List of Contributors to this Volume
M. O. ANDREAE Max Planck Institut for Chemie Mainz (Germany)
J. C. GILLE National Center for Atmospheric Research Boulder, Colorado (U.S.A.)
E. J. BARRON
Earth System Science Center University Park, Pennsylvania (U.S.A.) A. BERGER
Universit6 Catholique de Louvain Institut d'Astronomie et de Geophysique Louvain-la-Neuve (Belgium)
A. HENDERSON-SELLERS
Climatic Impacts Centre Macquarie University North Ryde (Australia) G. J. HOLLAND BMRC Melbourne Victoria (Australia)
G. BRASSEUR
National Center for Atmospheric Research Boulder, Colorado (U.S.A.) H. CLEUGH
Centre for Environmental Mechanics CSIRO Canberra (Australia) H. DIAZ Climate Research Division, ARL Environmental Research Laboratories Boulder, Colorado (U.S.A.) R. E. DICKINSON Institute of Atmospheric Physics University of Arizona Tucson, Arizona (U.S.A.) M. P. DUDEK Atmospheric Sciences Research Center University at Albany Albany, New York (U.S.A.)
P. D. JONES Climatic Research Unit University of East Anglia Norwich (U.K.) England G. N. KILADIS Cooperative Institute for Research in Environmental Sciences Boulder, Colorado (U.S.A.) L. KUMP Earth System Science Center University Park, Pennsylvania (U.S.A.) X.-Z. LIANG Atmospheric Sciences Research Center University at Albany Albany, New York (U.S.A.) J. E. LOVELOCK Cornwall (U.K.)
S. MADRONICH National Center for Atmospheric Research Boulder, Colorado (U.S.A.) B. MCAVANEY BMRC Melbourne Victoria (Australia) T. H. PENG Ocean Chemistry Division NOAA/AOML/OCD Miami, Florida (U.S.A.)
M. RAMPINO
New York University New York, (U.S.A.) W.-C. WANG Atmospheric Sciences Research Center University at Albany Albany, New York (U.S.A.)
Preface
Future Climates of The WorM: A Modelling Perspective is Volume 16 of the highly prestigious series World Survey of Climatology (editor-in-chief Professor H.E. Landsberg) published by Elsevier Science. As such, Future Climates of the Worm is part of a major, highly respected series of climatology reference books. All the chapter authors and, indeed, their students have, on numerous occasions, used the earlier volumes of the World Survey of Climatology. Since these vary in depth, breadth and insight and, to a relatively minor extent, in contemporary relevance, no single phrase can truly describe them. Nevertheless, they almost invariably provide a highly useful, often magisterial, reference source for comparative analyses, lectures and papers. Certainly for an introduction to the current climate of most regions of the world, and to climatology in general, they are very helpful. Most graduates with climatological interests have used them profitably. Although the series never seems to have had an explicit audience in mind, it seems to have been directed at and presented material at a level comprehensible to an interested non-climatologist with a scientific background. The present volume is intended to be aimed at a similar audience (the generally interested reader, climatology undergraduates and graduates in any discipline) and to offer a state-ofthe-art overview of our understanding of future climates. However, as its name suggests, this book clearly differs from all the earlier volumes in The Worm Survey of Climatology. All the chapter authors accepted a very difficult challenge when we agreed to contribute to
Future Climates of the Worm for we all know that we cannot yet predict future climates. This book does not and could not give tables of values of future climatic variables. Instead, each topic we discuss is described so that the way in which it may impact projections of the Earth's future climate can be more fully understood. Discussing Future Climates of the Worm is difficult for a number of reasons. The space and time scales employed by those describing future climates are capricious. Here most chapters take their space scale to be at least continental, and often global, while the time scale is decadal, and the time span the next couple of centuries. This is obviously not the complete suite of future climates of the world in time or space and, not coincidentally, they are the scales that are best addressed by Global Climate Models (GCMs) and their associated needs for observational data for evaluation, tuning and improvement. This same, understandable, GCM bias has produced a focus on the climatic elements of energy and temperature at the expense of many other climatic parameters. This book comprises a state-of-the-art review of our current understanding of climatic prediction and the way in which this depends crucially upon improvements in, and improved understanding of, climatic models. Of necessity, this Volume contains material that is much more ephemeral than the climatic facts and figures in Volumes 1-15. Nevertheless, the study of climate has moved from data
XI
Preface collection "climatology" to the model and experimentally based predictions of "climatic science". A wag once questioned a weather forecaster friend of mine as follows: "Long ago the science of astronomy developed from the classification and mythology of astrology; when will meteorology become quantitative enough to be termed meteoronomy?" Perhaps, Future
Climates, building on all the previous books in this series on climatology, is a first step towards "climatonomy". The book comprises four main themes which follow an introductory chapter. The themes encompass the geologic perspective (I) and present-day observations (II) as they pertain to future climates. Theme III focusses on human factors affecting future climates and the final theme (IV) tackles planetary geophysiology and future climates. Within these sections there are a total of 14 chapters. The Syst~me International (SI) of units is employed throughout. Most of the material for this book was collected during 1992 and 1993 and thus both benefitted from, and was held up by, the revision of the Intergovernmental Panel on Climate Change (IPCC) Reports. We are very grateful to all our colleagues around the world who took time out of their busy schedules to review and comment upon earlier drafts. I am particularly grateful to Dr Graham Cogley, Dr Michael Manton and Dr Peter Robinson, who acted as the publisher's reviewers for the whole book, completing this arduous task in a timely and supportive fashion. I am also, personally, most grateful to my own research group at Macquarie University who reviewed my chapters and many of the others. Much of the research that underpins my own chapters in this book and the reference research which I undertook as editor were completed at the National Cenl~er for Atmospheric Research. I am grateful to Dr Bob Serafin, the Director, and Dr Warren Washington, the Director of the Climate and Global Dynamics Division, for their continuing hospitality to Affiliate Scientists and other visitors. I wish to express my thanks to the Vice-Chancellor of Macquarie University, Emeritus Professor Di Yerbury, and the Senior Executives of the University who have supported my research and, especially, the activities of the Climatic Impacts Centre so wholeheartedly over the last six years. Finally, I wish to thank Brian and Kendal for supporting me in everything I do - the mad and ludicrous ventures as well as the r e s t - thank you both. April 1994
Professor A. Henderson-Sellers Director Climatic Impacts Centre Macquarie University Sydney Australia
XII
List of Abbreviations and Acronyms
AQs kts AT(u-r)
albedo Bowen ratio (QH/QE) coupling factor latitude Stefan-Boltzmann constant delta isotopic carbon 13 ratio heat capacity of the Earth net advective flux photosynthetic flux heat storage flux thermal admittance (of the surface) heat island strength
A AABW ADEOS AGCM AIRS AMIP ATN AVHRR
albedo Antarctic Bottom Water Advanced Earth Observing System Atmospheric General Circulation Model Atmospheric InfraRed Sounder Atmospheric Model Intercomparison Project Advanced Tiros-N Satellite Advanced Very High Resolution Radiometer
BMRC BP
Bureau of Meteorology Research Centre before present (used with reference to years in geological dating)
CCM CCN CERES CFC CLIMAP CPE CRU
Community Climate Model cloud condensation nuclei Clouds and the Earth's Radiant Energy System chlorofluorocarbon Climate Long-range Investigation, Mapping, and Prediction centrally planned economy Climatic Research Unit (University of East Anglia) heat capacity (by volume)
DMS DOD DOE DSDP
dimethyl sulphide Department of Defense (USA) Department of Energy (USA) Deep Sea Drilling Project
a
f2 0 o"
6~3C pC AQA AQp
XXI
List of abbreviations and acronyms
ECMWF ENSO ENVISAT EOS EOSAT EOSDIS ERB ERBE ERBS EROS
European Centre for Medium Range Weather Forecasting E1 Nifio Southern Oscillation Environmental Satellite Earth Observing System Earth Observation Satellite Company EOS Data and Information System Earth Radiation Budget Earth Radiation Budget Experiment Earth Radiation Budget Satellite Earth Resources Observation System
FAO FGGE FIFE FOV FPAR
Food and Agriculture Organization First GARP (Global Atmospheric Research Programme) Global Experiment First ISLSCP Field Experiment field of view fractional photosynthetically active radiation
GARP GATE GCM GEOSECS GFDL GMS GOES GPCP GRIP GENESIS
Global Atmospheric Research Programme GARP (Global Atmospheric Research Programme) Atlantic Tropical Experiment general circulation model or, synonymously, global climate model Geochemical Ocean Section Study Geophysical Fluid Dynamics Laboratory Geostationary Meteorological Satellite Geostationary Operational Environmental Satellite Global Precipitation Climatology Project Greenland Ice-core Project Global Environmental Ecological Simulation of Interactive Systems, a GCM
H
height
IPAR IPCC IR IS92 ISCCP ISLSCP ISRIC ITCZ
incident photosynthetically active radiation Intergovernmental Panel on Climate Change infrared IPCC 1992 Emission Scenarios International Satellite Cloud Climatology Project International Satellite Land Surface Climatology Project International Soil Reference Information Centre inter-tropical convergence zone
KS K* K/T k~ XXII
reflected shortwave radiation incoming shortwave radiation net shortwave radiation (K,I,- K'I') Cretaceous/Tertiary boundary thermal conductivity
List of abbreviations and acronyms
ka
kilo-years, i.e. 1000 years
L
length emitted (upwelling) longwave radiation incoming (downwelling) longwave radiation net longwave radiation (L$ - L'I') leaf area index Land Remote-Sensing Satellite last glacial maximum Little Ice Age
L$ L$ L* LAI LANDSAT LGM LIA
METEOSAT METOP MISR MJO mlo MODIS MPI MSLP MSU MWP
millions of years Meteorological Satellite operated by the European Space Agency Meteorological Operational Satellite Multi-angle Imaging Spectro-Radiometer Madden Julian Oscillation mixed layer ocean Moderate Resolution Imaging Spectroradiometer Max Planck Institute mean sea-level pressure Microwave Sounding Unit Medieval Warm Period
NADW NASA NCAR NMC NOAA NWP
North Atlantic Deep Water National Aeronautics and Space Administration National Center for Atmospheric Research National Meteorological Center National Oceanic and Atmospheric Administration Numerical Weather Prediction
OGCM
Ocean General Circulation Model
PAR PBL
Photosynthetically Active Radiation planetary boundary layer partial pressure of carbon dioxide Pacific-North American Polar-Orbit Earth Observation Mission
Ma
pCO2 PNA POEM
Q, QBO QE
QF QH
net all-wave radiation quasi-biennial oscillation latent heat flux anthropogenic heat flux sensible heat flux solar input
XXIII
List of abbreviations and acronyms
SA90 SAGE SAR SHIM SNR SPM SPOT SRB SSMI SST Sv SVF
IPCC 1990 Business-as-Usual Emission Scenario Stratospheric Aerosol and Gas Experiment Synthetic Aperture Radar surface heat island model signal-to-noise ratio suspended particulate matter Syst~me Pour l'Observation de la Terre Surface Radiation Budget Special Sensor Microwave sounder and Imager sea surface temperature Sverdrup (= 1 • 106 m 3 s-1)
t
TUTT
time effective temperature top of the atmosphere Total Ozone Mapping Spectrometer Ocean Topography Experiment Tropical Rainfall Measuring Mission surface temperature tropical upper tropospheric trough
UARS UBL UCL UKMO UN UNCOD UNEP USGS UV
Upper Atmosphere Research Satellite urban boundary layer urban canopy layer United Kingdom Meteorological Office United Nations United Nations Conference on Desertification United Nations Environment Programme United States Geological Survey ultraviolet
VI
vegetation index
W WCRP WMO WSBW
width World Climate Research Programme World Meteorological Organization Weddell Sea Bottom Water
re TOA TOMS TOPEX TRMM
rs
sky view factor
Chemical Formulae and Nomenclature
C2F6 CC12F2 CC13F CC14 XXIV
hexafluoroethane dichlorotrifluoromethane trichlorofluoromethane carbon tetrachloride
List of abbreviations and acronyms
CF4 CH3CC13 CH4 CHC1F2 CO CO2 H20 N20 NOx 03 SF6
XXV
tetrafluoromethane methyl chloroform methane chlorodifluoromethane carbon monoxide carbon dioxide water vapour nitrous oxide oxides of nitrogen (NO, NO2, NO3) ozone sulphur hexafluoride
Chapter 1
Climates of the future A. HENDERSON-SELLERS
Why consider the climate of the future? Human beings are curious: we seek to understand and hence to predict. We are dependent upon the climate and so our desire to predict is not driven solely by curiosity but by a need to predict future weather, its variability and other characteristics: future climates. The tools we employ in our attempts to predict future climates are the same as those employed by everyone attempting to understand other complexities of the world: observation, reconstruction of past events, interpretation, extrapolation and process studies. In the case of climate, observations comprise surface and satellite data retrievals; past events can be reconstructed from the geological record and also from the historical record (both of observations and of proxy information); extrapolation can take many forms but is increasingly being synthesized with simulations from computer-based models, themselves derived from interpretation of past events and studies of climatic and weather processes. So far our predictive skills are rather poor. In addition, technology and the harnessing of natural resources appear to have decreased the need to predict the future climate of industrial, housing or even agricultural developments. However, although oil and gas pipelines can be laid across permafrost, indoor climates can be controlled independently of the outdoors, airports operate year-round and irrigated land can grow a wide variety of crops, there are still massive costs, in lives and revenue, associated with weather extremes and with climatic shifts. Marginal changes in climate can be "managed" although this may be costly: financially in developed nations but in terms of human life in the less-developed nations. On the other hand, if the oceans were to "boil off" or if this planet were plunged into a global glaciation, it is difficult to see how technology could aid us. Thus it is arguable that global-scale climatic changes should be our greatest concern while regional to local changes might be viewed as of somewhat lesser importance. However, we inhabit "regions", called nations, so political responses are closely linked to regional climates and even local conditions. Overall, however, unless or until humans colonize other planets, our primary concern must remain the habitability and sustainability of the Earth as a whole.
Focus of this book Like all its predecessors in this distinguished series, this text was designed to offer an up-todate view of climatic science. Unlike its predecessors this text will be ephemeral. It is not a
Climates of the future collection of climatic facts but rather an overview of our current understanding of climate and the science of climatic prediction through the use of models. We cannot, yet, predict future climates. If we could, there would be no need for this text and, indeed, little need for the others in this series. We could simply "switch on" or "log in" and request the latest climate forecast. This book describes our current (1994) understanding of future climate predictions using climatic models. Despite our inability to predict future climates, we often behave as if we can. Policy, development, business, financial and even personal decisions are made every day around the world as if we knew what climates we shall face in the future. Of course, many activities seem not to depend very strongly on climate but increasingly it is being recognized that while our local-scale climatic dependencies can be significantly reduced by technology, for genetic engineering and international trade and aid, global-scale climate changes may not be so readily ignored. International policies regarding the global climate have been successfully negotiated and some (e.g. the Montreal Protocol) implemented while others (such as the Framework Convention on Climate Change, which calls for the reduction in emission of greenhouse gases) are currently being debated. These treaties focus on global-scale climates and so, predominantly, does this book. There is a second, more pragmatic, reason for focussing primarily on the large-scale in this text. Although observations and even reconstructions of past climates are point or regionally specific, our prediction tools, particularly numerical climate models, are global in character. We currently have little or no local-to-regional prediction skill for future climates. This text focusses upon future global climates, primarily, whilst recognizing that regional climates are a function of these global futures. Three aspects of future climates at less than the global scale are dealt with specifically: urban climates, land-use change and its interaction with regional climates, and atmospheric pollution. The format follows a logical progression: reconstruction of the geological record of climate, review of the historical record of climate and the present-day means of observing climate, recognition of the potential for future impact on climate of human activities and, finally, acknowledgement of climate as one component of the geophysiological system that is the Earth (SCHNEIDERand BOSTON, 1991).
Relationship to other reviews of the future climate
The Intergovernmental Panel on Climate Change (IPCC) was established in the late 1980s to review the science, impacts and response strategies associated with human-induced climatic change. This book was written after the first reports of the IPCC were published in 1990 and while these reports were being revised and updated (HOUGHTON et al., 1990, 1992; TEGART et al., 1990; IPCC, 1991). The IPCC has a significantly narrower brief than this book since it is concerned primarily with human modification of the climate following the release of trace (or greenhouse) gases into the atmosphere. Specifically, the IPCC report states (HOUGHTON et al., 1990, p xiii): There is concern that human activities may be inadvertently changing the climate of the globe through the enhanced greenhouse effect, by past and continuing emissions of carbon dioxide
Relationship to other reviews of the future climate and other gases which will cause the temperature of the Earth's surface to increase- popularly termed the "global warming". If this occurs, consequent changes may have a significant impact on society. The purpose of the Working Group I report, as determined by the first meeting of IPCC, is to provide a scientific assessment of: (1) the factors which may affect climate change during the next century, especially those which are due to human activity; (2) the responses of the atmosphere-ocean-land-ice system; (3) current capabilities of modelling global and regional climate changes and their predictability; (4) the past climate record and presently observed climate anomalies. On the basis of this assessment, the report presents current knowledge regarding predictions of climate change (including sea level rise and the effects on ecosystems) over the next century, the timing of changes together with an assessment of the uncertainties associated with these predictions. With these stated aims, the IPCC Science report seeks to quantify the relative importance of greenhouse gas warming and other factors affecting the climate. Thus HOUGHTON et al. (1990, p xxvii) make the following statements with reference to these "other factors". On a decadal time-scale solar variability and changes in greenhouse gas concentration could give changes of similar magnitudes. However the variation in solar intensity changes sign so that over longer time-scales the increases in greenhouse gases are likely to be more important. Aerosols as a result of volcanic eruptions can lead to a cooling at the surface which may oppose the greenhouse warming for a few years following an eruption ... over longer periods the greenhouse warming is likely to dominate. Human activity ... leading to an increase in aerosols ... might lead to a significant regional cooling. and finally,
Natural variability could act to add to, or subtract from, any human-made warming; on a century time-scale this would be less than changes expected from greenhouse gas increases. While these estimates of relative importance may be valid for the time-scale of the next century, they may require revision if either longer times are considered or more extreme events are contemplated. This book considers future climates from a planetary, or geological, perspective and therefore both includes time-scales longer than one century and examines the possibility of more extreme events than those contemplated in the IPCC reports. This book is therefore complementary to the IPCC process because it offers a wider context for the predictions of future climates than those based solely on the projection of future increases in greenhouse gases. However, in common with the IPCC reviews, the primary tool used here as the means for climatic prediction is numerical climate models. There are other similarities: the enhanced greenhouse is reviewed in Chapter 9 by WANG et al., but the wider scope here means that the treatment of topics is much less extensive than the review undertaken by IPCC. This book is also less quantitative in many areas because greater timescales are encompassed and hence less detail can be paid to the next 50-100 years. On the other hand, issues such as air quality, aerosol loadings, urban climates and land-use change are all dealt with in more detail than by IPCC.
Climates of the future Earth's climate and its future
In looking to the future, we consider in detail the factors described as "strategic threats" by the Vice President of the USA (GORE, 1992), viz. global warming, ozone depletion and deteriorating tropospheric air quality. Climatology is inevitably concerned with issues of habitability and sustainability. Faced with the question "can this planet sustain life?", humans tend to consider temperature (is it too hot or too cold for me?); atmospheric chemistry (is the atmosphere breathable?); whether there is food and water (too little for drinking and for growing crops or too much so that the land is flooded?); and, perhaps, comfort (will it "feel" pleasant, i.e. not too humid or too dry?). Indeed, these issues are interdependent: if the global mean temperature does not lie between 0~ and 100~ (at a pressure of about 1 atmosphere) water cannot exist in liquid form and the chemistry of the atmosphere is likely to be greatly changed (e.g. LOVELOCK, 1986). At the same time, the most important greenhouse gas in the Earth's atmosphere is water vapour so that evaporation becomes a sustaining mechanism for the conditions that we consider to be "comfortable". Thus, when considering "climate" it is not unreasonable to think first of temperature which is, in turn, primarily a function of radiation exchanges. Indeed, Volume 1 of this series entitled General Climatology focussed on the "current knowledge of the heat and radiation budget" (KESSLER, 1985, p vii). Radiation from the Sun drives the climate of the Earth and, indeed, of the other planets in the Solar System. Solar radiation is absorbed and, over periods of a few years, this absorption is balanced by radiation emitted from the Earth. This global radiative balance, which is a function of the surface and atmospheric characteristics, of the Earth's orbital geometry and even of solar output itself, controls the habitability of the Earth, mean temperatures, the existence of water in its three phase states and, together with the effects of the rotation of the Earth on its axis, the dynamics of the atmosphere and ocean. While temperature is an incomplete surrogate for climate, it is a useful one, both when reconstructing past climates and when trying to predict the future. The dearth of evidence about pal~eoclimates, the fact that temperature is often the climatic variable for which we have the longest and most complete record (both temporally and spatially), and the relationship between radiation and temperatures set the focus for this book. Figure 1 shows six temperature records of the Earth's past climate: the first (a) is based on observational evidence; the next three (b)-(d) are based on a range of palaeo-evidence; the fifth (e) is derived from patchy geological evidence and the last graph (f) is informed guesswork. There are many important characteristics of climate captured in this set of diagrams. The first trace (a) can be interpreted as possibly showing the anthropogenically induced enhanced greenhouse warming imposed on the natural variability of temperatures (see Chapter 5 by JONES). Indeed all of the first five graphs (a)-(e) illustrate this natural variability on a range of time-scales. Interestingly and perhaps significantly, although as the time-scale increases the range of temperatures seems to grow, the range appears to reach a maximum of about 10~ over the three largest time-scales shown. The oldest known record of the climatic conditions on Earth comes from the Isua rocks dated as being 3.83 billion years old, i.e. about 670 million years younger than the Earth itself. These rocks indicate the presence of liquid water on the surface (SCHOPF, 1983). From about 3.5 billion years ago, the fossil record includes increasingly abundant evidence of life
Earth's climate and its future Global Air Temperature ~ 0
-0 4
Northern Hemisphere Summer Temperatures
0.4
cold
LEGEND
1984 1954 < > 1904
1854
(a) T H E C A S T 100 Y E A R S
1
Recent warming
2.
Little Ice Age
3.
Cold interval (Younger Dryas)
4.
Present interglacial (Holocene)
5.
Previous interglacial (Eemian)
6.
Present glacial age
7.
Permo-Carboniferous glacial age
8
Ordovician glacial age
9
Late Precambrian glacial age(s)
10.
Earth's origin
warm
1900 1700 1500
< 19
)
1300
)
1100
)
900
t
I
..2oc
(b) THE LAST 1,000 YEARS
M~dlabtude A=r Temperature cold warm 0
-
Estimated Summer Sea-Surface Temperature (~ 5 10 15 I''
''1
'''
I '
10
_
20 < ~-
30
10
>-
40
o
50
w 15 13 r (1:1 ( ot -
~
20
_
60
J
70
\~
80 90 100 110 120 130
~ 10~ (C) THE LAST 10,000 YEAI:::i'S
(d) THE LAST 100,000 YEARS
0 100
8, 200 ,a: 300 19 >- 400 "6 500 1/)
,"
.Q
600
=- 700 9
QUATERNARY _0 , -, ~.4-- Last major chmat~c cycle E]'P- Ice sheets appear in N. Hemisphere 5 ~LIOCEN _ _ Antarctic ice sheet expands 10 k
15-
~
~dlOCENEI
30-
cold
sheet forms, mountain Qlaciers occur in the N Her~isphere
I /
o
] OLIGO- ~ CENE /
Small glaciers are widespread in Antarctica
"= >-
2
35-
900 1000
40-
J~.~---
c
Waters around Antarctica cool, sea ice forms
._
I h
O
800
warm I
Antarctic ice
2025-
Global Mean Temperature
3
J
>
I
4 5 - EOCENE I
\ 50?
~
55 '
- ~
Antarctica- Australian passage opens Cenozoic decline begins
~50"C (e) THE LAST 1,000,000,000 YEARS
(f) THE LAST 4,500,000,000 YEARS
Fig. l. The climate of the Earth as represented by average air temperature records over periods (a) 100 years (after JONES, 1995, Chapter 5), (b) 1000 years (after HUGHESand DIAZ, 1994; reprinted with permission, Kluwer Academic Publishers), (c) 10,000years (after US NATIONAL ACADEMY of SCIENCES, 1975), (d) 100,000 years (after BERGER, 1995, Chapter 2), (e) 1,000,000,000 years (after BERGER, 1988, 9 American Geophysical Union and BARRON, 1995, Chapter 3) and (f) 4,500,000,000 years (estimated from many sources including KUMP and LOVELOCK, 1995, Chapter 15 and HENDERSON-SELLERS,1989). Dashed lines indicate that the proxy records are inadequate for the reconstruction portrayed.
Climates of the future which is usually interpreted as indicating that globally averaged climatic conditions, such as temperature and precipitation, were not too different from the present day (see Chapter 15 by LOVELOCK and KUMP). Figure If shows mean temperatures rising slightly over the whole of Earth's history because we know that solar luminosity has increased by about 30% since the Earth was formed. It should also be noted that Fig. If is an interpretation of the probable record of the Earth's global mean temperatures based partly on observational evidence and partly on results from climate models which indicate that negative feedback effects can reduce large swings while "recovery" of habitable conditions from either a total planetary freeze or a "runaway greenhouse" is virtually impossible (KASTING, 1989; HENDERSON-SELLERS et al., 1991). The format of this book is guided, in part, by our understanding of this record of past climates and, in part, by the increasing recognition that human activities have the capacity to be as significant an influence on future climate as the natural factors which have, so far, shaped climatic evolution. The first section of this book reviews the geological history of climatic change assessing astronomical factors, pal~eo-evidence and massively disruptive events. The second section reviews observations of climate including both the historical record and the exploitation of satellite data. In the third section, the possible impacts of human activities on future climates are considered including the trace gas greenhouse, increased aerosols, pollution, ozone depletion and land-use change. In this section the future climates of the Earth's cities are also reviewed. Finally, the last section of the book closes the loop back to the geological record by reviewing the potential range of future climates in the context of global geophysiology: the perspective which considers the Earth system holistically. A potentially useful way of predicting patterns of future climate is to search for periods in the past when the global mean temperatures were similar to those we expect in the future, and then use the past spatial patterns as analogues of those which will arise in the future. For a good analogue, it is also necessary for the forcing factors (for example, greenhouse gases, orbital variations) and other conditions (for example, ice cover, topography) to be similar; direct comparisons with climate situations for which these conditions do not apply cannot be easily interpreted. HOUGHTON et al. (1990, p xxv) state that "analogues of future greenhouse-gas-changed climates have not been found" and therefore go on to say that, in the context of the IPCC scenarios for the next century, "we cannot therefore advocate the use of pala~o-climates as predictions of regional climate change due to future increases in greenhouse gases. However, pal~eo-climatological information can provide useful insights into climate processes, and can assist in the validation of climate models." (HOUGHTON et al., 1990, p xxv). In this book, pala~o-climatological evidence will be used (i) to offer a more complete view of "natural variability" (Chapter 2 by BERGER) and the processes underlying this variability, (ii) to set the framework for the longer time-scales of interest here and to examine the validation of climate models (Chapter 3 by BARRON) and (iii) to permit a quantitative discussion of unlikely events (Chapter 4 by RAMPINO) affecting climate or non-linear responses causing rapid changes (Chapter 14 by PENG). However, all chapters draw on the results of numerical models of the Earth's climate.
Modelling the Earth's climate
Modelling the Earth's climate The simplest possible way of constructing a model of the Earth's climate with which to predict its future is to consider the radiative balance of the globe as a whole. This is a zero dimensional model often written in the form S(1 - A )
(la)
"- tYTe 4
T s = T e + Tgreenhous e
(lb)
Here, S, the solar input, has a value of about 1370 W m -2 divided by 4 to give about 342 W m -2, the amount of solar radiation instantaneously incident at the planet per unit area of its (spherical) surface. Taking the Earth's albedo, A, as about 0.3, with tr, Stefan-Boltzmann constant of 5.67 x 10-8 W m -2 K -a, the effective blackbody radiating temperature of the Earth, Te, is found to be around 255 K. This is lower than the current global mean surface temperature of 288 K, the difference, about 33~
largely being due to the greenhouse ef-
fect. In Fig. 2, the Earth's globally and annually averaged radiation balance can be seen graphically. The numbers in parentheses represent energy as a percentage of the average solar constant- about 342 W m - 2 - at the top of the atmosphere. Note that nearly half the incoming solar radiation penetrates the clouds and greenhouse gases to the Earth's surface. These gases and clouds re-radiate most (i.e. 88 units) of the absorbed energy back down towards the surface. This is the basis of the mechanism of the greenhouse effect. The magnitude of the greenhouse effect is commonly measured as the difference between the blackbody emission at the surface temperature (a global average of 288 K gives 390 W m -2) and the outgoing infrared radiation at the top of the atmosphere (here 70 units or 239 W m-2), i.e. 151 W m -2 (see Fig. 9.1 in Chapter 9 by WANG et al.). In this zero dimensional model, the climate can only be changed if the incoming solar radiation alters, if the albedo changes or if the greenhouse effect is modified. Thus, to first order, 30
(a)
(b)
]~'~\~"~ IncomingSolar
/('.,:'l'..,,.=,~ so,..
k~,~,,~,~\~'~Radiation (100)
/
I ou,oo,~
I
/~, ~' Radiation(30) / / InT.ra.reo I Tota,Ener=,Ab~o~o~ / /'Rao=atK)n (70) 1 2 o I~.\"~ ~ \ \ ~ \ ~]x~/ and Infrared Re-emitted / 9 /~l~l I J ~ , \ \ \ \ \ \ \ ~ Reflectedb .~"~ by Atmosphere (66)--~./" --JU/ I I \~,,,~'~"~ ~/~ ~ . i # / i i ! (4) I
I~,\~\\~
,~
Atmospher,
[~ ~ I I
debr
by
OSPHERE
~ ~ ~ ' ~ - ~ ~ ' ' ~-----~',.~,a:esles" ~OPOPAUSE
\\\\.~ -"--(25)---~, ~ b y ~-"~.'-~,,~\ Surface(7) t ~ t Thermals (5 | I-"1 |
H,'
10
~ '11nnJ /,' / ,=n~aredlrom/ 1. . . . . ::::1// / an~tcn~uSdP; (e~)l
(~
~'-~
TROPOSP=HERE
~ t su~.aceis translated into sensible, latent and radiative losses J 200
I 250 Temperature
300 (K)
Fig. 2. Schematic of the Earth's energy budget (a) (modified from SCHNEIDER,1992, reproduced with the permission of Cambridge University Press and the University Corporation for Atmospheric Research) and temperature profile (b) of the lower atmosphere. Units are percentages of the incident solar radiation, 342 W m-2 and temperature.
Climates of the future
(a) 90ON 50~ 50~ 40~ 30~ 20= 10~ 0o 10~ 20~ 30~ 40~ 5O, 60" 90~
(b) Radiation
PolarCell ~" "~ ~
... i-".....
FerrelCell (' "=V'~~rr~~
A P~
H(~CelIs"
~,,
(~ TerrestrialInfraredRadiation ......
~r
~'~ L~
:'ha
~,,,.
~"
ReflectedSunlight /incOming Sunlight
~ ~
Outgoingiongwave .I~,-:... ~
80
160 240 Wm-2
SunHgat
i 320
TerrestrialInfraredRadiation Fig. 3. Schematic of (a) the latitudinal energy balance of the Earth and (b) the dynamics of the atmosphere (modified from HENDERSON-SELLERSand MCGUFFIE,1987). the Earth's climate is controlled by incident solar radiation, by the amount of this which is absorbed by the planet and by the thermal absorptivity of the gases in the atmosphere (e.g. KIEHL, 1992). Additional features control the climate. Of these, the most important are the latitudinal distribution of absorbed solar radiation (large at low latitudes and much less near the poles) as compared to the emitted thermal infrared radiation which varies much less with latitude (Fig. 3a). This latitudinal imbalance of net radiation for the surface-plus-atmosphere system as a whole (positive in low latitudes and negative in higher latitudes) combined with the effect of the Earth's rotation on its axis produces the dynamical circulation system of the atmosphere (Fig. 3b). Figures 2 and 3 describe schematically the most important processes controlling the atmospheric circulation and characteristics. The latitudinal radiative imbalance tends to warm air which rises in equatorial regions and would sink in polar regions were it not for the rotation of the Earth. The westerly waves in the upper troposphere in mid-latitudes and the associated high and low pressure systems are the product of planetary rotation affecting the thermally driven atmospheric circulation. The overall circulation pattern comprises thermally direct cells in low latitudes, strong waves in the midlatitudes and weak direct cells in polar regions. This circulation combined with the vertical distribution of temperature (Fig. 2b) represent the major aspects of the atmospheric climate system (e.g. SCHNEIDER, 1992). It is possible that even these fundamental characteristics of atmospheric dynamics could change in the future (Chapter 8 by MCAVANEY and HOLLAND). Processes in the atmosphere are strongly coupled to the land surface (Fig. 2a), to the oceans and to those parts of the Earth covered with ice and snow (the cryosphere). There is also strong coupling to the biosphere (the vegetation and other living systems on the land and in the ocean). These five components, the atmosphere, land, ocean, ice and biosphere (Fig. 4a), are now often considered to comprise the climate system (GARP, 1975). However, their time-scales differ quite significantly:
Modelling the Earth's climate atmosphere
-minutes to days
oceans
-weeks to thousands of years
biosphere
-years to hundreds of years
ice
-thousands to millions (or even hundreds of millions) of years -millions to hundreds of millions of years
land surface
The result of these different time-scales and of the complex interactions between these components of the climate system is a rich spectrum of climatic change (Fig. 4b). The largest
Changes of solar radiation SPACE
i Ten'estdalradiaItion
ATMOSPHERE
(a) u
H20, N2,02, CO2, 03 etc Aerosol Precipitation Atmosphere - land coupling Atmosphere - ice coupling ICESHEEwT~ t z~.. BIOMASS ~SEA-ICE Heat exchange ~ " " II I / - ~ ~ ' ~ ~' ~X :.-: . . : . ~ 1
!
/
LAND \ -
III.so c.a
atmospheric cordposition
-'~ta~'/////////////A
ii
i?I
~
FA _
I
I
I
II
ll- u~176 n
X l c e _ ocean ~
4k
EARTH
Changes of land features, orography, vegetation, albedo etc
104
Evaporation Wind stress
i
I
Changes of ocean basin shape, salinity etc. I
I
I
I
i
i
I
I
_
_
(b)
Annual
Tectonic
revolution
i
10 3
.~ -E
Orbital variations
Diurnal rotation r lo ,,..-
o r
102
t,,.
> G) ._> n-
c O
10
(1:1 "10
E
____j v , v
"'6
0.1 1010
tO4
-
to
1
1
1
1
1
1
I
1
1
1
1
1
1
10 9
10 8
10 7
10 6
10 5
10 4
10 3
10 2
10
I
011
10 .2
10 .3
10 -4
Period in Years
Fig. 4. (a) The Earth's climate system (after GARP, 1975). (b). Spectrum of climatic changes on Earth (after BERGER, 1988, 9 American Geophysical Union).
Climates of the future peaks in this spectrum relate to astronomical forcings: the Earth's rotation, its revolution around the Sun, variations in this orbit and the formation of the Solar System (see Chapter 2 by BERGER). Coupling amongst processes within the climate system components, such as the atmosphere with the oceans, the oceans and ice masses, is probably responsible for other peaks in this climate change spectrum. In this book, the perspective is longer than that adopted by IPCC, viz. the next century. Whilst recognizing the potential importance of anthropogenic activities, particularly but not exclusively the release of greenhouse gases (see Chapter 9 by WANG et al.), for future climate these are placed in the context of astrophysical, geological and biological variations which may also modify future climates. The most highly developed tool which we have to predict future climate is known as a general circulation model or global climate model, abbreviated to GCM. These models are based on the laws of physics and use descriptions in simplified physical terms (called parameterizations) of the smaller-scale processes such as those due to clouds and deep mixing in the ocean. In a climate model, an atmospheric component, essentially the same as a weather prediction model, is coupled to a model of the ocean, which can be equally complex (e.g. HENDERSON-SELLERS and MCGUFFIE, 1987; SCHLESINGER, 1988). The term GCM is nowadays taken to mean fully three-dimensional models of the atmosphere and oceans coupled together. If only the atmospheric component is represented the term AGCM (atmospheric GCM) is used. Such a model is generally linked to a simple representation of ocean temperatures such as offered by a mixed-layer ocean model. However, because the time-scales of, for example, the ice masses and the carbon cycle are very long they have not yet been incorporated into GCMs. For very long time-scale simulations of future, and past, climates simpler models are often used: energy balance models (EBMs) and twodimensional statistical dynamical models (2-D SDs). EBMs are called "one-dimensional", the dimension in which they vary being latitude. Vertical variations are ignored and the models are used with surface temperature as the dependent variable. Since the energy balance is allowed to vary from latitude to latitude, a horizontal energy transfer term must be introduced, so that the basic equation for the energy balance at each latitude, 0 is S[ 1 - A(0)] = OrZe(0) 4 + p C
AT"s(0) AT
+ transport out of zone 0
(2)
where pC is the heat capacity of the system and can be thought of as the system's "thermal inertia", S[ 1 - A(0)] is the absorbed solar radiation, crTe(0)4 the top-of-the-atmosphere net longwave radiative loss and Ts is the surface temperature varying with time, t. The radiation fluxes at the Earth's surface must be parameterized with care since conditions in the vertical are not considered. To a large extent, the effects of vertical temperature changes are treated explicitly. One possible use of EBMs is to employ them to obtain plausible distributions of ocean surface temperatures which can then be included in an AGCM simulation of a different climatic regime, such as a previous or future glacial epoch. The general circulation of the atmosphere can be schematically represented as cellular circulations. These Hadley, Ferrel and polar cells are meridional features, i.e. they consist solely of latitudinally averaged movement between zones (Fig. 3b). Most two-dimensional statistical dynamical climate models are constructed to simulate these motions. The two dimen-
10
Modelling the Earth's climate sions they represent explicitly are height in the atmosphere and latitude. Atmospheric variations around latitude zones (i.e. longitudinal variations) are neither resolved nor described. These models, in common with GCMs, solve numerically the fundamental equations listed in Table 1 and produce simulations of the large scale two-dimensional flow. The fundamental difference between these models and full atmospheric GCMs is that all the variables of interest are zonally averaged values. This zonal averaging is identified below by angle brackets. The equations to be solved are:
Zonal momentum 0 (u) Ot
O(u' v') S(v)-l-~ =F Oy
(3)
Meridional momentum (geostrophic balance) 0
f (u}+ R(T)--~y(In(p))= 0
(4)
Hydrostatic balance (vertical component) 0 (ln(p))
g
OZ
R(T)
(5)
Thermodynamic balance
o
-~ ~o(.' r') Ot
+
o(w' r')
Oy
Oz
g
O(T)]=
Q
+ <w> (p)c. + oz j
(6)
Continuity
o(p) o(p)<w) Oy
Oz
=0
(7)
where u, v and w are the zonal mean velocities in the eastward (x), northward (y) and vertical (z) directions, T is the temperature, Q is the diabatic heating and F the friction term, R the universal gas constant, co the specific heat at constant pressure, g the acceleration due to gravity, f the Coriolis parameter and (p)= (p)/R(T). The primed notation denotes a deviation from the zonal average of these parameters. As these equations are essentially those which are solved in GCMs, although here they are written in a simpler form, they are worth considering in some detail. The momentum equations are themselves expressed for unit mass, so that the density terms cancel and the momentum (mass times velocity) is represented simply by the velocity component in the direction of interest. Zonal momentum changes (with time) are thus represented by the first term on the left hand side of equation (3). These temporal changes are balanced by the Coriolis term, f(v) and the rate of change in the poleward direction of the correlation term, (u'v'), i.e. the eddy transport of momentum in the poleward direction. Finally there is an additional frictional dissipation term, F, to be taken into consideration. The meridional momentum equation is similarly constructed but the small temporal changes are neglected; if they were not the model might accumulate errors and predict non-zero momentum fluxes at the poles. Consequently the balance equation is simply between the
11
Climates of the future TABLE I FUNDAMENTALEQUATIONSSOLVEDIN GCMs (AFTERHENDERSON-SELLERSAND MCGUFFIE,
1987) Conservation of energy (the first law of thermodynamics) i.e. Input energy = increase in internal energy plus work done Conservation of momentum (Newton's second law of motion) i.e. Force = mass x acceleration Conservation of mass (the continuity equation) i.e. The sum of the gradients of the product of density and wind speed in the three orthogonal directions is zero Ideal gas law (an approximation to the equation of state) i.e. Pressure x volume = gas constant x absolute temperature
,
Coriolis force and the pressure gradient force in the poleward direction, friction being neglected. The hydrostatic equation is the third component of the conservation of momentum equation (Table I). In this case we remove vertical wind changes by them being negligibly small, but must keep changes in the pressure field (with height). This equation (equation (5)) can be rewritten as 10(p)
(p) oz
g =
-
~
R(r)
(8)
whence, from the ideal gas law, is derived the more common expression O(p_____))= _ g(p)R(T} = _g(p)
Oz
(9)
R(r)
The thermodynamic balance exists between the temporal rate of change of zonally averaged temperature and the rate at which temperature is both transported into and out of each latitude zone. This is accomplished by eddies in the lateral (northward) and vertical directions and represented by the two eddy correlation terms (terms 2 and 3 on the left hand side of equation (6)). A further term represents vertical transport, taking into account adiabatic heating and cooling due to the compressibility of the atmosphere. The balance is completed by the inclusion of the diabatic heating term on the right hand side. The horizontal component of the eddy momentum flux (u'v') is not only responsible for transferring zonal momentum but helps to drive the meridional circulations shown in Fig. 3b. The continuity equation says simply that mass can neither be created nor destroyed, i.e. the rate of change of mass in all three dimensions overall is zero. However, since zonal averages are under discussion, the change in the x direction has been averaged out, as expressed by the use of angle brackets, and only two components remain. The sum of these two is zero. Thus in regions where there is net divergence or convergence, there must of necessity be a vertical motion also. For two-dimensional climate models it is necessary to find representations for the eddy fluxes in equations (3)-(7) so that this system of equations can be solved numerically. In these models most emphasis is placed on the atmosphere which is represented on a latitude versus pressure (height) grid in about 11 layers and with 10-20 grid points between the
12
Modelling the Earth's climate poles. Often considerable effort goes into representing atmospheric radiative processes and surface features although the main problem remains the characterization of eddy transports. Eddy transport is of critical importance for determining the equator to pole temperature gradient and the vertically distributed zonal wind field, especially the strength of the jet stream winds. Large mid-latitude eddies are seen associated with the westerly jets in both hemispheres in Fig. 3b. Early parameterizations of eddy flux simply related eddy transports to gradients of zonal mean variables using empirically determined diffusion coefficients. This representation is quite similar to the parameterization used in some EBMs for the meridional energy transport This parameterization was based on the argument that, since baroclinic waves are driven by the meridional temperature gradient, their eddy transports might also be simply parameterized as being proportional to this gradient. Thus the eddy heat flux is given by
(v' T' ) = K'r ~/O, T__./ ._.L Oy
(10)
and the eddy momentum flux by
(u' v ' ) - - - g M O(u) Oy
(11)
where KT and KM are empirically derived coefficients for temperature and momentum. More detailed study has shown that, whilst the diffusive representation is fairly reasonable for eddy heat transport, it is a completely inadequate representation of eddy momentum flux, since momentum can be transported up as well as down the meridional gradient of momentum. Consequently, later parameterizations reformulated the transport equations in terms of the potential vorticity gradient. Until the mid-1970s, the parameterizations used in two-dimensional models were empirically based. However, subsequent theoretical analysis by a number of authors in the 1970s demonstrated that the diffusion coefficients as well as the eddy transport itself may be proportional to the meridional temperature gradient. It was found that the equator to pole temperature gradient was considerably different when computed with EBMs which used a value for the diffusion coefficient dependent on the temperature gradient as opposed to a constant eddy diffusion coefficient. This finding suggests that one of the reasons why the energy balance climate models (EBMs) showed considerable sensitivity to a small decrease in solar constant was that the diffusion coefficient in these models was constant, rather than being a function of the temperature gradient. A much greater decrease in the solar constant is necessary to initiate an ice age in a model which includes a temperature gradient dependency of the diffusion coefficient. This is because the temperature gradient remains high at low values of solar input. The basis of the parameterization problem is the simplification which is generally made in the solution of the zonal flow equation in baroclinic wave theory. The usual simplifications are to assume that the zonal wind, (u(y,z)), is a function of y only (the barotropic solution) or z only (the baroclinic solution). Instability to small disturbances of a zonal wind which varies only in the vertical (z) direction (a baroclinic instability) converts to eddy energy the energy that is stored in the current latitudinal variation of zonal temperature, T. This energy is released by the eddy flux of heat (v'T'). On the other hand, instability of a zonal wind to
13
Climates of the future horizontal (y component) perturbations (a barotropic instability) converts kinetic energy of the zonal wind to eddy energy through the flux of horizontal eddy momentum (u'v'). The parameterization of momentum fluxes is considerably more complex when theoretically based than the parameterization of heat fluxes. It has been shown that potential vorticity is more suitable for the treatment of (u'v') as the eddy momentum flux can be obtained once eddy potential vorticity and eddy heat fluxes have been derived. A further problem with eddy flux parameterizations is the existence in the atmosphere of large stationary eddies forced both by topography and by land/ocean temperature contrasts. Since the parameterization schemes described above represent only transient baroclinic eddies, it is possible that there will be an underestimation of the total eddy transport produced due to the neglect of these stationary eddies. However, observational data suggest that a compensatory mechanism may exist since total eddy flux seems to be correlated better with observed temperature gradients than is the transient eddy flux alone. Full formulations of two-dimensional statistical dynamical models (2-D SDs) often also include vertical and horizontal eddy transports of water vapour as well as those of heat and momentum described above. Since 2-D models attempt to parameterize only the eddy transport, whilst the mean meridional transport terms are computed explicitly, it is hoped that inadequacies in the eddy transport parameterizations are compensated for in the explicit calculation of meridional transport. Some 2-D SDs also include quite complex representations of other components of the climate system not generally incorporated into GCMs. For example, the LLN 2-D SD (see Chapter 2 by BERGER) incorporates a submodel of ice masses and ice sheet dynamics. All climate models employed for climate prediction comprise a set of non-linear differential equations which have to be solved by time-stepping forward into the future. All these equations represent only an approximation of the real climate system. These approximations are termed parameterizations. The solution of these sets of equations depend critically upon: (i) these parameterizations and how successfully they represent processes; (ii) the complexity of the system of equations itself; (iii) the values of internal parameters and initializations and (iv) the time periods and time steps involved in the solution. All climate models require extensive evaluation against observations before their predictions can be viewed with any confidence.
Climates of the future
This book places the predictions of a human-induced enhanced greenhouse warming in context by noting that this planet has undergone many natural large-scale climatic changes in the past. The climate in the past million years has been characterized by a series of quasicyclic glaciations. The response of the Earth's climate system to these natural variations is recorded in ocean sediments, peat bogs and polar ice. The results of analyzing the most recent record over the past 100,000 years indicate that Earth's climate does not respond to forcing in a smooth and gradual way. Instead, it responds with rapid, and sometimes discontinuous, changes, especially in the case of warm forcing. If this is correct, a lesson we might learn from the past is that the main responses of the Earth system to greenhouse gas buildup could come in "jumps" whose timing and magnitude are unpredictable.
14
Climates of the future On the other hand, the very long time-scale record of the Earth's climate seems to have been remarkably stable (Fig. !f and Chapter 15 by KUMP and LOVELOCK). Does this imply that while rapid and non-linear changes may well occur in the future they are likely to be buffered on long time-scales by strong negative feedbacks? The answer to this question is not known. The IPCC Executive Summary (HOUGHTON et al., 1990, p xi) states: We are certain of the following: 9 there is a natural greenhouse effect which already keeps the Earth warmer than it would otherwise be. 9 emissions resulting from human activities are substantially increasing the atmospheric concentrations of the greenhouse gases: carbon dioxide, methane, chlorofluorocarbons (CFCs) and nitrous oxide. These increases will enhance the greenhouse effect, resulting on average in an additional warming of the Earth's surface. The main greenhouse gas, water vapour, will increase in response to global warming and further enhance it. and Based on current model results, we predict: 9 under the IPCC Business-as-Usual (Scenario A) emissions of greenhouse gases, a rate of increase of global mean temperature during the next century of about 0.3~ per decade (with an uncertainty range of 0.2~ to 0.5~ per decade); this is greater than that seen over the past 10,000 years. This will result in a likely increase in global mean temperature of about 1~ above the present value by 2025 and 3~ before the end of the next century. The rise will not be steady because of the influence of other factors. Policy development requires information about future climates. For the immediate future 50-100 years, the continuing IPCC assessments provide the clearest available assessment. This book places those predictions in a wider context (Chapters 10 and 11 by ANDREAE and BRASSEUR et al.); provides a broader view of the uncertainties associated with prediction of climate even as far as the next century (Chapter 6 by DXAZ and KILADIS and Chapter 14 by PENG); and places these predictions in a human context by reviewing future urban climates (Chapter 13 by CLEUGH)and the possible impacts of human-induced land-use change on climate (Chapter 12 by HENDERSON-SELLERS). Evidence from traditional meteorological observations and palaeo-indices of climate cannot confirm, with certainty, the existence of an enhanced greenhouse warming signal caused by human activities. The observed temperature rise this century is less than that predicted by numerical climate models (Chapter 5 by JONES) and is commensurate with multi-decadal oscillations in the climate system which are almost certainly due to natural variability (Chapter 6 by DIAZ and KILADIS). However, the Cretaceous climate cannot be simulated by GCMs which have low or even mid-range IPCC-reported sensitivities to doubled CO2 and the Eocene climate, which is characterized by warm poles but weaker atmospheric dynamics, can only be explained if ocean transport of energy was greatly increased during that period compared with the present day (Chapter 3 by B ARRON). Pal~eoclimatic evidence indicates that the climate of the North Atlantic region, which is closely coupled to the formation of North Atlantic Deep Water and the deep ocean conveyor belt circulation (Chapter 14 by PENG), has remained remarkably constant since the very rapid transition from cold to warm conditions about 10,000 years ago (the Younger Dryas (3), noted in Fig. 1). The predicted enhanced greenhouse warming is likely not only to
15
Climates of the future modify the atmospheric circulation (Chapter 8 by MCAVANEY and HOLLAND) but could also strengthen the thermohaline circulation in the Atlantic by increasing the rate of water vapour loss from the Atlantic basin. If this were to occur, the effect could be to sustain the current warm conditions in the Atlantic. On the other hand, enhanced greenhouse warming coupled with changes in land-use (Chapter 12 by HENDERSON-SELLERS)could increase the flow of fresh water into the northern Atlantic tending to decrease salinity in northern Atlantic surface waters which could weaken the oceanic conveyor belt. Continuing reduction in salinity would eventually halt the formation of North Atlantic Deep Water and would thus shut down the ocean conveyor. MAIER-REIMER and MIKOLAJEWICZ (1989) have demonstrated, using an oceanic GCM, that addition of excess fresh water to this region can terminate the model's thermohaline circulation on a time-scale of a few decades. This would plunge the countries around the North Atlantic into a climate about 5~ colder than the present day and would have climatic consequences for other parts of the globe. Astronomical changes will modify the amount of solar radiation incident at the Earth and its latitudinal distribution (Chapter 2 by BERGER). Numerical models of long-period climatic evolution indicate that, in the absence of human-induced climate warming, the Earth will soon move into cooler climatic conditions culminating in a full glacial epoch. Quasioscillatory cooling will occur with progressively colder episodes occurring around 5,000, 23,000 and 60,000 years into the future. The culminating glaciation occurring 60,000 years in the future is predicted as having a similar intensity to the Last Glacial Maximum. Based on astronomical forcing alone, the Earth would not be expected to return to conditions similar to the current Holocene thermal optimum any earlier than 120,000 years from now. Human activities may modify these predictions quite dramatically. In Chapter 2 by BERGER, three possible scenarios relating to orbital changes combined with enhanced greenhouse forcing are described. The simplest scenario is that, for a relatively short period (<1,000 years), greenhouse-enhanced warming will prevail but then will be followed by a return to the "natural pattern" of glacial-interglacial cycles. The second possibility is that, following a period of enhanced greenhouse warming, the next glaciation will be delayed (further into the future than the naturally forced prediction of 60,000 years from now) and will be less severe (i.e. not as intense as the Last Glacial Maximum). The third possibility is that enhanced greenhouse warming will so greatly weaken the positive feedback mechanisms, which are believed to transform the relatively weak orbital forcing signal into global interglacial-glacial cycles, that the initiation of any future glaciations will be indefinitely prevented. It must be recognized that quasi-cyclic forcing and solar evolution are not the only natural factors affecting the Earth's climate. In Chapter 4, RAMPINOdemonstrates that the Earth's climatic history has included catastrophic events induced by the impacts of comets and asteroids. A large body (--2 km in diameter) impact on the Earth is estimated as having a 1 in 10,000 chance of occurrence in the next 100 years. Catastrophic climatic shifts including very rapid cooling and a massive reduction in solar radiation will follow such an impact. If no avoidance procedure is in place, the climatic impact will be very great and will persist for, at the least, hundreds of years. On a more modest scale, but with certainty of occurrence, the climate will continue to be modified by an increasing burden of atmospheric aerosols (Chapter 10 by ANDREAE). The inclusion of a negative forcing effect due to increasing atmospheric aerosols has a signifi-
16
References
cant influence on the interpretation of predictions from global climate models. The inclusion of aerosol-induced cooling in climate model simulations (e.g. HANSEN et al., 1993) may help to explain the apparent inconsistency between GCM predictions and observations (Chapter 10 by ANDREAE, cf. Chapter 5 by JONES). However, the compensatory effect of aerosol cooling compared to greenhouse warming is not an argument for "business as usual" in global industrialization. The much shorter atmospheric lifespan of atmospheric aerosols compared with the greenhouse gases means that the longer the industrially induced compensation is allowed to persist, the greater is the rapid greenhouse-only temperature rise when the "aerosol mask" is finally removed. Furthermore, while on a global mean basis, aerosol-induced cooling does offset greenhouse heating, invoking this as a global climate management policy would lead to an ever-widening difference in the climatic forcing between the Northern and the Southern Hemispheres which is potentially even more disruptive to the climate system than a uniformly distributed greenhouse effect (e.g. WIGLEY, 1991). The climate system is currently modelled by systems of coupled, non-linear differential equations. Chaotic behaviour is the prime characteristic of such systems. This results in unpredictable fluctuations at many time-scales and a tendency for the system to jump between highly disparate states. We do not yet know if chaos is the primary characteristic of the climate system (Figs. 1 and 4b). However, the Earth's climate has been documented as undergoing very rapid transitions on time-scales of decades to centuries (Chapter 14 by PENG). There is no reason to believe that this characteristic will disappear in the future. Future climates will be considerably modified by human activities but they will also be a function of the natural factors which have controlled climates since the Earth was formed. The balances and feedbacks between these forces are a subject urgently in need of research. This book sets the scene for research into, and improved understanding of, future climates.
