in determining importance of viscous forces to plankton, 5:488 differential diffusion and, 2:117–118 entrainment velocity and, 3:373 island wakes, 3:343, 3:344F Langmuir circulation, velocity and, 3:408 mixing efficiency as function of, 3:375–376, 3:376F ocean models, 5:137 for plankton, 5:489 surface, gravity and capillary waves, 5:573 swimming speeds of various animals, 5:489T topographic eddies, 6:58 turbulence, 6:20, 6:20–21 turbulent gas diffusion, 1:148 see also Shear instability; Turbulence Reynolds stress(es), 2:1, 4:723, 6:156–157, 6:156F, 6:158 Rhenium (Re), 3:776, 3:779, 3:783 anoxic sea water, 3:779 concentrations in ocean waters, 6:101T depth profile, 3:777F, 3:779 oxic sea water, 3:779 Rheology sea ice, 5:163–164, 5:164F, 5:166 sediment flows, 5:449T, 5:455, 5:458F Rhine, River dissolve inorganic phosphorus, 2:316F eutrophication, 2:308T Rhine estuary, The Netherlands, 4:756–757 dissolved loads, 4:759T enrichment factor, 3:773T
(c) 2011 Elsevier Inc. All Rights Reserved.
587
Rhine outflow, tidal mixing, 5:392F Rhizosolenia, mats, 3:651–653 Rhizosolenia borealis, 2:552F Rhizosolenia castrecaniae, 3:653 Rhizostomae medusas, 3:10 Rhodain Sailor, 4:770F Rhodes cyclonic gyre, 3:718–720, 3:719F, 3:720T Rhodium (Rh), 4:494 commercial demand/utilization, 4:502, 4:502F concentrations deep earth, 4:494T sea water, 4:494T, 4:496 vertical profile in sea water, 4:496, 4:496F see also Platinum group elements (PGEs) Rhodochrosite, 1:545 Rhodophyta spp. (red algae), 4:427 Rhyolitic glass, diagenetic reactions, 1:266T Ri, definition, 6:242 Richardson, L F, energy cascade, 6:19, 6:20 Richardson number, 2:579, 3:199–200, 3:372, 3:450F, 3:452F, 6:189, 6:192 entrainment velocity and, 2:115, 2:115F, 3:371, 3:373F stratification and, 3:374–375 under-ice boundary layer, 6:158–159 Richter rolls, 5:297–299 Ridge(s) deep-sea, microbiology see Deep-sea ridges, microbiology fast-spreading see Fast-spreading ridges intermediate-spreading, hydrothermal vent deposits, 3:145 mid-ocean see Mid-ocean ridge(s) (MOR) slow spreading see Slow-spreading ridges submarine see Submarine ridges Ridge axis discontinuity (RAD), 3:852–853, 3:855T, 3:856F, 3:864 higher-order (third-, fourth order), 3:854, 3:860–861 overlapping spreading center (OSC) (second order), 3:853F, 3:854 seismic structure, 3:827, 3:829F, 3:830, 3:832 transform faults (first order), 3:853F, 3:854, 3:864 Ridge transform intersection, 3:864F Riftia pachyptila, 3:133F, 3:136F anatomy, 3:133–134, 3:152–153, 3:152F, 3:153, 3:160–161, 3:160F, 3:161F blood circulation, 3:160–161, 3:161F carbon dioxide transport, 3:161, 3:161F chemosynthetic pathways, 3:160F ecophysiology, 3:160–162 endosymbiotic bacteria, 2:76, 3:133–134, 3:152–153 as a food source, 3:136–138
588
Index
Riftia pachyptila (continued) as a gastropod habitat, 3:135, 3:136F, 3:138F growth rates, 3:141–142, 3:141F, 3:142F, 3:154–155 habitat, 3:134–135, 3:135F, 3:152–153 microhabitat, 3:161–162, 3:161F hemoglobin, 3:153, 3:160–161 hydrogen sulfide detoxification, 3:161, 3:162 transport, 3:161, 3:161F metabolic requirements, 3:153 oxygen transport, 3:161, 3:161F respiratory plume, 3:160–161, 3:161–162 symbiotic bacteria, 3:161 trophosome, 3:160–161, 3:161 Venture Hydrothermal Field, 3:154–155 see also Vestimentiferan tubeworms Rifts doomed, 4:597, 4:599F failed, 4:597, 4:598F propagating see Propagating rifts and microplates Rift valley, mid-ocean ridge tectonics, volcanism and geomorphology, 3:852, 3:853F Right whale dolphins (Lissodelphis spp.), 2:153, 2:156 Right whales (balaenids), 1:276, 1:277T, 3:594 filter-feeding apparatus, 1:278F growth and reproduction, 1:284 habitat, 1:279 lateral profile, 1:278F sound production, 1:282–283 trophic level, 3:623F see also Baleen whales; specific species Rigs and offshore structures, 4:748–753 environmental issues, 4:749–750 drilling muds, 4:750 Gulf of Mexico (GOM) crustacean fishery, 4:750 net fisheries, 4:750 offshore structures, 4:749–750 ‘produced waters’, 4:750 relations with fishermen, 4:750 history, 4:748–749 Gulf of Mexico (GOM), 4:748–749, 4:751, 4:752T North Sea offshore structures, 4:749 variety of shapes and sizes, 4:749, 4:749F world distribution, 4:748, 4:748F removal, 4:751–752 Brent Spar incident, 4:751 decommissioning, 4:751 legal requirements, 4:751 ocean dumping, 4:751 technology for, 4:752 research, 4:752 current patterns, 4:752 ecological investigations, 4:752 hurricane predictions, 4:752
research stations, 4:752 ‘rigs to reefs’ program see ‘Rigs to reefs’ program ‘Rigs to reefs’ program, 4:748, 4:750–751, 4:751 artificial reefs, 4:750–751 fish densities, 4:751 fish species composition, 4:751 see also Demersal fish(es); Pelagic fish(es) hook and line fishery, 4:750–751 safe haven for fish species, 4:750 Rim Current, Black Sea, 1:404–407 Rimicaris exoculata (shrimp) deep-sea ridges, microbiology, epibonts, 2:76–77 hydrothermal vent ecology, swarming, 3:153F Ring nets, 5:470 fishing methods/gears, 5:470 Rio Declaration, 3:433 Rio Grande Rise, salinity distribution, 1:24F, 1:26 Rips, 6:313–314 Intra-Americas Sea (IAS), 3:293 Riser drilling, 2:39, 2:40F Riserless drilling system see Nonriser drilling Risk, exploited fish, population dynamics, 2:184 Rissaga, 5:344, 5:349, 5:350 Rissa tridactyla see Kittiwake (Rissa tridactyla) Risso’s dolphin (Grampus griseus), 2:149–153 River(s) anthropogenic loading, 3:398F Black Sea, 1:211, 1:402 carbon transport, 3:399F chemical flux to oceans, 3:394 flow, tritium, 6:120 inputs see River inputs metal pollution, 3:769–770 nitrogen transport, 1:257, 3:399F ocean margin sediments and, 4:141 outflow, coral-based paleoclimate research, 4:339T, 4:341 phosphorus transport, 3:399F runoff see River runoff salinity and, 5:391 sediment transport, 4:141–142 sewage, potential risk to humans, 6:273T trace element transport, 1:254–255, 1:254T uranium-thorium series isotope transport, 6:244–245 water see River water water composition, 3:395T see also individual rivers River dolphins, 2:156, 2:159 trophic level, 3:623F see also Odontocetes (toothed whales) River Ems, eutrophication, 2:308T River inputs, 4:754–761 clay minerals, 1:627
(c) 2011 Elsevier Inc. All Rights Reserved.
conservative element concentrations in sea water and, 1:627–628 dissolved silicate, 3:680–681, 3:680F, 3:681T dissolved solid load vs. basin area, 4:758F floods, impact of, 4:754, 4:755 fluvial discharge, 4:754–755 dissolved solid discharge, 4:756–757 freshwater discharge, 4:754–755 to global ocean, 4:757–758 sediment discharge, 4:755–756, 4:756F see also Habitat modification fluvial processes, changes in anthropogenic sources, 4:758–760 natural sources, 4:758–760 North Sea, 4:73–76 phosphorus, 4:403–406, 4:404T human impacts, 4:406 rare earth elements (REEs), 4:659, 4:662T uneven global database, 4:754 River outflow, coral-based paleoclimate research, 4:339T, 4:341 River Rhine see Rhine, River River runoff Baltic Sea circulation, 1:288, 1:290–291 cosmogenic radioisotopes and, 1:679 River surges, 4:59 River water anthropogenic impacts on composition, 1:627–628 composition, 3:395T major constituents, 1:627, 1:627T ratios, sea water vs., 1:627, 1:627T RMS velocity see Root mean square (RMS) velocity RMT (rectangular mouth opening trawl), 6:357T, 6:364, 6:365F Robotic arms, human-operated vehicles (HOV), 6:255–257 Rock(s) composition, seismic velocity and, 5:363 definition, 5:464–465 magnetization, 3:481–482 natural remanent magnetization, 3:26 porosity, seismic velocity and, 5:364 types, 3:33 Rockall Trough, nephelometric profile, 4:10F Rock fall, 5:450 Rockhopper penguin, 5:522T, 5:524–525 see also Eudyptes (crested penguins) Rock shag behavioral displays, 4:377F see also Shag(s) Rock slide, 5:450 see also Mass transport Rock sole, population density, body size and, 4:704 Rocky coasts geomorphology, 3:36 erosion, 3:36 plunging cliffs, 3:36, 3:36F shore platform formation, 3:36
Index shore platforms, 3:36, 3:36F wave energy, 3:36, 3:36F rock types, 3:33 Rocky shores, 4:762–769 contrasted with sandy beaches, 4:762 energy flow models, 4:766–767 advantages, 4:767 criticisms, 4:766–767 features revealed consumption of macroalgae, 4:767 feeding of intertidal grazers, 4:767 overlooked elements, 4:767 history of research, 4:762 human impacts, 4:768–769 compared to other species, 4:768–769 control requirements, 4:769 harvesting, 4:768 influencing factors, 4:769 resilience, 4:768 types, 4:768 integration of approaches, 4:767–768, 4:767F identifying best model, 4:767–768 interactions of factors, 4:768 physical/biological controls, 4:765 productivity, 4:766 community dynamics, 4:766 negative effects, 4:766 nutrient/productivity models, 4:765F, 4:766 research potential, 4:762 settlement of larvae/spores, 4:762–763 setting zonation limits, 4:762 settlement rate, 4:763 site selection, 4:762–763 negative cues, 4:763 positive cues, 4:763 wave action, 4:765–766, 4:765F benefits, 4:766 influence on distribution, 4:765–766 variation, 4:766 zonation, 4:762 influencing factors, 4:762 patterns, 4:762 zonation controls, 4:763–765 indirect influences, 4:764–765 limpets-algae, 4:763 lower limits, 4:763 physical, 4:763 adaptations, 4:763, 4:764F mobile species, 4:763 nonmobile species, 4:763 upper limits, 4:763 role of predators, 4:763–764 keystone predators, 4:764 Scottish barnacles, 4:763 upshore gradient, 4:764 see also Beach(es); Coastal circulation models; Coastal trapped waves; Phytobenthos; Sandy beach biology; Tide(s); Upwelling ecosystems; Waves on beaches Rodeo Lagoon, 3:405F RO desalinator, 6:302 Rod stirring, 3:372, 3:373F
ROFI (regions of freshwater influence), 5:392, 5:392F Rogue waves, 4:770–780 abnormal, 4:774, 4:777 definition, 4:770–771, 4:771 dynamics, 4:771–772 energy, 4:772 field measurements, 4:776–777 Draupner platform, 4:777–778 Frigg oil field, 4:777 satellite and radar, 4:778 generation mechanisms, 4:772 dispersive focusing, 4:772–773 nonlinear focusing, 4:773 spatial focusing, 4:772 superposition, 4:772 models, 4:774, 4:775F, 4:778 simulation, 4:778, 4:779F shape, 4:775–776, 4:776F statistics, 4:773–774 Gaussian distribution, 4:773–774, 4:774F probability density function (PDF), 4:773–774, 4:774F single point extremes, 4:774 space–time extremes, 4:774–775 Webull distribution, 4:774 supercarriers lost, 4:770F wave height distribution, 4:770–771 wave tank experiments, 4:776 Rollers, 6:313 Roll-on/roll-off ships (RoRo), 5:404 Rollup, 6:18–19, 6:19F Romanche Fracture Zone, 2:123, 2:565F, 2:566, 2:568F mixing, 2:570 potential temperature variation, 2:568F Romanche transform fault, 3:841F Romania, Black Sea coast, 1:211, 1:401 Roman wreck investigation, Cousteau, Jacques, 3:696 Ronne Ice Front, 5:547–548 Ronne Ice Shelf, 3:215, 5:547 climate change, effects of, 5:550 iceberg, satellite imagery, 3:185F overflows, 4:270–271 temperature and salinity trajectories, 5:545F Rooth, Claes, 4:645 Root mean square (RMS) velocity, 6:316 Ropes, wire, in moorings, 3:919–920 ROPOS ROV, 4:746T, 6:260T Rorquals see Balaenopterids (rorquals) ROS see Reactive oxygen species Rossby deformation scale, 3:766 Rossby number, 2:565, 3:199 island wakes, 3:344 topographic eddies, 6:59 Rossby radius, 5:134, 6:214 Rossby radius of deformation, 3:763, 4:784–785 tides, 6:36–37 Rossby similarity drag law, 3:201 Rossby waves, 2:243–244, 2:271, 2:276F, 2:282F, 2:283F, 4:715, 4:781–789
(c) 2011 Elsevier Inc. All Rights Reserved.
589
Antarctic Circumpolar Current (ACC), 4:788 background ocean flows, 4:788 baroclinic conservation of potential vorticity, 4:782, 4:782F definition, 4:781 propagation, 4:782, 4:782F, 4:783, 4:783F, 4:784F satellite observations, 4:783 speed, 4:781, 4:781F, 4:783, 4:784F, 4:788, 4:788F barotropic conservation of absolute vorticity, 4:781–782, 4:782F definition, 4:781 observation difficulties, 4:783 propagation, 4:781–782, 4:782F boundary reflection, 2:278–279 Coriolis parameter, 4:781–782, 4:784–785 deep convection, 2:20–21 definition, 2:195 delayed oscillator ENSO model and, 2:282 dissipative, 4:788 East Australian Current, 2:187–189, 2:191–192 effects of, 4:781 generation mechanisms, 4:782–783 geostrophic flow, 4:782, 4:783F Indonesian Throughflow and, 3:243 large amplitude, 4:788 mesoscale eddies, 3:762F, 3:763, 3:764F observations, 4:783–784 Hovmo¨ller diagram see Hovmo¨ller diagram Radon transform, 4:783 sea surface height (SSH), 4:783, 4:784F sea surface temperature (SST), 4:783–784 TOPEX/Poseidon, 4:783, 4:784F wave speed, 4:781, 4:781F, 4:783, 4:784F, 4:788, 4:788F propagation, 4:782, 4:783F Hovmo¨ller diagram see Hovmo¨ller diagram orientation, 4:781–782, 4:782F, 4:783, 4:783F, 4:784F, 4:785, 4:787–788 solitons, 4:788 solution, 2:275–276 speed, 4:781, 4:781F, 4:783, 4:784F, 4:788, 4:788–789, 4:788F theory, 4:784–786 horizontal variation, 4:784–786, 4:787 dispersion, 4:784–785, 4:785–786, 4:786F propagation, 4:784–785 Rossby radius, 4:784–785 improvements to, 4:789 normal mode theory, definition, 4:784 observed wave speed, comparison with, 4:781F, 4:788–789, 4:788F
590
Index
Rossby waves (continued) ocean spinup see Ocean spinup vertical variation, 4:784, 4:787–788 baroclinic mode, 4:786–787, 4:787, 4:787F barotropic mode, 4:786–787 topographic, 4:788 transit time, 2:273 vorticity see Vorticity wave dynamics, 2:275 waveguides, 4:781–782, 4:788 wind stress, response to, 4:787, 4:787F, 4:788 see also Coastal trapped waves; Ekman pumping; Ekman transport; Internal wave(s); Mesoscale eddies; Wind-driven circulation Ross Ice Shelf, 5:541, 5:547 Ross Sea biogenic silica studies, 3:683 seabird responses to climate change, 5:261, 5:262F sea ice cover, 5:146–147, 5:148 shelf water, contact with ice shelves, 1:417–418 Rosy Dory (Cyttopsis rosea), 2:483, 2:483F Rotary Core Barrel (RCB), 2:40, 2:41F, 2:52 Rotating gravity currents, 4:790–795 bottom currents see Bottom currents climate, 4:795 coastal currents see Coastal currents Coriolis force, 4:794 definition, 4:790 eddies, 4:791F, 4:795 intermediate timescale currents, 4:790–791 large-scale currents, 4:791 observations, 4:791–794, 4:794–795 rapid currents, 4:790 rotating hydraulics theory, 4:794–795 salinity-driven exchange flow, 4:792–793 shelf waves, 4:794F, 4:795 sill-overflow systems, 4:791F, 4:793–794 source region, 4:790, 4:794 surface straits, 4:791F, 4:792–793 theory, 4:794–795 rotating hydraulics, 4:794–795 timescale, 4:794, 4:795 velocity scale, 4:794, 4:795 width scale, 4:794, 4:795 turbidity currents see Turbidity currents turbulent boundary layers, 4:795 see also Cascades; Deep convection; Non-rotating gravity currents; Open ocean convection; Overflows Rotating hydraulics theory, rotating gravity currents, 4:794–795 Rotational slide see Slumps Rottnest Island, 3:445–446 Rough-toothed dolphin (Steno bredanensis), 2:157 Roundnose grenadier (Coryphaenoides rupestris), 4:226
distribution, 4:226 open ocean demersal fisheries, 4:227–228, 4:228F FAO statistical areas, 4:227–228, 4:231T overexploitation, 4:227–228 Total Allowable Catch, 4:227–228 ROV see Remotely operated vehicles (ROVs) ROVER benthic flux lander, 4:488–489, 4:492F, 4:493 Royal albatross (Diomedea epomophora), 4:590 see also Albatrosses Royal penguin, 5:522T, 5:524–525, 5:525 see also Eudyptes (crested penguins) rRNA, fluorescent tagging, 2:583 RR rays (refracted-refracted rays), 6:42 RSPGIW (Red Sea-Persian Gulf Intermediate Water), temperaturesalinity characteristics, 6:294T, 6:298, 6:298F RSR rays (refracted-surface-reflected rays), 6:42 RTR see Relative tide range (RTR) Rule, Margaret, Mary Rose recovery, 3:697 Runup height, tsunamis, 6:127–128 Russell Cycle, 4:713 Russia Arctic research, 1:92–93 Black Sea coast, 1:211, 1:401 Pacific salmon fisheries, catch, 5:14F, 5:15F, 5:17F, 5:19F, 5:20F, 5:21F Salmo salar (Atlantic salmon) fisheries, 5:1–2, 5:2T Russian Cosmos satellite, 5:81 Ruthenium (Ru), 4:494 concentrations deep earth, 4:494T sea water, 4:494T water column distribution, 4:495–496 see also Platinum group elements (PGEs) R/V Atlantis, support ship, 2:24F, 2:27F Rynchopidae (skimmers), 3:420–431, 3:420 breeding ecology and behavior, 3:420, 3:425, 3:429 chick-rearing, 3:429 clutch-size, 3:425–426, 3:429 egg incubation, 3:425–426, 3:429 phenology, 3:426 range, 3:422T climate change responses, 5:259 conservation, 3:430–431 measures, 3:431 status, 3:430, 3:430T distribution, 3:420, 3:421, 3:422T, 3:425 exploitation, 3:430–431 foraging, 3:429–430 habitats, 3:424, 3:425 nesting, 3:425 oil pollution, 4:193 physical appearance, 3:422–424, 3:423F, 3:424
(c) 2011 Elsevier Inc. All Rights Reserved.
plumage, 3:424 sexual dimorphism, 3:422–424 species, 3:421, 3:422T taxonomy, 3:420, 3:420–421 threats, 3:430–431 of world, 3:422T see also Seabird(s) Rynchops niger (black skimmer), 3:423F Ryther, John H., 4:19–20, 6:227–228
S Saber-toothed blenny (Aspridonotus taeniatus), 2:377 Saccopharynx spp., 4:6F SACLANTCEN, geoacoustic properties of seafloor sediments, measurement of, 1:81 sediment cores, 1:81, 1:82F Sacrificial electrodes, 2:252 SACW see South Atlantic Central Water (SACW) Saduria entomon, eutrophication, 2:313 SAF see SubAntarctic Front (SAF) SAFARI, acoustics in marine sediments, 1:90, 1:90F Safety of Life at Sea (SOLAS), 5:405 SAFIRE optical system, 3:249F see also Ocean optics Sahara, desertification, 1:5 Saharan dust, phosphate, removal proposal, 1:123–124 SAHFOS see Sir Alister Hardy Foundation for Ocean Science (SAHFOS) Sail, definition, 3:190 Sailfish (Istiophorus platypterus), utilization, 4:240 St. Lawrence Island dissolved loads, 4:759T polynya, 4:542 polynyas, 4:542F, 4:543–544 St Anna Trough, Atlantic water, 1:215 St Lawrence, Gulf see Gulf of St. Lawrence St Lawrence River, 1:2–3 Saithe (Pollachius virens), open ocean demersal fisheries, 4:228 Saline contraction coefficient, 4:25 Salinity, 1:348–349, 4:263–264 Alaska Coastal Current, 1:457F, 1:459 Antarctic Circumpolar Current (ACC), 1:737F, 4:127 Antarctic Intermediate Water (AAIW), 1:23F, 1:24F, 1:25–26 aquarium fish mariculture, 3:526 Wiedermann–Kramer saltwater formula, 3:527T Arctic Ocean, mixed layer, 1:211 Baltic Sea circulation see Baltic Sea circulation Benguela Current, 1:322F, 1:324 Brazil and Falklands (Malvinas) Currents, 1:422, 1:423F, 1:427
Index potential temperature–salinity diagram, 1:422, 1:424F salt transport, 1:427–428 Brazil/Malvinas confluence (BMC), 1:423F, 1:424F, 1:426F Cape Cod tidal front, 5:397F chlorinity and, 1:626, 2:249 coastal lagoons, 3:377 composition and, 4:30 conservative nature, 1:711 coupled sea ice-ocean models, 1:691 decrease over time, 4:264 deep convection, 2:13–15, 2:14F, 2:16–17, 2:17, 2:18F definition, 5:127–128, 6:163 based on conductivity, 2:247, 2:249–251, 2:249F determination, 1:626 diffusivity relative to temperature, 2:114 salt fingers and, 2:165–166 see also Differential diffusion; Double diffusion direct numerical simulation (DNS), 2:115–116 distribution, 2:13–15, 2:14F effects on demersal fisheries, 2:93–94 effects on fish larvae, 2:387 effects on salt marsh vegetation, 5:39–40 exchange flow, salinity driven, 4:792–793 fluid packets and, 5:136 global mean surface, 5:127, 5:128F Gulf Stream System, 2:558F hurricane Frances, 6:207F hydrothermal plume spreading level, 2:132, 2:133F Indian Ocean, 6:183F influence on fish distribution, 2:370 Intertropical Convergence Zone (ITCZ), 6:170 Intra-Americas Sea (IAS) salt balance, 3:290 intrusions see Intrusions Labrador Current (LC), 2:562 Labrador Sea see Labrador Sea measurement(s), 1:626, 4:125, 5:127–128 airborne, 5:129 all-weather observations, 5:128, 5:131 automated electronic in situ, 5:127 CTD profiler resolution, 1:713 Practical Salinity Scale (PSS-78), 5:127 practical salinity units (psu), 5:127 radio frequency, 5:128 remote sensing see Salinity, satellite remote sensing titration, 1:711–712 measuring devices, 1:711–713 Mediterranean Sea, 1:23F, 1:25–26, 4:125 Mediterranean Sea circulation, 3:714, 3:715F, 3:716–717, 3:724
preconditioning, 3:712–714, 3:716–717, 3:724 mid-ocean elevation, 5:128F mixed layer depth and, 6:219–220 molybdenum concentration and, 6:78 monsoons and, 6:170 normal (standard), 1:626 North Atlantic Deep Water (NADW), 4:127, 4:131 North Pacific Intermediate Water (NPIW), 1:23F, 1:25–26 Okhotsk Sea, 4:204, 4:204F, 4:205 open ocean convection, 4:220 d18O values and, 1:504–505, 1:505F practical, 6:379 in primitive equation models, forward numerical, 2:609 profiles Amundsen Basin, 1:213F, 1:214F, 1:217F Arctic Ocean, 1:213F, 2:120F Atlantic Ocean, 3:458F Atlantic Ocean, WOCE section 16, 3:301F Black Sea, 1:216F, 1:217F, 1:405F, 1:406F Gulf of Mexico (GOM), 6:196F Juan de Fuca Ridge, 2:132, 2:133F Loop Current (LC), 6:196F Nansen Basin, 1:213F, 1:214F, 1:217F Southern Ocean, 1:180F ranges, 5:127, 6:163, 6:381F seawater, 6:381F Red Sea, 5:127 Red Sea circulation, 4:666, 4:667, 4:669F, 4:670, 4:672–673, 4:675, 4:675T Rio Grande Rise, 1:24F, 1:26 satellite remote sensing, 5:127–132, 5:127, 5:128, 5:129 history of, 5:129 requirements, 5:129–130 resolution and error sources, 5:130 science requirements, 5:130 scientific issues, 5:129–130 scalar mixing see Scalar mixing sea level effects, 5:181 Southeast Asian seas, 5:309–311, 5:310–311, 5:312F Strait of Bab El Mandeb, 4:667, 4:669F theory, 5:127–128 T-S characteristics see Temperature–salinity (TS) characteristics Tyrrhenian Sea, 1:712F upper ocean, 6:184 global distribution, 6:170–171 variability, 2:16–17, 2:17, 2:18F water-column stability and, 6:163 water-column temperature inversion and, 6:222 wind driven circulation, 6:346–347 see also Freshwater flux; Temperature–salinity characteristics Salinity, temperature, depth (STD) profiler, 1:713
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591
Salinity effect (P/E), 2:102 Salinometers, 1:712 calibration, 1:713F laboratory-based, 1:712 microwave see Microwave salinometers ocean-going, 1:713 Salmon importance of Alaska Gyre coastal currents, 1:459 population, regime shifts, 4:702–703 see also Salmonids Salmon fisheries Atlantic see Atlantic salmon (Salmo salar) fisheries Baltic Sea, 5:4 Pacific see Pacific salmon fisheries Salmonid farming, 5:23–28 aims, 5:27 charrs, 5:23 disease agents, 3:520T, 3:521 genetically modified, 5:25 global, 5:23–24 production, 5:23, 5:24, 5:24T harvesting, 5:27 historical aspects, 2:528–530, 5:23 mortality associated, 5:27 operation, 5:26–27 automatic feeding systems, 5:26 sea lice infestation control, 5:27 seawater rearing, 5:23–24, 5:24–25 cage systems, 5:25, 5:26–27 phytoplankton blooms, 5:26 predator protection, 5:26 site selection, 5:25–26 smolts, 5:24–25 selective breeding, stress response minimization, 3:521 stock enhancement/ocean ranching, 4:146, 4:146–149, 5:23, 5:27 goal, 4:149 historical aspects, 2:528–530 migration, 4:148 operation, 5:26 problems, 4:153 spawning, 4:148, 4:149 species, 4:147–148, 4:147T, 5:3 stress minimization, 3:521, 5:27 see also Atlantic salmon (Salmo salar) fisheries; Pacific salmon fisheries; specific species Salmonids, 5:29–38 anadromous/nonanadromous forms, 5:29 diet, 5:33–34 Atlantic/Pacific salmon, 5:33 Atlantic salmon postmolts, 5:33–34 masu salmon, 5:33 pink, chinook and coho salmon, 5:33 sockeye, pink and chum salmon, 5:33 distribution, 5:30 arctic charr, 5:32 Atlantic salmon, 5:30 chinook salmon, 5:32 chum salmon, 5:32 coho salmon, 5:32 masu salmon, 5:32
592
Index
Salmonids (continued) pink salmon, 5:31–32 sea trout, 5:30 sockeye salmon, 5:30–31 environmental factors, 5:35–36 sea surface temperature, 5:36–37 homing, 5:37–38 directed navigation, 5:37–38 life histories, 5:30T, 5:31T Atlantic salmon, 5:31F similarities/differences, 5:29–30 migration, 2:403, 5:32–33, 5:32, 5:33F, 5:34F, 5:35F, 5:36F Atlantic salmon, 5:33 food-dependency, 5:32 movement patterns, 5:32 offshore movement, 5:32 Pacific salmon, 5:33 variation in postmolt patterns, 5:32 ocean climate affecting, 5:37 Atlantic Ocean, 5:37 effects of variations, 5:37 factors affecting abundance, 5:37 Pacific Ocean, 5:37 origins, 5:29 debates, 5:29 evolution, 5:29 predation, 5:34–35 Atlantic salmon predators, 5:35 Pacific salmon predators, 5:34 rates of oceanic travel, 5:37T sea surface temperature Atlantic Ocean, 5:36, 5:38F Pacific Ocean, 5:36 river and ocean, 5:36, 5:36–37 sockeye salmon, 5:36 surface salinity, 5:35–36 effects, 5:35–36 taxonomy, 5:29 identifying features, 5:29 see also Fish feeding and foraging; Fish horizontal migration; Fish larvae; Salmon Salmon louse (Lepeophtheirus salmonis), 1:650 Salmon shark (Lamna ditropis), 2:474 Salmo salar (Atlantic salmon) see Atlantic salmon (Salmo salar) Salmo salar (Atlantic salmon) fisheries see Atlantic salmon (Salmo salar) fisheries Salpidae (salps), competition with krill, 3:356 Salt concentrations see Salinity Salt exposure, effect on humidity measurement, 5:378 Salt fingers, 2:162–166, 2:165F, 3:20 cell width, 2:162, 2:164 conditions necessary, 2:162 mixing efficiency, 2:164–165, 2:166F temperature and salinity, 2:164, 2:165F turbulence and, 2:164 Salt Finger Tracer Release Experiment (SFTRE), 2:163–164, 2:164F Salt marsh(es), 3:38, 4:254, 4:254T biodiversity, 2:141
experimental oil treatments, effects of, 4:195F oil pollution, 4:195 primary production, 4:254T Salt marsh(es) and mud flats, 5:43–48 functions, 5:45 geomorphology, 5:43 erosion, 5:43 flooding, 5:43 salinity, 5:43 sediments, 5:43 human modifications, 5:46–47 direct effects, 5:46–47 diking, 5:47 indirect effects, 5:47 exotic species, 5:47 sediment loading changes, 5:47 marsh restoration, 5:47–48 sediment loading changes decreases, 5:47 increases, 5:47 upland diking, 5:47 examples and effects, 5:47 nutrients/elements cycling, 5:45–46 denitrification, 5:45 nitrogen fixation, 5:45 nutrient levels, 5:45 phosphorous cycling, 5:46 sulfur cycling, 5:46 organisms, 5:43–45 algae, 5:44 bacteria, 5:44 birds, 5:45 fish, 5:44 higher vegetation, 5:43–44 higher vegetation spatiality, 5:44 invertebrates, 5:44 mammals, 5:45 pollution, 5:46 metals, 5:46 organic compound degradation, 5:46 pollutant accumulation, 5:46 pollutant storage, 5:46 production and nursery role, 5:45 fish exportation, 5:45 fish production, 5:45 plant production, 5:45 storm damage prevention, 5:46 dissipation of wave energy, 5:46 structure, 5:43, 5:44F elevation changes, 5:43 vegetation see Salt marsh vegetation see also Intertidal fish(es); Lagoon(s); Mangrove(s); Salt marsh vegetation; Tide(s) Salt marsh cord grass (Spartina alterniflora), 4:254, 5:40–41, 5:46–47, 5:47 Salt marsh vegetation, 5:39–42, 5:43–44, 5:43 adaptations to stress factors, 5:39 description and distribution, 5:39 factors controlling patterns, 5:39, 5:39–41, 5:40F competition, 5:41
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frequency/duration of flooding, 5:39–40 grazing by domestic animals, 5:41 hydrologic alterations, 5:41 natural/human disturbances, 5:41 soil salinity, 5:39–40 waterlogged/anaerobic soils, 5:40–41 patterns, 5:39 age of marsh, 5:39 high marsh, 5:39 low marsh, 5:39 zonation and dynamism, 5:41–42 see also Intertidal fish(es); Mangrove(s); Phytobenthos; Salt marsh(es) and mud flats; Sea level changes/ variations; Tide(s) Salt transport, 6:168–170 Salt wedge estuary, 4:253 Salty subtropical water (STW), 3:447, 3:449, 3:449F Salvage difficulties for maritime archaeology, 3:699–700 government, early maritime archaeology, 3:696 Salvelinus (charr), 5:29 salmonid farming, 5:23 Salvelinus alpinus (arctic charr), 5:32 Salween, dissolved loads, 4:759T Samoan Gap, 2:572 see also Straits Samoan Passage, 2:565F Sampling application of coastal circulation model, 1:578 deep-sea fauna, 2:59–60 grabs see Grabs for shelf benthic sampling macrobenthos, 3:471, 3:474, 3:475 meiobenthos, 3:728 mesocosms, 3:655 SAMW see SubAntarctic Mode Water (SAMW) Sanctions, illegal fishing, 2:524 Sanctuaries see Marine protected areas (MPAs) Sand acoustics in marine sediments, 1:82F, 1:83T, 1:90F extraction, see also Pollution solids geoacoustic properties, 1:116T gravel vs., 4:182 mining, 1:588, 1:588F inshore-sourced replenishment, 1:589 offshore see Offshore sand mining offshore-sourced replenishment, 1:588–589 see also Pollution solids supply, coastal topography see Coastal topography impacted by humans see also Sandy beach biology Sandalion, 4:770F Sand bars, waves on beaches, 6:314, 6:315 Sand dike, 5:454F, 5:463
Index Sand dunes see Dunes Sand eels (Ammodytidae), 2:379, 2:395–396F, 2:461 Sanders, Howard, 2:61 Sand hopper (Talitrus saltator), 5:53F, 5:56 San Diego, California, wave power conversion, 6:302–303 Sandpipers see Phalaropes Sandwip Island, Bangladesh, storm surges, 5:531F Sandy beach biology, 5:49–57 food economies, 5:53 carrion-based, 5:53 kelp-based, 5:53 phytoplankton-based, 5:53–54, 5:54F food relationships, 5:52–54, 5:54F imported food, 5:53 invisibility of biota, 5:49 longshore distribution, 5:50 scattering, 5:50 macrofauna adaptations, 5:54–55 behavior, 5:56 energy conservation, 5:55, 5:56F feeding methods, 5:55 locomotion, 5:54–55 burrowing, 5:54–55, 5:55F swash-riding, 5:55 nutrition, 5:55 sensory systems, 5:55–56 crustaceans, 5:56 maintenance of position, 5:55–56 macrofauna diversity/abundance, 5:51–52, 5:51F above tide-line, 5:52 beach morphodynamics, 5:51–52, 5:51F criteria, 5:51–52 nontypical/seasonal species, 5:52 surf zone effects, 5:52 variability, 5:52 meiofauna diversity/abundance, 5:50–51 beach slope and porosity, 5:50–51 description and diversity, 5:50 tidal migrations and zonation, 5:49–50 exploitation of food resources, 5:49 zonation of species, 5:49–50, 5:50F water movement, 5:49 mobility and burrowing, 5:49 see also Beach(es); Coastal topography impacted by humans; Intertidal fish(es); Ocean gyre ecosystems; Rocky shores; Storm surges; Tide(s); Waves on beaches Sandy coasts geomorphology, 3:37–38 dunes, 3:37–38 erosion, 3:37 geological timescales, 3:37–38 sediment storage, 3:37–38 see also Beach states rock types, 3:33 Sandy contourites, 2:85 Sandy sediments burrows, 1:398
submarine groundwater discharge (SGD), 5:554–555, 5:554F see also Sand; Sediment(s) San Francisco, water-column temperature inversions, 6:223–224 San Gabriel Canyon, 5:448F Sanitary plastics, sewage contamination, indicator/use, 6:274T San Pedro Sea Valley, 5:448F San Petro Shelf, DDT concentrations, depth profile, 1:558F Santa Barbara Channel, 5:451 Santa Monica Basin radiocarbon analysis, lipid biomarkers, 5:425–426 radiocarbon values, 5:421, 5:421F Santa Monica Canyon, 5:448F Santa Ynex, USA, sediment load/yield, 4:757T Sapropels, 4:315 SAR see Satellite remote sensing SAR; Synthetic aperture radar (SAR) Sardina (sardines), 4:366–367 Sardina pilchardus (pilchard), 2:375 Sardine fisheries, multispecies dynamics, 2:508, 2:509 Sardines (Sardina, Sardinops, Sardinella), 4:366–367, 4:366–368 anchoveta fisheries, 4:367–368 anchovy fisheries, 4:367–368 Benguela upwelling, population, 4:705–707 California, 4:700F catch time series, 4:701F description and life histories, 4:367 distribution, 4:366–367 fisheries history, 4:367 pilchard fisheries, 4:367–368 population, anchovy fishing and, 4:707 production, sea surface temperatures in North Pacific, 4:390F Sargasso Sea aphotic zone oxygen consumption, 6:94–95, 6:95F copper complexation, 6:104 helium-3 flux, 6:98 lead, 1:196, 1:199F mesoscale eddies, nutrient transport, 5:481, 5:483F production estimates, 6:100 productivity, 6:95–96 temporal variability of particle flux, 6:1, 6:3F timescales, 6:4, 6:5–6, 6:5F, 6:6–7, 6:6F, 6:7, 6:8F tritium, 6:121, 6:122F see also Bermuda; North Atlantic Sargassum fish (Histrio histrio), aquarium mariculture, 3:528 SAS (SeaWiFS Aircraft Simulator), 1:142 Sashimi market, Japan, 4:239, 4:240, 4:241 SASW (Subantarctic Surface Water), temperature-salinity characteristics, 6:294T
(c) 2011 Elsevier Inc. All Rights Reserved.