References
BARRON, E. J., 1995. Warmer worlds: global change lessons from Earth's history. In: A. HENDERSONSELLERS(Editor), Future Climates of the World. Elsevier, Amsterdam. BERGER, A., 1988. Milankovitch theory and climate, Rev. Geophys., 26(4): 624-657. BERGER, A., 1995. Modelling the response of the climate system to astronomical forcing. In: A. HENDERSON-SELLERS(Editor), Future Climates of the World. Elsevier, Amsterdam. BRADLEY, R. S. and JONES, P. D., 1993. "Little Ice Age". Summer temperature variations: their nature and relevance to recent global warming trends. The Holocene, 3: 367-376. GARP, 1975. The physical basis of climate and climate modelling. GARP Publication Series No. 16. WMO/ICSU, Geneva. GORE, A., 1992. Earth in the Balance: Ecology and the Human Spirit. Houghton Mifflin, New York, 408 pp. nANSEN, J., LACIS,A., RUEDI, R., SATO,M. and WILSON,n., 1993. How sensitive is the world's climate? Natl. Geog. Res. Explor., 9: 142-158. HENDERSON-SELLERS, A., 1989. Archaean atmosphere-biosphere interactions. In: A. BERGER, S. n. SCHNEIDERand J.-C. DUPLESSY(Editors) Climate and Geosciences. A Challenge for Science and Society in the 21st Century. NATO, ASI Series C, Vol 285. Kluwer, Dordrecht, pp. 21-38. HENDERSON-SELLERS,A. and MCGUFFIE, K., 1987. A Climate Modelling Primer. Wiley, New York, 217 pp. HENDERSON-SELLERS,B., HENDERSON-SELLERS,A., BENBOW,S. M. P. and MCGUFFIE,K., 1991. Earth - the water planet: a lucky coincidence? In: Scientists on Gaia. MIT Press, Cambridge, MA, pp. 80-89.
17
Climates of the future HOUGHTON, J. T., JENKINS, G. J. and EPHRAUMS,J. J. (Editors), 1990. Climate Change. The IPCC Scientific Assessment. Cambridge University Press, New York, 365 pp. HOUGHTON, J. T., CALLANDER,B. and VARNEY, S. K., 1992. Climate Change 1992: The Supplementary Report to The IPCC Scientific Assessment. Cambridge University Press, New York, 200 pp. HUGHES, M. K. and DIAZ, H. F., 1994. Was there a "Medieval Warm Period", and, if so, where and when. Clim. Change, 26:109-142. IPCC, 1991. Climate Change. The IPCC Response Strategies. Island Press, Washington, DC, 272 pp. JONES, P. D., 1995. Observations from the surface: projection from traditional meteorological observations. In: A. HENDERSON-SELLERS(Editor), Future Climates of the World. Elsevier, Amsterdam. KASTING, J. F., 1989. Long-term stability of the Earth's climate. Palaeogeog., Palaeoclim., Palaeoecol., 75: 83-95. KESSLER, A., 1985. Heat Balance Climatology: General Climatology, a World Survey of Climatology. Elsevier, Amsterdam, 224 pp. KIEHL, J. T., 1992. Atmospheric general circulation modelling. In: K. E. TRENBERTH(Editor), Climate System Modelling. Cambridge University Press, Cambridge, pp. 319-370. KUMP, L. R. and LOVELOCK,J. E., 1995. The geophysiology of climate. In: A. HENDERSON-SELLERS (Editor), Future Climates of the World. Elsevier, Amsterdam. LOVELOCK, J. E., 1986. Geophysiology: a new look at earth science. Bull. Am. Meteorol. Soc., 67: 392-397. MAIER-REIMER, E. and MIKOLAJEWICZ, U., 1989. Experiments with an OGCM on the cause of the Younger Dryas. In: A. AYALA-CASTANARES,W. WOOSTER and A. YANEZ-ARANCIBIA (Editors), Oceanography. UNAM Press, Mexico, pp. 87-100. SCHLESINGER,M. E. (Editor), 1988. Physically-Based Modelling and Simulation of Climate and Climatic Change, 2 vols. Kluwer, Dordrecht. SCHNEIDER, S. H., 1992. Introduction to climate modelling. In: K. E. TRENBERTH (Editor), Climate System Modelling. Cambridge University Press, Cambridge, pp. 3-26. SCHNEIDER, S. n. and BOSTON, P. J. (Editors), 1991. Scientists on Gaia. MIT Press, Cambridge, MA, 433 pp. SCHOPF, J. W. (Editor), 1983. Earth's Earliest Biosphere: Its Origin and Evolution. Princeton University Press, Princeton, NJ, 534 pp. TEGART, W. J. McG., SHELDON, G. W. and GRIFFITHS, D. C. (Editors), 1990. Climate Change. The IPCC Impacts Assessment. Australian Govemment Printing Service, Canberra. US NATIONALACADEMY of SCIENCES, 1975. Understanding Climate Change. National Academy of Sciences, Report of the Panel on Climatic Variation, Washington DC, 127 pp. WIGLEY, T. M. L., 1991. Could reducing fossil-fuel emissions cause global warming? Nature, 349: 503-506.
18
Chapter 2
Modelling the response of the climate system to astronomical forcing A. BERGER
Introduction
The Earth's climate has always been changing (SHACKLETONand IMBRIE, 1990) and will no doubt continue to change. The future climate is unknown, but increasing attention is being given to its prediction. Over the decades, the reconstruction of past climates has largely improved. Key ingredients to this progress include the large variety of paleoclimatic indicators (geochemical, botanical, biological), the accuracy of dating, the expanding geographic coverage of measurements, and the application of statistical techniques for extracting the climatic signal from other signals- and noise- contained in geologic records. The aim of studying past climates is (i) to reconstruct the whole range of natural climatic variability, which includes abrupt changes (i.e. occurring after periods shorter than a human lifespan) and which did not occur during the period covered by instrumental observations; (ii) to test models using past conditions in order to understand better how the climate system works; and so (iii) to address the future with more confidence. The instrumental period database contains primarily details of the climate typical of presentday conditions. If we expect significant changes to occur within the next centuries, this record must be enlarged to cover other climatic types like those which characterize the extreme glacial and interglacial states and other gradual and abrupt climatic changes. Paleoclimatology has clearly demonstrated its ability to reconstruct the gross characteristics of such climatic situations of the past and has so helped the community to discover the natural variability of the climate system at time-scales from years (in ice cores) to hundreds of millennia for the broad geographical regions of the world. Simultaneously, a hierarchy of climate models of increasing accuracy, dimensionality, and versatility are being developed and applied. These models are an invaluable tool for the quantitative testing of theories and for predicting or suggesting phenomena that can subsequently be studied with observations. The reliability of models which are calibrated and validated for the present day and their power to "predict" significant climatic change in the future, can therefore be tested in many different climatic situations using paleoclimatic data, in particular over a range of known changes in orbitally induced radiation. These tests may reveal weaknesses of the models; they will also suggest further process studies which will help to improve the integrated understanding of the climate system (HECHT, 1985). In addition the reconstruction of climatic time series allows transient experiments to be conducted relating causes and effects of climatic changes, experiments which are expected to aid understanding of the progressive changes of our climate under the forcing of human activities.
21
Modelling the response of the climate system to astronomical forcing Climates of the past During most of the Earth's history the climate has been warm, even warmer than today. This warm climate has been interrupted by cold times, the so-called Ice Ages, which have, on the geological time-scale, been relatively short, covering only perhaps 5-10% of the Earth's whole history. The most well known are the Pre-Cambrian Ice Ages, the late Ordovician Ice Age, the Permo-Carboniferous Ice Age and our Present Ice Age (CROWLEY and NORTH, 1991). The current Ice Age, which the Earth entered 2-3 Ma ago (Ma, million years) is called the Quaternary Ice Age and is composed of the Pleistocene and the Holocene, which are usually preferred terminology for this period. It was preceded by the Antarctic ice-sheet formation 25-10 Ma BP (BP, before present) and a long cooling trend through all the Tertiary; in western Europe, for example, the mean temperature went down from 25~ 15~
50 Ma ago, to
at the end of the Pliocene (LLOYD, 1984). Warm pre-Quaternary climates are dis-
cussed in Chapter 3 by B ARRON. The current Ice Age is characterized by multiple switches of the global climate between glacials (with extensive ice sheets) and interglacials (with a climate similar or warmer than today by a few degrees Celsius). These past climates are reconstructed from analysis of proxy data taken from deep-sea cores (e.g. IMBRIE et al., 1992), ice cores (e.g. LORIUS et al., 1990) and land records (e.g. GUIOT et al., 1989). Throughout the past million years (Fig. 1), these data demonstrate that successive glaciation--deglaciation cycles have occurred with a dominant quasi-periodicity of 100 ka (ka, thousand years). The last cycle (Fig. 2) goes from the Eemian interglacial centered roughly 125 ka BP to the present day Holocene interglacial which peaked 6 ka BP, and includes the last glacial maximum (LGM) which occurred 20 ka BP.
Core V28-258 (*,4*N, 1600E) 8,e
0
ofPDB
t28 4z 3 4
5
25t s
7
347 8
9
I0
440 14
592
12 13
14
15
x t0 3 years
',, 750 I 18 t 9 2 0
2!
zz
z3
I
A
-2.0%
16 t7
A
- 1.5% - t.0=4
",1
e
-0.5% B R U N'HE S 0
200
400
600
800 DEPTH IN C M
MATUYAMA
t000
! 200
4400
t 600
Fig. 1. Oxygen isotope and paleomagnetic record of the last 1.6 million years in core V28-238 from the equatorial Pacific (~I~ 160~ as a proxy for long-term climatic changes. Isotope stages are shown in the upper part of the diagram. Isotopic values are from measurements on Globigerinoides sacculifer (after SHACKLETONand OPDYKE, 1976). These isotopic stages were defined by EMmL~NI (1955). With the recognition of consistent stable isotope signals in the sedimentary records of many different areas, warm periods (interglacials and interstadials) were assigned odd numbers (the present interglacial being number 1) and cold (glacials and stadials) were assigned even numbers (see e.g. BRADLEY, 1985).The date of the Matuyama-Brunhes boundary has been more recently discussed by SHACKLETONet al. (1990) and proposed to be 760 ka BP, it means 5-7% older than the currently adopted radiometric dates. Oxygen isotope is here a proxy for total ice volume over the Earth; this ice volume increases downward in this figure.
22
Climates of the past CLIMATIC STATE
Deglocial
ESTIMATED SUMMER SEA-SURFACE TEMPERATURE (CORE V25-82) (*C) 5 IO 15
PRESENT INTERGLACIATION .L
ISOTOPIC STAGE I
AGE, STRATIGRAPHIC YEARS CONTROL B.P. LEVELS -0 e-I0000
termination
I ~
- 20
ISOTOPIC
Ash z o n e
I
(9300 BP)
000
- 30 000 - 40 000
GLACIATION
- 50 000
STAGE
3
~
m
9 60 000
Ash z o n e 2
(65 OOO BP)
70 000
Main glacial transition
"
80 000 ISOTOPIC - 90
o~
EARLY WURM GLACIATION
STAGE
(5c~<
Borbados I (82 OOO BP)
000
- I00 000 Borbodos
"-~----~5d)
Glociol inception Deglacial
termination II
PEAK f5 INTERGLACIATION)~_ -,
(5e)
:~<___
,
II0 000 - 120 0 0 0
2
(IO5 000 BP) Borbodos 3
(125 OOO BP) 130000
~ S O T O P I C STAGE 6
Fig. 2. Summer sea-surface temperature reconstructions for the North Atlantic Ocean based on foraminiferal assemblage paleotemperature estimates, using core V23-82 from ~53~ 22~ (SANCETTA et al., 1973). Chronological controls used in other cores are shown on the right (tephra layers and Barbados sea-level stands). Generalized climatic conditions and major changes are shown on the left. Isotopic stages are after SHACKLETONand OPDYKE (1973). Isotopic stage 5 was subdivided into several sub-stages, bearing letter designations (5a to 5e). Stages 5a, 5c and 5e were periods of reduced terrestrial ice volume and/or higher temperatures, with sub-stage 5e being the peak of the interglacial called Eemian in NW Europe; stages 5b and 5d were periods of cooler temperature and/or terrestrial ice growth, but on a smaller scale than occurred in stage 4.
These LGM cold conditions were documented in great detail by the Climate Long-Range Investigation Mapping and Prediction group (CLIMAP, 1976, 1981). In the northern hemisphere, the LGM world differed strikingly from the present in the huge land-based ice sheets, reaching
approximately 2-3 km in thickness and amounting to about
(40--45) • 106 km 3 of ice. There was also a dramatic increase in the extent of pack-ice and marine-based ice sheets. In the southern hemisphere, the most striking contrast was the greater extent of sea ice. On land, grasslands, steppes and deserts spread at the expense of forests. This change in vegetation, together with extensive areas of permanent ice and sandy outwash plains, caused an increase in global surface albedo compared to modern values (cf. the possible impact of human-induced land-use change discussed in Chapter 12 by A. HENDERSON-SELLERS). Sea-level was lower by at least 115 m (CHAPPELL and SHACKLE-
23
Modelling the response of the climate system to astronomical forcing TON, 1986; LABEYRIE et al., 1987; TUSHINGHAM and PELTIER, 1991) which represents roughly 50 • 106 k n l 3 of ice more than now, and the global average surface air temperature was 5~ below present. CO2 levels were less than two-thirds their present value (BARNOLA et al., 1987; JOUZEL et al., 1993) and aerosol loading was higher than present (DE ANGELIS et al., 1987; JOUSSAUME, 1993). According to CLIMAP (1976), the LGM oceans in August were characterized by: (i) marked steepening of thermal gradients along polar frontal systems, particularly in the North Atlantic and Antarctic; (ii) an equator-ward displacement of polar frontal systems; (iii) general cooling of most surface waters, with a global average of-2.3~ (iv) increased cooling and upwelling along equatorial divergences in the Pacific and Atlantic; (v) low temperatures extending equator-ward along the western coast of Africa, Australia and South America, indicating increased upwelling and advection of cool waters; (vi) nearly stable positions and temperatures of the central gyres in the sub-tropical Atlantic, Pacific and Indian oceans; and (vii) little temperature change (-2~ in the tropical oceans. There are, however, geological data suggesting that the sea-surface temperatures in the tropics were lower than reconstructed by CLIMAP, about 5~ lower than today. The evidence came from corals around Barbados (ANDERSON and WEBB, 1994; GUILDERSON et al., 1994) and matches the cooling estimated from terrestrial evidence of lower snowlines and changes in ancient patterns of vegetation at mid to high elevations. According to the results by Co-operative Holocene Mapping Project Members (COHMAP, 1988), beginning around 16 ka BP, the climate system experienced major change during which the ice sheets retreated, ocean fronts shifted poleward, and the areas covered by sea ice contracted (RUDDIMAN and MCINTYRE, 1981). In the mid-latitudes, vegetation zones shifted poleward and after 14 ka BP, lake levels fell (for example, in the southwestern United States). The time interval 16-13 ka BP is sometimes known as the Late Glacial and is the time of maximum desiccation for African lakes (STREETand GROVE, 1979). Although residual remnants of the Laurentide Ice Sheet lasted until 6-7 ka B P most of the ice disappeared within an interval of about 5 ka, from 14 to 9 ka BP. Deglaciation actually occurred in two main steps: an abrupt warming around 13 ka BP, followed by a climate reversal at about 12 ka BP (termed the Younger Dryas in Europe) and then another abrupt warming at 10 ka BP. The two warming trends are also manifested as rapid changes in sea-level dated 13.5 and 11 ka BP (FAIRBANKS, 1989). This Younger Dryas may have been caused by an interruption of thermohaline circulation due to meltwater-induced changes in the surface waters of the North Atlantic (BROECKER et al., 1989), but the sea-level curve and other evidence from tracers of ocean circulation do not favour this mechanism. The finding that meltwater discharge was minimal during the Younger Dryas led DUPLESSY et al. (1992) to suggest that the surface-water salinity drop might have been caused by a reduction in poleward advection of sub-tropical saline water. The waxing and waning of ice sheets occurred in a more or less regular way. In Fig. 1, one can recognize a sawtooth shape with a 100-ka quasi-cycle over which shorter quasi-cycles of roughly 41 and 21 ka are superimposed. These kinds of broad climatic features characterizing the last few million years (and probably other climatic variations of non-Ice Ages, like those which occurred during the late Triassic (OLSEN, 1986)) are those explained by the astronomical theory of paleoclimates (BERGER, 1988). Proponents of this theory claim that the changes in the Earth's orbital and rotational parameters have been sufficiently large as to in-
24
Astronomical theory of paleoclimates duce significant changes in the seasonal and latitudinal distributions of irradiation received from the Sun and so, to force glacials and interglacials to recur in the manner deduced from geological records. This topic is the main theme of this chapter. In addition to these climatic changes at the millennia time-scale, climate shifts over periods as short as a few decades to a few centuries have also been detected. Sediments in the North Atlantic ocean contain a series of layers (named after their discoverer, Heinrich) deposited between 14 ka BP and 70 ka BP (BOND et al., 1992). These layers are rich in ice-rafted debris, which may reflect repeated rapid advances of the Laurentide ice sheet, perhaps associated with reductions in air temperature, although temperatures from Greenland ice cores appear to exhibit only a weak corresponding signal. Similar events are seen in land records; for example, major vegetation shifts seem to have occurred during the last 50 ka in Florida (GRIMM et al., 1993). Results from a deep-ice core drilled at the summit of the Greenland ice sheet, also reveal irregular but well-defined episodes of relatively mild climatic conditions during the mid and late parts of the last glaciation; these interstadials (the OeschgerDansgaard events) lasted from 500 to 2000 years (JOHNSEN et al., 1992). Climate instability is not confined to the last glaciation: isotope and chemical analyses of the GRIP ice core (GRIP, GREENLAND ICE-CORE PROJECT MEMBERS, 1993) reveal that climate in Greenland during the last interglacial period was characterized by a series of several cold periods, which began extremely rapidly and lasted from decades to centuries (although the intensity of these cold events needs to be confirmed, in particular by the analysis of the results obtained from the US Greenland Ice Sheet Project, GISP2; BOULTON, 1993; GROOTES et al., 1993; TAYLOR et al., 1993). In contrast, the past 8 ka has been strangely stable. Therefore, apart from the Holocene, instability seems to have dominated the North Atlantic climate over the past 230 ka (DANSGAARD et al., 1993). This recognition highlights the question of whether the Holocene will remain stable in spite of the growing human disturbance of the atmosphere. This question is tackled in other parts of this book, particularly Chapter 8 by MCAVANEY and HOLLAND and Chapter 9 by WANG et al.
Astronomical theory of paleoclimates Perturbations of Earth's orbital and rotational parameters The incoming solar radiation received over the Earth has an annual periodic variation due to the Earth's elliptic translation motion around the Sun. In addition, the seasonal and latitudinal distributions of this solar radiation have a long-period variation due to the so-called long-term variations in the orbital elements. The total solar energy received by the whole Earth over 1 year also varies, but by a very small amount, in relation to one of these orbital parameters, the eccentricity of the Earth's orbit. Other long-period variations affecting the solar constant and attributable to changes in the physical conditions of the Sun and/or in the opacity or transparency of the interplanetary medium have been postulated from time to time (e.g. LEAN, 1991; LEAN et al., 1992), but their effects remain difficult to prove. Analysis of the incoming solar radiation and of its latitudinal distribution shows that there exist three main orbital parameters whose long-term variations must be calculated (BERGER, 1993): the eccentricity, e, a measure of the shape of the Earth's orbit around the Sun, the
25
Modelling the response of the climate system to astronomical forcing obliquity, e, the tilt of the equator with respect to the plane of the Earth's orbit, and the climatic precession, e sin ff~, a measure of the Earth-Sun distance at the summer solstice ( ~ being the longitude of the perihelion measured from the moving equinox; seasons referred to in this chapter are always specific to the northern hemisphere). As determined from celestial mechanics, the secular variations of these elements of the Earth's orbit and rotation are due to the gravitational perturbations which the Sun, the other planets and the Moon exert on the Earth's orbit and on its axis of rotation (BERGER, 1976a, 1977a). For the long-term variations over the last few million years, the equations for the eccentricity, for the precession and for the obliquity cannot be integrated analytically, but their numerical solutions can be expressed in trigonometrical form as quasi-periodic functions of time: e sin ~ - ~
P/sin(a i t -I- 1]i )
(1)
e=e*+~A
i cos(~'itd-~ i )
(2)
E i cos(Ait +r
e = e* + ~
(3)
where the amplitudes Pi, Ai, El, the frequencies a i, ~i, 2i and phases ~i, ~i, ~i, are given in BERGER (1978) for calculations over one million years. BERGER and LOUTRE (1991) have calculated a new solution which can be used for paleoclimatic studies over 3 x 106 years in the time domain and over 10 x 106 years, at least, in the frequency domain. Its accuracy has been demonstrated from a comparison with two other similar solutions (BERGER and 0.06 :B 0.04 0.02 0 -0.02 -0.04 -0.06
'
'
'
'
I
.
.
.
.
.
.
'
'
I
.
.
.
.
'
'
'
'
I
.
.
.
.
25.0 24.5 24.0 23.5 23.0 22.5 22.0
0.06 0.05
I
-
0.04 0.03 0.02
0.01 0 100
50
0
I J I I J I I I J J I I I I J I I , j_l I -50 -100 -150 -200
Time (ka) Fig. 3. Long-term variations of precession, obliquity and eccentricity from 200 ka BP to 100 ka AP according to the astronomical solution given in BERGER(1978).
26
Astronomical theory of paleoclimates TABLE I AMPLITUDES, MEAN RATES, PHASES AND PERIODS OF THE 6 LARGEST AMPLITUDE TERMS IN THE TRIGONOMETRICAL EXPANSIONS OF CLIMATIC PRECESSION (A), OBLIQUITY (a) AND ECCENTRICITY (C)
Amplitude
Mean rate ("/year)
Phase (~
Period (years)
(a) Climatic precession e sin 0.018970 54.66624 0.016318 57.87275 0.012989 68.33975 0.008136 67.79501 0.003870 55.98574 0.002557 67.52198
32.2 201.3 153.4 311.4 78.6 38.1
23708 22394 18964 19116 23149 19194
(b) Obliqui~ e -1969.00 -903.50 -631.67 -602.81 -352.88 -266.00
31.54068 32.62947 32.08588 24.06077 30.99683 44.78645
247.14 288.79 265.33 129.70 43.20 18.77
41090 39719 40392 53864 41811 28937
(C) Eccentnci~ e 0.011268 0.008819 0.007419 0.005600 0.004759 0.003861
3.20651 13.67352 10.46700 13.12877 9.92226 0.54475
169.2 121.2 312.0 279.2 110.1 202
404178 94782 123818 98715 130615 2379077
It must be stressed that this very limited number of terms do not allow the exact numerical values of these astronomical parameters to be computed; more than 50 terms in equations (1), (2) and (3) are necessary to reach an acceptable accuracy (BERGERand LOUTRE, 1991)
LOUTRE, 1992). The six largest amplitude terms of this new solution are listed in Table I. Figure 3 shows the long-term variations of these three astronomical parameters over the past 200,000 years and into the future for the next 100,000 years. Over the past 3 x 106 years, the eccentricity of the orbit varies between near circularity (e = 0) and slight ellipticity (e = 0.07) at a period whose mean is about 100 ka. The most important terms in the series expansion occur, however, at 404, 95, 124, 99, 131 and 2380 ka (in decreasing order of the amplitudes). The tilt of the Earth's axis varies between about 22 ~ and 25 ~ at a period of nearly 41 ka. Although this period corresponds in equation (2) to the amplitude which is by far the largest, there are two other important terms with periods of 54 and 29 ka. As far as precession is concerned, two components must be considered. The first is the axial precession in which the torque of the Sun, the Moon and the planets on the Earth's equatorial bulge causes the axis of rotation to wobble like that of a spinning top. The net effect is that the North Pole describes clockwise a circle in space (provided the nutations, i.e. terms with small amplitude and much smaller periods, are neglected) with a period o f - 2 5 , 8 0 0 years corresponding to the period of the vernal equinox against a fixed reference point. The second is related to the fact that the elliptical figure of
27
Modelling the response of the climate system to astronomical forcing
e = 0.0167
Sept 23 (217) FE
I TODAY I
co= 102 = 23.45
,,,
(24) Dec 22
Jan 3
A July 4
ss
J u n e 22
( 478 )
SE Mar 21 (216)
June 23
_5,500 yr B ~
(498)
SS
e = 0.0185 (o=9
(224) Sept21 FE Oct 8
e = 24.06
P
A
Apr 8
s_9 Mar 21
(209)
WS Dec 19
(21)
Mar21
I II,000 yr BP]
(215)
e = 0.0195
SE
o~= 278 E= (522) June 18 SS p June 27
24.2
A Dec 26 S
Dec 17
(19)
FE Sept 15
(218)
Fig. 4. Shift of the position of the equinoxes and of the solstices around the Earth's elliptical orbit for today, 5,500 years BP and 11,000 years BP. SE, spring equinox; FE, autumn equinox; SS, summer solstice; WS, winter solstice; P, perihelion; A, aphelion. The orientation of this orbit has been kept arbitrarily the same and the beginning of the spring is fixed on calendar date March 21. The beginning of the other seasons is changing in time because the length of the seasons is changing. The numerical values of the eccentricity, e, of the obliquity, e, of the longitude of the perihelion, E~ (measured from FE), and of the 60~ insolation at the solstices and equinoxes (values between parentheses in W m -x) are taken from BERGER (1978). In this figure, the shape and angles are exaggerated for visibility.
28
Astronomical theory of paleoclimates the Earth's orbit is itself rotating counterclockwise in the same plane leading to an absolute motion of the perihelion whose period, measured relative to the fixed stars, is about 100 ka (the same as for the eccentricity). The two effects together result in what is known as the climatic precession of the equinoxes, a motion mathematically described by ~ and in which the equinoxes and solstices shift slowly around the Earth's orbit relative to the perihelion, with a mean period of 21 ka. This period results actually from the existence of two periods which are close to each other: 23 and 19 ka (Table I). In the insolation formulas used to study past and future astronomical forcing of climate, the amplitude of sin ~
is modulated by eccentricity in the term e sin ff~. The envelope of
e sin ~ is given exactly by e; this is because the frequencies of e originate strictly from combinations of the frequencies of ~ ; for example: 21 = a2 - al, 22 = a3 - al, 23 - a3 - a2, and 2 6 -- a 3 -- a 4 (BERGER and LOUTRE, 1990). Therefore, while today the winter solstice occurs near perihelion, during the deglaciation,
2 4 -- a 4 -- tZ1, '~'5 -" O~4 -- ~ 2 ,
roughly l0 ka BP, it occurred near aphelion (Fig. 4). Moreover, because the lengths of the seasons vary in time according to Kepler's second law, the solstices and equinoxes occurred at different calendar dates during the geological past and will alter in the future. Presently in the northern hemisphere, the longest seasons are spring (92 days 19 h) and summer (93 days 15 h), while autumn with 89 days 20 h and winter (89 days) are notably shorter. In --1250 A.D. spring and summer had the same length (as did autumn and winter) because the winter solstice was occurring at the perihelion. About 4,500 years into the future, the northern hemisphere spring and winter will have the same shorter length and consequently summer and fall will be equally long. Impact on solar radiation
The combined influence of changes in e, e and e sin ff~ produces a complex pattern of insolation variations. A detailed analysis of the changes in solar radiation (BERGER et al., 1993a) shows that it is principally affected by variations in precession, although the obliquity plays an important role for high latitudes, mainly in the winter hemisphere. At the equinoxes, in-
oo
. . . . .
/[IUi'!"
=
"
i
3O
2
'"""""
o
/
i
~..J.
I 0
.
~r -30
/\ -90
I 100
50
,
,
,
,
I 0
,
,
,
,
I -50
,
,
,
,
, -100
,
,
,
, - 1 5 0
,
,
, - 2 0 0
Time
Fig. 5. Long-term variations of the deviation from today's values of the irradiation (W m-2) at the northern hemisphere summer solstice from 200 ka BP to 100 ka AP calculated from BERGER(1978).
29
Modelling the response of the climate system to astronomical forcing solation for each latitude is only a function of precession. At the solstices, both precession and obliquity influence insolation, although precession is dominating for most of the latitudes (Fig. 5). Changes in incoming solar radiation due to changes in tilt are the same in both hemispheres during the same local season: an increase of E leads to an increase of insolation in the summer hemisphere and a decrease in the winter hemisphere. As the strength of the effect is small in the tropics and maximum at the poles, obliquity increases tend to amplify the seasonal cycle in the high latitudes of both hemispheres simultaneously. The precession effect can cause warm winters and cool summers in one hemisphere while causing the opposite effects in the other hemisphere. For example, portions of the northern hemisphere receive during present winter as much as 10% more insolation than 11 ka BP when the perihelion occurred in the northern hemisphere summer. It must be stressed that the pattern of solar irradiation at the top of the atmosphere differs significantly from the pattern of radiation absorbed by the surface of the Earth, particularly in high latitudes where the surface albedo is large (TRICOT and BERGER, 1988).
Milankovitch theory The orbital hypothesis of climatic change was first quantitatively formulated by the astronomer Milutin Milankovitch in the 1920s and 1930s. His early calculations provided information on the variations in incident solar radiation, as a function of latitude, for the last million years in winter and summer (MILANKOVITCH, 1920, 1941). Unlike CP,OLL (1864), one of the very first, with ADHI~MAR (1842), to suggest that the prime mover of the glacial-interglacial cycles might be variations in the way the Earth moves around the Sun (IMBRIE and IMBRIE, 1979), Milankovitch argued that insolation changes in the high northern latitudes during the summer season were critical to the formation of continental ice sheets. During periods when insolation in the summer was reduced, the snow of the previous winter would tend to be preserved- a tendency that would be enhanced by the high albedo of the snow and ice areas. Eventually, the effect of this positive feedback would lead to the formation of persistent ice sheets. According to the mathematics of insolation, a minimum in the northern hemisphere caloric summer 1 insolation at high latitudes requires a northern hemisphere summer occurring at the aphelion, a maximum eccentricity which leads to a large distance between the Earth and the Sun at the aphelion, and a minimum obliquity implying a weak seasonal contrast and an increased latitudinal energy gradient between the equator and the poles. Given these conditions, it is suggested that, not only would the northern high latitudes remain cool enough in summer for preventing snow and ice from melting, but also that mild winter would allow a substantial evaporation in the intertropical zone and, thus, abundant snowfalls in temperate
1 Milankovitch defined the caloric summer to avoid the variations of the length of the astronomical summer, as the half-year which comprises all the days of stronger radiation and consequently experiences the greatest possible irradiation; the other half-year is the caloric winter. This raises two problems: first, the beginning of these caloric seasons changes with time; second, it is difficult to define it in the equatorial regions where the seasonal march of insolation has two maximaand two minima.
30
Astronomical theory of paleoclimates and polar latitudes, the humidity being supplied there by an intensified general circulation due to a maximum latitudinal energy gradient. A simple linear version of the Milankovitch model would therefore predict that the total ice volume and climate over the Earth would vary with the same regular pattern as the insolation; this means that the proxy record of climate variations would contain the frequencies of the astronomical parameters that are responsible for changing the seasonal and latitudinal distributions of the incoming solar radiation. It happens that investigations during the last 20 years have indeed demonstrated that the 19 ka, 23 ka and 41 ka periodicities actually occur in long records of the Quaternary climate (HAYS et al., 1976), that the climatic variations observed in these frequency bands are linearly related to the orbital forcing functions and that there is a fairly consistent phase relationship between insolation, sea-surface temperature and ice volume (IMBRIE et al., 1984, 1989). The geological observation of the bipartition of the precessional peak, confirmed in astronomical computations by BERGER (1977b), was one of the first delicate and impressive tests of the Milankovitch theory. Another impressive confirmation is the discovery in environmental spectra of other astronomical peaks predicted in 1977: the 54 ka and 30 ka periods of the obliquity were found by RUDDIMAN et al. (1986) in the North East Atlantic winter sea-surface temperature record; the 412 ka eccentricity period was found in particular by BRISKIN and HARRELL (1980) and by MOORE et al. (1982) using 2 Ma sediment cores from the Atlantic and the Pacific. Despite these discoveries in support of the Milankovitch hypothesis, the same investigations identified the largest climatic cycle as being 100 ka. This eccentricity cycle is very weak in the insolation. So it cannot be related to the orbital forcing by any simple linear mechanism. Actually, the variance components centred near this 100-ka cycle seem to be in phase with the eccentricity cycle, but its exceptional strength in the climatic record demands non-linear amplification (i) by the glacial ice sheets themselves involving mechanisms such as the icealbedo feedback and the isostatic rebound of the lithosphere (BIRCHFIELDand WEERTMAN, 1978); (ii) by the carbon dioxide atmospheric concentration (LORIUS et al., 1990); and/or (iii) by the oceanic circulation (BROECKER and DENTON, 1990). Moreover, the determination of climatic periodicities from the geological records is not always as clear. The 100-ka cycle, the most dominant feature in the ice volume record for the late Pleistocene, does not exhibit a constant amplitude over the past (23) x 106years; it disappears before 106years ago, at a time when the ice sheets were much less extensive across the Earth (PRELL, 1982; SHACKLETON et al., 1988). The SPECMAP group (Spectral Mapping Project) has also shown that the shape of the spectra and the phase lags in the climate response to orbital forcing depend upon the location of the deep-sea core and the nature of the climatic parameter determined (IMBRIE et al., 1989, 1992, 1993). Since the publication of the papers by HAYS et al. (1976) and IMBRIE and IMBRIE (1980), a number of modelling studies have attempted to explain the relationship between astronomical forcing and climatic change. Both general circulation models, which provide snapshot views of the climate in equilibrium with given boundary conditions, and statisticaldynamical models, which can take into account long-period forcing of the climate system, have been used.
31
Modelling the response of the climate system to astronomical forcing
"Snapshot" simulations of past climate Equilibrium models Climate models can be divided into three very broad categories: (1) general circulation models (GCMs); (2) statistical-dynamical models, which include 2-D zonally or sectorally averaged dynamics; and (3) thermodynamic and energy balance (EBMs) models (KUTZBACH, 1985). GCMs, statistical-dynamical models and EBMs have been used for the modelling of paleoclimates (KUTZBACH, 1985, 1992). GCMs have been used for simulating geographic features of paleoclimates and for including, in the most explicit form, processes such as precipitation that depend on details of the atmospheric flow. However, because of the large computational costs that are involved, GCMs have been used to provide "snapshot" views of the climate in equilibrium with specific boundary conditions. These conditions include the seasonal and latitudinal changes of solar radiation at the top of the atmosphere (resulting from modifications in the Earth's orbit about the Sun), as well as variations in sea-surface temperatures, major ice sheets, atmospheric composition and opacity (see Chapter 4 by RAMPINO and 10 by ANDREAE), and the locations of continents (see chapter 3 by BARRON) for simulations distant enough in the past. On the other hand, statistical-dynamical models have great potential for long-period climate simulations. As they are less complex than GCMs, they consume less computer time, thus allowing account to be taken of additional parts of the climate system in an interactive and time-dependent way. Therefore, these models can be used to simulate long-period transient responses of the climate system to any "external" forcing or internal perturbation. For example, some of them have been coupled to slowly responding portions of the climate system (e.g. ice sheets) in order to investigate the temporal evolution of climate on millenia time-scales. Energy balance models, which are relatively simple one-dimensional models of the Earth's radiation balance, were also used for snapshot simulations of paleoclimates (e.g. DONN and SHAW, 1977; SCHNEIDER and THOMPSON, 1979; SUAREZ and HELD, 1979; NORTH et al., 1983; SELLERS, 1984; ADEM et al., 1984; ADEM, 1988), as well as 2-D zonally averaged dynamical models (e.g. OERLEMANS and VERNEKAR, 1981). For example, NORTH et al. (1983) used such an energy budget climate model with a realistic distribution of the continents and the oceans to show that for large eccentricity, January perihelion and minimum axial tilt, summer temperatures could be several degrees Celsius lower than present in northern continental interiors where present-day summer temperatures are only a few degrees Celsius above freezing. When an ice-albedo feedback was included, the cooling was enhanced. While this result lent some support to the hypothesis that certain orbital configurations favour initiation of glaciation, the role of the ice-albedo feedback mechanism remained uncertain because this model had no explicit hydrological cycle. Even where EBMs are used to model time dependent behaviour (HARVEY and SCHNEIDER, 1985) many important components such as snow and ice feedbacks, clouds and the deep oceans, may be grossly simplified or ignored. They can thus only be used to investigate isolated elements of the climate response to orbital forcing, such as the differential response of land and sea (SHORT et al., 1991). Over the last 25 years, the development of detailed three-dimensional global climate models (GCMs) has occurred in concert with high performance computing. These models, based on
32
"Snapshot" simulations of past climate physical laws of radiative transfer and thermodynamics (e.g. WASHINGTON and PARKINSON, 1986; SCHLESINGER, 1988; TRENBERTH, 1992), have been evaluated extensively against present climate (GATES et al., 1992). They show some skill in reproducing the main features of the general circulation of the atmosphere, and are being used to understand and predict the climatic effects of increases in greenhouse gases (MITCHELL, 1989; HOUGHTON et al., 1990, 1992; and Chapter 9 by WANG et al.), ozone depletion (Chapter 11 by BRASSEUR et al. ) and human disturbance (e.g. Chapter 12 by HENDERSON-SELLERS). In atmospheric general circulation models (AGCMs), prognostic equations governing the conservation of momentum, heat, mass and water are solved numerically at a set of discrete grid-points over the globe and at multiple levels in the vertical. The largest source of uncertainty is associated with the parameterization of the sub-gridscale processes, such as cloud, cumulus convection, surface evaporation and surface drag. Ocean general circulation models are constructed in a similar way to AGCMs, except that salinity rather than specific humidity is used and the parameterization of physical processes is generally simpler. When atmospheric and oceanic models are coupled together, errors in both components can lead to the accumulation of substantial errors in the simulation of sea-surface temperature and seaice extents and, often to "climatic drifts" away from present-day conditions. In order to produce a realistic simulation of present climate, a technique known as "flux correction" was introduced. This means that the coupled model is continually restored to observations to counteract the rate at which it tends to drift (MANABEand STOUFFER, 1988; SAUSENet al., 1988; HADLEY CENTER, 1992; MURPHY, 1992). Recent improvements in coupled AOGCMs so that these corrections will not be required have been fairly successful. Although there is a broad agreement among different models on the nature of the simulated changes at the largest scales (e.g. all GCMs produce a warmer climate when the amount of COa in the atmosphere is doubled, e.g. HOUGHTON et al., 1990, 1992), the regional and local response of these models is often dependent on the parameterizations used. Two models can actually simulate similar present climates, but substantially different responses to increases in greenhouse gases, for example (SCHLESINGER and MITCHELL, 1987; HOUGHTON et al., 1990, 1992; SENIOR and MITCHELL, 1993); consequently, validation against the present climate is not sufficient to discriminate between reliable and unreliable models. These models must, therefore, be tested against a larger set of different climatic situations which can be provided by the reconstruction of the climatic history of the Earth (CROWLEYand NORTH, 1991; BRADLEY, 1989; and Chapter 6 by DIAZ and KILADIS). The ability of a model to simulate a past climate does not necessarily guarantee that it will correctly predict future climates as the mechanisms of change may be different. Nevertheless, as stressed by MITCHELL (1993), failure to simulate a past climate successfully may help to identify shortcomings in model formulation. On the other hand, there have been numerous attempts to look for geologic analogs in the climatic history of the Earth in order to better understand future enhanced greenhouse warming, for example. However, as demonstrated by CROWLEY (1990) and MITCHELL (1990), there may be no warm time period that is a satisfactory past analog for future climate because the mechanisms producing such warm periods in the past may have been totally different from those that would occur following an increase in the concentration of greenhouse gases. Paleoclimates must therefore be primarily studied to provide important insights into processes operating in the climate system and for model testing rather than to provide analogs for future climates.
33
Modelling the response of the climate system to astronomical forcing At present, the length of the GCM simulations is still limited to decades and centuries (MANABE and STOUFFER, 1993; STOUFFER et al., 1994) by the lack of availability of computer resources. So, the evolution of climate over geological time-scales cannot yet be simulated by GCMs. Instead, it is assumed that on short time-scales (hundreds of years), climate is in approximate equilibrium with a "snapshot" description of the state of the more slowly changing components of the system, such as the major ice sheets, the deep oceans, the atmospheric composition and continental plates, and by the values of the slowly changing external factors, such as the Earth's orbital parameters and the solar energy output. These components are prescribed and used as boundary conditions and the response of the faster changing components of climate, such as clouds, sea ice and soil moisture, are simulated in the GCM. As well as this limit of having to use "snapshot" conditions it is also the case that current models still omit some of the faster processes; for example, the effects of vegetation, atmospheric dust and aerosols are not yet included interactively and the seasurface temperatures are still often calculated using a simple thermodynamic mixed-layer model of the upper ocean rather than considering the full three-dimensional ocean. This approach can give only snapshots of specific times of the past and the future where it is assumed that the final equilibrium is independent of the initial conditions. Excellent reviews of such equilibrium simulations of past climates have been done by KUTZBACH (1985), CROWLEY (1989), STREET-PERROTT(1991) and MITCHELL (1993). Paleoclimate general circulation experiments fall into two categories" (i) realistic experiments are designed to reproduce the past climate as accurately as possible and (ii) sensitivity experiments designed to assess the response of a given model to individual forcing factors. Both types of experiments are, however, designed to investigate the nature of climate conditions and circulation patterns at selected times in the past for which substantial quantities of paleoclimate data are available and/or which have distinctive insolation forcing characteristics. The Last Glacial Maximum (18-20 ka BP), the Holocene thermal optimum (6 ka BP) and the Eemian Interglacial (125 ka BP) are the climatic episodes on which most investigations have been focussed to date, but attempts to tackle earlier geological periods have also been made (see Chapter 3 by BARRON)(CROWLEYet al., 1992; RUDDIMAN and KUTZBACH, 1989). The Last Glacial Maximum (LGM) Considerable progress has been made in producing data and simulations for specific periods of the late Quaternary. When the changes in the boundary conditions are well known, the reliability of a GCM can be tested by comparing the changes in temperature and precipitation simulated by the model with those reconstructed from the geological data. Moreover, the model can be used to determine the accompanying changes in the atmospheric circulation and other parameters not easily derived from geological data. This has been done by a number of modelling groups for the climate of the LGM. This LGM was first dated as occurring at 18 ka BP (CLIMAP, 1976), a date which was used in all model experiments until 1992, but recent calibration of the 14C chronology provides an age which is 2-3 ka older (BARD et al., 1990). Orbital insolation values for January and July were within 1% of present-day values for all latitudes and seasons at 18 ka BP, so this effect is relatively minor for simulations of the 18 ka BP climate.
34
"Snapshot" simulations of past climate The first simulations of glacial climates with GCMs were made by ALYEA (1972) and WILLIAMS et al. (1974). When more detailed boundary conditions for August 18 ka BP became available (CLIMAP, 1976), further simulation experiments were performed by GATES (1976a,b) and MANABE and HAHN (1977). Since then, both August and February boundary conditions have been summarized (CLIMAP, 1981) and these data sets have formed the basis for additional experimentation (HANSEN et al., 1984; KUTZBACH and GUETTER, 1984a; MANABE and BROCCOLI, 1984). The ice-age simulations of GATES (1976a,b) and MANABE and HAHN (1977) indicated that global-averaged surface-air temperature was 4-5~ below present in August 18 ka BP. Consistent with the generally lower temperature, 15% reduction in the intensity of the hydrological cycle was simulated by both models, i.e. less precipitation and less evaporation. For both models, the simulated decrease in temperature over land exceeded the (prescribed) decrease of ocean temperature. This larger cooling of the land relative to the ocean tended to weaken the northern hemisphere summer monsoon circulations and, more generally, produced a tendency for anticyclonic outflow from the extratropical continents and hence further reduced precipitation (RIND, 1987). By using models that incorporate more of the climate system, such as models which couple the atmosphere to the oceans, the number of prescribed boundary conditions can be reduced, thus releasing the paleoclimatic information for verification rather than prescription. For example, MANABE and BROCCOLI (1984, 1985a) used a GCM of the atmosphere coupled with a static mixed-layer ocean model to study the influence of the LGM ice sheets on the simulated atmosphere-ocean climate. They found also a simulated global mean cooling greater over land than over the neighbouring ocean. In addition, the ice sheets exerted a significant influence on the upper air flow pattern, displacing the jet stream and the associated storm tracks southwards (see also KUTZBACH and WRIGHT, 1985; KUTZBACH and GUETTER, 1986). The westerly flow was also diverted around the north of the Laurentide ice sheet and to the south between North America and Greenland. This strong wind and frigid air caused a pronounced cooling of the northern Atlantic surface waters and contributed to the significant equator-ward extension of the polar front margin. Expansion of North Atlantic sea ice in turn affected European climate, the extensive area of winter sea ice upwind of Europe resuiting in a marked change of conditions from the present. Advection and local cooling from the Fennoscandian Ice Sheet resulted in winter temperature decreases (of about 20~ in Europe larger than for any other land area (LAUTENSCHLAGER and HERTERICH, 1990). Several other GCM simulations indicate also that considerable summer melting took place along the southern margin of the ice sheets. Further south, high lake levels in northwestern Africa and parts of the Mideast (STREET-PERROTT and HARRISON, 1984) may have been caused by winter storms tracking along the southern margin of the sea ice. MANABE and BROCCOLI (1985a) found also that in the northern hemisphere the simulated temperature distribution of the mixed-layer ocean resembled broadly that estimated by CLIMAP. However, the simulated influence of the ice sheet on the southern hemisphere oceans was small; they concluded that other changes in the heat budget, besides those directly caused by changes in ice sheet distributions, might be needed to explain the glacial climate; they suggested that changes in atmospheric CO2 concentration and interhemispheric oceanic heat transport were two possible candidates. This was confirmed by BROCCOLI and MANABE (1987) who have estimated the separate effects of the changes in land-ice, CO2 and
35
Modelling the response of the climate system to astronomical forcing vegetation. Reducing CO2 had the largest effect, producing a cooling in both hemispheres, but particularly in the southern hemisphere where there is a strong sea ice-temperature feedback. The cooling of the low latitudes ocean simulated by BROCCOLI and MANABE (1987) is larger than that reconstructed from paleoclimatic data (CLIMAP, 1981), particularly in the sub-tropics, a model result which is in agreement with data from mountains at these latitudes. RIND and PETEET (1985) found that a simulation with CLIMAP (1981) sea temperatures reduced everywhere by a further 2~ gives a better fit to the observed temperature reconstruction from tropical mountains. They also obtained a marked decrease in the strength of the hydrological cycle over the tropical continents, in agreement with paleoclimatic reconstructions and with the simulation of MANABE and HAHN (1977) who used the CLIMAP (1976) estimate of sea-surface temperatures; the latter indicating a greater cooling at low latitudes. On the other hand, accepting that the tropical ocean was no more than about 1~ cooler at 18 ka BP than at present and the snow lines on high peaks had descended 1 km, SUN and LINDZEN (1993) conclude that the lapse rate in the lower half of the tropical troposphere during the last glaciation would have been about 20% greater than at present. According to these simulations, it therefore became possible that CLIMAP reconstructions of the sea-surface temperature of the tropical ocean may have to be revised (as done by GUILDERSON et al., 1994), a recommendation which was made by the Paleoclimate Modelling Intercomparison Project in May 1991 at the NATO Advanced Research Workshop on Paleoclimate Modelling in Paris. This project, chaired by S. Joussaume, was initiated in 1991, and has as its goal to make model-model and model-data comparisons in the field of paleoclimate in order to understand better the mechanisms of climate change. Tracer studies are another Earth system linkage now being explored as a tool for improving our understanding of past climates and hence improving the prediction skills of models applied to future climates. The spatial and temporal distribution of isotope species, such as 6180 in precipitation and aerosols are important paleoclimatic indicators and are generally termed "tracers". Various modelling studies have used AGCMs to investigate the link between the ice age climate and the atmospheric cycle of windblown dust material from desert areas (e.g. JOUSSAUME, 1993) and water isotope cycles (e.g. JOUSSAUME and JOUZEL, 1993). These tracer studies can provide a test for evaluating models of present-day conditions and are also useful for checking paleoclimatic inferences made from the distribution of isotopes and dust in geologic records. For example, the reasons for which the LMD (Laboratoire de M6t6orologie Dynamique, Paris) model used in the experiment by JOUSSAUME (1993) simulates only a weak increase of the global atmospheric dust content at the LGM, contrary to the observations from ice cores, might include inaccuracies of the circulation patterns, of the dust model or more likely, of the actual sources of dust. On the other hand, the overall patterns of the simulated 6180-temperature relationship for the LGM climate are practically the same as for present day, which tends to support the use of water isotopes in paleoclimatology. This is not, however, true for deuterium excess. Climate since the LGM
The period from the LGM to present has also been the subject of many studies. There is a wide range of data for this time interval (COHMAP, 1988). Moreover, the errors in dating
36
"Snapshot" simulations of past climate are relatively small (BARD et al., 1990) and the known changes in boundary conditions are simple. Since about 20 ka BP, the time of perihelion shifted from January to July (about l0 ka BP) and back to January (present day). These changes, along with changes in the tilt of the rotational axis, led after 18 ka BP to increasingly extreme solar radiation at the solstices in the northern hemisphere which reached a maximum around 10 ka BP, followed by decreasing extremes from 10 ka B P to present. Combining the changes in solar radiation due to orbital forcing with the changes in prescribed boundary conditions (the ice-sheet configuration, sea-ice extent, ocean temperature, atmospheric CO2 concentration and aerosols), paleoclimate "snapshots" have been obtained from 18 ka B P to present at 3000-year intervals for both January and July conditions (KUTZBACH and STREET-PERROTT, 1985; KUTZBACH and GUETTER, 1986). Some comparisons between the early model results and the data revealed areas of disagreements. For example, the KUTZBACH and STREET-PERROTT (1985) model shows moisture increases in the northern tropics at 15 and 12 ka BP when the data indicate relatively dry conditions. Work continues to study these areas and times of disagreements and to use them to suggest re-interpretation of the data; improvements in the model and in the boundary conditions used; and better methods for comparing the data with the model results (WEBB et al., 1987). There have been attempts to use model simulations to also explain the Younger Dryas, a temporary reversion to colder conditions at around 11-10 ka BP. The GISS (Goddard Institute for Space Studies) general circulation model (RIND et al., 1986) shows that colder North Atlantic sea temperatures produce cooling over western and central Europe in good agreement with paleoclimatic evidence. On the other hand, MANABE and STOUFFER (1988) produced two stable equilibria in a coupled ocean-atmosphere GCM using present-day boundary conditions but different initial conditions. One is similar to present, with deep-water formation in a relatively warm, salty North Atlantic. In the other equilibrium, the northern North Atlantic becomes fresher and colder and meridional overturning almost ceases. This circulation is more or less similar to that believed to have prevailed during the Younger Dryas (BROECKER et al., 1988) and was also simulated by STOCKER and WRIGHT (1991) using a more simple atmosphere-ocean coupled model (cf. discussions in Chapter 14 by PENG). BIRCHFIELD (1989) has examined similar kinds of bimodality in coupled atmosphere-ocean box models. These oceanic changes seem likely to be linked to changes in biogeochemical cycling that may, ultimately, explain the glacial-interglacial difference of about 80 ppmv in the atmospheric concentration of CO2. Some of these indicators of ocean climate show significant amplitude variability and phase relationships consistent with orbital cycles (IMBRIE et al., 1992). Around 10 ka BP, changes in the Earth's orbital parameters- increased obliquity and a change in perihelion from northern winter to northern summer- led to an increase of up to 8% in northern hemisphere summer insolation and a decrease in winter, giving an enchancement of the seasonal cycle. For that reason, early simulations of the climate at the peak of the Holocene have focussed on 9 ka BP when the insolation changes are large but there was still a substantial Laurentide ice-sheet, instead of 6 ka B P when the ice sheets were similar to present and the insolation changes smaller. More recent model simulations show that results for 6 ka BP are similar to those 9 ka BP, but the effects are less pronounced (KUTZBACH and GUETTER, 1986; MITCHELL, 1993). Experiments with both low- and high-resolution GCMs show that the increased seasonality
37
Modelling the response of the climate system to astronomical forcing at 9 ka BP resulted in continental interiors that were warmer in summer and cooler in winter than they are today. This intensified the simulated summer monsoon circulation of Africa and southern Asia, because ocean temperatures during these seasons were much the same as today (KUTZBACH, 1981; KUTZBACH and OTTO-BLIESNER, 1982; KUTZBACH and GUETTER, 1984b). This stronger monsoon flow over the northern Indian Ocean in summer generates an increased and more extensive upwelling in the Arabian sea (LUTHER et al., 1990), consistent with paleoclimatic data. In northern winter, insolation is reduced, which has a number of consequences, according to the modelling experiment of MITCHELL et al. (1988): cooling of the continents; increasing the surface pressure in the tropics; and reducing precipitation over tropical land areas. In summer, the model simulates increases in soil moisture in the northern sub-tropics because of increased precipitation, but in midlatitudes, the increase in evaporation is greater than the increase in precipitation so that soil moisture decreases (MITCHELL, 1990). The simulated climate at 9 ka BP is also sensitive to changes in other boundary conditions. MITCHELL et al. (1988) found that including an idealised Laurentide ice-sheet reduced the warming over land in July by 20%, and STREET-PERROTT et al. (1990) found that reducing surface albedo over north Africa and Arabia, as suggested by PETIT-MAIRE et al. (1988), enhanced the intensification of monsoon precipitation. It must be said, however, that both numerical experiments and observations indicate that tropical precipitation is sensitive to small changes in sea-surface temperatures (FOLLAND et al., 1986) stressing even further the importance of an accurate paleoclimatic reconstruction of these sea-surface temperatures.
The Eemian interglacial Data from the previous (Eemian) interglacial (~125 ka BP) indicate a climate significantly warmer than the peak of the Holocene (6 ka BP). The Vostok ice core records show relative maxima in atmospheric concentrations of CO2 and CH 4 during this period (JOUZEL et al., 1993). In the tropics, there is evidence of stronger monsoons (PETIT-MAIRE, 1989). The seasonal and latitudinal changes in solar radiation caused by orbital changes are approximately twice as large at 125 ka BP as at 6-9 ka BP. This is because the eccentricity of the Earth's orbit was significantly larger then (0.04), so that the Earth-Sun distance was significantly smaller (by 3%) at perihelion and because perihelion passage occurred in northern summer around 125 ka BP, whereas it occurs now in northern winter. In the northern hemisphere high latitudes, summer radiation was increased by more than 50 W m -2 (12-13%) compared to present, winter radiation was slightly decreased and the annual average insolation was increased by 3--4 W m -2. According to ROYER et al. (1984) and PRELL and KUTZBACH (1987), warmer temperature in high latitudes, decreased sea-ice extent, increased mid-continent aridity and strengthened tropical monsoons are among the simulated responses in sensitivity experiments with AGCMs using 125 ka orbital parameters. Finally, PRELL and KUTZBACH (1987) have used a GCM to investigate monsoon variability over the past 150,000 years. The agreement between simulated and observed paleoclimatic time series suggests that both orbitally produced solar radiation changes and glacial age boundary condition changes are necessary to explain the major regional features of monsoon climates at millennial or longer time-scales. Moreover, some non-linearity of response is required to produce annual mean warmings and coolings as the changes in the Earth's
38
Simulations of temporal evolution of climate orbital parameters alter the seasonal distribution of insolation substantially, but modify the total amount of radiation reaching the top of the atmosphere over the year very little.
Initiation of the last glaciation The same snapshot approach has been used to determine whether or not the simulated climate is in long-term equilibrium with the prescribed boundary conditions. For example, it has been used to see if there is a net annual increase in snow depth in high latitudes over land at the initiation of the last glaciation at isotopic stage 5d which is characterized by a large volume of ice peaking at 110 ka BP (MARTINSON et al., 1987).This was a time with particularly large changes in summer insolation in high northern latitudes, with a maximum of insolation occurring around 125 ka BP, a minimum near 115 ka BP and a further maximum near 105 ka BP; at 65~
in June, the amplitude of that variation was ~100 W m -2, the
insolation going from 540 W m -2 to 440 W m -2 in about 10,000 years (BERGER, 1979). It is therefore a particularly well-suited period to test if these changes in the insolation may have led to an extension of perennial snowfields over northern North America and northwestern Europe, with the help of the temperature-albedo feedback, the orographic and continental effects of the growing ice sheets and changes in the concentration of atmospheric CO2. ROYER et al. (1984) simulated the annual cycle of climate at 125 and 115 ka BP using a GCM with the appropriate seasonal distribution of insolation and boundary conditions similar to the present day. The change of insolation from 125 ka BP to 115 ka BP produced a cooling and an increase of soil water content over eastern Canada in the model. These are favourable conditions for the accumulation of an ice cover, provoking an abortive glaciation. OGLESBY(1990) was able to obtain an extended permanent snow cover over part of the region occupied by the major ice sheets by reducing CO2 to 200 ppmv or by prescribing an initial snow depth of 1 m over the areas of interest although his results are very sensitive to the fraction of the grid square assumed to be covered by snow. However, in a similar experiment for the same isotopic stage 5d and using the GISS GCM, RIND et al. (1989) failed to maintain snow cover through the summer at locations of suspected initiation of the major ice sheets, despite the reduced summer and fall insolation. This failure to initiate ice sheets in response to applied orbital insolation variations seems to be related to serious flaws in the sensitivity of the hydrologic cycles in the GISS A-OGCM (SANTER et al., 1993).
Conclusions In all these snapshot experiments, many of the characteristics of the paleoclimate data are reproduced, but all these results must be regarded as tentative given the uncertainty associated with the parameterization of sub-grid scale processes and the treatment of sea-ice and of the cloud feedbacks (of which even the sign may vary from model to model in global warming experiments) (CESS et al., 1989).
Simulations of temporal evolution of climate As seen in the previous section, numerical simulations in powerful computers have allowed
39
Modelling the response of the climate system to astronomical forcing the first climatic simulations to be made using atmosphere, ocean and coupled atmosphereocean general circulation models. These resolve processes whose scales extend in time from days to decades and in space from hundreds of kilometres to the circumference of the Earth. They are typically used for transient CO2 (STOUFFERet al., 1989; WASHINGTONand MEEHL, 1989; MURPHY, 1992; MANABE and STOUFFER, 1993) or equilibrium Milankovitch (MANABE and BROCCOLI, 1985b; KUTZBACH and GALLIMORE, 1988) experiments. However, these paleoclimate studies carried out with GCMs and EBMs, being equilibrium studies, do not model the time-dependent behaviour of the climate system, which is crucial if we are to understand the processes of glacial initiation and decay. Because model boundary conditions, such as ice-sheet location and size and sea-surface temperature, are prescribed from the paleoclimate data, they are therefore limited in what they can reveal about the mechanisms linking orbital forcing and climate. Models which consider the physics of processes with larger characteristic time-scales of thousands to hundreds of thousands of years can be developed by relying on the results obtained by these atmosphere-ocean general circulation models for the parameterization of processes that they cannot resolve explicitly, such as the transport by the atmospheric eddies, for example. These models which simulate the time-dependent evolution of the slowresponse climatic variables over time-scales longer than the damping times of the fastresponse variables can be constructed by an essentially inductive process (SALTZMAN,1983, 1990) or by deriving statistical-dynamical equations directly from the conservation of mass, momentum and energy (SALTZMAN,1978). Such models can be used to simulate the transient response of the climate system to any external forcing or internal perturbation. Since the publication of the historic HAYS et al. (1976) paper, a number of modelling efforts have attempted to explain the relation between astronomical forcing and climate change. Most of these modelling studies have focused on the origin of the 100-ka cycle in ice volume. These studies have been motivated by the recognition that the amount of insolation perturbation at 100 ka is not enough to cause a climate change of ice-age magnitude. Specific explanations for the large 100-ka variance generally fall into two classes. In the first case, orbital variations are essential to ice volume fluctuations, but non-linear interactions in the air-sea-ice system modify the signal. In the second case, ice volume fluctuations result from inherently non-linear interactions in the air-sea-ice system, with orbital variations serving only to phase-lock the variations at the preferred time-scales. For models where the ice volume fluctuations are primarily driven by orbital forcing, IMBRIE et al. (1984)showed that at the 23-ka and 41-ka periods, ice volume responds linearly to orbital forcing, but at 100 ka the effect is non-linear. In particular, the 100-ka power can be generated by transmission of 19-ka and 23-ka frequencies through a non-linear system (WIGLEY, 1976), producing substantial power in both harmonics and 100-ka subharmonics. Specific details of this non-linear interaction vary considerably, but many mechanisms focus on the abrupt terminations of ice ages, which occur over an interval of about 10,000 years (RUDDIMAN and MCINTYRE, 1981; HUGHES, 1987). Other approaches to the 100-ka cycle focus on non-linear interactions between accumulation/ablation, ice-sheet flow, elastic lithosphere, and viscoelastic mantle (OERLEMANS, 1982; BIRCHFIELD et al., 1982; POLLARD, 1982; HYDE and PELTIER, 1985). In particular, POLLARD (1983) coupled an axisymmetric ice-sheet model to a one-level energy balance climate model containing landocean contrasts and both north-south and east-west heat exchange. The ice-sheet model had
40
Simulations of temporal evolution of climate provisions for bedrock response and for rapid melting at the southern tip of the ice sheet due to proglacial lakes or marine incursions. Solutions were obtained by using the solar radiation variations associated with orbital forcing for the past 700,000 years; the cumulative addition of bedrock lag and ice calving improved the fit to the oxygen isotope record of ice-volume fluctuations. In a similar experiment, WATTS and HAYDER (1984) found that a strong 100ka cycle is present in the simulated ice volume, but only if a mechanism that enhances icesheet collapse is introduced. A more recent model incorporates an improved scheme for glacial isostasy which takes into account mantle viscosity (PELTIER, 1987). The latest version is able to reproduce a reasonable 100-ka cycle over the last 500 ka, but is less successful in reproducing the record of the earlier period between 800 ka and 500 ka BP. The 100-ka model cycle has a sawtooth shape reflecting the typical slow growth and rapid melting of ice sheets (PELTIER, 1987; HYDE and PELTIER, 1987). The realistic representation of the rapid termination of glacial episodes is attributed to a two-stage mechanism, which reflects the greater sensitivity of ice sheets to changes in ablation as opposed to accumulation. First, during the glacial episode itself, the stability of the ice sheet decreases as it increases in area and height. As the model climate warms at the end of the glacial period, the ablation zone becomes progressively and disproportionately larger. In the second stage, a critical level of warming is reached and a large ice-free area develops on land equator-ward of the former ice-sheet margin, in a region which is still depressed due to glacial loading. Ice from the poleward area of accumulation then begins to slide and surge into this depression and rapidly melts. The 100-ka cycle of ice-sheet build-up and decay simulated by the model is not caused directly by the eccentricity forcing (HYDE and PELTIER, 1987). Since the strongest eccentricity forcing occurs at a point in each climate cycle when the model ice sheets respond purely to precession, and because ice-sheet decay is triggered once orbitally induced warming reaches a critical level, it is considered that eccentricity phase-locks the climate response to precession. Because of the presence of additional orbital periodicities (obliquity and the lower-frequency eccentricity cycles) the phase-locking is not perfect. This model is, therefore, an example of an internally driven system, the oscillations of which are phase-locked by external forcing (cf. discussion of oscillations in the deep-ocean circulation in Chapter 14 by PENG). In contrast, results from a model incorporating ice sheets, but with different representations of the physical processes, suggest that the external orbital forcing, together with internal forcing, drives the observed 100-ka cycles. Ghil and colleagues (GHIL and LE TREUT, 1981; LE TREUT et al., 1988) modelled such internally generated glacial-interglacial fluctuations which, when orbitally forced, produce characteristic Milankovitch periods, including harmonics (e.g. 10 ka) and sub-harmonics (e.g. 100 ka). It is particularly significant that PESTIAUX et al. (1988) detected in deep-sea cores records 10.3-ka, 4.7-ka and 2.5-ka periods which were shown to be combination tones of the classical 41, 23 and 19 ka. We see therefore that the most recent ice-sheet models are capable of reproducing both the spectrum and the broad pattern of sawtooth glacial-interglacial cycles found in the geological record of the last few hundred thousand years. They indicate that the climate response to orbital forcing is non-linear and that both external and internal forcing is involved. Despite the improvements in the performance of ice-sheet models, a number of problems remain (BROEcKER and DENTON, 1990): the models are unrealistic, lacking marine ice sheets for example; they show obvious errors and they leave out many of the proposed mechanisms
41
Modelling the response of the climate system to astronomical forcing linking orbital forcing and the climate response, including changes in atmospheric composition and ocean circulation changes. Another major group of models is that of numerical dynamic models. For example, KUKLA et al. (1981) combine three orbital parameters in a time-lag bivariant model, the astroclimatic index (ACLIN) describing the link between orbital perturbations, insolations and climate. BERGER et al. (1981) provide an autoregressive multivariate spectral model where climate is a function of insolation and of the climate state 3,000 years before in order to take into account the climatic persistence due to the inertia of the slow-response parts of the climate system. IMBRIE and IMBRIE (1980) give a simple non-linear model which simulates lag between orbital variation and ice-sheet response using four adjustable parameters to tune the model to the geological record from 0 to 150 ka BP. Output from these models indicates general agreement with the geological record. However, spectral analysis of model results and marine oxygen isotope records reveals shortcomings. None of these three models reflects the observed changes in the sensitivity of the climate system to the various types of orbital forcing, or the strength of the observed 100-ka cycle. They treat the response to orbital forcing as derived from an externally driven non-linear system. PISIAS and SHACKLETON (1984) introduce an element of internal forcing to the model of IMBRIE and IMBRIE (1980) in the form of the changes in atmospheric CO2 concentration recorded over the last glacial-interglacial cycle. This modification improves the simulation of both the spectral characteristics and the phase lags between orbital forcing and ice volume changes. The different versions of the dynamic model developed by Saltzman and colleagues suggest that the 100-ka cycle is attributable to a free oscillation of an internally driven non-linear system in which external orbital forcing acts as a pace-maker. The earlier version of the model (SALTZMANet al., 1984) consists of linked dynamic equations which represent the departure of three components of the climate system from equilibrium: the mass of the deep continental ice sheets; the mass of all marine ice sheets; and the mean temperature of the world's oceans. In the total absence of orbital forcing, the model produces an approximate 100-ka cycle. In the second stage of the model experiment, forcing from the three orbital parameters is introduced to the dynamic system. In comparison with the model run without orbital forcing, the shape of the 100-ka cycle is more realistic, higher-frequency variability at the precessional and obliquity periodicities appears and agreement with the SPECMAP geological record is reasonable. In the most recent experiments, three new variables are combined in a similarly constructed dynamic model: global ice mass, atmospheric CO2 concentration, and deep-ocean warmth and salinity (SALTZMANand MAASCH, 1988). Without orbital forcing, and using a time constant of 10 ka for ice-sheet response, 100-ka cycles of ice mass and CO2 are produced as part of a natural oscillation involving deep-ocean temperature and salinity. When orbital forcing is introduced, reasonably good agreement between ice mass and the SPECMAP oxygen isotope record and between CO2 and the Vostok record of past CO2 changes is achieved. In the latest experiment with this model, changes in the spectral character of the climate oscillations recorded in the Pleistocene geological record (claimed to be real in page 31) are explored (MAASCH and SALTzMAN,1990). It is shown that, in the absence of orbital forcing, slow linear changes in the model control parameters, representing tectonic changes, can lead to abrupt changes in the climate response when a critical value is reached. When orbital forcing is added to the model, the gradual emergence of the 100-ka cycle over the Late 42
Simulations of temporal evolution of climate Pleistocene is reproduced, the higher-frequency oscillations become apparent and the cycles are phase-locked so that glacial terminations occur at the correct time. Plausible causes of the control parameter changes are suggested. These include progressive growth or erosion of the ocean floor in the North Atlantic and Pacific which could modify the effect of ice on North Atlantic Deep Water production, and slow uplift of the Tibetan Plateau and western North America which could influence the atmospheric circulation and induce cooling in some regions. This later model (SALTZMANand SUTERA, 1987; MAASCH and SALTZMAN, 1990) is particularly interesting because it is able to reproduce with some success both the 100-ka cycle and the transition from dominant 41-ka ice-volume fluctuations prior to 900 ka BP to dominant 100-ka ice-volume fluctuations after 900 ka BP. The latter transition may also reflect the existence of "multiple equilibrium" states, whereby slowly changing boundary conditions can cause an abrupt transition in the climate state (e.g. NORTH and CROWLEY, 1985). An entirely different approach to modelling the low frequency climate variability involves the hypothesis that glacial-interglacial fluctuations are a consequence of non-linear "internal" interactions in a highly complex system (NICOLIS, 1984; SALTZMAN, 1985). As a simple example of this concept, it can be demonstrated that low-frequency (red noise) variance can be produced when white noise forcing, from a time series with a short-response time, is applied to another system with a relatively long response time. For example, variable atmospheric winds on the sea surface can create sea-surface temperature anomalies on a longer time-scale (FRANKIGNOUL and HASSELMANN, 1977; HERTERICH and HASSELMANN, 1987). From this perspective, a low-frequency peak (e.g. 100 ka) in the 6180 record would be generated via non-linear interactions in the air-sea-ice system. Theoretical studies suggest that the slope of a variance spectrum for such "stochastically driven" ice-volume fluctuations might lie b e t w e e n - 1 a n d - 2 , depending on the interactions involved (HASSELMANN, 1976; LEMKE, 1977). In fact, log-log plots of the variance spectrum of the 6180 record yield a red noise spectrum with a slope o f - 2 (KOMINZ and PISIAS, 1979) between periods of 100 ka and 12 ka. The trend is consistent with that predicted by white noise forcing from time-scales shorter than 12 ka. Finally, BROECKER et al. (1985, 1988) have postulated that "internal" glacial-interglacial fluctuations would not result from ice-sheet non-linearities but from instabilities in the ocean-atmosphere system (see also Chapter 14 by PENG). For example, ROOTH (1982) proposed that the Younger Dryas cold episode, which chilled the North Atlantic region from 11 ka to 10 ka BP, was initiated by a diversion of meltwater from the Mississipi drainage to the St Lawrence drainage system. The link between these events was postulated by BROECKER et al. (1989) to be a turnoff, during the Younger Dryas cold episode, of the North Atlantic's conveyor-belt circulation system which currently supplies an enormous amount of heat to the atmosphere over the North Atlantic region. This turnoff was attributed to a reduction in surface-water salinity, and hence in density, of the waters in the region where North Atlantic deep water now forms. Results from a zonally averaged oceanatmosphere model show also that the Atlantic thermohaline flow is sensitive to anomalous freshwater input (STOcKERand WRIGHT, 1991; STOCKER et al., 1992). However, data from deep-sea cores (DUPLESSY et al., 1992) and the model by HOVINE (1993) suggest that this drop of the surface-water salinity results from a reduction of poleward advection of saline sub-tropical water and not from input of ice-sheets meltwater.
43
Modelling the response of the climate system to astronomical forcing Transient response of a 2-D climate model to astronomical forcing Description of the 2-D LLN model
Although the models described in the previous section are based on parameters which are considered to be physically plausible, they are all highly simplified. None of them can be considered as a fully realistic representation of the whole climate system. Nor is any capable of explaining precisely how the orbital forcing produces dominant 100-ka cycles in marineand land-based geological records from so many different parts of the world. What these models do confirm is that the response to orbital forcing is non-linear and that it involves some element of internal forcing. Whether the external orbital forcing drives the internal forcing, phase-locks the oscillations of an internally driven system, or acts as a pace-maker for the free oscillations of an internally driven system remains, however, an open question. Nevertheless, all these models clearly underline the need for simulations made with a model of the climate system where the fast-response parts (atmosphere and upper ocean) are coupled to the slow-response ones (ice sheets, underlying bedrock, deep ocean), taking into account the most important feedbacks as the albedo-temperature feedback and those involving the greenhouse gases. As a consequence, the discussion of the response of the climate system to orbital forcing requires the construction of a physically realistic model of the time-dependent behaviour of the coupled climate system, including the atmosphere, the oceans, the cryosphere, the lithosphere and the biosphere. Unfortunately, such a model is likely to be too complex, given the constraints of computing power and speed and our lack of knowledge in the biogeochemistry of the climate system, in particular. This is why a transient simulation of global change at the thousands of years time-scale with more simple 2-D coupled models of the climate system is now tentatively used for testing the astronomical theory of paleoclimates (BERGER et al., 1990a,b; DEBLONDE and PELTIER, 1990). At that time-scale, plate tectonics, mantle convection, mountain building and Sun evolution are kept constant over the last glacialinterglacial cycles. The slow response parts of the climate system, such as the cryosphere and the lithosphere, are included in addition to the atmosphere and the ocean. As suggested earlier (BERGER, 1976b, 1979), the time evolution of the latitudinal distribution of the seasonal pattern of insolation appears to be the key factor driving the behaviour of the climate system where the complex interactions between its different parts amplify this orbital perturbation, suggesting that time-dependent coupled climate models could be used to test whether or not the astronomical forcing drives the long-term climatic variations. Such time-dependent climate models must therefore be forced only by the astronomical variations of insolations for each latitude, the so-called boundary conditions used in equilibrium atmospheric general circulation model experiments (ice-sheet size and area, sea surface temperature, albedo .... ) being all generated by the climate model itself. Therefore, in order to simulate the waxing and waning of the ice sheets over the last glacial-interglacial cycle, the models have to consider all parts of the climate system and the main physical processes and interactions concerned with the formation and melting of the ice sheets. At the same time, each of the sub-systems must be given a degree of complexity which could reflect its relative role in the real climate system within the frame of a Milankovitch experiment. This means, in particular, that the models must parameterize the evaporation and the transport of 44
Transient response of a 2-D climate model to astronomical forcing
water to the high polar latitudes where part of it falls as snow to build up the major ice sheets. The heat balance at the surface of the ice sheets, their dynamics and the bedrock adjustment to the ice loading will then govern their evolution. The land, ice sheets, ocean and sea-ice surfaces must interact with the atmosphere, which requires the surface processes to be accounted for adequately. A particular version (designated by LLN, Louvain-la-Neuve) of such models, which links the northern hemisphere atmosphere, ocean mixed layer, sea ice, ice sheets and continents, has been validated for the present-day climate (GALLI~Eet al., 1991), but in a first approach the chemical Earth does not interact with the physical climate system and only a few biological processes are considered. All principles and parameterizations which aim at simulating the interactions and processes were taken from the literature and the values of all the constants used were kept within the range of their physical uncertainty. In fact, such a model was designed primarily as a tool for learning how to couple the components of the climate system with such different characteristic time-scales, for understanding how the non-linear coupling will impact on the propagation, through the entire Earth-Climate system, of a change once introduced, and hopefully to test whether or not seasonal and latitudinal changes in insolation at the astronomical time-scale can lead to significant changes in the modelled climate variables. It is a latitude-altitude model. In each latitudinal belt, the surface is divided into at most five oceanic or continental surface types, each of which interacts separately with the sub-surface and the atmosphere. The oceanic surface types are ice-free ocean and sea-ice cover, while the continental surface types are the snow-covered and snow-free land and the Greenland ice sheet. The atmospheric dynamics is represented by a zonally averaged quasi-geostrophic model, which includes a new parameterization of the meridional transport of quasigeostrophic potential vorticity and a parameterization of the Hadley sensible heat transport. The atmosphere interacts with the other components of the climate system through vertical fluxes of momentum, heat and water vapour. The model explicitly incorporates detailed radiative transfer, surface energy balances, and snow and sea-ice budgets. The vertical profile of the upper ocean temperature is computed by a mixed layer model which takes into account the meridional convergence of heat. Sea ice is represented by a thermodynamic model including leads and a new parameterization of lateral accretion. Simulation of the present climate shows that the model is able to reproduce the main characteristics of the general circulation (GALLI~E et al., 1991). The seasonal cycles of oceanic mixed layer, sea ice and snow cover are also well reproduced. Sensitivity experiments show the importance of the meridional sensible heat transport by the Hadley circulation in the tropics, the seasonal cycle of the oceanic mixed-layer depth and sea-ice formation in latitude bands where the average water temperature is above the freezing point. The atmosphere-ocean model was asynchronously coupled to a model of the three main northern hemisphere ice sheets and their underlying bedrock in order to assess the influence of several factors (processes and feedbacks), including snow surface albedo over the ice sheets, upon ice-age simulations using astronomically derived insolation and CO2 data from the Vostok ice core as forcings (BERGER et al., 1990a,b; GALLI~Eet al., 1992). The ice-sheet lithosphere model is latitude and time dependent. The equation for ice thickness represents the conservation of the ice mass and is a vertically integrated, non-linear diffusion equation computed along a meridian. The ice diffusivity depends on the ice thickness 45
Modelling the response of the climate system to astronomical forcing and the ice slope. The lateral ice flow is represented by a diffusivity term calculated for each latitude by assuming that the east-west profile of the ice sheet is double parabolic. This parabolic shape has been calibrated against the 18-ka B P ice sheet. The net mass balance is the difference between the calculated local snow precipitation and the local ablation computed from the balance of the heat fluxes at the snow or ice surfaces. The isostatic rebound (i.e. the bedrock-surface elevation responding to the changing ice load) is calculated using a time-dependent diffusive equation of the asthenosphere along latitude. Over the ice sheets, the model includes the elevation-desert feedback which reduces the accumulation to low values as the ice sheet grows high. The snow albedo is dependent on the surface temperature and the snow age as in DANARD et al. (1984). This snow aging-albedo feedback is based on the fact that during daytime, the heat applied to the snow cover by radiative processes is used for recrystallization processes and subsequently for a decrease in the many facets of the minute crystals of fresh fallen snow. Thus the scattering processes in the uppermost layer of the snow are diminished, and radiation can penetrate deeper into the snow where increased absorption can take place. This results in a general decrease of the reflected portion of the shortwave solar and scattered radiation. Since metamorphism is an irreversible process, a snow cover which is once undergoing a change by metamorphism cannot recover during the night. The decrease in albedo due to metamorphism thus results in an overall decrease in the albedo of the snow cover from day to day (DIRMHIRN and EATON, 1975). It must be noted, however, that despite a very low accumulation rate, current snow albedo over central Antarctica is very high throughout the year because of low temperatures. This observation would possibly be in conflict with the model assumption if this present-day observation is confirmed for longer time-scale. This is why, in order to take into account high snow albedo at low surface temperatures, the snow albedo in our model is maintained at its maximum (0.85) for daily mean surface temperatures lower than -10~ Simulation of the last 200 ka
The model was first run with ice-sheet feedback by forcing it only with the astronomical insolation over the past 122 ka (BERGER, 1978) keeping the CO2 concentration at the Eem level (~270 ppmv). The atmosphere-land-ocean seasonal model is run every day during 20 years for reaching quasi-equilibrium; the output is then used to force the ice-sheets model which is run with a time step of 1 year for 1,000 years. Sensitivity tests have confirmed the adequacy of such choices. Large variations of ice volume are simulated between 122 and 55 ka BP, with a rapid latitudinal extension of the North American and Eurasian ice sheets starting at 120 ka BP. The model simulates a maximum ice volume of 40 x 106 km 3 at roughly 20 ka BP and a total deglaciation as well, this simulation of both the glaciation and deglaciation being a crucial test of the efficiency of the model. The simulated evolution of the three northern ice sheets is generally in phase with geological reconstructions. The major discrepancy between the simulation and observations lies in the temperature variations and in the ice-sheet extent, a discrepancy linked to an overestimation of the CO2 concentration which was assigned an interglacial value throughout the run. A set of experiments therefore addresses the effect of CO2 on the climate of the last glacialinterglacial cycle. This experiment made by forcing the model with both insolation and CO2 variations over the last 122 ka (BARNOLA et al., 1987) significantly improved the tempera-
46
Transient response of a 2-D climate model to astronomical forcing
ture results and the ice-volume reconstructions obtained in the insolation-only experiment (GALLI~E et al., 1992). The simulated total ice-volume deviation from present-day value (assumed to be 30.5 x 106 km 3, that is, 27.9 x 106 km 3 for Antarctica and 2.6 x 106 km 3 for Greenland; HUGHES et al., 1981) is displayed in Fig. 6 as a function of time compared to the variation of the global seawater oxygen isotopic ratio given by LABEYRIE et al. (1987) and DUPLESSY et al. (1988). The latter values are scaled and plotted such that their maximum corresponds to the deviation from present-day of the LGM total ice volume assumed to be 48.6 x 106 km 3, as reconstructed by MARSIAT and BERGER, 1990). The simulated deviations are obtained by adding the northern hemisphere ice-volume changes simulated by the model for each of the individual ice sheets (Eurasia, Greenland, North America) and the changes in Antarctica reconstructed as follows. We assumed (1) that the Antarctic ice volume at 122 ka BP and from 6 ka BP to the present was the same as now (J. OERLEMANS and D. RAYNAUD, personal communication, 1987); (2) that 18 ka ago, it was 9.8 x 106 km 3 larger than today (HUGHES et al., 1981); and (3) that intermediate values are given by linear interpolation. Assumption (2) seems to be in agreement with the results obtained by HUYBRECHTS (1990) from a three-dimensional ice-sheet model. The main characteristic of Fig. 6 is the similarity between the reconstructed and the simulated global ice volumes, except for variations with time-scales shorter than 5 ka and for an overestimation of the calculated ice volume during isotopic stage 3 when compared to LABEYRIE et al. (1987). Large ice-volume oscillations are simulated between 122 ka BP and 55 ka BP; in reasonable agreement with deep-sea records, two stadials are culminating at 110 ka BP and 90 ka and isotopic stage 5a is followed by a dramatic expansion to midWtirm ice-volume values between 75 ka and 60 ka BP. The deglaciation is abrupt both in reconstruction and in simulation. The ice volumes for each ice sheet simulated by the LLN model (BERGER et al., 1990a; GALLI~Eet al., 1992) are also in good agreement with independent reconstructions made from proxy data by MANGERUD (1991) and BOULTON et al. (1985). At 19 ka BP, the simulated temperature of the northern hemisphere is 3.4~ colder than the present day simulated value, and the simulated total ice-volume deviation is 53 x 106 km 3. An experiment (called the 200 ka experiment) with the LLN model was undertaken in which the model was forced by astronomically driven insolations and by prescribed CO2 concentrations over the last 200 ka (GALLI~Eet al., 1993), in order to assess the ability of the model to sustain glacial-interglacial cycles. At the time this experiment was done, the Vostok ice core (BARNOLA et al., 1987; RAYNAUD et al., 1993) did not provide a reconstruction of CO2 concentration variations before 150 ka BP (data are now extending to 220 ka BP; JOUZEL et al., 1993), so that the model was forced by CO2 concentrations adapted from SHACKLETON et al. (1992). The simulation starts by assuming that the ice sheets are melted at 200 ka BP, because this time corresponds to an interglacial in marine d 180 records. Two glacial maxima comparable in amplitude are simulated at 134 and 15 ka BP as found in the marine d180 records (e.g. IMBRIE et al., 1984; see Fig. 7). The phase lags between the insolation minima at 65~
and ice volume maxima are 6, 5, 6, 11 and 8 ka, respectively, for the ice volume
maxima at 180, 134, 109, 59 and 15 ka BP. A further comparison of the results of the 200 ka experiment with the SPECMAP record is made in Fig. 7. The variations correlate well and a spectral analysis of both time series gives spectral peaks of similar amplitude for the 100-, 41-, 23- and 19-ka periods. The correct 47
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48
Transient response of a 2-D climate model to astronomical forcing
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Fig. 7. (a) Upper panel: variations over the last 200 ka of (i) the simulated ice volume of the northern hemisphere (solid curve) (GALL~E et al., 1993), and (ii) 6180 variation as reconstructed in the SPECMAP time series (short-dashed curve) (IMBRIEet al., 1984; MARTINSON et al., 1987). The forcing used in the simulation is the insolation variation at the top of the atmosphere and the CO 2 variation adapted from SHACKLETONet al. (1992). (b) Lower panel: spectral amplitude in the Thomson multitaper harmonic analysis of (i) the simulated ice volume of the northern hemisphere for the 200 ka experiment (solid curve), and (ii) 6180 variation over the last 200 ka as reconstructed in the SPECMAP time series (short-dashed curve). 130 ka BP and a stable interglacial with high sea-level lasting from about 127 ka BP to 115 ka BP. This duration agrees well with geological evidence for the last interglacial (MOLLER, 1974), whereas a major weakness both of the S P E C M A P record and of previous model simulations (e.g. IMBRIE and IMBRIE, 1980; BERGER et al., 1981) is precisely their inability to depict the several thousand-year long stable interglacials.
49
Modelling the response of the climate system to astronomical forcing Finally, sensitivity tests to the CO2 forcing reconstructed either from BARNOLA et al. (1987) or from SHACKLETON et al. (1992) suggest that in the LLN model, the timing of the simulated ice-volume variations is more tightly locked to the timing of insolation variations than to the timing of CO2 variations. Moreover, the simulation tends to support the new extended geological time-scale proposed by JOUZEL et al. (1993) where the maximum of CO2 occurs closer to 130 ka BP than in BARNOLA et al. (1987). This chapter cannot provide a comprehensive summary of all relevant modelling efforts in dynamical modelling, but it is worthwhile to document the model of DEBLONDE and PELTIER (1991a,b) which differs rather substantially from the LLN model in the mix of ingredients that are proposed to account for the same phenomenon. This model is a global one-level seasonal energy balance model which differentiates land from sea in a geographically realistic way and in which multiple ice sheets evolve in specific geographic subdomains in response to the applied insolation anomalies. The model incorporates the influence of glacial isostatic adjustment, of elevation-desert feedback, and a realistic surface topography. The hydrological cycle is driven by a precipitation field that matches the presentday precipitation within each of the cryospheric sub-domains and the ice-sheet mass balances are computed as monthly averages on the basis of a geographically specific annual cycle that is diagnostically determined from the ice sheets. When it is initialized with ice free (except Greenland) northern hemisphere conditions beginning 124 ka BP, this model successfully predicts the observed locations and the maximum thickness achieved by both the North American and the Northwest European ice complexes. With the same minimal set of interacting physical ingredients as were employed in the simpler model of DEBLONDE and PELTIER (1990), however, the termination that commences near 18 ka BP is not predicted. Therefore, without additional feedback loops, the model is unable to explain the deglaciation process fully. A feedback that might achieve the desired effect in this regard is that associated with atmospheric dust. Ice cores and deep-sea sedimentary cores show that late glacial episodes are characterized by dry and dusty conditions for many thousands of years prior to major deglaciation events. When the albedo of the ablation zones in the Deblonde-Peltier model is modulated in a way implied by the dustiness records, complete deglaciations are then predicted to occur. In the LLN model, an impact of "ice-aging" is invoked to effect a similar modulation of albedo, and this, too, affects the desired collapse of the ice sheet in response to the Milankovitch anomalies. For distinguishing which, if either, of these mechanisms are correct, it would appear that the only acceptable course is to describe more of the physics explicitly as for example, the effect of aerosols and changes in atmospheric aerosol burden, on radiative transfer through the atmosphere. The feedback mechanisms
One important feature of the LLN model is that it simulates both the glaciation and deglaciation of the last two climatic cycles. This is due to a number of feedbacks introduced in the model. Although these represent only a sub-set of all the feedbacks acting in the climate system, it is useful to analyse their relative contributions. This is done for the 122 ka experiment (BERGER et al., 1992, 1993c) and the results are described in the following sections where all the processes which play a fundamental role in the simulation are given.
50
Transient response of a 2-D climate model to astronomical forcing Entering the glaciation At 60~
insolation starts to decrease at 133, 127 and 121 ka BP for March, June and Sep-
tember, respectively. Summer insolation therefore peaked around 123 ka BP at high northern latitudes. The minimum is reached 11-12 ka later. For June, insolation decreases from 545 W m -2 to 440 W m -2, a decrease of almost 20%. These latitudes and months are characterized by a strong precession signal whereas in December obliquity dominates the spectrum at this latitude (insolation maxima and minima are alternatively 147, 129, 115 and 88 ka BP). Each time this type of decrease in insolation occurs, positive feedbacks amplify the response of the climatic system to such changes in the external forcing, an amplification which leads to ice sheets accumulating not only up to the time of minimum insolation but continuing to accumulate until a few thousand years later (4-5 ka) due to the inertia of the slow-response part of the system. During these latter periods, negative feedbacks progressively slow the build-up of the ice sheets until they begin to retreat and melt following the ice maximum. When insolation decreases, surface temperature decreases which delays the melting of snow fields in high latitudes. At the same time, taiga is replaced by tundra which increases the albedo of the vegetated surface covered by snow. Both the snow fields and tundra are therefore leading to an increase of the surface albedo creating a positive feedback. This is reinforced by the subsequent decrease of water vapour content of the atmosphere that results in a decrease in the downward infrared radiation at the surface. But this cooling is also responsible for decreases of the upward infrared, of the latent heat and of the sensible heat fluxes at the surface which feedback negatively on surface temperature. During this initiation phase, which lasts roughly 4 ka, the zonal mean cooling at the surface leads to a cooling in the atmosphere which, with the insolation decrease, impacts the icesurface energy budget. The ice-surface temperature does not reach the melting point, even in summer. This means that we have a net accumulation at the surface, ablation being suppressed. As a consequence, the ice sheets are growing which depresses the lithosphere below. With the altitude of the ice sheets increasing, the temperature at their surface decreases (a positive feedback) which progressively decreases the snowfall (a negative feedback) and finally stops the growth of the ice sheet. At the same time, the ice sheets extend to the south. Because of the continentality effect, snowfall at the top of the ice sheets in the interior of the continents decreases (a negative feedback), slowing down the southwards motion of the southern front of the ice sheets. Finally, the maximum volume of ice is reached, at 110 ka BP, 4 ka later than the minimum of insolation.
The deglaciation process As insolation had already started to increase 4 ka before the ice maximum, this increase starts to be important at 110 ka B P, particularly at the southern edge of the ice sheets which begin to melt. At the same time, the decreased snow fall triggers the "snow ageing" process which is more efficient in regions of the ice sheets where the temperature is above -10~ This significantly decreases the albedo of both non-melting and melting snow cover, mainly to the south. In the meantime, snow accumulation has remained positive over the northern part of the ice sheets creating a N-S flux of ice within the ice sheets. At the southern edge,
51
Modelling the response of the climate system to astronomical forcing melting is faster than ice flow and isostatic rebound is not fast enough to level up the ice sheet which could prevent future net ablation. North, the ice sheets remain high allowing the North to South flux of ice to continue to be efficient. As a consequence, the ice-sheet volumes decrease, the height of the ice sheets decreases, temperature at their surfaces increases which increases the global ablation. This leads to a decrease of the zonal surface albedo and a further replacement of tundra by taiga which feedbacks positively on the albedo decrease, directly and by reducing the albedo of the continental surfaces covered by snow. This leads finally to a minimum of ice volume reached about 5 ka later than the insolation maximum.
The C02-water vapour-albedo feedback mechanisms at the LGM Although uncertainty still surrounds the mechanisms by which CO2 concentrations have varied over the last interglacial-glacial cycle, there is little doubt that such changes did occur. Modelling evidence supports the role of CO2 as a positive feedback mechanism. Using an energy balance model, HARVEY (1989) and HOFFERT and COVEY (1992), for example, find that the decrease in atmospheric CO2 at the LGM enhanced global cooling by up to 1.5~ GENTHON et al. (1987) estimate that the direct radiative effect of the CO2 changes over the last glacial-interglacial cycle, as recorded in the Vostok core, is 0.6~ The direct effect is amplified by various feedback mechanisms such as the water vapour feedback. Resuits from a multivariate analysis of the Vostok CO2 and temperature records, using a range of amplification factors, imply that the CO2 changes could account for 27-85% of the observed temperature variance (GENTHON et al., 1987). But analyses of air bubbles in the Vostok and Byrd cores, also reveal changes in the atmospheric concentration of methane (CH4). As a greenhouse gas, CH 4 has a direct radiative effect, but also has indirect photochemical effects involving ozone and water vapour. Allowing for both direct and indirect effects, CHAPPELLAZet al. (1990) estimate that CO2 and C H 4 changes may have accounted for about 2.3~ of a total global warming during the last glacial-interglacial transition of 4.5 +_ 1.0~ Another study, based on multivariate analysis of the Vostok records, suggests that the total contribution of greenhouse gas fluctuations to the regional warming seen in the Vostok temperature record is 3~ or 50 _ 10% (LORIUS et al., 1990). From these two studies, it follows that CO2 and CH 4 may be responsible for 50% of the observed glacial-tointerglacial warming, methane alone accounting for 10%. Finally, new results on the change of N20 levels during the last deglaciation indicate that N20 has also contributed significantly to the change in radiative forcing (up to 15% of that of CO2, i.e. as much as CH 4, LEUENBERGER and SIEGENTHALER, 1992). A similar analysis of the relative importance of the feedback mechanisms involving CO2, water vapour and albedo in the LLN experiments was therefore relevant. The comparison of the results obtained from the LLN transient experiments using the Milankovitch and the Milankovitch + CO2 forcings shows that, at the Last Glacial Maximum, the long-term CO2 changes are responsible for roughly 50% of the temperature change and 30% of the icevolume change. In an attempt to understand the role of the temperature-albedo feedback and the importance of the greenhouse gases (water vapour and CO2), several sensitivity experiments have been made (GALLI~Eet al., 1992; TRICOT, 1992; BERGER et al., 1993b). In particular, the physical processes responsible for the cooling simulated at the LGM under the forcing of both insolation and CO2 were investigated with a 1-D radiative convective 52
Transient response of a 2-D climate model to astronomical forcing
(RCM) climate model (TRICOT, 1992). A full description of this RCM, its validation and sensitivity tests are given in TRICOT (1992) and BERGER et al. (1993b). In particular, when the CO2 concentration is doubled (from 330 ppmv to 660 ppmv), the instantaneous perturbations of the net radiative budget (before the action of feedbacks) are estimated to be 3.72 W m -2 at the tropopause and 1 W m -2 at the surface. At equilibrium, the temperature increases by 1.8 K at the surface and in the troposphere and decreases in the stratosphere above 20 km. The sensitivity of the RCM to CO2 change is thus very similar to that calculated in other sensitivity studies using RCMs with the same basic assumptions (e.g. RAMANATHAN, 1981). Without allowing the water vapour feedback to operate, the warming is reduced to 1.2 K. As the purpose here is to quantify the relative contribution of each of the main climatic feedbacks, some improvements in the LLN model were first made by TRICOT (1992) in such a way that the sensitivity of this modified version, designated as LLN1, to changes in trace gas concentrations will be closer to the sensitivity of the RCM itself. These improvements concern mainly the radiative part of the model, involving new infrared and solar radiation schemes, and an explicit computation of the stratospheric temperature. Climatological data about cloud and aerosols also have been revised. LLN1 has been validated for the presentday climate. Its sensitivity to a doubling of CO2 concentration (AT = 1.97 K) is similar to the sensitivity of the original version of the LLN model (AT = 2 K). The cooling at the LGM simulated by LLN1 using the surface boundary conditions calculated by the LLN transient simulation, the seasonal cycle of insolation at 18 ka BP and a CO2 concentration of 194 ppmv amounts to 4.5 K. This cooling is associated with an increase of the planetary albedo from 31 to 32.6%, an increase of the surface albedo from 16.2 to 19.3% and a decrease in the annually (averaged vertically) integrated water vapour concentration from 2.44 to 1.99 g cm -2. At the LGM, in addition to the insolation and CO2-concentration variations, the hemispherically averaged changes in the surface albedo and in the vertical distribution of water vapour are available as part of the LLN1 model diagnostics. These changes were inserted one by one or in combination into the RCM. All these sensitivity tests lead to the following conclusions for the northern hemisphere: (1) The cooling using only the astronomical forcing but, allowing for the water vapour feedback, amounts to 3~ 67% of the 4.5~ cooling resulting from both the astronomical and CO2 forcings. It must be stressed that what we call astronomical forcing includes both the change in insolation and the consequent changes in surface and planetary albedo. (2) If the CO2 concentration is kept fixed to its interglacial level (330 ppmv), the astronomical-albedo forcing (AA) without the water vapour feedback (WVF) explains 60% of the 3~ cooling, the WVF being therefore responsible for 40% of the total cooling in this Milankovitch alone experiment. (3) In the astronomical + CO2 experiment, the direct effect of these forcings (i.e. without the WVF) explains 60% (2.7~ of the 4.5~ cooling. As in (2), the WVF is therefore responsible for 40% of the cooling. If we discriminate between the AA and the CO2 contribution (CO2), we can see that without the WVF, AA explains 40 of the 60% of the total cooling. The contributions to the WVF (40% of the total cooling) are 27% for AA and 13% for C O 2.
(4) In this astronomical + C02 cooling, it may also be interesting to analyse the proportion
53
Modelling the response of the climate system to astronomical forcing which is due to water vapour for each sub-experiment. Considering only the AA, the WVF is responsible for 27 of the 67% of the global cooling, the remaining 40% is the direct effect of AA. In the CO2 alone experiment, the WVF explains 13 of the 33% of the global cooling, the direct effect of CO2 accounting for the remaining 20%. Other feedbacks and future work
A number of improvements to the Louvain-la-Neuve model are under way, such as coupling the climate and ice-sheet models with deep-ocean and global carbon-cycle models and including a better chemical composition of the atmosphere. The importance of aerosols in particular is confirmed by the Vostok records which provide information about changes in the aerosol content of past atmospheres (LEGRAND et al., 1988). The atmospheric loading of aerosols from marine and terrestrial sources is generally greater during colder periods, such as 100-15 ka BP, than during warmer periods, such as 130 ka and 10 ka BP. The increased loading is related to increases in both the sources and transport of aerosols during glacial episodes and has a positive feedback effect. The particles reflect radiation back to space, thus enhancing surface cooling. Using an energy balance model, HARVEY (1989) estimates that the increased loading associated with the Last Glacial Maximum may have caused an additional cooling of 2.2~ LEGRAND et al. (1988) have examined the potential causes and effects of changes in the concentration of marine aerosols. Dimethylsulphide (DMS) is produced by planktonic algae and oxidizes in the atmosphere to form a sulphase aerosol called marine non-sea-salt sulphate (CHARLSONet al., 1987). Initial analyses of the data suggested that the concentration of marine non-sea-salt sulphate in the Antarctic atmosphere increased by 20--46% during the Last Glacial Maximum (LEGRANDet al., 1991). The peak concentrations of non-sea-salt sulphate in the Vostok core are believed to be due not only to more efficient poleward atmospheric transport, but also to increased productivity. The record shows a strong spectral peak at 21 ka and a weaker 42 ka peak. The existence of these peaks at the orbital frequencies, and the correspondence with the Vostok CO2 record, suggests a change in the surface ocean circulation which would lead to increased marine productivity and, hence, to increased DMS production and a reduction in atmospheric CO2 concentrations. It has been suggested (CHARLSONet al., 1987) that increased DMS production by marine microorganisms leads to increased atmospheric concentrations of cloud condensation nuclei (CCN). The increased CCN concentrations in turn lead to an increase in cloud albedo, thus more radiation is reflected back to space. Since increased marine productivity leads to surface cooling, the proposed feedback effect would be positive during glacial episodes. Assuming that the proposed feedback mechanism is plausible, and that concentrations of CCN increase in direct proportion to marine non-sea-salt sulphate, LEGRAND et al. (1988) have estimated that a 46% increase in CCN would increase cloud albedo by about 0.03 and that the direct radiative effect of this increased albedo would cause an additional surface cooling of 1~ A number of potential feedback effects involving changes in atmospheric composition over glacial-interglacial cycles have thus been identified. These range from highly plausible (CO2) to highly speculative (ocean productivity, cloud albedo) mechanisms. In terms of
54
Future climates under astronomical forcing helping to explain the links between orbital forcing and climate response, all the proposed feedbacks operate in the required direction (they are positive feedbacks amplifying the initial forcing) and on the required scale (global or hemispheric). On the basis of multivariate analyses, LORIUS et al. (1990) conclude that three of these mechanisms (changes in the concentration of greenhouse gases, aerosol loading and marine non-sea-salt sulphate), together with solar insolation and ice-volume changes, are sufficient to explain over 90% of the variance in the Vostok temperature record. Although the results presented here may be considered only preliminary, they confirm the results of many of the simpler and physically less realistic models discussed in the section on simulations of temporal evolution of climate. Orbital forcing is confirmed as a highly plausible cause of the Quaternary glacial-interglacial cycles. The modelling evidence also implies that internal processes and feedbacks, such as ice-sheet dynamics and changes in atmospheric composition, play an important part in the climate response.