593
Satellite(s) aircraft for remote sensing advantages over, 1:138 altimetry measurements see Satellite altimetry infrared data, 5:88 laser altimetry, 5:84 measurements by see Satellite altimetry; Satellite measurements; Satellite remote sensing ocean color sensing, 5:117–118 passive-microwave instruments, 5:81–82 see also Satellite passive-microwave measurements of sea ice; Satellite remote sensing SAR polar-orbiting, sun-synchronous, 5:380 salinity observation, remote sensing see Salinity, satellite remote sensing sea surface image, 3:445F, 3:447, 3:448F sea surface temperatures (SST), 3:447, 3:451F, 5:129 see also Satellite remote sensing of sea surface temperatures Satellite altimetry, 1:301, 5:58–64 accuracy, 5:58, 5:63–64 dynamic sea surface topography, 5:59–61, 5:64 dedicated gravity field missions, 5:61 dynamic topography, 5:59–61 global geostrophic circulation, 5:59–61, 5:61F global sea level rise, 5:61 long global sea level time-series, 5:61 extraordinary gravity field information, 5:61 geoid and, 3:80–81, 3:81 data correction, 3:83 global sea level rise see Sea level changes/ variations; Sea level rise gravitational sea surface topography, 5:58–59, 5:64 geoid or equipotential surface, 5:58–59, 5:59F global maps of, 5:59, 5:60F gravity anomalies, 5:58–59, 5:60F maps of bottom topography, 5:59, 5:60F internal tidal mixing, 3:256–257 internal tide observation, 3:261–263, 3:264F limitations, 3:261–263, 3:263 measurement method, 5:58 observation accuracy, 5:58 Topex/Poseidon satellite altimeter system, 5:58, 5:59F measurements made by, 3:449, 3:451 operational ocean applications, 5:64 sea level data, 5:129–130 sea level variability see Sea level changes/ variations sea surface topography profiles, 5:58, 5:59F tomography and, 6:50 wave height and wind speed, 5:63–64 Satellite-borne sensors, 3:108
594
Index
Satellite imaging icebergs, 3:183, 3:184 rogue waves, 4:778 Satellite measurements, meteorological, 5:380–381 polar-orbiting, sun-synchronous satellites, 5:380 precipitation estimates, 5:380 solar radiation by radiative transfer models, 5:380 surface-measured SST for calibration, 5:380–381 surface wind speed, 5:380 see also Wind-driven circulation Voluntary Observing Ships (VOS), 5:380 see also Satellite remote sensing Satellite monitoring, oceanographic research vessels, 5:412 Satellite oceanography, 5:65–79 challenges ahead, 5:74 data policy, 5:74 in situ observations, 5:74 integrated observations, 5:74–75 international integration, 5:77 oceanographic institutional issue, 5:75–76 transition from research to operations, 5:75 first generation, 5:67–68 missions, 5:72T origins, 5:65–67 second generation, 5:68–69 third generation, 5:69 implementation, 5:71 space policy, 5:71–73 studies, 5:70 understanding and consensus, 5:71 joint missions, 5:73 mission launch dates, 5:71 new starts, 5:71 partnerships in implementation, 5:69–70 promotion and advocacy, 5:70 research strategy for the decade, 5:70 Satellite passive-microwave measurements of sea ice, 5:80–90, 5:80, 5:84, 5:85F, 5:87F, 5:88, 5:88F background, 5:80 rationale, 5:80 theory, 5:80–81 see also Satellite oceanography Satellite radar altimeters, 5:58 sea level spatial variation, 5:58 see also Satellite oceanography Satellite radiometers, 5:205 Satellite remote sensing, 5:78 active sensors, 5:78, 5:78F air temperature, 5:206–207, 5:207 applications, 5:208–210 coastal waters, 4:732–741 applications, 4:737–740 non-optical, 4:739–740 data sets, 5:124–126 data validation, data set intercomparison, 5:121
electromagnetic signals showing atmospheric transmittance, 5:76F fishing and, 4:739 fluxes, 5:202–211, 5:208F history, 5:65 humidity, 5:206–207 ocean color, 5:114–126 applications, 5:124–126 atmospheric correction, 5:119–120 bio-optical algorithms, 5:120, 5:121F methodology, 5:116–118 postlaunch sensor calibration stability, 5:118–119 product validation, 5:120–124 sensor calibration, 5:118–119 sensor design, 5:116–118 oceanic observation techniques, 5:77F partnership with oceanography, 5:69 passive sensors, 5:78, 5:78F salinity, 5:127–132 see also Salinity suspended sediments, 4:739 turbulent heat fluxes, 5:206–207 wind stress, 5:202–205 see also Satellite radiometers; Satellite scatterometers Satellite remote sensing of sea surface temperatures, 4:222, 5:91–102, 5:206, 5:210F accuracy, 5:94 advantages, 5:91 applications, 5:97–99 air–sea exchanges, 5:101 coral bleaching, 5:99 coral reefs, threatened, time-series SST predicting, 5:99 El Nin˜o see El Nin˜o frontal positions, 5:99, 5:100F ‘global thermometer’, 5:101 see also ‘Global thermometer’ hurricane intensification, 5:99 instabilities in Pacific Ocean, 5:99, 5:101F oceanographic features resolution, 5:97 storm prediction, 5:99 black-body calibration, 5:91, 5:94 characteristics, 5:93–94 coverage, 5:94 global, 5:94 limited to sea surface, 5:93–94 future developments, 5:101 Advanced ATSR, 5:102 atmospheric correction algorithms improvement, 5:101 infrared radiometers, 5:101 SST retrieval algorithm validation, 5:101 infrared atmospheric corrected algorithms, 5:91–93, 5:101 atmospheric aerosols, 5:93 AVHRR see Advanced Very High Resolution Radiometer (AVHRR) constant temperature deficit, 5:91–92 contamination by clouds, 5:93
(c) 2011 Elsevier Inc. All Rights Reserved.
longer wavelength window, 5:91–92, 5:92F Pathfinder SST (PSST), 5:92–93 radiative transfer linearized, 5:92 water vapor correction algorithm, 5:92, 5:92F measurement principle, 5:91–93 brightness temperature, 5:91 infrared atmospheric windows, 5:91, 5:92F microwave measurements, 5:93 radiation attenuation, 5:91 temperature deficit, 5:91 thermal emission from sea, 5:91 see also Electrical properties of sea water; Infrared (IR) radiometers; Penetrating shortwave radiation; Radiative transfer (oceanic) Mediterranean Sea, eastern, 3:720, 3:721F microwave measurements, 5:93 infrared radiometers vs, 5:93, 5:93T penetration depth, 5:93–94 spacecraft instruments see Spacecraft instruments temperature characteristic of ‘skin of the ocean’, 5:93–94 time-series of global SST, 5:102 see also Sea surface temperature (SST) Satellite remote sensing SAR, 5:103–113 data collecting, 5:106–112 definition, 5:103 detecting change on decadal timescales, 5:112–113 examples of ocean features from, 5:106–112 bottom topography in shallow water, 5:105F, 5:107 eddies, 5:107F, 5:108 see also Satellite remote sensing of sea surface temperatures fronts, 5:108–109, 5:108F, 5:109F see also Surface films important marine applications, 5:106–107 internal waves of tidal frequency, 5:110–111, 5:111F long surface waves or swell, 5:107F, 5:109–110, 5:110F polar lows, 5:106F, 5:107–108 sea ice edges, 5:109, 5:109F see also Ice–ocean interaction; Satellite passive-microwave measurements of sea ice surface ship wakes, 5:111–112, 5:112F tracking oil spills, 5:104F, 5:107 history major spaceborne SAR missions, 5:103, 5:104T shuttle imaging radar (SIR) experiments, 5:104 imaging mechanism of ocean features, 5:104–106 Bragg resonant wave back scattering, 5:104–105, 5:104T
Index frontal features change wind stress, 5:106 ocean currents and wind-driven surface waves, 5:105–106 oil slicks dampening effect, 5:104F, 5:106 mapping features in coastal regions, 5:103 monitoring changes in the marine environment, 5:112 weather forecasting for coastal regions, 5:112–113 see also Synthetic aperture radar (SAR) Satellite salinity observation, remote sensing see Salinity, satellite remote sensing Satellite scatterometers, 5:204T deployment, 5:203 Satellite-tracked drifters, 3:446–447, 3:446F, 3:447 see also Drifters; Float(s) Satellite tracking, drifters, 2:173 Saturation (of a dissolved gas) definition, 4:57 noble gases, 4:57 Saturation humidity, definition, 2:325T Savannah River Plant, 4:632 SAVE (South Atlantic Ventilation Experiment), 4:641–642 Savu Sea, 3:238–239 Savu Strait, 3:238–239 Saxipendium coronatum (spaghetti worm), 3:140–141, 3:141F SBL (short-baselinetracking systems), 4:478 Scalar irradiance, Hydrolight simulation, 4:627–628, 4:627F Scalar mixing, turbulence, 6:18, 6:18F, 6:19, 6:21 Batchelor wavenumber, 6:21 definition, 6:23 molecular diffusion, 6:21, 6:23 Prandtl number, 6:21 salinity, 6:21 scalar variance, 6:21, 6:21F temperature, 6:21 Scale deposition, time series, California sardine and northern anchovy, 4:700F Scaled petrel, 4:591F see also Procellariiformes (petrels) Scallops (Pectinidae) adaptations to resist shear stress, 1:332–333 mariculture, 3:904, 3:905F stock enhancement/ocean ranching, 2:528–530, 4:146 see also specific species Scampi, 6:255, 6:256T Scandium concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:692 depth profile, 4:693F properties in seawater, 4:688T Scanfish towed vehicle, 6:65, 6:69
Scanning low frequency microwave radiometer (SLFMR), 5:129 Scanning multichannel microwave radiometer (SMMR), 2:329, 5:80, 5:81–82, 5:83, 5:84, 5:85F, 5:141 low spatial resolution, 4:543 polar pack/polynyas, 4:543 Scanning sonars, remotely operated vehicles (ROVs), 4:743 SCAR (Scientific Committee for Antarctic Research), 5:513 Scaridae (parrotfishes), 1:657 Scarp, definition, 5:465 Scattering coastal trapped waves, 1:596 internal waves see Internal wave(s) Scattering (acoustic), 1:107F acoustic noise, 1:56, 1:58 Scattering (optical), 1:8 suspended particles, 4:8, 4:11F Scattering (spectral) coefficient see Scattering coefficient Mie theory, 6:110–111 Rayleigh, 6:110–111 sensors see Nephelometry see also Volume scattering function (VSF) Scattering coefficient, 3:244–245, 6:109–110 definition, 4:621, 4:622 Hydrolight simulation, 4:625–626, 4:626F oceanic waters, 1:391, 1:391F as bio-optical model quantity, 1:386T, 1:387 time series, 3:250F see also Ocean optics Scatterometers, 2:329, 3:108, 5:70, 5:380 Advanced Scatterometer (ASCAT), 5:203, 5:204T NSCAT (NASA scatterometer), 5:71 satellite see Satellite scatterometers Scatterometry, 2:329, 3:108, 5:70, 5:202–203 microwave, 5:203 rain and, 5:203 tropical cyclones, 5:209F Scavenging, 6:234 Scheldt River estuary, Belgium elemental mercury, 3:6 enrichment factor, 3:772–773, 3:773T metal pollution, 3:771, 3:771T Schleicher, K E, 1:712, 1:713 Schlumberger, logging tools, 2:41–42 Schmidt, J., 2:208–209 Schmidt (Prandtl) numbers, 1:148, 1:148F, 1:149T, 1:157–158, 1:169, 3:2, 3:202, 3:372, 4:219, 4:222 controlled flux technique and, 1:155 gas transfer velocity and, dual tracer release experiments, 6:90 open ocean convection, 4:219, 4:222 relation to entrainment velocity, 3:374 relation to Richardson and Reynolds numbers, 3:374 three-dimensional (3D) turbulence, 6:21
(c) 2011 Elsevier Inc. All Rights Reserved.
595
Scholte wave, 1:78T, 1:79–80, 1:79F Schro¨dinger equation, surface, gravity and capillary waves, 5:578 Sciaenops ocellatus (red drum), stock enhancement/ocean ranching programs, 4:147T, 4:150 SCICEX see Scientific Ice Expeditions Science deep-sea drilling initiatives, 2:46–47 deep submergence see Deep submergence science fishery management basis, 2:525–526 manned submersible (shallow water) use, 3:516 marine policy focus, 3:664T Science Working Groups (SWGs), 5:69 Scientific Committee for Antarctic Research (SCAR), 5:513 Scientific Committee on Oceanic Research (SCOR), 3:94, 3:277–278, 5:513 Global Ocean Ecosystem Dynamics, 3:278 International Indian Ocean Experiment, 3:277–278 Joint Global Ocean Flux Study, 3:278 large-scale climate patterns, 3:278 membership, 3:278 scientific working groups, 3:278 Tropical Ocean – Global Atmosphere Study (TOGA), 3:278 World Ocean Circulation Experiment (WOCE), 3:278 Scientific expeditions, deep-sea drilling, 2:52 Advanced Piston Corer (APC) operation, 2:52 borehole logging and instrumentation, 2:52 leg duration, 2:52 Rotary Core Barrel (RCB), 2:52 ship crew and scientific party, 2:52 Scientific Ice Expeditions (SCICEX), 5:151 Scientific Measurements Panel (SCIM), deep-sea drilling, 2:53 Scientific observations, history, 3:121 Scientific research vehicles, 4:745 advantages over manned submersibles, 4:745–746 current ROVs, 4:746, 4:746T manned submersibles use with, 4:745 Scientists, deep-sea drilling, 2:52 Scleractinians, definition, 1:677 Scolopacidae, Phalaropes see Phalaropes Scomber scombrus (Atlantic mackerel), 2:375, 2:404–405, 2:405F see also Mackerel Scombridae, 2:395–396F diet, 4:135 Indian mackerel, 4:368 mackerels, 4:368 migration, 2:404–405 tunas, 4:368 Scopelarchus analis (short fin pearleye), 2:449F
596
Index
SCOR see Scientific Committee on Oceanic Research (SCOR) Scorpaenid fisheries, 4:228–229, 4:229F see also specific species SCOR WG 95, 4:699 Scoters fisheries interactions, 5:270–271 see also Seabird(s) Scotia Front, 6:323 Scotland Atlantic salmon farming, 5:24 Atlantic salmon fisheries, 5:2T, 5:5 catch, 5:8F, 5:9 Scottish seines, fishing methods/gears, 2:537 Scours, icebergs, 3:189 Scripps Institute of Oceanography, 1:154T autonomous underwater vehicles, 6:263T remotely-operated vehicles (ROV), 6:260T Scripps Institution’s re-entry vehicle, 2:24–26, 2:29F SCUBA, invented by Cousteau, Jacques, 3:695 Scuba diving, corals, human disturbance/ destruction, 1:675 Scyliorhinus canicula (spotted dogfish), 2:464 Sea–Air Exchange (SEXREX) Program, 1:123 Sea–air heat flux see Air–sea heat flux Sea–air momentum transfer, 6:308 see also Wind forcing Sea–air partial pressure of CO2, 1:489–491, 1:490F Sea bass see Dicentrarchus labrax (sea bass) Seabed flow regime, benthic flux measurement and, 4:489, 4:491–492 flow stress estimation, 6:144–147 Law of the Sea jurisdiction, ‘area,’ definition, 3:435 mixing in front generation and, 5:394–395 optical properties, 4:734, 4:735T roughness, turbulence and, 6:145 satellite remote sensing, 4:739, 4:740F topography, acoustic profiling, 1:39 vertical temperature gradient, 5:555F see also Seafloor SeaBED, 6:263, 6:263T, 6:264F Seabird(s), 5:265, 5:279–284 by-catches, 4:232, 5:267T, 5:268–270, 5:268T albatross, 2:203, 5:517 gill nets, 5:265, 5:268–270, 5:268T, 5:272–273 longline fishing, 4:596, 5:249, 5:267T, 5:268 climate change responses see Climate change, seabird responses conservation see Conservation cost of flight, 5:279
distribution, 5:279 influence of oceanic currents, 5:279 diving, 5:230, 5:265, 5:266 flying vs., 5:520–521 effects of and on fisheries, 5:282–283 exploitation see Human exploitation feeding in gyre ecosystems, 4:135 feeding methods, 5:281–282, 5:281F fish consumption, 5:282, 5:282T fisheries interactions, 4:592–593, 5:234, 5:265–273 by-catches see Seabird(s), by-catches discarded waste as food source for scavengers, 5:265, 5:269T, 5:270, 5:272–273 effects of overfishing see Overfishing history, 5:266–267 seaduck, 5:270–271 foraging ecology see Seabird foraging ecology foraging methods, 5:282 hazards/threats, 5:220–221, 5:221F, 5:222–223, 5:249 habitat loss/modification, 5:222 human see Human activities, adverse effects; Human exploitation management see Conservation military activities, 5:226 predation, 5:222 impact on rocky shore biota, 4:768 importance of krill, 3:356 indicators of ecosystem change, 5:283 as indicators of ocean pollution, 5:225, 5:274–278 acid rain, 5:277 bio-assays, 5:274, 5:275, 5:277 heavy metals, 5:225, 5:274, 5:275–276 history, 5:274–275 mercury, 5:275 oil, 5:224, 5:276–277, 5:276F organochlorines, 5:274, 5:274–275, 5:275 PCBs (polychlorinated biphenyls), 5:275 plastic, 5:276F, 5:277 radionuclides, 5:277 life history, 5:281 mercury levels in feathers, 5:275 migration see Seabird migration nesting and feeding of young, 5:279–281 North Sea populations see North Sea oil pollution, 4:197 population dynamics see Seabird population dynamics population increases, discarding effects, 2:203 prey, 5:281–282 regime shifts and, 4:700–702 reproduction see Seabird reproductive ecology reproductive rates, 5:281 role in oceanic carbon cycling, 5:282 scavenging, 5:265–266 fishery discards/offal as food, 5:265, 5:269T, 5:270, 5:272–273 consumption rates, 5:269T, 5:270
(c) 2011 Elsevier Inc. All Rights Reserved.
species included, 5:279, 5:280T taxonomy, 5:265, 5:266T threats, 5:283 vulnerabilities, 5:221–222, 5:221F activity patterns, 5:222 adults, 5:222 chicks, 5:221–222 ecosystem, 5:221F, 5:222 egg stage, 5:221 juveniles, 5:222 wing loadings, 5:520–521 migration patterns and, 5:238, 5:238F see also specific orders/families/genera/ species Seabird CTD instrument, towed vehicles, 6:68F, 6:73F Sea-Bird Electronics, Inc., 1:714 Seabird foraging ecology, 5:227–235 behavior, 5:229–230 wind and, 5:231 habitat, 5:227 environmental gradients, 5:227–228 fronts, 5:228, 5:228F sea ice, 5:229, 5:229F topographic features, 5:228–229, 5:228F water masses, 5:227, 5:227F prey associations, 5:231 resource partitioning, 5:231–232 competition, 5:234 competition with fisheries, 5:234, 5:271, 5:272–273 day vs. night feeding, 5:233 habitat type, 5:232–233 kleptoparasitism, 5:230, 5:233 morphological/physical factors, 5:233–234 mutualism, 5:230, 5:233 prey/predator size, 5:232, 5:233F prey selection, 5:231–232, 5:232F, 5:233F strategies, 5:230, 5:265–266 feeding flocks, 5:230 maximization of search area, 5:230–231 nocturnal feeding, 5:230 physical features, 5:230 subsurface predators, 5:230 Seabird migration, 5:236–246 distances, 5:279 morphological adaptations, 5:237–239 wing loading, 5:238, 5:238F wing shape, 5:237–238 orientation and navigation, 5:236 sensory mechanisms, 5:236–237 physiological/behavioral adaptations, 5:237 post-breeding vs. pre-breeding, 5:237 terrestrial species vs., 5:237 reasons for, 5:236 studies, 5:236 types, 5:239 dispersal, 5:239 partial, 5:239 true, 5:239
Index Seabird population dynamics, 5:247–250 characteristics, 5:247 clutch size, 5:248 colony size, 5:247 delayed breeding age, 5:248, 5:249 food availability, 5:247, 5:249 winter, 5:249 hypotheses, 5:249 inshore-foragers, 5:247, 5:248, 5:248–249 interannual variation, 5:248, 5:248–249 inter-colony variation, 5:247–248 life spans, 5:249 offshore-foragers, 5:247, 5:248–249 philopatry, 5:247 genetic implications, 5:247 population increases, discarding effects, 2:203 survival rates, 5:249 Seabird reproductive ecology, 5:251–256 abandonment of breeding attempt, 5:253–254, 5:255T due to low resources, 5:254 early, 5:254 young breeders, 5:254–255 age of first breeding, 5:251–252, 5:255T delayed, 5:252 young, 5:251 breeding vs. nonbreeding, 5:252–253, 5:255T coloniality, 5:256 global effects on strategies, 5:256 inshore strategies, 5:251, 5:252T, 5:255–256, 5:255T investment in breeding, 5:253, 5:254F, 5:255, 5:255T offshore strategies, 5:252T, 5:255–256, 5:255T reproductive rates, 5:281 timing of breeding, 5:252, 5:255T Sea bottom acoustic reflection, 1:97 see also Seabed; Seafloor; entries beginning bottom Sea butterflies (Thecosomata), 3:14 SeaCAPS system, 4:277F Sea Cliff (US Navy submersible), 3:505–506, 3:509 Sea cow, Steller’s, 3:639, 5:436–437, 5:437F see also Dugongidae Sea cucumbers (Holothuroidea), 1:355, 2:56F, 3:16 Sea Dragon 3500, 6:260T Seaduck, fisheries interactions, 5:270–271 Seafloor acoustic reflection/scattering, 1:97, 1:113, 1:114–115, 1:115–116, 1:115F depth and age, 3:868F drifters, 2:172 ice-induced gouging see Ice-gouged seafloor imaging by AUVs, 6:263 manganese nodules, 3:490–491 map, 3:867, 3:867F
roughness, acoustics in marine sediments, 1:80 sediments see Seafloor sediments spreading see Seafloor spreading topography see Seafloor topography variability, 1:297 see also Seabed; entries beginning bottom Seafloor cables, in current velocity measurements, 2:253 Seafloor equipment, deep-sea drilling, 2:51 Hard Rock Guide Base (HRGB), 2:51 reentry cones, 2:51 Seafloor mapping, active sonar images, 5:509, 5:509F Seafloor observatories, deep-sea drilling, 2:50 Seafloor sediments, 3:864–865 accretionary prisms see Accretionary prisms acoustics see Acoustic remote sensing; Acoustics, marine sediments bulk density, 1:78, 1:78T, 1:80 bulk modulus, 1:78, 1:78T, 1:80 clay see Clay core samples see Sediment core samples mud see Mud sand see Sand water-sediment interface, seismoacoustic waves in, 1:78–79, 1:79F see also Acoustics, marine sediments Seafloor spreading magnetic anomalies, 3:27–28, 3:28F, 3:30 magnetic anomaly and, 3:483 sea level fall and, 5:187, 5:188F, 5:189 theory, historical background, 3:123 see also Fast-spreading ridges; Geomagnetic polarity timescale (GPTS); Slow-spreading ridges; Spreading centers Seafloor topography acoustic noise, 1:56 coastal shelf topography, coastal trapped waves, 1:596 geophysical heat flow and, 3:43 gravitational, satellite altimetry, maps, 5:59, 5:60F internal tides see Internal tides internal waves see Internal wave(s) ridge topography, hydrothermal plumes, 2:131, 2:134–135 vortical mode generation mechanism, 6:287–288 see also Bathymetry; Bottom topography Sea foam, 6:331–336 features, 6:335F stabilized, 6:334–336 see also Whitecaps Seaglider, 3:60, 3:61F, 3:62, 3:62–63, 6:263T missions, 3:64–66, 3:65F Seagrasses, 2:141–142 destruction, threat to manatees, 5:444 dugong ‘cultivation grazing’, 3:603
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597
as habitat, 2:141–142 Posidonia, use of artificial reefs, 1:228 species, 2:141–142 Thalassia, thermal discharges and pollution, 6:14 Seahorses (Syngnathidae), 2:395–396F see also Hippocampus (sea horse) Sea ice, 1:418F, 5:141–158, 5:170–178 acoustic noise, 1:98 acoustic reflection, 1:95 acoustic reverberation, 1:97 Antarctic bottom water, role in, 1:416–417 Arctic, extent, 1:93F see also below area, 5:143 Baltic Sea circulation, 1:288 benthic microfossils, studies of, 5:173 biological effects, 5:171–172 bottom water formation, 5:80 brightness temperatures, 5:80, 5:81F, 5:82, 5:83, 5:88, 5:88F, 5:89 brine, composition of, 5:172–173 concentration maps, 5:84, 5:84F concentrations, 5:80, 5:81, 5:82, 5:82–84, 5:83, 5:88, 5:89 conservation law, 5:162–163 cover annual cycles, 5:80, 5:81 extents, 5:84, 5:89, 5:170 extents and trends, 5:84–86, 5:88–89 future monitoring, 5:88–89 global, 5:81 interannual differences, 5:81, 5:84 monitoring, 5:80, 5:81F, 5:88–89 seasonal cycle, 5:84, 5:85–86 trends, 5:84, 5:88–89 data, global, 5:80 deformation, 5:173–175 determinations from satellite passivemicrowave data, 5:82–84, 5:84, 5:85F, 5:87F, 5:88F diffusive convection under, 2:167 drift, 5:173–175 drift problem, 5:165, 5:165F dynamics, 5:159–169 edges, satellite remote sensing application, 5:109, 5:109F equation of motion, 5:164–165, 5:165F scaling, 5:165T formation, 4:127–128 free drifting, 5:165–166, 5:166F ‘fresh’ layer role, 5:171 geographical extent, 5:84, 5:89, 5:170 Antarctic seasonal variability, 5:146–150 Arctic interannual trends, 5:143–146, 5:144F, 5:145F, 5:147F Arctic pressure fields, 5:147F Arctic seasonal variability, 5:141–143 definition of ‘extent’, 5:143 global interannual variability, 5:151F trends, 5:84–86, 5:88–89 geophysical importance, 5:170–172 greenhouse climates, 4:326 human activities, effects on, 5:171–172
598
Index
Sea ice (continued) kinematics, 5:159–163 melting, 5:162–163 microbial communities organisms, 4:515–516 primary production, 4:515 microwave emissions, 5:80 modeling, 5:167 short-term, 5:167 multiyear, 5:141 Arctic, 5:143 Weddell Sea, 5:157 North Atlantic Oscillation (NAO) and, 4:70 ocean circulation, 4:123 Okhotsk Sea, 4:203–204, 4:203F operations under, autonomous underwater vehicles (AUV), 4:473, 4:481–482 pancake ice, 5:157 plastic yield curves, 5:164F polar climate state, 5:80 pressure ridges, 5:174 properties, 5:172–173 rheology, 5:163–164, 5:164F satellite images, 5:160F satellite passive-microwave measurements, 5:80–90 see also Satellite passive-microwave measurements of sea ice seabird abundance and, 5:229, 5:229F sediment transport, 3:887 shear zone, 5:159 solar radiation reflection, 5:80, 5:82 stationary, 5:165 structural types, 5:173 see also Sea ice, typessee specific types surveillance by SAR, 5:106–107 thermal growth, 5:162–163 thickness, 5:84, 5:85 Antarctic, 5:155–157 Arctic, 5:151–155, 5:152F, 5:154T data variability, 5:153, 5:154 distribution, 5:174, 5:174F drilling from ships and, 5:157 information, data techniques, 5:176 trends, 5:84–86, 5:88–89, 5:175–177 types, 5:80, 5:82, 5:86–87 first year ice, 5:86, 5:88F frazil ice, 5:86 grease ice, 5:86 multiyear ice, 5:86, 5:88F nilas, 5:86 pancake ice, 5:86 slush ice, 5:86 variables affecting, 5:87–88 season length, 5:87–88 summer melt, 5:87–88, 5:88 temperature, 5:80, 5:81–82, 5:87–88 velocity, 5:87–88, 5:88 velocities, 5:174–175 Weddell Sea, 5:160F multiyear, 5:157 Weddell Sea circulation current measurement restriction, 6:318–319, 6:319
drift, 6:318, 6:319, 6:322 formation, 6:323, 6:324 melting, 6:323, 6:324 polynyas see Polynyas sea ice-ocean coupled models, 6:320–321 seasonal variations, 6:318, 6:323–324 see also Bottom water formation; Coupled sea ice-ocean models; Drift ice; Ice–ocean interaction Sea Ice Mechanics Initiative (SIMI), 1:92–93 Seal(s) see Pinnipeds (seals); see specific species Sea level anomaly, tomography vs. satellite altimetry, 6:55F changes see Sea level changes/variations El Nin˜o Southern Oscillation and, 2:235 eustatic, glacio-hydro-isostatic models, 3:54 fall see Sea level fall function, anatomy of, 3:54–56 crustal rebound phenomena, 3:52F, 3:54, 3:55F hydro-isostatic effect dominant, 3:54–56, 3:55F local isostatic approximation, 3:54 physical quantities estimated from observations, 3:55F, 3:56 viscous response of the planet, 3:54, 3:55F gas hydrate stability and, 3:785 global, tectonics and, 3:49–50, 3:50F ice-volume equivalent, 3:51F, 3:53 Indonesian Throughflow gradient, 3:237, 3:240 mean (MSL), storm surges, 5:539 methane hydrate reservoirs and, 3:794, 3:794F Peru-Chile Current System (PCCS), 4:387, 4:388F relative, isostatic contribution, 3:53 rise see Sea level rise sequence formation and, 4:144–145 Southern Ocean, 1:186F subterranean estuaries and, 5:555 variations see Sea level changes/ variations see also Economics of sea level rise Sea level annual pulse, 3:444 Sea level changes/variations, 3:49–58, 5:179–184 fall see Sea level fall geological timescales, 3:35, 5:185–193 due to changing volume of ocean basin, 5:187–189, 5:188F, 5:193 due to volume of water in ocean basin, 5:185–187, 5:186F, 5:193 Milankovitch scale, 5:187 see also Million year scale sea level variations geological timescales, estimations, 5:179 backstripping method, 5:189–191, 5:190F, 5:193 continental hyposography, 5:189
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from location of strand line on stable continental craton, 5:189 long-term change, 5:190F, 5:191–193 million year scale, 5:192F, 5:193 from observations on continents, 5:189–191 oxygen isotope ratio (d18O), 5:185 see also Oxygen isotope ratio (d18O) from sedimentary records, 5:189 sequence stratigraphy, 5:192–193, 5:192F uncertainties, 5:189, 5:193 geomorphology boundary condition, 3:33 deltas and estuaries, 3:38 glacial cycles and, 3:50–51 cyclic global climate change, 3:50–51, 3:51F glacio- and hydro-isostatic effects, 3:51 glacio-hydro-isostatic models see Glaciohydro-isostatic models human resistance, 1:585–586 isostatic contribution, 3:54 methane release from gas hydrates and, 3:784, 3:787–788, 3:787F, 3:788 proportional to heat anomaly, 5:62–63, 5:63F see also El Nin˜o Southern Oscillation (ENSO) recent, observations, 5:179–180 altimeter, 5:180–181 tide-gauge, 5:179–180, 5:180F recent, rate-determining processes, 5:181–182 Antarctic ice sheet, 5:182–183 Greenland ice sheet, 5:182–183 nonpolar glaciers and ice caps, 5:182, 5:182F, 5:183 ocean thermal expansion, 5:181–182, 5:182F terrestrial storage changes, 5:183 relative change between land and, 3:49 rises see Sea level rise satellite altimetry, 5:61–63 1997-98 El Nin˜o event, 5:62–63, 5:62F global sea level variability, 5:61–62, 5:62F global tide models, 5:61 sea level proportional to heat anomaly, 5:62–63, 5:63F sea level signal record, 5:62–63, 5:62F shoreline migration see Shoreline migration since last glacial maximum, 3:51–53, 5:179 areas of former major glaciation, 3:51, 3:52F characteristic sea level curves, 3:52F positions of past shorelines, 3:50F, 3:51, 3:52F spectrum of variation, 3:53 tectonics and, 3:49–50 see also Tectonics
Index see also Climate change; Sea level fall; Sea level rise; Upper ocean, time and space variability Sea level fall mid-ocean ridges and, 5:187, 5:188F, 5:189 seafloor spreading, 5:187, 5:188F, 5:189 ‘snowball earth’, 5:186 see also Sea level changes/variations Sea level rise continental breakup and, 5:187, 5:188F, 5:189 dynamic sea surface topography, 5:61 economics see Economics of sea level rise evidence from ancient corals, 5:185 global-average rates estimates, 5:180, 5:181, 5:184 recent acceleration, 5:180 large igneous province (LIPs) and, 5:186F, 5:189 projections for twenty-first century, 5:183, 5:183F, 5:184 longer-term, 5:183–184 regional, 5:183 reduction, dam building and, 5:183 satellite altimetry, 5:63 dense coverage of satellite altimeter data, 5:63 global hydrologic system, 5:63 volcanism and, 5:189 see also Climate change; Sea level changes/variations Sea level variations see Sea level changes/ variations Sea lice, salmonid farming, 3:522 infestation control, 3:522, 5:27 Sealing, 3:635, 3:638–639, 3:639F decline, 3:638–639 history of, 3:638 Sealing age, 3:46 Sea Link, 6:258F Sea lions see Otariinae (sea lions) Seals see Pinnipeds (seals); see specific species Sea MARC 1, 5:464 Seamount(s), 2:57, 4:136 coastal trapped waves, 1:593 definition, 1:268 internal tides, 3:265 magnetic anomalies, 3:486–487 near-ridge, 5:292–294 characteristics, 5:293F, 5:294 distribution, 5:294 East Pacific Rise (EPR), 5:294, 5:294F, 5:295F, 5:296 formation mechanisms, 5:296 isolated seamounts, 5:294 Juan de Fuca Ridge, 5:294, 5:296 linear chains, 5:293F, 5:294 trends and plate motion, 5:294F, 5:295F, 5:296, 5:296–297, 5:299F lithospheric influence, 5:296 magma supply, 5:296 mapping and exploration, 5:294
Mid-Atlantic Ridge, 5:295–296, 5:295F oceanic crust formation, 3:817 plume-ridge interaction, 5:296–297 spreading rate correlation, 5:294–295, 5:295F potential vorticity, 6:288, 6:288F seabird abundance and, 5:228 see also Large igneous provinces (LIPs); Seamounts and off-ridge volcanism Seamount phosphorites, 1:264 Seamounts and off-ridge volcanism, 5:292–304 melt availability, 5:292 near-ridge seamounts see Seamount(s) oceanographic effects, 5:292–294, 5:297–301 biogeochemical cycles, 5:301–302 ocean currents, 5:301–302 sediment composition, 5:301 off-ridge non-plume related volcanism, 5:296–297 clustered seamounts, 5:292, 5:300 crackspots, 5:300–301 en echelon volcanic ridges, 5:292, 5:299–300, 5:300F flexural loading, 5:300, 5:302F fossil ridge volcanoes, 5:300, 5:301F island chains, 5:300–301 isolated seamounts, 5:292, 5:300 Vesteris, 5:300, 5:303F lava composition, 5:299–300 lava fields, 5:292, 5:300 magma supply mechanisms, 5:297–299 mantle origin, 5:300–301 Puka Puka Ridges, 5:299–300, 5:300F Richter rolls, 5:297–299 off-ridge plume related volcanism, 5:294–296 Hawaii-Emperor chain, 5:296, 5:297F island chains, 5:292, 5:296, 5:298F large igneous provinces (LIPs), 5:292, 5:296 lava composition, 5:296 mantle plumes, 5:296 oceanic plateaus, 5:292, 5:296, 5:297F Pacific plateaus, 5:296, 5:297F seamount chains, 5:292, 5:296, 5:298F starting plumes, 5:292 well-behaved plume, definition, 5:296 see also Authigenic deposits; Calcium carbonate (CaCO3); Deep-sea fauna; Igneous provinces; Midocean ridge tectonics, volcanism and geomorphology Sea of Okhotsk see Okhotsk Sea Sea otter (Lutrinae), 5:194–201 adaptations to life at sea, 5:196 diet, 5:197–198 diving, 5:197–198, 5:198F see also Marine mammals, diving physiology locomotion, 5:196
(c) 2011 Elsevier Inc. All Rights Reserved.