Future climates under astronomical forcing Simulation of the waxing and waning of the ice sheets over the past 1 million years seems to indicate that the climate is sensitive to the orbital parameter variations, or at least that these are able to trigger feedbacks which then induce significant climatic variations at that timescale. No general circulation model has been able to generate such long-term climatic variations, because the complexity of the different parts of the climate system themselves and of their mutual interactions requires considerable computer time and space. Moreover, the nonlinearities in the climate system can easily introduce spurious response (which can be masked sometimes by compensating errors) if one process is given too great a weight compared to the others (including those which are missing). Simplified 0-D and 1-D models have thus largely been used to simulate these long-term climatic variations. The problem with such a basic approach is that it is possible to obtain almost any desired sensitivity by tuning procedures which involve parameterizations not tied firmly to first principles (although their general formulation derives sometimes directly from such first principles). The LLN 2-D climate model has however reproduced fairly well the seasonal and latitudinal distributions of surface air temperature and of ice volume for both present day situation and for the last 200 ka. In particular, a good agreement was found between the low frequency parts of the simulated long-term climatic variations and of the most recent reconstructions of sea-level and ice-volume changes from geological observations; the 100-ka cycle was well reproduced by the model as well as the timing of the glacial maxima and the length of the interglacials; and its sensitivity to greenhouse gases (water vapour and CO2) is well within the range of GCMs' results. Such a validation allows this model to be used for predicting future climates. Although climate models have been widely used to explore the reality of orbital-climate relationships and the potential mechanisms linking cause and effect, comparatively few model studies have attempted to predict future climate on the basis of orbital variations. In a paper for studying the stability of repository sites for nuclear waste disposal, BERGER et al. (1991) have identified seven statistical/dynamical models and time-dependent ice-sheet models
55
Modelling the response of the climate system to astronomical forcing which do attempt such a prediction. The principal characteristics of the seven models are also presented in GOODESS et al. (1992). Climate reconstructions for the last 120 ka and projections for the next tens to hundreds of thousands of years have been computed and, despite some shortcomings, the models provide a reasonably coherent guide to the range of future climate change caused by periodicities in the orbital parameters. Although there are some discrepancies between the future sequences of climate predicted by the models, the major changes are common to all seven studies. These models suggest that, setting aside the potential for anthropogenic change, the world's climate, under the astronomical forcing alone, should soon begin a slow deterioration towards glacial conditions. Oscillatory cooling is expected to continue with progressively colder episodes at about 5 ka, 23 ka and 60 ka after the present-day. The final extreme glaciation around 60 ka from now, is expected to rival the intensity of the LGM and should be followed by a gradual shift towards warmer conditions. All the models indicate that climates as warm as the present day are relatively rare; the world is not expected to return to conditions matching the Holocene thermal optimum before 120 ka in the future. Preliminary results from the LLN climate model, forced by insolation variations only (i.e. that the CO2 concentration is kept fixed at its pre-industrial level), indicate also that in the absence of enhanced greenhouse warming, the next glacial maximum in the northern hemisphere will happen about 55 ka AP (after present). The principal features of the simulation for the next 80 ka AP are shown in Fig. 8 (BERGER et al., 1991); the long-term cooling trend which began 6,000 years ago will continue for the next 5,000 years; this first slight minimum will be followed by a stabilisation at around 15 ka AP, by a cold interval centred at
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Fig. 8. The future ice volume in the northern hemisphere resulting from the astronomical forcing alone without anthropogenic disturbances (full line) and assuming no Greenland ice sheet today (dashed line) (GALLC.E,1989; BERGERet al., 1991). The range between these two curves may be assumed to provide a range of uncertainties related to the approximations made in the model, assuming that the greenhouse gas concentrations are constant and equal to their pre-industrial values. Ice volume increases downward in this figure.
56
Future climates under astronomical forcing 25 ka AP and finally by a major glaciation at 55 ka AP. This tendency for our natural climate to be steered astronomically towards the next glacial maximum leads to an average cooling of 0.01 ~ per century. At the human time-scale, this is negligible when compared to the 1-5~
warming expected from the increase of greenhouse gas concentrations in the
course of the 21st century (HOUGHTON et al., 1990, 1992). This is not the case for the related sea-level change. The build up of 27 • 106 km 3 of ice in the northern hemisphere at 55 ka AP would indeed be responsible for a eustatic sea-level drop of about 70 m which represents a falling of the sea-level at an average rate of 10 cm per century. This is the same order of magnitude as the 15 cm rise over the past century, but in the reverse direction. If we assume that this long-term trend in equivalent sea-level fall is already underway since the Holocene climatic peak 6,000 years ago, the absolute rise over the past century, whatever its cause may be, must have been larger. This may have implications on the prediction for the next century, as it is expected that sea-level may rise between 20 and 60 cm at the end of the 21st century under the influence of human activities alone (WARRICKet al., 1993). These experiments consider only the response of the climate system to orbital forcing, the influence of shorter-term forcing factors, including anthropogenic effects, being ignored. However, recently, the LLN model has been used in a series of simulations using different scenarios of CO2 concentration and of possible impacts of large CO2 concentration expected to result from human activities. In a first experiment for the next 5,000 years (LOUTRE, 1993), it has been assumed that the pre-industrial concentration of CO2 will rise from 280 to 710 ppmv within the next 500 years and then decreases progressively to reach 450 ppmv and 350 ppmv, respectively 1,000 years and 1,500 years from now. A new equilibrium might then maintain this concentration roughly constant for the future. The temperature response of the LLN model (Fig. 9)
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Fig. 9. Simulation of the northern hemisphere temperature (dashed line, right-hand scale) and of the Greenland ice sheet volume (full line, left-hand scale) over the next 5000 years using the LLN model (LotrrRE, 1993).
57
Modelling the response of the climate system to astronomical forcing is what we could expect from its sensitivity to CO2 changes; surface-air temperature in the northern hemisphere increases from 15~ to 18~ over the next 500 years. The changes are particularly important in the high latitudinal zones (north of 65~
during spring and fall.
These changes are related to a parallel reduction in the extent of the areas covered by snow, a phenomena which acts as a positive feedback in the system. This result is similar to the findings of GROISMAN et al. (1994) who claim that a 10% decline in northern hemisphere snow cover over the past 20 years caused by a general warming of spring temperatures may itself have forced spring temperatures to rise even higher. Between 500 and 1,500 years from now, the air temperature decreases to reach a minimum of 16.4~ Temperature will afterwards increase slightly but steadily up to 5000 years into the future. This is related to the melting of the Greenland ice sheet which disappears at the end of the integration period, a disappearance which, through the ice-albedo-temperature feedback, explains the warming. This is in line with previous sensitivity experiments for which the CO2 concentration was kept constant (HUYBRECHTS et al., 1991; GALLI~Eet al., 1992, 1993) and which show that a concentration larger than the pre-industrial value leads to a progressive decay of the Greenland ice sheet, every other external forcing being kept constant. It is also worth mentioning that the sensitivity of the LLN model is in agreement with a 500-year integration made by MANABE and STOUFFER (1993) using a coupled ocean-atmosphere model. They assume that the CO2 concentration increases by 1% year -1 (compounded) until it reaches two times (after 70 years) and four times (after 140 years) the initial value and remains unchanged thereafter. During the 500-year period of the doubling and quadrupling experiments, the global mean surface air temperature increases by about 3.5~ and 7~ respectively. The rise of sea-level due to the thermal expansion of seawater is about 1 and 1.8 m, respectively, but they conclude that "it could be much larger if the contribution of meltwater from continental ice sheets were included". As an extreme case to test the sensitivity to the possible impact of human activities, it was therefore assumed that the greenhouse warming of the 21st century would melt the Greenland ice sheet totally. The main results of an integration of the LLN model for the next 80 ka with this initial condition (Fig. 8 and GALLI~E, 1989) are that the ice sheets do not reappear in the northern hemisphere before 15 ka AP and that the next glaciation occur 60 ka after present (5,000 years later than in the simulation without the enhanced greenhouse assumption) and is less extensive (19 instead of 27 x 106 km3). The main difference between the "normal" and enhanced greenhouse simulations, as far as the behaviour of the individual ice sheets is concerned, arises mainly for the Fennoscandian ice sheet which appears only 50 ka after present (35,000 years later than in the "normal" case) and reaches only half its "natural" size (4 instead of 7 x 106 km3); the Greenland and Laurentide ice sheets reappear 15 ka after present in the no-initial-Greenland ice-sheet run, the Laurentide ice sheet reaches a maximum size of 11 instead of 14 • 106 km 3 and the Greenland ice sheet recovers its 5 • 106 km 3 quite rapidly. This is in agreement with the GRIP results (DANSGAARD et al., 1993) which show that the Greenland ice sheet did not disappear during the Eemian Interglacial and therefore is a resilient part of the natural climate system under conditions similar to present-day. However, the representation of enhanced greenhouse warming in this experiment is very crude and the model does not yet have a carbon cycle. This simulation must therefore be considered only as a guide to the possible sensitivity of orbital forcing effects to potential
58
References
changes in cryospheric boundary conditions due to the human-induced enhanced greenhouse. There remain clearly great uncertainties surrounding the relationship between greenhouse and orbital forcing; three possible patterns describing the relationship between enhanced greenhouse warming and orbital forcing have been identified by GOODESS et al. (1992). First, the simplest assumption is that a relatively short (say 1 ka) period of greenhouse gasinduced warming will be followed by a switch back into the "natural pattern" of glacialinterglacial cycles. The second possibility is that, following a period of warming, the next glaciation will be delayed and will be less severe. The third possibility is that enhanced greenhouse warming will so weaken the positive feedback mechanisms which transform the relatively weak orbital forcing into global interglacial-glacial cycles, that the initiation of future glaciations will be prevented. This is the so-called "irreversible greenhouse effect". On the basis of the limited evidence available, GOODESS et al. (1992) and BERGER et al. (1991) considered that the second possibility, delayed and reduced glaciation, had the highest probability. However, new experiments based upon a more recent version of the LLN model (GALLI~Eet al., 1992) show that the future climate behaviour is very sensitive to the greenhouse gas concentrations and to their hypothetical changes in time. According to these new results, the third possibility of an "irreversible greenhouse effect" could become the most likely future climate. Modelling results presented here confirm that, potential anthropogenic forcing apart, the pattern and range of climatic conditions likely to be experienced over the next tens to hundreds of thousands of years will be close to those experienced over the last million years. This implies that it is reasonable to use the reconstructed record of Quaternary climate to better understand the behaviour of models of the climate system and as a guide to future conditions. These studies also provide some indication of the ways in which future climate sequences may diverge from past sequences because of enhanced greenhouse warming.
References
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Chapter 3
Warmer worlds" global change lessons from earth history ERIC J. BARRON
Introduction
The climate over the last 600 million years of Earth history ranges from periods of extensive polar glaciation to episodes of extreme warmth, lacking any evidence of permanent ice. The most recent occurrences of these extremes have the best documented climates. The midCretaceous, about 100 million years ago (the Cretaceous extends from approximately 144 million years ago to 65 million years ago), is the warmest climate which can be welldocumented from both terrestrial and marine observations. BARRON (1983) estimates that the globally averaged surface temperature was 6-12~
higher than the present day and that
the planet was warmer at every latitude. Some authors (e.g. FRAKES et al., 1992) suggest that the entire record of climate for the last 600 million years can be divided into warm and cold climate modes of which the Cretaceous is a primary example of a warm climate (Fig. 1). However, closer examination of past climates reveals major differences between warm climates. For example, the early Eocene (approximately 50 million years ago) appears to be characterised by very warm polar regions yet cooler tropics. The globally averaged surface temperature has been estimated at only 2~ higher than at present (BARRON, 1987) yet regions above the Arctic circle are characterised by abundant floras and temperature sensitive cold-blooded animals. The large differences between the Cretaceous and the early Eocene are suggestive of very different explanations of global warmth. The climatic changes recorded over the last 600 million years may have been influenced by a wide variety of climatic forcing factors. These forcing factors can be divided into three major categories: (1) changes in solar input due to factors such as solar luminosity variations and modifications to the Earth's orbital elements; (2) changes in the opacity of the Earth's atmosphere due to variations in the concentrations of greenhouse gases or aerosol and particulate loading; and (3) changes to the surface of the Earth including different positions of the continents (area of land at the poles, barriers or gateways to ocean circulation), changes in total continental area due to sea-level variations and differences in continental topography due to mountain building events. The Cretaceous and the early Eocene may be viewed as two "case studies" of global warmth. How might these two cases contribute to the understanding of future climates? There are two possibilities. First, extensive analysis of the geologic observations would yield a reconstruction of global temperatures which could be utilised as an analogue for future warm climates. Unfortunately, so many conditions are different, including the distribu-
71
Warmer worlds: global change lessons from earth history
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I Probable Age Range Possible Age Range Fig. 1. Glacial record of the earth (in millions of years before present) indicating warm and cold climate modes. Geologic eras are given: A, Archean; EP, Early Proterozoic; LP, Late Proterozoic; C, Cambrian; O, Ordovician; S, Silurian; D, Devonian; C, Carboniferous; P, Permian; T, Triassic; J, Jurassic; K, Cretaceous; P, Paleogene; N, Neogene. The Eocene is the latter half of the Paleogene. tion of the continents, that true analogue climates are improbable. Second, this paleoclimatic information can be utilised to provide useful insights into the importance of different climate processes and to validate the climate models which are the primary tool for predicting future climates. If climate models successfully predict conditions for time periods dramatically different from today, then we gain increased confidence in their capabilities. If major discrepancies between geologic observations and the models occur, then these results focus our attention on model inadequacies, lack of knowledge about forcing factors or inadequate observations. The mid-Cretaceous and the early Eocene case studies provide a basis for exploring a number of the potential forcing factors and for determining the sensitivity of the climate system to external factors. In addition, the early Eocene introduces the possibility that internal mechanisms can have a significant impact on climate. Each of these cases provides interesting and valuable opportunities to validate models used to predict future global change and to assess the nature of climatic change and climatic sensitivity. Specifically, these two case studies provide two important "lessons". The first addresses the most likely response to a future doubling of CO2. The INTERGOVERNMENTALPANEL ON CLIMATE CHANGE (1990) has adopted a range of 1.5--4.5~ globally averaged temperature increase for a CO2 doubling. The geologic case studies indicate that a climatic sensitivity in the lower half of this range would make past warm climates very difficult to simulate. In other words, the geologic record suggests that the climate system must be more sensitive than some of the current climate models would allow. Second, the analysis of the case studies of past global change indicate that the oceans played a very important role. Explicit incorporation of the role of the ocean in future climate model predictions is essential. The geologic observations and model studies indicate the potential for different modes of ocean circulation, which then result in equilibrium climates very different than allowed by current models with rudimentary ocean physics.
Cretaceous warmth The climate record
The climatic data from the Cretaceous have been reviewed in detail by BARRON (1983) and more recently by SPICER and CORFIELD (1992). The key evidence for extreme warmth stems from the high latitude record (see Fig. 2 for a map reference for data site locations). As yet
72
Cretaceous warmth
-
-
-
o
,,
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-',:
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Fig. 2. Reconstruction of mid-Cretaceous geography. Present continental outlines are included with mid-Cretaceous continental area (shaded). 30~ paleolatitude lines are given. Modern five degree latitude-longitude crosses are located on the continents for ease in comparing with observations.
there is no convincing evidence for any permanent polar ice, with the possible exception (FRAKES et al., 1992) of southern Australia during the Early Cretaceous (Australia was attached to Antarctica during this period and southern Australia was a high elevation region at latitudes greater than 75~
Evidence for winter freshwater ice is available from Siberia
(EPSHTEYN, 1978; FRAKES and FRANCIS, 1988). The evidence for greater polar warmth during the mid-Cretaceous in comparison with the present is strong. Cretaceous cores from the Arctic Ocean recovered abundant silicoflagellates. The particular genera recovered are normally rare if the sea surface temperatures are below 4~
(CLARK,
1977). Northern
Alaska (well within the Arctic circle at 85~
has more than 400 plant species recorded
from the latter half of the Cretaceous
1967). Based on angiosperm leaf physiog-
(SMILEY,
nomy and vegetation types, SPICER and PARRISH (1990) and SPICER and CORFmLD (1992) interpret the mean annual temperature from the North Slope of Alaska to be 10-13~ the mid-Cretaceous (similar to the present climate of London) and near 5~ Cretaceous. High latitude (65~ tures of 4.5-10.5~
during
during the late
shelf seas of the Antarctic Peninsula have surface tempera-
recorded in the oxygen isotopic composition of planktonic foraminifera
during the Late Cretaceous (BARRERA et al., 1987). Based on more than 150 taxa of vertebrates, invertebrates and plants, RICH et al. (1988) assign a cool temperate climate in Cretaceous Australia at 75~
All the evidence from both polar regions is indicative of mean an-
nual temperatures well above 0~
but would allow seasonal subfreezing conditions.
The warmest estimates of Cretaceous polar warmth are derived from an interpretation of the formation of Cretaceous deep waters. Cretaceous deep water temperatures derived from oxygen isotopic composition of benthic foraminifera are as warm as 15-17~
during the
mid-Cretaceous (SAVIN, 1977). If Cretaceous deep water represents the coldest water formed at the Earth's surface, then high latitude ocean temperatures must have been above 15~
However, BRASS et al. (1982) have suggested that warm saline waters formed in the
subtropics may have been the source of Cretaceous deep waters. This view receives some support from ocean General Circulation Model (GCM) experiments (BARRON and PETERSON, 1991). However, the sites of Cretaceous deep water formation are not well estab-
73
Warmer worlds: global change lessons from earth history lished. Cretaceous polar mean annual temperatures from 0~
to 15~
encompass the full
range of possible estimates of polar warmth. Substantial temperature data are available from the mid-latitude continental regions based on the analysis of leaf assemblages (WOLFE and UPCHURCH, 1987). Leaf physiognomy (shape, nature of the margins, leaf type) tends to take the same form in environments with the same basic climate. In cases of large assemblages, leaf-margin characteristics have been widely utilised to determine the mean annual temperature and range of temperature. WOLFE and UPCHURCH (1987) estimate that the southeastern United States, which has one of the most complete records for the mid- to late-Cretaceous, had a mean annual temperature in the range of 21-24~
The floral evidence also suggests that the regions adjacent to the Western
Interior Seaway of North America at latitudes as high as 50~ did not experience subfreezing winter conditions during the mid-Cretaceous. In general, the leaf assemblage data indicate that the low- to mid-latitudes were characterised by seasonal climates with moderate precipitation. The evidence from the Cretaceous tropics is perhaps more problematic. Sea surface temperature changes of even a few degrees are likely to be very significant, yet this resolution severely taxes the capabilities to interpret paleoclimatic observations. The best evidence is derived from oxygen isotopic temperature measurements from planktonic foraminifera. SAVIN et al. (1975) report tropical temperatures from shallow dwelling forms which yield paleotemperatures of 25-27~ However, based on modern observations, the shallowest dwelling planktonic foraminifera are still 3-5~ cooler than the surface temperature. Therefore, 3-5~ must be added to the 25-27~ measurement. If these specimens represent unaltered material (diagenesis tends to bias measurements in the warm direction), then midCretaceous tropical temperatures may have been in the range of 27-32~
similar to or
somewhat warmer than the present day. Other evidence is less robust. For example, corals appear to be displaced to higher latitudes and deeper water by rudists (a reef building clam) which has been interpreted as a possible indicator of water temperatures in excess of the optimum range (above 30~ of hermatypic corals (e.g. BARRON, 1995). A summary of these observations is presented in Fig. 3, which gives the plausible range of mid-Cretaceous mean annual temperatures with respect to latitude in comparison with presI
510 f 500
I
I
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_
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No Permanent Ice
\
ii
ii
Warmest Cretaceous ......... "Coolest" Cretaceous --.-- Present Day
240 I N 80
I 60
I 40
I 20
I 0
I 20
I 40
-
.
/
25O -
250
I
~,,~,,/
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260
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~Foraminifera
~.~ 290 I.L.I n,- 2 8 0
I
Benthic Foraminifera
-
.
--
"~ I 60
I 80
S
LATITUDE
Fig. 3. Cretaceous mean annual surface temperature limit in comparison with modern values.
74
Cretaceous warmth
ent day values. This range yields global mean annual temperatures which are 6-12~ higher than the present day. This range also appears to satisfy the large majority of Cretaceous observations.
Cretaceous climatic forcing factors Since the formulation of plate tectonic theory, changing geography (land-sea distribution, sea-level and topography) has become one of the most frequently cited explanations of Cretaceous warmth (e.g. LUYENDYKet al., 1972; SELLERS and MEADOWS, 1975; DONN and SHAW, 1977; BEATY, 1978). The two major hypotheses centre on changes in land area. First, decreases in high latitude land area are considered to be a major factor in promoting global warmth because the area of potential accumulation of high albedo snow decreases. Second, global warmth is correlated with higher sea-level (decreased total land area), originally interpreted as a function of albedo differences between land and ocean. There are very large differences between the Cretaceous continental geometry and the present day (e.g. the area of high latitude land area is substantially lower in the mid-Cretaceous and the total area of land is lower by 17% during the mid-Cretaceous because of higher sea-level). Increased levels of atmospheric carbon dioxide are also plausible explanations (e.g. BUDYKO and RONOV, 1979; FISCHER, 1982) of global warmth. The carbon dioxide hypothesis has received credible quantitative support from geochemical models (BERNER et al., 1983; BERNER, 1991). BERNER (1991) calculates Cretaceous CO2 levels of 2-6 times present day values. On long time-scales the primary source of atmospheric CO2 is the rate of volcanic emissions. The mid-Cretaceous is associated with increased sea floor spreading resulting in greater subduction (destruction) of crust and increased volcanic CO2 release. Similarly, on long time-scales the primary control on the removal of CO2 from the atmosphere is the weathering of silicate rocks. The increased sea floor spreading is the primary explanation for higher sea-level and continental flooding during the mid-Cretaceous. A more rapid sea floor spreading gives rise to more thick (warm) oceanic crust at mid-ocean ridges, resulting in a decrease in ocean volume and flooding of the continents. The decreased land area also limits the rate at which CO2 can be removed from the atmosphere through the weathering of continental silicate rocks. These simple concepts are the basis for a complex assessment of the carbon mass balance by BERNER et al. (1983) and BERNER (1991). FREEMAN and HAYES (1992) have also determined Cretaceous CO2 levels from fractionation of carbon isotopes from phytoplankton and have calculated values of 4 times the present day values. CERLING (1991) used evidence from paleosols to determine Mesozoic CO2 values of 4-9 times the present. These diverse observations and calculations are indicative of much higher CO2 levels during the mid-Cretaceous than for today.
Model predictions BARRON and WASHINGTON (1984) performed the first General Circulation Model (GCM) experiments to determine the role of paleogeography in explaining Cretaceous warmth. The specification of mid-Cretaceous paleogeography with no permanent ice caps in a mean annual experiment with a simple energy balance ocean resulted in a 4.8~ increase in globally averaged surface temperature compared to a present day control experiment. Polar surface
75
Warmer worlds: global change lessons from earth history temperatures warmed 20-30~ while tropical temperatures warmed slightly. The experiments appeared to establish changing paleogeography as a significant climatic forcing factor. A series of sensitivity experiments was utilised to determine which geographic change resulted in the global warming (continental positions were different, sea-level was higher, no permanent ice was specified and continental elevations were lower in the experiment). The northern hemisphere warming resulted largely because of decreased high latitude land area and the southern hemisphere warming resulted almost entirely because of the deglaciation of Antarctica (decrease in Antarctic elevation and removal of specified permanent ice cover). These experiments suggested that mid-Cretaceous geography resulted in global warming. In particular, they appeared to confirm the notion that high latitude land area is a major factor in determining global temperature. However, the 4.8~ warming is insufficient to explain the globally averaged temperature increase of 6-12~ or the distribution of temperatures reconstructed from observations. Furthermore, much of the warming was achieved through the removal of permanent ice which should have been part of the response, not a separate forcing factor. Using the same climate model, BARRON and WASHINGTON (1985) suggested that increased carbon dioxide concentrations approximately four times the present would be required to explain the Cretaceous warmth (Fig. 4). This level of CO2 increase brought polar and mid-latitude temperatures to the minimum estimate of Cretaceous warmth, while tropical temperatures slightly exceeded observations. However, mean annual models with simple energy balance oceans which lack heat capacity probably do not give a realistic estimate of the climatic sensitivity to changes in continental area and geometry and are certainly inadequate for comparing model-predicted temperatures with geologic observations. Consequently, BARRON et al. (1993a) analysed the role of geography and CO2 utilising a GCM (GENESIS, developed by POLLARD and THOMPSON, 1994, 1995) with an annual cycle. The change from present day geography to mid-Cretaceous geography resulted in a global cooling of 0.2~ a result which is very different from the 4.8~ warming in the mean annual model described by BARRON and WASHINGTON (1984). The Antarctic warmed substantially with the removal of the permanent ice cap. However, the northern hemisphere experienced marked cooling. With the exception of the removal of Antarctic ice, land-sea distribution dominates the differences in temperature between the present day and the Cretaceous simulations (Fig. 5). However, unlike the mean annual experiments, the seasonal cy310
..-- 3 0 0 w rr
290
<[ rr 280 w (2. ~E w 270 l-
260 90 N
60
30
0 LATITUDE
30
60
90 S
Fig. 4. A comparison of the est;,nates of Cretaceous temperature limits from Fig. 3 with predicted zonally averaged surface temperatures for Cretaceous geography derived from mean annual GCM experiments of BARRONand WASHINGTON(1984, 1985).
76
Cretaceous warmth a
90oN
_.
,,
30~ 90~ 180~
180~
~J'lf~r,,fJ~ -45
-40
[~ -25
-35
-15
-10
-5
' ",i
"i
' . . . . ~, :~ ,~,
0
5
10
15
25
35
40
45
~
b 90~
60ON -
30ON -
,--,
r"'l 0 ~_
30os-
4
60oS I
I
i.
,i
90oS -
180~
180~ [ 0
,,, 5
10
15
~,,, 25
35
40
~
Fig. 5a,b.
cle simulations result in responses which are not a simple function of the change from land to sea or sea to land. At mid to high latitudes, present day continental regions which were oceanic in the Cretaceous are predicted to be substantially warmer in winter (25-35~ warmer) and cooler in summer (20~
cooler). This result follows simply from arguments
based on the differences in heat capacity between land and ocean. Since the Cretaceous had less total land area in mid to high latitudes than at present, this result would suggest a net warming for the Cretaceous compared to the present. However, present day oceanic regions which are continental in the Cretaceous are predicted by the climate model to be substantially cooler in winter (by as much as 45~ somewhat warmer in summer (by 9~
and are only
The reason is that the North America-Greenland-
Europe-Asia land mass (see Fig. 2) acts as one large land mass. The widespread shallow continental seas pole-ward of the landmass are ice-covered in winter, yielding a strongly continental climate with substantial winter cooling. In summer, these seas become ice-free
77
Warmer worlds: global change lessons from earth history
90~
60oN -
30ON -
0 ~-
30os -
60oS -
90~ 180~
180~
-15
-10
-5
0
5
10
15
25
~
90~ 0 60ON
-
30oN -
0 ~_
30oS-
1 ~ U "~I::
180~ 0
5
10
15
25
~
Fig. 5. Differences between model experiments (~ (a) Cretaceous minus Present day; December, January, February averages, (b) Cretaceous minus present day; June, July, August averages, (c) Cretaceous 4 x CO2 minus Cretaceous; December, January, February averages, (d) Cretaceous 4 x CO2 minus Cretaceous; June, July, August averages. and the planet is more oceanic in nature, yielding cooler summer temperatures than the present day. Consequently, in both summer and winter the northern hemisphere is cooler above 40~ in the Cretaceous simulation than in the present day control experiment. Although these results may be model dependent, a similar experiment with the Community Climate Model (CCM) at the National Center for Atmospheric Research (NCAR) yielded a very similar result. A series of GENESIS experiments with a full annual cycle GCM for a variety of continental configurations suggests that land-sea distribution plays a very modest direct atmospheric role in explaining past warm climates. The Cretaceous seasonal cycle experiment was also repeated with 2 times, 4 times and 6 times present day CO2 levels. The globally averaged surface temperature increased by 3.0, 5.5 and 6.9~ for the 2 x , 4 x and 6x CO2 cases, respectively. The globally averaged surface temperature increase of 5.5~ for the 4 x CO2 case is close to the lower limit suggested
78
Cretaceous warmth
by BARRON (1983) as required to explain the geologic observations. The 6 x CO2 case is the first experiment for which the model predictions exceed the minimum estimate based on observations. These simulations suggest that: (1) geography plays a small role in explaining global warmth, but that increased levels of carbon dioxide may provide a reasonable explanation and (2) if the role of geography is small then the Cretaceous can be utilised as a test of climate model sensitivity to changes in CO2 concentrations.
Comparison of predictions with observations The Cretaceous simulation with four times the present day concentration of atmospheric carbon dioxide has a predicted globally averaged surface temperature which is 5.5~ higher than the present day control simulation. Based on observations, the globally averaged surface temperature for the mid-Cretaceous was probably between 6 and 12~ higher than at present. The Cretaceous simulation is at the lower limit of Cretaceous observations. However, the globally averaged surface temperature is not a very useful measure for model validation. A much better measure is the ability to predict the distribution of temperatures indicated by the geologic observations. The primary observations cited earlier on Cretaceous warmth include: (1) North Slope of Alaska with a mean annual temperature of 10-13~
(2) evidence for seasonal ice in Siberia,
(3) lack of permanent ice in the Arctic with some regions likely to have surface temperatures in excess of 4~ near 4.5-10.5~
(4) shallow seas around the Antarctic peninsula with temperatures
(5) tropical sea surface temperatures in the range of 27-32~
eastern US (30~ paleolatitude) mean annual temperatures 21-24~
(6) south-
The Cretaceous model
simulation with 4 x CO2 (Fig. 6) predicts (1) a mean annual temperature of near 5~ for the northern margin of Alaska, (2) winter temperatures well below freezing for Siberia and summer temperatures from 5 to 20~
(3) permanent ice in the centre of the Arctic but not at
the margins with only the marging having temperatures above 4~ in the summer, (4) shallow seas around the Antarctic peninsula with temperatures ranging from below 0~ to near
60~
90~ 180~
,,
;
-
[
180~
].~_ -10
0
10
20
30
oc
Fig. 6. Predicted mean annual temperatures for Cretaceous geography and 4 x CO2 derived from GCM experiments (GENESIS). 10~ contour interval.
79
Warmer worlds: global change lessons from earth history 10~ (5) tropical sea surface temperatures above 30~ southeastern US mean annual temperatures of 10-20~
and regionally near 32~
and (6)
The Cretaceous model simulation with 6x CO2 results in some additional warming and a seasonally ice-free Arctic. However, the mean annual temperature for the northern margin of Alaska is still below 10~ only a portion of the southeastern US has a mean annual temperature which is above 20~ and tropical sea surface temperatures exceed 32~ regionally. The prediction for the mid-Cretaceous for both 4 x and 6x CO2 concentration approaches the estimates from the geologic data but, with the exception of the tropics, the model simulation remains too cool in comparison with the observations. There are two alternatives. First, the CO2 concentration may have been somewhat higher during the mid-Cretaceous. Both the geochemical model predictions and all the geochemical observations encompass four times present day CO2. The estimates of BERNER (1991) and CERLING (1991) which range from 2 to 6 and 4 to 9 times present day, respectively, would allow 6x CO2 levels. Currently only the Cerling estimates allow for still higher CO2 levels. However, if higher CO2 estimates are allowed, the model predictions will exceed the temperature estimates for the Cretaceous tropics. Second, the model sensitivity may underestimate the climate response to increased levels of carbon dioxide. Alternatively, additional mechanisms or forcing factors may need to be considered to explain the Cretaceous climate. A major limitation of the models remains the role of ocean dynamics in climatic change, an issue which is explicitly considered in discussions of the early Eocene climate and in Chapter 14 by Peng.
Implications for the prediction of future climate The sensitivity of GCMs to a doubling of carbon dioxide generally falls within the range of 1.5-4.5~ This range has been adopted by the IPCC (INTERGOVERNMENTALPANEL ON CLIMATE CHANGE, 1990) as the most likely climatic response to a future doubling of CO2. The geologic record has been utilised to try to calibrate model sensitivity to increases in CO2 (HANSEN and LACIS, 1990; LORIUS et al., 1990; HOFFERTand COVEY, 1992; HANSEN et al., 1993). Two studies (LORIUS et al., 1990; HOFFERT and COVEY, 1992) suggest that the midrange of IPCC estimates fits the geologic data but the estimates are somewhat different: 34~ and 2.3 _+0.9~ respectively. CROWLEY (1993) discusses these results, indicating that the geologic data do not narrow the uncertainties in the IPCC results. However, these two studies are not constrained by the actual distribution of global data or seasonal climate indices (e.g. the Hoffert and Covey estimate is based on global, mean annual, equator-to-pole temperatures) nor by GCM simulations. The sensitivity of the model utilised in the above discussion (GENESIS), based on present day continents, is 2.3~ increase in globally averaged surface temperature for a doubling of carbon dioxide- in the lower range for similar GCM experiments. In the Cretaceous experiments, a CO2 doubling resulted in a 3.0~ increase in globally averaged surface temperature. Each additional increment two times the present CO2 level resulted in decreased sensitivity (i.e. 2.5 and 1.4~ increases in globally averaged surface temperature for each increment). Consequently, the GENESIS model requires the uppermost range of CO2 concentration estimates from geochemical models and from observations in order to explain the global distribution of Cretaceous paleoenvironmental data. If the climatic sensitivity to CO2 was lower (e.g. 1.5~ for a CO2 doubling) and the response to increased levels of CO2 is as-
80
An alternative warm climate: an Eocene example
sumed to be linear, then more than nine times CO2 would be required just to achieve a minimum estimate of Cretaceous warmth. GCM experiments suggest that the response is substantially less sensitive at higher CO2 levels. The problem is further exacerbated if estimates of solar luminosity for the mid-Cretaceous are included. For instance, GOUGH (1977) calculated the solar luminosity for 100 million years ago at 0.9% lower than at present. If solar luminosity was lower, then either even higher CO2 levels or even greater model sensitivity would be required to achieve Cretaceous warmth (see Chapter 15 by KUMP). The geologic record provides an important global change lesson. The differences in the IPCC estimates represent differences in model parameterisations, which as yet cannot be verified. The geologic record suggests that a climatic sensitivity in the lower half of the IPCC range would make past climates very difficult to simulate, unless the three different methods for determining past CO2 levels all substantially underestimate the actual value. This conclusion must be validated by direct simulation of past climates for a variety of different time periods.
An alternative w a r m climate: an Eocene example The climate record
An examination of the cold and warm extremes of Earth's climate seems to permit a generalisation. The greatest temperature change occurs at high latitudes with a smaller, but of the same sign, change in low latitudes. Essentially, the whole world warms or cools at every latitude but the surface temperature gradient steepens in glacial cases and weakens in the warm climate cases because the greatest sensitivity is at the high latitudes. If such a generalisation is applicable throughout Earth's history, then the validation of climate models and an understanding of climatic sensitivity might be greatly simplified. The first order climate response might be achieved through the development of a model which would accurately achieve the sensitivity in polar regions and in the tropics recorded in a host of geologic case studies. However, the expansion of the paleoclimatic research focus to a range of time periods reveals some significant differences between different warm climates. The early Eocene is a primary example suggestive of different modes of climate and climatic change. Reconstructions of sea surface temperatures (Fig. 7) for the early Eocene based on oxygen isotopic measurements on planktonic foraminifera indicate that the high latitude oceans were quite warm (as much as 10~ warmer than present at 60~ but that the tropics were as much as 5~ cooler than at present (SHACKLETON and BOERSMA, 1981; KEIGWIN and CORLISS, 1986). For these values, the globally averaged surface temperature would be 2~ higher than at present. The condition of a warmer Earth with substantially warmer polar regions yet cooler tropics distinguishes the early Eocene from other warm climates such as the mid-Cretaceous. The interpretation of the oxygen isotopic values which indicate cooler tropics is not without debate. MATTHEWS and POORE (1980) suggest that tropical temperatures have been stable throughout Earth's history and that the apparent decrease in temperature reflects the possible storage of the lighter oxygen-16 isotope in ice on Antarctica. However, there is little evi-
81
Warmer worlds: global change lessons from earth history I
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PRESENT and EOCENE TEMPERATURES
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LATITUDE,
I 0
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Areo-weighfed
Fig. 7. Isotopic paleotemperatures of the Eocene surface ocean from SHACKLETONand BOERSMA (1981) in comparison with modern values. Northern and Southern hemisphere data are plotted in both hemispheres (mirror sites are plotted as open squares) in order to draw the surface temperature distribution with respect to latitude. dence for substantial ice during the early Eocene. The oldest ice rafted debris found in marine deposits surrounding Antarctica (an indicator of growth of continental ice to the continental margin) is dated in the range of 26-31 Ma (million years ago) (HAYES and FRAKES, 1975; HARWOOD, 1987). The initial ice build-up may have occurred substantially earlier. For instance, glacial debris has been found on the South Shetland islands below a lava dated at 49.8 Ma and oxygen isotopes suggest a major cooling event, with probable sea-ice formed around Antarctica, at 38 Ma (SHACKLETON and KENNETT, 1975). The northern hemisphere glaciation occurred much later, with intermittent glaciation starting near 10 Ma in Alaska (DENTON and ARMSTRONG, 1969) and significant expansion of ice over Greenland at 5.2 and 4.8 Ma (KEIGWIN, 1987). ZACHOS et al. (1993) suggest that all oxygen isotopic measurements of surface paleotemperatures must be corrected for latitudinal variations in the evaporation/precipitation balance. Without any adjustments, the tropical (0-20 ~ latitude) temperature range for the early Eocene is 20-22~ With an adjustment at each latitude to reflect modern moisture balance differences, the tropical temperature range for the early Eocene is 24-26~ (Fig. 8). For comparison, the best determination for recent tropical sea surface temperatures using modern foraminifera is 27-28~ Use of these values would suggest that the Eocene tropics were 1-4~ cooler than the present day temperatures. The interpretation of polar warmth is supported by an abundance of floral and faunal evidence (ESTES and HUTCHISON, 1980; MCKENNA, 1980; WOLFE, 1980). The remains of ectotherms at sites above the Arctic Circle have been utilised to suggest frostless winters in coastal regions above 70~
82
Floral assemblages of both macrofossils and palynomorphs and
An alternative warm climate: an Eocene example
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i .... 50
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70
Absolute Paleolatitude Fig. 8. Early Eocene surface temperatures calculated from oxygen isotopes for surface dwelling planktonic foraminifera (ZACHOS et al., 1994) in comparison with modern temperatures (dashed line). Surface temperatures are calculated as adjusted for precipitation-evaporation balance (open circles) and unadjusted (closed circles). fossil leaf physiognomic characteristics suggest that continental interior temperatures during the early Eocene were also substantially warmer than today (see review by SLOAN and BARRON, 1992; WING and GREENWOOD, 1993). These data indicate very mild winters even at 50~
within the interior of North America.
The nature of early Eocene climate is also evident from measures of aeolian dust transported from desert regions and deposited in deep sea cores far from the continents. An analysis of
Eolian grain Size (~50) 0
"-- 40
9.4 9.0 a_I . . . . . .
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o
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Fig. 9. Aeolian grain size distribution for quartz and total sediment for the central Pacific from the Late Cretaceous to the Pleistocene after JANACEKand REA (1983). The q~ scale (-log 2 of grain diameter in mm) describes smaller size with increasing tp.
83
Warmer worlds: global change lessons from earth history aeolian grain size (Fig. 9) recorded over the last 70 million years reveals a dramatic drop in size across the Paleocene-Eocene boundary (JANACEK and REA, 1983; JANACEK, 1985; REA et al., 1985). The effect is global and has been interpreted as a considerable reduction in the intensity of the atmospheric circulation. Such a change in atmospheric winds is consistent with lower tropical temperatures, warmer poles and the large decrease in equator-to-pole surface temperature gradient. The sum of the early Eocene paleoclimatic data suggests a different climate mode, useful for evaluating the mechanisms of climatic change during Earth history or alternative hypotheses on the nature of climatic sensitivity and climatic change. Eocene climatic forcing factors There is some evidence for possible increases of atmospheric concentration of CO2. However the estimates are more modest (i.e. less than 2x the present day) than for the midCretaceous (e.g. BERNER et al., 1983; KASTING and RICHARDSON, 1985; OWEN and REA, 1985). The changes in continental configuration for the early Eocene are certainly much less dramatic than for the Cretaceous and annual cycle GCM simulations again suggest that the response of the atmosphere to the changes in geography is minimal. If paleogeography has a role, then this role must reflect changes in ocean gateways and marginal seas which influence the surface ocean circulation or the thermohaline circulation. A large number of studies from the early Earth to the Pleistocene (the last 1.9 Ma) have suggested that changes in continentality and continental positions have modified the role of the oceans (LUYENDYK et al., 1972; KENNETT, 1977; WALKER, 1982; MAIER-REIMER et al., 1990). Additional studies have demonstrated that climate simulations are very sensitive to the distribution of sea surface temperatures (RIND and PETEET, 1985; RIND, 1986; RIND et al., 1986; SLOAN and BARRON, 1990; CHANDLER et al., 1992). A change in oceanic heat transport has also been invoked to explain the equator-to-pole surface temperature distribution for past warm climates like the Eocene (BARRONet al., 1981; BARRON and WASHINGTON, 1985; SCHNEIDER et al., 1985; BARRON, 1987; RIND and CHANDLER, 1991). The hypothesis of a more efficient pole-ward heat transport may be valid as a response to some external forcing factor (e.g. new gateways for ocean circulation or changes in sites of deep water formation) or as a response to an internal mechanism regulating the respective roles of the ocean and the atmosphere. Other internal mechanisms such as latitude dependent cloud-climate feedbacks might also play a role in producing the Eocene distribution of temperatures. Model studies Current models have yet to simulate cooler tropics and warmer poles for any external forcing factor. In fact, STONE (1978) argues that the total pole-ward heat transport is governed by the distribution of incoming solar energy and that the modes of pole-ward heat transport basically compensate for any changes in land-sea configuration. In GCM experiments (e.g. MANABE et al., 1975), the addition of an oceanic role in pole-ward heat transport was compensated for by a decreased role of the atmosphere. However, an explanation of the early Eocene is even more problematic. The Eocene temperatures cannot be explained just from a change in the relative role of the ocean and the atmosphere, but rather require an increase in
84
An alternative warm climate: an Eocene example
the total pole-ward heat transport. Each of these early studies would suggest that the Eocene surface temperatures are difficult to achieve. However, none of these early experiments explicitly tested the response of the climate to increased oceanic heat transport. More recently, SPELMAN and MANABE (1984) and COVEY and THOMPSON (1989) have shown that an increase in oceanic heat transport may not be fully compensated for by a change in atmospheric heat transport, and therefore the equilibrium climate resulting from a change in oceanic heat transport may be different. COVEY and THOMPSON (1989) assume values of oceanic heat transport for modern continental geometry (mixed layer model with no oceanic heat transport, mixed layer with one-half realistic oceanic heat transport, and mixed layer with realistic oceanic heat transport specified). The standard experiment for future predictions with a GCM is a mixed layer model with no oceanic heat transport. In the case of specified modern oceanic heat transport, the tropical temperatures cooled by 5~
re-
suiting in large changes in the strength of the atmospheric circulation and weakening of the Hadley Circulation. RIND and CHANDLER (1991) provide a different perspective by calculating the oceanic heat transport required to satisfy specific sea surface temperature assumptions. They concluded that perturbations in oceanic heat transport, if strong enough to alter sea-ice cover, may be self-sustaining in terms of radiative balance. They determined that a 6~ increase in globally averaged surface temperature could be achieved by a 46% increase in oceanic heat transport for the Jurassic and a 6.5~ increase in temperature could be achieved by a 68% increase in pole-ward oceanic heat transport for the Cretaceous. Using the GENESIS model, BARRON et al. (1993b) found smaller increases in globally averaged surface temperature for modest changes in the role of the ocean (the addition of 15% of the CARISSIMO et al. (1985) estimate of the oceanic pole-ward heat transport to a control simulation resulted in a 0.6~ globally averaged surface temperature increase). The 15% change in total pole-ward heat transport by the ocean decreased tropical sea surface temperatures by 1.5~ and resulted in a pole-ward retreat of sea-ice by 4.5 ~ latitude. Each of these studies suggests that the role of the ocean may be a significant factor in climatic change and climatic sensitivity. The only possible explanation for an increased role of the ocean in pole-ward heat transport must involve the thermohaline circulation. Cooler tropical temperatures and warmer poles would result in decreased latent and sensible heat transport by the atmosphere. With a weaker atmospheric circulation, the wind-driven surface ocean circulation will also be weaker. BARRON and PETERSON (1990a,b, 1991) have shown, utilising an ocean GCM, that changes in continental geometry and atmospheric carbon dioxide concentrations have the potential to alter the site of deep water formation from high latitudes to the subtropics in the mid-Cretaceous and the Eocene. In a Cretaceous simulation, the site of deep water formation shifted to the subtropics when the ocean GCM was driven by an atmosphere with imposed higher CO2 levels. In a series of experiments for the last 60 million years, the site of deep water formation shifted from high latitudes during the Paleocene (60 Ma) to the subtropics in the Eocene as the subtropical oceanic seaway (Tethys) became more restricted. A change in the site of deep water formation will not necessarily result in a change in total pole-ward heat transport, but these results are suggestive that the role of the ocean may be a major factor in explaining past climates. Changes in the site of deep water formation will also appear to be geologically abrupt (see also Chapter 13 by Cleugh), since the time-scales associated with the ocean are of the order of centuries. The question remains
85
Warmer worlds: global change lessons from earth history whether both CO2 and changes in oceanic heat transport are required to explain the early Eocene record.
Comparison with observations The explanation of the early Eocene climate provides two potential opportunities for validation. First, the decreased intensity of the atmospheric circulation is supported by the dramatic decrease in size of aeolian material transported to the deep sea (JANACEK and REA, 1983; JANACEK, 1985; REA et al., 1985). Second, the transition from the Paleocene to the early Eocene is characterised by a major extinction of benthic foraminifera (MILLER et al., 1987; THOMAS, 1989). Benthic foraminifera distributions closely reflect the characteristics (temperature and salinity) of water masses, and water mass changes are a logical result of a major change in the site of deep water formation from a cold source to a subtropical warm saline source. Both these data are indicative of abrupt change, matching the proposed mechanism of a change in the thermohaline circulation. The sea surface temperature record of the Eocene does not represent an independent validation of model efforts since the entire focus of the RIND and CHANDLER (1991) and BARRON et al. (1993b) experiments was to increase oceanic heat transport or change specified sea surface temperatures in order to explain the SST distribution. The only additional alternative for model validation is the continental record. SLOAN and BARRON (1992) have synthesised the quantitative observations from the early Eocene for North America. Based on floral assemblages of both macrofossils and palynomorphs and on fossil leaf physiognomic characteristics, minimum temperatures, mean an-
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86
An alternative warm climate: an Eocene example
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.
.
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87
Warmer worlds: global change lessons from earth history nual temperatures and maximum ranges of temperatures have been reconstructed for the early Eocene. These data can be compared (Fig. 10) with Eocene GCM simulations with specified sea surface temperatures for both modern equator-to-pole gradients and for a gradient similar to SHACKLETON and BOERSMA (1981). In both cases the model-predicted January surface temperatures are too low to explain the observations. This may partly reflect the nature of the experiment performed by SLOAN and BARRON (1992) which was a perpetual January simulation, but the differences are as much as 20~
The predicted mean annual
temperatures are a reasonable match with the observations, but the high latitude sites are only explained in the low gradient case with warm polar oceans. The seasonal ranges of temperatures derived from the observations are less than half those of the model simulation. The low gradient case appears to be slightly closer to the observations. In summary, the observations qualitatively support an interpretation that the early Eocene climate may have been characterised by a different role of the oceans in pole-ward heat transport. However, the data from continental interiors have not been adequately explained. Continental climates are not predicted to be warm enough to explain the observations and the amplitude of the seasonal cycle is predicted to be too large.
Implications for the prediction of future climates The early Eocene case study provides two "lessons" for future climate prediction. First, the early Eocene introduces the possibility that changes in the role of the ocean, either through changes in geography or in response to increases in carbon dioxide, may yield substantially different equilibrium climates than currently simulated by GCMs with mixed layer oceans. The most likely mechanism for a change in the role of the ocean in pole-ward heat transport involves the intensity and location of deep water formation. The potential importance of the thermohaline circulation in climatic change is also evident from a variety of other studies. Modern observations from tracer studies in the North Atlantic (OSTLUND et al., 1976; TALLEY and MCCARTNEY, 1982; BROECKER et al., 1985; AAGAARD and CARMACK, 1987; DICKSON et al., 1988) also indicate that the production of North Atlantic Deep Water is sensitive to variations in North Atlantic moisture fluxes. Geochemical studies of glacialinterglacial cycles support the concept of significant changes in deep water production (e.g. BOYLE and KEIGWIN, 1987; DUPLESSY et al., 1988). Climate model studies (BRYAN, 1986; MANABE and STOUFFER, 1988) demonstrate that changes in the hydrologic balance can result in dramatic changes in the strength and character of the thermohaline circulation, suggestive of two modes of ocean circulation. The geologic record and these additional studies suggest that explicit incorporation of the role of the ocean in future climate model predictions is essential. A different role for the ocean could result in a substantially different future climate. Second, the early Eocene study highlights substantial discrepancies between model predictions and the observations from continental interiors. There are many possible explanations of these differences. The model simulations for continental interiors may have improper sensitivities due to poor land-vegetation-atmosphere parameterisations (see also Chapter 11 by Brasseur et al.). Additional forcing factors may be involved (e.g. higher CO2). The fossil data may be misinterpreted if floras, such as palm trees, had different environmental limits. The early Eocene case study suggests that each possibility warrants further examination.