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reproduction, 5:198, 5:198F thermoregulation, 5:196–197 conservation status, 3:608T decline, 5:194 exploitation, 3:635, 3:640 history of, 3:640 food/foraging, 3:616, 5:195, 5:200, 5:200F habitat, 5:194, 5:195, 5:195F foraging, 5:195 life history, 5:195–196 longevity, 5:196 mortality, 5:196 reproduction, 5:195–196, 5:198, 5:198F, 5:200–201 survival, 5:196, 5:200F, 5:201 myoglobin concentration, 3:584T physical characteristics, 5:194–195 body outline and skeleton, 3:610F dentition, 5:194–195, 5:196F fore legs, 5:194–195 fur, 5:194–195 hind feet, 5:194–195, 5:196 insulation, 5:194–195, 5:197 tail, 5:194–195, 5:196 weight, 5:194–195 range, 5:195, 5:195F responses to changing ecological conditions, 5:200 diet, 5:200, 5:200F populations, 5:201 reproduction, 5:200–201 survival, 5:201 role in structuring coastal marine communities, 5:198–199 kelp forests, 3:625, 5:198–199, 5:199F soft-sediment subtidal, 5:199–200 trophic level, 3:622, 3:623F see also Marine mammals Sea salt, atmospheric, 1:248–249 concentrations, 1:249T Seasat-A satellite, 5:202–203, 5:204T Seasat satellite, 3:83, 5:67F, 5:68, 5:81–82 global sea surface topography, 5:73F SeaSoar towed vehicle, 6:65, 6:69, 6:74F Seasonal cycles open ocean convection, 4:218, 4:224 upper ocean, 6:215 Seasonal thermocline, 6:211 subduction, 4:156, 4:157F, 4:158 upper ocean, 6:178–180, 6:179F see also Thermocline, main Sea spiders (pycnogonids), 1:377T, 2:59F Sea strait see Straits Sea surface acoustic reflection, 1:113 bubble formation, 1:440 cooling, 6:187–188 drag coefficient, high wind speeds, 6:306 eddy formation, wind forcing, 3:762 heat fluxes see Heat flux heat transfer processes, 5:202 height see Sea surface height (SSH) momentum fluxes see Momentum fluxes
600
Index
Sea surface (continued) net carbon dioxide flux, 1:489, 1:491–493, 1:492F, 1:493T sources of error, 1:493 nitrogen, atmospheric input, 1:123 salinity see Sea surface salinity (SSS) temperature see Sea surface temperature (SST) see also Ocean surface Sea surface height (SSH) Intra-Americas Sea (IAS), 3:290F, 3:293F Rossby waves, 4:783, 4:784F Stommel’s model, 6:353F Sea surface inclination, Baltic Sea circulation, 1:290–291, 1:292, 1:292F Sea surface processes, wind driven see Wind-driven sea surface processes Sea surface salinity (SSS), 6:175, 6:176F, 6:177F coral-based paleoclimate research, 4:339T, 4:340 seasonal variations, factors, 6:175–176 Sea surface skin temperature (SSST), measurement, 3:320–322 see also Infrared (IR) radiometers Sea surface temperature (SST), 3:447, 3:451F, 4:125, 4:129, 6:175, 6:176F, 6:177F anomalies, Kuroshio–Oyashio outflow regions and, 3:368–369, 3:368F Black Sea, 1:413F regime shifts and, 4:704–705 Brazil and Falklands (Malvinas) Currents, 1:427–428, 1:428F, 1:429F Cape Cod, 5:397F characteristics, 2:98 cool skin, 4:222 coral-based paleoclimate research, 4:339T, 4:340 depth profile, idealised, 2:99F eastern tropical Pacific Ocean, 2:241, 2:241F effect on meteorological parameters, 2:230 Ekman transport and, 6:342 El Nin˜o events, 2:229F, 2:241, 2:241F time series 1950-1998, 2:237F El Nin˜o Southern Oscillation east-west variations, 2:230 interannual variation, 2:237 prediction and, 2:239 global, 6:339–340, 6:339 global distribution, 6:167F heat stored in the ocean indicated by, 5:99 (pre)historic see Sea surface temperature paleothermography hurricane development, 6:171–172 hurricane Ivan, 6:202, 6:202F hurricanes, 6:192 hurricanes Isidore and Lili, 6:201F hurricanes Katrina and Rita, 6:204–205
ice core vs. marine sediment determination, 1:3F Intra-Americas Sea (IAS), 3:293–294 Irish Sea, 5:393F La Nin˜a and, 2:241, 2:241F long-chain alkenone index and, 2:105–106 measurements, 5:377, 6:217 infrared radiometers see Infrared (IR) radiometers mechanisms controlling, 2:244 mesoscale eddies, 3:757, 3:758F mixed layer temperature and, 6:166 North Atlantic Oscillation and, 4:68F, 4:69 North Pacific, regime shifts, 4:711, 4:712F observed vs simulated, one-dimensional models, 4:213, 4:214F ocean anoxic events, 4:320 Ocean Station Papa, 4:212–213, 4:213F agreement with model, 4:213, 4:214F Pacific Ocean, interannual variations, 2:272F range, 2:98, 6:163 Rossby waves, 4:783–784 satellite measurements, 4:222 satellite remote sensing see Satellite remote sensing of sea surface temperatures seasonal variations, factors, 6:175–176 ship-based measurements, 4:222 sound speed and, 5:352F Southeast Asian Seas, 5:309, 5:311F spectral range for remote sensing, 4:735T surface film effects, 5:571 surface-measured for calibration of satellite measurements, 5:380–381 tidal mixing and, 5:392–393 tropical mean, 2:100F tropical Pacific, 6:344F in tropics, thermoclines and, 2:242 wind change effects, 2:244 wind effect, 2:231 winds causing/resulting in change, 2:241 Sea surface temperature paleothermography, 2:98–113 Last Glacial Maximum, 2:99F methods, 2:98–101 alkenone unsaturation, 2:101T, 2:105–106 fossil assemblage transfer functions, 2:108–110 magnesium/calcium ratio, 2:103–104 nature of SST signal in geology, 2:100–101 oxygen isotope ratio, 2:101–103 paleothermometers, 2:101–103 strontium/calcium ratio, 2:104–105 tetraether index, 2:106–108 proxy sources, 2:99F Sea surface topography gravitational see Satellite altimetry Marianas Trench, 5:58–59, 5:60F satellite altimetry, 5:58, 5:59F
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SeaTech transmissometer, 4:8, 4:9F, 4:11 Sea trout (Salmo spp.), 5:29, 5:30 Sea turtles, 5:212–219 adaptations to aquatic life, 5:212 lacrimal salt glands, 5:212, 5:214, 5:215F limbs, 5:212, 5:213–214, 5:213F, 5:214F physiologic, 5:212, 5:214, 5:214F by-catch issues, 2:203 as endangered species, 5:213 evolution, 5:212, 5:213 fossils, 5:213 general biology, 5:213–215 growth rates, 5:213 oil pollution, 4:196–197 reproduction, 5:213–214 egg(s), 5:212 egg incubation, 5:212, 5:213–214 nest chamber, 5:212 nesting behavior, 5:213–214, 5:214F temperature-dependent sex determination, 5:212, 5:213–214 taxonomy, 5:212 family Cheloniidae see Cheloniids family Dermochelyidae see Dermochelyids see also specific species Sea urchins (Echinoidea) barrens, 5:199F coral cover and, 4:702 sea otter effects, 3:625, 5:198–199, 5:199, 5:199F threat to kelp forests, 4:431 Sea-viewing Wide Field-of-View Sensor (SeaWIFS) see SeaWiFS Seawalls, engineering see Coastal engineering Sea water adiabatic lapse rate, 6:382 analysis, routine see Wet chemical analyzers artificial see Artificial sea water complex dielectric constant, 5:127–128, 5:129, 5:131F composition, hydrothermal circulation and, 3:46 conductivity, measurement in situ, 1:710 constituents conservative see Conservative elements major, 1:627T minor, 1:628 optical see Sea water, optical constituents ratios, river water vs., 1:627, 1:627T see also specific constituents density, 6:163 effect of monsoonal precipitation, 3:911 in equations of motion, forward numerical models, 2:605 dielectric properties, 5:127 electrical conductivity, 5:127 electrical properties see Electrical properties of sea water
Index emissivity coefficient, 5:127 equation of state see ‘Equation of state’ (of sea water) fluorescent species, direct measurement, 2:593–594, 2:593T freezing point, 1:690, 6:382–383 optical constituents, 4:624 dissolved organic compounds, 4:624 inorganic particles, 4:624–625 organic particles, 4:624 bacteria, 4:624 detritus, 4:624 phytoplankton, 4:624 water, 4:624 physical properties, 6:379–383, 6:380T potential temperature, 6:382 properties of, 3:164, 3:166–167, 3:167F, 3:169T chemical composition, 3:169T critical point, 3:166–167, 3:167F hydrothermal vent fluid, comparison to, 3:169–170, 3:169T two-phase curve, 3:166–167, 3:167F pure, spectral absorption, 3:245 salinity range, 6:381F see also Salinity sound speed, 6:380T, 6:382 specific heat, 6:380T, 6:381–382 specific volume anomaly, 6:381 standard, salinity, 1:712 surface see Surface sea water; entries beginning surface surface emissions, 5:127 temperature conservativity, 1:708–709 range, 6:381F see also Sea surface temperature (SST) thermal expansion coefficient, 6:380T, 6:381 see also Water Seaways, paleoceanographic models, 4:308–309 Seaweed(s), 3:538, 5:317–326, 5:317 in biomitigation, 5:322–326 Chondrus crispus, 5:322F in coastal systems, 5:317–318 importance, 5:318 species diversity, 5:317–318 definition, 5:317–318 Eucheuma denticulatum, 5:321F Gracilaria chilensis, 5:321F Laminaria japonica, 5:319F life cycles environmental controls, 4:428 two-phase life cycle, 4:428 isomorphic vs. heteromorphic, 4:428 mariculture see Seaweed mariculture Monostroma nitidum, 5:322F phytomitigation by IMTA systems, 5:323–324 flexibility of IMTA systems, 5:324 interest and development of IMTA systems, 5:324–325 repositioning at seaweeds’ roles in coastal ecosystems, 5:325–326
value of phytomitigation industry, 5:326 Porphyra yezoensis, 5:320F species diversity, 2:142 Undaria pinnatifida, 5:320F uses, 3:538, 5:321–322 see also Algae; Phytobenthos Seaweed ecology effects of wave action, 4:429 phytobenthos, 4:428–429 successional colonization, 4:429, 4:430T conditions favoring opportunists, 4:429 replacement of opportunists, 4:429 temperate species, 4:428 zonation deep-growing plants, 4:429 estuaries, 4:429 physical and biotic factors, 4:429 rock pools, 4:429 subtidal area, 4:429 temperate shores, 4:428–429 Seaweed mariculture, 3:538–539, 5:318–322 biomass, products and value of seaweedderived industry in 2006, 5:325T breeding/genetic manipulation, 3:539 cultivation method, 3:538 cultivation technologies, 5:318–319 global distribution by region and organisms, 5:325F health problems, 3:539 percentage of aquaculture biomass, 5:319 percentage of seaweed from cultivation, 5:318–319 production by tonnage, 5:319–321 main genera of seaweed, 5:324T main groups of seaweed, 5:323T production by value, 5:319–321 main genera of seaweed, 5:324T main groups of seaweed, 5:323T species cultivated, 3:538, 5:319–321 statistics from 1996 to 2004, 5:323T suitability for undeveloped areas, 3:539 Sea whips (Gorgonacea), 2:56F SeaWiFS, 1:365, 5:118T, 5:396 data, chlorophyll a, 5:122F, 5:123F data validation, 5:120–121 global area coverage, 5:117–118, 5:118F polarization errors, 5:121 sensor degradation, 5:116, 5:119F surface chlorophyll measurements, 4:91F SeaWiFS Aircraft Simulator (SAS), 1:142 SeaWiFS algorithm, 4:628 SeaWinds scatterometer, 5:204T see also ADEOS II; QuikSCAT Sebastes (redfish), open ocean demersal fisheries, 4:228–229, 4:229F FAO statistical areas, 4:231T Sebastes alutus (Pacific Ocean perch), open ocean demersal fisheries, 4:229, 4:229F FAO statistical areas, 4:229, 4:231T
(c) 2011 Elsevier Inc. All Rights Reserved.
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Sebastes marinus (ocean perch), open ocean demersal fisheries, 4:228–229 Sebastes mentella (deepwater redfish), open ocean demersal fisheries, 4:228–229 Sebastolobus (rockfishes), open ocean demersal fisheries, 4:228–229 FAO statistical areas, 4:229, 4:231T SEC see South Equatorial Current (SEC) SECC see South Equatorial Countercurrent (SECC) Secondary glide plane, definition, 5:465 Secondary production, 2:147 Second Law of Thermodynamics, 4:167–168 Second-order sea level change see Million year scale sea level variations Section inverse models/modeling, 3:302 nitrate transport, 3:305F see also Hydrographic sections Sediment(s) biogeochemical zonation see Biogeochemical zonation bioturbation see Bioturbation continental shelves, 4:255–256 cosmogenic isotope concentrations, 1:681T deposition, slides and, 3:793 drifts see Sediment drifts estuarine see Estuarine sediments extraterrestrial material in, platinum group elements as tracers, 4:499–502, 4:501F flows see Sediment flows gas-bearing, Pressure Core Sampler (PCS) for, 2:50 ice rafting, 3:887 iron cycling, 4:566–567, 4:567F layering, Mediterranean, 1:113F layers see Sediment layers load, 4:755 magnetic signal, 3:26–27, 3:27F see also Geomagnetic polarity timescale (GPTS) nitrogen isotope ratios, 4:51–52 ocean margin see Ocean margin sediments paleoceanography see Paleoceanography particle size, bioturbation and, 1:398 phosphorus accumulation through Cenozoic, 1:518–519, 1:519F mobilization, 4:407 reservoir, 4:401, 4:403T, 4:407 see also Phosphorus cycle physiographic storage, 4:138T pore pressure, slides and, 3:795 profiles, bioturbation and, 1:397 radiocarbon content, sources, 5:419–420 river inputs, 4:754 sandy see Sandy sediments seafloor see Seafloor sediments suspended see Suspended sediments thermal conductivity, 3:43–44
602
Index
Sediment(s) (continued) transport see Sediment transport type, 00704.slumps and, 3:792 see also Pore water chemistry; Sediment sequences; entries beginning sediment Sedimentary acoustic medium, 1:75, 1:78 Sedimentary records high-resolution, Advanced Piston Corer (APC), 2:50 Holocene climate variability, 3:126 nitrogen isotope levels, 4:52, 4:53F productivity reconstructions, 5:333–343 examples, 5:338–340 coastal upwelling centers, 5:340–342, 5:340F equatorial upwelling, 5:339–340, 5:339F Matuyama opal maximum off southwestern Africa, 5:341F, 5:342 future directions, 5:342 proxies barite, 5:333, 5:337, 5:339F cadmium/calcium ratio (Cd/Ca), 5:337, 5:337F carbon isotope ratios (d13C), 5:333, 5:336–337 flux vs. nutrient, 5:336 microfossil assemblages, 5:333, 5:337–338, 5:338F nitrogen isotope ratios (d15N), 5:333, 5:337 opal, 5:333, 5:335–336 organic carbon, 5:333, 5:333–335, 5:335F oxygen demand, 5:335, 5:339F sea level changes and, 5:186–187, 5:189 see also Conservative elements (sea water); Sequence stratigraphy Sedimentary sequences calcium carbonate content, 3:912 clay minerals, 3:912 deposition rate, 3:911 magnetic susceptibility, 3:912 marine, at continental margin bioturbation, 3:911 monsoon activity and, 3:910 organic carbon content, 3:911–912 Sedimentation rate cyclic signals and, 4:314F slides and, 3:793 slumps and, 3:792 Sediment chronologies, 5:327–332 chronological determination, 5:327–329 example profiles, 5:329–331 radionuclides, 5:328T supply, 5:327 Sediment cores benthic flux measurement and, 4:486 bioturbation and, 1:397 dating, 3:881 depth and age, 4:311 high-accumulation-rate sediments, 3:881–883
oxygen isotope ratios, glacial cycles and, 4:505, 4:507 sea surface temperature determination from, 2:100 Waquoit Bay subterranean estuary, 3:95F Sediment core samples, geoacoustic parameters, measurement of, 1:75, 1:80–81, 1:83T SACLANTCEN samples, 1:81, 1:82F sample degradation, 1:81 X-ray tomography, 1:75, 1:76F Sediment drifts deep-sea see Deep-sea sediment drifts definition, 2:80 Sediment flows, 5:455–459 characteristics, 5:449T definition, 5:455, 5:465 initiation, 5:450 mass transport and, 5:447–467 recognition, 5:464 Sediment flux, 4:760 deep oceans see Deep-sea sediment drifts definition, 5:465 Sediment irrigation, 1:544F Sediment layers analysis of deep-sea samples at surface, limitations, 4:485 concentration gradients, recovery time after disturbance, 4:489 disturbance by landers, 4:488–489, 4:491–492, 4:493 oxygen concentration profile, 4:490 see also Benthic flux Sediment load, 4:755 Sediment mass transport, 4:142, 4:143F Sedimentology, 5:465 Sediment rating curve, 4:755 Sediment sequences, 4:144 pore water chemistry and, 4:564 Sediment stratigraphy see Sediment cores Sediment transport acoustic measurement, 1:38–51 bed topography, 1:40–42 case study, 1:44–48 flow, 1:42 instrumentation, 1:39, 1:39F see also Acoustic backscatter system; Acoustic Doppler current profiler; Acoustic ripple profiler; Coherent Doppler velocity profiler; Rapid backscatter ripple profiler limitations, 1:50 overview, 1:38–39 suspended sediments, 1:42–44 Intra-Americas Sea (IAS), 3:288, 3:289F polynyas, 4:544 processes, 1:38, 1:38F tides and, 4:141–142 waves on beaches, 6:310F, 6:313, 6:314 see also Large-scale sediment transport Sediment traps, temporal variability of particle flux, 6:1, 6:2F, 6:3F Seepage forces, seabed, slides and, 3:793
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Seepage meters, 3:92F, 3:94F, 5:551 groundwater detection and, 3:91–92 Seiches, 5:344–350 amplitude, 5:347, 5:348 Baltic Sea circulation, 1:296 closed basin model, 5:344F, 5:346 continental shelf, 5:346–347 currents, 5:344, 5:344F, 5:345F definition, 5:344 dynamics, 5:345–346 frequency, 5:345, 5:346, 5:347 frictional damping, 5:346, 5:347 harmonic modes, 5:346, 5:347 modes, 5:347 mouth correction, 5:347 mouth width, 5:347 node, 5:344F, 5:345F, 5:346 quarter-wave resonances, 5:347 radiation damping, 5:346–347, 5:347 sea-surface elevation, 5:345–346 forcing, frequency, 5:347 generating mechanisms, 5:347–350, 5:348F atmospheric pressure fluctuations, 5:348, 5:348F, 5:349 infragravity waves, 5:349 internal waves, 5:349, 5:349F storm surges, 5:348F, 5:531–532, 5:532 surface gravity waves, 5:347–348 see also Tsunami(s); Wave generation tidal association, 5:349–350, 5:349F tsunamis, 5:348–349 wind stress, 5:348 harbor, 5:344, 5:345, 5:346–347, 5:347–348, 5:348, 5:348–349, 5:348F abiki, 5:344, 5:349 harbor paradox, 5:347 Marrobbio, 5:349 rissaga, 5:344, 5:349, 5:350 history of study, 5:344–345 Chrystal, G, 5:345 Defant A, 5:345 Forel, F A, 5:345 Honda, K et al., 5:345 Merian’s formula, 5:344–345 Omori, F, 5:345 Wilson, B W, 5:345 lakes, 5:344 generation mechanisms, 5:348 Swiss lake studies, 5:345 Merian’s formula, 5:345 meteorological tsunamis, 5:349 modeling, 5:345 node, definition, 5:344, 5:344F, 5:345F observations, 5:347–350 partially open basin model, 5:345, 5:345F, 5:346–347 sea level, 5:344, 5:344F, 5:345F, 5:346, 5:348 surface gravity waves, 5:346 tide recorders, 5:345
Index see also Internal tides; Internal wave(s); Storm surges; Surface, gravity and capillary waves; Tide(s); Tsunami(s); Wave generation Seine estuary, France enrichment factor, 3:773T metal pollution, 3:771, 3:771T Seine nets, 2:536–537, 2:537F Atlantic salmon harvesting, 5:1 beach, 2:536, 2:536–537, 2:537F boat, 2:536, 2:537, 2:537F Danish, 2:537, 2:537F purse see Purse seines Scottish, 2:537 Seismic coupling coefficient, 3:840 Seismic experiments, historical, 5:361 Seismicity East Pacific Rise, 3:843F, 3:848F Galapagos Spreading Center, 3:843F global map, 3:837F global tectonic patterns, 3:839–841 hydrothermal, 3:847 hydrothermal systems and, 3:849–850 Mid-Atlantic Ridge, 3:842–843, 3:843F see also Mid-ocean ridge(s) (MOR) mid-ocean ridge, 3:837–851 monitoring, 3:838, 3:838F transform and segment boundary, 3:839–841, 3:839F see also Earthquakes; Seismometers Seismic layer 2A, 3:826 characteristics, 3:827–829 definition, 3:826 early studies, 3:826 evolution with age, 3:829 velocity increase, 3:829 layer 2A/2B transition, geological significance, 3:826–827 lithological transition, 3:826–827, 3:827, 3:827F porosity boundary, 3:827, 3:827F magma supply model, 3:861F P-wave velocities, 3:826, 3:827, 3:827F, 3:829 spreading rate, variation with, 3:834F see also Mid-ocean ridge seismic structure; Seismic structure Seismic moment, 6:131 Seismic observatories, 2:44 Seismic profiles deep-sea sediment drifts, 2:84F, 2:85 fracture zones, 5:364–365 Seismic reflections, sound speed gradients and, 5:352–353 Seismic reflection water-column profiling, 5:351–360 compared with other acoustic technology, 5:351–353 conductivity-temperature-depth profiler measurements and, 5:354 internal waves and, 5:358–359 method, 5:351 observations, 5:353–359, 5:353F Kuroshio Current, 5:354 ocean temperature and, 5:353F, 5:354 resolution, 5:352–353
Seismic stratigraphy, 4:138 Seismic structure, 5:361–366 accretionary prisms, 1:34 anomalous crust, 5:364–365 crustal systematic structure, 5:365–366 age dependence, 5:366 orientational anisotropy, 5:366 spreading rate, 5:365–366 data interpretation, 5:363–364 drill holes, 5:363 uncertainties, 5:364 data resolution, 5:361–362 gradient-change models, 5:362 large igneous provinces, 5:365 layer-cake models, 5:361, 5:363 inconsistency with data, 5:361–362 layer 2-3 transition, 5:363 mid-ocean ridge see Mid-ocean ridge seismic structure normal oceanic crust, 5:361–363 traditional vs. modern summaries, 5:362T velocity models, 5:362F Seismic tomography, mantle plumes, 3:222, 3:222F Seismo-acoustic waves, 1:78 arrival structure, 1:80, 1:80F body waves see Body waves compressional waves see Compressional waves ducted waves, 1:79, 1:79F head wave, 1:80, 1:80F, 1:88 interface waves see Interface waves Love waves, 1:78T, 1:79, 1:79F arrival times, 1:80, 1:80F mixed wave types, 1:80 shear waves see Shear waves water-sediment interface, 1:78–79, 1:79F wave generation, 1:78–79, 1:79 wave properties, 1:76–78, 1:78, 1:78T, 1:80 Seismogenisis, accretionary prisms, 1:34–35 Seismology sensors, 5:367–374 broadband instruments see Broadband (BB) ocean bottom seismometers considerations, 5:369–371, 5:373F hydrophones, 5:373–374 seafloor, 5:373 short period instruments see Short period (SP) ocean bottom seismometers see also Mid-ocean ridge seismic structure; Seismic structure Seismometers, 3:838, 3:838F broadband ocean bottom see Broadband (BB) ocean bottom seismometers short period ocean bottom see Short period (SP) ocean bottom seismometers Selective deposit feeders, 1:351–352, 1:352, 1:356 Selective tidal stream transport, 2:217 Selectivity issues, 1:652, 2:92, 2:203, 2:546
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Selenate, 6:80 depth profile, 6:78F Selenite, 6:80 depth profile, 6:78F Selenium (Se), 3:776, 3:782, 3:783 chemical speciation, 6:80 concentration N. Atlantic and N. Pacific waters, 6:101T in phytoplankton, 6:76T in seawater, 6:76, 6:76T depth profiles, 3:782, 3:782F, 6:78F dissolved forms, 3:782, 3:782F metabolic functions, 6:84 organic compounds, 6:78F oxic vs. anoxic waters, 3:782 see also Trace element(s) Selenocysteine, 6:80 Selenomethionine, 6:80 Self-contained imaging profiler (SCIMP), 1:712F Self Propelled Underwater Research Vehicle (SPURV), 4:473 Sellafield, UK, 4:82 EARP 99Tc pulse study, 4:87 location, importance of, 4:82 nuclear fuel discharges circulation of, 4:85–86 coastal circulation, 4:87 history, 4:86–87 regional setting, 4:85, 4:86F surface circulation, 4:87 radionuclides releases into ocean, 4:82 total discharges, 4:632, 4:632T Selli event, 4:320 Semaeostomae medusas, 3:10, 3:11F Semibalanus balanoides (acorn barnacle), 1:332, 4:763 Semidiurnal tides, 6:37 amphidromes, 6:37, 6:37F, 6:38, 6:39F equilibrium tide, 6:34, 6:35 internal tides, 3:259, 3:261, 3:262F resonance, 6:35–36, 6:36 spring/neap modulation, 6:34 Semi-enclosed evaporative seas, 4:128 Semi-taut moorings, 3:923–924, 3:924F, 3:925T Sensible heat flux, 6:164–165, 6:339 global distribution, 6:169F satellite remote sensing, 5:206–207 Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS), 5:120–121 Sensors acoustic survey work, 6:73–74 see also Ship(s); Sonar systems active, 3:108 aircraft for remote sensing see Aircraft for remote sensing backscattering, 3:246, 6:115 chemical see Chemical sensors depth, ROVs, 4:743 electromagnetic velocity, 2:253, 5:435 expendable see Expendable sensors
604
Index
Sensors (continued) hot film, 6:152 hyperspectral, 4:737–738 magnetic, archaeology (maritime), 3:698 meteorological, moorings, 3:922–923 passive, 3:108 pressure, strain gauges, 1:714F remotely operated vehicles (ROVs), 4:743 satellite see Satellite remote sensing seismology see Seismology sensors towed vehicles, 6:72–74 turbulence see Turbulence sensors Sensors for mean meteorology, 5:375–381 future developments, 5:381 Global Ocean Observing System (GOOS), 5:381 humidity, 5:377–378 pressure, 5:375 satellite measurements see Satellite measurements, meteorological temperature, 5:377 wind speed and direction, 5:375–377 see also Humidity; Pressure measurements; Temperature; Wind(s), direction; Wind speed Sensory systems cephalopods, 1:526 copepods, 1:648 demersal fishes, 2:464 dolphins and porpoises, 2:157–158 fish hearing, 2:476–477 fish lateral lines, 2:480–481, 2:480F fish schooling, 2:433–434 sperm and beaked whales, 3:648–649 see also Bioluminescence; Fish hearing and lateral lines; Fish vision Sentry, 6:263T Sepiidae (cuttlefish) buoyancy, 1:526 spawning, 1:527 Sepiolite, 1:261–262 Sequences, 4:144 controlling factors, 4:144–145 Sequence stratigraphy estimation of million year scale sea level variation, 5:192–193, 5:192F global sea level curve and, 5:192–193 limitations, 5:192–193 lower crust, 2:49 see also Deep-sea drilling Sequential t-test algorithm for analyzing regime shifts (STARS), 4:719, 4:720 Seriola quinqueradiata (Japanese amberjack), 3:539 Serpentine, accretionary prisms, 1:32 Serpulid polychaetes (feather dusters), 3:139, 3:140F Seston, 1:331 Set-down waves, 6:312–313 Set-up waves, 6:312–313, 6:313, 6:314 Sevastopol Eddy, 1:412–413, 1:412F Seven star flying squid (Martialia hyadesi), Southern Ocean fisheries, 5:518
Sewage bather shedding, potential risk to human health, 6:273T contamination, indicator/use, 6:274T coral exposure effects, 1:673 disposal, 6:271 potential risk to human health, 6:273T treatment, pathogen removal, 6:270, 6:271T Sewage outfalls, 4:59 Sewage-polluted waters, beaches, microbial contamination, 6:267 Sexual dimorphism, 2:160, 3:650 dolphins and porpoises, 2:149 eels (Anguilla), 2:211 killer whale (Orcinus orca), 2:149 mesopelagic fish(es), 3:750 pinnipeds (seals), 5:289 Rynchopidae (skimmers), 3:422–424 sperm whales (Physeteriidae and Kogiidae), 3:644–645 SFTRE (Salt Finger Tracer Release Experiment), 2:163–164, 2:164F SGD see Submarine groundwater discharge SGS see Subgrid-scale parameterization (SGS) Shackleton, Nicholas, 1:505–506 Shadowed image particle profiling and evaluation recorder (SIPPER), 6:366–368 Shadow regions, 1:102–103 Shag(s) cormorants vs., 4:373–374 plumage, 4:374 rock, behavioral displays, 4:377F see also Phalacrocoracidae Shallow water acoustic noise, 1:56 acoustic remote sensing, characteristic signal, 1:84, 1:84F acoustics see Acoustics, shallow water bottom topography, satellite remote sensing application, 5:105F, 5:107 ferromanganese oxide deposits, 3:488T storm surges dissipation, 5:532 wind waves, 5:538 surface, gravity and capillary waves dissipation, 5:576–577 gravity waves, 5:576 linear waves, 5:575 tides, 6:39 topographic eddies, 6:63 Shallow-water submersibles see Manned submersibles (shallow water); Remotely operated vehicles (ROVs) Shallow-water waves, 6:127 Shannon diversity index, 4:534, 4:535F Shanny (Lipophrys pholis), 3:282–283, 3:283F Sharks deep-water, 4:230–232 by-catch issues, 4:230–232 fishing pressure impact, 2:203
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liver size, acoustic scattering and, 1:67 market demand, 4:240–241 over-exploitation vulnerability, 4:232, 4:242 tropical fisheries development, impact, 1:651–652 world landings, 4:240 see also specific types ‘Sharon’ meddy see Meddy ‘Sharon’ SHARPS acoustic positioning system, archaeology (maritime), 3:698–699 Shatsky Rise, Kuroshio Extension, 3:364 Shear instability measurement, 2:296F see also Kelvin–Helmholtz shear instabilities Shear modulus, seafloor sediments, 1:78, 1:78T, 1:84–86 Shear probe, 2:294F, 2:295 Shear (airfoil) probes, 6:151–152 Shear/strain ratio, vortical modes, 6:288–289 Shear stress, 5:383 measurements see Momentum flux measurements resistance adaptations, 1:332 Shearwater(s), 4:590 Audubon’s, 4:590, 5:252 Cory’s, 5:253 Hutton’s, 5:253, 5:254F Manx, expansion of geographical range, 4:593 migration, 5:238F, 5:240–242, 5:241T pursuit plunging, 5:234 short-tailed, 4:593, 5:238 sooty see Sooty shearwater (Puffinus griseus) see also Procellariiformes (petrels) Shear waves acoustics in marine sediments, 1:78, 1:79–80, 1:79, 1:79F, 1:83, 1:83F, 1:87–88 horizontally polarized (SH), 1:79 velocity, 1:78T, 1:80, 1:82, 1:84F, 1:88, 1:89, 1:90F velocity-depth profile, 1:89 vertically polarized (SV), 1:79 see also Acoustic remote sensing waves on beaches, 6:315–316 generation, 6:315–316 root mean square (RMS) velocity fluctuations, 6:316 turbulence, 6:316 Shelf break, 4:139 internal tides, 3:260, 3:260F, 3:265 Shelf-dominated continental margins, 4:255–256 ecosystems, 4:257F, 4:258T primary production, 4:259T Shelf ecosystems, seabird abundance and, 5:228, 5:228–229 Shelf seas boundary conditions of model, 4:727 fronts, 5:391–400
Index circulation pattern, 5:395–396, 5:395F types, 5:391F metal pollution, 3:768F, 3:771F models, 4:722–731 seabed inclination, 5:397 Shelf slope, definition, 5:397 Shelf slope fronts, 5:397–398 carbon cycle and, 5:399 data collection, 5:397 implications, 5:398–399 modeling, 5:397 phytoplankton and, 5:398–399 position, 5:397–398 Shelikof Strait, SAR image, 5:107F, 5:108, 5:109–110, 5:110F Shellfish disease agents, mariculture, 3:520T farming see Mollusks; Oyster farming harvesting, 2:501 health limits, Mediterranean species mariculture, 3:536 see also specific species Shells, calcareous, cadmium/calcium ratio as productivity proxy, 5:337 Shelter Island, groundwater flux, 3:94, 3:94F Shepherd’s beaked whale (Tasmacetus shepherdii), 3:646 Shikmona eddy, 3:718–720, 3:719F, 3:720T Shikoku Basin, Kuroshio Current, 3:360–362 Shinkai (Japanese submersible), 3:505–506, 3:508, 3:511, 3:511F Shinkai 6500, 6:257T, 6:258F Ship(s), 5:409–418 acoustic noise, 1:53F, 1:55–56 data measurement, 1:55 directional spectra, 1:56 deep water, 1:56, 1:57F pedestal of high noise, 1:56, 1:58F shallow water, 1:56 frequency spectra, 1:55–56, 1:56F summation, 1:55–56, 1:56–57 very low frequency band (VLF), 1:55, 1:57 burial, 3:695 cargo, high-value, future developments, 5:408 construction, early history (archaeology), 3:697 container, 5:401–402, 5:403T, 5:404, 5:406T cruise ships, 5:404 discharges, environmental protection and Law of the Sea, 3:440 as drifter, 2:172 early history, timbers documented/ recovered, 3:697 ferry fleet, 5:404 financial performance see World fleet, financial performance general cargo, 5:404 general purpose vessels see General purpose vessels
ice-breaking, 4:481–482 Law of the Sea jurisdiction over, on high seas, 3:435 liner carriers, 5:404 observational disadvantages, 3:59 oceanographic research vessels see Oceanographic research vessels oldest intact, archaeology, 3:695 passenger vessels, 5:404 Phoenician, discovery, 3:699 refrigerated, 5:404 roll-on/roll-off (RoRo), 5:404 salinity and temperature measurements, 3:449–451, 3:450F, 3:452F size, 5:401 SST measurements, 4:222 sunken, undiscovered, 3:695 support, for manned submersibles (deep water), 3:509, 3:510–511, 3:511 tankers see Tankers temperature and salinity measurements, 6:165 wakes, satellite remote sensing application, 5:111–112, 5:112F wave-induced motion, effect on towed vehicles see Towed vehicles World War II, documentation, 3:698 see also Port(s); Shipping Shipbuilding, 5:407 boom, oceanographic research vessels, 5:411 nations undertaking, 5:407 prefabrication, 5:407 subsidies, 5:406, 5:407 support agreement, 5:407 Ship crew, deep-sea drilling, 2:52 Shipping, 5:401–408 activities, coral disturbance/destruction, 1:675–676 financial performance of ships see World fleet, financial performance future developments, 5:101, 5:408 container cargo flows, 5:408 high-value cargo ships, 5:408 improved container terminals, 5:408 investment returns, 5:405 law and regulation, 5:405 environmental issues, 5:406–407 ballast and bilge water, 5:407 hazardous cargoes, 5:406 tanker double hulls, 5:405, 5:406 liability and insurance, 5:407 P&I (Protection and Insurance) clubs, 5:407 third-party liability, 5:407 liner conferences see Liner conferences protectionism/subsidies see Protectionism/subsidies legal regimes controlling see Legal regimes protectionism and subsidies see Protectionism/subsidies, shipping world fleet see World fleet world seaborne trade see World seaborne trade
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605
see also Antifouling materials; Exotic species introductions; Port(s); Ship(s); World fleet Ship wakes, satellite remote sensing application, 5:111–112, 5:112F Shipwreck Kyrenia wreck raised by Michael Katzev, 3:697 as time capsule, archaeology, 3:695 torn apart by salvage ship, 3:696 Yassi Adav, excavation, 3:696 Shoaling, 6:310, 6:310F, 6:311–312, 6:312–313 pelagic fish see Pelagic fish Shoaling density surfaces, nutrient transport, mesoscale eddies, 5:481, 5:483F Shore-based hf radar, North Sea measurements, 4:78–80 Shore cleaning factors affecting, oil pollution, 4:192, 4:192F methods, for oil spills, 4:194 Shoreline migration, 3:49–58 past positions, glacial maximum and, 3:50F, 3:51, 3:52F sea level change and, 3:56–58 Australia’s past shorelines, 3:58 Europe’s past shorelines, 3:56–58, 3:57F ice-volume equivalent sea level function, 3:56, 3:56F South East Asia’s past shorelines, 3:56F, 3:57F, 3:58 see also Beach(es) Shoreline reconstruction Australia, Northwest Shelf, 3:58 Europe, 3:56–58, 3:57F South East Asia, 3:56F, 3:57F, 3:58 Shoreline sensitivity map, oil spill example, 4:197F oil pollution, 4:198 Shoreline stabilization hard, 1:583 soft, 1:583–584 Shore-zone ecosystems, 4:253–254 see also Estuaries; Mangrove forests; Salt marsh(es) Short-baseline tracking systems, 4:478 Short fin pearleye (Scopelarchus analis), 2:449F Short period (SP) ocean bottom seismometers, 5:367–369 characteristics, 5:368T, 5:369 GEOMAR-SP, 5:368T, 5:371F JAMSTEC-ORI, 5:368T, 5:369 SIO-IGPP-SP, 5:368T UTIG, 5:367F, 5:368T WHOI-SP, 5:368T, 5:370F Short-tailed shearwater (Puffinus tenuirostris), 4:593, 5:252, 5:279 Shortwave heat flux, global distribution, 6:169F
606
Index
Shortwave radiation penetration see Penetrating shortwave radiation upper ocean, 6:187 Shot peening, 3:925 Shrimp Alvinocaris lusca, 3:139F Rimivaris exoculata, thermal adaptations, 3:154 swarming, 3:139 symbiosis, 3:153, 3:153F SHRIMP, 6:256F, 6:256T Shrimps/prawns fisheries methods, 1:700 mortality, 1:700 freshwater species, 1:699–700 marine species, 1:700–701 see also Crustacean(s); Decapod shrimps (Caridea); Krill (Euphausiacea) Shuttle imaging radar (SIR), history, 5:104 Shy albatross (Diomedea caut), 4:593, 5:240 see also Albatrosses Siberian shelf, sea ice cover, 5:141 Sicily, Strait of see Strait of Sicily SICW see South Indian Central Water (SICW) Side-entry sub technology, 2:42–43, 2:42F Siderophores, 3:334, 3:338–339, 6:80–81, 6:105 definition, 6:85 see also Iron Side-scan sonar, bathymetry, 1:299 Sigma-coordinate, coastal circulation model, vertical approach, 1:573 Signal excess, sonar, 1:109–110 Signal-to-noise ratio, sonar, 1:109–110 Significant wave height, 6:312–313 definition, 6:312 Silica, 4:90–91 amorphous see Opal (amorphous silica, SiO2) concentration in river water, 1:627T cycle see Silica cycle mobile see Opal see also Biogenic silica Silica cycle, 3:331–342, 4:684–685, 4:684F basic concepts, 3:678 dissolved silicate measurement, 3:684–685 sources of, 3:680–681, 3:680F, 3:681T marine, 3:678–685, 3:680–681 measurement of rates of processes, 3:684–685 removal of silica, 3:681–682, 3:681T measurement, 3:684–685 see also Biogenic silica; Carbon cycle Silica ocean, 1:374 Silicate (Si[OH]4), 6:227 benthic flux, 4:486–487, 4:488F deposits, 1:265–266 mean oceanic residence time, 3:678
natural radiocarbon, 4:646, 4:646F profiles, 1:216F Black Sea, 1:405F rocks chemical weathering see Chemical weathering strontium isotopic ratios, Himalayan area, 1:517 sea water concentrations in distinguishing different water masses, 3:679–680, 3:679F impact of phytoplankton growth on, 4:680–681, 4:681F, 4:682F nitrate vs., 3:679F, 4:682, 4:683F, 4:684 supply/removal balance, 3:678 vertical profile, 3:335F, 3:678–679, 3:678–680, 3:679F, 4:682F see also Silica cycle Siliceous biogenic contourites, 2:86 Siliceous oozes, thermal conductivity, 3:43–44 Siliceous sponges, as biogenic silica in marine sediments, 3:683–684 Silicic acid, depth profiles, 6:77F Siliclastics, 4:140–141, 4:141 Silicoflagellates as biogenic silica in marine sediments, 3:683–684 opal as productivity proxy, 5:336 Silicon (Si), 4:587 biogenic, total flux, 1:372–373, 1:373–374, 1:374F cosmogenic isotopes, 1:679T production rates, 1:680T reservoir concentrations, 1:681, 1:681T specific radioactivity, 1:682T tracer applications, 1:683T radiolarian skeletons, 4:615 role in harmful algal blooms, 4:441–442 Silicon-32, tracer applications, 1:686 Silicon-35, cosmogenic isotopes, oceanic sources, 1:680T Silicon cycle, 4:90F Silicon:germanium ratio, as weathering vs. hydrothermal input tracer, 3:780 Sill-overflow systems, rotating gravity currents, 4:791F, 4:793–794 Sills, Intra-Americas Sea (IAS), 3:287, 3:291–292 Silt, geoacoustic properties, 1:116T Silty contourites, 2:85 Silver anthropogenic, 1:549 in sewage, 1:200 Silver eels see Eels Silver hake, biomass, north-west Atlantic, 2:505–506, 2:506F Silver nitrate, 1:711–712 Silvery John Dory (Zenopsis conchifera), 2:483, 2:483F Silvia Ossa, 4:770F SIMBIOS (Sensor Intercomparison and Merger for Biological and
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Interdisciplinary Oceanic Studies), 5:120–121 SIMI (Sea Ice Mechanics Initiative), 1:92–93 Simple opening/closing nets, zooplankton sampling, 6:355–356, 6:358F Simpson’s index, 4:534 Simulated annealing schemes, direct minimization methods, in data assimilation, 2:8 Simultaneous localization and mapping (SLAM), 4:478–479 Single-beam echo sounders, bathymetry, 1:298, 1:299 Single compound radiocarbon measurements, 5:419–427 analysis methods, 5:422–423 accelerator mass spectrometry (AMS), 5:424 compound selection, 5:422–423 compound separation and isolation, 5:423–424 process, 5:424F applications, 5:424–426 lipid biomarkers, 5:422F, 5:423F, 5:425–426 monosaccharides, 5:426–427 bomb carbon and, 5:421F carbon isotopes, 5:420 organic carbon reservoirs, 5:419F radiocarbon distribution mechanisms, 5:421 anthropogenic, 5:421–422 natural, 5:421 radiocarbon systematics, 5:420–421 see also Radiocarbon Single point current meters, 5:428–435 acoustic Doppler see Acoustic Doppler current meters acoustic travel time see Acoustic travel time (ATT) current meters calibration, 5:433–434 characteristics, 5:430T design, 5:428–429, 5:429F directional measurement, 5:433 bar magnet, 5:433–434 fluxgate compass, 5:433–434 electromagnetic see Electromagnetic current meters evaluation, 5:433–434 evolutionary trends, 5:429F, 5:430T, 5:434F, 5:435 historical aspects, 5:428 intercomparison, 5:433–434 measurement problems, 5:428 near surface, 5:428 surface wave zone, 5:428–429 mechanical, 5:429F, 5:431 platforms, 5:428 see also Moorings remote sensing, 5:429F, 5:433 vector averaging current meter, 5:429–431, 5:429F, 5:430T, 5:432 vector measuring current meter, 5:432
Index see also Ocean circulation; Sonar systems; Three-dimensional (3D) turbulence; Turbulence sensors Single-scattering albedo, 4:622–623 Single turnover fluorescence induction, 2:583 Singular value decomposition (SVD), 3:316 least-squares solution by, 3:315, 3:316 Sinking, deep convection, 2:20–21 Sinking phase, 4:126, 4:126–127 see also Ocean Subduction SIO see Scripps Institute of Oceanography SIO/IGPP-BB ocean bottom seismometer, 5:369T, 5:370F SIO/IGPP-SP ocean bottom seismometer, 5:368T SIO/ONR ocean bottom seismometer, 5:369T, 5:372F Siphonophores, 3:10–12 bioluminescence, 1:378 Calycophorae, 3:12, 3:13F Cystonectae, 3:12, 3:13F fragility of colonies, 3:12 Physonectae, 3:12, 3:13F SIPPER (shadowed image particle profiling and evaluation recorder), 6:366–368 Sir Alister Hardy Foundation for Ocean Science (SAHFOS), 1:630 open access data policy, 1:631 training provided by, 1:631 see also Continuous Plankton Recorder (CPR) survey Sirenians, 3:605, 3:610, 3:610F, 5:436– 446 behavior, 5:440–442 classification, 3:589, 3:589T, 3:608T, 5:436–437 family Dugongidae see Dugongidae family Trichechidae see Manatees conservation, 5:442–444 status, 3:608T distribution, 5:436–437 ecology, 5:442 evolution, 3:593–594, 5:436 fossil history, 5:436 exploitation, 3:635, 3:639–640, 5:442–443, 5:444F future outlook, 5:442–444 grinding molars, 3:616F mating behavior, 5:441–442 migration and movement patterns, 3:603 morphology, 5:439–440, 5:441F physiology, 5:440 population biology, 5:442 social organization, 5:440–442 species extinct, 3:594–595, 5:436 living, 3:589T, 3:594–595, 3:595F, 5:436–437 threats, 5:442–443, 5:443F, 5:444F, 5:445F see also Marine mammals; specific species
Site Survey Panel (SSP), deep-sea drilling, 2:53 Size-based population models, 4:554 see also Population dynamic models Skagerrak, Baltic Sea circulation, 1:288, 1:289F, 1:294 Skampton ratio, 3:790 Skate (USS), 1:92 Skimmers see Rynchopidae (skimmers) Skin of the ocean, satellite remote sensing of SST, 5:93–94 Skipjack tuna (Katsuwonus pelamis) pole and line fishing, 4:235–236 response to changes in production, 2:486–487 Skipper 1, 4:770F Skuas migration, 5:244 see also Charadriiformes Skylab, 5:68 ‘Slab’ models, upper ocean mixing, 6:191 SLAM (simultaneous localization and mapping), 4:478–479 Slepian model representation (SMR), 4:775–776 Slide blocks, 5:451F Slides, 5:451–452 basal shear zone, 5:457F characteristics, 5:449F, 5:449T, 5:451 definition, 5:451 deposits, 5:447 dimensions, 5:455T glide plane, 5:454F global distribution, 3:795F gravity-based mass transport/sediment flow processes and, 5:447–467 headwalls, pore pressure and, 3:796 mechanical classification, 5:447 methane hydrate and, 3:790–798, 3:793–795 recognition, 5:464 slope inclination and, 3:793 slumps and, 3:790 trigger mechanisms, 3:793 tsunamis and, 6:132 see also Gaviota slide; Goleta slide; Slumps Slip deficit, 3:840 Slipper limpet see Crepidula fornicata (slipper limpet) Slipper oyster, production, 4:275T Slocum glider, 3:60, 3:61F, 3:62 Slope apron, 4:143F Slope convection, Red Sea circulation, 4:671, 4:673 Slope-dominated continental margins, 4:255, 4:255F ecosystems, 4:257F, 4:258T primary production, 4:259T Slope to Shelf Energetics and Exchange Dynamics (SEED) project, 6:202–203 Slope Water gyre, 2:562–563 SLOSH (Sea, Lake and Overland Surges from Hurricanes) model, storm surges, 5:536
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Slow-spreading ridges, 3:852 abyssal hills, 3:864–865 axial depth profile, 3:854 crustal thinning, 3:855–856 eruption frequency, 3:862 lava morphology, 3:815–816, 3:816F, 3:862 magma composition, fractional crystallization, 3:821–822 magma upwelling, 3:855–856 seismic structure axial magma chamber (AMC), 3:832, 3:833F, 3:834, 3:835–836, 3:835F crustal formation, 3:833–834 layer 2A, 3:834, 3:834F see also Mid-Atlantic Ridge (MAR) vent fauna biodiversity, 3:157 see also Fast-spreading ridges; Mid-ocean ridge geochemistry and petrology; Mid-ocean ridge tectonics, volcanism and geomorphology; Propagating rifts and microplates; Spreading centers Slumping, gas hydrates and, 3:785, 3:787F Slumps, 5:452–455 brecciated zone, 5:457F characteristics, 5:449F, 5:449T, 5:452 compressional folding, 5:456F cross-section, 5:456F definition, 5:452 deposits, 5:447, 5:457F dimensions, 5:455T folding, 5:456F gravity-based mass transport/sediment flow processes and, 5:447–467 mechanical classification, 5:447 recognition, 5:464 slides and, 3:790 see also Slides Slush ice, 5:86 Small-bodied fishes, harvesting, 2:500–501 Small-scale patchiness behavior (planktonic) affecting, 5:485–486 coastal processes affecting, 5:481–485 homogenous isotropic turbulence affecting, 5:475F, 5:476–477 models see Small-scale patchiness models ocean currents affecting, 5:474 organisms affecting, 5:474 physical–biological–chemical interactions, 5:474, 5:481 space–time fluctuations, 5:474, 5:476F, 5:486–487 Small-scale patchiness models, 5:474–487 behavior (planktonic), 5:485–486 fluid transport effects with, 5:485–486 swarm maintenance, 5:485 coastal processes, 5:481–485 coupled physical–biological models, 5:474–476, 5:481, 5:486–487 coupled problem, formulation, 5:474–476
608
Index
Small-scale patchiness models (continued) advection-diffusion-reaction equation, 5:474, 5:476, 5:481 growth and diffusion (‘KISS’) model, 5:476 homogenous isotropic turbulence, 5:475F, 5:476–477 chlorophyll spatial variability, Gulf of St Lawrence, 5:477, 5:477F Denman and Platt model, 5:477, 5:477F individual-based (planktonic behavior), 5:485 mesoscale processes, 5:479–481 implications, 5:481 internal weather of sea, 5:479–481 mesoscale jet, meander systems, 5:481, 5:482F one-dimensional physical models, 5:478, 5:479F process-oriented numerical, 5:486–487 recent advances affecting, 5:487 sampling of scales (‘small’), 5:474, 5:475F two-dimensional advection-diffusionreaction equation, 5:474, 5:476, 5:481 two-dimensional physical–biological models, 5:481 vertical structure, 5:477–479 broad-scale, 5:478–479 deep chlorophyll maximum (DCM), 5:477–478, 5:477F four-compartment planktonic ecosystem model (nitrogen flow), 5:478, 5:478F impact of near-inertial waves, 5:478–479 one-dimensional physical model of upper ocean, 5:478, 5:479F thin layers, high-resolution fluorescence measurements, 5:478–479, 5:480F Small-scale reefs, topographic eddies, 6:57–58 Small subunit ribosomal RNA (SSUrRNA), 1:269, 1:270F SMC (South-west Monsoon Current), 1:733, 3:232–233 Smectites, 1:266 composition, 1:267F, 1:567T diagenetic reactions, 1:266T distribution, 1:266–268, 1:564 Indian Ocean, 1:565F reworking, 1:564 Smelting, 3:895–896 Smithsonian Tables, 5:377–378 SMMR see Scanning multichannel microwave radiometer Smolts, salmonid farming, 5:24–25 Smooth transitions, regime shifts, 4:702 SMOS (soil moisture and ocean salinity), 5:129 SMOS satellite, 6:166 SMOW (Standard Mean Ocean Water), 1:502
SMS see Sources minus sinks SNAP 9A, radioactive wastes, 4:634 Snappers, tropical fisheries development, impact, 1:651–652 Snares penguin, 5:522T, 5:524–525 see also Eudyptes (crested penguins) Snellius I expedition, 5:316 Snell’s law, 1:102, 1:104, 1:105F, 1:108–109, 6:42 Snow cover, 5:170 d18O values, 1:503, 1:504F ‘Snowball earth,’ sea level fall and, 5:186 Snow crab see Chionoecetes (snow, tanner crab) Snow petrels (Pagodroma nivea), 4:594 see also Procellariiformes (petrels) Snurrevaads see Danish seines SO see Southern Oscillation (SO) Social science, disciplines, marine policy research foci, 3:665–666, 3:665T Sockeye salmon (Oncorhynchus nerka), 2:400F, 5:30–31, 5:33, 5:33F, 5:36 population time series, 4:703F Socotra Gyre, 5:501, 5:501F Sodium (Na) concentrations river water, 1:627T, 3:395T sea water, 1:627T determination, 1:626 cosmogenic isotopes, 1:679T production rate, 1:680T reservoir concentrations, 1:681T Sodium-22, cosmogenic isotopes, oceanic sources, 1:680T Sodium chloride electrolytic dissociation, 2:247–248 see also Chloride (Cl-); Salinity SOFAR float, 2:176 SOFIA (State of Fisheries and Aquaculture report), 3:576 Soft-shell clam (Mya arenaria), 2:332 Software, autonomous underwater vehicles (AUV), 4:477 SOI see Southern Oscillation Index (SOI) Soil(s) particulate emission, 1:248 nitrogen, 1:255T phosphorus, 4:401, 4:403T, 4:406F see also Phosphorus cycle Soil moisture and ocean salinity (SMOS), 5:129 SOIREE see Southern Ocean Iron Enrichment Experiment (SOIREE) Solar constant, 3:114 Solar energy, ocean thermal energy conversion, 4:167 Solar heat, 4:129 Solar irradiance spectrum, 5:116F Solar nebula, water for origin of oceans, 4:263, 4:263F Solar radiation, 3:244 cloud cover and, 6:339 clouds and, 5:205 emission levels, glaciation and, 1:5 infrared range, 3:244
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ocean surface, 6:339 open ocean convection, 4:223–224 penetration, consequences of, 4:379 satellite measurements by radiative transfer models, 5:380 seasonal variations, Southern Oscillation and, 2:244, 2:245 ultraviolet range, 3:244 visible range (light), 3:244 see also Insolation; Radiative fluxes Sole (Solea senegalensis), 2:334 Sole (Solea solea), 2:376 Solea senegalensis (sole), 2:334 Solea solea (sole), 2:376 Solenosmilia variabilis coral, 1:615–616 Solid-phase extraction (SPE), 6:104, 6:104T Solid waste dumping coral disturbance/destruction, 1:674–675 see also Ocean dumping Solitons, 4:788, 6:213 generation, 3:267 interfacial waves, 3:266–267, 3:267F internal tides, 3:258, 3:261, 3:262F, 3:264 rotational effect, 3:267 seiche generation, 5:349–350 surface, gravity and capillary waves, 5:578 Solubility pump, 1:481–484, 1:481F, 1:482F see also Carbon cycle; Carbon dioxide Somali Current, 1:734, 5:494–503, 5:495–501 at depth, 5:501–503 seasonal variations, 5:501–502, 5:502F Great Whirl, 1:732, 5:496–497, 5:499–501, 5:500F, 5:501F during monsoon transition periods, 1:732, 5:495, 5:499–501 current profile, 3:227, 3:228F salinity, 5:497–499, 5:499F, 5:501F Socotra Gyre, 5:501, 5:501F Southern Gyre, 5:496, 5:501F studies, 1:732, 5:494, 5:495, 5:503 during summer monsoon, 1:236, 1:732, 5:495, 5:497F, 5:498F current profiles, 1:235F, 1:236, 3:227, 3:228F early phase, 5:496, 5:497F late phase, 5:499–501, 5:501, 5:501F upwelling wedge formation, 1:732, 5:496–497, 5:498F during winter monsoon, 1:732, 5:502F current profiles, 3:227, 3:228F, 5:502F see also Indian Ocean current systems; Indian Ocean equatorial currents; Monsoon Somateria mollissima (eider duck) fisheries interactions, 5:270–271 see also Seabird(s) Somatic coliphages, sewage contamination, indicator/use, 6:274T
Index Sonar, 1:109, 5:504 autonomous underwater vehicles (AUV), 4:479–480 echo integration, 1:62 figure of merit, 1:109–110, 1:110 fish, 1:62 marine animals, development, 1:62 side-scan, 1:299 signal excess, 1:109–110 surface wave profiling, 1:433 see also Acoustic navigation; Echo sounders; Upward-looking echo sounders Sonar equation, 1:109–110 active, 1:110 passive, 1:109–110 Sonar (Sound Navigation and Ranging) systems, 5:504–512 active sonar, 5:505–508 absorption limits range, 5:507 absorption loss, 5:506–507, 5:507F active sonar equation, 5:506 ambient noise, 5:505 beamformers, 5:505, 5:506, 5:507F echoes, 5:505 see also Acoustics, deep ocean history, 5:504 maximum operating range, 5:506–507 noise-limited, 5:506 operating frequency, 5:506 pulse repetition frequency (PRF), 5:505 Rayleigh region, 5:507 receivers, 5:506, 5:507F resolution, 5:506–507 reverberation, 5:505 scattering losses, 5:507 see also Acoustics, shallow water scattering strength, 5:506 see also Acoustic scattering (marine organisms) side-scan, 5:506 synthetic aperture, 5:506 target cross-section, 5:507 transmitters, 5:505, 5:505F typical operating frequencies, 5:507, 5:508T active sonar image examples, 5:509 multibeam bathymetric mapping, 5:509, 5:510F seafloor mapping, 5:509, 5:509F unmanned underwater vehicle (UUV), 5:509 advanced beamforming, 5:512 plane wave model, 5:512 wavefront curvature, 5:512 components, 5:507–508 beamforming, 5:508–509 electronic array processing, 5:509 spatial resolution, 5:508 reverberation-limited environment, 5:505F, 5:507–508 waveform design, 5:504 Doppler gating, 5:508
optimum design, 5:508 range gating, 5:508 definition, 5:504 history, 5:504–505 passive sonar, 5:509–510 applications, 5:509 equation, 5:509–510 history, 5:504 passive sonar beamforming, 5:510–511 bearing-time recording, 5:511–512 bearing-time processing, 5:511 directional components, 5:511 display formats, 5:511 FRAZ displays, 5:512 frequency domain beamforming, 5:511 LOFAR (Low Frequency Acoustic Recording and Analysis), 5:511–512 time-series display formats, 5:511, 5:511F trackers, 5:512 shallow-water, 1:112 side-scan sonars, in archaeology, 3:698 Songs, marine mammals, 1:360–361, 3:618, 3:618F, 3:619F see also Marine mammals, bioacoustics Sonic anemometers, 5:376F, 5:377, 5:386, 5:386F Sonic thermometers, 5:388 Sonograph, 3:192F Sontek Argonaut-ADV acoustic travel time, 5:430T Sooty shearwater (Puffinus griseus), 4:591F climate change responses, 5:260–261, 5:260F, 5:262 exploitation of inshore and offshore resources, 5:255 migration routes, 5:240–242, 5:243F see also Shearwater(s) Sooty tern, 3:423F see also Sternidae (terns) SOSUS (Sound Surveillance System), 3:168, 3:839 Sotalia fluviatilis (tucuxi), 2:149, 2:156 Soucoupe, Cousteau, Jacques, 3:513 Sound(s) made by marine mammals see Marine mammals, bioacoustics physics, 1:357–358 see also Marine mammals and ocean noise Sound fixing and ranging (SOFAR), 3:702–703 Sound fixing and ranging (SOFAR) floats, 4:27–28 Sound propagation research, sonar systems, 5:504 Sound ranging and fixing (SOFAR) channel, 3:839 Sound speed, 1:101, 6:41–42, 6:54–56 Arctic, 1:94–95 depth profile, 1:101F Atlantic, 1:102F North Atlantic, 6:42F
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sea surface temperature and, 5:352F seawater, 6:380T, 6:382 shallow water, 1:113F temperature and, 1:112 variability, 1:112 temperature and, perturbation, 6:56, 6:56F temperature conversion, 6:54–56 see also Deep sound channel Sound Surveillance System (SOSUS), 3:168, 3:839 Sound velocity probe, expendable, see also Expendable sensors Source flux, overflows and cascades, 4:266 Sources minus sinks (SMS) of a variable, 4:93 NP models, 4:98 Sousa spp. (humpback dolphins), 2:153 South Africa fishing policy, regime shifts and, 4:705 rocky shore nutrient/productivity models, 4:765F, 4:766, 4:768 South America cholera epidemic, 1991, 2:340 El Nin˜o region, interannual variability, 2:237 El Nin˜o Southern Oscillation, precipitation, 2:230–231 river water, composition, 3:395T South American coral (Oculina patagonica), 2:332–333 South American shelf oxygen concentration, 1:263F phosphate concentration, 1:263F Southampton Water, UK, thermal discharges, effects of, 6:13–14, 6:14 South Atlantic (Ocean) Agulhas rings, 3:119 carbonate compensation depth, 1:453F deep and abyssal waters, 6:296–297, 6:296F dust deposition, 1:254T rates, 1:122T dust deposition rates, 1:122T organochlorine compounds, 1:123T, 1:246T regime shifts, drivers, 4:714 river inputs, 4:759T South Indian Ocean and, interbasin exchange of waters, Agulhas rings in, 1:134–135, 1:135T see also Atlantic Ocean South Atlantic Bight, submarine groundwater discharge (SGD), radium, 5:556F South Atlantic Central Water (SACW) Brazil Current, 1:422, 1:424F temperature–salinity characteristics, 6:294T, 6:297F South Atlantic Current transport, 1:724T see also Atlantic Ocean current systems South Atlantic heat transport, 4:129
610
Index
South Atlantic Ventilation Experiment (SAVE), 4:641–642 South Atlantic Water, 2:561 South Caribbean Sea, regional models (baroclinic circulation model), 4:727–729, 4:729F South Carolina, groundwater flux, 3:93F South China Sea, 5:305 monsoons, historical variability, 3:914–915 Radarsat ScanSAR image, 5:110–111, 5:111F seasonal variability, 5:310 upper layer velocity, 5:314F winds, 5:306 Southeast Asia artificial reefs, 1:227 El Nin˜o events and, 2:228 paleo shorelines, migration and sea level change, 3:56F, 3:57F, 3:58 Southeast Asian rivers dissolved solid concentration, 4:760F sediment discharge, 4:757 Southeast Asian seas, 5:305–316, 5:305F air–sea heat flux, 5:306 currents, surface, 5:311–314, 5:313F, 5:314F evaporation, 5:310F Indian Ocean and, 5:314–315 Indonesian Throughflow and, 5:315 mass transport, 5:314 meteorology, 5:306 precipitation, 5:307, 5:309F salinity, 5:309–311, 5:310–311, 5:312F sea surface temperatures (SST), 5:309, 5:311F surface forcing, 5:306 surface freshwater, 5:306–308 surface heat, 5:306, 5:308F tides, 5:315–316, 5:315F upper ocean circulation, 5:312, 5:313F upper ocean variability, 5:308–311 winds, 5:306, 5:307F see also Banda Sea; Celebes Sea; South China Sea South-east Atlantic, seabird responses to climate change, 5:264 prehistoric, 5:258 Southend (Thames Estuary, UK), tidesurge interaction, 5:534F South Equatorial Countercurrent (SECC), 1:733, 3:233–234, 3:235F, 5:495 flow, 1:721–723, 4:287F, 4:288, 4:288F velocities, 3:234 latitudinal range, 3:234 satellite-tracked drifting buoy trajectories, 3:235F, 3:236 transport, 1:724T, 3:234, 5:495, 5:496F see also Atlantic Ocean current systems; Atlantic Ocean equatorial currents; Pacific Ocean equatorial currents South Equatorial Current (SEC), 1:234, 1:234F, 1:425, 1:720–721, 1:730, 1:731F, 3:234–236, 3:235F, 5:312–313, 5:495
flow, 1:723F, 4:287F, 4:288, 4:288F, 4:290F, 4:291F Indonesian Throughflow and, 3:238–239 latitudinal range, 3:234–235 salinity, 1:730, 3:234–235 satellite-tracked drifting buoy trajectories, 3:235F, 3:236 transport, 1:724T, 3:234–235 velocities, 3:234–235 see also Atlantic Ocean current systems; Atlantic Ocean equatorial currents; Pacific Ocean equatorial currents South Equatorial Undercurrent (SEUC) flow, 1:721–723, 1:723F transport, 1:724T see also Atlantic Ocean current systems; Atlantic Ocean equatorial currents Southern Antarctic Circumpolar Current front, 1:179F water properties, 1:180F Southern bluefin tuna (Thunnus maccoyii), 2:404–405, 3:444–445 Commission for the Conservation, 4:242 Southern blue whiting, acoustic scattering, 1:66 Southern California Bight, 4:102F Southern California Countercurrent, 1:459, 1:460F Southern California Eddy, 1:459, 1:460F Southern Caribbean Sea, regional models (baroclinic circulation model), 4:727–729, 4:729F Southern elephant seal (Mirounga leonina), 5:513 Southern Gyre, 5:496, 5:501F Southern hemisphere carbon dioxide sinks, 1:491 chlorofluorocarbons, 1:531–532, 1:532F particulate organic carbon, 1:122–123 sea ice, 5:170 seasonal thermocline, 6:180T sparse salinity data, 5:127 subtropical gyre, 4:121 Southern monsoon, Indonesian Throughflow, 3:241F Southern Ocean, 6:231 bathymetric map, 1:186F benthic foraminifera, 1:339T current systems, 1:735–743, 1:736F Antarctic Circumpolar Current see Antarctic Circumpolar Current (ACC) salinity and, 1:736–738, 1:737F water density and, 1:736, 1:737F water temperature and, 1:736–738, 1:737F Weddell Gyre see Weddell Gyre wind stress and, 1:735F, 1:736 see also specific currents deep convection within, 1:420 ferromanganese oxide deposits, 3:488T fisheries see Southern Ocean fisheries fronts, 6:183–184, 6:184F impact of conditions on fish, 1:191 internal waves, 3:271
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isolation, 1:191 krill see Krill (Euphausiacea) mixing, 2:267–268 nitrate and phytoplankton uptake thereof, 4:48F opal flux, 5:335–336 overturning, 1:735–736 biogeochemical cycles and, 1:189 overturning circulation, 1:188–189, 4:128, 4:129F phytoplankton and nitrate consumption, 4:46 predicted sea level rise, 5:183 radiocarbon, 4:641F, 4:642 concentrations, 3:307–310 rare earth elements, vertical profiles, 4:655, 4:658F sea–air flux of carbon dioxide, 1:493T seabird responses to prehistoric climate change, 5:257–258 sea level, 1:186F sea surface height, latitude and, 1:187F sedimentary nitrogen isotope ratios, 4:53F stratification, 1:179–181 temperature variations, 1:191 warming, 1:188 water properties, latitude and, 1:180F wind driven circulation, 6:354 see also Antarctic fish(es); Antarctic Ocean; Polar ecosystems Southern Ocean Current, 3:445 see also Southern Ocean, current systems Southern Ocean fisheries, 5:513–519 albatross by-catch issues, 5:517 CCAMLR see Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) competitor removal effects, 2:205–206 crabs, 5:517 finfish, 5:514–515 historical aspects, 5:513 krill see Krill mackerel icefish, 5:515–517 management regime, 5:518 seal populations, harvesting impact, 2:205–206, 5:513 squid, 5:517–518 toothfish see Toothfish whale populations, harvesting impact, 2:205–206, 2:510–511, 5:513 Southern Ocean Iron Enrichment Experiment (SOIREE), 3:335, 3:336, 4:588, 6:92 questions remaining, 3:340 results, 3:337, 3:339 see also Iron fertilization Southern Oscillation (SO), 2:228, 2:241, 2:244, 5:88–89 atmospheric pressure and, 2:230F damped oscillation effects, 2:241 definition, 2:242 global effects, 2:238 gradual modulation of, 2:244–245 long-term variability, 2:238
Index models, 2:245 see also El Nin˜o Southern Oscillation (ENSO) models thermocline depth effects, 2:245 weather prediction and, 2:242 Southern Oscillation Index (SOI), 2:228, 2:231F time series 1866-1998, 2:238F Southern phocids see Monachinae (southern phocids) Southern Subsurface Countercurrent (SSCC) flow, 4:287F, 4:289, 4:290F see also Pacific Ocean equatorial currents Southern Weddell Sea hydrographic section over continental slope, 5:544F tidal model, 5:549F South Indian Central Water (SICW), 3:447, 3:449F temperature–salinity characteristics, 6:294T, 6:298, 6:298F South Indian Ocean currents, 1:128, 1:728, 1:730–731, 1:731F see also specific currents dust deposition, 1:254T Rossby waves, 4:784F South Atlantic Ocean and, interbasin exchange of waters, Agulhas rings in, 1:134–135, 1:135T see also Indian Ocean South Intermediate Countercurrent (SICC), 1:723F South Java Current, intraseasonal variation, 3:242 South Pacific dust deposition rates, 1:122T El Nin˜o, rainfall, 2:236F gravity anomaly, 3:85F heat transport, 3:117–118 lead profile, 1:195, 1:196F organochlorine compounds, 1:123T, 1:246T regime shifts, drivers, 4:714 river inputs, 4:759T South Pacific Convergence Zone, El Nin˜o Southern Oscillation and, 2:230 South Pacific Current, 4:388 South Pacific Ocean dust deposition rates, 1:122T organochlorine compounds, 1:123T, 1:246T radiocarbon, 4:643–644, 4:644F, 4:645F river inputs, 4:759T South-western Africa, Matuyama Diatom Maximum, productivity reconstruction, 5:341F, 5:342 Southwest Indian Ridge, 3:867–868, 3:876F South West Indian Ridge, morphology, 3:870F South-west Monsoon Current (SMC), 1:733, 3:232–233 Soviet-Japan Fisheries Commission, 5:20
Soviet Union Arctic research, 1:92–93 see also Russia Soviet Union North Pole Drifting Stations program, 5:159 Soya Current, 4:202F, 4:203 eddies, 4:203, 4:203F Soya Strait, 4:200F, 4:201, 4:203 Space, components of global climate system, 2:48F Spacecraft instruments, 5:94–95 Advanced Very High Resolution Radiometer (AVHRR) see AVHRR Along-Track Scanning Radiometer see Along-Track Scanning Radiometer (ATSR) black-body calibration, 5:94 cooled detectors for infrared radiometers, 5:94 geosynchronous orbit measurements of SST, 5:97 GOES Imager, 5:97 Moderate Resolution Imaging Spectroradiometer see Moderate Resolution Imaging Spectroradiometer (MODIS) TRMM Microwave Imager see TRMM Microwave Imager (TMI) Space Shuttle Challenger disaster, 3:517 Spaghetti worm (Saxipendium coronatum), 3:140–141, 3:141F Spain aquaculture development levels, 3:535 see also Mediterranean species, mariculture artificial reefs, 1:228F Spanish galleon, relocated by treasure hunters, 3:700 Spartina alterniflora (salt marsh cord grass), 4:254, 5:40–41, 5:46–47, 5:47 Sparus aurata (gilthead sea bream), mariculture Italian market, 3:535 marketing problems, 3:536 production systems, 3:534, 3:535 stock acquisition, 3:532 Spatial discretization, coastal circulation models, 1:573 Spatial scales, forward numerical models, 2:609 Spawning cephalopods see Cephalopods copepods, 1:647 coral reef fishes, 1:657 cuttlefish (Sepia spp.), 1:527 deep-sea fishes, 2:71 demersal fishes, 2:464–465 eels see Eels (Anguilla) exotic species introductions, ships’ hulls, 2:337 intertidal fishes, 3:284, 3:284–285 mesopelagic fish(es), 3:749–750 Octopodidae (octopuses), 1:527 salmonid farming, 4:148, 4:149
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salmonids, stock enhancement/ocean ranching, 4:148, 4:149 Sepiidae (cuttlefish), 1:527 sprat, 2:505–506, 2:507F see also Fish reproduction SPCZ (South Pacific Convergence Zone), El Nin˜o Southern Oscillation and, 2:230 Spearfish (Tetrapturus), utilization, 4:240 Spearfishing, coral impact, 1:673 Special Sensor Microwave/Imager (SSM/ I), 2:329, 4:543, 5:80, 5:81–82, 5:84, 5:85F, 5:88–89, 5:88F, 5:206, 5:207, 5:380 Special sensor microwave temperature sounder (SSM/T), 5:207 Species diversity indices, 4:534–535 latitude and, 4:356, 4:357T see also Marine biodiversity Species flocks, Antarctic fishes, 1:191 Species interactions, ecosystems, fishing effects, 2:205 Species matrix, 4:533, 4:534F Species replacements, ecosystems, fishing effects, 2:206, 2:206F Specific gravity, 6:379–381 Specific heat capacity, 1:696 Specific humidity, definition, 2:325T Specific volume anomaly, seawater, 6:381 Spectacled porpoise (Phocoena dioptrica), 2:154, 2:159 Spectra absorption see Absorption spectra infrared, 5:91, 5:92F reflectance, water types, 4:733F Spectral absorption coefficient see Absorption coefficient Spectral attenuation coefficient, as biooptical model quantity, 1:386T Spectral beam attenuation coefficient, 3:244–245, 3:245–246, 6:109–110 definition, 4:621 measurement see Transmissometry see also Ocean optics Spectral diffuse attenuation coefficient, 4:623 Spectral interval, 5:91–92 Spectral radiance see Radiance Spectral scattering coefficient see Scattering coefficient Spectral volume scattering function see Volume scattering function (VSF) Spectroradiometers, 3:247–248, 3:327–328, 3:328F Specular reflection, 1:8 Speed autonomous underwater vehicles (AUV), 4:475 gliders, 3:62 of sound see Sound speed Sperm whales (Physeteriidae and Kogiidae), 3:606–607T, 3:643–650, 3:643, 3:644T, 3:648F acoustics and sound, 3:648–649 acoustic behavior, 3:648–649
612
Index
Sperm whales (Physeteriidae and Kogiidae) (continued) sound production mechanism, 3:649 spermaceti organ, 3:644–645, 3:649 anatomy and morphology asymmetry of the skull, 3:645 cranial features, 3:644–645 rostrums, 3:650 sexual dimorphism, 3:644–645 spermaceti organ, 3:644–645, 3:649 conservation, 3:649–650 current threats, 3:649–650 anthropogenic noise, 3:650 whaling industry, 3:649 defense from predators, 3:617 distribution and abundance, 3:645–646 global distribution, 3:645–646 diving characteristics, 3:583T evolution, 3:593 exploitation, 3:637–638, 3:637F foraging ecology, 3:646 competition between species, 3:646 diving ability, 3:646 squid diet, 3:646 suction feeding, 3:646 growth and maturation, 3:612F, 3:613 home ranges, 3:613 lack of knowledge, 3:643 migration and movement patterns, 3:598, 3:598F myoglobin concentration, 3:584T Physeter macrocephalus, 3:643, 3:648F predation, 3:649 Kogia spp. defence mechanisms, 3:649 predators and defence mechanisms, 3:649 relationship to other cetaceans, 3:645F social organization, 3:646–648 allomaternal care, 3:647 epimeletic behavior, 3:647, 3:650 female groups, 3:647 Kogia spp., 3:647 male groups, 3:646–647 sound production, 1:361–362, 1:361F mechanism, 3:649 trophic level, 3:623F see also Odontocetes (toothed whales) Spheniscidae (penguins), 3:356 Sphenisciformes (penguins), 3:356, 3:800, 5:520–528 adaptations to aquatic lifestyle, 5:520, 5:521T, 5:526–527 balance of life at sea and time ashore, 5:527 breeding age at start of, 5:252 chick-rearing, 5:527 success, determinants of, 5:527 characteristics, 5:520 conservation, 5:527–528 distribution, 5:520, 5:522T diving, 5:527 flying vs., 5:520–521 fat storage, 5:527 flightlessness, 5:520, 5:521, 5:527–528
foraging, 5:527 inshore foragers, 5:527 offshore foragers, 5:527 fossils see Fossil(s) insulation, 5:527 migration, 5:239 molting, 5:527 nearest living relatives, 5:520, 5:521F porpoising, 5:526–527 Southern Ocean populations, fishing effects, 2:205–206 species, 5:521–523, 5:522T taxonomy, 5:266T threats, 5:527–528 global warming, 5:527 predation, 5:527–528 underwater swimming, 5:526–527 see also Seabird(s); specific genera/ species Spheniscus, 5:522–523 breeding patterns, 5:523 characteristics, 5:522T, 5:523, 5:523F discovery, 5:522 distribution, 5:522T, 5:523 feeding patterns, 5:522T, 5:523 migration, 5:239 nests, 5:522T, 5:523 species, 5:522 see also Sphenisciformes (penguins); specific species Spheniscus demersus (African penguin), 5:522, 5:522T, 5:523, 5:527–528 Spheniscus humboldti (Humboldt penguin), 5:522, 5:522T, 5:523, 5:527–528 Spheniscus magellanicus (magellanic penguin), 5:522, 5:522T, 5:523, 5:523F Spheniscus mendiculus see Galapagos penguin Spherical navigation, 4:478 Spherical spreading (sound), 1:102, 1:114, 1:114F Sphyraena spp. (barracuda), 2:395–396F Spillhaus, Athelstan, 1:709 Spilling breakers, 1:431, 6:312 turbulence, 1:435 Spillways, 2:564 Spinner dolphin (Stenella longirostris), 2:149–153, 2:158–159, 2:158F, 2:159–160 Spinup see Ocean spinup Spiny dogfish biomass, north-west Atlantic, 2:505–506, 2:506F fishing effects, 2:206 Spiny eel (Notacanthus chemnitzii), 2:452F Spiochaetopterus oculatus polychaete worm, 1:333 Spio setosa polychaete worm, 1:333 Spirula cephalopod, buoyancy, 1:526 Spirulina, 3:570 Split volcano, abyssal hills development model, 3:864–865, 3:865F
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Spotted dogfish (Scyliorhinus canicula), 2:464 Spotted sea trout (Cynoscion nebulosus), stock enhancement/ocean ranching programs, 4:147T, 4:150 Sprat, 4:366 description and life histories, 4:366 distribution, 4:366 spawning biomass, Baltic Sea, 2:505–506, 2:507F Sprat (Clupea sprattus), 4:366 Sprat (Sprattus sprattus), 2:375 Spratley islands, coral reefs, human disturbance/destruction, 1:676 Sprattus sprattus (sprat), 2:375 Sprattus sprattus balticus (Baltic Sea sprat) see Baltic Sea sprat (Sprattus sprattus balticus) Spray (glider), 3:60, 3:61F, 3:62, 3:62–63, 4:474F, 6:263T, 6:264F Spray, high wind conditions and, 6:306 Spray-removal devices, humidity measurement, 5:379–380 Spreading-center earthquakes, 3:841–843 Spreading centers back arc spreading centers, 3:164, 3:166F fast-spreading centers see Fast-spreading ridges fossil spreading centers, 5:300, 5:301F intermediate-spreading centers, hydrothermal vent deposits, 3:145 overlapping spreading center (OSC), 3:853F, 3:854, 4:597, 4:601 propagating rifts and microplates, 4:597, 4:597–600, 4:601, 4:604 spreading center jumps, 4:601 spreading rates, 4:597 slow-spreading centers see Slow-spreading ridges Springs (water), 5:551, 5:553 Spring tides, 6:26, 6:34 definition, 6:32 front position and, 5:395F mixing in regions of freshwater influence and, 5:392 Spume drops, 6:335–336 Spur dog (Squalus acanthias), 2:375 SPURV (Self Propelled Underwater Research Vehicle), 4:473 Squalus acanthias (spur dog), 2:375 Squat lobsters see Galatheid crab (Munidopsis subsquamosa) Squid (Teuthida), 1:527, 3:14–16 acoustic scattering, 1:68 bioluminescence, 1:380 harvesting, 3:902 Ommastrephes spp., 4:135 Southern Ocean fisheries, 5:517–518 Squid jigs, cephalopods harvesting, 3:902 Sr/Ca (strontium/calcium ratio), sea surface temperature and, 2:104–105 SSCC see Southern Subsurface Countercurrent (SSCC) SSH see Sea surface height (SSH)
Index SSM/I see Special Sensor Microwave/ Imager (SSM/I) SSS see Sea surface salinity (SSS) SST see Sea surface temperature (SST) SSUrRNA, 1:269, 1:270F St. Anna Trough, Atlantic water, 1:215 St. Lawrence, Gulf see Gulf of St. Lawrence St. Lawrence Island see St. Lawrence Island (as if ‘Saint’) St. Lawrence River, 1:2–3 Stability parameter, definition, 4:221–222 STABLE II instrument platform, 1:46, 1:46F Stage-structured population models, 4:549–550, 4:550F Calanus marshallae, 4:552, 4:553F Euterpina acutifrons, 4:551F interactions between species, 4:554 ordinary differential equations, 4:549 see also Population dynamic models Stagnation periods, fiords, 2:353–354 Stalked barnacle (Neolepas zevinae), vent fauna origins, 3:156, 3:156F Stamuki, 3:191–193 Standard error, regime shift analysis, 4:718–719 Standard Mean Ocean Water (SMOW), 1:502 Standard seawater, salinity, 1:712 Standards of Training, Certification and Watchkeeping (STCW), 5:405 Standing waves, harmonic mode, 5:345 Stanton numbers, 3:201, 3:202 Stargazers (Astrocopus and Uranoscopus spp.), 2:474, 3:100F STARS (sequential t-test algorithm for analyzing regime shifts), 4:719, 4:720 State estimation, tomography and, 6:47 State of Fisheries and Aquaculture report (SOFIA), 3:576 State variables, physical, data assimilation in models, 2:1 Static suction dredging, 4:185 Station ALOHA, nitrogen concentration depth profiles, 4:51F Stationary, homogeneous, isotropic turbulence, 6:19–21 Stationary uncovered pound nets, traps, fishing methods/gears, 2:540, 2:541F Statistical areas Commission for the Conservation of Antarctic Marine Living Resources, 5:514, 5:514F Food and Agriculture Organization, 4:226, 4:227F, 4:231T, 4:232–233 STCC (Subtropical Countercurrent), 3:359 STD (salinity, temperature, depth) profiler, 1:713 Steady state, definition, 4:651 Steady-state model, nitrogen isotopes, 4:41, 4:41F Steady tracers, 1:682
Steel, in mooring lines, 3:919–920 Steelhead trout see Oncorhynchus mykiss (rainbow trout) Steller’s sea cow (Hydrodamalis gigas), 3:639, 5:436–437, 5:437F, 5:442–443, 5:443–444 see also Dugongidae Stenella (dolphins), 2:155–156 Stenella attenuata (pantropical spotted dolphin), 2:158F, 2:159–160 Stenella coeruleoalba (striped dolphins), 2:159 Stenella longirostris (spinner dolphin), 2:149–153, 2:158–159, 2:158F, 2:159–160 Stenella longirostris roseiventris (dwarf spinner dolphin), 2:153 Steno bredanensis (rough-toothed dolphin), 2:157 Stercoracidae migration, 5:244 see also Charadriiformes Steric height, 5:129–130, 5:130 definition, 2:195 East Australian Current, 2:187–189 Sterna fuscata (sooty tern), 3:423F Sterna hirundo (common tern), 3:423F Sternidae (terns), 3:420–431 body size colony size and, 3:425, 3:426F territory size and, 3:425, 3:426F, 3:428 breeding ecology and behavior, 3:420, 3:425, 3:426F, 3:428–429 chick-rearing, 3:428, 3:429 clutch size, 3:425–426, 3:429 courtship, 3:428 egg incubation, 3:428 ‘fish fights’, 3:428–429 mobbing, 3:425 nest site selection, 3:428, 3:429 phenology, 3:426 range, 3:422T climate change responses, 5:259 conservation, 3:430–431 measures, 3:431 status, 3:430, 3:430T daily activity patterns, 3:429 distribution, 3:420, 3:422T, 3:425, 3:428 foraging, 3:429–430, 5:233–234 habitat, 3:424, 3:425 nesting, 3:425 migration, 3:425, 5:244, 5:245T, 5:246F physical appearance, 3:422–424, 3:423F, 3:424 Laridae (gulls) vs., 3:424 plumage, 3:424 species, 3:420, 3:422T taxonomy, 3:420 threats, 3:430–431 of world (types), 3:422T see also Seabird(s); specific species Stern–Volmer equation, fluorescence quenching, 2:592, 2:592F
(c) 2011 Elsevier Inc. All Rights Reserved.