88
Discussion of implications f or future climate and conclusions Discussion of implications for future climate and conclusions The geologic record preserves the integrated response of the Earth system to a large number of perturbations. Two case studies, the mid-Cretaceous and the early Eocene, have been utilised to illustrate global change lessons from the Earth's history. In each case study, the climate is characterised by extreme warmth in comparison with the present day. Although the older the record, the less certain are the interpretations, the observations are sufficiently dramatic to provide challenging problems. The cases of extreme warmth also represent large system responses. A large climatic "signal" with identifiable forcing factors provides an excellent opportunity for climate model study. With the exception of the last ice age, the midCretaceous and the early Eocene are probably the two most studied intervals of geologic time involving the application of climate models. Furthermore, in each case, increased atmospheric carbon dioxide concentration has been suggested as a primary or partial explanation of global warmth. The two case studies provide interesting insights into climatic change. If our understanding of the direct effect of major changes in paleogeography on the atmosphere is correct, then the explanation of Cretaceous warmth rests largely with the climatic response to increased levels of atmospheric carbon dioxide. The evidence for a mid-Cretaceous atmosphere with higher levels of carbon dioxide is strong. However, even a GCM with a sensitivity in the mid-range of IPCC estimates (see also Chapter 8 by McAvaney and Holland) cannot achieve the degree of Cretaceous warmth without resorting to CO2 levels which exceed the estimates from geochemical models and observations. Sensitivity at the lower range of IPCC estimates (e.g. 1.5~ warming for a CO2 doubling) would make explanations of warm time periods like the Cretaceous much more difficult. Of course there is substantial room for error. All the estimates of CO2 concentration for the mid-Cretaceous may be underestimates. Additional factors, such as an increased role of oceanic heat transport, may mask the true role of CO2 during the Cretaceous unless the change in ocean circulation (e.g. changes in sites of deep water formation) are in response to CO2 increases. The geologic observations of the environment may also be in error. However, the climate models cannot readily achieve even the most conservative estimates of Cretaceous warmth for plausible CO2 concentrations. The evidence that time periods like the Cretaceous demand a climatic sensitivity which is in the upper half of the IPCC estimates is further supported by a survey of all paleoclimatic simulations. In no case to date has a climate model over-predicted geologic observations for warming or cooling. It becomes increasingly difficult to assume that in each of these cases the geologic data have been over-interpreted or that in each case additional forcing factors are required which, in total, yield a colder or warmer climate. The fact that in all previous paleoclimate experiments the observations have been under-simulated provides growing evidence that climate model sensitivity for doubled CO2 is far from excessive. The early Eocene provides a very different lesson. The vast majority of projections of future climate depend on atmospheric GCMs with simple mixed layer oceans. The nature of the deficiency has been clearly recognised and the incorporation of an explicit dynamic ocean is a major goal of climate research (as yet, these models do not produce very accurate simulations of the present day). The early Eocene is suggestive of how significant the lack of a realistic ocean may be for future climate predictions. One plausible explanation of early Eo-
89
Warmer worlds: global change lessons from earth history cene climate is an alternative mode of ocean-atmosphere heat transport with the ocean taking a much more significant role than today. A change in the thermohaline circulation of the oceans, in response to changes in continental geometry or to higher CO2 levels, involving a shift in deep water source from high latitudes to the warm, salty subtropics, has the potential to change the role of the ocean in pole-ward heat transport and the nature of the climate. The Eocene climate was dramatically different from the present day. The polar regions were substantially warmer than at present yet tropical sea surface temperatures appear to have been a few degrees lower than today. The size of aeolian material transported by the atmosphere was considerably smaller than today, suggesting a much weaker atmospheric circulation. The notion of warmer poles with a weaker atmosphere is enigmatic without a more efficient role being played by the oceans. A variety of model simulations indicate that an increased pole-ward heat transport by the oceans has the potential to explain the early Eocene observations. A major question is whether the early Eocene climate is in response to increased levels of CO2 or to changes in continental geometry. If increased levels of CO2 can modify the nature of the thermohaline circulation and have the potential to "reverse" the current deep water circulation of the oceans, then the GCM simulations of future climate using atmospheric GCMs may be very far from an accurate picture of climatic change. The changes in the strength of the atmospheric circulation, midlatitude storminess, tropical sea surface temperatures and precipitation would produce dramatic differences in climate from current model predictions. Although the explanations of the early Eocene climate remain as unproven hypotheses, this case study suggests that explicit incorporation of the role of the ocean in future climate model predictions is essential. The investigation of the mid-Cretaceous and the early Eocene is far from a comprehensive analysis of past warm climates and their implications for future climate. The geologic record offers a wealth of case studies. The Holocene record of the last 10,000 years has the potential to provide temporal and spatial detail on decadal to century climate variability unavailable from any other data source. Other interglacial episodes, some potentially warmer than today, may provide insight into the range of interglacial climates. The Pliocene warm interval of 3-5 million years ago has the potential to provide much more abundant and more accurate climate data for an interval of warmth which is likely to generate substantial modelling study. Many of these time periods have been studied with climate models (e.g. KUTZBACH, 1985; KUTZBACH and GUETTER, 1986; KUTZBACH and GALLIMORE, 1988; CROWLEY and NORTH, 1991; KUTZBACH and ZEIGLER, 1993; VALDES, 1993). Finally, the geologic record is characterised by a number of abrupt transitions which may be a key to understanding system response and recovery from short term perturbations. The geologic record consists of numerous opportunities for comprehensive case studies which can improve our understanding of climatic change, provide a valuable time perspective on global change and challenge our constructs of how the Earth system operates.
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Warmer worlds: global change lessons from earth history tion of Antarctic glaciation: oxygen and carbon isotope analysis in DSDP sites 277, 279 and 281.
Initial Reports of the Deep Sea Drilling Project, Vol. 219. Government Printing Office, Washington, DC, pp. 743-755. SLOAN, L. C. and BARRON, E. J., 1990. "Equable" climates during Earth history. Geology, 18: 489492. SLOAN, L. C. and BARRON, E. J., 1992. A comparison of Eocene climate model results to quantified paleoclimatic interpretations. Palaeogeogr., Palaeoclimatol., Palaeoecol., 93:183-202. SMILEY, C. J., 1967. Paleoclimatic interpretations of some Mesozoic floral sequences. AAPG BulL, 51: 849-863. SPELMAN,M. J. and MANABE, S., 1984. Influence of oceanic heat transport upon the sensitivity of a model climate. J. Geophy. Res., 89: 571-586. SPICER, R. A. and CORFIELD, R. M., 1992. A review of terrestrial and marine climates in the Cretaceous with implications for modelling the 'greenhouse earth'. Geol. Mag., 129" 169-180. SPICER, R. A. and PARRISH, J. T., 1990a. Late Cretaceous-Early Tertiary palaeoclimates of northern high latitudes: a quantitative view. J. Geol. Soc., London, 147: 329-341. STONE, P. H., 1978. Constraints on dynamical transports of energy on a spherical planet. Dyn. Atmos. Oceans, 2: 123-139. TALLEY, L. D. and MCCARTNEY, M. S., 1982. Distribution and circulation of Labrador sea water. J. Phys. Oceanogr., 12:1189-1205. THOMAS, E., 1989. Mass extinctions in the deep sea in global catastrophes in earth history. Geol. Soc. Am., Spec. Pub., Boulder, CO. VALDES, P., 1993. Atmospheric general circulation models of the Jurassic. Philos. Trans. R. Soc. London, Ser. B, 341: 317-326. WALKER, J. C. G., 1982. Climatic factors on the Archean earth. Palaeogeogr., Palaeoclimatol., Paleoecol., 40:1-11. WING, S. L. and GREENWOOD,D. R., 1993. Fossils and fossil climate: the case for equable continental interiors in the Eocene. Proc. R. Soc., 341: 243-252. WOLFE, J. A., 1980. Tertiary climates and floristic relationships at high latitudes in the Northern Hemisphere. Palaeogeogr., Palaeoclimatol., Palaeoecol., 30: 313-323. WOLFE, J. A. and UPCHURCH, G. R., 1987. North American nonmarine climates and vegetation during the Late Cretaceous. Palaeogeogr., Palaeoclimatol., Palaeoecol., 61: 33-77. ZACHOS, J. C., STO~, L. D. and LOHMANN,K. C., 1994. Evolution of Early Cenozoic marine temperatures. Paleoceanography, 9: 353-387.
94
Chapter 4
Catastrophe" impact of comets and asteroids MICHAEL R. RAMPINO
Introduction
Long before comets were known to be large bodies travelling through the Solar System, they were feared as bad omens, with changes in the weather as one of their possible effects. The discovery of the true nature of comets in the 1600s soon led to dramatic theories of the Earth involving comets and their catastrophic effects on climate. For example, in his "New Theory of the Earth" (1696) WILLIAMWHISTON proposed a cosmogeny in which our planet originated when a comet was transformed into an ideal world, with a circular orbit, and without tilt or rotation. Later, God sent another comet towards the Earth, and its collision changed the planet's orbit and started it rotating. The impact cracked the crust, releasing the waters of the Flood, while the vapours of the comet's tail condensed into torrential rainfall. By the 18th century, calculations showed that large comets might commonly cross the path of the Earth, and scholarly reports of the possible catastrophic climatic effects of comet collisions or near-collisions produced panics among the general populace (HEUER, 1953). In the uniformitarian view of the geologic record, proposed by James Hutton, and codified by CHARLES LYELL in his "Principles of Geology" (1830-1833), the use of such extraordinary events to explain geologic changes was rejected. Past climatic fluctuations were attributed by Lyell to gradual geologic processes, such as changes in the distribution of land and sea resulting from erosion and uplift. Lyell specifically maintained that drastic shifts in climate could occur "without help from a comet, or any astronomical change" (quoted in MARVIN, 1990). We now know that collision of extraterrestrial bodies with the Earth represents a natural process that can be observed during meteorite falls and airbursts (CHAPMANand MORRISON, 1994). The size distribution of comets and asteroids that move through the Solar System on Earth-crossing orbits and the record of impact craters on the terrestrial planets can be used to determine the average intervals between impacts of various sizes. Like many such natural processes, impacts follow an inverse power law distribution, and large bodies, - 5 - 1 0 km in diameter, are expected to hit the Earth about every 20-100 million years (BARLOW, 1990; SHOEMAKER et al., 1990). Although a number of modern studies prior to 1980 discussed the possible climatic, biological and geologic effects of a large planetesimal impact (e.g. DELAuBENFELS, 1956; UREY, 1973; NAPIER and CLUBE, 1979), little attention was paid to this work until the publication of geochemical evidence for a major asteroid or comet impact at the end of the Cretaceous Period (--65 million years ago) by the Alvarez group at Berkeley (ALVAREZ et al., 1980) and others (SMIT and HERToGEN, 1980; GANAPATHY, 1980). The major geological boundary
95
Catastrophe: impact of comets and asteroids
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Fig. 1. Iridium measurements at the K/T boundary at Gubbio, Italy (GLEN, 1990, after ALVAREZet al., 1980). The 4-m section shown represents about 750 000 years. between the Cretaceous and the subsequent Tertiary Periods (the so-called K/T boundary) is marked by the mass extinction of some 75% of the species of marine organisms (RAUP, 1992) including more than 95% of marine plankton and the apparently sudden extinction of the dinosaurs (SHEEHAN et al., 1991) and other terrestrial animals and plants (JOHNSON, 1992a). Discovery of anomalous concentrations of iridium and other trace elements in a thin globally distributed clay-rich layer that occurs in geologic sections coincident with the K/T boundary (Fig. 1) was followed by reports of microspherules of various composition, diagnostic shock-deformed minerals, glassy microtektites and impact-wave deposits (e.g. ALVAREZ, 1986; ALVAREZ and ASARO, 1990; SIGURDSSON, 1990; SMIT, 1990; SMIT et al., 1992). The evidence is now overwhelming that the basal few millimetres of the clay layer represents ejecta from the impact of a large asteroid or comet on the Earth (e.g. GLEN, 1990). A large (>200 km diameter) candidate crater, the Chicxulub impact structure in northern Yucatan (HILDEBRANDet al., 1991) dates from 65.2 _+0.4 Ma (SHARPTONet al., 1992). The apparent coincidence of the impact (or impacts) with the abrupt extinctions, including that of the dinosaurs and the possibility that climatic and environmental changes caused by the impact led to the extinctions, revived interest in the physical effects of large impact events. Although much attention has been focused on the relatively short-term (immediate to several hundred thousand years) effects of impacts on the environment, the possibility also exists that impact perturbations can trigger or set in motion longer term environmental
96
Theoretical estimates of impact-induced climate change and geological changes, such as ice ages (e.g. KYTE et al., 1988) or pulses of volcanic and/or tectonic activity that might, in themselves, affect long-term global climate (UREY, 1973; NAPIER and CLUBE, 1979; RAMPINO and STOTHERS, 1984a,b, 1988; RAMPINO and CALDEIRA, 1993). The possible connection between climatic change and mass extinctions has been a muchdebated subject, with some arguing that extinctions are generally related to cooling of the climate (e.g. STANLEY, 1984, 1988), while others have implicated warming in massextinction scenarios (e.g. MCLEAN, 1978). Estimates of climatic and environmental changes that might be caused by the impact of large extraterrestrial bodies have been approached in two basic ways: theoretical studies that attempt to estimate the kinds and magnitudes of climatic and geologic changes that impacts of various sizes might induce and study of proxy environmental and climate indicators in the geologic record at times of documented or suspected large-body impacts and associated mass extinctions.
Theoretical estimates of impact-induced climate change Global dust cloud Cosmic objects greater than a few kilometres in diameter, travelling tens of km s-1, release 107-108 megatonnes of TNT equivalent energy on impact with the Earth and are capable of producing global-scale dust clouds (Fig. 2). Events such as these are estimated from the population of Earth-crossing asteroids and comets to occur on time-scales of tens of millions of years (SHOEMAKER et al., 1990; CHAPMAN and MORRISON, 1994). For example, the initial kinetic energy of a 10 km diameter asteroid travelling at --20 km s-1, such as has been proposed to have caused the K/T mass extinction, is estimated at between --1024 and 1025 J (>108 Mt of TNT equivalent). Comets travel at higher velocities (up to --70 km s-1) and hence the impact of a significantly smaller comet can produce an explosion equivalent to
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97
Catastrophe: impact of comets and asteroids that of a 10 km asteroid. In such an impact, > 1016 g of excavated rock and vaporized asteroid, crust (and possibly ocean water) can be launched ballistically to >100 km and ~ 10-20% of these ejecta might be distributed globally (O'KEEFE and AHRENS, 1982a,b; MCLAREN and GOODFELLOW, 1990). The large amount of fine ejecta that was apparently distributed worldwide by the K/T boundary impact could have created a dense dust cloud while in the atmosphere and ALVAREZ et al. (1980) suggested that the darkness and short-term surface cooling beneath such a cloud led to cessation of photosynthesis and frigid conditions (impact winter), resulting in the observed mass extinctions. Calculations suggest that the solar transmission reduction resulting from a dust injection of>1016 g (only 0.01 times the mass of a 10 km diameter object) uniformly over the surface of the Earth would reduce photosynthesis by a factor of
105 (GERSTL and ZARDECKI, 1982) and could lead to a collapse of marine and terrestrial food chains. Initially, the Alvarez group estimated that the duration of the global dust cloud would have been several years, based on atmospheric opacity increases after historical volcanic eruptions. However, such relatively long-lived volcanic effects are the result of volcanogenic sulphuric acid aerosols in the stratosphere (RAMPINO and SELF, 1984) - volcanic dust settles out largely within 3-6 months - and thus the K/T boundary dust cloud would most likely have dissipated in a few months (POLLACK et al., 1982; TOON et al., 1982). Calculations (MILNE and MACKAY, 1982) and experiments (GRIFFIS and CHAPMAN, 1988) suggest that even a few months of such darkness would have been sufficient to produce the degree of extinction seen among pelagic phytoplankton at the K/T boundary, breaking the food chain. Analysis of carbon and nitrogen in the K/T boundary clay suggests that the amounts of incorporated marine and terrestrial biomass are approximately equivalent to the entire global standing biomass that would have been swept out of the ocean and buried by the ejecta and/or burned in global wildfires (GILMOUR et al., 1990). Predicted climatic effects from impact produced dust clouds are always severe, but to some extent model dependent. TOON et al. (1982) used a 1-D model of aerosol physics and a onedimensional radiative/convective climate model to calculate the evolution and climatic effects of such a dense dust cloud with an atmospheric lifetime of 3-6 months. Model results suggested that light levels would have remained too low for visibility for up to 6 months and too low for photosynthesis for up to 1 year after the impact. Calculations of surface cooling showed reductions in continental temperatures to below freezing for up to 2 years, whereas ocean-surface temperatures fell only a few degrees (Fig. 3). Increased reflectivity from snow cover in continental interiors might provide a positive feedback process that could prolong cooling once the dust settled out of the atmosphere (TOON et al., 1982). Possible changes in atmospheric thermal structure were also investigated in a similar model study by POLLACK et al. (1982). In normal times, solar energy is absorbed by the ground and the infrared emission back to space comes largely from the upper troposphere. At times of heavy dust loading, however, both the solar energy deposition level and the infrared emission level of the atmosphere are controlled by the dust and both lie within the stratosphere. The surface no longer receives any solar radiation and has a net energy deficit. Under these conditions, drastic surface cooling is inevitable and POLLACK et al. (1982) predicted land-surface temperature decreases of-30~
in the first 1-2 months after impact of a
10 km diameter body. Furthermore, these modelling studies did not include the possible ef-
98
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Time (Seconds) after Impact Fig. 3. Estimates of the reduction in global temperatures as a result of a global cloud of fine dust produced by a 10 km diameter asteroid collision, using a one-dimensional radiative-convective climate model (open squares) (after TOON et al., 1982), and a 3-D Global Climate Model (diamonds) (after COVEYet al., 1990). fects of soot produced by global fires, which should exacerbate the situation (CROWLEY and NORTH, 1991). More recently, COVEY et al. (1990) utilized a more sophisticated three-dimensional global climate model (GCM) to study the effects of an impact-induced global dust cloud on climate. For a dust loading of 5 • 1015g after a 10 km diameter impact, their results were qualitatively similar to the earlier one-dimensional model results, although in the GCM land-surface cooling was somewhat mitigated by the heat capacity of the oceans and by atmospheric circulation patterns set up by the dust cloud that transported additional heat from the oceans to land areas. In this simulation, however, fixed sea-surface temperatures exaggerated the oceanic heat reservoir, providing an unrealistic situation. Land-surface cooling was less than that of POLLACK et al. (1982) by more than a factor of two, but the landsurface temperatures fell below freezing in less than a week (decreases of about 15~ compared to nearly 2 months in the one-dimensional simulation (Fig. 3). GCM studies also suggest an almost complete collapse of the hydrologic cycle after the impact. The GCM model results indicated that impacts of smaller objects (~1 km diameter) could cause less severe, but still quite significant decreases in temperature (-5~ over the continents within 20 days of impact. Such rapid and severe decreases in temperatures could have devastated global vegetation (TINUS and RODDY, 1990).
Water vapour in the atmosphere In the case of an oceanic impact, water would probably comprise a significant fraction of the ejecta lofted to high altitudes. For a 10 km impactor hitting the ocean, it is estimated that the expansion of a ,-500 km 3 steam bubble would drive a plume of mixed impactor vapour, de-
99
Catastrophe: impact of comets and asteroids bris and water vapour more than 100 kilometres above the surface (CROFT, 1982). Condensation of the cloud of water vapour and meteoroid vapour could produce a combination of dust and ice particles in the upper atmosphere (MELOSH, 1982). MCKAY and THOMAS (1982) considered the consequences of enhanced water vapour concentrations on the middle atmosphere (50-100 km) chemistry and heat budget. They estimated that the increased mixing ratio of hydrogen would have caused a decrease of ozone concentration above 60 km. The ozone reduction would lead to a lowering of the average height of the mesopause and lowering of average temperatures. These conditions were predicted to produce a long-lived (possibly 105-106 years) global layer of mesospheric ice clouds. An increase in global albedo of up to several percent is predicted from such clouds, but the net climatic effect (cooling or warming) depends upon how much infrared radiation from below is also trapped by the clouds, which is a function of the mean size of the ice crystals in the clouds. KYTE et al. (1988) suggested that similar ice clouds in the upper stratosphere following a relatively small (0.5 km diameter) ocean impact in the Late Pliocene might have triggered Northern Hemisphere Pleistocene glaciation. The size of the dust and ice grains produced in the atmosphere is also critical to the mean lifetime of the dust and ice clouds if the grains are too large, rapid fallout would occur and long-term darkness and climatic effects would be less likely. A measure of the initial grain-size distribution of material in the K/T boundary fallout layer would help in improving the understanding of the likely outcomes. The water vapour should locally supersaturate the stratosphere and thus much of the vapour might rapidly recondense and precipitate out of the atmosphere (CROFT, 1982). If the coagulation time of the water vapour is similar to that of the dust as calculated by TOON et al. (1982), then most of the water would leave the atmosphere within weeks to months. However, during this time, an enhanced greenhouse effect and reduction of stratospheric ozone could result (O'KEEFE and AHRENS, 1982b). EMILIANI(1980) and EMILIANI et al. (1982) suggested that such a water vapour greenhouse effect would cause sudden global heating and that an average global rise of only a few degrees in surface temperatures would be intolerable to many species, including reptiles weighing more than 25 kg. On the other hand, some evidence suggests that dinosaurs may have been quite adaptable to changing environmental conditions and hence climatic change alone may not have been responsible for their demise (LEHMAN, 1987). Formation of NO and acid rain effects
The shock waves from the KfI' bolide and the transfer of energy from the fine ejecta would have heated the global atmosphere. The fraction of energy transferred to the atmosphere is estimated to be ~40% (O'KEEFE and AHRENS, 1982a,b). Calculations suggest that, for a 1024 J impact, this could result in an immediate heat pulse with a global average temperature increase of >_15~ and ocean-surface temperature increases of ~5~ The high-temperature shock waves produced by the passage of the impactor through the atmosphere (TURCO et al., 1981; LEWIS et al., 1982) and interaction of the high velocity plume of ejecta with the atmosphere (O'KEEFE and AHRENS, 1982) could create large amounts of NO; PRINN and FEGLEY (1987) estimated as much as 3 x 1018 g. They predicted that the global atmosphere could be loaded with 100 ppmv of NO2, about 1,000 times more
100
Theoretical estimates of impact-induced climate change than during the heaviest air-pollution episodes today. This amount of NO 2 is enough to poison plants and animals, but it could also produce destructive nitric acid rain with a pH of ~ 1. NOx in the stratosphere would also rapidly remove the ozone layer. The large amount of fixed nitrogen deposited on the earth's surface after an impact might be denitrified to produce N20 and NO. Smog reactions, involving the oxidation of CH 4 produced by anaerobically decaying organic matter, might then lead to significant amounts of ozone in the troposphere (CRUTZEN, 1987). Production of N20 (along with CO2, HNO3 and CH4) could result in an enhanced greenhouse effect over the ~ 150 year lifetime of N20 in the atmosphere (CRUTZEN, 1987) and the N20 could also interact with the stratospheric ozone layer, depleting it over about a decade (TuRco et al., 1981). More recently, ZAHNLE (1990) estimated a much smaller total NO production of ~1014 mol from the impact of a 10 km diameter asteroid travelling at 20 km s-1. In his model, most of the global NO production came not from the initial shock wave or plume, but from the dispersed ejecta re-entering the earth's atmosphere. MELOSH et al. (1990) performed calculations on the heat emitted from these ejecta as they re-entered the atmosphere and found values that might reach 50-150 times the solar output for periods up to several hours. According to Zahnle's calculations, larger yields of NO would accompany only relatively rare grazing impacts. MACDOUGAL'S (1988) report of a global Sr-isotope spike at the K/T boundary that might indicate enhanced continental weathering supports the idea of acid rain at the boundary. The bleached white limestone beds below the boundary in Italy could have had a similar acidleached origin (LOWRIE et al., 1990). Oblique impacts were specifically investigated by SCHULTZ and GAULT (1990), who found that a 10 km object with a velocity of 20 km s-1, impacting at 10 ~ to the horizontal, could cause ricocheting fragments of size 0.1-1 km at hypervelocity, producing a global swarm of Tunguska-scale events. Nitrate production from such a swarm could greatly exceed that of a single large impactor. Energy partitioned to the target apparently increases for impact angles between 45 ~ and 15 ~, increasing the ability of the impact to vaporize potentially volatile targets (e.g. ocean water, CO2-rich terrains, sulphates). Oblique impacts also provide the possibility for inserting substantial amount of material in orbit, possibly forming a temporary debris ring around the planet. The ring shadow on the Earth's surface could create additional and extended climate changes through seasonal effects on solar insolation. Global wildfires
The immediate creation of a large, heated mass of low density air with peak temperatures of -20,000 K at the impact site and the intense heat emitted globally by the re-entering impact ejecta (MELOSH et al., 1990), are calculated to ignite combustible material and to create widespread wildfires. Large amounts of dead vegetation, killed by the lack of sunlight and the abrupt cooling (TINUS and RODDY, 1990), would have provided abundant fuel for the wildfires. The soot produced by the fires could add to the opacity of the atmosphere, exacerbating the darkness and cooling following an impact. Large amounts of such soot were discovered at the K/T boundary (estimated at > 1017 g worldwide), which supports the burning of a significant fraction of the terrestrial biomass (ANDERSet al., 1986; WOLBACH et al., 1985, 1988; GILMOUR et al., 1989). It has been estimated that such forest fires could pro-
101
Catastrophe: impact of comets and asteroids duce more than 1019 g of CO 2, 1018 g of CO, 1017 g of CH 4, 1016 g of N20 together with reactive hydrocarbons and oxides of nitrogen (NO + NO2). This might have led to an intense photochemical smog and an increase in the greenhouse effect estimated to produce a heating of ~ 10~ (CRUTZEN, 1987). Poisoning by noxious chemicals, such as polynuclear aromatic hydrocarbons (PAH) and CO from the wildfires (VENKATESANand DAHL, 1989), trace metals released by the impactor, the fires, and/or by acid-enhanced weathering (ERICKSON and DICKSON, 1987; LEARY and RAMPINO, 1990), or possibly cyanide released in a cometary impact (HSu, 1980; Hsu et al., 1982) could have contributed to the extinctions on land and in the surface oceans (DAVENPORT et al., 1990).
Impact into carbonates or evaporites Several recent studies suggest that the target material of the impact might be important in terms of climatic impact. For example, impact of a 10 km diameter asteroid into a carbonate-rich terrain (like that at Chicxulub) might lead to a release of CO2 that could increase atmospheric carbon dioxide levels by factors of 2-10. This increase in CO2 has been estimated to cause a possible rise in global temperatures of 2-10~ for 104-105 years after the impact (O'KEEFE and AHRENS, 1989). SIGURDSSON et al. (1993) noted that the proposed K/T impact site at Chicxulub in the Yucatan was underlain by thick Cretaceous evaporites including CaSO4 and that some K/T impact glasses were rich in Ca and contained up to 1% SO 3. They predicted that the total sulphur degassing from the evaporites at the Chicxulub impact site could have led to up to 1019 g of sulphate aerosols, enough to cause significant cooling after the dissipation of the short-lived dust/soot cloud and to create acid fallout equal to that proposed for the nitric acid produced by bolide-atmosphere interactions.
Other possible effects Comet showers on the Earth might be triggered by the passage of the Solar System through interstellar clouds, so that effects of the cloud encounter might coincide with comet impacts (RAMPINO and STOTHERS, 1984a, 1986). YABUSHITAand ALLEN (1989) suggested that hydrogen and dust accreted from interstellar clouds would form dust grains coated with ice in the upper atmosphere leading to global cooling and proposed that this may have happened at the end of the Cretaceous. Dust from large comets can also be swept up by the Earth both before and after collisions and ZAHNLEand GRINSPOON(1990) suggested this for the origin of extraterrestrial amino acids reported from the K/T boundary. It has also been proposed that large impacts might cause changes in the earth's rotation and tilt that could have global climatic effects (DAOHANet al., 1986), although major changes in orbital parameters from impact of a 10 km object seem unlikely.
Climatic changes from perturbations of biogeochemical cycles in the aftermath of impact-induced extinctions The Cretaceous/Tertiary boundary is marked by a major perturbation of the global carbon cycle, marked by severe reduction in pelagic carbonate deposition, decrease in biomass and
102
Theoretical estimates of impact-induced climate change oceanic productivity and changes in organic carbon deposition (Hsu and MCKENZIE, 1990). The carbon cycle involves the transfer of carbon between the solid Earth and the ocean/atmosphere system. Carbon dioxide releases associated with metamorphic decarbonation of sediments at subduction zones, mantle outgassing at mid-ocean ridges and the chemical weathering of carbonate rocks, represent the primary sources of carbon dioxide to the oceans and atmosphere. The primary source of alkalinity (excess positive charge) to the oceans is the riverine cation flux (primarily Ca 2§ and Mg 2§ derived from the chemical weathering of carbonate and silicate rocks. The two major sinks for alkalinity and carbon in the oceans and atmosphere are the deposition of shallow-water carbonate sediments and the accumulation of deep-water carbonates derived from the calcareous tests of pelagic plankton, primarily since their global dissemination in the Jurassic Period (~ 150 Ma) (BERNER et al., 1983). A major disruption of the pelagic alkalinity and carbon sinks may have occurred in the aftermath of the mass extinction and reduction in populations of calcareous plankton (~97% of planktonic foraminifera and ~88% of calcareous nannoplankton species disappeared) at, and/or very close to, the designated K/T boundary (THIERSTEIN, 1982a,b; KELLER, 1988a,b; BARRERA and KELLER, 1990; SMIT, 1990) and the apparent reduction of ocean primary productivity in the earliest Paleocene, the so-called "Strangelove Ocean" interval (HSu et al., 1982a,b; Hsu and MCKENZIE, 1985; ZACHOS and ARTHUR, 1986). KASTING et al. (1986) performed early model calculations with a 2-box ocean model of the carbon-cycle perturbations that might accompany a large planetesimal impact. They investigated Hsu's suggestion that an impact event would cause ocean surface waters to become undersaturated with respect to calcium carbonate, leading to the extinction of calcareous organisms and also to the delay in recovery of calcareous plankton during the Strangelove Ocean period of up to 500,000 years. Global darkening could have killed off most of the existing phytoplankton within several weeks to months, while deposition of atmospheric NOx created in the impact would have lowered the pH of ocean surface waters and released COa into the atmosphere (Hsu et al., 1982a,b). However, model results indicated that, because of mixing, ocean surface waters would only remain acidified for ~20 years or less. KASTING et al. (1986) also looked at the direct input of atmospheric CO2 from a comet or from oxidation of terrestrial and marine organic matter. The net results might be a greenhouse effect raising temperatures by several degrees and perhaps a surface ocean uninhabitable by calcareous organisms for a couple of decades, but the model runs suggested that the surface waters would not remain corrosive for long and thus could not have led to the Strangelove Ocean conditions of decreased carbonate productivity. However, a longer lived event is predicted if mixing of the deep ocean was involved. For example, if all life in the oceans were to die off suddenly and if sufficient time (> 1,000 years) were allowed for the deep waters to mix upward and equilibrate with the atmosphere, then the model predicted that the CO2 partial pressure of the atmosphere might increase ~2-3 times. Ocean mixing normally takes ~ 1,000 years (perhaps longer in the latest Cretaceous), but an oceanic impact(s) might temporarily speed up mixing. Model results indicated that these events could increase atmospheric temperatures by perhaps 3-4 ~, but still would not lead to a surface ocean undersaturated in calcium carbonate for a significant period of time.
103
Catastrophe: impact of comets and asteroids Hsu and MCKENZIE (1990) thought that blooms of opportunistic species of nannoplankton might have caused repeated rapid fluctuations in CO2 exchange between the ocean and atmosphere, creating unstable climatic conditions during the early Tertiary Strangelove Ocean period, although the blooms may have been partly in response to unstable climates, suggesting possible feedbacks between biota and climate.
Ocean alkalinity crisis at the K/T boundary ? At the time of the K/T mass extinctions, the rate of pelagic carbonate accumulation apparently fell by about a factor of three (ZACHOS and ARTHUR, 1986). The latest Cretaceous deep-water carbonate accumulation rate was about 20% of the total carbonate accumulation rate in the oceans (OPDYKE and WILKINSON, 1988). This contrasts markedly with modern carbonate sedimentation, in which more than 60% occurs in deep-water environments. The estimated reduction in calcium carbonate accumulation in the earliest Tertiary means that --6 • 1012 equivalents of alkalinity and 3 • 1012 mol of carbon could have accumulated in the oceans and atmosphere each year. CALDEIRA et al. (1990) utilized a carbonate-silicate cycle model coupled to a three-box ocean/atmosphere model to investigate the effects of the reduction in pelagic productivity at the K/T boundary. Their model results predicted that curtailed pelagic carbonate deposition could have caused ocean carbon and alkalinity concentrations to increase drastically, leading to an "alkalinity crisis" in the oceans and causing major fluctuations in atmospheric carbondioxide levels and climate. In order to investigate possible processes that might mitigate such perturbations, CALDEIRA and RAMPINO (1993) developed a five-box biogeochemical model of the oceans and atmosphere, incorporating a new parameterization for carbonate deposition in shallow waters, where the flux of calcium carbonate from the mixed layer to shallow-water sediments depends on the carbonate-ion concentration and temperature of the mixed layer. The model was run in a time-dependent mode, in which all pelagic carbonate and organic carbon production was instantaneously set to zero. Because the carbonate flux from the ocean-surface layer to the deep ocean was eliminated and because this flux carries more alkalinity than carbon, the short-term (less than -300 years) effect of this productivity crash was to cause a slight reduction in deep-ocean carbonate-ion concentration (Fig. 4a), which caused a reduction in the area of carbonate accumulation (Fig. 4b). This is consistent with evidence of increased dissolution of pelagic carbonate sediments just after the K/T boundary event (ZACHOS and ARTHUR, 1986; STOTT and KENNETT, 1990). In shallow continental shelf sections, carbonate dissolution at the K/T boundary seems to have ranged from negligible (KELLER, 1989a,b) to considerable, most likely depending on local conditions. In the model, as the pelagic biological carbon pump is turned off, CO2 begins to outgas from the surface oceans, increasing atmospheric CO2 levels (Fig. 4c). The elevated atmospheric CO2 causes an increase in the rate of chemical weathering of silicate and carbonate rocks. The elimination of the biological carbon pump in the model also increased total dissolved CO2 in the surface oceans causing carbonate-ion concentration to drop on the 1001,000 year time-scale. According to OPDYKE and WILKINSON (1990), this would act to reduce shallow-water carbonate accumulation and such conditions might also favour dolomitization in shallow-marine settings. Lowermost Tertiary sediments in the shallow-shelf
104
Theoretical estimates of impact-induced climate change
<1
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Time After Cessationof Pelagic Productivity(yr)
Fig. 4. (a) Model results for carbonate-ion concentration as a function of time after the K/T extinction of calcareous plankton. Note that the horizontal time axis is logarithmic. (b) Model results for effective fractional area of the deep-sea floor that was accumulating carbonate. This variable is computed based on deep-ocean carbonate-ion concentration as a function of time, ocean hypsometry, the saturation constant for calcite and aragonite as a function of pressure, and the estimated calcite to aragonite productivity (see text). The horizontal time axis is logarithmic. (c) Model results for atmospheric pCO 2 as a function of time, shown on linear and logarithmic scales (after CALDEIRA and RAMPINO,
1993).
Brazos River, Texas boundary section contain dolomite, which is absent from the uppermost Cretaceous deposits (BARRERA and KELLER, 1990). After about 1,000 years of the model run, the ocean has largely completed its outgassing and the influx of alkalinity from rivers begins to make the oceans more alkaline, drawing atmospheric CO2 back into the oceans. From ~ 1,000-10,000 years, the influx of carbon and alkalinity from rivers that is not balanced by pelagic carbonate accumulation begins to overw h e l m the effects of reduced carbon pumping to the deep sea and both deep-ocean and surface-ocean carbonate-ion concentrations begin to rise (Fig. 4a), causing a near-exponential decrease in atmospheric pCO2. From that time up until about 100,000 years, a less steep exponential drop in atmospheric pCO2 level occurs. This may be related to the fact that
shallow-water carbonate sedimentation might for a time exceed the influx of carbon and alkalinity from rivers. In the revised model, the carbonate-ion concentrations of the surface and deep ocean stabilized within about 20,000 years, as a result of the increased shallowwater carbonate accumulation. Between about 105 and 106 years, total carbonate sedimentation is again in balance with chemical weathering and the atmospheric pCO2 level slowly decays to an equilibrium value.
105
Catastrophe: impact of comets and asteroids Within about 1,000 years after the cessation of pelagic productivity, the carbon-isotope value of the surface-ocean layer in the model became as great as that of the deep ocean. From about 103 to 106 years after the productivity turn-off, both the deep-ocean and surface carbon-isotopic signals moved towards the model's pre-cessation mixed-layer value. KUMP (1991) came to similar conclusions regarding carbon-isotopic behaviour using a somewhat different model. Within a million years, the system approaches a new steady state and the isotopic composition of pelagic carbonate in the model (neglecting the effects of organic carbon burial) once again equals the pre-cessation value. The deep-ocean ~13C values in the model actually became greater than those of the surface ocean approximately 1,000 years after the cessation of productivity. This effect lasted for roughly a million years. This trend is seen during the post-K/T boundary "Strangelove Ocean" interval in a number of ocean drilling sites (e.g. ZACHOS and ARTHUR, 1986).
Plankton extinction, DMS reduction and possible climatic warming Another possible climatic effect resulting from the mass extinction of marine organisms was investigated by RAMPINO and VOLK (1988). Marine phytoplankton release the gas dimethyl sulphide (DMS), which oxidizes to form sulphuric acid aerosol that may be the precursor for most cloud condensation nuclei (CCN) over the oceans (see Chapter 9 by WANG).If the total liquid water content in the clouds is held constant, changes in the number density of CCN would affect the size of droplets in the cloud, which affects the cloud reflectivity or albedo. Modelling has quantified the effects of either increasing the number density of cloud droplets, which increases the cloud albedo, or decreasing the number density with its associated decrease in the cloud albedo. The extinction of almost all marine calcareous phytoplankton at the K/T boundary would have drastically reduced output of DMS and thus cloud condensation nuclei. RAMPINO and VOLK (1988) used model results that showed the effect upon stratiform topof-cloud albedo due to variations in the CCN number density, along with Global Climate Model (GCM) results to convert the equivalent changes in incoming solar radiation into changes in global average surface temperature. For a DMS reduction o f - 8 0 % from the reference value, global temperature was predicted to rise by more than 6~ and by nearly 10~ when the DMS is reduced by 90%. Even a 50% reduction in DMS should produce a significant global warming of 3-4~ The thermal mass and mixing structure of the ocean would delay the full surface warming by several thousand years. These results indicate that a drastic reduction in DMS production, if maintained, could lead to a substantially warmer Earth essentially simultaneous with the phytoplankton extinction event. This issue is also discussed in Chapter 14 by PENG. As noted above, several authors have suggested that a greenhouse warming from increased atmospheric CO2, N20, CH4 and/or H20 could have taken place at the K/T boundary. A considerable decrease in marine cloud albedo could have provided an independent mechanism for climate warming. This global heating could have contributed to extinctions subsequent to the impact and initial plankton destruction. A severe climatic warming might also inhibit the full recovery of the marine biosphere and may have contributed to the maintenance of low productivity Strangelove Ocean conditions for 105 years or longer.
106
Evidence of environmental perturbations at the K/F boundary Evidence of environmental perturbations at the KfI' boundary In addition to the extinctions themselves, several lines of evidence point to a trauma in the global biosphere at the K/T boundary. Carbon isotope analyses provide a proxy for fluctuations of marine productivity and burial rates of organic carbon. Sedimentological/stratigraphic studies of pelagic and continental shelf sections contain data on accumulation rates of carbonate, organic carbon, amount and composition of detrital components and evidence for varying degrees of dissolution, diagenesis and precipitation of non-biogenic carbonates at the boundary. Proxy paleotemperature analyses from oxygen-isotopic variations in marine carbonates and paleo-floral/palynological studies of terrestrial boundary sections provide a record, albeit problematical, of Late Cretaceous to Early Tertiary climate changes.
Carbon isotope and carbonate changes 't
Many studies report a significant negative anomaly in 613C of up to 3 parts per thousand (per mil) in the carbonate fine fraction ( < 63/~m, largely nannoplankton debris) and in individual planktonic foraminifera, in K/T boundary sediments (Fig. 5). This anomaly appears to be a worldwide phenomenon and it indicates a surface ocean of very low primary productivity, the so-called Strangelove Ocean (Hsu and MCKENZIE, 1990). In the South Atlantic, for example, the carbon isotope anomaly begins just above the K/T boundary (as marked by the iridium anomaly in the boundary clay) and reaches the minimum value -50,000 years later; 613C values did not return to their pre-boundary values for at least 300,000 years and 600
Lithology
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Fig. 5. Detailed K/T boundary section from Agost, Spain showing negative oxygen- and carbonisotope shifts at the K/T boundary (as marked by an iridium anomaly), and severe reduction in pelagic biogenic calcium carbonate deposition (after SMrr, 1990).
107
Catastrophe: impact of comets and asteroids possibly up to 1 Ma, after the K/T event (ZACHOS and ARTHUR, 1986). The magnitude of the 613C decrease varies somewhat from locality to locality and it has been detected solely in surface-water calcareous organisms (ZACHOS and ARTHUR, 1986). As noted above, the K/T boundary is also commonly marked by a drastic reduction in CaCO 3 deposition in the deep sea, reflecting primarily the mass extinction of calcareous nannoplankton and planktonic foraminifera (Fig. 5). CaCO 3 deposition was depressed for at least 300,000 years, possibly as long as 1 Ma, in some areas. This decrease in carbonate was apparently the result of a severe decrease in surface primary production and not of a longterm dissolution event. Benthic foraminifera were apparently less affected by the K/T boundary event (e.g. KAIHO, 1992; WIDMARK and MALMGREN, 1992), supporting the idea of a primarily surface-ocean perturbation.
Oxygen-isotopic studies and paleotemperatures Oxygen-isotope data from marine carbonates have been used in many studies as an estimator of ocean temperatures at the K/T boundary. In most studies, a 0.2 per mil change in 6180, other things (e.g. salinity, isotopic composition of seawater as affected by, for example, ice-sheet volume) being equal, is inferred to be equivalent to a --I~ temperature change. However, a number of problems exist in the use of 6180 as a measure of oceanwater temperatures at the time of deposition of the sediment, as well as in correlating isotopic data from site to site at the K/T boundary (e.g. JONES et al., 1987; ZACHOS et al., 1989a,b). These problems include: (1) Diagenesis: post-depositional alteration, which includes dissolution and re-precipitation of calcium carbonate on the sea floor and after burial. (2) Vital effects and depth-habitat variability: the calcareous components analysed for surface-water temperature estimates include various species of planktonic and benthic foraminifera together with bulk samples and fine-fraction carbonate, which are inferred to consist mainly of coccoliths. The mix of species can be quite variable from one site to another and thus differences in the depth zone in which calcification takes place among calcareous plankton and species-specific vital effects in isotope fractionation, can affect the isotopic composition of bulk material (ZACHOS et al., 1989a,b). (3) Stratigraphic problems: the problem of correlating oxygen isotope records from site to site is made difficult by the possible occurrence of minor hiatuses in many boundary sections. The stratigraphic time resolution provided by various boundary sections is variable as a result of differences in sedimentation rates, bioturbation intensity and especially in the density of sampling across the boundary. Real variations in regional paleotemperatures may also complicate correlation and the interpretation of isotopic temperature (ZACHOS et al., 1989a,b). Some ambiguity exists with regard to the salinity distribution and isotopic composition of seawater at K/T boundary time. During the Late Cretaceous, the primary mode of deepwater formation may have involved the seasonal sinking of relatively warm >8~
saline
waters in low to mid-latitude shelf and marginal sea regions. Some have suggested that the continental shelves of Antarctica were a source of Late Cretaceous ocean bottom waters in the Pacific (BARRERA et al., 1987), but study of benthic foraminifera from southern high latitudes argues against this idea (STOTTand KENNETT, 1990). Paleotemperatures for latest Cretaceous bottom waters in the South Atlantic range from -6.5 to 10~ at Deep Sea Drilling Project (DSDP) Site 527 on the Walvis Ridge in the South Atlantic (SHAcKLETON et al.,
108
Evidence of environmental perturbations at the K/T boundary 1984). Existing paleooceanographic evidence is insufficient to completely constrain Late Cretaceous/Early Tertiary ocean circulation and it is possible that patterns changed significantly in response to K/T boundary perturbations on the 105-106 year time-scale (KELLER, 1989a,b). Recently, KAJIWARA and KAIHO (1992) found evidence of positive sulphur isotope shift at the boundary indicating development of low oxygen conditions in the oceans.
Oxygen-isotopic paleotemperature studies at the K/T boundary The many published reports of oxygen-isotopic studies across the K/T boundary show a range of results. Some of the earliest oxygen-isotopic studies of pelagic sediments at the K/T boundary from Deep Sea Drilling Project (DSDP) Sites in the Atlantic Ocean (Sites 152, 356, 357, 384, Falkland and Agulhas Plateau Sites in the South Atlantic) were carried out by BOERSMA et al. (1979), who interpreted a persistent negative oxygen-isotopic excursion as evidence for a significant rise in ocean temperatures across the boundary, in both deep and surface waters. The temperature rise seems to have occurred before the early Tertiary
"Globigerina" eugubina zone (beginning -50,000 years after the boundary), so that in the oldest Tertiary sample analysed (at DSDP Site 356), temperatures were already inferred to be 3~ higher than in the latest Cretaceous. However, part of the earliest Tertiary and the very latest Cretaceous section may be missing at this and other sites (BOERSMA and
SHACKLETON, 1981; MACLEOD and KELLER,1991 a,b). At DSDP Site 384, an inferred I~ by a 2~
surface-water cooling across the boundary is followed
warming by the end of the eugubina zone (-280,000 years after the K/T bound-
ary), whereas at Site 152, there is isotopic evidence for a net surface-water cooling of 2~ across the same sampling interval (BOERSMAand SHACKLETON, 1981), although the first 150,000 years of the Tertiary may be missing at Site 384 (MACLEOD and KELLER, 1991a,b). Site 357 shows no change in surface-water temperatures across the boundary, whereas the Agulhas Plateau Site shows an inferred net 2~ ferred to exhibit a cooling of 1-3~
cooling. Deep-water temperatures are in-
at Sites 384, 356 and 357, but a warming of 1-2~
at
Site 152 and on the Agulhas Plateau. THIERSTEIN (1980, 1981) reported that a 2 per mil shift towards lighter oxygen-isotopic values at the K/T boundary at South Atlantic Site 356 (over a thickness of 40 cm) indicates either a surface temperature increase of up to 10~ or alternatively a significant salinity decrease in surface waters. Note that this does not agree with the results of BOERSMA and SHACKLETON (1981) as quoted above and a hiatus may be present in the earliest Tertiary (MACLEOD and KELLER, 1991a,b). At Site 524, in the South Atlantic, Hsu et al. (1982) reported an average 6180 excursion in the carbonate fine fraction o f - 0 . 4 per mil between preand post-boundary samples, with a difference o f - 2 per mil between extremes in the standard deviation, suggesting warmings of at least 2~ and possibly up to 10~ although here too there may be a minor hiatus. The maximum negative departure in 6180 occurs at about the same level as the most negative d l3C anomaly in the lowermost Tertiary. A negative departure in oxygen-isotopic ratios in benthic foraminifera of ~1 per mil at about the same time in some sections suggests a possible warming of ocean bottom waters by -4-5~ Late Cretaceous values (BOERSMA et al., 1979; HSU et al., 1982).
over
Boundary sections in Spain at Caravaca, Sopelana and Zumaya exhibit maximum negative 6180 excursions ranging from -1.4 to -2.4 per mil in bulk carbonate samples at or just
109
Catastrophe: impact of comets and asteroids above the K/T boundary, corresponding to possible warmings of ~7-12~
closely corre-
lated with the maximum negative 613C excursion (SMIT, 1990). Bulk carbonate from sections at Biarritz, France shows a maximum negative 6180 excursion of-1.5 per mil across the boundary and the boundary sequence at Lattengebirge in SW Germany, although possibly affected by diagenesis and containing a possible hiatus of ~200,000 years (MACLEOD and KELLER, 1991a,b), shows a negative 6180 excursion of-2.5 per mil, in both cases corresponding to the maximum 613C excursion. In the Pacific, DSDP Sites 47.2 and 577 at ~20~ paleolatitude and Site 465 at ~15~
pa-
leolatitude show little or no isotopic evidence for a significant temperature change across the KfF boundary (ZACHOS and ARTHUR, 1986). At Site 577, on the Shatsky Rise in the North Pacific, t5180 values from G. eugubina from below the KfF boundary are essentially the same as those above the boundary (GERSTEL et al., 1986). Some cooling of surface ocean waters is indicated ~20,000 years before the boundary, but some 50,000 years after the boundary may be missing in these sections (MACLEOD and KELLER, 1991a,b). It is possible that some important paleooceanographic changes preceded the recognized boundary and aberrant foraminifera in the early Tertiary may be evidence of ecological stress and/or instability of the marine environment after the boundary event. At southern high-latitude deep-water sites on the Maud Rise in the Weddell Sea (Ocean Drilling Project (ODP) Holes 689B and 690C), STOTT and KENNETT (1989, 1990) reported an oxygen-isotopic decrease of ~0.7-1.0 per mil in planktonic and benthic foraminifera beginning about 500,000 years before the KfI' boundary and a positive excursion of similar magnitude across the boundary (estimated from ~200,000 years before to ~100,000 years after). In this particularly detailed section, they interpreted the anomalies as representing a latest CretaceoUs year-round 4~
warming of Antarctic surface and intermediate waters,
followed by a similar cooling across the boundary, with return to previous paleotemperatures. The shifts in t5180 are mirrored by negative shifts in 613C and STOTT and KENNETT (1990) suggested that the two are related through feedback loops in the carbon cycle. In the Woodside Creek, New Zealand site (upper bathyal water depths, ~600-800 m), a very detailed study of the 0.6 cm thick boundary clay shows a -1.8 per mil shift in 6180 from 0 to 0.3 cm, followed by a + 1.3 per mil shift from 0.3 to 0.4 cm and a -1.0 per mil change at 0.4-0.6 cm (WOLBACHet al., 1988). The deposition time for the thin boundary clay is estimated by WOLBACH et al. (1988) at <1 year. If interpreted in terms of surface water temperatures, these isotope data would indicate rapid temperature fluctuations of _9~ coincident with the deposition of the iridium-rich layer at the K/T boundary. These drastic and immediate climatic events would have occurred before any possible changes induced by perturbations of the carbon cycle. Based on oxygen-isotopic analyses of the shallow-shelf Brazos River section of the Texas Gulf Coast, BARRERA and KELLER (1990) proposed that early Tertiary climate was unstable, with relative temperature fluctuations of +8 to -6~ beginning about 50,000 years after the K/T boundary and lasting for more than 200,000 years. JONES et al. (1987) showed that the 6~80 variations in bulk-rock carbonate in the Braggs, Alabama shelf section were most likely diagenetic. The 6180 data from benthic forams and macrofossils are enriched relative to the bulk rock and are interpreted as indicating Late Cretaceous-Tertiary continental shelf water temperatures in the range of 16-23~
at ~33~
paleolatitude, with a cooling trend of <4~ over a period of about 300,000 years across the
110
Evidence of environmental perturbations at the K/T boundary K/T boundary and a gradual warming over the next ~ 1 million years. ZACHOS et al. (1989a) performed oxygen-isotopic analyses on a few oyster shells from Braggs that showed no evidence of significant recrystallization or changes in Sr-isotope ratios that might be expected to accompany diagenetic alteration. They found evidence for only minor 6180 variations, with no apparent major temperature fluctuations and an overall 3--4~ cooling over a 3 million year period from the Late Cretaceous to Early Tertiary. However, they note that the low rates of sedimentation and the presence of a hiatus below the K/T boundary at Braggs make it impossible to resolve any brief (<100,000 years) climatic events that might have occurred at this shallow-water locality. In a very detailed study of the apparently very complete pelagic boundary sections in Agost and Caravaca, Spain, SMIT (1990) interpreted a 2 per mil negative shift in 6180, beginning at the K/T boundary and lasting for only about five thousand years, as representing a rapid warming of--8~ (Fig. 5). A sharp 2 per mil negative spike in oxygen isotope ratios, indicating perhaps 8~ warming, also occurs at the K/T boundary in Italy (CORFIELDet al., 1990), superimposed on a long-term positive shift across the boundary indicating a possible cooling trend.
Paleofloral, paleosol and other analyses In a remarkably detailed study, WOLFE (1991) reported that the K/T impact could be constrained to early June based on floral evidence at the boundary in Wyoming. Fossil aquatic leaves at the boundary apparently showed evidence of structural deformation that suggested freezing temperatures in western North America during a brief impact winter. Early studies of leaf physiognomy at the K/T boundary in the northern Rocky Mountains and Great Plains were interpreted as indicating a major temperature decline by as much as 10~ from the latest Cretaceous to early Paleocene and mean cold-month temperatures were inferred to have been well below freezing during the early Paleocene (HICKEY, 1980). However, later studies suggested that estimates of average temperatures for the early Paleocene of the northern Rocky Mountains and Great Plains apparently cannot be taken at face value. First, the inferred gradient from 46 to 56~ for the early Paleocene was most likely steeper than that for the North American continental interior today. Second, in North America today, leaf physiognomy provides estimates of average temperature that are anomalously cold (WOLFE and UPCHURCH, 1986). Third, the inferred cold temperatures are contradicted by abundant occurrences of ectothermic aquatic vertebrates such as crocodilians and by floras containing palms (UPCHURCH, 1989). Apparently, because of extinctions of mesothermal evergreen taxa at the K/T boundary, early Tertiary vegetation of the northern Western Interior and Great Plains may have been out of equilibrium with climate for a period of several million years (WOLFE, 1987). More recent work on plant fossils in the western interior of North America has been interpreted as suggesting an increase of 10~ in mean annual temperature across the K/T boundary, which persisted for 500,000 to 1 million years, followed by a decrease of 4-5~ (WOLFE, 1990). JOHNSON and SIMMS (1989) and JOHNSON and HICKEY (1990) found that plant megafossils suggest a warming in latest Cretaceous time. A brief low temperature excursion (impact winter?) may have occurred prior to the longer term warming (WOLFE and UPCHURCH, 1986, 1987). RETALLACKet al. (1987) studied paleosols in the western US and
111
Catastrophe: impact of comets and asteroids reported evidence for a transition across the K/T boundary from a seasonally dry, sub-humid environment to a humid one with waterlogged soils and much more powerful streams that cut downward into the Cretaceous. This is supported by floral evidence (UPCHURCH,1989). Acid-rain effects on the soil development at the boundary are also possible. By contrast, NICHOLS et al. (1986) reported no evidence of lasting paleoclimatological change across the boundary in western Canada and interpreted floral changes as local ecological changes. In Asia, KRASSILOV (1975) reported evidence of a cooling trend from the latest Cretaceous to the earliest Paleocene. Palynological study of the Seymour Island, Antarctica boundary section shows a lack of "warmth-loving" angiosperm species in early Paleocene strata, suggesting a possible high southern latitude cooling across the K/T boundary (ASKIN, 1990), whereas, a somewhat muted climatic effect is seen in New Zealand (JOHNSON,1992b). Clay mineral composition of deep-sea sediments may also give some indication of environmental changes at the boundary. For example, ROBERT and CHAMLEY (1990) found an increase in kaolinite at the boundary, which might indicate the effects of increased warming, although a tectonic explanation was favoured by these authors.