613
Stictocarbo magellanicus (rock shag) behavioral displays, 4:377F see also Shag(s) Stingray (Dasyatis sayi), 2:446F Stirring, definition, 6:23 Stochastic inverse method (Gauss–Markov method), 3:314–315, 3:314F, 3:316 Stock acquisition, Mediterranean mariculture see Mediterranean species, mariculture Stock assessment, methods, crustacean fisheries, 1:706–707 Stock effect definition, 3:673 marine protected areas, 3:673 Stock enhancement/ocean ranching programs, 4:146–155 bluefin tuna, 4:241 clams, 4:146 cod, Norwegian evaluation, 4:150–151, 4:151F commercial, 4:146 evaluation, 4:150–151, 4:152–154 experimental, 4:146 funding, 2:533 genetic considerations, 2:531–532, 4:153 historical aspects, 2:528–530, 4:146 investment, 4:152–153 marine fish, 4:149–151 species, 4:147T, 4:149 marine invertebrates, 4:147T, 4:151–152, 4:152F mortality rates, 2:530 Norwegian Cod Study, 4:150–151, 4:151F objectives, 4:152–153 pilot, 4:146 release methods, 2:531 salmonid farming see Salmonid farming scallops, 2:528–530, 4:146 species involved, 2:528, 2:529T survival issues, 2:530–531 see also specific species Stokes Drift, 2:300, 3:406, 6:189 and Langmuir instability, 3:409 surface, gravity and capillary waves, 5:576 Stolpe Channel, Baltic Sea circulation, 1:288, 1:290–291, 1:293 Stomiiform fishes, bioluminescence, 1:381–382 Stommel, Henry, 3:60 Gulf Stream System, 2:554 wind driven circulation model, 6:352, 6:352F, 6:353F Stommel–Arons theory, 1:16–18, 1:18F, 1:29 Stoneley wave, 1:79–80 Stony coral (Porites), heavy metal exposure effects, 1:674 Stoplight loosejaws (Malacosteus spp.), 2:455F Storegga slide, 3:790, 5:452 Storfjorden, 1:219
614
Index
Storis, 5:141 Storm(s) internal waves, 3:270 mid-latitude see Mid-latitude storms North Atlantic Oscillation and, 4:68 sediment transport, 4:142–143 severe, heat and, 6:171–172 surges see Storm surges see also Hurricane(s); Monsoon(s) Storm forecasting, 6:172 Storminess, storm surges, 5:539 Storm petrels (Oceanitidae), 4:590 migration, 5:241T, 5:242 see also Procellariiformes (petrels); specific species Storm surges, 5:530–540 areas affected, 5:532–535 Bangladesh, 5:531F, 5:532, 5:535F Gulf of Mexico, 5:532–535, 5:537F mid-latitude storms, 5:532 North Sea see North Sea tropical cyclones, 5:532, 5:534F, 5:535F, 5:539 Venice, 5:532 atmospheric boundary layer interaction, 5:536–537 bottom stress, 5:532, 5:536, 5:538 climate change, 5:539 coastal erosion, 5:530 coastal flooding see Coastal flooding coastal morphology, 5:531–532 coastal trapped waves see Coastal trapped waves data assimilation, 5:538–539, 5:539F deep ocean, dissipation, 5:532 definitions, 5:530 drag coefficient, sea surface, 2:63, 5:530–531 see also Drag coefficient dynamics, 5:531–532 amplification, 5:531–532 dissipation, 5:532 free wave propagation, 5:532 equations, 5:530–531 extremes, 5:539 generation, 5:531–532 inverse barometer effect, 5:531 longshore current, 5:531 wind stress, 5:531 Intra-Americas Sea (IAS), 3:293 life, loss of, 5:532 negative, definition, 5:530 North Sea, 4:78 positive, definition, 5:530 prediction, 5:535–537 coupled models, 5:537–538, 5:538, 5:538F finite difference methods, 5:535–536 finite element methods, 5:536, 5:537F flood warning systems, 5:532, 5:536 hindcasts, 5:539 mid-latitude storms, 5:536–537 observation analysis, 5:535 SLOSH (Sea, Lake and Overland Surges from Hurricanes) model, 5:536
surface wind stress, importance of, 5:536–537 three-dimensional (3D) models, 5:536, 5:538 tide-surge models, 5:535–536, 5:539 tropical cyclones, 5:532, 5:536–537 regional impacts, 5:183 seiches, 5:348F, 5:531–532, 5:532 shallow water, dissipation, 5:532 storminess, 5:539 surge residual, 5:530, 5:531F tide gauge data, 5:535, 5:538–539, 5:539F tide interaction, 5:532, 5:534F, 5:535–536 wind waves interaction see Wind waves see also Fish feeding and foraging; Tide(s); Waves on beaches; Winddriven circulation Stow nets, traps, fishing methods/gears, 2:541, 2:541F Strabo, 5:551 Strain gauges, pressure sensors, 1:714F Strait of Bab El Mandeb, 4:666, 4:666F, 4:667, 4:674 inflow, 4:667, 4:674 outflow, 4:667, 4:673, 4:674, 4:675F salinity, 4:667, 4:669F Strait of Dover dissolved inorganic nitrogen, 2:311F dissolved inorganic phosphorus, 2:311F Strait of Florida, 3:286F, 3:287 Strait of Gibraltar, 2:572 flow, 2:574 historical aspects, 2:572 tidal forcing, 2:575, 2:575F NADW formation, 4:306 paleoceanography climate models in, 4:306 gateway, climate and, 4:306 gateway closure during Cenozoic, 4:304F see also Straits Strait of Istanbul see Bosphorus Strait of Messina, 2:572 see also Straits Strait of Sicily forecasting and data assimilation, 2:3–5, 2:4F Marrobbio, 5:349 Straits definition, 2:572 flows in, 2:572–577 barotropic forcing, 2:574–575, 2:575F quasi-steady response, 2:574, 2:575F strong, 2:574, 2:575F barotropic transport, 2:574 effects due to rotation, 2:572, 2:576–577, 2:577F history, 2:572–573 instability, 2:575, 2:576F maximal exchange, 2:572, 2:573 mixing, 2:575–576, 2:576F over sills, 2:575–576, 2:575F, 2:576F
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research, 2:572 subcritical, 2:573 supercritical, 2:573 topography and, 2:572 two-layer exchange, 2:572, 2:575F frictionless theory of layered flow, 2:573 see also Estuarine circulation see also specific straits Straits of Florida, 3:286F, 3:287 Strandings, 2:160 STRATAFORM programs, 4:138–139 Stratification, 6:225, 6:231 coastal trapped waves, 1:593, 1:593–594 bottom-trapped waves, 1:594 Kelvin waves, 1:593–594 seasonal variation, 1:593–594 unstratified, 1:591–592 continental shelf waves, 1:593–594 deep convection see Restratification definition, 3:173 emergence, 3:374–375, 3:375F gravity currents, effect on, 4:63–64 impact on primary productivity, 4:586 internal tides, 3:258, 3:261 internal waves, 3:266 North Sea see North Sea ocean gyres, 4:132–133 three-dimensional (3D) turbulence, 6:22, 6:24F see also Restratification Stratification parameter, estuarine circulation, 2:302, 2:302F Stratified fossil turbulence detection, 2:618 formation, tilted density surface, effects on, 2:615F, 2:618 universal similarity theory, 2:612, 2:613F, 2:615–616 Stratigraphic analysis see Sequence stratigraphy Stratigraphic record, accretionary prisms, 1:31–32 Stratigraphic sequence lower crust, 2:49 see also Sequence stratigraphy Stratospheric chemistry, halogenated compounds, 1:161 Stress minimization mariculture disease management, 3:519–520, 3:520 salmonid farming, 5:27 Stress patterns, ice shelf stability, 3:215 Stress responses, aquarium fish mariculture, 3:529 Stretching vorticity, 6:287 Striped bass (Morone saxatilis), 2:333 Striped dolphins (Stenella coeruleoalba), 2:159 Striped marlin (Tetrapturus audax), utilization, 4:240 Strong atmospheric forcing events upper ocean response, 6:192–210 see also Hurricane(s)
Index Strontium (Sr2+) concentration in sea water, 1:627T determination, 1:626 isotope ratios, 3:459F Cenozoic, 3:460F Cenozoic carbon cycle changes and, 1:516–517, 1:516F, 1:522 deep-water distribution, 3:457 governing processes, 3:461 incongruent release, 3:465T Phanerozoic, 3:460F present-day sea water, 1:516 long-term tracer properties, 3:456T results, 3:458–462 source materials, 3:457–458 isotope ratios, 3:457T Strontium-90 (90SR), nuclear fuel reprocessing, 4:84T Strontium/calcium ratio, sea surface temperature and, 2:104–105 Strouhal number, island wakes, 3:343–344 Structured population models, 4:547–549 continuous-time see Continuous-time structured population models individual-based models vs., 4:547 matrix models see Matrix models representation of population interactions, 4:554 see also Population dynamic models Structure I gas hydrates, 3:792, 3:793 Structure II gas hydrates, 3:792 Sturzstrom, 5:450 see also Mass transport STW (salty subtropical water), 3:447, 3:449, 3:449F Stylophora pistillata (club finger coral), oil pollution effects, 1:673–674 SubAntarctic diving petrel, 4:591F see also Procellariiformes (petrels) SubAntarctic Front (SAF), 1:178, 1:179F transport, 1:184 water properties, 1:180F SubAntarctic Mode Water (SAMW), 1:178–179, 1:180F, 1:424, 3:447–449, 3:449F formation, 1:188, 1:189F SubAntarctic Surface Water (SASW), temperature–salinity characteristics, 6:294T SubAntarctic waters, 3:444, 3:444F, 3:447 SubAntarctic Zone, 1:181–182 SubArctic Boundary, 4:136 SubArctic Current, 3:359F Kuroshio Extension and, 3:364 Oyashio Current contribution, 3:367 SubArctic Front, 3:367 Sub-basin circulation, Baltic Sea circulation, 1:292–293, 1:293F Subduction, ocean see Ocean subduction Subduction zone processes, deep submergence science studies, 2:29–30 Subduction zones geophysical heat flow, 3:47
mantle composition, melting and, 3:879F tsunamigentic earthquakes and, 6:129–131 Subduction zone volcanoes, helium plumes, 6:283 Subductive feeding, 1:395 Subgrid-scale parameterization (SGS), 5:134–135 forward numerical models, 2:609–611 Global Climate Models, 4:111 vertical advection, 5:137 Sub ice-shelf, circulation and processes, 5:541–550 Antarctic continental shelf, 5:544–545, 5:546F climate change, 5:549–550 factors controlling, 5:541 geographical setting, 5:541–542 melting, seawater effects of, 5:543–544 modes, 5:544–547 numerical models, 5:541 oceanographic setting, 5:542–543 thermohaline modes, 5:544–547 cold regime external ventilation, 5:544–547 internal recirculation, 5:547–548 warm regime external ventilation, 5:548, 5:548F tidal forcing, 5:548–549 SUBICEX (Submarine Ice Exercises), 1:93–94 Sublimation, 2:328 Sublittoral zone, 1:351T Submarine(s) acoustics research and, 1:93–94 detection, internal waves, 3:266 sea ice thickness determination, 5:151 sonar system history, 5:504 see also Human-operated vehicles (HOV); Submersibles Submarine cables, sediment transport processes and, 5:464 Submarine groundwater discharge (SGD), 3:88–97, 3:88, 5:551–558, 5:552F aquifers and, 5:552, 5:553, 5:554 chemical tracers, 3:92–94 composition, 5:551–553 definition, 5:551 measurements, 5:555 direct, 5:555 tracer techniques, 5:555–557 mechanisms driving, 5:553–555 quantification, 3:90, 3:91–92, 5:555 chemical tracers, 3:92–94 direct measurements, seepage meters, 3:91–92 hydrology, 3:90–91, 5:557 infrared thermography, 3:90 role in hydrological cycle, 5:551 see also Pore water Submarine Ice Exercises (SUBICEX), 1:93–94 Submarine measurements, 5:84, 5:85 Submarine-mounted sonar, sea ice, 5:176
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615
Submarine permafrost see Sub-sea permafrost Submarine ridges, 3:218, 3:219–222, 3:220T, 3:225 see also Large igneous provinces (LIPs) Submarine Science Ice Expeditions (SCICEX), 1:93–94 Submergence, 3:33 Submersibles cold-water coral reefs knowledge/ research, 1:616F deep, role in seafloor spreading theory, 3:123 floc layers, 2:548, 2:549F gravimetry, 3:82 manned see Manned submersibles (deep water); Manned submersibles (shallow water) Nekton, 3:514 research, history, 3:123 see also Human-operated vehicles; Submarine(s); Vehicles Submicrometer aerosol particles, 1:238–239 Suboxic, definition, 1:268 Subpolar ecosystems continental margin area, 4:258T continental margins, primary production, 4:259T Subpolar gyres, 6:231 Ekman suction, 6:350–351, 6:351 geostrophic fluid columns, 6:351, 6:352, 6:353–354 North Atlantic see North Atlantic subpolar gyre ocean subduction, 4:158, 4:159 rotation, 6:346 Subpolar Mode Water see SubAntarctic Mode Water (SAMW) Subpolar regions, 6:179–180 Sub-sea permafrost, 5:559–569 characteristics, 5:561–562 definition, 5:559 distribution, 5:559F, 5:565–566 see also specific seas formation, 5:560–561 geothermal heat flow, 5:561 investigation, methods of, 5:559 models, 5:567–569 nomenclature, 5:559–560 occurrence, 5:565–566 processes, 5:562–564 heat transport, 5:564–565 salt transport, 5:564–565 submergence, potential regions, 5:562–564, 5:565F temperature profiles, 5:560, 5:561F thawing, 5:560–561, 5:561 of negative seabed temperatures, 5:564–565 Subsidies, shipping see Protectionism/ subsidies Subsistence fisheries, Salmo salar (Atlantic salmon), 5:1 Substratum, oil pollution, 4:192 Subsurface drogues see Drogues
616
Index
Subsurface floats see Float(s) Subsurface moorings see Moorings, subsurface Subsurface waters phosphate content, cadmium/calcium ratio as tracer, 5:333, 5:337, 5:337F productivity, sedimentary records see Sedimentary records, productivity reconstructions surface water vs., d13C values, 5:336 Subterranean estuary, 3:90, 5:552F geochemistry, 3:94–96 oxygen levels, 5:552–553 sea level and, 5:555 Subtropical Convergence, Agulhas Return Current and, 1:128, 1:135–136, 1:136F, 1:136T Subtropical convergence areas, 2:217 Subtropical Countercurrent (STCC), 3:359 Subtropical Front, 6:181–182 Subtropical gyres, 2:217, 4:120–121, 4:121F, 6:351 absolute vorticity, 6:351 Ekman pumping, 6:351, 6:352 geostrophic fluid columns, 6:351, 6:352, 6:353–354 idealized models, 6:352, 6:352F, 6:353F ocean subduction, 4:158 main thermocline formation, 4:159–160 relative vorticity, 6:351–352 response timescales, 4:124 rotation, 6:346 westward intensification, 6:352–353 Subtropical waters, 3:444, 3:444F, 3:446 eastern boundary currents, 3:444 Successive corrections, method of, estimation theory, 2:7 Suess effect, 5:421–422 Suez, Gulf of see Gulf of Suez Suezmax tankers, 5:402–403, 5:403T Sula bassana see Northern gannet Sula leucogaster (brown booby), 4:372F see also Sulidae (gannets/boobies) Sulawesi Sea see Celebes Sea Sulfate (SO42-), 5:46 atmospheric, 1:248–249 concentrations in river water, 1:627T, 3:395T in sea water, 1:627T determination, 1:626 depth profiles, estuarine sediments, 1:544F reduction in pore water, 4:566T Sulfate aerosol, 1:120–121 Sulfur (S) anthropogenic emission perturbations, 3:398F, 3:401–403 atmospheric deposition, projected, 3:402F cosmogenic isotopes, 1:679T production rate, 1:680T reservoir concentrations, 1:681T cycling in estuarine sediments, 1:546–547, 1:547F
powder, as Langmuir circulation tracer, 3:411F, 3:412 primeval oceans, 6:84–85 river fluxes, 3:397 salt marshes and mud flats, 5:46 total dissolved, river water, 3:395T Sulfur-35, cosmogenic isotopes, oceanic sources, 1:680T Sulfur dioxide (SO2) pollution, 5:225, 5:277 river water concentration, 3:395T Sulfur hexafluoride (SF6), 2:123 air–sea gas diffusion experiments, 1:153 chemical and physical properties, 6:87 depth profile, 6:88F diffusion coefficients in water, 1:147T estuaries, gas exchange, 3:3 gas chromatographic analysis, 6:90–91 iron release patch labeling, 6:91 Schmidt number, 1:149T tracer release, 6:87–88 Sulidae (gannets/boobies), 4:370, 4:373 breeding patterns, 4:373 characteristics, 4:373, 4:376T distribution, 4:373 feeding patterns, 4:373, 4:376T, 5:234 migration, 5:242–244 species, 4:372F, 4:373 see also Pelecaniformes; specific species Sulu Sea, 5:305 outflow surface velocity, 5:314F Sumba Strait, 3:238–239 Summer (boreal), monsoon activity, Northern Hemisphere, 3:910, 3:910F Summer melt onset, 5:80, 5:88 process, 5:86 see also Marine mammals; Pinnipeds (seals); Seabird migration Summer solstice insolation, 4:509, 4:511F Sun radiation emission levels, glaciation and, 1:5 see also Solar radiation Sunfish (Mola mola), 2:395–396F Sunlight, near sea surface temperatures and, 5:93–94 Sunscreens, marine organisms, 3:571 Sun-synchronous orbits, ocean color remote sensing and, 5:117–118 Supercarriers, lost to rogue waves, 4:770F Superchrons, 3:26 see also Paleomagnetism Supercooled ice, formation, transmissometers in study of, 6:117T Superoxide dismutase, 6:76, 6:83 Superoxide radical, definition, 6:85 Superposition (surface waves), 4:772 Super viscosity see Eddy viscosity Support ships, manned submersibles (deep water), 3:509, 3:510–511, 3:511 Support vessels, 5:416–417 development, 5:416–417
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Suprabenthos (hyperbenthos), 1:328, 2:55, 3:468 see also Benthic boundary layer (BBL) Surface, of sea see Sea surface Surface algal blooms Dutch airborne survey, 2:313F see also Algal blooms Surface circulation, 5:127 see also Ocean circulation; Upper ocean, mixing processes Surface convection, oxygen saturation and, 6:224 Surface cooling, open ocean convection, 4:220 Surface currents see Brazil and Falklands (Malvinas) Currents; Florida Current, Gulf Stream and Labrador Currents; Intra-Americas Sea (IAS); North Brazil Current (NBC) Surface films, 5:570–572 air–sea gas exchange, 1:151 air–sea interaction, modifications of, 5:570–571 attenuation of surface waves, 5:571 gas transfer, reduction of, 5:571 radar back scattering, 5:571–572 reflection of sunlight, change of, 5:571 surface sea temperature, change of, 5:571 wave breaking, reduction of, 5:571 anthropogenic sources, 5:570 ‘dry surfactants’, 5:570 of natural origin, 5:570 biological producers, 5:570 origins, 5:570 ‘wet surfactants’, 5:570 wind speeds, 5:570 Surface freshwater exchange, 6:165 Surface, gravity and capillary waves, 5:573–581 air–sea interaction, 5:573, 5:580 basic formulations, 5:573–574 Bernoulli equation, 5:574 Laplace’s equation, 5:573–574 limitations, 5:574 Navier-Stokes equations, 5:573 Reynolds number, 5:573 capillary waves, 5:573, 5:576 currents see Current(s) deep-water capillary waves, 5:576 dispersive waves, 5:575–576 dissipation, 5:576–577 gravity waves, 5:576, 5:578–579 nonlinear effects, 5:578 dispersion relationship, 5:578 dispersive waves, 5:575–576 dissipation, viscous, 5:573, 5:579–580 energy density, 5:576 exchange with currents, 5:577 propagation, 5:576 wave breaking, 5:580
Index fish-line problem, 5:579–580 gravity-capillary waves, 5:575F, 5:579 resonant interactions, 5:578 gravity waves evolution, 5:579F group velocity, 5:576 nonlinear effects, 5:578 resonant interactions, 5:578–579 group velocity, 5:576, 5:579–580 deep-water capillary waves, 5:576 deep-water gravity waves, 5:576 shallow water gravity waves, 5:576 intermediate depth gravity waves, 5:578 Laplace pressure, 5:574–575, 5:579 linear waves see Linear waves long-wave-short-wave interaction, 5:577–578 nondispersive, 5:575 nonlinear effects, 5:578–579 deep water gravity waves, 5:578 dispersion relationship, 5:578 gravity waves, 5:578 phase speed, 5:578 Schro¨dinger equation, 5:578 solitons, 5:578 Stokes, 5:578 vertical asymmetry, 5:578 wave slope, 5:578 wave-wave interactions, 5:578, 5:578–579 parasitic capillary waves, 5:575F, 5:580 generation, 5:579, 5:579F phase speed linear waves, 5:575, 5:575F nonlinear effects, 5:578 potential energy, 5:576 propagation, towards shore, 5:575, 5:576–577, 5:577 refraction, 5:577 resonant interactions, 5:579–580 deep water gravity waves, 5:578–579 gravity capillary waves, 5:578 intermediate depth gravity waves, 5:578 second order quantities, 5:576–577 dissipation, 5:576–577 energy density, 5:576 mean momentum density, 5:576 Stokes drift, 5:576 seiches, 5:346 shallow water see Shallow water surface tension, 5:574, 5:575–576, 5:576, 5:579 swell, 5:573, 5:574F, 5:576–577 turbulence, 5:580 viscosity, 5:573, 5:579–580 wave breaking see Breaking waves; Wave breaking wave property prediction, 5:577–578 waves on currents see Current(s) wave-wave interactions, nonlinear effects, 5:578, 5:578–579 wind-driven period, 3:406 Stokes drift, 3:406 see also Wind-driven circulation
wind-generated, 5:574F, 5:578 see also Internal wave(s); Surface films; Wave energy; Wave generation Surface gravity currents idealized flow model, 4:60, 4:61F ocean, 4:59 Surface heat exchange, 6:164–165 Surface heat flux, global distribution, 6:169F Surface heat loss, deep convection, 2:13 calculation, 2:13 Surface layer Auckland-Seattle transect, 6:221F fiords, 2:353 density, 2:356 mixed layer and, 6:220–221 Surface layer depth, definition, 6:219 Surface mixed layer, 6:183 convection plumes see Ocean convection plumes deep convection, 2:13, 2:17 depth, 2:13, 2:14F, 2:19 density, 2:13, 4:220 freshwater influx, 2:13 depth deep convection, 2:13, 2:14F, 2:19 factors affecting, 2:13, 4:218, 4:220, 4:221F, 4:223–224 horizontal variability, 2:17 internal waves, 3:272 open ocean convection, 4:218, 4:220, 4:223–224, 4:224 fronts, 6:213 open ocean convection, 4:218, 4:221F depth, 4:218, 4:220, 4:223–224, 4:224 turbulence, 6:24, 6:24F, 6:211–212 Surface nepheloid layer (SNL), 4:8 Surface polar currents, thermohaline circulation, 4:122 Surface radiation budget (GEWEX-SRB) project, 5:205 Surface reflectance, 5:115 see also Reflectance Surface salinity, 5:127, 5:130 global mean, 5:127, 5:128F interannual variations, 5:130 Surface sea water chlorinated hydrocarbons see Chlorinated hydrocarbons temperature, deep sea water vs., 4:167F see also Surface waters Surface-seeking organisms, small-scale patchiness, behavior/fluid transport joint effects, 5:485–486, 5:486F Surface straits, rotating gravity currents, 4:791F, 4:792–793 Surface tension non-rotating gravity currents, 4:60 surface, gravity and capillary waves, 5:574, 5:575–576, 5:576, 5:579 Surface (barotropic) tides, 3:255 Surface waters phosphorus cycle research, 4:409–410, 4:411T, 4:412
(c) 2011 Elsevier Inc. All Rights Reserved.
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productivity, 5:333, 5:334F sedimentary records see Sedimentary records, productivity reconstructions subsurface waters vs., d13C values, 5:336 see also Surface sea water Surface waves air–sea gas exchange and, 1:151 amplitude measurement, 1:435F exceeding wind speed, 6:307–308 generation by wind, 6:304–309 long, satellite remote sensing application, 5:107F, 5:109–110, 5:110F one-dimensional models and, 4:214–215 spectral density function, 1:435–436 spectral evolution, 4:771 surface films, 5:571 turbulence, 1:436 see also Breaking waves, turbulence wind-driven, SAR imaging mechanism, 5:105–106 see also Breaking waves; Deep-water surface waves; Rogue waves; Wave(s) Surface wind velocity, measurement of, 3:108 Surf beat, 6:314 Surf clam, acoustic scattering, 1:69 Surf zone, 1:311 definition, 6:310 processes, 6:310F, 6:311–312, 6:312–313 Surrounding gears, 2:536, 5:470 without purse lines, 2:536, 2:536F with purse lines/seines, 2:536, 2:536F Surveillance, fishery management, 2:524, 2:524–525 Surveying, AUVs, 6:262–263 Suspect terranes, 3:483–484 Suspended particles areas of high concentration, 4:15–16 scattering (optical), 4:8, 4:11F see also Particle(s) Suspended particulate matter (SPM), 3:769 Suspended sediments acoustic backscatter, 1:38–39, 1:42–44 concentration, 1:47–48 profiles, 1:44F, 1:45F entrainment mechanisms, 1:44–46, 1:45F modeling, 1:47–48, 1:49F waves, 1:48F particle size, profiles, 1:44F, 1:45F remote sensing applications, 4:739 spectral range for remote sensing, 4:735T Suspension feeders, 1:351–352, 1:352, 1:356, 3:468 Suspension freezing, 5:173 Susquehanna River, eutrophication, 2:319F Sustainability exploited fish, population dynamics, 2:180, 2:180F
618
Index
Sustainability (continued) see also Maximum sustainable yield (MSY) Sustainable development coastal zone management, 1:600 see also Coastal zone management Law of the Sea, 3:433 Rio Declaration, 3:433 Susus (Platanista spp.), 2:156, 2:157, 2:158, 2:159 SVD see Singular value decomposition (SVD) Sverdrup balance, Rossby waves, 4:787–788, 4:787F Sverdrup modeling, Antarctic Circumpolar Current and, 1:185–187 Sverdrup relation definition, 6:352 limitations, 6:352 see also Ekman pumping Sverdrup’s model, of seasonal cycle of phytoplankton, 4:359, 4:361T Sverdrup transport, 4:715, 6:352, 6:353, 6:354 Sverdrup unit, definition, 4:165 Swaged mooring terminations, 3:920 Swallow, John, 2:176, 3:59 Swallow floats, 2:176 Swarms plankton see Plankton, swarms Rimicaris exoculata (shrimp), 3:153F Swash, 6:312, 6:314–315, 6:315T Swash zone, 1:306, 1:311 SWATH (Small Waterplane-Area Twin Hull) ships, oceanographic research vessels, 5:418 Sweden fishing records, 4:709–710 Salmo salar (Atlantic salmon) fisheries, 5:2T Sweep zone, 3:35 Swell, 3:33 acoustic noise, 1:54 satellite remote sensing application, 5:107F, 5:109–110, 5:110F surface, gravity and capillary waves, 5:573, 5:574F, 5:576–577 Swell shark (Cephaloscyllium ventriosum), 2:448F Swimbladder, 1:65F acoustic scattering, 1:65 boundary element model, 1:66F Swimbladder retia, 2:217 Swimming, beaches, microbial contamination, 6:268 Swimming crab (Portunus trituberculatus) stock enhancement/ocean ranching, Japan, 2:528–530 world landings, 1:701T, 1:702 Swimming crabs (Ovalipes spp.), 5:55F Swordfish (Xiphias gladius), 2:474, 4:135, 4:234, 4:234F longline fishing, 4:237 open ocean fisheries see Pelagic fisheries utilization, 4:240
world landings, 4:240 see also related species Swordfishes (Xiphiidae), 2:395–396F Sydney oyster, production, 4:275T Sylt, island, 5:50–51 Symbiotic algae, heavy metals accumulation, impact on corals, 1:674 Symbiotic relationships algae–gelatinous zooplankton, 3:10 algae–radiolarians, 4:613–614, 4:617 bacteria–deep-sea animals, 1:355 bacteria–fish, 1:380–381 bacteria–squid, 1:380, 1:527 chemoautotrophic bacteria–vent animals, 2:57–58 dinoflagellates–radiolarians, 3:9 ‘Symplectic refinement’, 3:22 Synechococcus cyanobacteria, 2:582F, 3:799–800, 6:84 Syngnathidae, 2:395–396F Synopticity, 3:244 Syntactic foam, 3:920 on benthic flux landers, 4:486 Syntectonic lava flows, 3:865–866, 3:865F Synthetic aperture radar (SAR), 1:144–145, 4:739–740, 4:778, 5:70, 5:103 all-weather, day/night imaging, 5:103 description, 5:103 ocean features detected, 5:103 ocean surface roughness measured, 1:144–145 satellite remote sensing see Satellite remote sensing SAR side-looking imaging radar, 5:103 see also Aircraft for remote sensing; Satellite altimetry synthesized long antenna, 1:144 see also Bio-optical models; Inherent optical properties (IOPs); Irradiance Synthetic organic compounds, atmospheric deposition, 1:241–242 Synthetic trace organics, 1:123 Synthliboramphus, 1:171T reproduction, 1:174, 1:175 see also Alcidae (auks) Syria, 5:551 Systeme Acoustique Remorque´ (SAR), 6:256T
T t, definition, 6:242 t1/2, definition, 4:651, 6:242 TA see Titration alkalinity Table Bay Harbor, Cape Town, seiches, 5:348, 5:349 TAC see Total Allowable Catch (TAC) Tahiti, atmospheric pressure anomaly time series, 2:231F Taiwan Strait, upper layer velocity, 5:314F
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Taiwan Tan, shallow water bathymetry, SAR image, 5:105F, 5:107 Talik, definition, 5:559–560 Talitrus saltator (sand hopper), 5:53F, 5:56 Tampa Bay, Florida, thermal discharges, effects of, 6:14, 6:14–15 Tanaid crustaceans, 2:59F Tanker fleets, 5:403T, 5:406T Tankers, 5:404 cargoes, global trade, 5:401, 5:401T charter rates, 5:404, 5:404T double hulls, environmental issues, laws/ regulations, 5:405, 5:406 gas carriers, 5:404 liability insurance, 5:407 liquid bulk charters, 5:404, 5:404T Suezmax tankers, 5:402–403, 5:403T Tanner crab see Chionoecetes (snow, tanner crab) Tantalum concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:694 depth profile, 4:695F properties in seawater, 4:688T TAO array, 2:283–284, 2:284F TAP (Transarctic Acoustic Propagation Experiment), 1:92–93, 6:52–54 Tapes see Clams Target catch, definition, 2:202 Target strength (TS), measurement, zooplankton sampling, 6:369 Tasmacetus shepherdii (Shepherd’s beaked whale), 3:646 Tasman–Antarctic Passage, opening of, 4:304, 4:304F Tasmania, 3:444, 3:446, 3:449 Tasman Rise, 1:511–512 Tasman Sea, as East Australian Current source, 2:187, 2:195 Tatar Strait, 4:200F, 4:201 tsc, definition, 6:242 Taxonomic relatedness measures, pollution, effects on marine communities, 4:535 Taxonomy see Classification/taxonomy (organisms) Taylor, G I, 2:579 Taylor columns, 6:61–62 TBT see Tributyl tin (TBT) Techa River, radioactive wastes, 4:632 Technetium (99Tc), 4:632, 4:635 concentrations in ocean waters (N. Atlantic and N. Pacific), 6:101T nuclear fuel reprocessing, 4:82, 4:85 transit time (Irish Sea to North Sea), 4:632 Technogarden, coastal zone management, 1:604 Technology, access, Mediterranean mariculture, 3:532, 3:536 Technology Committee (TEDCOM), deep-sea drilling, 2:53 Tectonic activity, clay mineral composition and, 1:570–571
Index Tectonic compression, sediment transport process initiation, 5:450 Tectonic cycle, Earth, 2:49, 2:49F Tectonic plates, 6:130F Tectonics mid-ocean ridge see Mid-ocean ridge tectonics, volcanism and geomorphology sea level change and, 3:49–50, 3:50F global sea levels, 3:49–50, 3:50F local tectonic causes, 3:50 raised coral reefs, 3:49, 3:50F vertical crustal displacements, 3:49–50, 3:50F see also Coral reef(s) see also Plate tectonics Teleconnections, 4:65 Telemetry, marine mammal bioacoustic research, 1:362F, 1:363 Teleosts, 2:470–471, 2:471F acanthopterygian spp., 2:470–471 body fluids and osmoregulation, 2:473 buoyancy, 2:473 classification difficulties, 2:471 euteleosts, 2:470–471 features, 2:471F fins, 2:393, 2:393F four main radiations, 2:470, 2:470F habitat refinements, 2:467 majority of all fish, 2:471 osmoregulation, 2:473 radiations, 2:470 Telephone cables, flow measurement using, 3:116–117 Tellurium (Te), 3:776, 3:782–783, 3:783 depth profile, 3:782–783, 3:782F Temperate bloom cycle, 4:133 Temperature biological effects of, 6:12 brightness see Brightness temperature changes, noble gas saturations and, 4:57–58 coral reef aquaria, 3:530 deficit brightness temperatures, 5:92 definition, 5:91 water vapor as contributor, 5:91–92 effect on copepods, 1:646–647, 1:646F effect on primary production, 4:573 effect on radiolarians, 4:616–617 effects on fish larvae, 2:386–387 extremes, Mediterranean mariculture problems, 3:533 fluctuations over ocean surface see Heat flux global-average, predicted rise, 5:181 ice, 3:188–189, 3:188F influence on fish distribution, 2:369 intrusions, 3:295 latitudinal differences, 1:348 measurements, 5:377 digital, 1:715 positioning of sensors, 5:377 radiation shields for sensors, 5:376F, 5:377
sea surface temperature (SST), 5:377, 6:217 skin temperature, 5:377 thermometer types, 5:377, 5:378T mixed layer see Mixed layer temperature Ocean Station Papa, 4:214F perturbation rifle, 6:56 potential see Potential temperature prehistoric see Paleotemperature profile Black Sea, 1:216F, 1:405F Kuroshio extension front, 5:356F Southern Ocean, 1:180F range of seawater, 6:381F relationship to nutrient concentrations, 6:230, 6:230F salinity and see Temperature–salinity characteristics scale, definition, 1:710 sea surface see Sea surface temperature (SST) skin measurement, 5:377 see also Radiative transfer (oceanic) from sound speed, 6:54–56 sound speed and, perturbation, 6:56, 6:56F upper ocean, distribution, 6:166 vapor pressure vs., 2:327, 2:327F vertical differences, 1:348 water see Sea water; Water temperature water-column, Massachusetts Bay, 4:481F water-column stability and, 6:163 see also Heat; Heat transport; Ocean warming; Sea surface temperature (SST); Temperature gradient Temperature cutoff scale (LT), turbulent dissipation, 6:149–150, 6:150, 6:151F Temperature-dependent sex determination (TSD), sea turtles, 5:212, 5:213–214 Temperature gradient global, greenhouse climates, 4:319, 4:323–325, 4:326, 4:327T see also Heat transport Temperature microstructure sensors, measurement of turbulent dissipation see Turbulence sensors Temperature probes, turbulence measurement, temperature profile, 2:293–294 Temperature proxies bias, 4:327T see also Magnesium/calcium ratio; Oxygen isotope ratio (d18O); TEX86 Temperature ramps, upper ocean mixing, 6:189–190 Temperature–salinity (TS) characteristics Gulf Loop Current (GLC) rings, 3:289–290, 3:290 Intra-Americas Sea (IAS), 3:292 TS curves, 6:291–293 Atlantic Ocean, 6:297, 6:297F
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defining and locating water masses, 6:292, 6:297F, 6:298F Indian Ocean, 6:298, 6:298F Pacific Ocean, 6:292F, 6:297–298, 6:298F scatter plot, 6:291–292, 6:292F single station, 6:291–292 standard deviation, 6:292, 6:292F volumetric TS curve, 6:292–293, 6:293F water masses, 6:293, 6:294T, 6:297–298 Yucatan Current, 3:289 Temperature–salinity (TS) relationship, 6:181 Tench (Tinca tinca), 2:451F TEP (transparent exopolymer particles), 4:332–333, 4:333F Terada, T, 5:345 Terminal gravitational transport, 1:372 Terns see Sternidae (terns) Terrestrial biosphere, carbon dioxide cycle, 1:487 Terrestrial mammals hearing, 1:359–360, 1:360 sound production, 1:361 Terrestrial runoff, monitoring, using scattering sensors, 6:117T Terrestrial storage, changes, sea level and, 5:183 Territorial sea, Law of the Sea jurisdictions, 3:434 Testarossa, 4:770F Tether management system (TMS), 4:743, 4:744F computer control, 4:743, 4:744–745 control systems, 4:744–745 deck winch, 4:743–744 hardwire control, 4:743, 4:744–745 launch and recovery system (LARS) and winch, 4:744 surface control stations, 4:744 tether cable, 4:743 see also Autonomous underwater vehicles (AUVs) umbilical cable, 4:743–744 vehicle tether, 4:743 Tethys Ocean, 1:211, 1:401–402 closure, 1:512 Tethys–Paratethys connection, paleoceanographic model, 4:308–309 Tetrachlorobiphenyls, structure, 1:552F Tetraether (TEX86) index see TEX86 index Tetrapturus (spearfish), utilization, 4:240 Tetrapturus audax (striped marlin), utilization, 4:240 Tetrapturus spp. (marlins), 4:135 Teuthida (squids), 1:527, 3:14–16 bioluminescence, 1:380 Ommastrephes spp., 4:135 Tevnia jerichonana, 3:133F, 3:136F anatomy, 3:133–134 endosymbiotic bacteria, 3:133–134 habitat, 3:134–135, 3:135F
620
Index
Tevnia jerichonana (continued) Venture Hydrothermal Field, 3:154–155 see also Vestimentiferan tubeworms TEX86 index, 2:106–108 crenarchaeotal membrane lipids, 2:106–108 marine biocycle and global geochemical cycle, 4:298F Paleocene-Eocene Thermal Maximum, 4:322F sea surface temperature and, 2:107F sea surface temperature paleothermometry and, 2:101T Tanzania, 4:324F Texas, USA, salt flats, 5:43 Texas A&M University (TAMU), Ocean Drilling Project (ODP), 2:53 Thailand, artificial reefs, 1:227 Thailand, Gulf o, fisheries development impact, 1:651 Thalassia (seagrass systems), thermal discharges and pollution, 6:14 Thalassia testudinum, 2:315–317 Thalassiosira, 3:574F Thalassiosira oceanica, 6:81F Thalassiosira pseudonana, 3:554–555 Thalassiosira weissflogii, 3:554–555, 4:44 Thalassiothrix longissima, 3:651F, 3:653 Thalassocalycida ctenophores, 3:12 Thalassoica antarctica (Antarctic petrel), 5:253 Thalassoma bifasciatum (cleaner wrasse), 2:423 Thale cress (Arabidopsis thaliana), 3:553 Thaliacea tunicates, 3:16, 3:660 Doliolida, 3:16–17 Pyrodomida, 3:16 Salpida, 3:17–18, 3:17F Thames Estuary, UK, tide-surge interaction, 5:534F Thawed layer, development, 5:560 Thecosomata (sea butterflies), 3:14 Themisto compressa, 3:690–691 Theories, basic building blocks, 3:21 Theragra chalcogramma (Alaska/walleye pollock), 2:405–406, 2:406F, 2:414–415, 2:418F, 2:423F avoidance of turbulence, 5:491 population, El Nin˜o and, 4:704 total world catch, 2:91, 2:91T Thermal boundary layer convection plumes, 2:15, 2:16F open ocean convection, 4:219 Thermal compensation depth, 4:223–224 Thermal convection, open ocean convection, 4:218 evaporative cooling, 4:219 latitudinal variation, 4:218 thermals, 4:219, 4:219F turbulent, 4:219 Thermal discharges biological effects, 6:12–13 entrainment, 6:12–13, 6:13F pollution and see Pollution receiving waters, effects in, 6:13–14 research directions, 6:16–17
Thermal expansion, oceanic, sea level variation and, 5:181–182, 5:182F, 5:183 Thermal expansion coefficient, 4:25, 6:380T mixed-layer depth and, 6:219–220 seawater, 6:381 Thermal gradient engine, gliders, 4:474–475 Thermal imagers, 3:328–329, 3:329F focal plane array detector technology, 3:329 problems with, 3:329 Thermal ionization mass spectrometry (TIMS), 5:327 Thermal plumes, 6:11–12, 6:11F Thermal power generation, 6:10 Thermals, open ocean convection, 4:219, 4:219F, 4:220 Thermal sink, ocean thermal energy conversion, 4:167–168 Thermal wind balance, 3:759 Thermarces andersoni (zoarcid fish), 3:133F, 3:135, 3:135F, 3:136F, 3:138F, 3:140 Thermistors, 1:710, 5:387, 6:152–153 glass-bead, 2:294F microbead, 5:387 thin film sensors vs., 6:152–153 Thermit (welding compound), 3:190 Thermoacidophiles, definition, 2:78 Thermobaric parameter, 4:26 Thermocapillary convection, 4:218 Thermocline, 2:242, 4:128, 4:129, 4:129F, 4:130, 4:130F, 4:167, 6:218 Banda Sea, 3:240 barrier layers and heat flux, 6:222 deep, Southern Oscillation not possible, 2:245 deepening, sea surface temperature rise, 2:242 definition, 4:165 depth El Nin˜o Southern Oscillation and, 2:231–234 empirical orthogonal functions, 2:285, 2:285F equatorial, empirical orthogonal functions, 2:285, 2:285F tropics, sea surface temperature and, 2:280 El Nin˜o conditions, 2:231–234, 2:242, 2:243F equatorial, oscillatory wind forcing response, 2:278 Langmuir circulation and, 3:405 La Nina conditions, 2:242, 2:243F main formation, 4:159–160 ocean circulation, 4:120–121, 4:121–122, 4:121F, 4:122 potential vorticity distribution see Potential vorticity subduction, 4:156, 4:158, 4:159, 4:159–160, 4:165
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formation, 4:159–160 ideal thermocline theory, 4:159–160, 4:160–161 stratification, 4:160 thermohaline circulation, 4:122 turbulence, 6:24, 6:24F see also Seasonal thermocline maintenance, 6:218–219 models, carbon cycle, 4:110–111, 4:110F permanent see Permanent thermocline polar regions, 6:218 pycnocline and, 6:218 seasonal see Seasonal thermocline shallow, Southern Oscillation short, 2:245 sound speed and, 1:101 thickness, hurricane Lili, 6:195T vertical advection and turbulent diffusion in maintenance of, 4:208 wave guiding action, 2:271 see also Upper equatorial thermocline Thermocline gravity waves, 6:212–213 Thermocline ventilation rate chlorofluorocarbons, 1:535–536 radiocarbon, 4:650–651, 4:651F Thermococcales (archaea), 2:77–78 Thermocouples, 5:387, 5:387F Thermography active, 1:155 passive, 1:155 Thermohaline circulation, 2:122, 2:126–127, 4:119–122, 4:126, 4:128, 6:218, 6:354 abrupt climate change and, 1:3, 1:4 Atlantic Ocean, 1:3, 1:4, 2:554 Baltic Sea circulation, 1:292–294 buoyancy fluxes, 4:122 chlorofluorocabon, 1:537 Coriolis force, 4:122 deep ocean currents, 4:122 see also Abyssal currents definition, 4:122 density, horizontal variations, 4:122 double-diffusive processes and, 2:169–170 Gulf Stream, 2:555–556 horizontal pressure gradient, 4:122 hyperthetical ocean model, 4:122 Late Cretaceous, 4:308 Mediterranean Sea circulation, 3:710–712, 3:713F eastern basin, 3:714–715 Eastern Mediterranean Transient (EMT), 3:716, 3:720, 3:724 thermohaline cells, 3:710–712, 3:711F, 3:714–715 western basin, 3:714 see also Eastern Mediterranean North Atlantic, 4:122 ocean basin bathymetry, 4:122 Red Sea circulation, 4:667 salinity, 4:122 stability, 4:125 surface polar currents, 4:122 thermocline, 4:122
Index western Mediterranean basin, Mediterranean Sea circulation, 3:714 see also North Atlantic Deep Water (NADW) Thermohaline convection, 5:127, 5:130 open ocean convection, 4:218 see also Climate change, abrupt; Heat transport; Open ocean convection; Thermohaline circulation Thermohaline forcing, 5:544 cold regime external ventilation, 5:544–547 internal recirculation, 5:547–548 modes, 5:544–547 warm regime external ventilation, 5:548, 5:548F Thermohaline interleaving, 3:298 Thermohaline staircases, 2:162, 2:163F Arctic, 2:167F diffusive convection and, 2:166 microstructure, 2:164 see also Double diffusion; Salt fingers Thermometers, 6:165–166 calibration, 1:709–710 CTD profilers, 1:714 response time, 1:714–715 electronic, 1:709–710 ‘global’ see ‘Global thermometer’ reversing, 1:708–709, 1:708F sonic, 5:388 subaquatic, 1:708–711 thin film, 6:152–153 types, 5:377, 5:378T see also Thermistors Thermophilic microbes archaea, 2:77–78 bacteria, 2:78 definition, 2:73–75 diversity, 2:77–78 habitats, 2:73–75, 2:75F and origins of life, 2:78–79 Thermoremanent magnetization (TRM), 3:26 Thermostad, 6:222 Thermotogales (bacteria), 2:78 Thermotolerant coliforms, sewage contamination, indicator/use, 6:274T Thermus (bacteria), 2:78 THETIS-2 experiment, 6:51–52, 6:54F Thick-billed murre, 1:171, 1:173F see also Alcidae (auks) Thin film sensors, measurement of turbulent dissipation see Turbulence sensors Thin film thermometers, 6:152–153 Thin layers, high-resolution fluorescence measurements, small-scale patchiness models, 5:478–479, 5:480F Thioploca, Peru-Chile Current System, 4:390 Thiothrix (microbes), 2:77 Third-order sea level change see Million year scale sea level variations
Third-party liability, shipping and ports, 5:407 Thorium (Th), 6:235–237 bioturbation tracer as, 1:396–397 counting, 6:246 crustal abundance, 4:688T dissolved, 4:696 distribution, 6:245 properties in seawater, 4:688T distribution, governing equations, 6:248 isotopes, 4:106–107 reversible exchange between forms, 6:236–237, 6:237F nepheloid layer flux, 4:13–15 Thorium-228 (228Th), 6:247 distribution, Pacific, 6:247F Thorium-230 (230Th), 6:235–236, 6:238F, 6:247–248 sediment chronology, 5:328T sediment profile, 5:330F Thorium-232 (232Th), 6:233, 6:233T concentration depth profiles, 6:248F decay series, 6:244F dissolved, depth profile, 4:697F Thorium-234 (234Th) sediment chronology, 5:328T uranium-238 ratio, 6:247–248 Thorpe scales, 2:296 Thorp’s formula, 1:114 Thorson, Gunnar, 1:352T, 3:471 classification of the benthos, 1:349–350 distribution of benthic larvae, 1:353, 1:353F Three-box model, 4:97F Three-component ultrasonic anemometer, 3:106, 3:106F Three-dimensional (3D) fluorescence, 2:590, 2:591F Three-dimensional (3D) models estuary, 2:304 storm surges, 5:536, 5:538 Three-dimensional (3D) turbulence, 6:18–25 air–sea interactions, 6:23 anisotropic turbulence, 6:22–23, 6:23F causes, 6:18 computer simulation, 6:19F convective turbulence, 6:22 Corrsin scale, 6:22 density stratification, 6:24F stable, 6:22 unstable, 6:22 energy dissipation, 6:20, 6:20F, 6:24F in geophysical flows see Geophysical flows history of study, 6:18 hydraulic jump, 6:23, 6:24F internal gravity waves, 6:22, 6:22–23, 6:23F breaking, 6:23 main thermocline, 6:24, 6:24F mechanics of, 6:18–19 equilibrium, 6:19, 6:20 strain, 6:18–19, 6:19F
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viscous dissipation, 6:18–19, 6:19F, 6:20, 6:20F vorticity, 6:18–19, 6:19F momentum transport, 6:18, 6:22 ocean turbulence, length scales, 6:23–24 bottom boundary layer, 6:24, 6:24F Kolmogorov scale, 6:23–24 Ozmidov scale, 6:22, 6:23–24 surface mixed layer, 6:24, 6:24F tidal channels, 6:24, 6:24F open ocean convection see Open ocean convection rollup, 6:18–19, 6:19F scalar mixing see Scalar mixing stationary, homogeneous, isotropic turbulence, 6:19–21 statistical analyses, 6:19 energy spectra, 6:20, 6:20F, 6:23F dissipation subrange, 6:20 inertial subrange, 6:20 standard assumptions, 6:19 temperature spectra, 6:21, 6:21F inertial-convective subrange, 6:21 viscous-convective subrange, 6:21 viscous-diffusive subrange, 6:21 stirring, definition, 6:23 turbulent boundary layer, 6:23, 6:24F upper ocean mixing, 6:23, 6:24 velocity fields, 6:19–21 energy cascade, 6:20, 6:21 energy dissipation, 6:20, 6:20F molecular viscosity, 6:20 Reynolds number, 6:20, 6:20–21 vortex stretching, 6:18–19, 6:19F vortical modes, 6:22 see also Heat flux; Heat transport; Langmuir circulation; Mesoscale eddies; Momentum fluxes; Turbulence; Vortical modes Three-spined stickleback (Gasterosteus aculeatus), 2:378 Thresher, USS, 3:513 Throckmorton, Peter, archaeological artifacts, 3:696 Thrust anemometer, momentum flux measurements, 5:385 Thrust belts, accretionary prisms, comparison with, 1:33–34 Thulean basalts, eruption, 1:511 Thunnus (tuna), 2:377, 2:393 optimization of behavior, 2:377–378 see also Tuna (Thunnus) Thunnus alalunga (albacore tuna), 2:404–405, 2:404F Thunnus albacares (yellowfin tuna), 4:234, 4:234F acoustic scattering, 1:66 hook and line fishing, 4:235 pole and line fishing, 4:235–236 response to changes in production, 2:486–487 Thunnus maccoyii (southern bluefin tuna), 2:404–405, 3:444–445 Commission for the Conservation, 4:242 Thunnus obesus (big-eye tuna) acoustic scattering, 1:66
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Index
Thunnus obesus (big-eye tuna) (continued) economic value, 4:237 Thunnus orientalis (Pacific bluefin tuna), fisheries, historical aspects, 4:235 Thunnus thynnus (Atlantic bluefin tuna), 2:377–378, 2:395–396F, 2:474, 2:475 fisheries, historical aspects, 4:235 mariculture, 3:547 feeding, 3:532 marketing problems, 3:536 production systems, 3:534–535, 3:535 stock acquisition, 3:532 230 Thxs, definition, 6:242 Thysanoessa inermis (Euphausiidae), 3:352–353 Thysanoessa raschii (Euphausiidae), 3:352–353 Tiburon ROV, 2:26F, 4:746T, 6:260T, 6:261F TIC see Total inorganic carbon (TIC) Tidal analysis see Tide(s), analysis Tidal bore, 3:38 Tidal channels, turbulence, 6:24, 6:24F Tidal currents, 6:32 diurnal, 1:596–597 Intra-Americas Sea (IAS), 3:292–293 Kelvin waves, 1:596–597 Tidal cycles, 6:26 seal haul-out sites and, 3:600 Tidal dissipation astronomic evidence, 3:255 possible mechanism, 3:255 Tidal dynamics, 6:35–36 earth rotation, 6:35–36, 6:36–37 Kelvin waves see Kelvin waves Poincare´ waves, 6:37 standing wave, 6:37 long waves, 6:35–36, 6:36–37 nondispersive propagation, 6:36 no rotation, 6:36 reflection, 6:36 rotating earth, 6:36–37 standing waves and resonance, 6:36 definition, 6:36 energy, non-transmission of, 6:36 rotating earth, 6:37 Tidal energy, 6:26–31 extraction approaches, 6:27, 6:27–29, 6:29–30 nuclear power plants, 6:27 unconventional turbines, 6:29–30 power plants see Tidal power plants research directions, 6:30 utilizing, tidal power plants, 6:30 see also Tide(s), energy fluxes and budgets Tidal forces abyssal mixing and, 2:265, 2:267F astronomical periods, modulating, 6:35T energy input to oceans, 2:265, 2:267F lunar, 6:33, 6:34F potential energy budget and, 2:262–263 seismicity and, 3:847–849 solar, 6:34
Tidal friction, orbital parameters and, 4:312 Tidal mixing fronts, 5:392–393 circulation patterns, 5:395–396 current strength and, 5:393 dynamics, 5:393 nutrient supply mechanisms, 5:396–397, 5:397F position, 5:393, 5:393–395, 5:394F water depth and, 5:393 Tidal motions, 4:128 Tidal power plants, 6:28T design, 6:27–28 double action method, 6:27–28 flooding, 6:29 installations, potential sites, 6:29, 6:29T single action method, 6:28–29 Tidal prism, 2:299–300, 3:38 Tidal pumping, 2:303–304 Tidal straining, 2:300–301 Tidal streams effects on migration, 2:408–409, 2:408F, 2:409F see also Tidal currents Tidal wheels, 6:27 Tidal whirlpool, 6:57 Tide(s), 3:33, 6:32–39 age of, 6:34 analysis, 6:34–35 harmonic, 6:35 non-harmonic, 6:35 purpose, 6:34–35 response, 6:35 shallow-water tides, 6:39 tidal constants, 6:34–35 Atlantic Ocean, 6:37 biological processes, 6:38 Black Sea, 1:407 boundary conditions, oceanographic, waves, 3:33 coastal zone management see Coastal zone management continental shelf see Continental shelf currents see Tidal currents definition, 6:32 diurnal see Diurnal tides dynamics see Tidal dynamics energy fluxes and budgets, 6:38–39 internal tidal waves, dissipation by, 6:38 Moon-Earth system, 6:38 tidal friction, 6:38 see also Tidal energy equilibrium tide see Equilibrium tide fiords, 2:354 forces see Tidal forces freshwater input, 6:38 front positions and, 5:393–394, 5:395F geomorphology, tidal processes, 3:33, 3:38 global ocean, estimation from inverse methods, data assimilation, 2:11 gravity and gravitational potential, 6:32–33, 6:33 gravitational tides, definition, 6:32 gravity currents, 4:59
(c) 2011 Elsevier Inc. All Rights Reserved.
Moon-Earth system, 6:33, 6:33F, 6:34F energy loss, 6:38 ocean tides, 6:37 solar, 6:34 groundwater flow and, 3:89–90 impact on vertical migration, 2:413–414 internal mixing see Internal tidal mixing internal waves, 3:267, 3:270 Kelvin waves see Kelvin waves Laplace, 6:35–36 mapping, bathymetric data resolution requirements, 1:299T mixing in regions of freshwater influence (ROFI) and, 5:392 neap, definition, 6:32 see also Neap tide North Sea, 4:78, 4:79F ocean tides, 6:37–38 co-oscillation, 6:37 gravitational, 6:37 semidiurnal, 6:37 Okhotsk Sea, 4:200, 4:201, 4:201F period, definition, 6:32 pollutants, 6:38 potential energy budget and, 2:262–263 radiational, definition, 6:32 range, 6:35–36 definition, 6:32 residual circulation, 6:38 Rossby radius of deformation, 6:36–37 sediment processes, 6:38 sediment transport, 4:141–142 see also Sediment transport semidiurnal see Semidiurnal tides Southeastern Asian seas, 5:315–316, 5:315F spring, definition, 6:32 see also Spring tides storm surges, 5:532, 5:534F, 5:535–536 tide gauge data, 5:535, 5:538–539, 5:539F tide-surge models, 5:535–536, 5:539 submarine groundwater discharge (SGD) and, 5:553 tidal forces see Tidal forces tidal front formation in shelf seas, 6:38 tidal patterns, 6:32 see also Beach(es); Coastal trapped waves; Estuarine circulation; Geomorphology; Internal wave(s); Sea level changes/variations; Waves on beaches Tide-dominated beaches, 1:312–313 sand flats, 1:313 sand ridges, 1:313 tidal sand flat, 1:313 see also Tide-modified beaches Tide gauges, in estimation of recent sea level variations, 5:180, 5:180F Tide-modified beaches, 1:311–312 reflective plus low tide bar and rips, 1:312, 1:313F reflective plus low tide terrace, 1:311–312, 1:312F ultradissipative, 1:312, 1:312F, 1:313F
Index zones, 1:311 see also Tide-dominated beaches Tidepool sculpin (Oligocottus maculosus), 3:282 Tide wave, 6:26 energy of, 6:26–27 first tables, 6:26 high, ranges of amplitude, 6:26T internal mixing see Internal tidal mixing Tiger prawn (Penaeus esculentus), fishery assessment research, 1:703, 1:704F, 1:705F Tiki Basin, manganese nodules, 3:493, 3:494 Time closure, fishery management control systems, 2:516, 2:546 Time-lapse photography, floc layers, 2:548, 2:548F, 2:550F Time-resolved fluorometry, 2:590–591, 2:592F Time-series analysis, 4:718 orbital tuning and, 4:315 Time-series sediment traps, 1:371, 1:372 Time-space diagram see Hovmo¨ller diagram Time-stepping momentum, ocean climate models, 5:137–138 Time variability, upper ocean see Upper ocean Timor Passage, 3:238–239 mass transport, 3:239 Timor Sea, 5:306 Tin (Sn), inorganic, in oceanic environment, 1:200 Tinca tinca (tench), 2:451F Titanic, maritime archaeology project, 3:698 Titanium (Ti) concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:692–693 depth profile, 4:693F properties in seawater, 4:688T Tito Campanella, 4:770F Titration, salinity measurement, 1:711–712 Titration alkalinity (TA), benthic flux, 4:486–487, 4:488F TKE see Turbulent kinetic energy (TKE) TL see Transmission loss TMI see TRMM Microwave Imager (TMI) TMS see Tether management system (TMS) TMW (Transitional Mediterranean Waters), 3:717 Toadfish (Opsanus tau), 2:478–479 TOBI, 6:256T TOC (total organic carbon), river water, 3:395T Todores pacifica, acoustic scattering, 1:68–69 Todorokite, 1:258–259 Toe thrusts, 5:452, 5:454F
TOGA (Tropical Ocean – Global Atmosphere) Study, 2:173, 3:275, 3:278 Toggweiler model, radiocarbon, 4:648 Tokra Strait, Kuroshio Current, 3:360 volume transport, 3:360–362 seasonal cycle, 3:360–362 Tolo Harbor, red tides and associated fish kills, 2:318–319, 2:321F Tomography, 6:40–56 advantages, 6:40 barotropic and baroclinic tides, 6:50 convection, 6:49–50 data, perturbation field models, 6:43–44 data assimilation, 6:47 development, 6:40 example experiment, 6:41F forward modeling, 6:40–42 deep sound channel, 6:40 ray travel time, 6:42–43 heat content, 6:50–54 inverse modeling, 6:43 data, 6:43 horizontal slice, 6:46–47 ray properties, 6:45 ray travel times, 6:43 reference states, 6:43–44 time-dependent, 6:47 uncertainty, 6:45 vertical slice, 6:44–45 range-dependent, 6:45–46 range-independent, 6:45 noise, 6:40 observables, 6:41 principle, 6:40 resolution (spatial), 6:47F sampling density and, 6:46 resolution matrix, 6:44 results, 6:47–50 sampling geometry, 6:46, 6:48F satellite altimetry and, 6:50, 6:51F temperature conversion, 6:54–56 transceiver arrays ATOC, 6:55F Greenland Sea, 6:49F Puerto Rico, 6:53F THETIS-2 experiment, 6:54F travel-time perturbation depth profile, 6:46F TOMS (Total Ozone Mapping Spectrometer), 5:120 TON see Total organic nitrogen (TON) Tongs, molluskan fisheries, harvesting methods, 3:900F, 3:901 Toothed whales see Odontocetes (toothed whales) Toothfish Southern Ocean fisheries, 5:517 by-catch issues, 5:517 market value, 5:517 production, 5:517, 5:518T see also specific species TOPEX/Poseidon satellite, 5:66–67, 6:134, 6:135F altimetry, 3:256, 3:256F
(c) 2011 Elsevier Inc. All Rights Reserved.
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data, global ocean tides estimate, 2:10F, 2:11 internal tides, 3:264F measurements compared with models, 6:136F Rossby waves, 4:783, 4:784F Topex/Poseidon satellite altimeter system, 3:256, 3:256F, 5:58, 5:59F global sea level variability detection, 5:61–62, 5:62F mission, 5:181 Topographic eddies, 6:57–64, 6:59F biological implications, 6:63 coastal waters, 6:60, 6:63F deep sea water, 6:63 generation, 6:57 headland, generation mechanisms for, 6:61F historical evidence, 6:57 larger scale category, 6:58–60 reefs, 6:62–63 Reynolds number see Reynolds number shallow waters, 6:63 small-scale bottom topography, 6:62–63 stratified flows, bottom topography effects, 6:60–62, 6:62F Topographic features, seabird abundance and, 5:228–229, 5:228F Topographic focusing, surface waves, 4:772 Torne, Norway, dissolved loads, 4:759T Torpedo AUVs, 4:473 Tortonian–Messinian Global Boundary Stratotype Section and Point, 3:30, 3:31F Tortuosity, 4:490 Total Allowable Catch (TAC), 2:516, 2:523 demersal fisheries, 2:95 open ocean, 4:227–228 mackerel icefish, Southern Ocean fisheries, 5:517 see also Fishing quotas Total carbon dioxide signature, 6:95 photosynthesis and, 6:96–97 see also Carbon dioxide Total dissolved nitrogen (TDN) determination, 4:32 river water, 3:395T see also Dissolved nitrogen; Nitrogen cycle Total dissolved phosphorus, river water, 3:395T Total dissolved sulfur, river water, 3:395T Total inorganic carbon (TIC) benthic flux, 4:486–487 seasonal depth profile, Bermuda, 6:96F Total lipid extract (TLE), 5:423 Total organic carbon (TOC), river water, 3:395T Total organic nitrogen (TON), 4:50 Total oxidised nitrogen (TON) determinations, air-segmented continuous flow analyzers, 6:326, 6:326F
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Index
Total oxidised nitrogen (TON) (continued) flow injection analysis manifold arrangement, 6:328F Total Ozone Mapping Spectrometer (TOMS), 5:120 Total Ozone Vertical Sounder (TOVS), 5:120 Total precipitable water, 5:206–207 Total production export production vs., 4:680 see also Photosynthesis; Primary production Tourism diving see Diving tourism Mediterranean mariculture problems, 3:533 TOVS (Total Ozone Vertical Sounder), 5:120 Tow cable, types, 6:66 Tow cable drag, 6:65–66 depressing forces, 6:66 drag coefficient normal, 6:66, 6:66F, 6:71, 6:71F tangential, 6:66–67, 6:66F induced drag coefficient, 6:69 normal, 6:66 reduction, 6:67 faired cable winch, 6:74, 6:74F flexible ribbon and hair fairing, 6:67–68 ‘hair’ fairing, 6:67–68, 6:67F of normal drag, 6:67 ribbon and hair replacement, 6:68 ribbon fairing, 6:67–68, 6:67F, 6:70F rigid airfoil-shaped fairing, 6:67 rigid clip-on fairing, 6:67, 6:67F rigid compressive load, 6:67 rigid fairing expense, 6:67 rigid fairing tow-off, 6:67 wrap-round rigid fairing, 6:67, 6:67F tangential, 6:66, 6:66–67 vortex-induced oscillation, 6:66 TowCam, 6:255, 6:256F, 6:256T Towed deep-sea craft, 6:255, 6:257T Towed vehicles, 6:65–74 active depth control (with), 6:65 advantages, 6:65 methods, 6:69, 6:72 types, 6:65 advantages, 6:65 aerodynamics, 6:68–70 airfoil stall, 6:68, 6:68F, 6:69 angle of attack, 6:68F, 6:69, 6:69F aspect ratio, 6:69 cambered airfoil, 6:68, 6:68F, 6:69F delta wing, 6:69 depth control methods, 6:69, 6:72 forces and moment, 6:68, 6:68F, 6:72T induced drag coefficient, 6:69 passive towed, 6:70, 6:70F roll stability, 6:69–70, 6:70F vehicles generating lift, 6:68–70 vehicles not generating lift, 6:70 winged vehicles, 6:68, 6:68F
compared with autonomous underwater vehicles (AUV), 4:479 components, 6:65 controllable wings, 6:65 drag, 6:71, 6:72T flight control, 6:72 tow speeds, 6:72 undulating mode, 6:72 passive, 6:70, 6:70F, 6:73–74, 6:73F computer-controlled winch, 6:65 performance of vehicle/cable system, 6:70–71 computer-controlled winches, 6:65 depth range, 6:70F, 6:71, 6:71F equilibrium angle, 6:71, 6:71F equilibrium depth, 6:71, 6:71F, 6:72T normal drag coefficient, 6:71, 6:71F vehicle drag, 6:71, 6:72T sensors, 6:72–74 acoustic survey work, 6:73–74 CTD recorders, 6:68F, 6:72–73, 6:73F plankton collectors, 6:72 Seabird CTD instrument, 6:68F, 6:73F types, 6:65 wave-induced ship motion effects, 6:71–72 minimizing ship motion, 6:72 towing in rough seas, 6:71 without active depth control, 6:65 Towing, oceanographic research vessels, 5:412 Townsend, Belcher, Hunt wave growth model, 6:305–306 Toxic algae see Algae, toxic Toxic blooms see Algal blooms Toxins biotoxins, 2:160 bivalve concentration, 3:903 exotic species introduction impacts on society, 2:340 genotoxins, 3:565 phytoplankton blooms, 4:437–439 see also Phytoplankton blooms plankton viruses enabling hosts to produce, 4:469–470 TPD (Transpolar Drift), 1:212 TPXO.2 tidal model, 6:50 Trace element(s), 3:776 anthropogenic see Anthropogenic trace elements atmospheric deposition, 1:254, 1:254T behavior types, 3:776 conservative, 2:256T, 2:258, 3:776, 3:783 particle association, 2:258–260 see also Conservative elements (sea water) coral-based paleoclimate records, 4:339–340, 4:339T, 4:346 seasonal variation, 4:341 temperature reconstructions, 4:339T, 4:340 upwelling, 4:339T, 4:340–341 depth profile, 6:76–78 hybrid/mixed, 3:776, 3:783 land-sea global transfers, 3:396
(c) 2011 Elsevier Inc. All Rights Reserved.
ligands, biogenic, 6:84 nutrient-like (recycled), 2:256T, 2:258, 3:776, 3:783 particle association, 2:258–260 nutrients, 6:75–86 biological uptake, 6:80–82 chemical speciation, 6:78–80 distribution in seawater, 6:76–78 metabolic role, 6:82–84 seawater chemistry and, 6:76–78 oxyanions, 3:776–783 chemical speciation, 3:776 redox chemistry, 6:78–80 redox-controlled, 2:256T, 2:258 requirements for primary productivity, 4:586, 4:587 scavenged, 2:256T, 2:258, 3:776, 3:783 particle association, 2:258–260 in submarine groundwater discharge (SGD), 5:552–553 transient, 2:258 see also Cadmium; Cobalt; Copper; Elemental distribution; Iron; Manganese; Molybdenum; Nickel; Nutrient(s); Selenium; Transition metals; Zinc; specific trace elements Trace gases air–sea transfer, 1:157–162, 1:163–170 see also specific gases photochemical production/reactions, 4:416–417 Trace metals aeolian input, 1:124–126 aerosols, seawater solubility, 1:125, 1:125T fluvial input, 1:126T marine-influence rainwater, concentrations in, 1:125, 1:126T ferromanganese deposits, 1:260–261 isotope ratios, long-term tracer applications, 3:456–457, 3:456T leaching from rocks, 3:464–465 in marine atmosphere see Atmosphere photochemical production/reactions, 4:417–420 see also Refractory metals; Trace element(s) Tracer(s) categorization, 1:682 chemical, 4:119 deep convection, 2:20, 2:21 dynamic, potential vorticity, 6:287 see also Potential vorticity (PV) evaluation, 1:685–686 inverse modeling, 3:300–311 hybrid models, 3:305, 3:306F see also Inverse models/modeling Langmuir circulation, 3:404–405, 3:405, 3:410–411, 3:411 limitations, 1:685–686 long-term, 3:455 proxies, 3:455 long-term changes see Long-term tracer changes North Atlantic Tracer Release Experiment (NATRE), 6:287
Index nuclear fuel reprocessing see Nuclear fuel reprocessing ocean productivity see Productivity tracer techniques residence time, 3:455 section inverse modeling, conservation law, 3:303–304 transient, 4:159, 4:162 tritium-helium age, 4:159, 4:160F see also Tritium-helium dating transport, linear momentum, 5:137 types, 1:531 see also Chemical tracers; Radionuclides; Tracer release experiments; specific types Tracer budgets, 3:303–304 inverse methods, 2:290–291 limitations, 2:291 mixing estimation, 2:290–291 see also Chemical tracers Tracer fluxes boundary conditions, forward numerical models, 2:608 mesoscale eddies, 2:610–611 Tracer flux gauges, 6:97–98 Tracer injection, 1:153 Tracer release experiments, 6:87–92 air–sea gas exchange experiments, 6:89–90 dual tracer, 6:89–90 results, 6:89F biogeochemical patch experiments, 6:90–92 iron enrichment, 6:91–92 buoy marking, 6:90–91 current experiments, 6:92 deep ocean mixing experiments, 6:87–88 hydrodynamic forcing, 6:88 mixing, 2:290 North Atlantic Tracer Release Experiment, 6:287 results, 6:88 sulfur hexafluoride properties, 6:87 tracer release method, 6:87–88 see also Chemical tracers; Sulfur hexafluoride; Tracer(s) Tracers in the Ocean (TTO) North Atlantic Study (NAS), 4:641–642 Trachurus trachurus see Horse mackerel (Trachurus trachurus) Trachymedusae medusas, 3:10, 3:11F Trackers, passive sonar beamforming, 5:512 Tracking drifters, 2:172–173 RAFOS floats, 2:177–178 errors, 2:178 Trade international see International trade seaborne, global see World seaborne trade Trade-off enclosed experimental ecosystems, 3:732, 3:734F feeding-predator avoidance, 2:423
Trades biome, 4:359, 4:361T, 4:362F boundary, 4:359 zooplankton community composition, 4:357T Trade winds, 2:225–226 coastal upwelling and, 1:467, 1:469, 1:471F El Nin˜o events and, 2:235, 2:241, 2:242 Intra-Americas Sea (IAS), 3:287, 3:293–294 seasonal variation, 6:343 Traditional ecological knowledge, fishery management, 2:526 Traenadjupet slide, 3:790 Tragedies of the commons, fishery management, 2:527 Trailer suction dredging, 4:185, 4:187F Trailing-edge coasts, 3:33 Trammel nets, 2:540, 2:540F Transarctic Acoustic Propagation (TAP) experiment, 1:92–93, 6:52–54 Transduction chemical, chemical sensors, 1:10, 1:11 see also Molecular recognition element DNA, 4:471 Transects, trace element gradients across, 6:76 Transferable effort quotas, control systems, fishery management, crustacean fisheries, 1:705 Transfer coefficient, 3:1–2, 3:2F definition, 3:7 Transfer efficiency (of Photosystem II), 2:582 Transfer functions, fossil assemblage abundances and sea surface temperature, 2:108–110, 2:110F fossil groups used, 2:110–112 modern analog technique, 2:109–110 revised analog technique, 2:109–110 weighted average, 2:109 Transfer resistance, 1:149 air–sea gas exchange, 1:149 Transfer velocity, 1:149 air–sea gas exchange, 1:149 carbon dioxide vs. water vapor, 1:152F Transformation, DNA, 4:471 Transform faults mid-ocean ridges, 3:853F, 3:854, 3:864 propagating rifts and microplates, 4:597, 4:598F, 4:603, 4:604F Transforms (plate boundary) see Plate boundary transforms Transient tracers, 1:682 definition, 4:113 source strength, 1:684 see also Radionuclides Transient Tracers in the Ocean (TTO), 4:88 Transitional Mediterranean Waters (TMW), 3:717 Transition metals analytical techniques, 6:102 conservative type, 6:101, 6:102F distribution and concentrations, 6:100
(c) 2011 Elsevier Inc. All Rights Reserved.