Climate change at the K/T boundary: summary Taken at face value, the results of paleoclimatic studies would seem to indicate significant fluctuations of global and regional climate on various time-scales prior to and subsequent to the K/T boundary event. However, after a review of the many studies presenting evidence for climatic change at the K/T boundary, it is striking that a consensus picture of the timing and degree of global climatic fluctuations across the boundary still cannot be constructed. The incongruities and conflicting results seen in the reports of climatic change at the boundary probably represent the effects of real variations in regional climate, uncertainties in salinity variations and the isotopic composition of seawater, diagenesis of carbonates, unrecognized minor hiatuses in the sections, correlation problems, inadequate and variable sampiing across the boundary, local variations in deposition rates and other factors specific to the individual studies. Thus, these results cannot be taken at face value and are difficult to correlate from one section to another. Since many of the theoretical studies predict global warming at the boundary for various reasons (e.g. greenhouse gases of various kinds, reduced cloud albedo), it is worthwhile to ask if any clear evidence of such a warming and its extent and duration, can be discerned in the paleoclimatic data. In fact, a number of the analyses suggest a possible dramatic warming of ocean surface waters by as much as 10-12~ at the boundary (e.g. BOERSMA et al., 1979; HSU et al., 1982; MARGOLIS et al., 1987; SMIT, 1990). For example, the proxy temperature data for Cretaceous/Tertiary boundary sections in Spain at Caravaca, Sopelana and Zumaya, in Denmark and at Biarritz, France have been interpreted as showing warmings of about 7-12~
which correlate closely with the maximum negative dl3C excursion.
In the South Atlantic, at DSDP Site 524, Hsu et al. (1982a,b) reported evidence for a warming of at least 2~
and possibly up to 10~ and the maximum negative excursion in
d180 occurs at about the same level as the most negative d13C anomaly in the early Tertiary. The negative departure of about-1 per mil in d180 in benthic foraminifera, in some sections, at about the same time indicates possible warming of ocean bottom waters of up to 5~ over Late Cretaceous values (e.g. BOERSMA et al., 1979; HSU et al., 1982a,b). In gen-
112
Other geological boundaries: climatic changes and possible role of impacts eral, the inferred surface-ocean temperature increases seem to be greater in European and Atlantic sites than in the Pacific. By contrast, a number of the other studies of K/T boundary sections did not identify a marked negative 6180 departure. One would expect, however, that the magnitude of any temperature increase and hence the oxygen-isotopic anomaly, might vary considerably from site to site, as seen in the record. For example, an increase in surface-water temperatures might be suppressed in the tropics. It may be significant, therefore, that some of the evidence for little or no increase in surface ocean temperatures comes from the sections at low paleolatitudes, for example, DSDP sites 47.2 and 577 at about 20~ paleolatitude and DSDP site 465 at about 15~ paleolatitude, in the Pacific. If we restrict ourselves to the most detailed 6180 studies of sections which are believed to be the most complete, then the results suggest a very brief cooling at the boundary, followed by a warming lasting at least a few thousand years (Fig. 5) (SMIT, 1990) and perl~aps as long as a few hundred thousand years, possibly with significant fluctuations of climate during that interval. The long-term (a few times 106 year) trend across the boundary seems to have been global cooling, when one compares the earliest Tertiary with the Late Cretaceous in general.
Other geological boundaries: climatic changes and possible role of impacts Recent work in paleobiology suggests that extinction events represent a different evolutionary regime from that which characterizes times of background extinction levels (JABLONSKI, 1986, although see MCKINNEY, 1987). Compilations of the ranges of various taxa show the extinction events as pulses of increased rates of extinction within a single sub-stage (an in-
60-
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o 40t"
o tO 0
9 20-
13..
--
~
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..... O .....
500
ISl .... DIII]....... e .... ~----I.... P I I I i I I~ 460
300
1
1
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200
100
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;
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Geologic time (Ma) Fig. 6. Marine mass extinctions for the Phanerozoic based on extinction rates of genera of marine organisms per geologic stage or sub-stage (data from J. SEPKOSI,a, personal communication, 1992). ~, Cambrian; O, Ordovician; S, Silurian; D, Devonian; C, Carboniferous; P, Permian; Tr, Triassic; J, Jurassic; K, Cretaceous; T, Tertiary.
113
Catastrophe: impact of comets and asteroids terval o f - 2 - 3 Ma) (SEPKOSKI, 1990, personal communication, 1991) (Fig. 6). However, plots of numbers of taxa and changes in diversity by stage or sub-stage such as Fig. 6 are of little value in detecting the true range of an extinction interval and cannot resolve an event that takes place at a narrow horizon. Because of the nature of the geologic record and limitations on sampling intervals, it is often difficult to find the true last occurrence of any particular species and hence sudden extinctions can appear to have been gradual or stepped (SIGNORand LIPPS, 1982; WARD, 1990). It is important to point out that chronostratigraphic boundaries are formally defined on the basis of first appearances or last appearances of certain taxa and not by the total number of species that disappear. However, at major boundaries coinciding with mass extinctions, using high-resolution stratigraphic techniques, it is commonly possible to identify a global horizon or horizons of "mass killing" at which time a large proportion of the biomass disappears over very brief intervals (<10,000 years and possibly instantaneously) (MCLAREN and GOODFELLOW, 1990; RAMPINO and HAGGERTY, 1994), although they may occur in a number of steps over several hundred thousand to several million years (e.g. KAUFFMAN, 1988). Many studies have sought to relate mass extinctions to changes in climate (warming and cooling) (see DONOVAN, 1989), sea-level fluctuations (HALLAM, 1989), biotic interactions and other purely terrestrial causes, perhaps in random combinations that produce ecological thresholds or times of unusual biotic stress. Some workers maintain that it is almost impossible to determine the ultimate cause of mass extinction (e.g. BUGGISCH, 1991). However, the generally minor degree of Pleistocene extinctions, at a time when climate and sealevel fluctuations were especially rapid and extreme (WISE and SCHOPF, 1981), argues against this view. By contrast, in a series of statistical studies, RAUP (1990, 1991,1992) explored the possibility that all above-background extinction pulses were related to environmental perturbations caused by large-body impacts on the Earth and found good agreement between the theoretical, impact induced extinction record and the actual record of faunal crises. DONOVAN (1989) recently claimed that each mass extinction is typified by its own unique group of chemical, physical and biological environmental conditions, which are generally different than that found at the impact-induced K/T boundary. However, if we use the K/T boundary as a model for impact-induced extinctions, we might expect other impact-related extinction boundaries to show (1) a globally synchronous or near-synchronous mass killing level, (2) evidence of extraterrestrial impact (Ir and other characteristic trace elements, shocked minerals, microspherules, tektites, tsunami beds, etc.), (3) marked negative shifts in 6180 and t~13C,(4) a positive shift in t~34S,(5) a period of reduced diversity and productivity (Strangelove ocean), followed by recovery and radiation of new forms. MCLAREN and GOODFELLOW(1990) recognized such a common sequence among extinction horizons (see also RAMPINO and HAGGERTY, 1994). The extinction horizons commonly correlate closely with perturbations in the isotope systems of carbon, oxygen and sulphur suggesting significant and sudden disturbances in ocean productivity, chemistry, circulation and climate (e.g. Hsu and MCKENZIE, 1985, 1990; AHARON et al., 1987; MAGARITZ, 1989; MCLAREN and GOODFELLOW, 1990; GOODFELLOWet al., 1992). In the past decade, a number of studies have provided evidence that extinction events visible in Fig. 6 are correlated with evidence of planetesimal impacts, which includes dated large impact craters, shocked minerals, tektites, microtektites and microspherules and element
114
Other geological boundaries: climatic changes and possible role of impacts anomalies (primarily iridium and other platinum-group elements). Shocked minerals and/or microtektites/tektites, considered the best evidence of impacts, are now well-documented at or near the end-Cretaceous (ALVAREZ et al., 1980), Late Eocene/Early Oligocene (-36 Ma) (ALVAREZ et al., 1982; GANAPATHY, 1982a), Pliocene (--2.3 Ma) (KYTE et al., 1986), endTriassic (--205 Ma) (BICE et al., 1992) and the Frasnian-Famennian (~367 Ma) (CLAEYS et al., 1992; WANG, 1992) extinction events. The K/T iridium anomaly, averaging 1,000s of parts per trillion (ppt), is globally well documented (ALVAREZ, 1986). Iridium anomalies have been searched for at other extinction boundaries and although elevated iridium levels have been found at a number of boundaries, they are generally significantly weaker (100s of ppt) than the K/T iridium anomaly (Table I) and may be associated with non-chondritic element abundance patterns (ORTH, 1989; ORTH et al., 1990). For example, the iridium anomalies at boundaries other than the K/T are found to be associated with elevated osmium concentrations, although with Os/Ir ratios 10-25 times higher than observed at the KfF boundary and thus more like those of crustal or floodbasalt volcanism sources (WANG et al., 1992). These factors have led to the general conclusion that the anomalies are probably not related to impact processes (KYTE, 1988; ORTH et al., 1990). Thus, an interesting situation exists in which iridium abundance peaks were specifically searched for at extinction boundaries, elevated Ir levels over background were found, but then were rejected as evidence of impacts for a number of reasons. However, three cases now exist where "small" iridium anomalies are accompanied by definitive evidence of impacts: (1) in the Eocene/Oligocene transition interval, the iridium anomalies commonly range from only ~50 to 200 ppt, but are associated with microtektites, clinopyroxene microspherules and shocked quartz (e.g. MONTANARI, 1990); (2) at the Triassic/Jurassic boundary, iridium peaks o f - 2 0 0 ppt over a background of ~30 ppt correlate with the occurrence of shocked quartz (OLSEN et al., 1990; BICE et al., 1992); and (3) the Frasnian/Famennian boundary in the Late Devonian is marked by multiple peaks of 75160 ppt (MCGHEE et al., 1986) and up to --300 ppt over a background of ~20-30 ppt (ORTH et al., 1990; WANG et al., 1991) in widely separated regions. Although originally interpreted as non-impact in origin, the subsequent discovery of microtektites at or near the FrasnianFamennian boundary (WANG, 1992; CLAEYS et al., 1992) points to a re-interpretation of the iridium peaks as impact-related. KYTE and WASSON (1986) searched for Ir anomalies during the entire interval from 33 to 67 Ma in a slowly deposited deep-sea core and found only the large peak at the K/T boundary and smaller peaks near the Eocene/Oligocene transition, showing that Ir anomalies are not common in the sedimentary record (see also ALVAREZet al., 1990). Recent theoretical studies (VICKERY and MELOSH, 1990) suggest that large impacts may produce relatively weak iridium anomalies, because most of the vaporized impactor is blown off the Earth in the energetic collision. The Kfr iridium anomaly may be unusually high for an impact signature because the impactor was unusually enriched in iridium, or due to exceptional preservation of the K/T boundary. Older extinction events are represented primarily in shallow-water deposits where reworking and diagenesis of sediments would be expected to dilute Ir concentrations, or change the elemental composition of trace metal anomalies (MCLAREN and GOODFELLOW, 1990). Comet impacts, although highly energetic, might produce relatively minor iridium anomalies. For example, ASARO et al. (1982) estimated that an iridium-poor comet, consisting
115
Catastrophe: impact of comets and asteroids roughly of 50% ice and 50% chondritic material, with a mass only a few percent of the K/T bolide, but with an impact velocity most likely several times higher than that of Earth-crossing asteroids, could produce an impact as energetic as the proposed 10 km diameter K/T impactor. Such a comet impact might be expected to produce only a few % as much iridium as seen in K/T boundary sections, or down in the range of hundreds of ppt Ir. With this information in mind, it may be worthwhile to reconsider the possible impact origin of iridium anomalies that have been discovered at other geological boundaries (RAMPINO and HAGGERTY, 1994) as shown in Table I. Although the chemistry and trace-element ratios of some of these layers suggests the involvement of non-impact processes (biologic, volcanic, sedimentary) in the concentration and re-distribution of the anomalous elements
(ORTH, 1989), an impact source for the iridium cannot be ruled out. Element anomalies that might be related to a large impact were also recently reported at the Ordovician-Silurian boundary in the Yukon Territory, Canada (GOODFELLOW et al., 1992) and because sampling across the boundary was spotty, an Ir peak might have been missed. An iridium peak (up to 230 ppt) and other trace-metal anomalies have now been reported at or near that boundary in China (WANG et al., 1993)
TABLE I ELEVATED IRIDIUM AT OTHER BOUNDARIES
Pliocene (-2.3 Ma) Lower/Mid Miocene (~ 15 Ma) Eocene/Oligocene (-36 Ma)
Cenomanian/Turonian (-91 Ma) Callovian/Oxfordian (~ 163 Ma) Bajocian/Bathonian (?) (176 Ma) Triassic/Jurassic (-205 Ma)
Permian/Triassic (-245 Ma)
Missippian/Pennsylvanian (-320 Ma) Frasnian/Famenian (-367 Ma) multiple peaks Ordovician/Silurian (-438 Ma)
Precambrian/Cambrian (-570 Ma)
_>5,000 ppt , Southern ocean cores (KYTE et al., 1982) 152 ppt, ocean cores (ASAROet al., 1988) -50-200 ppt, microtektites, microspherules, shocked quartz (e.g. MONTANARI,1990); correlate with isotope anomalies 5 peaks ___110 ppt, Colorado, correlate with stepwise extinctions, d180 and dil3c anomalies (ORTH et al., 1987) 1,000-2,400 ppt, Spain and Poland (BROCHWICZ-LEWINSrd et al., 1985) 3,200 ppt, ROCCHIAet al., 1986 <400 ppt, in 2 European sections (MCLARENand GOODFELLOW,1990); two layers of shocked quartz (BICE et al., 1992) 165 and 230 ppt, 2 layers, Austria, correlate with large, abrupt negative d l3c anomalies (ORTH and SHONLAUB, 1991); 90-145 ppt, in 3 sections, Carnic Alps (ODDONE and VANNUCCI, 1988); 73 and 114 ppt, India, 2 layers (BHANDARIet al., 1992); several localities in China; 100s of ppt (DAo-YI et al., 1989) 380 ppt, Texas (ORTHet al., 1986) 75-160 ppt (MCGHEEet al, 1986) to -300 ppt (PLAYFORD et al., 1984; WANGet al., 1991) in widely .separated areas. Microtektites (CLAEYSet al., 1992) 58 ppt, clay layer, Anticosti Island (no shocked quartz found) (ORTHet al., 1986), ___250ppt, Scotland (WILDEet al., 1986) 2,900 ppt, China (ORTH 1989)
For references, see text and ORTHet al. (1990), ORTH (1989).
116
Other geological boundaries: climatic changes and possible role of impacts Sudden and widespread ecological crises at a number of these boundaries are evidenced by the sudden crash of planktonic communities and by the presence of opportunistic and "disaster" forms such as stromatolites at the Permian/Triassic (SCHUBERTand BOTTJER, 1992) and Frasnian/Famennian boundaries (see ORTH et al., 1990), the fern-spore spike at terrestrial K/T boundaries (NICHOLS et al., 1986; SAITO et al., 1986) and at the Triassic/ Jurassic boundary in the Newark Basin (OLSEN et al., 1990) and a fungal spore spike and evidence of gradual ecosystem recovery at the Permianffriassic boundary in Europe (VISSCHER and BRUGMAN, 1988), Israel (ESHET, 1990) and Greenland (BALME, 1979; PIASECKI, 1984). Climatic changes at times of extinction events
A number of studies have examined climatic fluctuations at geologic boundaries that coincide with times of other known impacts, and/or mass-extinction events that might be impact related. Climatic changes and extinctions have been correlated and cause-and-effect connections were proposed in a number of cases. The ultimate causes of the climatic fluctuations are in most cases poorly known and they could well be related to impact perturbations.
Late Pliocene KYTE et al. (1981) discovered evidence (iridium, microspherules) for the impact of a small (-0.5 km) asteroid into the Southern Ocean in the Late Pliocene (about 2.3 million years ago) and later suggested that it may have triggered the concurrent latest Pliocene increase in Northern Hemisphere ice volume (KYTE et al., 1988; see also MARGOLIS et al., 1991). Detailed study of ocean drill sites in the North Atlantic shows abrupt shifts in lithology and oxygen-isotopic composition in the latest Pliocene (SANCETTAet al., 1992), with the occurrence of three especially severe glacial events between -2.4 and 2.3 Ma. SANCETTAet al. (1992) interpret the period as an "interruption" of the system, marked by a decline in primary productivity and calcite preservation, increased off-shelf transport (lowered sea level) and apparently hyper-aridity on the continents. However, the events at -2.3-2.4 Ma were apparently sudden and may constitute an abrupt steplike shift from one climate regime to another (SHACKLETONet al., 1984; RAYMO et al., 1989). Recently, a high-resolution sea-surface temperature record from the northeast Atlantic provides additional evidence of a step-like cooling of--9~ at about 2.4 Ma, coincident with near full-glacial 6180 values and the first major episode of ice rafting in the North Atlantic (DOWSETT and LOUBERE, 1992). The same Late Pliocene time interval is marked by the most recent extinction event of marine genera identified by SEPKOSKI (1990), including the disappearance of characteristic molluscan fauna in the western Atlantic (STANLEYand CAMPBELL,1985). Spectacular bone and shell beds in Florida, with mixed marine, freshwater and terrestrial organisms, including abundant aquatic birds (JONESet al., 1991), dated at between -2.5 and 2 years, suggest some kind of catastrophic event(s). The period also correlates with extinction of many forestadapted species of mammals and important changes in hominid evolution in Africa, with the first appearance of the genus Homo (STANLEY,1992).
117
Catastrophe: impact of comets and asteroids Eocene-Oligocene The Eocene-Oligocene boundary has been dated at 36.4 years in the most widely used recent geologic time-scale, although younger ages (33-34 years) have been suggested (MONTANARI, 1990; SWISHER and PROTHERO, 1990). Biotic changes seem to have begun in the middle Eocene and marine species apparently suffered a ~35% extinction from Late Eocene through Early Oligocene time (RAuP, 1992). This interval of transition from the Late Eocene to the Early Oligocene is marked by a number of indicators of extraterrestrial impacts, including a double iridium anomaly (GANAPATHY, 1982a,b; MONTANARI, 1990), shocked quartz, the North American tektite strewn field (GLASS, 1982) and several microtektite layers in the ocean (GLASS, 1982; D'HONDT et al., 1987; MILLER et al., 1987). The large (~100 km diameter) Popigai impact structure in Siberia is radiometrically dated at 39 _+3 Ma, within the Late Eocene-Early Oligocene crisis interval (GRIEVE, 1991). In pelagic environments, the Late Eocene/Early Oligocene biotic changes in plankton seem to have been stepwise over 1-2 million years (KELLER, 1986) and some steps may correlate with the microtektite and Ir layers. For example, each of the microtektite horizons identified by KELLER (1986) seems to have had some effect on microplankton communities, producing stepwise events of accelerated faunal turnover characterized by generally less than 15% species extinction. The relative species abundance changes at each stepwise extinction event, however, indicate a turnover involving >60% of the population. The final plankton extinction was selected as the formal epoch boundary (CORLISSet al., 1984). The Eocene-Oligocene transition is marked by an abrupt global increase in 6180 of 1.52 per mil in planktonic foraminifera that represents one of the major steps in Cenozoic ODP Leg 120 Site 748
5!80 PDB (~).
IRD Concentration grains/g
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300
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Fig. 7. dt180 values from benthic foraminfera and ice-rafted debris (IRD) distribution for the 3436 Ma interval at Ocean Drilling Project Site 748 on the Kerguelen Plateau in the Southern Ocean. Rapid glaciation and climate cooling are indicated by thc spike of ice-rafted sediment near the Eocene/Oligocene boundary. Chrons are periods of normal (black) and reversed (white) global magnetism (after ZACHOSet al., 1992).
118
Other geological boundaries: climatic changes and possible role of impacts cooling (THUNELL, 1981, MILLER et al., 1987). An abrupt increase in 6180 in benthic foraminifera of >1 per mil, indicating either cooling of deep waters, ice-volume increases, or some combination of the two, also marks the E/O transition interval (ZACHOS et al., 1992). The first indications of probable Antarctic glacierization at sea level are ice-rafted sediments in Middle Eocene (--45.5 Ma) deposits on the Maud Rise and Kerguelen Plateau, but a distinct strengthening of glacial conditions and the apparent onset of continental East Antarctic glaciation is recorded by abundant ice-rafted debris on the Kerguelen Plateau in the earliest Oligocene (--36 and 35.8 Ma). The occurrence of Nothofagus (southern beech) and relatively warm sea-surface temperatures around Antarctica suggest temperate conditions close to the ice sheet (EHRMANN and MACKENSEN, 1992; MACKENSENand EHRMANN, 1992). ZACHOS et al. (1992) found that the same transition may be a very rapid climatic change, marked by a spike of ice-rafted sediment in the southern Indian Ocean (ODP Site 748 on the Kerguelen Plateau) and by rapid shifts in the carbon- and oxygen-isotope records. Although the oxygen-isotopic shift is permanent, the pulse of ice rafting apparently lasted less than 100,000 years (Fig. 7), perhaps as little as 10,000 years! They interpreted this as indicating the brief appearance of a large Antarctic ice sheet during the transition from a non-glaciated to a glaciated world.
Late Triassic BICE et al. (1992) discovered two layers of shocked quartz at the Triassic-Jurassic (Tr/Jr) boundary (--205 Ma, but perhaps as young as 201 Ma), indicating multiple impacts, and the best estimated age of the --100 km wide Manicouagan crater in Quebec is indistinguishable from the estimated age of the boundary (OLSEN et al., 1990). Trace metal anomalies, including Ir (--200-400 ppt), are reported to occur in two European sections (Kendelbach, Austria and Audries Bay, England) (MCLAREN and GOODFELLOW, 1990), associated with a negative d 13C anomaly. The vertebrate faunal and floral transition are apparently quite marked in the Newark deposits of eastern North America, where the pollen and spore transition, showing a fern spike followed by gradual replacement of flora, took place in <20,000 years; the vertebrate extinction may have occurred over a period <700,000 years, but is less well constrained
(OLSEN et al., 1990). WEEMS (1992) argues that the vertebrate extinctions were gradual or perhaps stepwise (see also BENTON, 1985, 1986), but his arguments are based largely on tabulations of family diversity of vertebrates, with limited time resolution of possible abrupt killing events in the record (see MCLAREN and GOODFELLOW, 1990). Marine groups also show a rapid extinction and the few calcareous nannoplankton then in existence exhibit an almost complete turnover at the boundary (HALLAM, 1990). The latest Triassic climatic record is, however, still rather poorly known (e.g. SIMMS, 1990; WEEMS, 1992; DICKINS, 1993). Negative shifts in oxygen- and carbon-isotope ratios have been noted in some European boundary sites (MCLAREN and GOODFELLOW, 1990). The post-Triassic disappearance of Alpine reefs was attributed to cooling, but isotopic measurements across the Tr/Jr boundary that suggest a temperature decrease may be problematic (HALLAM, 1990). A major increase in rainfall is indicated in some continental areas in the mid-Carnian, succeeded in the Norian by more arid climates (climatic cooling?) (SIMMSand RUFFELL, 1990; WEEMS, 1992), and JOHNSON and SIMMS (1989) suggested a causal con-
119
Catastrophe: impact of comets and asteroids nection with the Late Triassic extinctions. These changes could have occurred in the wake of large-body impacts, but a causal connection between the impact event(s) and Late Triassic climatic shifts is not yet convincing.
Permian-Triassic The Permian-Triassic (P/Tr) boundary (-250 Ma) is marked by the disappearance o f - 9 6 % of marine species (RAUP, 1979), 99% of reptile genera and a major floral extinction, including the abrupt obliteration of the diverse Glossopteris flora in the Southern Hemisphere (TIWARI and VIJAYA, 1992). Sudden disappearance of Late Permian palynomorphs, a global spike in fungal spores and vast numbers of acritarchs at the boundary horizon around the world (e.g. Israel, Greenland, Australia, Pakistan) indicate a sudden global catastrophe, followed by a disaster ecology (Fig. 8) (e.g. BALME, 1979; PIASECKI, 1984; VISSCHER and BRUGMAN, 1988; ESHET, 1990). Planktonic (including foraminifera and radiolaria) and nektonic groups and groups with planktonic growth stages, also show a sudden crash at the boundary (VALENTINE, 1986; LI et al., 1991). Shallow water faunas in the earliest Triassic are depauperate, whereas algal mats (another post-disaster form) suddenly become widespread (see various papers in CASSINIS, 1988). The end-Permian extinctions are commonly regarded as gradual in nature and or composed of a series of extinction episodes from mid-Permian to early Triassic (MAXWELL, 1989, 1992). However, MCLAREN and GOODFELLOW (1990) summarized the ways in which problems related to the official definition of the P/Tr boundary (e.g. first appearances versus last appearances of different groups of organisms) and problems in correlation and sampling have tended to obscure the fact that the major extinctions and biomass loss apparently took place over a time no longer than a few times 10,000 years at the end of the Permian and they concluded that extraterrestrial impact was very probably the ultimate cause of the global Permian-Triassic killing event. The P/Tr boundary is also marked by sudden shifts in carbon, oxygen (SWEETet al., 1992), sulphur (LI et al., 1991) and strontium isotope ratios and by europium and cerium anomalies (DAO-YI et al., 1989; BHANDARIet al., 1992; CHIFANG et al., 1992; GRUSZCZYNSKIet al., 1989, 1992). The entire carbon-isotope excursion is protracted over a period of about 2 million years in the Carnic Alps, (HOLSER et al., 1991; HOLSERand MAGARITZ, 1992) but the major negative isotope shifts of-1.5 and 2 per mil take place rapidly in two abrupt (<50,000 years) events that coincide with abrupt negative shifts in 6180 (Fig. 9). In the southern Alps, the abrupt negative shift in 6180 of more than -4 per mil coincides with a sudden negative 613C excursion of-1.5 per mil (MAGARITZ et al., 1988). If the entire 6180 signal is related to paleotemperature changes, then a drastic warming is indicated. A marked positive shift in ~34Sat the boundary indicates the development of anoxic conditions in the oceans. Two iridium anomalies, coinciding with the two major negative 613C shifts, mark the boundary in a number of localities (e.g. CASSINIS, 1988; BHANDARIet al., 1991; HOLSER et al., 1991) (Table I) (Fig. 9). A larger Ir anomaly reported from Chinese sections (e.g. 2,000 ppt at Shangxi; Xu et al., 1985) has not been reproduced (ZHOU and KYTE, 1988), but this may be a function of sample inhomogeneities. Microspherules are apparently abundant in the boundary clay (see DAO-YI et al., 1989). This is similar to the lower part of
120
Other geological boundaries: climatic changes and possible role of impacts
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121
Catastrophe: impact of comets and asteroids
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the Chicxulub (?) impact layer in the western US - low iridium, abundant spherules. However, large impacts are known or suspected to have occurred at or near the P/Tr boundary; the --40 km wide Araguinha impact structure in Brazil has an 4~ age of 247 _.+5.5 Ma (ENGELHARDT et al., 1992) and two very large (200-350 km wide) impact structures of possible Latest Permian age (-248 Ma) have been reported on the Falkland Plateau (Fig. 10) (RAMPINO, 1992).
VALENTINE (1986) suggested that extinction of planktotrophs might have resulted from climatic changes involving high seasonality accompanying the assembly of Pangaea, whereas regression of shallow seas could have led to decreased habitat space for marine organisms. STANLEY (1988) argued that drastic cooling of the climate was the only reasonable cause of the extinctions and suppression of reef organisms for millions of years, whereas WATER
122
Other geological boundaries: climatic changes and possible role of impacts TABLE II CONTINENTAL FLOOD BASALTS AND TIMES OF MASS EXTINCTIONS
Continental flood
Basalts (Ma)
Extinction boundaries
(Ma)
Columbia River Ethiopian North Atlantic Deccan Madagascar Rajmahal Serra Geral Antarctic Karoo Newark Siberian
16.2 • 1" 36.9 • 0.9* 60.5* 65.5 • 2.5* 94.5 _ 1.2 117 • 1" 133 • 1" 176 • 1" 190 • 5 201 • 1" 248 • 4*
Lower/Mid-Miocene Eocene/OligoceneIr, mt/t,q end-Danian stage boundary Ir,mt Cretaceous/TertiaryIr,mt/t,q Cenomanian/Turonian Ir Aptian/Albian Jurassic/Cretaceous Bajocian/Bathonian Pliensbachian end-Triassicq,Ir Permian/TriassicIr,q ?
14 • 3 36 • 1 60.5 65 _+ 1 92 • 1 110 • 3 137 • 7 173 • 3 193 • 3 211 • 8 251 • 4
Asterisks indicate recent 4~ dates. Several boundaries show stratigraphic evidence of largebody impact: shocked quartz (q), microtektites/tektites (mt/t) and/or iridium (Ir) (see text). HOUSE (1973) suggested climatic warming as the cause of the P/Tr extinctions. STANLEY (1984) utilized both cooling and warming in a scenario where tropical regions cooled while polar regions warmed and temperature gradients became more gentle without a net global warming. From a compendium of vertebrate taxonomic data on the family level, MAXWELL (1992) concluded that non-marine tetrapods experienced four significant episodes of extinction in
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L I Fig. 10. Proposed Late Permian impact structures on the Falkland Plateau (RAMPINO, 1992). Putative structures are marked by negative gravity anomalies and reset basement ages -248 Ma.
123
Catastrophe: impact of comets and asteroids the Permian and early Triassic- in the Artinskian (-263 Ma), Ufimian (-253 Ma), Tatarian (-245 Ma) and Scythian (-240 Ma). He related these extinctions to climatic changes resulting from the waning of Permo-Carboniferous glaciation, subsequent global warming throughout the early Permian and Late Permian and a brief period of bipolar glaciation in the latest Permian. However, this study suffers from a lack of resolution of Late Permian events, paucity of fossils and poor correlation between the marine and non-marine realms. It does not explain the sudden extinctions seen in invertebrates and plants at the end of the Permian. A catastrophic cause for the end-Permian extinctions seems the most reasonable and a very large impact or series of impacts could explain the patterns of extinction quite well.
Frasnian- Famennian The evidence is now quite strong that the Frasnian/Famennian (F/F) extinctions at about 365 Ma coincided with a large body impact or impacts. The F/F extinctions were first related to an impact or impacts by MCLAREN (1970). Several impact craters have ages that agree closely with the estimated age of the boundary (-365-370 Ma), although none of these are thought to be large enough to be associated with a major mass extinction event. Thus, an impactor shower is a possibility (RAMPINO and STOTHERS, 1984a; HUT et al., 1987). A weak iridium anomaly found at several localities (Table I) was considered to be most likely of non-impact origin (ORTH et al., 1990; MCGHEE et al., 1986), although WANG et al. (1991) recently discovered an Ir anomaly of 250 ppt in an F/F boundary section in China. This was confirmed by CLAEYS et al. (1992) who reported evidence of glassy microtektites near the F/F boundary in Belgium. The F/F extinctions apparently involved catastrophic collapse of plankton communities and an abrupt ecosystem collapse (MCGHEE, 1988) and although the extinctions of different groups may have been stepwise, they apparently took place during a brief period of time; extinction rates were high within the last sub-stage of the Frasnian and the boundary is placed at a crisis of organisms within one conodont zone or perhaps at a zone boundary (MCGHEE, 1988; BUGGISCH, 1991). The biotic crisis seems to have culminated during the widespread "Kellwasser Event" of organic-rich black-shale deposition (e.g. SANDBERG et al., 1988; BUGGISCH, 1991). The deposition of black shales and the storage of a great amount of organic carbon in the shelf sediments, correlates with broad positive excursions of 613C in pelagic limestones in Europe and Australia, showing the worldwide nature of this probable oceanic anoxic event. Lack of hypoxic facies in some areas may be the result of water depth at the time of deposition (BECKER et al., 1991). Like the K/T and P/Tr boundaries, the extinction interval itself is marked by abrupt shifts in carbon, sulphur and oxygen isotopes (GOODFELLOWet al., 1989). A large negative shift in 613C of 2-3 per mil occurs at the top of the Lower Kellwasser limestone (Lower/Upper P.
gigas conodont zone boundary) in Germany (BUGGISCH, 1991, Fig. 7), indicating a sudden loss of biomass. This appears to be a worldwide phenomenon (e.g. Australia, Europe, China). In China, the large carbon isotope shift of-3.5 per mil coincides with the Ir anomaly (WANG et al., 1991). The iridium anomaly in Australia, which seems to occur just above the stratigraphic boundary, may have been preserved by the trapping of increased oceanic Ir 124
Other geological boundaries: climatic changes and possible role of impacts by the "disaster" cyanophyte Frutexites just after the sudden extinction and biomass loss marked by the negative carbon-isotope anomaly (MCLAREN, 1985; MCLAREN and GOODFELLOW, 1990). A large positive sulphur-isotope shift indicates reducing conditions on the sea floor (GELDSETZER et al., 1987) Several abrupt changes in conodonts occurred within ~ 100,000 years in the latest Frasnian. According to SANDBERG et al. (1988), the actual extinction event seems to have been abrupt, from as long as 20,000 years to as short as several days, with the demise of Frasnian reefs having taken place about 1 Ma earlier. They note that debris flow and other chaotic deposits, possibly related to tsunami, are common at the boundary in many places (e.g. Australia, China, Europe, Nevada). Using data from many F/F boundary sections, SANDBERG et al. (1988) have defined an event stratigraphy of the F/F mass extinctions related to possible multiple large-body impacts. dt180 fluctuations of ~1-2 per mil may indicate possible climatic fluctuations of up to 8~ or so during the Lower/Upper Kellwasser sequence (WANG et al., 1991, Fig. 3; BUGGISCH, 1991, Fig. 8), but these measurements could be affected by burial diagenesis and recrystallization. BRAND (1989), using d1180 data from brachiopods, estimated that water temperatures for tropical epeiric seas suddenly rose about 15~ (from -25~ to ~40~ although such warm water over large areas seems unlikely) during the Frasnian/Famennian crisis (above the ~38~ thermal threshold limit of most marine invertebrates) and later dropped by ~25~ across the Devonian/Mississippian boundary. However, these data may also be distorted by diagenesis or by unusually low salinities of ocean surface waters during the F/F interval. By contrast, CAPUTO (1985) published evidence for an early to middle Famennian (?) glaciation in South America, although the exact correlation with conodont zonation is poorly known. BUGGISCH (1991) suggested that a transition from a warm CO2 greenhouse to a cooler climate led to an overturn of anoxic oceans which in turn led to the extinction of low-latitude marine organisms. The large negative shift in 613C, possible abrupt warming, crash of plankton, spike of disaster flora and indications of anoxia, are similar to the changes seen at the K/T boundary and in light of the recent direct evidence for impacts at the F/F boundary, these climatic and oceanographic perturbations might be best explained as the aftermath of multiple planetesimal impacts in the late Frasnian (WANGet al., 1991).
Ordovician-Silurian Recently, GOODFELLOW et al. (1992) reported siderophile and chalcophile trace metal anomalies at the Ordovician/Silurian (--438 Ma) boundary, coinciding with reduction in carbonate content and negative oxygen- and carbon-isotope excursions and suggested that these may be impact related. Earlier, ORTH et al. (1986) found a weak Ir anomaly (58 ppt) in a clay layer at the recognized O/S boundary in the Anticosti Island, Quebec section (however, no shocked quartz was found) and maximum values of 250 ppt were reported from the Dobbs Linn, Scotland boundary site (WILDEet al., 1986). However, these were interpreted as most likely not related to impact (Table I). Although unresolved problems in correlation exist at the boundary, the major change apparently takes place suddenly at a globally recognizable event horizon just prior to the Glyptograptus persculptus graptolite zone (prior to 1985, this was the accepted O/S boundary)
125
Catastrophe: impact of comets and asteroids
(COCKS and RICKARDS, 1988). The boundary is marked by negative carbon- and oxygenisotopic anomalies that may indicate biomass loss/productivity crisis and sudden climatic warming and a positive sulphur-isotope excursion indicating reduced bottom waters, very similar to those seen at other abrupt extinction boundaries (MCLAREN and GOODFELLOW, 1990; GOODFELLOWet al., 1992). Phytoplankton show an abrupt global extinction at the Ordovician/Silurian boundary, coincident with extinctions among benthic organisms (COLBATH, 1986), much like that seen at other boundaries where impact is documented or suspected. More positive 613C values are found after the biomass-loss event, similar to that seen after the K/T boundary (MCLAREN and GOODFELLOW, 1990). BRENCHLEY (1989) reported evidence for separate episodes of extinction within <500,000 years in the latest Ordovician, with a pattern that suggests that trilobites, echinoderms and plankton living in temperate latitudes disappeared first at the beginning of a cooling trend, followed by brachiopods and corals in shallow tropical seas as sea level fell, presumably as a result of Late Ordovician glaciation. The last wave of extinctions of shallow water organisms seems to have occurred during postglacial warming as sea level rose again. Brenchley and colleagues connect the extinctions with the climatic effects of glaciation and deglaciation, but the climatic changes may have been triggered by a large impact or impacts and it is noteworthy that, like the K/T event, the apparently globally synchronous extinctions began with a sudden crash in planktonic organisms or species with planktonic larval stages. These facts suggest that scenarios of gradual changes of sea level or climate as a cause of the extinctions are unsatisfactory and MCLAREN and GOODFELLOW (1990) favour impact as a cause of the end-Ordovician extinctions. The latest Ordovician evidence of continental glaciation in North Africa and northern South America presents some problems for climatic reconstructions, as the Late Ordovician is predicted to have been a time of very high atmospheric CO2 according to carbon-cycle models (BERNER, 1990). If impacts triggered the extinctions, then they might have been important in the climatic events of the Late Ordovician (MCLAREN and GOODFELLOW, 1990). P re camb rian/Camb rian
Rocks spanning the Precambrian/Cambrian boundary (about 540 Ma) (the official boundary has not yet been agreed upon) are marked by profound changes in global biota from nonskeletal organisms to those with mineralized skeletons. The "Cambrian Explosion" of skeletalized forms may have been preceded by a mass extinction of soft-bodied organisms that allowed this explosive evolution (Hsu et al., 1985). The boundary may be marked by a global iridium anomaly (averaging -20 ppb), increase in Os and other trace elements and isotope anomalies as seen, for example, at the China C marker, separating the Tommotian and Atdabanian Series, at the first appearance of trilobites (FAN et al., 1984; Hsu et al., 1985). The boundary is also accompanied in many sections by a change in sedimentary facies from carbonates to black shales and a persistent carbon-isotope anomaly (e.g. in China, the Siberian Platform, Lesser Himalaya and Anti-Atlas). The 613C shift takes place just before the
126
Impact-induced volcanism ? first appearance of larger skeletalized fossils including archaeocyathids and trilobites. In the Lesser Himalaya, for example, the PC/C boundary zone is marked by a positive shift of--8 per mil followed by a negative 613C anomaly of up to ~7 per mil (AHARON et al., 1987); in Siberia, the positive shift o f - 8 per mil is followed by a sharp decrease o f - 5 per mil (MAGARITZ et al., 1986). These fluctuations are interpreted as indicating marked changes in ocean fertility- a bloom of biomass in the late Vendian, followed by possible Strangelove ocean conditions in the Tommotian. Oxygen-isotope anomalies of up to _+4 per mil are reported in the same sequences, commonly with a pronounced negative shift at the same level as the most negative carbon-isotope excursion (Hsu et al., 1985; MAGARITZ et al., 1986). The combination of Ir and trace metal anomaly, negative shifts in carbon- and oxygenisotope ratios, apparent Strangelove conditions and development of anoxia looks much like boundaries known or suspected to have been impact related. The large Lake Acraman impact structure (>160 km in diameter) in Australia seems to be older than the PC/C boundary.
Impact-induced volcanism? Continental flood basalts with volumes of >106 km 3 are the largest known outpourings of basaltic magma and recent studies suggest that the eruptions are sudden, short-lived events, where the entire volume of the lava is erupted in a series of huge flows over a period of a few hundred thousand to perhaps a couple of million year. Although the convergence of evidence suggests that some (and possibly all) significant extinction events are correlated with extraterrestrial impacts, the K-Ar and other age data compiled by RAMPINO and STOTHERS (1988) showed a correlation between the mass extinctions and the times of continental flood-basalt eruptions over the past 250 Ma. More reliable 4~ and U-Pb age determinations that are now available for the flood basalt episodes support the initial dating and improve the correlation (COURTILLOTet al., 1986; BAKSI, 1988; BAKSI and FARRAR, 1990; DUNNING and HODYCH, 1990; RENNE and BASU, 1991; SEBAI et al., 1991; CAMPBELL et al., 1992; HEIMAN et al., 1992; RENNE et al., 1992; EBINGER et al., 1993; STOREVEDTet al., 1992), as shown in Table II. For example, the Deccan Flood Basalts of India (65.5 + 2.5 Ma) (VANDAMME et al, 1991) were erupted very close to the time of the end-Cretaceous mass extinction and large-body impact (64.5 _+0.1 Ma) and the Siberian Flood Basalts (248 + 2.3 Ma) correlate with the endPermian boundary clays (251 + 3 Ma) (CAMPBELLet al., 1992). Stratigraphic studies in India now place the Deccan eruptions near the paleontologically defined K/T boundary and the eruptions could have lasted only --250,000years (COURTILLOTet al., 1986). The most recent direct study of the Deccan lavas in relationship to foraminiferal changes at the K/T boundary in India (JAIPRAKASH et al., 1993) suggests that the first flows were erupted at the beginning of the faunal changes at the boundary; the first intertrappeans contain foraminiferal zones that begin up to ~350,000 years above the canonical K/T boundary, while the earliest Tertiary zone seems to be missing; and the last flows seem to have occurred about 500,000 years after the boundary. JAIPRAKASH et al. (1993) record that, within the stratigraphic resolution of the study, all Cretaceous planktonic
127
Catastrophe: impact of comets and asteroids foraminifera became extinct prior to or within the K/T transition interval marked by the first flows. Impacts large enough to form craters >100 km in diameter, flood-basalt eruptions and extinctions, are first-order geological events that apparently occur once every few tens of million of years. The recurrent close association in time of these major events over at least the last 250 Ma suggests that they are related (RAMPINO and STOTHERS, 1988) and recent statistical tests of the correlation exhibit a statistical significance of > 98% (STOTHERS,1993). Impacts of 10-km diameter asteroids or comets are estimated to produce earthquakes of Richter magnitude of--12, with large amplitude ground waves thousands of kilometres from the impact site that could deeply fracture and disturb the lithosphere and upper mantle. RAMPINO (1987) pointed out a possible mechanism of inducing flood-basalt eruptions at or near sites of large impacts through lithospheric fracturing and pressure-release melting in the upper mantle. Calculations suggest that large impacts (impactors of >10 km diameter) could excavate initial transient cavities deep enough to result in decompression melting in the upper mantle, with ensuing flood-basalt volcanism along deep impact-induced fractures that penetrated the lithosphere. WHITE and MCKENZIE (1988) raised objections to the impact-volcanism model, pointing to theoretical studies which suggested that large volumes of basaltic melt could only be produced by decompression melting of anomalously warm mantle (MCKENZIE and BICKLE, 1988), such as was inferred to exist primarily in the 2,000 km diameter regions of inferred hotspot swells over proposed mantle plume heads. Therefore, they inferred, impacts would have to preferentially hit these areas in order to trigger flood-basalt volcanism, which they considered very unlikely. However, calculations showed that the 2,000-km diameter hotspot swells related to the estimated 40 to ~ 100 present hotspots would cover a significant portion of the Earth (50 _ 25%), making impact into anomalously warm mantle surprisingly likely and it was thus concluded that impacts of large asteroids or comets might well be responsible for the initiation or triggering of flood-basalt volcanism and perhaps hotspot outbreaks, although this must be considered quite speculative at present (RAMPINOand STOTHERS, 1988). Moreover, the volcanism might be induced by lithospheric fracturing at the antipodes of the large impact sites and the Deccan and Siberian eruptions may have been near the reconstructed antipodes of the Chicxulub and proposed Falkland impact sites, respectively (RAMPINO and CALDEIRA, 1992). Seismic tomographic evidence now suggests that -50% of the global upper mantle is warm (possibly from broad mantle upwellings, within-mantle heating, or through insulation of the upper mantle by former continental lithosphere) (ANDERSON et al., 1992), providing temperature conditions under which large impacts might lead to significant decompression melting. In an impact-induced hotspot model, continued activity might be the result of a combination of impact heating and long-lasting perturbation of mantle geotherms. Examples of possible impact-related volcanism can be found in the earlier history of the Earth, for example in the Vredefort Dome and Bushveld Complex of South Africa, which have been interpreted as large impact basins (~400 km in diameter) created about 2 billion years ago (ELSTON and TWIST, 1990). Within the Bushveld, mafic rocks occur in overlapping ring complexes around of the central uplift of the basin (layered mafic rocks are apparently absent from the central part of the complex). ELSTONand TWIST (1990) interpret these as mantle melts induced by deep ring fracturing related to the impact structure.
128
Climatic changes caused by flood-basalt eruptions The Mackenzie igneous events in Canada represent one of the most widespread episodes of mafic magmatism on the continents. The mafic rocks consist of the Coppermine River and Ekalulia flood basalts (>140,000 km3), the Muskox layered intrusion and the spectacular Mackenzie dyke swarm that radiates from the Coronation Gulf across northwestern Canada to a distance of more than 2,400 km. The Muskox intrusion and the Mackenzie dykes have been dated by the U-Pb method using trace amounts of zircon or baddeleyite (ZrO2) with ages of 1270_ 4 and 1267 _+2 Ma BP, respectively (LECHEMINANT and HEAMAN, 1989). The contemporaneous flood basalts occur in the southern part of a large circular feature more than 500 km across, a portion of its perimeter outlining the Coronation Gulf itself. SEARS and ALT (1992) recently proposed that such Proterozoic mafic magmatism and layered intrusions are indicative of impact. The association of rapidly erupted flood basalts, a layered intrusion capped by granophyre (melted crustal rocks?) and radiating dykes, with a large circular structure supports the idea that the magmatism may have been generated by a large impact in the Middle Proterozoic (D. HYNDMAN, personal communication). However, despite these suggestive relationships, the geologic consensus is best summarized by the recent statement by MELOSH (1989) that, "to date, there is no firm evidence that impacts can induce volcanism."
Climatic changes caused by flood-basalt eruptions Flood basalt eruptions have been suggested as a cause of both cooling and warming of the climate and such climatic changes related to the eruptions have been proposed as a primary or contributing cause of mass extinctions - a "volcanist" alternative to the impact theory (e.g. MCLEAN, 1985; COURTILLOTet al., 1986; COURTILLOT, 1990; GLEN, 1990).
Cooling of the climate Climatic cooling at the earth's surface attributed to volcanic eruptions is primarily a result of the formation and spread of stratospheric HzSO4 aerosols. These aerosols are formed from sulphur volatiles (SO2, HzS, etc.) injected into the stratosphere by convective plumes rising above volcanic vents and fissures. Residence time of sulphuric acid aerosols in the stratosphere is several years; fine volcanic ash lofted into the stratosphere largely settles out of the atmosphere in 3-6 months (RAMPINO et al., 1988). Basaltic magmas are usually rich in dissolved sulphur (a function of the iron content of the magma) and commonly show concentrations of >1,500 ppm sulphur (SIGURDSSON, 1982, 1990). The largest historic basaltic eruption, the Laki fissure eruption in southern Iceland of 1783 A.D. (THORDARSON and SELF, 1993), produced an estimated 14.7 _ 1 km 3 of magma. SIGURDSSON (1982) developed techniques to estimate the sulphur release from magmas by petrological methods. According to their work, the Laki magma contained 800 to 1,000 ppm of sulphur prior to eruption and only ~ 150 ppm were retained in the erupted rocks, indicating an 85% release, equivalent to about 3 x 1013g of sulphur, or ~8 x 1013g of H2SO4 aerosols. The Crete, Greenland ice core contains a large acidity peak in 1783 A.D., equivalent to about 3 x 1013g of atmospheric sulphur in the Northern Hemisphere, but much of the
129
Catastrophe: impact of comets and asteroids H2SO4 (and HC1 and HF) contributing to the acidity peak could have been transported from Iceland to Greenland in the troposphere, so that total acidity should not be used as a direct measure of stratospheric loading. However, atmospheric effects of Laki were quite widespread. Haziness and dimming of sunlight were noticeable in 1783 A.D. in Europe. SIGURDSSON (1982) presented data that show 1783-1784 as the coldest winter ever recorded in the eastern United States (in a 225-year record), with a - A T = 4.8~ and he estimated a possible Northern Hemisphere -AT = 1~ The conversion of such a large amount of SO2 to H2SO 4 would have probably greatly depleted stratospheric H20 and OH, which at present consists of about 1015g globally (STOTHERS et al., 1986), but a large amount of water may have been injected into the stratosphere by the eruption plumes. A major unknown remains the possibility of strong selflimiting physical and chemical effects in very dense aerosol clouds, which may mitigate severe volcanic perturbations. More accurate modelling of dense stratospheric aerosol clouds and their effects on atmospheric dynamics and chemistry is needed. It is conventional wisdom that volcanic eruptions must inject a significant amount of sulphur volatiles into the stratosphere to have widespread climatic effects (RAMPINO and SELF, 1984). Basaltic eruptions are commonly effusive in character and much less explosive than silicic eruptions of comparable volume, so that they are commonly considered to be ineffective in lofting volatiles to significant altitudes (e.g. ALVAREZ, 1986). However, theoretical modelling of plume rise from fissure eruptions suggests that a fraction of sulphur volatiles from effusive eruptions can reach the stratosphere in eruption plumes driven by large basaltic fire-fountains (STOTHERS et al., 1986). Observations and model calculations suggest that the fire fountains in the Laki eruption were 800-1,400 m in height, with average masseruption rates during the most active phases of the eruption estimated from 4.5 to 5.6 • 103 kg s-1 per meter length of fissure (THORDARSON and SELF, 1993). According to theoretical models of convective plume rise from fissure eruptions (STOTHERS et al., 1986), the Laki plumes could have attained altitudes up to 12 km above sea level. In support of this estimate, observations of the widespread haze over Europe in 1783 suggest that the eruption plume may have just reached the tropopause over Iceland, which is located at a height of --11 km in Northern Hemisphere summer (STOTHERSet al., 1986). TRIPOLI and THOMPSON (1988) used a convective storm model to calculate plume growth, evolution and stabilization heights in a simulation of the very large (-700 km 3) Roza flow eruption (~ 15 Ma ago) in the Columbia River Flood Basalts. The complex model included effects such as wind shear, rotational effects, rainout and fallout. For a fissure assumed to be 90 km long, tremendous updrafts were produced that combined with the atmospheric circulation. As the surface winds settled into a large cyclonic circulation, the updrafts decreased by about a factor of 1/2. In this model 14% of the gases and ash were above the tropopause (11 km) after 3 h and 5% was above it after 6 h. This demonstrated that some material could be injected into the stratosphere by such large fissure eruptions, although soluble tracers used in this model did not make it past the tropopause. However, even 10% of the total release of SOa from a Roza-sized eruption is estimated to be equivalent to ~3 x 1014g of aerosols, more than three times the estimated output of Laki. Sulphate aerosols of modal diameter -0.5/tm should cool the earth's surface for all altitudes, with maximum cooling for low level aerosols. Therefore, volcanogenic aerosols in the troposphere will cool the surface as well. In most volcanic eruptions, tropospheric aero-
130
Climatic changes caused by flood-basalt eruptions sols have a very short lifetime of about a week, before they are washed out of the lower atmosphere. A flood basalt eruption, however, could release large amounts (1015 g) of sulphuric acid aerosols creating regional optical depths of > 10 and perhaps cooling the climate and suppressing convection, so that rainout might be less effective at removing the aerosols. A continuous curtain of aerosols from large, long-lived fire fountains might be a possibility. Scaling upward from the-15 km 3 Laki eruption, sulphur emissions from the entire sequence of Deccan Traps eruptions could have been equivalent of ~ 1019 g of sulphuric acid aerosols. Averaged over a 500,000 year eruption period, this is equal to -2 x 1013 g of sulphuric acid aerosols per year. Recently, COURTILLOT(1990) estimated that individual Deccan eruptions could have emitted 6 x 1018 g of sulphur and 6 x 1016 g of halogens into the atmosphere over a few hundred years. However, this sulphur release estimate is three orders of magnitude greater than that determined by using the Laki eruption as a scaling factor and seems to be much too high. Individual historic volcanic aerosol clouds in the stratosphere show an e-folding time of about 1 year, so that the ocean/atmosphere climate system does not have a chance to come to equilibrium with the typical volcanic perturbation. Historic eruptions that created -1013 g of aerosols in the stratosphere are associated with surface coolings of only a few 10ths of a ~ in the 1 or 2 years following the eruption. GCM model results, using the Goddard Institute for Space Studies (GISS) model, however, suggest that if maintained for 50 years, a stratospheric loading of about 1013 g of aerosols would lead to an equilibrium 5~ global cooling (D. RIND, personal communication, 1992). Therefore, if flood-basalt eruptions were continuous at the average activity level for 50 years or more, a significant cooling of climate is predicted. Eruptions in the Deccan show evidence of intermittent activity. Average thickness of individual flows in the Deccan is about 12 m (with a maximum of 160 m), suggesting that the total Deccan lava pile could be composed of--100 individual large flows or flow complexes. At Mahabaleshwar, the 1,200 m section contains about 50 flows and the flows are traceable for considerable distances within the Deccan (MAHONEY, 1988). Therefore, it is possible that flow complexes of up to -103 km 3 were erupted at intervals of several thousand years. Weathering profiles of <1 m thick on flow tops (so-called red boles) and fossiliferous intertrappean non-marine sediments up to 5 m thick suggest that at times eruptive activity waned for tens of thousands of years. For comparison, the largest well-studied individual lava flow in the Columbia River Flood Basalts is the Roza Flow (STOTHERSet al., 1986). The Roza Flow eruption is estimated to have produced 7 x 102 km 3 of magma in a time that may have been as brief as about 1 week. If this was the case, then each individual mega-eruption in the Deccan could have released up to 1016 g of SO2 in a short time, enough to form about 1017 g of stratospheric H2SO 4 aerosols, if all of the SO2 reached the stratosphere. To be very conservative, however, it can be considered that only -0.1% (~1014 g) of the SO2 released in a flood-basalt eruption of ~103 km 3 is converted to aerosols in the stratosphere (-1015 g). In such a case, global stratospheric aerosol optical depths of about 10 would be produced, with the initial fraction of transmitted sunlight only about 1% of unperturbed conditions (Fig. 11) (RAMPINO et al., 1988). This would be similar to proposed nuclear winter scenarios (see above).