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distribution maps, 6:102 micronutrient aspects, 6:107 mixed type, 6:102 nutrient type, 6:101–102, 6:102F oceanic profiles, 2:256T, 2:257–258, 2:259F as oxyanions, 3:776 scavenged type, 6:101, 6:102F speciation, 6:100–108, 6:102–103 biological effects, 6:106 inorganic, 6:103 organic, 6:103 supply to oceans, 6:100 see also Elemental distribution; Platinum group elements (PGEs); Trace element(s); specific transition metals Transition Zone Chlorophyll Front, 4:136 Transmission loss acoustics, 1:55–56, 1:56F geoacoustic parameters, 1:89–90, 1:90F Transmissometry, 3:245–246, 6:109–118 definition, 6:109 nephelometry vs., 6:109, 6:118 new technologies, 6:116–118 sensors (transmissometers), 6:111–113, 6:111F, 6:113F applications, 6:109, 6:115–116, 6:117T beam size and, 6:112–113 calibration, 6:113 components, 6:111, 6:111F deployment, 6:116 instrument transmittance, 6:111–112 measurements, 6:109–110, 6:110F particle size and, 6:112–113 resolution, 6:112 sensitivity, 6:112 see also Inherent optical properties (IOPs); Ocean optics; Optical particle characterization; Turbulence sensors Transparent exopolymer particles (TEP), 4:332–333, 4:333F Transpolar Drift, 1:212 Trans-Polar Drift Stream, 5:174–175 Transponders acoustic, in LBL, 6:265 autonomous underwater vehicles (AUV) navigation and, 4:478 Transport bioreactive elements, 4:96 Mediterranean mariculture, 3:532 Transport profile, Southern Ocean, 1:180F Traps, 2:540, 2:541F aerial, 2:541 corrals, 2:541, 2:541F crab fishing, 5:218 fyke nets, 2:540–541, 2:541F Pacific salmon fisheries, 5:13 pelagic fisheries, 4:235, 5:468–469 pots, 2:540, 2:541F stationary uncovered pound nets, 2:540, 2:541F stow nets, 2:541, 2:541F weirs, 2:541
626
Index
‘Trashfish,’ tropical fisheries development, 1:651–652 Trawlers tonnage, 2:544, 2:545F see also Fishing fleets Trawls/trawl nets, 2:537, 4:239, 5:469–470 beam, 2:537, 2:538F benthic species, disturbance, 2:204 bottom, 2:537, 2:538F, 5:517 bottom otter, 2:537, 2:538F bottom pair, 2:537, 2:538F coral impact, 1:672–673 midwater, 2:538, 2:538F, 5:515, 5:517 midwater otter, 2:538, 2:538F midwater pair, 2:538 otter multiple, 2:537–538, 2:538F seabed effects, 2:204–205 habitat modification, 2:204–205 twin principle, 2:537–538 zooplankton sampling see Zooplankton sampling Treasure hunters, Spanish galleon relocated, 3:700 Trenches coastal trapped waves, 1:593 nepheloid layers and, 4:17 see also Deep ocean passages Tributyltin (TBT), 1:203, 1:204, 1:205 in oceanic environment, 1:200 oyster farming, risks to, 4:283, 4:283F seabirds as indicators of pollution, 5:275 Trichechidae see Manatees Trichechus inunguis (Amazonian manatee), 5:439, 5:439F see also Manatees Trichechus manatus (West Indian manatee), 5:437–439, 5:438F see also Manatees Trichechus manatus latirostris (Florida manatee), 5:437, 5:438F, 5:441F, 5:443F see also Manatees Trichecus senegalensis (West African manatee), 5:439, 5:439F see also Manatees 2,4,5-Trichlorobiphenyl, structure, 1:552F Trichlorobiphenyls, structure, 1:552F Trichlorofluoromethane diffusion coefficients in water, 1:147T Schmidt number, 1:149T Trichodesmium, 1:252–253, 4:40 Tridacna squamosa (giant clam), 3:141–142 Trieste, sediment property measurements, 1:81–82 Trieste bathyscaph, history, 3:505, 3:511 Trieste submersible, 6:255, 6:255F Trinity Test, 4:638 Triple-junctions, microplates, 4:601–602 Triple point, water, thermometer calibration and, 1:709–710 Triple point cells, 1:709–710, 1:710, 1:710F Triploid oysters, 4:277 Tritiogenic helium, 6:277
Tritium (T, 3H), 6:119 bomb see Bomb tritium circulation tracer, 4:106–107, 4:107 components, 6:119, 6:119F cosmogenic production rate, 1:680T Ekman pumping, 6:121 half-life, 6:119 northern hemisphere, 6:119, 6:119F nuclear fusion weapons, 6:119 in the oceans, 6:119–122 southern hemisphere, 6:119, 6:120F ‘spike’, 6:121–122 subpolar gyre, 6:121 tracer applications, 1:683T vapor exchange, 6:120 Tritium-helium-3 age air–sea gas exchange experiments, 1:153 definition, 4:113 Tritium-helium-3 tracing, 6:94 isopycnal mixing and, 6:94 mixing and, 6:94–95 Tritium-helium dating, 6:119–126 advection–diffusion equations, 6:125–126 age distribution, 6:123F, 6:124 concept, 6:122–123, 6:123F in ocean, 6:122–126 water mass mixing, effects of, 6:125, 6:125F, 6:125T TRMM Microwave Imager (TMI), 5:97, 5:206 measurements restricted to tropical regions, 5:97 provides SST in the tropics, 5:97 see also Tropical Rainfall Measurement Mission (TRMM) Trolling, pelagic species, 4:237 Trophic cascade, phytoplankton blooms, 2:510 Trophic effect, 4:52 Trophic levels, 4:707 definition, 3:622 fisheries landings, 2:206F, 2:207 marine mammals see Marine mammals, trophic level(s) Tropical Atlantic Study (TAS), 4:641–642 Tropical Atmosphere-Ocean array, 2:231–234, 2:234F sea temperature depth profiles, 19961997, 2:234F Tropical cyclones, 2:327–328, 5:465 cross-section, 6:193F heat potential, 6:172F storm surges areas affected, 5:532, 5:534F, 5:535F, 5:539 prediction, 5:532, 5:536–537 Tropical ecosystems continental margin area, 4:257F, 4:258T continental margins, primary production, 4:259T Tropical fisheries, 1:651–654 coral reef see Coral reef fisheries development, 1:651–652 Gulf of Thailand, 1:651 ecosystem perspective, 1:652
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environmental impact, 1:652–653 globalization impact, 1:651, 1:653 growth/development, 1:651 habitat features, 2:511 marine protected areas, 1:653–654, 3:673 poverty issues, 1:653 taxonomic diversity, 1:652 Tropical instability waves (TIWs), 2:286, 2:286F Tropical Ocean – Global Atmosphere (TOGA) Study, 2:173, 3:275, 3:278 Tropical oceans, ocean thermal energy conversion, 4:167 Tropical Pacific waters, 3:444, 3:446 Tropical Rainfall Measurement Mission (TRMM), 5:207–208, 5:380 evaporation, estimation of, 2:329 see also TRMM Microwave Imager (TMI) Tropical regions, 6:231 Tropical spiny rock lobster (Panulirus ornatus), 3:539 Tropical Surface Water, southern Agulhas Current, 1:133–134 Tropical Waters (TW), Brazil Current, 1:422, 1:424F Tropic birds see Phaethontidae (tropic birds) Tropics rainfall, 6:171 wind direction, 6:342 Troposphere, dimethylsulfide, 1:159 Trout, freshwater, farming, 5:23 Trumpet fish (Aulostomus maculatus), 2:377 TS characteristics see Temperature–salinity (TS) characteristics TS curve, see also Temperature–salinity (TS) characteristics Tsunami(s), 6:127–140 amplitude, 6:127, 6:133–134 causes, 6:127, 6:129–132 earthquakes, 6:129–132 landslides, 6:132, 6:132–133 volcanic eruptions, 6:133 definition, 5:465–466 early warning system, 6:137F, 6:138–139, 6:138F effect on shore, 6:127 etymology, 6:127 historical and recent, 6:128–129 Intra-Americas Sea (IAS), 3:287, 3:294 inundation maps, 6:133 modeling, 6:133–134 bathymetric data resolution requirements, 1:299T coastal effects, 6:134–137 frequency dispersion, 6:134 generation and propagation, 6:133–134 linear shallow water equations, 6:134 wave dispersion, 6:133–134
Index period, 6:127 prediction, 6:128 recent, 6:128 runup height, 6:127–128 sediment flow during, 5:463 sediment transport process initiation, 5:450 seiches, 5:348–349 shoaling, 6:127 speed, 6:127 warning systems, 6:133 wave height, 6:137F wavelength, 6:127, 6:133–134 see also Banda Aceh Tsunami earthquakes, 6:129–132, 6:132 Tsushima Current, 3:359F, 3:360 TTO (Transient Tracers in the Ocean), 4:88 Tubeworm Pillar, 3:134–135, 3:135F see also Vestimentiferan tubeworms Tubeworms see Polychaetes/polychaete worms; Vestimentiferan tubeworms Tucker trawl, 6:356, 6:356F Tucuxi (Sotalia fluviatilis), 2:149, 2:156 Tuna (Thunnus), 2:377, 2:393, 4:234, 4:234F, 4:368 acoustic scattering, 1:66 Atlantic/Pacific fisheries, 4:368 canning, 4:240 description and life histories, 4:368 diet, 4:135 distribution, biogeochemical provinces and, 4:362–363 economic value, 4:239 fisheries see Tuna fisheries metabolic rates, 4:234 principle species, 4:368 topographic eddies, 6:57 utilization, 4:240–241 see also Thunnus (tuna); specific species Tuna fisheries by-catch issues, 2:202 dolphin mortality associated, 4:241–242 Mediterranean, 4:368 world landings, 4:240, 4:240F see also Pelagic fisheries Tungsten (W), 3:776, 3:779, 3:783 concentrations in ocean waters, 6:101T depth profile, 3:777F, 3:779 Tunicates bioluminescence, 1:377T, 1:379–380 Larvacea/Appendicularia, 3:16, 3:17F, 3:18 Salpida, 3:17F Thaliacea, 3:16 Doliolida, 3:16–17 Pyrodomida, 3:16 Salpida, 3:17–18, 3:17F Turbidites, 5:447–450, 5:448F, 5:462F characteristics, 5:460 dimensions, 5:455T slide determination, 5:450 Turbidity sewage contamination, indicator/use, 6:274T
see also Nephelometry; Suspended particles Turbidity currents, 5:448F, 5:459–462 characteristics, 5:449F, 5:449T, 5:461–462 cross-section, 5:461F debris flows and, 5:460 definition, 5:459–462 deposits, 5:447–450 gravity-based mass transport/sediment flow processes and, 5:447–467 misclassification, 5:461–462 non-rotating gravity currents, 4:59 recognition, 5:464 rotating gravity currents, 4:790, 4:791 sandy unit, 5:460, 5:461F Turbidity flows, sediment thermal conductivity and, 3:43–44 Turbidity maximum, estuarine circulation, 2:303–304, 2:303F Turbidity minimum, 4:15 Turbidity sensors see Nephelometry, scattering sensors Turbid plumes, 4:187 Turborotalita quinqueloba, 2:109F Turbot, mariculture disease, 3:520T, 3:521 Turbulence, 5:455–456, 6:148–150 3D see Three-dimensional (3D) turbulence air–sea heat flux and, 6:339 benthic boundary layer, 6:141–147 see also Breaking waves; Threedimensional (3D) turbulence boundary layers see Turbulent boundary layers breaking waves and, 1:433–436 dissipation level transients, 1:434–435 energy dissipation, 1:433, 1:434, 1:436 measurement, 1:433 causes, 6:18–19 definition, 2:612, 2:617–618, 6:58, 6:148 diffuse seafloor flows, acoustic backscatter and, 1:71–72 dissipation, 6:148, 6:149F rate, 6:148–149, 6:149F temperature cutoff scale, 6:149–150, 6:150, 6:151F velocity spectra, 6:148, 6:149F viscous cutoff scale, 6:148–149, 6:150, 6:151F dissipation measurement, 6:148–149, 6:150, 6:150F, 6:153 free-fall profilers, 6:151 horizontal, 6:151–152 sampling frequency, 6:150, 6:151F sensors see Turbulence sensors temperature fluctuations, 6:149–150, 6:150F, 6:152–153 units, 6:150 velocity fluctuations, 6:148–149, 6:149F, 6:150, 6:153 vertical profilers, 6:150, 6:150F, 6:151
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as dissolved silicate source, 3:681 eddy formation see Turbulent eddies Ekman layer, 6:141–143 energy dissipation, 3:371 geostrophic, 5:134 homogeneous isotropic energy transfer from large to small eddies, 5:476 nature of, 5:476 small-scale patchiness, 5:475F, 5:476–477 increase in predator-prey encounter rates, 5:491 intermittency, 2:616–617 laboratory studies see Laboratory turbulence studies Langmuir circulation and, 3:407 length scales, 6:23–24 mixing and see Turbulent mixing Navier–Stokes equation, 6:148 in one-dimensional models, 4:208–209 power-law relations, 3:373–374 shear forces, breaking waves, 1:433 shear stress, 3:198 surface layer buoyancy and, 6:339–340 thermodynamics, 3:371 tidal mixing fronts, 5:393 under-ice boundary layer, 6:155, 6:157–158 upper ocean see Upper ocean wall layer, 6:144 wind flow wave growth and, 6:305 wave onset and, 6:304–305 see also Kelvin–Helmholtz shear instabilities; Langmuir circulation; Plankton and small-scale physical processes; Reynolds number; Shear instability; Turbulent diffusion Turbulence sensors, 6:148–154, 6:150–152 acoustic current meters, 6:153 airfoil probes, 6:151–152 thin film sensors vs., 6:152 Pitot tubes, 6:152 temperature microstructure sensors, 6:152–153 of conductivity, 6:153 thermistors see Thermistors thin film thermometers, 6:152–153 thin film sensors, 6:152 airfoil probe vs., 6:152 disadvantages, 6:152 thermistors vs., 6:152–153 see also Momentum flux measurements Turbulent activity coefficient, 2:616 Turbulent boundary layers, 2:579–580 3D turbulence, 6:23, 6:24F open ocean convection, 4:223F rotating gravity currents, 4:795 Turbulent density flux, 2:295–296 Turbulent diffusion, 4:732 advection in maintenance of ocean thermocline and, 4:208 dissolved gases, 1:148
628
Index
Turbulent diffusion (continued) Lagrangian ecosystem modelling and, 4:212 molecular diffusion and, 4:732 Turbulent eddies, 2:324, 3:198, 5:382–383 Ekman transport, 2:223–224 Turbulent heat flux, 2:289, 6:164–165 under-ice boundary layer, 6:161, 6:161F see also Latent heat flux Turbulent kinetic energy (TKE), 6:158, 6:160F benthic boundary layer, 6:144 breaking waves, 1:434 budget, mixed layer, 6:341 of ocean mixed layer, 4:210, 4:216F, 6:341 turbulent mixing rate and, 2:295 wall layer, 6:144 Turbulent mixing, 2:610, 4:128 compared with salt fingers, 2:164 deep ocean, observations in, 2:122–128 diapycnal, forward numerical models, 2:610 diffusivity-kinetic energy relation, 2:263–264 eddy correlation measurement, 2:291–292 laboratory studies see Laboratory turbulence studies neutral buoyancy surfaces and, 4:25–26 numerical simulation, 2:288F parameterization approaches, 2:610 tides, 3:257 timescale, general circulation model, 3:20 upper ocean, 6:211 Turbulent momentum, primitive equation models, forward numerical, 2:608 Turbulent shear stress, 3:198 Turbulent stress Ekman solution, 6:156 under-ice boundary layer, 6:156 Turbulent temperature gradient variance, 2:289–290 Turkey, Black Sea coast, 1:211, 1:401 Turkey Point thermal plume, 6:14–15 Tursiops truncatus see Bottlenose dolphins (Tursiops truncatus) Turtle-excluder devices, 1:652 fishermen’s resistance to, 2:203 fishing methods, by-catch minimization, 2:546 Turtles by-catch issues, 2:203 oil pollution, 4:196–197 see also Sea turtles Turtle submersible, Bushnell’s, 3:513 TW (Tropical Waters), Brazil Current, 1:422, 1:424F T-wave acoustic underwater eruption observation, 3:155 Twenty foot equivalent unit (TEU), 5:401 Twin principle trawl nets, 2:537–538 Two-box model, 4:96 limitations, 4:96–97
Two-dimensional models, estuary, 2:304 Tylos, 5:50 Tylos granulatus see Pill bug (Tylos granulatus) Typhoons storm surges, 5:532 see also Tropical cyclones Tyrrhenian Sea salinity microstructure, 1:712F thermohaline staircases, 2:163F
U UBL see Under-ice boundary layer (UBL) UCDW see Upper Circumpolar Deep Water (UCDW) UK economic value of salmon fisheries, 5:4, 5:4–5, 5:5 flooded marshes of East Anglia, 5:44 improvement of salmon habitat, 5:3 reduction in salmon netting, 5:3, 5:9 UK37, 3:912 Ukraine, Black Sea coast, 1:211, 1:401 Uldolmok Strait, floating tidal power plant, 6:31F ULES (upward-looking echo sounders), 5:157 Ultralow frequency band (ULF), 1:52–54 definition, 1:52 wave–wave interaction noise see Wave–wave interactions Ultrashort baseline (USBL) acoustic navigation, towed vehicles, 4:478 Ultrasonic sounds, 3:650 Ultraviolet absorbance spectroscopy see Absorbance spectroscopy Ultraviolet radiation, 3:244 UV-B radiation, ozone, concentration effects, 4:414 see also Solar radiation Ulvaria subbifurcata (radiated shanny), 5:491 UNCLOS see United Nations Convention for the Law of the Sea (UNCLOS) UNCTAD (UN Conference on Trade and Development), 5:406 Undaria pinnatifida (a brown seaweed), 5:320F Under-ice boundary layer (UBL), 6:155 basic concepts, 6:155–157 buoyancy flux, 6:157, 6:159F characteristics, 3:198–201, 3:199F drag, 3:198–201, 3:208 history, 6:155–157 molecular sublayer, 3:198 outer layer, 3:199 outstanding problems, 6:161 rotational physics, 6:155–157 roughness elements, 3:198–199 seasonal cycle, 6:157 stress vectors, 3:200 supercooling, 3:202 surface layer, 3:198
(c) 2011 Elsevier Inc. All Rights Reserved.
temperate open ocean boundary layers vs., 6:155 turbulence, 6:157–158 scales of, 6:158–160 velocity vectors, 3:200 Undertow, 6:313 Underwater flow cytometers, development of, 6:117–118 Underwater light fields examples, 4:625–628 Hydrolight simulations, 4:625F, 4:626F, 4:627F, 4:628F see also Ocean optics; Radiative transfer (oceanic) Underwater Sound Laboratory, 1:92 Underwater video profiler (UVP), 6:368 Undulating oceanographic recorder (UOR), 6:359–361 UNEP, Oceans and Coastal Areas Program, 3:668T UNESCO equation of state, yn neutral density surfaces and, 4:28 Uniformitarianism, 3:34 United Nations (UN) Conference on Environment and Development, Rio de Janeiro, 1992, 1:600 Conference on Straddling Fish Stocks 1993-1995, 2:495 Environment Program, Oceans and Coastal Areas Program, 3:668T FAO see Food and Agriculture Organization (FAO) Joint Group of Experts on Marine Environmental Protection (GESAMP), 4:526 Law of the Sea Convention see United Nations Convention for the Law of the Sea (UNCLOS) World Commission on Environment and Development, Our common future report (Brundtland report), 1:600 United Nations Committee on Fisheries, Code of Conduct for Responsible Fishing, 2:515, 2:520 United Nations Convention for the Law of the Sea (UNCLOS), 1:297, 2:494, 3:432, 4:242, 5:405, 5:415, 5:417 bathymetric requirements, 1:302 binding framework for Law of the Sea dispute settlement, 3:441 economists’ concerns, 2:494 long-term stability, 2:494 non-cooperation of states, 2:494 encouragement for technology transfer, 3:439 extensions, 3:432 fishery management, 2:515 fishery resources rights, 2:494–495 global marine pollution, 3:67–68 interaction between states, 2:494–495 International Court of Justice recognised by, 3:442 Law of the Sea, underlying principles, 3:432
Index marine policy emergence role, 3:665 rights/duties, on environmental protection under, 3:439 see also Law of the Sea United States Defense Meteorological Satellite Program (DMSP), 5:80, 5:81–82, 5:84F, 5:85F, 5:88–89, 5:88F United States of America (USA) artificial reefs, 1:227, 1:228F East Coast, slope stability, 3:795 El Nin˜o, rainfall, 2:236F Environmental Protection Agency, offshore drilling and oil spills, 4:749–750 hurricanes, 6:192–193 National Aeronautics and Space Administration (NASA) see NASA Navy, acoustics research, 1:92 Pacific salmon fisheries, 5:12 catch, 5:14F, 5:15F, 5:17F, 5:19F, 5:20F, 5:21F power station, thermal discharge example, 6:11F Salmo salar (Atlantic salmon) farming, 5:24 tsunami early-warning system, 6:138–139 water, microbiological quality, 6:272T see also entries beginning US Univariate methods, pollution, effects on marine communities, 4:533, 4:534–535 Universal Tree of Life, 2:75 University National Oceanographic Laboratories System (UNOLS), 2:22–23, 2:27F University of Heidelberg, air–sea interaction research facilities, 1:154T University of Miami, air–sea gas transfer, 1:154T University of Washington autonomous underwater vehicles, 6:263T AUVs, 4:473 Unmanned underwater vehicles (UUV), 4:475 active sonar images, 5:509 see also Autonomous underwater vehicles (AUVs) Unsteady flow, 5:466 definition, 5:451 UOR (undulating oceanographic recorder), 6:359–361 Upper Circumpolar Deep Water (UCDW), 1:425, 1:426F, 1:427 overturning circulation and, 1:189F water properties, 1:180F see also Circumpolar Deep Water (CDW); Lower Circumpolar Deep Water (LCDW) Upper equatorial thermocline, turbulence, 6:24, 6:24F Upper Labrador Sea Water, 1:537 Upper mixed layer, 2:98, 6:217–218
Upper North Atlantic Deep Water, 2:20 see also North Atlantic Deep Water (NADW) Upper North Atlantic Intermediate Water, 1:746 Upper ocean advective fluxes, 6:165 air–sea fluxes, 6:211 bubbles, 1:439 measurement of, 1:439 optical effects, 1:443 circulation, Southeast Asian seas, 5:312 distributions (heat/water), 6:166–170 diurnal heating, 6:170F equatorial thermal structure, 2:271F freshwater budget, 6:163–174 climate change and, 6:172–173 processes governing, 6:163–165 freshwater distributions, 6:170–171, 6:171F heat budget, 6:163–174, 6:163–165 processes governing, 6:163–165 heat distribution, 6:166, 6:166–170 heat flux, 6:164–165 diurnal, 6:166 global distribution, 6:169F inversions, 6:222–224 main layers, 6:217–219 mean horizontal structure, 6:175–184 barrier layer, 6:180–181, 6:180F definition, 6:175 equatorial region, 6:182–183 mixed layer, 6:178–180 permanent thermocline, 6:181–182 polar regions, 6:183–184 property fields, 6:175–178 salinity distribution, 6:176–178, 6:178F seasonal thermocline, 6:178–180 subtropical gyres, 6:181–182 measurements, 6:165–166 mixed layer, modeling, coordinate choice, 5:138–139 mixing, 4:208 3D turbulence, 6:23, 6:24 mixing processes, 6:185–191, 6:187F breaking waves, 6:188–189 convection, 6:187–188 historical observations, 6:185, 6:186F ice, presence of, 6:190–191 Langmuir circulation, 6:189 nocturnal mixed layer, 6:185 parameterizations of, 6:191 precipitation, effects of, 6:190 superadiabatic surface layer, 6:185 temperature ramps, 6:189–190 turbulence, 6:190 wind-driven shear, 6:189 wind forcing, 6:188–189 one-dimensional physical model, 5:478, 5:479F response to strong atmospheric forcing events, 6:192–210 see also Hurricane structural variability, vertical, 6:221–222
(c) 2011 Elsevier Inc. All Rights Reserved.
629
surface freshwater exchanges, 6:165 surface heat exchanges, 6:164–165 surface mixed layer see Surface mixed layer temperature, interannual variation, 6:167–168 time and space variability, 6:211–216, 6:212F climatic signals, 6:215 convection, 6:211–212 eddies, 6:213–214 fronts, 6:213–214 internal waves, 6:212–213 Langmuir circulation, 6:211–212 mixing, 6:211 physical balances, 6:211 seasonal cycles, 6:215 turbulence, 6:211 wind-forced currents, 6:214–215 tracer constraints, 6:94F vertical structure, 6:217–224, 6:217F see also Barrier layer; Fossil layers; Inversions; Mixed layer Upper waters, 6:293–295, 6:295F, 6:297 Upward-looking echo sounders (ULES), 5:157 Upward-looking profiling sonar, 1:93–94 Upwelling, 6:231 Baltic Sea circulation, 1:293–294, 1:294F Benguela Current see Benguela Current California Current, 1:461–463, 1:463, 1:464F Canary Current see Canary Current, coastal upwelling coastal, small-scale patchiness, 5:481, 5:484F coral-based paleoclimate research, 4:339T, 4:340–341 definition, 3:774 as dissolved silicate source, 3:680F, 3:681 El Nin˜o Southern Oscillation and, 2:235 equatorial, productivity reconstruction, 5:339–340, 5:339F Gulf of Alaska, 1:456, 1:457F index, 1:469 modeling, radiocarbon and, 4:107 particle flux variability, 6:1–2 Peru-Chile Current System (PCCS), 4:387–388, 4:391 Portugal Current see Portugal Current, coastal upwelling radiocarbon, 4:647 submesoscale, plankton distribution, 5:481, 5:482F Trade Winds and, 1:467, 1:469, 1:471F tropical Pacific, El Nin˜o Southern Oscillation (ENSO) and, 2:235, 2:238 see also Coastal trapped waves; Coastal upwelling; Upwelling ecosystems Upwelling ecosystems, 6:225–232 chemical environment, 6:227 iron cycle, 6:227 nitrogen cycle, 6:227
630
Index
Upwelling ecosystems (continued) nutrient concentrations, 6:227 oxygen depletion zones, 6:227 regeneration of nutrients, 6:227 see also Iron fertilization climatic forcing and food web responses, 6:229–231 ecosystem resilience, 6:231 El Nin˜o-Southern Oscillation (ENSO), 6:229–230 Coriolis force, 6:225 defined/described, 6:225 ‘ecosystem’ defined, 6:225 El Nin˜o-Southern Oscillation (ENSO) chemical changes, 6:229–230 effects on fish populations, 6:230 effects on nutrient availability, 6:230 food web characteristics, 6:225–226 non-upwelling systems, 6:225 optimal light and nutrients, 6:226 primary productivity, 6:226 food web function quantification, 6:227–228 increased nutrient transfer efficiency, 6:228 Ryther’s explanation, 6:228 understanding unique traits, 6:227–228 food web structure and function, 6:228–229 adaptations in higher organisms, 6:229 diatoms blooms, 6:229 dominance of, 6:228 factors influencing size, 6:228–229 sedimentation, 6:229 large diatom/large grazer food path, 6:229 see also Microbial loops new vs. regenerated production, 6:228 nutrient transfer efficiency, 6:229 physical setting, 6:226–227 diagram, 6:226F geographic locations, 6:226–227 response to wind field, 6:227 role of winds, 6:226–227 see also Alaska Current; Antarctic Circumpolar Current; California Current; Canary Current; Pacific Ocean equatorial currents; Portugal Current planktonic foraminifera, 4:609 recovery, ENSO and, 6:230–231 seabird populations and, 5:248 types, 6:225 see also Ocean gyre ecosystems; Pelagic biogeography; Pelagic fish(es); Plankton Upwelling irradiance, 1:391, 3:246–247 Upwelling radiance, 5:115 Uranascopus spp. (stargazers), 2:474 Uranium (U), 6:233 anoxic environments, 6:246 dissolved, distribution, 6:246
isotope ratios, 6:246 depth profile, 6:246F example, 6:237F isotopic composition of sea water, 6:233T oceanic supply, 5:327 underground estuaries, 5:553 see also Uranium-thorium series isotopes Uranium-235 (235U), 6:233, 6:233T decay series, 6:244F palladium-231 activity ratio, 6:248–249 Uranium-238 (238U), 6:233, 6:233T decay series, 6:244F Uranium-thorium decay series, 6:233– 243, 6:234F disequilibrium, 6:234–237, 6:235F mobile parent with particle-reactive daughter, 6:234–237, 6:235T reactive parent with mobile daughter, 6:239–240, 6:239T focusing factor, 6:235–236 isotopes, distribution of, 6:233–234, 6:233T isotopes in ocean profiles, 6:233–234 processes investigated by, 6:242T radionuclides, distribution of, 6:233 scavenging, 6:235–236, 6:236F scavenging control, conceptual model of, 6:238F scavenging residence time, 6:234T Uranium-thorium series isotopes, 5:327, 6:244–254 cosmogenic radionuclide tracers and, 1:685 distribution, 6:245–246 actinium, 6:252–253 palladium-231, 6:248–250 radium, 6:251–252 radon-222, 6:250–251 thorium, 6:246–248 uranium, 6:246 sediment depth profiles, 5:328–329 supply to oceans, 6:244–245 atmospheric and sediment interfaces, 6:245 rivers, 6:244–245 in situ production, 6:245 see also Thorium (Th); Uranium (U) Urashima, 6:263T, 6:264F Urbanization, Mediterranean mariculture problems, 3:533 Urchin barrens, 5:198–199, 5:199F see also Sea urchins Urea profile, Black Sea, 1:216F, 1:405F Urey, Harold, 1:502 Uria, 1:171T diet, 1:174 see also Alcidae (auks) Uria aalge, 1:171 Uria lomvia (Brunnich’s guillemot), 1:171, 1:173F Urick, R J, 1:52 Ursell number, 6:313 Ursids, 3:605, 3:608T Ursus maritimus see Polar bear (Ursus maritimus)
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Uruguay, water, microbiological quality, 6:272T US 1988 Ocean Shipping Reform Act, 5:406 US 1990 Oil Pollution Act (OPA), 5:406, 5:407 USBL (ultrashort baseline acoustic navigation multibeam), 4:478 US Coast Survey, 3:122 US Commission on Ocean Policy, Ocean blueprint for the 21st century, A, 1:603–604 US Minerals Management Service, offshore structures and, 4:749–750, 4:751, 4:752 US National Data Buoy Center, 3:923 US National Weather Service, SST record provided by, 5:380–381 USS Thresher, 3:513 UTIG ocean bottom seismometer, 5:367F, 5:368T U-Tow, 6:72 UUV see Unmanned underwater vehicles (UUV) UV see Ultraviolet radiation UV-B radiation, ozone, concentration effects, 4:414 UVP (underwater video profiler), 6:368
V V230, definition, 6:242 V231, definition, 6:242 Vaccination, mariculture see Mariculture diseases Validation of data, for data assimilation in models, 2:2 Vanadium (V), 1:249–250, 4:586 atmospheric concentration, 1:249T concentrations in ocean waters, 6:101T depth profile, 3:777, 3:777F oxic vs. anoxic waters, 3:777 Vancouver Island Coastal Current, 1:455, 1:458–459 Van Drebel, Cornelius, shallow-water submersibles, 3:513 Vapor exchange tritium, 6:120 see also Air–sea gas exchange Vapor flux, measuring, direct method, 2:324–325 Vapor-phase organic carbon (VOC), land–sea exchange, 1:122 Vapor power cycle, 4:168–169 Vapor pressure definition, 2:325T temperature vs., 2:327, 2:327F Vaquita (Phocoena sinus), 2:154F, 2:159 VAR (vector-autoregressive functions), 4:720 Vargula spp. ostracod, 1:376–378 Variable fluorescence induction, 2:583 Variance, regime shift data, 4:718–719
Index Vascular plants lipid biomarkers, 5:422F applications, 5:422 species, 2:140 see also specific vascular plants Vector-autoregressive (VAR) functions, 4:720 Vector averaging current meter (VACM), 5:429–431, 5:429F, 5:430T, 5:432 Vegetation salt marshes and mud flats, 5:43–44 terrestrial, and monsoon generation, 3:911 see also Plants; Salt marsh vegetation Vehicles autonomous underwater see Autonomous underwater vehicles (AUVs) deep-sea, 6:255–266 autonomous, 6:260–265 future prospects, 6:265–266 human-operated (submersibles), 6:255–257 navigation, 6:265 remotely-operated, 6:257–260 towed, 6:255, 6:256T human operated see Human-operated vehicles (HOV) ROVs see Remotely operated vehicles (ROVs) towed see Towed vehicles Veined rapa whelk (Rapana venosa), environmental impact, 3:908 Velocity defect law, 6:142–143 Velocity logs, 4:478 Velocity profiles, benthic boundary layer, 6:145 bottom stress estimates, 6:146–147 Velvet scoter (Melanitta fusca) fisheries interactions, 5:270–271 see also Seabird(s) Vema, 4:296 Vema Channel, 2:565F, 2:566, 2:567F long-term measurements, 2:569–570, 2:570F Vema Gap, 2:565F Venezuela, water, microbiological quality, 6:272T Venice, storm surges, 5:532 Vent(s), hydrothermal see Hydrothermal vent(s) Ventana remotely operated vessel, 2:26F, 4:746T, 6:260T Ventilation deep convection, 2:15 definition, 4:113 Intra-Americas Sea (IAS), 3:292 oceanographic research vessels, 5:412 Ventilation depth, 6:219 Ventral grooves, definition, 1:287 Verdine, 1:567 Vernatide, 1:258–259 Vertical, definition, 2:290 Vertical advection, along neutral buoyancy trajectories, 4:26–27, 4:27F
Vertical density gradient, open ocean convection, 4:222 Vertical diffusivity, salinity and temperature, salt fingers and, 2:165–166 Vertical eddy diffusivity, 6:58 Vertical eddy viscosity, Ekman dynamics, 6:350 Vertical erosion, meddies, 3:706–707 Vertical line array (VLA), acoustic noise data, 1:57F, 1:58–59, 1:59 Vertical migration see Fish vertical migration Vertical profilers internal tides, 3:261 internal waves, 3:268–269 Vertical relative vorticity, vortical modes, 6:287 Very low frequency band (VLF), 1:54–55 Crouch/Burt data, 1:54–55, 1:55 deep ocean noise, 1:55 definition, 1:52 Nichols data, 1:55 noise mechanisms, 1:55 shallow water noise, 1:55 shipping noise, 1:55, 1:57 spectral density, 1:54–55 wave-wave interactions, 1:55 wind speed, 1:54–55 Vesicomyid clams, 3:137F Calyptogena magnifica, 3:133–134, 3:137F ecophysiology, 3:162 hydrogen sulfide detoxification, 3:162 hydrogen sulfide transport, 3:162 microhabitat, 3:162, 3:162F oxygen transport, 3:162 symbiotic bacteria, 3:162 Galapagos Rift, 3:137F symbiosis, 3:153, 3:162 vent community dynamics, 3:154–155 see also Hydrothermal vent biota; Hydrothermal vent ecology; Hydrothermal vent fauna, physiology of Vessel(s) see Oceanographic research vessels; Ship(s); see Ship(s) Vessel discharges environmental protection and Law of the Sea, 3:440 see also Discharge contaminants; Ocean dumping Vessel monitoring systems (VMS), fishery management surveillance, 2:525 Vesteris seamount, off-ridge non-plume related volcanism, 5:300, 5:303F Vestimentiferan tubeworms Riftia pachyptila see Riftia pachyptila symbiosis, 2:76, 3:133–134, 3:152–153, 3:152F Tevnia jerichonana see Tevnia jerichonana trophosome, 3:133–134, 3:152–153 vent community development, 3:141–142, 3:141F, 3:142F, 3:154–155
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631
Vibriosis, vaccination, mariculture, 3:522T, 3:523 Victor 6000, 6:260T, 6:261F Victor ROV, 4:746T Video cameras, remotely operated vehicles (ROVs), 4:743 Video plankton recorder (VPR), 4:250, 4:349, 4:353, 4:353T, 6:357T, 6:365–366, 6:367F, 6:371 image, 4:354F Viperfish (Chauliodus macouni), 4:6F Viral disease, mariculture see Mariculture Viral hemorrhagic septicemia virus (VHSV), mariculture disease, 3:520T, 3:521 Virginia Beach, Virginia, USA, coastal erosion, 1:585F Viruses, 3:800, 4:465, 4:467, 4:468, 4:471 abundance, 4:467 analytical flow cytometry, 4:247 attack of bacterioplankton, 1:275 blooms, control by, 4:470 contributing to bacteria mortality, 4:465, 4:468–469 description, 4:465–466 effects on host species composition, 4:470 general properties, 4:465–466 genetic transfer, 4:471 life cycles, 4:466F lytic infections, 4:467–468 movement via aquaculture, 2:334 plankton see Plankton viruses reproduction, 4:465–466, 4:466F resistance to, 4:470–471 see also Plankton viruses Viscosity benthic boundary layer, 6:143–144 surface, gravity and capillary waves, 5:573, 5:579–580 see also Reynolds number Viscous boundary layer, dissolved gas diffusion, 1:148 Viscous cutoff scale (Lv), turbulent dissipation, 6:148–149, 6:150, 6:151F Viscous remanent magnetization (VRM), sediments, 3:27 Viscous scale, 6:143 Viscous shear stress, 3:198, 3:199F Viscous stress, internal energy and, 2:262–263 Viscous sublayer, 6:141, 6:141F, 6:143–144 Visible and infrared scanning radiometer (VISR), 5:68 Visible light, absorption of, 4:414 Visible radiometry, 5:70 Vision dolphins and porpoises, 2:157 fish see Fish vision marine mammals, 3:587–588 remotely operated vehicles (ROVs), 4:742–743
632
Index
VISR (visible and infrared scanning radiometer), 5:68 Visual pigments, fish vision, 2:450–451 spectral absorption, 2:451–454, 2:454F bioluminescence detection, 2:453, 2:455F cone visual pigment, 2:453–454, 2:456F fresh/saltwater species differences, 2:452–453 optical environment, 2:453, 2:455F optimization, 2:454 range, 2:451–452 spectral responses, 2:456 limits, 2:456 proving color vision, 2:456 structure, 2:450–451 chromophore and opsin, 2:450–451 factors affecting absorption spectrum, 2:451 Vitamin B12, 6:83 Viviparity, 1:356, 2:428 VLA (vertical line array), acoustic noise data, 1:57F, 1:58–59, 1:59 VLF see Very low frequency band (VLF) VOC (vapor-phase organic carbon), land–sea exchange, 1:122 Volatile organic compounds (VOCs), estuaries, gas exchange in, 3:6 Volcanic arc magmas, accretionary prisms, 1:31F, 1:32 Volcanic crust, discovery of organisms in, 2:48 Volcanic environments, clay minerals, 1:565–567 Volcanic eruptions, tsunamis and, 6:133 Volcanic glass, diagenetic reactions, 1:266T Volcanic growth faults, 3:865–866, 3:865F development, 3:865F Volcanic helium, 6:124–125, 6:277–284 history, 6:277–279 hot spots, 6:280–283 isotopic composition, 6:277 mid-ocean ridge, 6:279–280, 6:280F plumes, 6:283 subduction zone, 6:283 Volcanic passive margins, 3:218, 3:219–222, 3:223, 3:225 see also Large igneous provinces (LIPs) Volcanism abrupt climate change and, 1:5 Cretaceous, ocean circulation and, 4:320–321 mid-ocean ridge see Mid-ocean ridge tectonics, volcanism and geomorphology off-ridge see Seamounts and off-ridge volcanism sea level rise and, 5:189 Volcanoes magnetic anomalies, 3:486–487 particulate emission, 1:248 whole, abyssal hills development model, 3:864–865, 3:865F
Volterra, Vito, 2:505, 2:510–511 Volume attenuation (sound in seawater), 1:103–104, 1:104F Volume backscattering, measurement, zooplankton sampling, 6:369 Volume displacement, gliders, 3:60 Volume scattering coefficient, marine organisms, 1:64 Volume scattering function (VSF), 3:245, 6:110 bio-optical models, 1:387–388 measurement(s), 3:246 constraints, 6:111, 6:117 sea water, 4:622, 4:622F see also Nephelometry particle size and, 6:110–111 Rayleigh scattering and, 6:110–111 Volume scattering phase function, 4:623 Voluntary observing ships (VOS), 2:328–329, 3:107, 5:202 satellite meteorological measurements, 5:380 von Foerster equation, 4:549 von Karman constant, 3:198, 4:221–222, 6:341 von Karman vortex street, topographic eddies, 6:58, 6:59F von Karman vortices, Intra-Americas Sea (IAS), 3:292F, 3:293 Vortex force (Langmuir force), 3:406–407 Vortex stretching, three-dimensional (3D) turbulence, 6:18–19, 6:19F Vortical modes, 6:285–289 aspect ratios, 6:286, 6:287 basin scales, 6:286–287 Burger number, 6:286 definition, 6:285 energy ratios, 6:286, 6:286F, 6:287 fine-scale, 6:285, 6:287 Doppler shifting, 6:287, 6:288–289 generation mechanisms, 6:285, 6:287, 6:287–288 identification, 6:288–289 internal waves, 6:287, 6:288 isopycnal diffusivities, 6:287 observational challenge, 6:288–289 isopycnals, 6:286F, 6:287–288 mesoscale, 6:287 Meddies, 6:287 passive fine-structure, 6:285 potential vorticity see Potential vorticity pycnoclines, 6:287, 6:288 shear/strain ratio, 6:288–289 stretching vorticity, 6:287 three-dimensional (3D) turbulence, 6:22 vertical relative vorticity, 6:287 vorticity Rossby number, 6:286 see also Acoustics, deep ocean; Acoustics, shallow water; Diffusion; Dispersion; Double-diffusive convection; General circulation models (GCMs); Internal tidal mixing; Internal tides; Internal wave(s); Rossby waves; Threedimensional (3D) turbulence;
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Tracer(s); Upper ocean, mixing processes Vortices seabed, sediment entrainment and, 1:44–46, 1:45F see also Langmuir circulation Vorticity absolute conservation of, 4:781–782, 4:782F definition, 4:781–782 subtropical gyres, 6:351 conservation of, 4:781–782, 4:782, 4:782F, 4:784–785 meddies, 3:702 non-rotating gravity currents, 4:59–60, 4:62 potential see Potential vorticity relative, 6:287 Rossby waves, 4:781–782, 4:782, 4:782F, 4:784–785 stretching, 6:287 tomography, 6:40 see also Vortical modes Vorticity conservation equation, 2:618 Vorticity equation, conservation/ dissipation features in equations, 3:22 Vorticity Rossby number, vortical modes, 6:286 VOS see Voluntary observing ships (VOS) VPR see Video plankton recorder (VPR) VSF see Volume scattering function (VSF)
W Wa¨chterha¨user, Gunter, origins of life, 2:78–79 Wadden Sea (Netherlands) riverborne nutrients, 2:316F seaduck–fisheries interactions, 5:270–271 Wainae Volcano, 5:455 Waipara (New Zealand), fossil penguins, 5:520 WAIS see West Antarctic Ice Sheet (WAIS) Wake Island Passage, 2:565F Walker circulation, 3:910 Walleye pollock see Theragra chalcogramma (Alaska/walleye pollock) Wall layer flow, 1:433–434 Wall layer scaling, 6:188, 6:188–189 Walruses see Odobenidae (walruses) Walsh, Don, 6:255 Walvis Passage, 2:565F Wandering albatross (Diomedea exulans), 4:590, 4:591F, 4:594, 4:596, 5:240 see also Albatrosses Waning flow, 5:466 Wanninkhof, 1:488–489 Wanninkhof gas exchange parameterization, 1:152, 1:153F dual tracer gas exchange results and, 6:90, 6:90F
Index Waquoit Bay, 3:90, 3:91F seepage meter measurements, 3:92F subterranean estuary, 3:95F Warm core rings (WCR), 5:99, 6:192 hurricane Ivan, 6:202–203 hurricane Katrina, 6:203–205 hurricane Rita, 6:205 Loop Current and, 6:198 Warm Deep Water, 6:323 Warming phase, upwelling and return flow, 4:128–129 Warm poleward flow, 4:126 ‘Warm Pool,’ El Nin˜o, satellite remote sensing of SST, 5:97–98 Warm saline intermediate water, bottom currents and, 2:80, 2:81 War/war-related activities coral disturbance/destruction, 1:676 World War II vessels, 3:698 WASIW (Western Atlantic Subarctic Intermediate Water), temperaturesalinity characteristics, 6:294T, 6:297F Wasp-waist flow control, 4:700–702 Wastewater re-use, sewage disposal, 6:271 Watch circle, 3:923 Water beaches, microbial contamination, 6:267–268 density, front structures and, 5:398 depth, seabird abundance and, 5:228–229 loss from Earth’s surface, 4:262–263 see also Origin of oceans meteoric origin, 4:261 microbiological quality, guidelines/ standards, 6:272T origin of oceans and see Origin of oceans quality, aquarium fish mariculture see Aquarium fish mariculture sources, on Earth, 4:263 steady-state on Earth, 4:264 triple point, thermometer calibration and, 1:709–710 waves, 6:300 see also Sea water; entries beginning water Water budget Baltic Sea circulation, 1:288, 1:291–292 Mediterranean Sea circulation, 3:710 Water-column profiles/profiling autonomous underwater vehicles (AUV), 4:475, 4:477 Massachusetts Bay, 4:481F Water-leaving radiance, 5:114, 5:115 satellite vs.in situ measurements, 4:738F SeaWiFS data, 5:122F Water mass(es), 3:447 conversion, 4:130 deep convection, 2:20–21 definition, 6:291, 6:292 global distribution, 6:293–297, 6:295F, 6:296F individual water parcels, 4:126 interdecadal changes, 4:129F
interleaving, 6:223–224 intermediate-depth, 4:128 investigated by uranium-thorium decay series, 6:242T Mediterranean Sea circulation, 3:718F acronyms, 3:721T formation, 3:711F, 3:712–714, 3:714–715, 3:723–724 transformation, 3:715F, 3:717–718 newly formed, 4:127 off West Australia, 3:447–449 properties, diffusion, 6:293 salinity structure, 3:449F seabird distribution and, 5:227, 5:227F upper ocean mixing see Upper ocean, mixing processes Weddell Gyre, transformation, 6:324 Weddell Sea circulation characteristics, 6:320F, 6:322, 6:323 properties, 6:319, 6:320F see also Water types and water masses Water-mass interleaving, 6:223–224 Water movement, coral reef aquaria, 3:530 Water packets, chemical tracers and, 4:110–111 Water pressure manned submersibles see Manned submersibles (deep water) relationship to depth, 1:348 Water temperature aquarium fish mariculture, 3:526 effects, demersal fisheries, 2:93, 2:93F natural sea surface, 6:10 thermal discharges, effects of, 6:10–11 Vema Channel, 2:569–571 see also Sea surface temperature (SST); Sea water Water transparency, 4:738–739 see also Light attenuation coefficient Water transport, internal waves, 3:267–268 Water types and water masses, 6:291–299 bottle sampling, 6:291, 6:299 Brazil and Falklands (Malvinas) Currents see Brazil and Falklands (Malvinas) Currents conservative properties, 6:291 core-layer method, 6:292 core properties, 6:292, 6:298–299 TS characteristics see Temperature–salinity characteristics deep and abyssal waters, 6:296–297, 6:296F diffusion of water mass properties, 6:293 electronic profiling systems, 6:291, 6:299 formation region, 6:291, 6:292 global distribution, 6:293–297, 6:295F, 6:296F intermediate waters, 6:292, 6:295, 6:296F upper waters, 6:293–295, 6:295F, 6:297 water type, definition, 6:292
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633
see also Alaska Current; California Current; Kuroshio Current; Ocean circulation; Ocean Subduction; Oyashio Current; Pacific Ocean equatorial currents; Thermohaline circulation; Water mass(es); Winddriven circulation Water vapor bubbles, 1:439–440 flux, measuring, direct method, 2:324–325 temperature deficit and, 5:91–92 variability requiring atmospheric correction algorithm, 5:92 Water velocity fluctuations see Turbulence measurements, based on electrical properties see Electrical properties of sea water vertical, float measurement, 2:177 Wave(s) on beaches see Waves on beaches breaking see Breaking waves; Wave breaking coastal trapped see Coastal trapped waves dynamics see Wave dynamics edge see Edge waves equatorial see Equatorial waves generation, by wind, 6:304–309 see also Wave generation; Wave growth; Wind gravity see Gravity waves height see Wave height internal see Internal wave(s) long surface, satellite remote sensing application, 5:107F, 5:109–110, 5:110F ocean surface, 3:33 see also Surface, gravity and capillary waves; Surface waves power see Wave power rogue see Rogue waves sediment transport, 4:141–142 see also Sediment transport statistics see Wave statistics types, 3:36, 3:36F, 3:37F wind see Wind waves see also other specific types of waves Wave action conservation, 5:577 Wave age, 6:306 Wave breaking, 1:431, 5:580, 6:304, 6:314 acoustic noise, 1:57, 1:58, 1:59–60 dissipation, 1:60 individual breaking events, 1:60 Kennedy data, 1:59, 1:59F Kerman data, 1:59 see also Acoustic noise; Wind-driven sea surface processes beaches, 6:314 breakers, 6:312 break point, 6:310F, 6:311–312, 6:313 processes, 6:313 see also Wave-dominated beaches
634
Index
Wave breaking (continued) bubble formation, 1:440 bubbles, 5:580 deep-water, 1:431–438 eddy viscosity, 5:576–577 energy loss, 5:580 internal tides, 3:258, 3:264–265 internal waves, 3:270, 3:271, 3:272, 6:23 measurement, 1:436 modeling, 5:578, 5:580 momentum loss, 5:573, 5:580 North Atlantic, 5:580F onset, 1:432 periodicity, 1:431–432, 1:432F surface films, 5:571 turbulence see Breaking waves upper ocean mixing, 6:188–189 wave growth and, 6:306 wave saturation and, 1:432 whitecaps, 6:334 wind speed and, 1:431–432 see also Breaking waves Wave-current interactions, 4:772 focusing, 4:772, 4:772F Waved albatross (Phoebastria irrorata), 5:239–240, 5:240 see also Albatrosses Wave-dominated beaches, 1:305–306 bar number, 1:310–311 dissipative beaches, 1:307F, 1:308F, 1:310, 1:310F erosion, 1:311 intermediate see Intermediate beaches modes of beach change, 1:311 reflective beaches, 1:306, 1:307F, 1:308F relative tide range see Relative tide range (RTR) system, 1:305, 1:306F see also Waves on beaches Wave dynamics equatorial waves, 2:273–274 shallow-water equations, 2:274–275 free-wave solutions, 2:274–275 Wave energy conversion, 6:300–303 buoy system, 6:300 historical aspects, 6:300 wave power see Wave power geomorphology, 3:36, 3:36F beaches, 3:37, 3:37F deltas and estuaries, 3:38 rocky coasts, 3:36, 3:36F Wave generation coastal trapped waves, 1:596, 1:596–597 internal waves see Internal wave(s) parasitic capillary waves, 5:579, 5:579F rogue waves see Rogue waves shear waves on beaches, 6:315–316 surface waves, 6:304–309 by wind, 6:304–309 see also Wave growth; Wind Wave growth field observations, 6:306–307
atmospheric pressure at sea surface, 6:305 high wind speeds, 6:306 mature growth, 6:305–306 Miles theory, 6:305 Townsend, Belcher,Hunt, 6:305–306 nonlinear interactions, 6:304, 6:307–308 onset, 6:304–305 rates, direct measurement, 6:306–307 sea-air momentum transfer, 6:307–308 theories, 6:304–305 wave breaking and, 6:306 wind modeling, 6:308 Waveguides, 6:314 acoustic noise, 1:54, 1:57–58, 1:58, 1:58–59 Rossby waves, 4:781–782, 4:788 Wave height North Atlantic Oscillation and, 4:68–69 sea state and, 1:109T wind speed and, 6:304–309 satellite altimetry, 5:63–64 see also Satellite scatterometers; Surface, gravity and capillary waves; Wind-driven circulation Wavelength, optical fibers, evanescent wave penetration and, 1:9 Wavelength selector, absorptiometric chemical sensors, 1:9, 1:10 Wavelet analysis, 5:88 Wavenumber integration acoustic modeling, 1:119 Wave power conversion, economics of, 6:302–303 exploitation, 6:301–302 floating oscillating water column, 6:302, 6:302F fundamental frequency, 6:302 mathematical expression, 6:301 resource, 6:301–302 Waves on beaches, 6:310–317 beach topography, 6:310F, 6:314 sediment transport, 6:310F shear waves, 6:315–316 steepness, 6:312, 6:314–315 breaking see Breaking waves; Wave breaking circulation, 6:313–314 currents see Current(s) depth dependent processes, 6:313 dynamics, 6:310–312 depth variation, 6:311, 6:313 energy density, 6:311, 6:311T phase velocity, 6:311, 6:311T wave power, 6:311, 6:311T wave steepness, 6:312 edge waves see Edge waves energy evolution, 6:310F, 6:316 energy flux, depth variation, 6:311 generation, 6:310 groups, 6:314, 6:316 group velocity, 6:311T infragravity waves see Infragravity waves leaky modes, 6:314
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linear, kinematic properties, 6:311T longshore currents see Longshore currents longshore uniform, definition, 6:310 longshore variable, definition, 6:310 monochromatic, 6:311–312, 6:313 definition, 6:310 properties, 6:311, 6:311T nonlinear, 6:312, 6:313 offshore, processes, 6:310, 6:310F, 6:311 properties, 6:310, 6:311T radiation stress see Radiation stress random, 6:311–312, 6:313, 6:314 definition, 6:310 reflection, 6:314 refraction, 6:311, 6:314 refractive focusing, 6:313–314 rips, 6:313–314 rollers, 6:313 sand bars, 6:314, 6:315 sediment transport, 6:310F, 6:313, 6:314 set-down, 6:312–313 set-up, 6:312–313, 6:313, 6:314 shear waves see Shear waves shoaling, 6:310, 6:310F, 6:311–312, 6:312–313 significant wave height, 6:312–313 definition, 6:312 surf beat, 6:314 surf zone definition, 6:310 processes, 6:310F, 6:311–312, 6:312–313 swash, 6:312, 6:314–315, 6:315T undertow, 6:313 wave height, 6:311, 6:312, 6:314 wavelength, 6:311T wave momentum flux, 6:311T see also Beach(es); Breaking waves; Coastal circulation models; Coastal trapped waves; Sea level changes/ variations; Surface, gravity and capillary waves; Wave-dominated beaches Wave statistics 2-D field, 4:774–775 Gaussian size distribution, 4:773–774 Weibull distribution, 4:774 Wave tank experiments rogue waves, 4:776 wave growth, 6:307 Wave–wave interactions acoustic noise, 1:52–54 causes, 1:53–54 microseism spectral density, 1:54 pressure spectral density, 1:53–54 very low frequency band (VLF), 1:55 wind-speed, 1:52, 1:54, 1:54F surface, gravity and capillary waves, 5:578, 5:578–579 Waxing flow, 5:466 WCP (World Climate Program), 3:275 WCR see Warm core rings (WCR) WCRP (World Climate Research Program), 3:275
Index Weather climate differences, 2:242 forecasting, for coastal regions, satellite remote sensing, 5:112–113 ocean decadal variability and, 4:714 predictability, loss of, 2:3 prediction ocean prediction for, data assimilation models, 2:3 Southern Oscillation and, 2:242 westerly, frequency time-series, 1:633–634, 1:635F Weather center data, model evaluation and, 1:696 Weathering, chemical see Chemical weathering Webb, Doug, 2:176, 3:59 Weddell-Enderby Basin, sea ice thickness, 5:155 Weddell Front, 6:323 definition, 6:318 Weddell Gyre, 1:737F, 1:740–742, 6:318, 6:319F, 6:321–322 Antarctic Coastal Current see Antarctic Coastal Current barotropic currents, 1:741–742 bottom boundary layer, 6:322, 6:322F Circumpolar Deep Water, 6:323 current velocities, 6:321–322, 6:322F eddy field, 6:323 export, 1:741–742 global ocean circulation, contribution to, 6:324 deep open ocean convection, 6:324 meridional exchange, 6:324 Weddell Sea Deep Water, 6:324 seasonal variations, 6:323 surface circulation, 6:319, 6:322, 6:322F surface currents, 1:741–742 transport, 1:735, 1:741–742 volume transport, 6:321–322 Warm Deep Water, 6:323 water mass transformation, 6:324 Weddell Sea Deep Water, 6:323, 6:324 see also Southern Ocean Weddell Polynya, 1:420, 5:147–148 Weddell–Scotia Confluence, 1:735–736, 1:736F, 1:741, 6:323 Weddell Sea, 4:127–128 bottom water formation see Weddell Sea Bottom Water diffusive convection, 2:167–168 pycnocline, outstanding problems, 6:161 sea ice, 5:160F cover, 5:148, 5:155F thickness, model evaluation, 1:695F see also Sea ice sea ice models, 5:167, 5:168F thermobaric instability, 6:162 thermohaline circulation, 6:218 water mass formation region, 6:297 see also Weddell Sea Circulation Weddell Sea Bottom Water Antarctic Coastal Current, 6:323 formation, 1:418–420
potential temperature, 1:419F shelf water, contact with ice shelves, 1:417–418 Weddell Sea circulation, 6:318–325 atmosphere-ocean interaction, 6:324 bottom water formation, 6:324 contribution to see Weddell Gyre current structure, 6:321–323 Antarctic Coastal Current see Antarctic Coastal Current measurement, 6:319 Scotia Front, 6:323 shelf waters, 6:323, 6:324 Weddell Front, 6:323 Weddell Gyre see Weddell Gyre Weddell-Scotia Confluence, 6:323 freshwater transport, 6:318 ice-ocean interaction see Ice–ocean interaction limits of, 6:318 geographic, 6:318 oceanographic, 6:318 measurements and observations, 6:318–321 ALACE floats, 6:319, 6:321F constraints, 6:318–319 geopotential anomaly measurements, 6:319 moored instruments, 6:319, 6:321F numerical models, 6:320, 6:322F sea ice drift, 6:319, 6:322 sea ice-ocean coupled models, 6:320–321 water mass properties, 6:319, 6:320F weather center data, 6:319, 6:320–321, 6:321 polynya see Polynyas; Weddell Polynya sea ice see Sea ice variability, 6:323–324 Antarctic Circumpolar Wave, 6:323–324 interannual, 6:323–324 seasonal, 6:323 water mass characteristics, 6:320F, 6:322, 6:323 Weddell Front see Weddell Front Weddell Gyre see Weddell Gyre see also Antarctic Circumpolar Current (ACC); Bottom water formation; Deep convection; Non-rotating gravity currents; Rotating gravity currents; Sub-ice shelf, circulation and processes Weddell Sea Deep Water (WSDW), 1:425, 1:426F, 1:427, 6:323, 6:324 Brazil/Malvinas confluence (BMC), 1:426F Weddell seal (Leptonychotes weddellii) dive duration and blood lactate concentration, 3:585, 3:585F myoglobin concentration, 3:584T see also Phocidae (earless/‘true’ seals) Weight-structured population models, 4:548 equations, 4:549 see also Population dynamic models
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Weirs Salmo salar (Atlantic salmon) harvesting, 5:1 traps, fishing methods/gears, 2:541 Wenz, G M, 1:52, 1:53F West Africa, particulate organic carbon (POC) flux, 3:310 West African manatee (Trichecus senegalensis), 5:439, 5:439F see also Manatees West America, particulate organic carbon (POC) flux, 3:310 West Antarctic Ice Sheet (WAIS), 3:215–216 disintegration, implications of, 5:184 see also Antarctic Ice Sheet Westerlies biome, 4:359, 4:361T, 4:362F boundary, 4:359 zooplankton community composition, 4:357T Westerly weather, frequency, time-series, 1:633–634, 1:635F Westerly wind(s), 2:276–279, 4:128, 4:129F, 4:131 Westerly wind bursts, 2:276, 2:277F satellite remote imaging, 5:209 Western Alaska sockeye salmon, population time series, 4:703F Western Atlantic salinity, 4:127, 4:127F see also Salinity Western Atlantic Subarctic Intermediate Water (WASIW), temperature–salinity characteristics, 6:294T, 6:297F Western Blanco Transform, 3:849F Western boundary current(s), 2:217, 5:495 sea-air heat flux, 6:339 see also specific currentssee specific oceans Western boundary current ecosystems continental margin area, 4:257F, 4:258T continental margins, primary production, 4:259T Western boundary layer currents, 6:346, 6:353 Agulhas Current see Agulhas Current Brazil Current see Brazil Current East Australian Current see East Australian Current (EAC); Gulf Stream Gulf Stream see Gulf Stream Kuroshio Current see Kuroshio Current measurement, 6:346 Sverdrup relation, 6:352 Western Boundary Undercurrent, sediment interflow, 4:15F Western Dutch Wadden Sea, riverborne nutrients, 2:316F Western equatorial Pacific Ocean, thermocline, 2:242 Western Indian Ocean, temporal variability of particle flux, 6:4F
636
Index
Western Interior Seaway of North America (Cretaceous), paleoceanographic model, 4:308–309 Western Mediterranean basin, Mediterranean Sea circulation bottom topography, 3:710, 3:711F geography, 3:710, 3:711F thermohaline circulation, 3:714 water mass circulation, 3:718F Western Mediterranean Deep Water (WMDW), 1:745–746, 3:717–718, 3:718F, 4:125 formation, 3:712–714 pathways, 1:747F, 1:748 Western Mediterranean Sea, 1:746–748 morphology, 1:744, 1:745F nitrogen, atmospheric input, 1:241T thermohaline circulation, 1:746 deep, 1:746, 1:747F intermediate layer, 1:746, 1:747F upper, 1:746, 1:747F see also Thermohaline circulation see also Mediterranean Sea Western North Atlantic Central Water (WNACW), temperature–salinity characteristics, 6:294T, 6:297F Western North Pacific Central Water (WNPCW), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F Western Pacific Ocean, mixing, indirect estimate, 2:297, 2:297F Western rock lobster see Panulirus cygnus (western rock lobster) Western South Pacific Central Water (WSPCW), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F Western Subarctic Gyre, 3:359F, 3:365 West Florida Shelf food web and water circulation coupled model, 4:723–724, 4:724F Gynodinium breve trajectories/model, 4:729–730, 4:730F regional model case study, 4:729–730, 4:730F West Greenland Current (WGC), 1:724, 4:122 transport, 1:724T see also Atlantic Ocean current systems West Greenland salmon fishery regulations, North Atlantic Salmon Conservation Organization, 5:6, 5:7T Salmo salar (Atlantic salmon), 5:6, 5:6F West Indian manatee (Trichechus manatus), 5:437–439, 5:438F see also Manatees West Kamchatka Current, 4:202, 4:202F West Spitsbergen Current (WSC), 1:213 reprocessing discharges, circulation of, 4:86 sea ice and, 5:141 water column profiles, 1:214F
Westward intensification of subtropical gyres, 6:352–353 Wet-bulb temperature, definition, 2:325T Wet chemical analyzers, 6:326–330 air-segmented continuous flow see Airsegmented continuous flow analyzers flow injection analyzers see Flow injection analysis (FIA) historical aspects, 6:326 in-situ monitoring, 6:329–330 constraints, 6:329–330 instrumentation, 6:329–330 ‘Wet’ deposition, 1:250, 1:250–252 atmospheric contaminants, estimation of, 1:239 iron, 1:124 WetLabs transmissometer, 4:8 Wetlands, carbon monoxide, 1:168 Whalebone whales see Baleen whales (Mysticeti) Whalers’ Bay, 5:141 Whales acoustic scattering, 1:69 baleen see Baleen whales (Mysticeti) exploitation see Commercial whaling prohibited species protection, fishery management, 2:516 Southern Ocean populations, harvesting impact, 2:205–206, 2:510–511, 5:513 toothed see Odontocetes (toothed whales) vocalizations, 1:55, 1:56–57 see also specific species Whaling commercial see Commercial whaling Southern Ocean fisheries, historical aspects, 5:513 Whaling industry, sperm and beaked whales, 3:649 Whiptail (Coryphaneodes subserrulatus), 1:63 acoustic scattering, 1:66 Whiptail gulper (Saccopharynx spp.), 4:6F Whirlpool, 6:57 Whitecaps, 1:431, 6:306, 6:331–336 coverage, wind-dependence of, 6:334 features, 6:335F global implications, 6:336 ocean color sensing and, 5:120 periodicity, 1:431–432 stage A, spilling wave crests, 6:331–332 alpha plumes, 6:331 bubbles, 6:331, 6:332F observations within alpha plume, 6:332 ocean surface coverage, 6:333F stage B, delaying foam patches, 6:332–334 beta-plume, 6:332–333 bubbles, 6:332–333 decay of, 6:332–333 ocean surface coverage, 6:333F size, discrepancies, 6:332–333
(c) 2011 Elsevier Inc. All Rights Reserved.
White-flippered penguin, 5:523 see also Eudyptula White noise, 4:715 atmospheric weather as, 4:714 WHOI see Woods Hole Oceanographic Institution WHOI-BB ocean bottom seismometer, 5:369T WHOI-SP ocean bottom seismometer, 5:368T, 5:370F Whole volcano, abyssal hills development model, 3:864–865, 3:865F Wideawake (Sterna fuscata), 3:423F see also Sternidae (terns) Wiedermann–Kramer saltwater formula, aquarium fish mariculture, 3:527T Wien displacement law, 4:380–381 Wild larvae collection, oyster farming, 4:276 Wilson, B W, 5:345 Wilson’s phalarope, 4:393 appearance, 4:393 diet, 4:398 distribution, 4:397 habitat, 4:396–397 migration, 4:398 names, 4:398, 4:399T surface-tension feeding, 4:395 see also Phalaropes Wilson’s storm petrel, 4:591F see also Procellariiformes (petrels) Winch, 6:74F computer-controlled passive towed vehicles, 6:65 towed vehicles, 6:65 deck, tether management system (TMS), 4:743–744 launch and recovery system (LARS), 4:744 oceanographic research vessels, 5:412 purpose-built, towed vehicles, 6:74, 6:74F Wind(s) cause/consequence of SST change, 2:241, 2:244, 2:244–245 deep convection, 2:19–20 direction measurement, wind vanes, 5:376–377, 5:376F problems for sensors, 5:377 sonic anemometers, 5:376F, 5:377 effect on waves, 3:33 El Nin˜o as consequence, 2:243–244 El Nin˜o Southern Oscillation, SST and, 2:231 forcing see Wind forcing fresh water outflows, 4:792 Indonesian throughflow and, 5:315 internal waves, 3:270, 3:271 numerical models, wave growth and, 6:308 open ocean convection, 4:221–222, 4:223, 4:224 seabird foraging behavior and, 5:231
Index seasonal variations, Intertropical Convergence Zone movements and, 1:235 Southeast Asian Seas, 5:306 speeds see Wind speed stress see Wind stress trade see Trade winds wave generation, 6:304–309 see also Wave growth; Wind waves see also Monsoon(s); entries beginning wind-driven; specific current systems; specific oceans Wind-driven circulation, 4:119–122, 4:126, 4:131, 6:346–354 Baltic Sea circulation, 1:292–294 coastal jets, 1:292, 1:292–293 Ekman transport and pumping, 1:292 potential vorticity, 1:292 sub-basin circulation, 1:292–293, 1:293F wind-induced currents, 1:288, 1:292F bathymetry, effect of, 6:353, 6:354 computer models, 6:353–354 density stratification, 4:120–121, 4:121–122, 6:353–354 dissipation, 6:353 drag coefficient, 6:350, 6:352 see also Drag coefficient earth’s rotation, effect of, 6:351 see also Coriolis force Ekman dynamics, 6:350–351 equatorial ocean, 6:354 extreme southern ocean, 6:354 fresh water exchange, 4:121–122 geostrophic currents see Geostrophic flow Gulf Stream, 2:555–556 idealized models limitations, 6:353 Munk, 6:352–353 Stommel, 6:352, 6:352F, 6:353F large-scale dynamics, 6:351–352 large-scale surface currents, 6:347F nonlinear effects, 6:354 observations and measurements, 6:346–349 density, 6:347 dynamic height, 6:347–349, 6:349F, 6:353F salinity, 6:346–347 ship drift, 6:346, 6:348F temperature, 6:346–347 wind systems, 6:346, 6:350 pressure gradients, estimation of, 6:347–349 Red Sea circulation, 4:667–668, 4:674 subtropical gyres see Subtropical gyres surface heat transfer, 4:121–122, 4:121F surface mixed layer, 6:349, 6:349–350 definition, 6:349 mixing mechanisms, 6:349–350 momentum mixing, 6:350 Sverdrup transport, 4:715, 6:352, 6:353, 6:354 thermohaline circulation see Thermohaline circulation
vertical extent, 6:354 western boundary layer currents see Western boundary layer currents westward intensification, 6:352–353 wind stress see Wind stress see also Surface, gravity and capillary waves; Wind waves; entries beginning wind-driven; specific currents Wind-driven currents, 4:128, 4:129–130 Wind-driven gyres, 4:126 Wind-driven sea surface processes, acoustic noise, 1:53F, 1:57–59 bubbles, 1:57, 1:58, 1:60 peak frequency, 1:59, 1:60 source spectral density, 1:58F, 1:59 Chapman/Cornish data, 1:58F, 1:59 Kennedy data, 1:59–60, 1:59F Kewley et al. data, 1:59 wind speed, 1:59 vertical directional spectrum, 1:57–59 reflection, 1:58 refractive shadow zone, 1:58 scattering, 1:58 wave breaking see Wave breaking Wind-driven shear, upper ocean mixing, 6:189 Wind-driven surface waves, satellite remote sensing, 5:105–106 Wind field Baltic Sea circulation, 1:292 major inflow events, 1:295 Red Sea circulation, 4:666–667, 4:674 Wind flow turbulence, wave onset and, 6:304–305 variability, wave growth and, 6:306 Wind-forced currents currents driven by, 4:128, 4:129–130 upper ocean, 6:214–215 Wind forcing abyssal mixing and, 2:264–265, 2:264F Antarctic Circumpolar Current, 1:185, 1:187 barrier layer formation and, 6:222 coastal trapped waves, 1:592, 1:594F, 1:595, 1:596, 1:596–597 eddies, formation of, 3:762 energy dissipation, 2:264–265 equatorial waves, 2:279–280 internal wave generation, 2:265 longshore wind stress, 1:596 mixed layer properties and, 6:218 North Sea, 4:78–80 ocean dynamics, 6:337–339 upper ocean mixing, 6:187–188 wave generation, 6:304–309 see also Wave generation work done (global), 2:266F see also Westerly wind bursts; Wind stress Wind-induced currents, Baltic Sea circulation, 1:288, 1:292F Wind roughness correction, 5:131 radar backscatter sensor, 5:131 Windrows, 3:404, 3:405F downwelling and, 3:405, 3:411
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formation time, 3:405 spacing, 3:405 threshold wind velocity, 3:404–405 see also Langmuir circulation Wind speed acoustic noise, 1:52, 1:54, 1:54–55, 1:54F, 1:59 albedo, 4:380 Black Sea, 1:402–404 bubble distribution, 1:443–444 gas exchange, 1:157–158 measurements, 5:375–377 calibration sensors, 5:375–376 cup anemometers, 5:375, 5:376F problems for sensors, 5:377 propellor anemometers, 5:375, 5:376F by satellite, 5:380 sonic anemometers, 5:376F, 5:377 Ocean Station Papa, 6:343F ocean surface and, 1:109T ocean surface drag coefficient and, 6:194F sea–air carbon dioxide flux, 1:493 surface films, 5:570 wave breaking and, 1:431–432 wave properties and, 6:306 see also Wind forcing whitecaps, 6:334, 6:336 see also Whitecaps see also Wind velocity Wind stress, 2:224, 6:348F, 6:350–351 Ekman transport relation, 2:225 equation, 6:350 governing equation, 6:193 hurricane Lili, 6:195T longshore, 1:596 Mediterranean Sea circulation, 3:710 momentum flux, 6:341 North Pacific, 1966-1986, 4:711F ocean frontal features, satellite remote sensing, 5:106 Red Sea circulation, 4:666–667 gyre formation, 4:668–669 Rossby waves, 4:787, 4:787F, 4:788 satellite remote sensing, 5:202–205 accuracy, 5:203 empirical function, 5:202–203 sea shelf front maintenance and, 5:398 storm surges, 5:531, 5:536–537 see also Drag coefficient; Wind forcing Wind vanes, 5:376–377, 5:376F Wind vectors, Peru-Chile Current System (PCCS), 4:386F Wind velocity, 2:224 El Nin˜o events and, 2:232F sea ice velocity and, 5:163F see also Wind speed Windward Passage, 3:286F, 3:287 subsurface flows, 3:291–292 Wind waves storm surges, 5:537–538 modeling, 5:537–538, 5:538F radiation stress, 5:538 shallow water, 5:538 wave age, 5:537–538
638
Index
Wind waves (continued) wave induced mean flow, 5:538 wave set-down, 5:538 wave set-up, 5:538 surface, gravity and capillary waves, 5:574F, 5:578 Winged snails (Pteropoda), 4:460 Wings, gliders, 3:59, 3:60 Winter (boreal), monsoon activity, Northern Hemisphere, 3:910, 3:910F Winter flounder, biomass, north-west Atlantic, 2:505–506, 2:506F Winter Intermediate Water (WIW), 3:717–718, 3:718F Winter skate, biomass, north-west Atlantic, 2:505–506, 2:506F Winter Weddell Gyre Study (WWGS), 5:155 Winter Weddell Sea Project (WWSP), 5:147–148 Wire grids, early maritime archaeology, 3:697 Wire ropes, 3:919–920 ‘3 x 19’, 3:920, 3:927 WIW (Winter Intermediate Water), 3:717–718, 3:718F WMDW see Western Mediterranean Deep Water (WMDW) WMO see World Meteorological Organization (WMO) WMO/IAEA, 6:119 WNACW (Western North Atlantic Central Water), temperature–salinity characteristics, 6:294T, 6:297F WNPCW (Western North Pacific Central Water), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F WOCE see World Ocean Circulation Experiment (WOCE) WOCE autonomous float, 2:174–176, 2:177–178 cost, 2:175 WOCE drifter, 2:173, 2:174F Woods Hole Oceanographic Institution (WHOI), 3:505–506, 5:66 autonomous underwater vehicles, 6:263T deep-towed vehicles, 6:256T Marine Policy Center, 3:665 remotely-operated vehicles (ROV), 6:260 Wordie Ice Shelf, 3:212–213, 3:212F, 3:213 Workboats, oceanographic research vessels, 5:412 World Bank, 3:275 currently funded projects, 3:275 Global Environment Facility (GEF), 3:275 World Climate Program, 3:275 World Climate Research Program (WCRP), 3:275
World Congress on Fisheries Management and Development (1984), flag state responsibility, 2:524 World fleet, 5:402–404 development, 5:402, 5:403T dry bulk carriers, 5:403–404 see also Dry bulk carriers financial performance, 5:404–405 charter rates, 5:404–405, 5:404T shipping investment returns, 5:405 general cargo/container ships, 5:404 container ships, 5:403T, 5:404, 5:406T liner carriers, 5:404 refrigerated ships, 5:404 roll-on/roll-off ships (RoRo), 5:404 ocean-going barges, 5:403 passenger vessels, 5:404 see also Passenger vessels ship size increase, 5:402 standard vessel classes, 5:402–403, 5:403T tankers, 5:404 see also Tankers see also Ship(s); Shipping World Meteorological Congress, 3:275 World Meteorological Organization (WMO), 3:107, 3:274–275 Global Ocean Data Assimilation Experiment, 3:275 Global Ocean Observing System, 3:275 Intergovernmental Panel on Climate Change, 3:275 Tropical Ocean – Global Atmosphere Study, 3:275 World Climate Research Program (WCRP), 3:275 World Meteorological Congress, 3:275 World Ocean Circulation Experiment (WOCE), 3:275, 3:278 see also World Ocean Circulation Experiment (WOCE) World Meteorological Organization/ International Atomic Energy Authority (WMO/IAEA), 6:119 World Ocean Circulation Experiment (WOCE), 2:15, 2:173, 3:117, 3:118F, 3:302, 6:166, 6:278 Antarctic Circumpolar Current transport, 1:184 autonomous float, 2:174–176, 2:177–178 cost, 2:175 background to, 3:123, 3:278 Hydrographic survey, 2:173, 3:117, 3:118F, 3:275, 3:278, 3:302, 6:166 improved understanding of Kuroshio and Oyashio Currents, 3:369 measurements provided by, 4:119, 4:124–125 purposeful tracer experiment, 1:687 radiocarbon, 4:642, 4:643–644, 4:645F salinity, phosphate, oxygen profile, 3:301F Southeast Asian seas, 5:316
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World seaborne trade, 5:401–402 container shipping, 5:401–402 dry bulk trades, 5:401, 5:401T global cargo volume, 5:402, 5:402T global cargo weight, 5:401, 5:401T tanker cargoes, 5:401, 5:401T tonnage, 5:401, 5:401T trade routes, 5:402, 5:402T see also International trade World War II vessels, documentation, 3:698 World Weather Watch system, 3:107, 3:108 Wounding gear, 2:542 Wrasse (Labroides spp.), 1:656, 1:657, 2:377, 2:395–396F Wrasse blenny (Hemiemblemaria simulus), 2:423 Wright, Sewall, 4:559 Wroblewski JS, stage-structured population model of Calanus marshallae, 4:552, 4:553F Wroblewski’s model, small-scale patchiness and coastal processes affecting, 5:481 WSDW see Weddell Sea Deep Water (WSDW) WSPCW see Western South Pacific Central Water (WSPCW) WSPCW (Western South Pacific Central Water), temperature–salinity characteristics, 6:294T, 6:297–298, 6:298F WWGS (Winter Weddell Gyre Study), 5:155 WWSP (Winter Weddell Sea Project), 5:147–148 Wyrtki jet, 1:732–733, 3:227–228, 3:228F, 3:230–232 see also Indian Ocean equatorial currents
X XBP see Expendable bottom penetrometer probe (XBP) XBT see Expendable bathythermograph (XBT) XCP see Expendable current profiler (XCP) XCTD see Expendable conductivitytemperature-depth profilers Xenodermichthys copie (bluntsnout smooth-head), 2:452F Xenon diffusion coefficients in water, 1:147T Schmidt number, 1:149T Xiphias gladius (swordfish), 2:474, 4:135 Xiphiidae (swordfishes), 2:395–396F XKT see Expendable optical irradiance probe (XKT) X-ray fluorescence, 2:594
Index X-ray tomography, sediment core samples, 1:75, 1:76F XSV see Expendable sound velocity probe (XSV)
Y Yanai waves solution, 2:275–276 wave dynamics, 2:275 Yangtze river dolphin (Lipotes vexillifer), 2:154F, 2:155, 2:156, 2:159 Yantze River (Changjiang) dissolved loads, 4:759T hypoxia, 3:175 river discharge, 4:755T sediment load/yield, 4:757T Yellow eels see Eels Yellow-eyed penguin, 5:522T, 5:523–524 breeding patterns, 5:523–524, 5:527–528 characteristics, 5:522T, 5:523–524, 5:524F feeding patterns, 5:522T, 5:524, 5:527 migration, 5:239 nests, 5:522T, 5:523–524 see also Sphenisciformes (penguins) Yellowfin tuna see Thunnus albacares (yellowfin tuna) Yellow-nosed albatross (Diomedea chlororhynchos), 4:594, 4:596 see also Albatrosses Yellow River (Huanghe) hypoxia, 3:175 land-sea fluxes and, 3:401 sediment load/yield, 4:757T data problems collecting, 4:754 Yellow substance see Colored dissolved organic matter (CDOM); Gelbstoff Yellowtail flounder see Limanda ferruginea (yellowtail flounder) Yenisei, river discharge, 4:755T Yorktown, maritime archaeology project, 3:698 Yoshida, Y, 5:345 Younger Dryas, 1:2–3, 3:126F, 3:127 coral-based paleoclimate records, 4:345 termination of glaciation, 3:785–786 Yo-yo pattern, autonomous underwater vehicles (AUV), 4:477 Ytterbium, concentrations in ocean waters, 6:101T Yucatan Channel, 3:286F, 3:287 subsurface flows, 3:291 Yucatan Current, 2:561, 3:288–289, 3:293F Yucatan Peninsula, subterranean limestone dissolution, 5:552 Yugoslavia, water, microbiological quality, 6:272T
Z Z (atomic number), definition, 6:242 z (depth), definition, 6:242 Zalophus californianus see California sea lion Zambia, fishery management enforcement, 2:524 Zanzibar Current see East African Coastal Current (EACC) ‘Z’-coordinate, coastal circulation model, vertical approach, 1:573 Zebra mussel see Dreissena polymorpha (zebra mussel) Zeehan Current, 2:187F, 2:193F Zenopsis conchifera (silvery John Dory), 2:483, 2:483F Zeolite, definition, 1:268 Zeolites, 1:266 Zinc (Zn), 6:106 atmospheric deposition, 1:254T biological uptake, phytoplankton, 6:80, 6:81F chemical speciation in seawater, 6:79 complexation, biological uptake and, 6:80 concentration N. Atlantic and N. Pacific waters, 6:101T phytoplankton, 6:76T seawater, 6:76, 6:76T, 6:82F depth profiles, 6:77F global atmosphere, emissions to, 1:242T inorganic speciation, 6:103 ligands, biogenic, 6:84 metabolic functions, 6:83 oceanic, 1:200 organic complexes, 6:105 depth profile, 6:106F pollution anthropogenic and natural sources, 3:769T enrichment factor, 3:773T riverine flux, 1:254T see also Trace element(s) Ziphiidae (beaked whales) see Beaked whales (Ziphiidae); Odontocetes (toothed whales) Ziphius cavirostris (Cuvier’s beaked whale), 3:646, 3:647F Zirconium (Zr) concentrations in ocean waters, 6:101T crustal abundance, 4:688T dissolved, 4:693–694 depth profile, 4:694F hafnium atom ratio, 4:694F properties in seawater, 4:688T surface distribution, 4:690F Zoarcid fish (Thermarces andersoni), 3:133F, 3:135, 3:135F, 3:136F, 3:138F, 3:140 Zoeppritz, 3:254 Zombie turbulence, 2:614 Zonal average models, 4:109–110
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Zonation, 2:217 biogeochemical see Biogeochemical zonation coral reefs, 1:661F, 1:662–664 lagoons, 3:386 mangroves, 3:501–502 rocky shores, 4:762, 4:763–765 salt marshes, 5:41–42 sandy beaches, 5:49 Zone refining, 3:897–898 Zoning, 3:670 definition, 3:672 see also Marine protected areas (MPAs); Ocean zoning Zooplankton, 4:454, 5:489, 6:195 abundance, CPR survey data, 1:633–634, 1:635F acoustic scattering, 1:67 gas-bearing bodies, 1:68 hard-shelled bodies, 1:67–68 liquid-like bodies, 1:67 biodiversity, CPR survey data, 1:636–637, 1:637F biogeochemical/ecological models and, 4:100 definition, 4:337 diversity in epipelagic zone, latitude and, 4:356, 4:357T gelatinous see Gelatinous zooplankton importance in food web, 4:455 marine snow, 3:690–691, 3:691F, 3:692–693, 3:693F nitrogen cycle and, 4:33T see also Nitrogen cycle patchiness, 4:348 sensors for observing, 4:353T see also Patch dynamics Peru-Chile Current System (PCCS), 4:389–390 population, groundfish recruitment and, 4:700 thermal discharges, effects of, 6:14 timing of biomass peak, 4:458 see also Copepod(s); Fiordic ecosystems; Plankton and small-scale physical processes Zooplankton analysis analytical flow cytometry, 4:247–248 imaging techniques, 4:250 photographic, 4:250 using remotely operated vehicles, 4:250–251 video, 4:250 optical plankton counting see Optical Plankton Counter (OPC) Zooplankton sampling autonomous underwater vehicles (AUVs), 6:370 see also Autonomous underwater vehicles (AUVs) gear types, 6:355, 6:357T with nets and trawls, 6:355–371 current status of systems, 6:368–369, 6:370F future developments, 6:369
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Index
Zooplankton sampling (continued) high-frequency acoustics, 6:357T, 6:368 history, 6:355 net systems, 6:357T closing cod-end systems, 6:361, 6:363F high-speed samplers, 6:355–356, 6:357T, 6:360F moored plankton collection systems, 6:361–364, 6:366F multiple, 6:357T, 6:361, 6:365F, 6:366T
neuston samplers, 6:356–359, 6:361F non-opening/closing nets, 6:355, 6:356F planktobenthos plankton nets, 6:361, 6:362F simple opening/closing nets, 6:355–356, 6:358F optical systems, 6:357T, 6:364 image-forming systems mounted on non-opening/closing nets, 6:364
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optical instruments for nonquantitative studies, 6:365–368 particle detection systems, 6:364–365, 6:367F stand-alone image-forming systems, 6:364–365, 6:367F see also Continuous Plankton Recorder (CPR) survey Zooxanthellae, 1:665 coral reef aquaria, 3:529 corals, symbiotic relationship, 1:671 definition, 1:677