131
Catastrophe: impact of comets and asteroids
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Greenhouse effect from volcanic outgassing A greenhouse warming caused by emissions of carbon dioxide from the Deccan Traps flood basalt volcanism has also been suggested as a cause of the terminal Cretaceous extinctions (e.g. MACLEAN, 1985; COURTILLOT, 1990). In response to these suggestions, CALDEIRA and RAMPINO (1990a,b) estimated the total eruptive and non-eruptive CO2 output by the Deccan eruptions ((6-20) x 1016 mol) over a period of several hundred thousand years based on best estimates of the CO2 weight fraction of the original basalts and basaltic melts, the fraction of CO2 degassed and the volume and timing of the Deccan Traps eruptions. Results of a model designed to estimate the effects of increased CO2 on climate and ocean chemistry suggested that increases in atmospheric pCO2 due to Deccan Traps CO2 emissions would have been less than 75 ppm, leading to a predicted global warming of less than I~ over several hundred thousand years (CALDEIRA and RAMPINO, 1990a).
132
Climatic changes caused by flood-basalt eruptions The same authors also took into account the possible changes in ocean alkalinity and effects on atmospheric CO2 related to the H2SO 4 and HCI that could have been released into the sea by the eruptions (CALDEIRA and RAMPINO, 1990b). Inclusion of this altered ocean chemistry led to a greater total p C Q increase of about 200 ppm over several hundred thousand years and an estimated long-term temperature increase of--2~
(Fig. 12). They concluded that the
greenhouse warming caused by CO2 and acid emissions from the Deccan eruptions would have been too weak to have been an important factor in the end-Cretaceous extinctions (CALDEIRA and RAMPINO, 1990a,b) and the same apparently holds true for other flood basalt eruptions and extinctions. In an alternative approach, the results of GERLACH and GRAEBER (1979) for volatile emissions from Kilauea volcano may also be used to estimate Deccan output. Over the period from 1956 to 1983, Kilauea emitted an estimated total of 1.8 x 1013g CO 2 per km 3 of magma supplied to the volcano. For a Deccan volume of 2 x 106 km 3, this would equal a total of 3.6 x 1019 g of CO2 or about 10 TM mol of CO2 outgassed over several hundred thousand years. This is twice the amount used in the modelling studies of CALDEIRA and
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133
Catastrophe: impact of comets and asteroids RAMPINO (1990a,b) and could lead to a greater greenhouse warming of up to 4~ over a few hundred thousand years, but such a warming is still of questionable significance in contributing to mass extinctions. By contrast, COURTILLOT (1990) estimated an extremely high Deccan CO2 emission rate of 3 x 1019g (7 x 1017 mol) of CO2 outgassed over only ~100 years. This estimate of CO2 outgassing from the Deccan eruptions seems much too high based on information on the CO2 emission rates from historical basaltic eruptions. The possible role of volcanism in mass extinctions
The wealth of physical evidence for an extraterrestrial impact at the K/T boundary and the close timing of many of the extinctions with the worldwide impact ejecta layer, suggest that the primary cause of the K/T mass extinctions was the collision of an asteroid or comet with the Earth (ALVAREZ, 1986; GLEN, 1990). Some critics of the impact interpretation (the socalled volcanists), however, have attempted to attribute all of the important components of the K/T boundary layer to volcanism, or to dismiss the impact evidence (e.g. LYONS and OFFICER, 1992). However, suggestions that the anomalous iridium at the boundary was a product of Deccan volcanism (e.g. CROCKET et al., 1988) are apparently ruled out by the generally low iridium values in the Deccan lavas, in soils and weathering profiles between flows and in K/T boundary sections on the Indian sub-continent (ROCCHIA et al., 1988b; BHANDARI et al., 1993). Furthermore, despite arguments to the contrary, experimental and observational evidence shows that shocked quartz (with multiple planar deformation features) and stishovite cannot be produced at the pressures characteristic of volcanic eruptions (GRATZ et al., 1992; DA SILVA et al., 1990) and that the K/T Haitian tektite glass has features apparently incompatible with a volcanic origin (SIGURDSSONet al., 1991). However, several workers have argued that volcanism could have been a contributing factor in the events at the K/T boundary (e.g. COURTILLOT,1990). This would be especially interesting if it could be clearly shown that extinctions and/or climatic changes preceded the K/T impact event (or events), as the Deccan eruptions may have begun prior to the major Ir anomaly (COURTILLOT, 1990), and/or that some of the extinctions took place over ~105 years after the impact. KELLER and BARRERA (1990) maintained that K/T extinctions and environmental changes were not instantaneous and may have begun prior to the deposition of the inferred impact horizon. They presented evidence that the K/T microfossil extinctions began ~300,000 years prior to the K/T iridium-rich layer and may have continued for about 50,000 years after the deposition of the Ir spike. However, even if all the extinctions were not instantaneous (and an impact model does not demand that they were), the abrupt negative shift in 613C at the boundary indicates a sudden major loss of biomass, or killing event (MCLAREN and GOODFELLOW, 1990). As noted above, some boundary sections show evidence for significant climatic fluctuations prior to the boundary event as defined by the iridium anomaly. For example STOTT and KENNETT (1989, 1990) suggest that shifts in 6180 in Antarctic deep-sea sediments evidence a 4~ warming beginning some 500,000 years before the boundary, followed by a 4~ cooling across the boundary and ZACHOS et al. (1987) presented evidence that a climatic cooling preceded the K/T boundary by about 200,000 in the North Pacific. However, other sections do not exhibit such pre-boundary fluctuations and the climate record at the K/T boundary remains problematic.
134
Future climates ?
Future climates? Astronomical observations show that the Earth lies within a swarm of Earth-crossing asteroids and comets (e.g. SHOEMAKERet al., 1990; CHAPMAN and MORRISON, 1994). Impact of objects greater than a few kilometres in diameter have predictable far-field effects that are very likely to constitute a global environmental disaster. The collision rates of asteroids and comets of various sizes with the Earth and the corresponding production of impact craters, can be calculated from the observed flux of Earth-crossing bodies of different types (SHOE-
MAKERet al., 1990). The estimated production rates of large craters from asteroid and comet collision on Earth during the last 100 Ma based on the recent flux is estimated as (4.9 _+ 2.9) x 10-15 km -2 year -1, which is in excellent agreement with the rate of (5.4 _ 2.7) x 1015 km-2 year-1 estimated from the geologic record of impact craters over the last 120 Ma. The chances of a large-body impact affecting global climate in the near future have been calculated by CHAPMAN and MORRISON (1994). They find that there is a 1/10,000 chance that a large (--2 km diameter) asteroid or comet will collide with the Earth during the next hundred years. They point out that although impacts of this magnitude are so infrequent as to be beyond human experience, the long-term statistical hazard is comparable to other more familiar hazards. For example, the chances of the average American dying in a passenger aircraft crash are estimated at about 1/20,000, or in a flood, about 1/30,000 (CHAPMAN and MORRISON, 1994). Consideration of the "impact winter" phenomenon led, in part, to the appreciation that the climatic effects of dense smoke and dust clouds produced by nuclear war might be severe (TURCO et al., 1983). Initial model calculations suggested that for most scenarios of nuclear exchange, smoke from burning cities and forest fires would cover large portions of the globe and cause a major drop in temperatures to sub-freezing levels in midlatitudes even in summer, creating a so-called nuclear winter. There has been considerable debate as to the severity and extent of nuclear winter (e.g. COVEY et al., 1984; SCHNEIDER and THOMPSON, 1988), but most recent GCM studies predict that (for a worst-case July smoke injection) land temperatures in the 30 ~ to 70~ latitude zone could drop from 5 to 15~ with freezing events in mid-latitudes during the first months (TURCO et al., 1990). During the subsequent 1-3 years, significant cooling could continue in areas covered by the residual smoke cloud and ocean-surface cooling of ~2-6~ may extend for several years. Longer term (decadal) climatic cooling might arise primarily through climate feedbacks such as increased snow cover and sea-ice and perturbed sea surface temperatures. The after-effects of large-body impacts, including massive dust clouds, increased water vapour in the atmosphere from an ocean impact, water and/or ice clouds, wildfires and soot production, production of NOx and acid rain, heating pulses due to re-entering ejecta, increased greenhouse gases (CO2, SO2) and sulphuric acid aerosols from impact into carbonate or evaporite sediments together with perturbations of biogeochemical cycles resulting in fluctuations of CO2, reduction of dimethylsulphide for cloud condensation nuclei and other effects, are predicted to produce climatic changes on various time-scales ranging from instantaneous to 106 years. These climatic and environmental fluctuations may have been severe enough to cause the mass extinctions on land and in the sea, which mark major geologic boundaries, such as the Cretaceous/Tertiary boundary (-65 Ma). 135
Catastrophe: impact of comets and asteroids The K/T boundary is marked by a suite of convincing evidence of large-body impact, including a global boundary layer with elevated levels of iridium and other characteristic trace metals, shock-deformed minerals, tektites and microtektites, microspherules, impact-wave deposits and the Chicxulub impact crater. The boundary is also marked by the apparently sudden extinction o f - 7 5 % of marine species, including >95% of calcareous plankton, a major floral transition and all of the extant dinosaurs. These extinctions can be explained by the severe conditions predicted at the boundary including a brief dark and cold "impact winter", global wildfires and climatic changes resulting from changes in greenhouse gases as a result of the marine extinctions. A review of the details of biotic changes and the environmental, isotopic and climatic indicators at times of recognized extinction events reveals some general patterns that may implicate large-body impacts and their climatic after-effects as a general cause of pulses of extinction. The major mass extinctions are accompanied by abrupt negative carbon-isotope shifts indicating sudden losses of biomass and reduction in marine productivity, abrupt negative shifts in oxygen-isotopic ratios indicating possible climatic warming, sudden crashes in global plankton and in organisms having planktonic growth stages, negative sulphur-isotope shifts suggesting development of anoxic conditions, and outbreaks of disaster fauna and flora suggesting a sudden ecological catastrophe. These conditions, combined with growing evidence of coincident large-body impacts from iridium anomalies, microtektites, shocked minerals and well-dated craters, lead to the working hypothesis that all extinction pulses are the result of the impacts of large asteroids or comets on the earth' s surface. Large impacts may trigger flood basalt volcanism, as indicated by a correspondence among mass extinctions, evidence of impact, and flood basalt eruptions over the last 250 Ma. Aerosols and carbon dioxide from massive flood basalt eruptions are predicted to produce climatic effects that could exacerbate environmental changes at mass extinction boundaries. Episodic delivery of impact energy to the Earth may even be great enough to have an effect on terrestrial geologic processes that determine long-term climate (cf. Chapter 2 by BERGER and Chapter 3 by BARRON). Although the chances of a large asteroid or comet collision in the near future are small such an occurrence is as likely as other "accepted" hazards of modern life. When the next largebody impact occurs the climatic effects, especially on human food resources, would be massive: crop failures would almost certainly result in mass starvation. In response to the possible threat, programmes to detect large asteroids and comets that are on collision courses with the Earth and to attempt to divert these bodies if necessary, have been proposed (CHAPMAN and MORRISON, 1994). If these are enacted the climatic impacts can be reduced or removed; if they are not, a massive climatic shock equivalent to that which caused the Cretaceous/Tertiary extinctions is a possible future climate.
References
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136
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Chapter 5
Observations from the surface" projection from traditional meteorological observations P. D. JONES
Introduction Although meteorological recording began earlier, the period since the middle of the 19th century is that traditionally associated with instrumental records. This chapter examines in detail the reliability of temperature, precipitation and sea-level pressure data, concentrating on the construction of the hemispheric and global average temperature series. The key piece of observational evidence in the "global warming debate" is the "global" temperature series (JONES and WIGLEY,1990). How much has the temperature risen and how certain are we of the causes? The remainder of the chapter considers these issues, together with an assessment of the record in a longer paleoclimatic context (see also Chapter 6 by DIAZ and KILADIS) and the representativeness of the longer surface record with respect to free-atmosphere observations since the late 1950s. The chapter concludes by considering possible explanations of the instrumental record (for more discussion of the possible explanations see also Chapter 4 by RAMPINO, Chapter 6 by DIAZ and KILADIS, Chapter 9 by WANG et al., Chapter 10 by ANDREAE, Chapter 11 by BRASSEUR et al. and Chapter 12 by HENDERSON-SELLERS)and indicates what each suggests concerning the course of climate change in the next century.
Development of instrumentation and meteorological observational networks The instrumental period of weather recording began in the late 17th century with the development of barometers and thermometers. Up until the late 18th century, the early observers were dedicated amateurs, mostly physicians, parsons and country squires and their equivalents in countries other than England. Careful analyses are necessary to enable the early records to be used. Calibration scales and the exposure of the early instruments must be scrutinized with, in some cases, experiments performed to duplicate the conditions (CHENOWETH, 1992, 1993). Long records have been developed for some European regions (e.g. MANLEY (1974) and PARKER et al. (1992) for Central England; DETTWILLER (1981) for Paris and SCHAAKE (1982) for Berlin). There was some correspondence and liaison between the early observers through societies such as the Royal Society in London, but little central organisation. Many of the original data have been lost and are only available in society proceedings. Sometimes the entire records of early observers have been published (e.g. KINGTON(1988a) for Lyndon in England). The first real weather observing network was set up in 1778 by the Socigtd Royale de
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Observations from the surface: projection from traditional meteorological observations M~dicine in France under the patronage of Louis XVI. The French meteorologist Louis Cotte was appointed to establish and maintain the network of observers. Meanwhile in Mannheim, then the capital of the Palatinate of the Rhine, the Elector Karl Theodor founded the Societas Meteorologica Palatina in 1780. In both cases detailed instructions on how and when to record information were sent to observers. In the German case, standard instruments were also issued. The networks, however, did not survive the change in the political climate in Europe in the late 18th and early 19th centuries and both ceased in the 1790s. KINGTON (1988b) has produced, from the station data, weather maps for most of Europe for the 1780s. Further expansion of the meteorological recording network began following the Vienna Meteorological Congress of 1873. This meeting provided the impetus for the expansion of recording networks worldwide and for the international exchange of data that continues today under the auspices of the World Meteorological Organization (WMO). When national meteorological centres were established in the late 19th century, observing networks expanded, instruments and instrument shelters were standardised, and uniform instructions to observers were issued. As a result, a reasonably comprehensive global network of temperature, precipitation and pressure recording stations emerged, many of which have continued in operation to the present. Unfortunately, standardisation of instruments and exposure did not extend to a universally adopted policy so that, even today, vastly different protocols are followed. The effects of this are discussed in the remainder of this section. Further discussion on the history of instrumentation has been presented by LAMB and JOHNSON (1966), VON RUDLOFF(1967) and MIDDLETON(1966, 1969). Land areas represent only 30% of the Earth's surface and it is important to consider marine weather observations. Both merchant and naval vessels have taken observations of weather, including measurements of the temperature of the sea surface (SST), since the 1850s. Data were stored in log books by the major maritime nations following an international agreement signed in Brussels in 1853. The force behind this was an American naval captain, Matthew Fontaine Maury. In the last 20 years, major international efforts have been made to put all this log-book information into computer data banks. Two such compilations exist, the Comprehensive Ocean-Atmosphere Data Set (COADS) produced at Boulder, Colorado
(WOODRUFFet al., 1987) and the UK Meteorological Office marine data bank (BOTTOMLEY et al., 1990). About 80 million individual observations of SST exist between 1854 and 1990. Homogeneity
of temperature
records
In this section we define homogeneity according to CONRAD and POLLAK (1962), who call a numerical series representing the variations of a climatological element homogeneous if the variations are caused only by variations of weather and climate. It is vital that all meteorological observations contain as few non-meteorological variations as possible. Although observers may take readings with meticulous care, other influences can easily affect the readings. The following sections discuss the most important causes of non-homogeneity.
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changes in instruments, exposure and measurement technique;
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changes in station location;
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changes in observation times and the methods used to calculate monthly averages;
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changes in the station environment with particular reference to urbanisation.
Development of instrumentation and meteorological observational networks Changes in instrumentation, exposure and measuring techniques For land-based temperature, the effects of changes in thermometers have been slight so far this century. More important to the long-term homogeneity is the exposure of the thermometers. Readings now are generally from thermometers located in louvered screened enclosures, which are generally painted white. Earlier readings often were from shaded wall locations, sometimes under roof awnings. These need corrections which can only be estimated by parallel measurements or by reconstructing past locations (CHENOWETH,1992, 1993). The greatest potential discontinuity in temperature time series is currently being induced in first order stations in the United States. Here mercury-in-glass thermometers have been replaced by a thermistor installed in a small louvered housing (model HO-83). The change was made by the National Weather Service in the USA at most first order sites during early 1982. There appears to have been little thought given to effects on the homogeneity of the record. The continuity of the record for climatic purposes was only a minor consideration of the weather service. Parallel measurements were not made as is generally recommended. The first signs of a problem were noticed by the frequent breaking of records for extreme daily maximum temperatures. A warm bias was clearly evident, possibly being indicative of an aspiration problem in the replacement instrumentation (GALL et al., 1992; KESSLER et al., 1993). As more developed countries might follow the lead of the United States, the problem is likely to recur. However, with good design and adequate testing through parallel observations, the problems induced by any changes should be surmountable. Marine temperature data are seriously affected by homogeneity problems. SST data were generally taken before World War II by collecting some seawater in an uninsulated canvas bucket and measuring the temperature. As there was a short time between sampling and reading, the water in the bucket cooled slightly due to evaporation. Since World War II most readings are made in the intake pipes which take water on to ships to cool the engines. The change appears to have been quite abrupt, occurring within a month during December 1941. The sources of ships' observations in the two marine data banks (COADS and UKMO) changed from principally European to mainly American at this time (see also FOLLAND and PARKER, 1995). Studies of the differences between the two methods indicate bucket temperatures are cooler than intake ones by 0.3-0.7~ (JAMESand Fox, 1972). A correction technique for bucket measurements has been derived based on the physical principles related to the causes of the cooling (BOTTOMLEY et al., 1990; FOLLAND and PARKER, 1995). The cooling depends on the prevailing meteorological conditions, and so depends on the time of year and on location. Although a day-to-day phenomenon, the various influences on the bucket are basically linear, so cooling amounts can be calculated on a monthly basis. Assuming that there has been no major change in the seasonal cycle of SSTs over the last 100 years, the time between sampling and reading can be estimated as that which best minimises the residual seasonal cycle in the pre-World War II data. The estimate of between 3 and 4 min is both quite consistent spatially and agrees with instructions given to marine observers (BOTToMLEY et al., 1990; FOLLAND and PARKER, 1991, 1995). Coverage of SST data is generally dictated by shipping routes and is, therefore, poor over the Southern and tropical oceans. From the late 1970s, it has been possible to include infor-
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Observations from the surface: projection from traditional meteorological observations mation for all oceanic areas using satellite measurements. Co-located in-situ and satellite values do not agree quantitatively because the satellite is measuring the skin temperature and the in-situ observations, the average temperature of the top few metres. However, the anomaly patterns of the two are in excellent agreement and a blending technique (REYNOLDS and MARSlCO, 1993) has been developed to anchor the globally complete satellite patterns to the in-situ observations which act as the ground truth. The blending technique also makes use of sea-ice extents, which are also determined from satellite measurements. It will be some time, however, before there is a long record of complete SST fields to assess the significance of the much sparser coverage, prior to the late 1970s, for hemispheric and large scale averages.
Changes in station locations It is rare that a temperature recording site will have remained in exactly the same position throughout its lifetime. Information concerning station moves is of primary importance to homogenisation. Such information about a station's history is referred to as metadata. Assessment of station homogeneity requires nearby station data and appropriate metadata.
Changes in observation time and the methods used to calculate monthly averages In the late 19th and early 20th centuries, there was considerable discussion in the climatological literature concerning the best method of calculating true daily and, hence, monthly average temperatures (e.g. ELLIS, 1890; DONNELL, 1912; HARTZELL, 1919; RUMBAUGH, 1934). Many schools of thought existed and, unfortunately, no one system prevailed in all regions. At present, there is no uniform system, although the majority of nations use the average of the daily maximum and minimum temperatures to estimate monthly mean temperatures. The remainder use a variety of formulae based on observations at fixed hours, some of which are designed to simulate the true daily mean that would be estimated from readings every hour. There would be no need to correct readings to a common standard, however, provided the observing systems had remained internally consistent. This is because analysts are generally interested in relative changes rather than the absolute values. Unfortunately, only in a few countries has the methodology remained consistent since the 19th century (BRADLEY et al., 1985). If absolute temperatures are important for some study then a common standard will be necessary. In the routine exchange of data, countries exchange monthly mean temperatures, using whatever observational practice is applied in the country. Proposals currently before WMO seek to change the number of meteorological variables routinely exchanged. When this takes place, maximum and minimum temperatures will be exchanged and it is likely these will become the preferred method of calculating mean temperature. Due to data limitations, studies of past temperature variations have had to concentrate on mean temperature. Maximum and minimum temperatures will be extremely useful when considering both the causes and impacts of climate changes (see later). Using maximum and minimum temperature, however, to calculate monthly means is extremely susceptible to the times at which the observations are made (BAKER, 1975; BLACKBURN, 1983). In the United States, KARL et al. (1986) have developed a model to correct observations made in the
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Development of instrumentation and meteorological observational networks morning and afternoon to the 24-h day ending at midnight. The corrections to the monthly means are called time-of-observation biases.
Changes in the station environment The growth of towns and cities over the last 200 years around observing sites can seriously impair the temperature record. Affected sites will appear warmer than adjacent rural sites. The problem is serious at individual sites but appears relatively small in averages calculated for large continental-scale areas (JONES et al., 1990). A correction procedure has been developed for the contiguous United States by KARL et al. (1988). It depends on population size. Population is generally used as a ready surrogate for urbanisation but other indices such as paved area (OKE, 1974), although more useful, are only available for specific cases. The individual nature of the effect means that the corrections applied to US data by KARL et al. (1988) will only be reliable on a regional rather than a site basis. The corrections are also specific to North America and would not apply to Europe, for example, where urban development has taken place over a much longer period of time. The problem is likely to become important in the future in developing countries as cities expand rapidly (OKE, 1986).
Precipitation and pressure homogeneity Both of these variables are also affected by severe homogeneity problems. For precipitation, there are problems associated with the gauge size, shielding, height above the ground and the growth of vegetation near the gauge. All can impair the performance of the gauge, affecting the efficiency of the catch. The biggest problem concerns the measurement of snowfall, where continual attempts to improve gauge performance affect the long-term homogeneity of the station records. RODDA (1969) has reviewed the possible errors and inhomogeneities that can result in precipitation records. The total of these problems, coupled with the greater spatial variability of precipitation data, makes the problem of homogeneity much more difficult to deal with than for temperature. Precipitation networks are rarely dense enough to allow for the homogeneity checks discussed in the next section to be undertaken. Instead of studying individual records, analyses of regional precipitation series have been made (BRADLEYet al., 1987a; DIAZ et al., 1989; FOLLAND et al., 1990, 1992). Precipitation climatologies for land regions have been developed (LEGATESand WILLMOTT, 1990; HULME, 1992) partly for the evaluation of the performance of General Circulation Models (GCMs) (see Chapter 7 by DICKINSON). The Hulme climatology is based on the 1951-1980 period and has values for each month of the period allowing model variability as well as model precipitation totals to be compared. The Legates and Willmott climatology uses all available precipitation data and is not geared to any specific time period. This means that temporal variability variations cannot be considered. These authors have, however, attempted to allow for gauge undercatch using correction methods devised by SEVRUK (1982). Taken globally they estimate that precipitation is underestimated by about 10% varying from 40% near the poles in winter to less than 5% at the tropics. In 1986, the World Climate Research Programme (WCRP) established the Global Precipitation Climatology Project (GPCP). The aim of GPCP is to produce a global 10-year precipi-
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Observations from the surface: projection from traditional meteorological observations tation data set for the decade 1986-1995, 2.5~ 2.5 ~ box resolution. Year-to-year estimates over ocean areas have never been attempted before (RUDOLF et al., 1991). Initial results for 1987 have so far been published (RUDOLF et al., 1992). Recently WCRP has extended the project indefinitely. The GPCP will integrate various satellite and gauge measurements of precipitation and should provide a truer representation of the spatial and temporal variability of precipitation than previously achieved (ARKIN and ARDANUY, 1989). Various precipitation climatologies, including ground-based data, satellite precipitation estimates and model precipitation forecasts have been compared by JANOWIAK (1992) over the tropics. Differences are sometimes large, although the intercomparisons made by SPENCER (1993), between the new estimates from microwave-sounding unit MSU (see section on Upper air data during the last 40 years for a description of this source) data and the satellite infrared index are very encouraging, indicating that the GPCP aims will be achieved, even if the initially published data have to be revised. Pressure data have an advantage over the temperature and precipitation databases because they are routinely analysed on to regular grid networks for weather forecasting purposes. Monthly mean data for the Northern Hemisphere (N of 15~ extend back to 1873 and for the Southern Hemisphere routine analyses began in the early 1950s. Neither analyses are complete for the entire period, particularly during the earliest years. The sources of the data are discussed and their quality assessed in a number of papers (Northern: WILLIAMSand VAN LOON, 1976; TRENBERTH and PAOLINO, 1980; JONES, 1987; Southern: VAN LOON, 1972; KAe,OLY, 1984; JONES, 1991). Global analyses have been produced at the major operational weather centres since 1979. The most widely available analyses are those from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Meteorological Center (NMC) of NOAA. However, because of changes to the model and to data assimilation schemes, the homogeneity of the analyses for many climate applications is questionable (TRENBERTH,1992). A consistent set of analyses will soon be produced as part of the World Climate Research Programme (WCRP) re-analysis project at ECMWF and NMC (WCRP, 1993).
Data homogenisation techniques Many methods have been proposed for testing the homogeneity of station records relative to those at adjacent stations (CONRADand POLLAK, 1962; WMO, 1966). Generally, tests involve the null hypothesis that a time series of differences (ratios for precipitation) between neighbouring observations will exhibit the characteristics of a random series (e.g. MITCHELL, 1961; CRADDOCK, 1977; POTTER, 1981; ALEXANDERSSON, 1986; JONES et al., 1986a,c; YOUNG, 1993). The methods work with or without metadata. The scope of the method and the ability to explain and correct inhomogeneities is dramatically improved, however, with detailed metadata. The most comprehensive homogeneity exercise performed produced the United States Historic Climate Network (KARLand WILLIAMS,1987).
What surface observations tell us about the last 140 years
The longest and most spatially extensive record of surface variations is available for three meteorological variables: temperature, precipitation and mean sea-level pressure (MSLP).
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What surface observations tell us about the last 140 years
Long records often exist for other variables such as sunshine duration, cloudiness, humidity, wind speeds etc., but these are rarely "global" in extent and these variables can have severe problems related to long-term homogeneity due to changing instrumentation (e.g. sunshine recorders; KARL and STEURER, 1990) or to changing practices (e.g. clouds; HENDERSON-
SELLERS, 1990). Coverage for the three principal variables is, however, never truly global. Even now, in-situ observations are rare over the Southern Oceans and routine observations are only available over Antarctica since 1957. Improvements are being made and since the late 1970s it has been possible to integrate satellite and surface measurements.
Surface temperature Hemispheric averages
Various research groups have synthesised the individual site temperature series into gridded and/or hemispheric average time series. The three main groups recently involved are the Climatic Research Unit/UK Meteorological Office (CRUAJKMO) (JONES, 1988; FOLLAND NORTHERN HEMISPHERE LAND+MARINE TEMPERATURES
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Fig. 1. Northern Hemisphere surface air temperatures for land and marine areas by season, 18541994. Standard meteorological seasons for the Northern Hemisphere are used: winter is December to February, dated by the year of the January. Data are expressed as anomalies from 1950 to 1979. Time series in this and subsequent plots have been smoothed with a 10-year Gaussian filter.
157
Observations from the surface: projection from traditional meteorological observations et al., 1990, 1992; JONES et al., 1991), the Goddard Institute for Space Studies (HANSEN and LEBEDEFF, 1987, 1988) and the State Hydrometeorogical Institute in St. Petersburg
(VINNIKOVet al., 1990). The differences between the groups arise both from the data used and from the method of interpolation. Intercomparison of the results of the three groups can be found in various publications (e.g. ELSAESSER et al., 1986; FOLLAND et al., 1990, 1992; JONES et al., 1991; ELSNER and TSONIS, 1991a). Here we consider only CRU/UKMO because they are the only group to incorporate marine data. Time series of the mean hemispheric annual and seasonal temperature anomalies are shown in Figs. 1 and 2. Both series have been widely discussed (WIGLEY et al., 1986; FOLLAND et al., 1990, 1992; JONES and WIGLEY, 1990). The accuracy of the individual seasonal and annual estimates undoubtedly varies with time. The most reliable period is from about 1950. Various techniques have been tried to assess error estimates, particularly for years prior to the 1920s. Frozen grid analyses (JONES et al., 1985, 1986a,b, 1991; BOTTOMLEY et al., 1990) indicate that hemispheric estimates can be well estimated from the sparse data available during the late nineteenth and early twentieth centuries. Individual annual estimates appear to have about twice the variability of the post 1950 data but the average temperature anomaly during the late 19th century is well approximated by the sparse network. This reSOUTHERN HEMISPHERE LAND+MARINE TEMPERATURES
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1880
1900
1920
1940
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1980
Fig. 2. Southern Hemisphere surface air temperatures for land and marine areas by season, 18541994. Standard meteorological seasons for the Southern Hemisphere are used: summer is December to February, dated by the year of the January. Data are expressed as anomalies from 1950 to 1979.
158
What surface observations tell us about the last 140 years sult has been confirmed by more sophisticated techniques which also use GCM results to estimate the additional uncertainty associated with the lack of data for the Southern Oceans (TRENBERTH et al., 1992; MADDEN et al., 1993). GUNST et al. (1993) estimate uncertainty using optimal statistical sampling techniques. In Figs. 1 and 2 warming begins in the hemispheric series around the turn of the century in all seasons. Only in summer in the Northern Hemisphere are the 1980s not the warmest decade. In this season, temperatures during the 1860s and 1870s were of a comparable magnitude to the most recent decade. In the Northern Hemisphere, interannual variability is greater in winter compared to summer. No such seasonal contrast is evident in the Southern Hemisphere. The hemispheric annual time series and their average (the global series) (Fig. 3) represent the major observational evidence in the "global warming" debate. Before moving to explanations of the past record (see section on Explanations of the instrumental temperature record) and to projections of it into the future (see section on Projections to the future), it is essential to consider both the spatial and diurnal nature of the changes and the longer-term context within which the instrumental record is perceived (section on The last 140 years in a longer term context), and temperature change throughout the atmospheric column (section on Upper air data during the last 40 years). Spatial patterns of change Although hemispheric and global series are heavily relied upon as important indicators of past climatic change, they mask the spatial details of temperature variability across the globe. Annual time series for 11 regions are given in WMO's report on the Global Climate
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0.0 --0.5 1860 1880 1900 1920 1940 1960 1980 Fig. 3. Global and hemispheric annual surface air temperatures for land and marine areas, 1854-1994. Data are expressed as anomalies from 1950 to 1979.
159
Observations from the surface: projection from traditional meteorological observations
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Fig. 4. Seasonal temperature anomalies for the Northern Hemisphere, 1981-1990. The anomalies are based on the 1950-1979 period. The contour interval is 0.5~ with negative anomalies dashed. Shaded areas indicate regions with insufficient data.
System (WMO and UNEP, 1993). The various curves highlight different levels of high-tolow frequency variability in each region. On a priori grounds there are only weak arguments to suggest why any regional series should be more indicative of global scale change than any other of comparable size. The issue has been addressed by a number of workers (see e.g. BARNETT, 1978; JONES and KELLY, 1983; FOLLAND et al., 1990, 1992; JONES and BRIFFA, 1992; BRIFFA and JONES, 1993; PARKER et al., 1994). Here we consider the spatial pattern of warmth during the 1981-90 decade. Seasonal temperature anomalies for the Northern and Southern Hemispheres, relative to the 1950-1979 reference period, are plotted in Fig. 4 (NH) and Fig. 5 (SH). Annual temperature anomalies are shown in Fig. 6. Most areas of the globe experienced above normal (1950-1979) temperatures for the 1981-1990 decade, although there was great variability from season to sea-
160
What surface observations tell us about the last 140 years
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Fig. 5. Seasonal temperature anomalies for the Southern Hemisphere, 1981-1990. The anomalies are based on the 1950-1979 period. The contour interval is 0.5~ with negative anomalies dashed. Shaded areas indicate regions with insufficient data.
son in the Northern Hemisphere (Fig. 4). Much of the decadal warmth was apparent during the DJF and MAM seasons, with the warmth located over northern and central Asia and over northwestern North America. During JJA, anomalies were smaller in magnitude over North America and negative over parts of Asia. During SON, temperatures were below normal over western Canada and Alaska but slightly above normal over Siberia. Over northern Africa temperatures were above normal during MAM, JJA and SON but below normal in DJF. Major areas of relatively consistent below normal temperatures included the central North Pacific Ocean and the northern North Atlantic region encompassing Iceland and Greenland. Over the Southern Hemisphere (Fig. 5) anomalies were generally smaller in magnitude except over parts of Antarctica. Almost all of the hemisphere was warmer than normal. The
161
Observations from the surface: projection from traditional meteorological observations
Fig. 6. Annual temperature anomalies for the Northern and Southern Hemispheres. The anomalies are based on the 1950-1979 period. The contour interval is 0.5~ with negative anomalies dashed. Shaded areas indicate regions with insufficient data.
major exception to this was a part of eastern Antarctica during MAM and SON. In tropical and temperate latitudes Australia, the Indian Ocean and the eastern equatorial Pacific were warmer than normal. The regions with the greatest warming over Antarctica were the Australian sector in JJA, SON and DJF and the Antarctic Peninsula in MAM and JJA. The annual anomaly maps for the two hemispheres (Fig. 6) obviously encompass the average features of the four seasons. Over the Northern Hemisphere relative warmth prevailed over most of Eurasia, especially Siberia, the western half of North America and western Africa. Temperatures were cooler during the decade over the North Pacific Ocean and the northern Atlantic region surrounding Greenland and Iceland. Most regions of the Southern Hemisphere have experienced warmth during the decade except for parts of eastern Antarctica, the Amazon Basin and part of the southwestern Pacific. Warmth during the decade was
162
What surface observations tell us about the last 140 years
greatest over the Indian Ocean, southern Africa, the eastern equatorial Pacific Ocean, the Antarctic Peninsula and the Australian sector of Antarctica. Although this decade has clearly been the warmest recorded since the beginning of the instrumental era, it is clear that the warming has not been global in extent. The term "global warming" therefore, is something of a misnomer. The warmth has also varied seasonally, being more significant in the boreal spring and winter and less in the boreal autumn and summer. Assessment of the spatial patterns of change is particularly important when considering possible causal factors for the changes. Diurnal temperature change
Most of the focus of past and future temperature change has been concerned with mean temperature. For past changes, this has resulted from a lack of readily available databases of monthly mean maximum and minimum temperatures. These data, since November 1994, are routinely exchanged between countries. For models, the diurnal cycle in the control runs is often poorly simulated. Few GCM experiments have so far considered maximum and minimum temperatures and the associated diurnal range. The issue is, however, particularly important with regard to climate change impact studies. The impacts of a change will, for example, be very different if the change affects only minimum temperatures rather than affecting both minimum and maximum equally. Recently developed data sets (KARL et al., 1993) have permitted analyses of maximum and minimum temperatures to be made for 37% of the global land mass (encompassing the contiguous United States, Canada, Alaska, the former Soviet Union, China, Japan, the Sudan, South Africa and eastern Australia). The analyses indicate (Fig.7) that over the 1952-1989 period, minimum temperatures have risen at a rate three times that of maximum temperatures. The reduction in the diurnal temperature range is approximately equal to the temperaI
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Fig. 7. Annual maximum, minimum temperatures and the diurnal temperature range for 1952-1989.
163
Observations from the surface: projection from traditional meteorological observations ture increase. The changes are detectable in all of the regions studied and in all seasons. Extension of the analyses to other regions is planned over the next few years. Results for New Zealand (SALINGERet al., 1993) suggest less organised changes compared to those for the major northern mid-latitude land masses seen by KARL et al. (1993). The causes of the differential increases in maximum and minimum temperatures are closely related to changes in cloudiness. Increases in cloud cover have been reported from Europe, Canada and Australia (HENDERSON-SELLERS, 1986, 1989; JONES and HENDERSON-SELLERS, 1992, respectively) although there has been marked station-to-station variability. Although decreasing diurnal temperature range is a characteristic signal of increasing urbanisation, irrigation usage and desertification, the widespread nature of the response and the lack of any seasonal bias suggests a large-scale climatic forcing. Possible factors are anthropogenic increases in sulphate aerosols and/or greenhouse gases. Neither factor is entirely convincing as more regional variability in the changes might be expected with sulphate aerosols (CHARLSONet al., 1991) while, for greenhouse gases, GCMs indicate a much smaller level of response (RIND et al., 1989; CAO et al., 1992). Natural variability is always a candidate for the explanation of the changes. Some long individual European records reveal large changes in diurnal temperature range with the recent decline being a relatively minor feature. With increasing data availability, studies in this area will become increasingly important in the issue of the detection of climatic change (see section on The next century).
Precipitation Analyses of precipitation data have tended to focus on regional rather than hemispheric scales. The reasons for this stem from two factors: precipitation data have much greater spatial variability compared to temperature and precipitation data from oceanic areas are virtually non-existent. For most areas of the world, precipitation variability, both in space and time, is so large that it will be generally difficult to detect trends statistically until after significant impacts have been felt in the agricultural and water resource sectors. Various regional time series were developed for the IPCC Scientific Assessments (FOLLAND et al., 1990, 1992). All of the studied regions in North America, Eurasia, Africa and Australia show large year-to-year variability in either annual or growing-season precipitation totals (see also WMO and UNEP, 1993). All show marked decadal-scale variation but with little long-term change on the century time-scale. There are two major exceptions to this. Average annual series for the former Soviet Union show a gradual increase in precipitation since the beginning of this century (Fig.8). Much of the increase has occurred in the non-summer season. Some of the increase may be related to the underestimation of snowfall during winter but even allowing for this a significant increase over the former USSR south of 70~ is still evident (GROISMAN et al., 1991). The most significant and dramatic changes in precipitation have occurred over the Sahel region of sub-Saharan Africa. Here the reduction of precipitation during the rainy season in recent years has been highly statistically significant. At some sites in the region there has been a decline of about 30% between averages for the two standard WMO periods of 19311960 and 1961-1990. The steep change would be even greater if the periods 1941-1970 and 1971-1990 were compared as the 1960s were relatively wet. Figure 9 plots the average time series for the region using the two standard WMO reference periods. Using the most recent
164
What surface observations tell us about the last 140 years
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Fig. 8. Standardised regional annual precipitation anomaly time series for the territory of the former Soviet Union. Standardisation of each station time series is achieved by subtracting the reference period precipitation and dividing by the standard deviation. The regional series is the average of all available station series. No form of areal weighting is used. The reference period used for calculating the annual means and standard deviations was 1951-1980. 1940
1860 1880 1900 1920 -~ r----r T r----r ~ I I_ Sahel (I0-15~ 1900-1992 2 t with r e s p e c t t o 1 9 3 1 - 6 0 m e a n
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Fig. 9. Standardised regional (annual) precipitation anomaly time series for the Sahel regions (1015ON; 20~ Two reference periods 1931-1960 and 1961-1990 are shown for comparison of the results.
165
Observations from the surface: projection from traditional meteorological observations period changes the appearance of the time series from the "Sahel drought" of the last 20years (relative to 1931-1960) to the "Sahel wet period" of the 1920s to the 1960s (relative to 1961-1990). The difference between the two analyses is not a simple change in level because of the use of standardised anomalies. Interannual variability is greater at most stations during the 1961-1990 period compared to 1931-1960. The reasons for the decline in rainfall have been widely discussed and a variety of causes have been postulated (LAMB, 1978; LOUGH, 1986; NICHOLSON, 1989). Rainy season (June-September) totals for the region appear to be partially predictable from the previous seasons' (March-May) sea surface temperatures in the Atlantic Ocean (FOLLAND et al., 1986; ROWELL et al., 1992). Global precipitation data sets have been developed recently, principally to assess the performance of GCMs (see section on Precipitation and pressure homogeneity). Assessment is achieved by comparing spatial patterns of model (control) and real-world precipitation climatologies (HULME, 1991). GCM climatologies, however, with 2x CO2 levels (perturbed) indicate an enhanced hydrological cycle with between a 7 and 15% increase in global total precipitation (MITCHELL et al., 1990). A reason for analysing global-scale precipitation, therefore, is to see if any increase is occurring. Detection of future climate change is developed in more detail later. Although large-scale precipitation series are a poor detection variable, because of greater uncertainties in both observed and model data, the impacts of climate change will be principally felt through changes in precipitation. Runoff, for example, is much more sensitive to precipitation than temperature (WIGLEYand JONES, 1985). Hemispheric- and global-scale precipitation have been studied in two papers (BRADLEY et al., 1987a; DIAZ et al., 1989). In both studies, the non-normal distribution of precipitation and its large spatial variability were accounted for by transforming all seasonal and annual precipitation totals using the gamma distribution. With this, precipitation totals are scaled between 0 and 1, median values that occur half the time having a value of 0.5. The distribution was fitted over the 1921-1960 period, and for each station, seasonal and annual estimates of the scale and shape parameters of the distribution were made. Large scale averages were calculated after the transformed precipitation data were interpolated onto an equal-area grid. For the Northern Hemisphere (BRADLEY et al., 1987a), the most interesting finding was a decline in precipitation during the last 40 years over subtropical areas (5-35~ and an increase in mid-latitudes (35-70~ These trends are consistent with many other analyses and are partially accounted for by the Sahel and the former Soviet Union trends discussed earlier. For the NH as a whole, there is considerable decade-to-decade variability but little overall trend. Northern summer and autumn seasons show a slight decline whereas winter and spring seasons show an increase. These trends are in accord with hemispheric temperature changes, providing evidence for a more intense hydrological cycle when average temperatures are higher. The Southern Hemisphere analyses (DIAZ et al., 1989) indicate increases in precipitation in both subtropical and temperate latitudes. The rise in precipitation is primarily due to increases in autumn and spring over South America. A slight increase is evident over Australasia and no change over southern Africa. The changes in precipitation in both hemispheres are broadly consistent with a number of GCM results with doubled CO2 levels (MITCHELL et al., 1990). The consistencies, however, are only on the largest of scales and do not survive scrutiny on small spatial and seasonal scales.
166
What surface observations tell us about the last 140 years
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Fig. 10. Winter (November-March) pressure difference (mb) between Ponta Delgada, Azores and Stykkisholmur, Iceland. Year dated by the January. Higher values indicate stronger westerlies over the North Atlantic.
Pressure
The interrelationships of the climate system mean that past changes in the patterns of temperature and precipitation patterns will undoubtedly also be accompanied by changes in circulation throughout the troposphere. Changes that have been noted range from local-scale studies such as the decline in westerlies over the British Isles (LAMB, 1972) to much larger regional scale indices such as the North Atlantic Oscillation (VANLOON and ROGERS, 1978), North Pacific winter pressure (TRENBERTH, 1990) and various Southern Hemisphere indices (including the Southern Oscillation) (KAROLY, 1995). The North Atlantic/European region has probably been studied more than other parts of the world, almost certainly because of the availability of long (>150 years) records. The wellknown out-of-phase relationship between winter temperatures over northern Europe (especially Fennoscandia) and Greenland has long been recognised (VAN LOON and ROGERS, 1978). The link between surface temperature anomalies in the region and the circulation of the North Atlantic region is evident in indices such as the North Atlantic Oscillation (NAO). Figure 10 shows seasonal (November-March) values of the NAO (difference in pressure between Iceland and the Azores). Stronger westerlies prevailed during the first two decades of the 20th century and again during the 1970s and 1980s. The weakest westerlies occurred during the 19th century and the 1960s. In the North Pacific region a major change in the strength and position of the Aleutian Low took place during the mid-1970s. After about 1977 the strength of the low pressure centre
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150~
Observations from the surface: projection from traditional meteorological observations increased and the centre moved slightly south particularly in winter (Fig. 11). In many respects the change may have been a return to the conditions that prevailed during the 1920s, 1930s and the early 1940s. Some of the change since the 1970s has reversed in the most recent years. The effects of the change in the mid-1970s in the climate of the whole N. Pacific region have been discussed by numerous workers (e.g. DOUGLAS et al., 1982; NITTA and YAMADA, 1989; TRENBERTH, 1990). The decreased pressures led to greater advection of warm maritime air on to the northwest of North America leading to enhanced precipitation and warmer temperatures. Alaska has experienced the greatest regional warmth over the Northern Hemisphere with average decadal temperatures I~ warmer than the 1951-1980 period during the 1980s. In contrast sea temperatures have been much cooler than normal in the central North Pacific and cooler air temperatures have been experienced over Japan and the Okhotsk/Kamchatka region. Although the region only explains part of the hemispheric increase, the change in climate of the region, particularly in the winter, has been abrupt. Some of the cause of the extratropical circulation change may be tropical in origin due to a lack of any significant La Nifia (see PHILANDER 1985 and Chapter 6 by DIAZ and KILADIS) events (TRENBERTH, 1990). Modelling studies support the tropical Pacific link (GRAHAM, 1995).
The last 140 years in a longer term context
The purpose of this section is to address, partly, the question of how much of the rise of temperatures can be explained by natural fluctuations. In addressing this issue we need to consider what is known about climatic variations of the last 1,000 years. Prior to the development of instruments, climatic information must be inferred from various naturally recording phenomena as well as from written historical records. The reconstruction of past climates is generally referred to as paleoclimatology. Numerous indicators exist, e.g. trees, ice cores, historical records, corals, varves, glacier movements, etc. (see BRADLEY, 1985 for a complete discussion of the methods and their strengths and weaknesses). In the following sections the changes in climate inferred, from the proxy climate sources, for the last 1,000 years are surveyed (see WILLIAMS and WIGLEY, 1983; JONES and BRADLEY 1992; BRADLEY and JONES, 1992a, 1993; see Chapter 6 by DIAZ and KILADISfor more details). Over the last 1,000 years three main episodes are evident in many, but not all, proxy records from the Northern Hemisphere. Although less well studied, Southern Hemisphere evidence from South America, Australia and New Zealand suggests that these main events also occurred there. The first episode is a cool period spanning approximately the 9th and 10th centuries. Following this a warm period, the "Medieval Warm Period", occurred which was at its maximum during the early 12th century A.D. After this period, climate entered the period known as the "Little Ice Age". This period was marked by cooler conditions between the 14th and 19th centuries, although not always. It was probably cool from 1300 to 1450 and again from 1550 to 1850 (WILLIAMS and WIGLEY, 1983). A general warming of the climate from the 10th to the 12th century is evident from both North America and Europe. By the 12th century, trees were living beyond their present limits in Alaska and the Yukon. In Europe winter temperatures were generally mild. Conditions in Greenland were best for human exploitation during the 10th and 1 lth centuries and this
168
Upper air data during the last 40 years allowed the establishment of two main Norse settlements in western and southern Greenland with combined populations of over 5,000 people (McGOVERN, 1981). The ensuing cooler conditions are confirmed by glacier advances in North America and Europe during the 14th, 16th and 17th centuries. The advances in different regions were never synchronous, but they point to cooler conditions for about 300 years interspersed with a few warmer episodes in different regions at different times (GROVE, 1988). Paintings of glaciers in Switzerland
(ZUMBUHL, 1976) show evidence of cooler summers, with the glaciers reaching their maximum extent in the late 17th century. Tree ring evidence in Switzerland and Scandinavia indicates similar timings. Hill farms were abandoned in many areas of upland Europe. It is impossible to say when the coldest periods were globally, because of different seasonal timings of the coldest phases in different parts of the world. From an analysis of 16 "summer-responding" proxy records in the middle-to-high latitudes of the Northern Hemisphere BRADLEY and JONES (1993) conclude that the coldest conditions of the last 560 years were between 1570 and 1730 and in the 19th century. Longer single-site and composite instrumental records confirm the annual warming from the late 19th century. The long European records, however, show that the 1880s were the coldest decade, at least since 1700, so part of the warming since then may reflect this unusually low starting point.
Upper air data during the last 40 years There are two methods for measuring temperatures at different levels in the atmosphere. These are the conventional radiosonde network (ANGELL, 1988) and the microwavesounding unit (MSU) on the TIROS-N series of satellites (SPENCER and CHRISTY, 1990 and see also Chapter 7 by DICKINSON). The conventional network extends back to 1958 and the MSU data to 1979. Before comparing the two sets of analyses with each other and with the surface, their advantages and limitations are discussed. Both sets of information are used routinely in global scale analyses undertaken at several operation centres (e.g. ECMWF, NMC, World Meteorological Centre-C at Melbourne), but changes to the operational models and data assimilation schemes mean that the homogeneity of long-time series (as for surface pressures also, see above) must be questionable (TRENBERTH, 1992). In the following it is preferable to use the original station and satellite observations rather than the analysed fields. There are many potential problems even with the original station measurements due to changes in sonde design and the timing of observations (see GAFFEN, 1994; PARKER and Cox, 1994) The conventional radiosonde network began in the late 1940s, but an important instrument alteration in the mid-1950s and a change of observation timing means that the most consistent long series begin in 1958 (ANGELL, 1988). Extension back prior to 1958 may be possible but would be limited spatially to the mid-to-high latitudes of the Northern Hemisphere because of data availability. The most widely studied data set is that produced by Angell and Korshover (see ANGELL, 1988) using a network of 63 stations spread as evenly over the world as data availability allows. The data are available seasonally from 1958 for seven zones of the world, each the average of the stations in each zone. Using up to four times as many stations as ANGELL (1988) for the northern polar zone, KAHL et al. (1993) have confirmed the earlier results. The spatial representativeness of the Angell network on a global
169
Observations from the surface: projection from traditional meteorological observations scale has been examined by TRENBERTH and OLSON (1991). They compared complete global analysed fields from the ECMWF for 1979-1987 and found that correlations between the two were quite high, although root-mean-square errors for Angell's data were high in zones with fewer stations particularly the Southern Extratropics. The advantage of the 63 site network is that averages are easy to compute. The disadvantages are that the network is sparse and only the very largest of spatial features will be measured. Recently OORT and LIU (1993) have interpolated monthly radiosonde data onto a regular latitude/longitude grid from over 800 radiosonde sites. Although there is a considerably greater amount of data used, agreement with the Angell data set is extremely high (FOLLAND et al., 1992). In the following comparisons we use the Angell data set because it has been more widely used. Two levels are used, lower troposphere (850-300 mb) and lower stratosphere (100-50 mb). The MSU data are direct satellite measurements of microwave emission of radiation from space due to molecular oxygen in the atmosphere (SPENCERand CHRISTY, 1990). The satellite measures four channels but most analyses have concentrated on channels 2 (lower troposphere) and 4 (lower stratosphere). Because channel 2 is contaminated to some extent by variations in the upper troposphere, a modification placing greater emphasis on the lower troposphere, channel 2R was developed (SPENCERand CHRISTY, 1992b). This is used here and in other related studies (FOLLAND et al., 1992). The advantages of MSU are a single instrument and global coverage which means lower standard errors than conventional radiosonde data (SPENCERand CHRISTY, 1992a,b). The major disadvantages are that the series is short (1979 to the present) and is developed from a number of instruments on different satellites. Although overlaps enable corrections to be made, these may slightly affect the long" term homogeneity of the record.
Comparisons of lower tropospheric data sets Comparisons of the data sets have been made by a number of other studies (WIGLEYet al., 1985, 1986; FOLLAND et al., 1990, 1992; TRENBERTH et al., 1992). This section is focussed upon the period since 1979. Correlations between the three data sets are shown in Table I, on the monthly, seasonal and annual time-scales. ANGELL's (1988) data are only available for the traditional seasons and his annual series is for a December to November year. Correlations are always higher for the Northern than for the Southern Hemisphere, and higher the greater the averaging period. MSU2R data correlations with Land/Marine, Land Only and 850-300 mb data have similar values increasing slightly for each time-scale. Lower correlations between MSU2R and the surface over oceanic areas (which dominate the SH record) have been noted by TRENBERTH et al. (1992). The highest correlations of all are found between Land Only and Land/Marine data, but this is to be expected as the Land Only data set is the most variable part of the combined data set. Monthly time series of the Land/Marine and MSU2R data are shown in Fig. 12 for the 1979-1992 period. The interhemispheric correlations for MSU2R are clearly higher than for Land/Marine (see Table II). Variations of MSU2R between the two hemispheres are highly correlated on all time-scales. At the surface, the variability is clearly greater over the Northern Hemisphere. The marked cooling of the records during 1991 is discussed in the next section and in the section on External forcing of the climate.
170
Upper air data during the last 40 years TABLE I INTERCORRELATIONS BETWEENRADIOSONDE (850-300MB), M S U 2 R AND SURFACE DATA (1979--1992)
Time period
Correlation pair
NH
SH
Global
Monthly (164) d
MSU2R v LM a MSU2R v Land b LM v Land MSU2R v LM MSU2R v Land MSU2R v 850-300 c LM v Land LM v 850-300 Land v 850-300 MSU2R v LM MSU2R v Land MSU2R v 850-300 LM v Land LM v 850-300 Land v 850-300
0.62 0.58 0.96 0.69 0.63 0.76 0.98 0.67 0.65 0.84 0.81 0.89 0.99 0.93 0.92
0.45 0.56 0.85 0.57 0.67 0.74 0.83 0.51 0.63 0.59 0.74 0.88 0.97 0.63 0.74
0.62 0.62 0.94 0.70 0.70 0.80 0.96 0.69 0.70 0.79 0.81 0.93 0.99 0.89 0.89
Seasonal (52) d
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a LM, land + marine (JONES et al., 1991) b Land, land only (JONES et al., 1986a,b) c 850-300, 850-300mb (ANGELL, 1988) d No. of cases.
Comparisons of lower stratospheric data sets FOLLAND et al. (1990, 1992) have performed a number of comparisons between MSU channel 4 (MSU4) data and conventional radiosonde data from ANGELL (1988) and OORT and LIU (1993). Table III gives correlations between MSU4 data (SPENCER and CHRISTY, 1993) and the 100-50 mb data from ANGELL (1988). These correlations are slightly higher than the similar comparisons for the lower troposphere. Figure 13, which shows the monthly time series of MSU4 data for the two hemispheres, clearly suggests a different pattern between the two hemispheres. Interhemispheric correlations are significantly lower than for the lower troposphere (see Table II). The warming and cooling episodes in the lower stratosphere are related to the increase in aerosol loading resulting from the E1 Chich6n and Mt. Pinatubo volcanic eruptions (see section on External forcing of the climate).
TABLE II INTERHEMISPHERIC CORRELATIONSFOR RADIOSONDE (850-300MB AND 100-50MB), MSU2R, M S U 4 AND SURFACE DATA (ABBREVIATIONSAS IN TABLE I)
MSU2R LM Land 850-300 mb MSU4 100-50 mb
171
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1980 1982 1984 1986 1988 1990 1992 1994 Fig. 12. Hemispheric monthly averages of land and marine temperatures (surface; data from Figs. 1 and 2) and MSU2R data (lower troposphere; SPENCERand CHRISTY, 1992b). The time intervals given in each panel are the reference intervals from which anomalies have been calculated.
Explanations of the instrumental temperature record Explanations of changes in hemispheric- and global-mean climate over the past 100 years or so have concentrated on temperature variations. Temperature is the most reliably measured variable, in terms of accuracy of regional averages, and the most widely studied. Changes in precipitation and pressure, particularly on the regional scale, have undoubtedly occurred and variations in all three are strongly interrelated. It might be suspected that precipitation totals over global land-areas have increased over the 20th century but we are not as confident of the data as we are for the 0.5~
rise in global temperatures. Despite the fact that precipita-
tion variations have a greater impact on human activities than variations in other variables, TABLE III INTERCoRRELATIONS BETWEEN RADIOSONDE (100-50MB) AND M S U 4 DATA (ABBREVIATIONSAS IN TABLE I)
172
Time period
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0.89 0.93
0.78 0.97
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Explanations of the instrumental temperature record
1980 1982 1984 1986 1988 1990 1992 1994 2.0
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1.5 1.0 0.5 0.0 -0.5 -1.0 2.0 1.5 1.0 0.5 0.0 -0.5 -1.0 1980 1982 1984 1986 1988 1990 1992 1994
Fig. 13. Hemispheric monthly averages of MSU4 data (lower stratosphere; SPENCERand CHRISTY, 1992b). The time intervals given in each panel are the reference intervals from which anomalies have been calculated. we concentrate here on global-mean temperature, which is a fundamental measure of the state of the climate system. All variations in the historic and geologic past are considered as cold or warm epochs. The possible causal factors affecting global-mean temperature are conveniently grouped as either "internal" or "external" (ROBOCK, 1978). Internal factors are those which must be considered even in the absence of potentially larger changes in external forcing. Factors include natural changes in planetary albedo resulting from changes in cloudiness or in surface characteristics and changes in the circulation of the atmosphere and/or the ocean. The latter factor determines the lower boundary conditions for the atmosphere and the rates of heat exchange between the ocean and atmosphere. The former factors determine the spatial distribution of heat sources and sinks, as well as the horizontal and vertical fluxes of sensible and latent heat. Man-induced surface albedo changes should strictly be classified as external but, although their effects may be important at the regional scale, they are unlikely to be at the global scale. The main external factors are changes in the Sun's output or luminosity, changes in the fraction of shortwave solar radiation reaching the troposphere (due to injection of particulate matter and sulphate aerosols in the stratosphere following volcanic eruptions), changes in the reflectivity of clouds due to industrial activity and changes in the vertical distribution of outgoing longwave radiation flux in the troposphere due to increasing concentrations of greenhouse gases. Internal forcing of the climate It is likely that most of the interannual variability shown in Figs. 1-3 is the result of natural variability, even though the precise causes cannot be quantified. On slightly longer timescales, such as 2-8 years (but still classed as natural variability as it results from internal forcing), the ocean circulation and related changes in sea surface temperatures in the tropical Pacific Ocean associated with the E1 Nifio/Southern Oscillation (ENSO) phenomenon
(RASMUSSEN and CARPENTER, 1982; PHILANDER, 1983; see also Chapter 6 by DIAZ and
173
Observations from the surface: projection from traditional meteorological observations KILADIS) have a noticeable effect on hemispheric and global temperatures. This phenomenon, along with the similar long-term trends, is responsible for much of the high annual correlation ( r = 0.79, 1901-1990) between the two hemispheres. Many warm years relative to the filtered curves have been shown to be E1 Nifio or "warm event" years (BRADLEY et al., 1987b; VAN LOON and SHEA, 1985). In contrast many cold years relative to the filtered curve have been previously classified as La Nifia (PHILANDER, 1985) or "cold event" years. Even during the last 12 years the warm and cold event years can be seen in the MSU2R record (see Fig. 12). Using the Southern Oscillation Index (SOI), the pressure difference between Tahiti and Darwin, (see ROPELEWSKI and JONES, 1987; ALLAN et al., 1991; and Chapter 6 by DIAZ and KILADIS for more details), JONES (1989) has removed the ENSO influence from the ,annual hemispheric and global temperature series. The SOI explains about 25-30% of the high frequency (<20 years) variations in hemispheric temperature anomalies (see Fig. 14). Removal of the influence may assist in the early detection of greenhouse gasrelated trends (NICHOLLS and KATZ, 1991). When the ENSO effect is factored out, the warming in recent years becomes more obvious and the long-term warming more significant. In explaining the century time-scale temperature history we need to consider natural variability on decadal and longer scales. It is not possible to estimate the scale of natural internal variability from the observational record because there is only a single realisation of global temperature change on this time-scale and this record is almost certainly contaminated by many external factors. We do know, however, that considerable decadal and longer timescale variability should occur as a result of the way the ocean modulates all high-frequency forcing. Because of the ocean's large thermal inertia, the system tends to behave like a first
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174
Explanations of the instrumental temperature record order autoregressive process in which white-noise atmospheric forcing is converted to a rednoise response (HASSELMANN, 1976). In this way even if there are only purely random changes in the atmospheric part of the system, the large heat capacity will produce a shift towards lower frequencies. This effect can be quantified by using an appropriate energy balance model, forcing it with white noise of an amplitude sufficient to reproduce the observed high frequency variations of global mean temperature. WIGLEY and RAPER (1990, 1991) have run such a model and have shown that low-frequency changes in global mean temperature similar to those that occur can be produced. Similar effects have been seen in some GCM results (STOUFFERet al., 1989; HANSEN et al., 1988). On the century time-scale, these variations could easily be as much as 0.2-0.3~ Thus, up to half of the observed warming since the 19th century could be a natural, internal fluctuation. Equally well, however, a much larger externally forced warming of 0.7-0.8~ could have been partially offset by a natural, internally generated cooling.
External forcing of the climate The most widely considered factors are changes in solar irradiance, the effects of explosive volcanic eruptions and the enhanced greenhouse effect. Solar irradiance changes and their effect on weather and climate are one of the most studied areas of climatology. Most theories have been shown to fall down when statistically tested with independent data (PITTOCK, 1979, 1983). Recently solar weather relationships have received a resurgence of interest, following work by VAN LOON and LABITZKE (1988) (see next section ). It is only recently that we have obtained, through satellite observations, evidence that the Sun's output does vary in parallel with the 11-year sunspot cycle (WlLLSON and HUDSON, 1991; see also Chapter 7 by DICKINSON). These variations, however, are small, amounting to at most about 0.1%. Because only 12% of this is absorbed at the Earth's surface (the intercepted radiation covers only a quarter of the Earth's surface and 30% is reflected back to space) the change in forcing of 0.24 W m -2 would be virtually impossible to detect. If the climate system were able to reach a new equilibrium state after the forcing, a change of 0.08-0.24~ could occur at the surface. However, as the climate system takes decades to reach a new equilibrium and the forcing is approximately cyclic with a period of about 11 years the response is less than 0.03~ in global-mean terms. Periods of prolonged sunspot minima such as the Maunder, Sp6rer and Wolf minima have occurred in the historic past (EDDY, 1976; STUIVER and BRAZIUNAS, 1989). These were long enough for the climate to reach a new equilibrium and they may be the cause of the Little Ice Age events (WIGLEY and RAPER, 1995). Solar radius variations have been suggested as a cause of variations over the past 100 years (GILLILAND, 1981, 1982). These should affect solar output, according to astrophysical studies, with a cycle of about 80 years, and there is evidence of quasi-cyclic radius changes over the past few centuries. A new approach (FRIIS-CHRIsTENSEN and LASSEN, 1991) uses the length of the sunspot cycle which is known to be related to solar activity. The authors achieve a high correlation (-0.95) between highly smoothed cycle length data and similarly smoothed hemispheric average temperatures for the Northern Hemisphere. Further discussion of this relationship is given by KELLY and WIGLEY (1992) and SCHLESINGER and RAMANKUTTY (1992). Both ideas, however, suffer from the same p r o b l e m - namely that the
175
Observations from the surface: projection from traditional meteorological observations forcing is not great enough and the nature of the mechanism, and presumably also any required amplification, is not known. Only time, and satellite observations of solar irradiance (measurements above the atmosphere) and other solar parameters such as the radius, will eventually resolve the uncertainties surrounding solar forcing. The situation with regard to volcanic influences is more clear cut, at least on short timescales. It was Benjamin Franklin, in the 1780s, who first associated unusual weather in Europe with an Icelandic volcanic eruption in 1783. Curiously, this particular eruption (Skaft~ireldar, often referred to as Laki) was not of the explosive type now associated with effects on climate. Hemispheric climatic effects generally only occur if the ejected dust and gases reach the stratosphere, since it is only here that their residence time is sufficient to have a noticeable cooling effect. Normally, however, such a layer is only likely to occur through the violence of an explosive eruption and the rapid and direct injection of dust and sulphur dioxide into this part of the atmosphere. There is now a considerable body of modelling and observational evidence for the cooling effect of individual volcanic eruptions (BRADLEY, 1988; BRADLEY and JONES, 1992b, 1993; see also Chapter 4 by RAMPINO). Major eruptions, of the size, for example, of Krakatoa (1883) appear to have caused short time-scale cooling of the lower atmosphere of a few tenths of a degree Celsius, beginning within a few months of the eruption and noticeable for 1 or 2 years subsequently (KELLY and SEAR 1984; SEAR et al., 1987). Less violent eruptions, if they have high sulphur dioxide emissions, may also have noticeable effects: the best example here is the eruption of Agung in 1963 (ANGELL and KORSHOVER, 1985). In recent centuries, the eruption of Tambora in 1815 appears to have been the most violent. The following summer was so cool and wet in Europe and eastern North America that 1816 came to be known as "the year without a summer" (HARRINGTON, 1992). Unfortunately, Tambora occurred too early for us to be able to quantify its cooling effect reliably in global terms. When the record of historical information on major eruptions is compared with hemispheric temperatures in Figs. 3 and 14, short term cooling for a year or two can be seen to be associated with the eruptions of Krakatoa (1883), Pelee/Soufri~re/Santa Maria (1902) and Agung (1963). The effect of the recent eruption of Mt. St. Helens (1980) was negligible because most of the explosion was directed more sideways than vertically, while the effects of E1Chich6n (1982) and Mt. Pinatubo (1991) may have been, to some extent, confounded by E1 Nifio events which occurred at about the same time. Clear cooling, however, is evident during the period April-November 1992 and again during the same period in 1993 in both surface and MSU2R data (Fig. 12). The stratospheric warming following the event is apparent in Fig. 13, despite being superimposed on the compounding effects of other sources of natural variability. Modelling studies (HANSEN et al., 1992) indicated a cooling after the Mt. Pinatubo eruption of about 0.5~ in global terms. The effects of the eruption may not be finished yet, but the magnitude of the observed cooling is at most 0.3~ for annual means. The tropospheric/stratospheric contrast is less clear after the E1 Chich6n eruption. When just the annual mean values are examined (Figs. 3 and 14), however, there are many short term cooling events that are not associated with volcanic activity. It is necessary, therefore, to go to the monthly time-scale to identify volcanic effects clearly (SEAR et al., 1987). The decadal-to-century time-scale effects of volcanic eruptions are much more debatable, although sound arguments for their importance can be made (BRADLEYand JONES, 1993). One of the problems here is that we have no convincing continuous record of the volcanic
176
Explanations of the instrumental temperature record aerosol forcing, and so no way to say with any confidence what the longer time-scale climatic response might be. There are numerous independent indicator time series which might be (and have been) used. These include the historical record of eruptions together with estimates of their strength, the Volcanic Explosivity Index (SIMKIN et al., 1981) and LAMB's (1970) record of the Dust Veil Index. This latter index uses a variety of sources including tephra volume and unusual sunsets to assign an index value to each eruption. For a few eruptions in the 17th century, Lamb uses the presumed temperature cooling following the eruption. Another historic record is the record of atmospheric transparency which, unfortunately, comes from a rather limited network of observation sites (PIVOVAROVA, 1977). There are also records of sulphate concentration and acidity in Greenland and Antarctic ice cores (HAMMER et al., 1980; MOORE et al., 1991). These show strong parallels with the eruption history and are thought to be an indicator of the history of stratospheric sulphate aerosol loading. Unfortunately, when these different forcing "proxies" are compared, they correlate rather poorly (BRADLEY and JONES, 1985). Furthermore, none of the indices is clearly a measure of the global amount and duration of sulphur dioxide in the stratosphere following an eruption. If one accepts the volcanic influence on short time-scales, then, even if the aerosol is removed from the stratosphere within a few years, as seems likely, it still could be argued that there may be more prolonged climatic effects because of oceanic thermal inertia (ROBOCK, 1979). The warming between 1920 and 1940 may, thereby, be partly attributable to the dearth of large eruptions over this period (ROBOCK, 1991). Unfortunately, modelling studies do not offer any strong support for this idea. In any event, explaining the 1920-1940 warming in this way is a rather selective interpretation of the data as cooling began in the early 1940s and the first major eruption was not until 1957. What then of the enhanced greenhouse effect- the term for the build-up of radiatively active gases in the atmosphere due to anthropogenic activity? At least in this case (see also Chapter 9 by WANG et al.) we have a good record of the forcing changes over the past few centuries (WATSON et al., 1990, 1992). During this time carbon dioxide (CO2) concentrations have increased from around 280 ppmv to more than 350 ppmv today, methane (CH4) concentrations have more than doubled (from 800 ppbv to around 1700 ppbv), nitrous oxide has increased by some 10% and, over the last 30 years or so, the concentrations of a large number of chlorofluorocarbons (CFCs) have increased at alarming rates. These are all important greenhouse gases. Molecule for molecule, CH 4 is some 30 times more powerful than CO2 while some CFCs are more than 10,000 times as efficient as CO2. The combined effect of these gases amounts to a radiative forcing change at the top of the troposphere of about 2.5 W m -2 over the past few centuries, i.e. roughly equivalent to increasing solar output by 1% (HOUGHTON et al., 1990). The corresponding equilibrium global-mean temperature change would be a warming of between 0.7~ and 2.5~ (the uncertainty is due to a lack of quantitative understanding of various feedbacks in the climate system's response to external forcing, in particularly the climate sensitivity). However, because the thermal inertia of the oceans causes a lag in the response, the expected observed warming is substantially less than this - probably somewhere between 0.5~
and 1.3~
over the period 1880-1992
(HOUGHTON et al., 1990, 1992). Thus, the observed warming of around 0.5~
appears to be consistent with that expected
from the greenhouse effect, but only if the climate sensitivity (best guess IPCC value in
177
Observations from the surface: projection from traditional meteorological observations 1992 is 2.5~
is at the low end (~1.4~
of the range predicted by General Circulation
Models (WIGLEY and BARNETT, 1990; WIGLEY and RAPER, 1990). This does not, however, mean that we can claim to have positively detected the enhanced greenhouse effect, nor to have demonstrated that it is relatively small. Given the possible magnitude of natural, internally generated variability, and the possibility that changes may have occurred as a result of other external forcing factors, the observed warming could still be attributed to factors other than the greenhouse effect. Alternatively, a larger greenhouse effect may have been offset by these other factors. There are a number of characteristics of the observed record that appear to be in conflict with the greenhouse hypothesis (WIGLEY and BARNETT, 1990). The warming between 1920 and 1940 was too rapid, while the cooling between 1940 and the mid-1970s occurred at a time when all greenhouse gas concentrations were increasing rapidly. Furthermore, the records from the individual hemispheres do not accord with expectations; more ocean in the Southern Hemisphere should lead to a damped response there, yet it seems more as if the Southern Hemisphere has been leading slightly in the warming race. Of course, all of these discrepancies can be explained away, at least qualitatively. The rapid early 20th century warming could be a manifestation of internal variability or it may partly reflect lessened volcanic activity and/or solar irradiance changes. The cooling from 1940 may also just be natural variability superimposed on (and offsetting) the greenhouse effect. This cooling appears to have been forced in the Northern Hemisphere and communicated in a reduced form to the Southern Hemisphere by interhemispheric transport mechanisms. One possible hemispherically specific forcing mechanism is changes in ocean circulation, specifically changes in the rate of North Atlantic Deep Water formation. Alternatively, this cooling (and NH/SH differences in general) could be the result of anthropogenic sulphur dioxide emissions, which, it has been suggested, could lead to noticeable increases in the albedo of oceanic cloud masses (CHARLSON et al., 1991). Since the dominant sources of sulphur dioxide are in the Northern Hemisphere, and since this gas has a short atmospheric residence time, the implied cloud albedo changes would be mainly in the Northern Hemisphere. Invoking this effect enables a higher climate sensitivity (2.5 ~ compared to 1.4~ to be compatible with the observational record (WIGLEY and RAPER, 1992). Incorporating changes in solar irradiance (using the solar cycle length series as a proxy) further alters the estimation of the climate sensitivity made from the observational record (SCHLESINGER and RAMANKUTTY, 1992). Given these uncertainties, most of which, because of the absence of suitable data, can never be resolved, it is impossible to give any firm interpretations of the undeniable global-scale warming that has occurred this century. We can note that the warming is at the lower end of the range predicted by the models of greenhouse conditions, but this does not preclude the possibility that the greenhouse effect is even smaller than current models suggest. Neither, however, does it preclude the possibility of a very strong greenhouse effect which, up until now, has been partially offset either by natural variations in climate or by other anthropogenic influences. Climatologists, therefore, are keeping a close watch on global temperatures and on possible forcing factors. Together with advances in modelling, this will eventually lead to reduced uncertainties in the magnitudes of all the factors which are thought to influence the climate (including the enhanced greenhouse effect) and to better predictions of future climatic
178
Projections to the future change. In the meantime, attempts to explain past variations in global-mean temperature, particularly those using a single external factor, are bound to be unsatisfactory. Quite probably, we will have to wait until future observations have clarified the magnitude of the enhanced greenhouse effect before we can say much more about the causes of past climatic change. Almost certainly, we will find that the past record (which is only known in global terms with some certainty since the middle of the 19th century) will be explained by an as yet unknown combination of the various factors discussed here, some of whose histories we now know well and some which we do not. Determining the combination is, unfortunately, embroiled in the pro- and anti-greenhouse debate.
Projections to the future The near future (<30 years)
On this time-scale any change due to the enhanced greenhouse effect is likely to be at most 0.5~ It is likely that any greenhouse warming should be detectable in this time frame despite the scale of natural variability of the climate system (see the next section for a more complete discussion of greenhouse effect detection). We cannot adequately explain the changes that have taken place over the last 140 years. IPCC estimates an increase of temperature relative to 1990 of about 0.5~ by 2010 (GREGORY and MITCHELL, 1992; IPCC emissions scenario IS92a). Prediction of climate trends and patterns has been one of the goals of climatology since the birth of scientific instrumentation. The most widely tried forecasting method (predictions on time-scales of 5-10 years) has used presumed solar weather relationships, all of which have been found to fail when better statistics and/or more data have been utilised (PITTOCK, 1979, 1983). The FRIIS-CHRISTENSEN and LASSEN (1991) approach (see above) is the latest in a long line of speculative ideas. A more convincing hypothesis, from a statistical point of view, has been postulated (VAN LOON and LABITZKE, 1988) which links changes in tropospheric circulation with the 11-year solar cycle, the exact relationship dependent on the phase of the wind direction in the stratosphere at the equator (the quasi-biennial oscillation, QBO). The relationships have been shown to be strong in certain regions and it has even been used in seasonal forecasting (BARNSTON and LIVESEY, 1989). Such work is, however, still somewhat premature, as no mechanism has been proposed. Although sunspot data are available since 1700, data for the QBO are only available since the late 1940s. If the relationship is found to continue to hold during the next 20 years, greater emphasis should be placed on finding the link through which the process operates. Another means of climate prediction that has been developed recently is Singular Spectrum Analysis (SSA) (GHIL and VAUTARD, 1991). The method is an eigenvector decomposition of a time series, concentrating on variations with periods greater than 5 years. Projection of the leading components into the future gives the forecast. GHIL and VAUTARD (1991) used the method to project global mean temperatures into the future, forecasting a fall in temperatures during the early 1990s, followed by a later rise. The method is somewhat controversial, with ELSNER and TSONIS (1991b) suggesting that the principal oscillations used by the technique depend critically on the length of the data record used (see also ALLEN et al.,
179
Observations from the surface: projection from traditional meteorological observations 1992). Whoever is right, the method warrants further research. One means of ascertaining whether the method is useful is to use it with longer time series. Some of the recent years can then be kept back for verification of the method (as is the common practice in paleoclimatology). The second half of the next century
Whether people are capable of altering the climate of the Earth through the enhanced greenhouse effect, by past and continuing emissions of greenhouse gases, is the most important issue in climatology today. The issue, popularly termed "global warming", could have a significant impact on society. On the time-scale of the next century, if our current understanding of the climate system is correct, the average global temperature by 2100 should be about 3~ warmer than present values (GREGORYand MITCHELL, 1992; IPCC emissions scenario IS92a). A temperature rise of this order, coupled with the associated changes in the hydrological components (especially precipitation, cloudiness and evaporation) will undoubtedly change the climate of every location on the planet. Regionally, the warming and the disturbances in the hydrology might be large; a few regions might even cool. Impacts and policy responses will be determined by local-to-regional scale effects. The enhanced greenhouse effect, however, will only be detected at the global scale, and is to some extent independent of what happens at smaller scales. In this final section, we discuss this aspect of the problem: detection of the effect in the global observational record. Much of the climatological research undertaken today, both directly in atmospheric sciences and in many related disciplines, is focussed towards improvements in our understanding of this one issue. There have been a number of international assessments over the last 10 years of which the two IPCC reports (HOUGHTON et al., 1990, 1992) are the most recent. The important aspects of the issue are therefore constantly changing, as research solves some questions, but generally asks many more. Modelling is a case in point. Although dramatic improvements have been made, principally through General Circulation Models (see Chapter 9 by WANG et al.) over the last 25 years, it is likely to be several decades before modellers will have much faith in their scenarios (cf. Chapter 7 by DICKINSON and Chapter 3 by B ARRON). In other words, predictions made now for some future time frame will change countless times before their veracity can be assessed, possibly with reference to satellite data (Chapter 7 by DICKINSON). How should policymakers respond to the projections? Given uncertainties in other areas, a typical response strategy is to spread the risk by insurance. In the global warming issue, the "no regrets" response would be to incorporate all energy saving options into new designs, cutting back on all wasteful energy usages while funding research that it is hoped will narrow scientific uncertainty. Even this response is too radical for many, who state that nothing should be done until we have categorical proof that we can see the effect in the climatic record. The importance of detecting the effect in the observations is therefore clear. In attempts to detect the enhanced greenhouse effect, the key step is to be able to attribute an observed change in climate to this specific cause. A rise in temperature over the last 130 years has occurred, but it might have occurred without any increase in greenhouse gases. Attribution almost certainly requires the identification in the observational record of a multivariate signal characteristic of greenhouse gas-induced climatic change. The signal
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Projections to the future should ideally be unique to this specific cause. This approach to detection has been termed the fingerprint method (MADDEN and RAMANATHAN, 1980; MACCRACKEN and MOSES, 1982). In most applications tried so far, the detection variable has been a vector, whose components have been different scalar variables (e.g. temperature, precipitation, etc.) or the same variable measured at different places (e.g. temperatures measured at different locations on the Earth's surface or at different levels in the atmosphere). The strategy of detection is to compare the observed time series of the vector with an estimate from GCM results (e.g. the difference in the equilibrium response experiments for 2 x CO2 and 1 x CO2 or the difference between a transient model run with time-dependent forcing and the 1 x CO2 equilibrium response) using pattern correlation techniques. Some thought should be given to the choice of detection vector. All the individual components should have high signal-to-noise ratios (SNRs). Poor choices in this regard are precipitation and sea-level pressure, while a better choice would be surface temperature. The detection vector should not be model specific. If GCMs give different results this would lower confidence in the model signal which is being sought. The detection vector should be easily distinguishable from other signals. Important in this regard is that it should, ideally, be very different from the pattern of natural climatic variability. Finally, suitable long observation records should exist. Long records are needed because it is the decadal-to-century time-scale that is of most interest. At present all detection attempts have been unsuccessful. BARNETT (1986) and BARNETT and SCHLESINGER (1987) failed to find the 2x CO2 signal from the Oregon State University GCM in surface temperature data. More recently, SANTER et al. (1993) failed to find the spatial pattern of the signal from a number of GCMs in surface temperature data, while KAROLY et al. (1994) failed to find the elevational signal (temperature change at different levels in the atmosphere) from GCMs in tropospheric and stratospheric radiosonde data. The lack of success can be interpreted in a number of different ways. If the model results are correct, our lack of success could be due to the signal being obscured by the background noise of natural climatic variability or by the signals due to other forcing factors. Another possibility is that the climatic sensitivity is much less than the models suggest. In the same vein, the lack of success may be because the signal patterns, from the current generation of GCMs, are wrong. Other than waiting for the models to improve sufficiently and/or for the accumulation of more observational data in which the signal might be more readily apparent, what can be done to speed up the time by which detection might be achieved? First, we should experiment with other pattern correlation or optimum detection techniques, addressing the issue of quantifying the signal. It is not adequate to claim detection per se, it is also necessary to attempt to quantify the strength of the signal (i.e. to estimate the climate sensitivity and/or how much of the rise in temperatures is due to this specific cause). This assessment is vital to strategies to mitigate the build-up of greenhouse gases in the atmosphere. Second, attempts should be made to detect the signals of other forcing factors such as sulphate aerosols and volcanoes, as these may be easier to detect than greenhouse gases. If these can be detected it may be possible to remove their influence and thus reduce noise levels. Addressing the attribution question is crucial. To do this we need to improve our understanding of both low-frequency natural variability and the climatic signals due to other forcing factors.
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Observations from the surface: projection from traditional meteorological observations The evidence from traditional meteorological observations cannot confirm the existence of an enhanced greenhouse signal commensurate with the predictions of state-of-the-art Climate Models. Thus, if the models are to be believed (cf. Chapter 9 by WANG et al.) there must be other factors which, individually or in combination, are moderating or slowing the observed warming (see e.g. Chapter 10 by ANDREAE). If these factors persist the model predictions will be overestimated but if they "switch off" (cf. Chapter 14 by PENG), the final warming by, say, 2100 might even be greater than predicted.
Acknowledgements Mike Hulme provided the precipitation data used in Figs. 7 and 8 and John Christy provided the MSU2R and MSU4 data used in Figs. 12 and 13. Many of the data sets and time series discussed in the chapter have been developed with the support of the United States Department of Energy, Atmospheric and Climate Research Division, under grant No. DE-FG0286ER60397.
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189
Chapter 6
Climatic variability on decadal to century time-scales HENRY F. DIAZ AND GEORGE N. KILADIS
Introduction
Variability is an intrinsic property of the Earth's climate system. It is evident in the vast glaciated landscapes of North America and northern Europe, the product of massive continental ice sheets that have periodically waxed and waned during the Pleistocene epoch (approximately the last two million years of the Earth's history). It is inferred from fossil records which indicate that, tens of millions of years ago, warm habitat species thrived in high-latitude areas which, today, are too cold to support them (see Chapter 3 by BARRON). MITCHELL (1976) developed a synthesis of the spectrum of climatic variability as a function of frequency and characteristic spatial scale. He also listed three categories of potential sources of climatic variability: (i) internal stochastic mechanisms, (ii) external forcing mechanisms and (iii) instabilities or resonant modes of the climate system. The first category refers to processes operating within the system, defined here as the atmosphere, hydrosphere and cryosphere. Stochastic mechanisms involve chaotic feedback effects (processes which amplify or diminish an initial perturbation of the system) that arise in large part from the non-linear nature of the governing equations. The second source of climatic variability derives from processes independent of the climate system, and involve mechanisms which are external to the state of the system, such as solar radiation changes due to orbital variations, tectonic movements, etc. The third category involves some form of resonant amplification of internal modes of the system forced by recurrent (or periodic) external mechanisms. The quasi-periodic reversal of wind direction in the lower stratosphere, known as the quasi-biennial oscillation, is an example of this type of climatic variability. The E1 Nifio/Southern Oscillation phenomenon could be considered a less regular example of this type of feature. On the time-scale of climatic variability of interest here (decadal to century scale variations), the variance spectrum associated with various long-term climatic indices is essentially red, that is, the amplitude of the variations increases with increasing period of the oscillation (KUTZBACH and BRYSON, 1974). Another way of stating this is that temporal persistence in long-term climatic series inflates the variance contribution of longer-period oscillations relative to those at higher frequencies (GILMAN et al., 1963). This property is illustrated in Fig. 1, where the theoretical spectra of random time series with different levels of temporal persistence are shown. The lag-one autocorrelation of a time series, which samples some continuous process such as temperature, expresses quantitatively the degree of temporal persistence between adjacent samples or time intervals of that particular process. A zerovalued lag-one autocorrelation coefficient indicates that successive realisations of the time
191
Climatic variability on decadal to century time-scales
One-Lag Autocorrelation 9 = .90 8 = .80
6
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~
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ol 0
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Fig. 1. Red noise spectra for selected values of the lag-one autocorrelation (after GILMANet al., 1963). Ordinate is variance expressed as a ratio to white noise value (with zero autocorrelation). Abscissa is frequency expressed as decimal fraction of the data sampling interval. For example, a frequency value of 0.1 for data sampled yearly corresponds to a period of 10 years.
series process are effectively independent of each other. By contrast, high values of the lagone autocorrelation indicate that successive values are not statistically independent, but that the process, in effect, retains a "memory" of previous realisations or values. The spectrum of time series with the latter characteristic tends to exhibit higher variance at lower frequencies compared to the former class of processes (known as white noise). Within the frequency interval of interest here (~10-100 years), there are certain periods which tend to exhibit, more or less consistently, an excess of variance when compared to higher or lower frequencies (MITCHELL, 1976; STOCKER and MYSAK, 1992). A likely source of climatic variability on these time-scales may be related to changes in the ocean's thermohaline circulation (see a review by HELD (1993)), which can modify the large-scale exchanges of heat between the atmosphere and the oceans and between high and low latitudes. Other possible sources of natural variability are volcanism, solar variability, and changes in biogeochemical cycles. Changes in the solar flux are totally external to the Earth's climate system. Volcanism may also be considered to be largely independent of climate. In the past there have been large changes in the Earth's biochemistry arising from varying combinations of climatic and non-climatic forcings. Since the Industrial Revolution, humans have entered the picture as a possible cause of regional and global scale climatic variation.
192
Climate variations in the past 1,000 years In the sections that follow, we consider each of these possible sources of climatic variability on the decadal to century time-scales. In this chapter, information about regional and global climates during the last 1,000 years is reviewed, along with a broad evaluation of the types of data upon which much of our knowledge about the climate during the pre-instrumental period is based. Since the large-scale ocean-atmosphere phenomenon known as E1 Nifio/ Southern Oscillation (ENSO) represents the largest source of interannual variability in the modern climate system, it is also necessary to review some aspects of the low frequency behaviour of ENSO, in addition to providing an overview of the structure and evolution of these events. Finally, a brief appraisal is made of possible future changes in climate, including anthropogenically induced changes, and uncertainties in the projections of such changes derived mostly from so-called general circulation models. We also examine possible "surprises", that could arise from potentially rapid changes in the thermohaline circulation of the North Atlantic Ocean.
Climate variations in the past 1,000 years The Medieval Warm Period Around the turn of the first millennium A. D., analysis of historical, botanical and paleoclimatic records suggests that parts of Europe, North America and the North Atlantic experienced a relatively warmer climate than the present. LAMB (1982) writes that in these regions, where this warm episode was perhaps the most pronounced, prevailing temperatures may have, at times, "approached the level of the warmest of post-glacial times." The information available places the "Medieval Warm Period" (MWP) roughly between the 10th and 13th centuries (LAMB, 1977, 1982). During this period, cultivation limits were higher in elevation and farther north than at present, and the tree-line migrated upward in parts of central and northern Europe. The expansion of the Norse culture across Iceland into southern Greenland, and their ultimate establishment of isolated settlements in Newfoundland, occurred during this time (see ACTA ARCHAEOLOGICA, 1991). Grain cultivation in Norway was extended north of the Arctic Circle, while average summer temperatures in England and central Europe have been estimated to be 0.7-1.4~ warmer than at present based on the limits of vine cultivation (see LAMB, 1982). Observations of unusual sea-ice conditions and historical accounts of significant climatic events in Iceland since its settlement over a thousand years ago have been used to reconstruct climatic conditions in the northern North Atlantic Ocean. BERGTHORSSON (1969) used that information to reconstruct prevailing temperatures around Iceland since the 10th century A.D. The record suggests that temperatures in Iceland during the MWP were the warmest until the early decades of this century. This information is derived primarily from records of sea-ice around Iceland. KELLY et al. (1987) have shown that the modern Icelandic sea-ice record is a useful indicator of atmospheric circulation in the North Atlantic sector and of the character of the East Greenland current. The latter is an important component of the oceanic thermohaline circulation, and hence, of meridional heat exchange processes in the climate system. For an overview and summary of what is known about climatic conditions during the period of Iceland' s settlement, see OGILVIE (1991). 193
Climatic variability on decadal to century time-scales
In North America, we must rely almost exclusively on paleoenvironmental records to reconstruct the climate of the Medieval Warm Period. A significant amount of archeological evidence also exists, particularly for cultures in the Southwest United States (GUMERMAN, 1988), the Great Plains (BAERREIS and BRYSON, 1967; WENDLAND and BRYSON, 1974) and the American Arctic (LAMB, 1977). Botanical and soil analyses in northern Canada indicate warm conditions prevailing during the MWP, with the northern treeline moving poleward by several tens of kilometres compared to its present position (BRYSON et al., 1965). Wetter conditions in the US Great Plains are suggested by evidence of corn cultivation in northwestern Iowa (e.g. BAERREIS and BRYSON, 1967), while the Anasazi culture of the southwestern United States reached its zenith during this time (GUMERMAN, 1988). Towards the end of 13th century, tree-ring evidence indicates the occurrence of more frequent and/or severe droughts in the American Southwest (DEAN, 1994; PETERSEN, 1994) which may have been linked to the disappearance of the Anazasi culture. Records from other parts of the world also consist of a combination of historical and paleoenvironmental indicators, such as variations in the deposition rate of organic material and oxygen isotopic changes. BRYSON and SWAIN (1981) reconstructed the summer monsoon rainfall for the Rajasthan region of northwest India. Their results show that the period encompassing the MWP was one of enhanced monsoon rainfall. Based on analysis of modern instrumental records, they make the case that the increase in rainfall was probably related to an enhanced monsoon circulation due to warmer temperatures in general over land areas of the Northern Hemisphere. A study by SUKUMAR et al. (1993) using carbon isotope ratios from plant material found in peat bogs from the highlands of southern India also indicates the presence of enhanced summer monsoon rainfall in this general region around that time. Farther west, a record of annual flood levels of the Nile River kept near Cairo also shows that the years spanning the MWP were characterised by average to above average flows (HASSAN, 1981; FRAEDERICH and BANTZER, 1991). Most recently, QUINN (1992) tabulated the years with deficient Nile River flows using a variety of sources. The results indicate that during the MWP, there were fewer years with major streamflow deficiency than for other periods, a result that is consistent with those of the other studies cited above. In the Southern Hemisphere, temperature reconstructions from tree-ring records show the presence of several periods of above normal growing season temperatures in Tasmania (COOK et al., 1992) and in Patagonia (VILLALBA, 1994) in the centuries spanning the MWP, although decadal-scale variability is present throughout these records. The 1,000-year reconstruction of November-April temperatures for Tasmania attests to the presence of decade-long periods of relative warmth from about the 10th to the 12th centuries, with approximately 40% of decadal mean values occurring in the upper tercile of the full reconstructed record. In South America the occurrence of a warm-dry period from the latter part of the 11 th century to the mid-13th century in northern Patagonia has been reconstructed by VILLALBA (1990). Long-term summer temperature reconstructions for Scandinavia (BRIFFA et al., 1992) also support the idea that the 10th and 1 lth centuries were particularly warm. However, summer temperature reconstructions for the northern Urals (GRAYBILL and
SHIYATOV, 1992) show the warmth to be most prevalent during the 13th century, when climatic conditions from Scandinavia to Greenland had already begun to deteriorate. HUGHES and DIAZ (1994) have carefully reviewed the evidence in support of the existence of a unique climatic episode from the 10th to 13th centuries A.D., including an assessment
194
Climate variations in the past 1,000 years
of its geographical extent. They note that while paleoclimatic records from different parts of the globe are suggestive of spatially extensive periods of warmth during the Medieval Warm Period, the actual number of sites with such records is quite small. Therefore, inferences about whether the MWP was truly a global or even a hemispheric scale climatic episode must await the availability of additional information. HUGHES and DIAZ (1994) summarise the present uncertainty regarding the climatic characteristics of the MWP on hemispheric to global space scales: "...the time interval known as the Medieval Warm Period from the ninth to perhaps the mid-fifteenth century A.D. may have been associated with warmer conditions than those prevailing over most of the next five centuries (including the twentieth century), at least during some seasons of the year in some regions. It is obvious, however, that we have only, at best, a rough picture of the climate of this epoch, and that much work remains to be done to portray in greater detail the climate essence of the ninth through fourteenth centuries."
The Little Ice Age Towards the end of the 13th century, the climate seems to have become progressively colder, and in some areas stormier (see LAMB, 1977). The decline in temperature appears to have been quite widespread, and it is recorded in a wide variety of historical and paleoclimatic indices. After about A.D. 1450, the incidence of sea-ice on the coast of Iceland increased rapidly. In Europe, the frequency of severe winters and cool wet summers rose, leading to more frequent harvest failures. During the 16th century, the greater occurrence of narrow growth rings in climate-sensitive trees and the expansion of mountain glaciers in most parts of the world corroborate a shift towards a colder climate. This cooling is also reflected in the occurrence of more negative oxygen isotope values in ice core records extracted from different parts of the world. Variations in the ratio of 180 to 160 with respect to an arbitrary standard (6180) in glacier ice are used to infer changes in the prevailing atmospheric temperature in the general vicinity of the ice core sites (BRADLEY, 1985). More negative d180 ratios reflect the colder environmental conditions under which the moisture is evaporated from the sea surface, transported to, and condensed onto the ice fields. Current understanding of causal mechanisms associated with decadal to century time-scale climate changes increasingly points towards two major forcing factors, namely solar irradiance changes (see, e.g. REID, 1991), and changes in the oceanic thermohaline circulation, particularly in the North Atlantic Ocean (BROECKER et al., 1985; AAGAARD and CARMACK, 1989; BROECKER, 1991; STOCKER and MYSAK, 1992). Below, the evidence for a "global" cooling event covering the period since about A.D. 1500 is reviewed- the Little Ice Age and questions regarding its uniqueness as a climatic episode in the late Holocene are considered. The term "Little Ice Age" is used to identify a period of renewed glacier advances and generally colder temperatures spanning the last several centuries. The start of this colder epoch is generally regarded as occurring in the early 16th century (BRADLEYand JONES, 1992a), although, as we have previously noted, a climatic deterioration signalling the end of the Medieval Warm Period had set in during the late 13th century (LAMB, 1982). The end of the Little Ice Age (LIA) is also a matter of some controversy, although in general, the mid- to late-19th century is taken as its terminus. Thus, even for this relatively major climatic epi-
195
Climatic variability on decadal to century time-scales
sode, which occurred during a time of increased observation of natural phenomena and historical record-keeping in most parts of the world, and which overlaps with part of the instrumental meteorological record that begins in the late 17th century, a universally accepted time frame is not yet at hand (BRADLEY and JONES, 1992a). Evidence for the occurrence of the LIA came initially from Europe. The story has been exhaustively documented in, for example, LAMB (1977, 1982) and GROVE (1988). BRADLEY and JONES (1992b) have edited a collection of papers which document worldwide climatic variations since A.D. 1500 using historical and paleoclimatic records. One of the most important features associated with the LIA is the well-documented advance of alpine glaciers in Europe (GROVE, 1988). Evidence of glacier advance in other mountainous regions of the world is also well-documented, for example in the Andes of South America (MERCER,
1976; WRIGHT, 1984; ROTHLISBERGER and GEYH, 1986; SELTZER,1990) and in the central and northern Rocky Mountain region (PORTER and DENTON, 1967; LUCKMAN, 1986, 1992; OSBORN and LUCKMAN, 1988). Given that considerable uncertainty exists with regard to both the initiation and termination of the LIA, it seems important to consider what time periods, between the early 15th century and the end of the 19th century, were associated with the coldest episodes, and what locations exhibit the greatest synchronicity of response. It is pertinent here to quote from BRADLEY and JONES (1992b, p. 659) with regard to these issues: The last 500 years have not experienced a monotonously cold Little Ice Age; certain intervals have been colder than others ... The coldest periods in one region are often not coincident with those in other regions ... Different seasons may show different anomaly patterns over time ...". The available record suggests that the following times and places were unusually cold during the LIA. In Europe, the 19th century was generally colder in comparison with the most recent half-century. North American records point to the 19th and 17th centuries as being generally colder than modern normals. In eastern Asia, the picture is somewhat different, with the 17th century being the coldest interval, and portions of the 18th and 19th centuries also experiencing relatively lower temperatures. Southern Hemisphere records suggest that the main phase of the LIA occurred earlier than in the Northern Hemisphere, with prevailing temperatures colder than those typical of the 20th century during the 16th and 17th centuries. BRADLEY and JONES (1992b) point out that only a few short intervals during the LIA phase, lasting perhaps for two or three decades, can be regarded as being associated with "global" or even hemispheric-scale cooling. Among these widespread relatively cold periods are the decades of the 1590s to 1610s, the 1690s to 1710s, the 1800s to 1810s, and the 1880s to 1900s (BRADLEY and JONES, 1992b, p. 659). They also underscore the fact that widespread warm periods lasting for a decade or two are also evident in the record of Little Ice Age climate. A quantitative picture of large-scale temperature changes since the beginning of the LIA has long been a goal of climatologists trying to understand historical aspects of climatic variability. BRADLEY and JONES (1993) have analysed in detail summer temperature variations for the last 500 years in different regions of the globe. All the temperature indices that were used (except for the Central England record) were reconstructions of the temperature field based on a variety of proxy records such as tree rings, glacial melt records and documentary sources. They also evaluated the relationship between regional summer temperature and a composite index based on an average of all the regional series. The composite record based
196
Climate variations in the p a s t 1,000 years
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Fig. 2. Composite surface summer temperature anomaly series for the Northern Hemisphere. Time series is derived from individual normalised temperature indices (referenced to the 1869-1968 period) and averaged by decade (after B~DLV.Y and JONES, 1993). Dotted curve refers to decadal means of Northern Hemisphere normalised land temperature anomalies from JONES et al. (1986). Units are in standard deviations. on the sites for the Northern Hemisphere is reproduced in Fig. 2. Correlations between the composite mean and individual regional values over the common period from 1600 to 1959 vary from r = -0.20 for the western United States, to r > 0.60 for parts of China. The authors suggest that the time evolution of this multicentury composite "Northern Hemisphere" summer temperature record can support two alternate interpretations. One possibility is that there has been a gradual rise in temperature since about the late 1500s, interrupted by several decadal-scale episodes of cooler conditions in the 19th century. In that view, the coolness of the late 16th and 17th centuries is the more unusual feature. The other alternative view is for a more or less stable climate from around 1400 to the turn of the this century (with superimposed decadal-scale fluctuations), followed by an unusual warming episode thereafter. During the 18th century, quantitative measurements of climate variables, primarily surface temperature and precipitation, were begun first in Europe, and then in North America (see JENNE and MCKEE, 1985; Chapter 5 by JONES,for reviews). There are very few sites possessing lengthy homogeneous temperature or precipitation records. Nearly all of the longest climatic series contain a variety of non-climatic effects due to changes in instrumentation, observing practices and location changes. Complicating these factors is the general growth of cities, which leads to urban warming compared to nearby rural sites (KARL et al., 1988; JONES et al., 1990). As the focus of this chapter is on climatic variability on decadal to century time-scales, we have taken the Northern Hemisphere land surface temperature record
(JONES et al., 1986) and plotted it in sequential 10-year means (Fig. 3). We refer the reader to the previous chapter in this volume (Chapter 5 by JONES)which examines this same rec197
Climatic variability on decadal to century time-scales
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198
Possible causes o f climatic variability on decadal to century time-scales
efforts aimed at detecting human-induced changes in our climate. In general, most studies that have examined the connection between temperature and precipitation trends, and corresponding changes in the variance of these two key climate variables, have found no clear evidence to indicate that increases or decreases in either field are associated with systematic changes in variance. In the foregoing discussion we have provided an overview of what is known about climatic (primarily temperature) variations over the past several centuries based on a variety of historical and paleoclimatic sources. In the following section, we consider some of the key phenomena that can lead to decadal to century time-scale variability in the climate record.
Possible causes of climatic variability on decadal to century time-scales Solar variability
A direct connection between solar variability and climatic variation at interannual to decadal time-scales has long been sought. However, such a link has proved difficult to find. Precise measurements of solar irradiance from space are less than a couple of decades in length. However, satellite measurements of the sun's energy output over the course of a full solar cycle have shown that the solar "constant" undergoes changes on the order of 0.1% of its mean value, or about 1 W m -2 (WILLSONand HUDSON, 1988, 1991). Observations of other stars similar to the Sun indicate that the Sun's radiative output may vary in response to its 11-year magnetic activity or sunspot cycle (BALIUNAS and JASTROW, 1990; RADICK et al., 1990). Such variations in the solar "constant" may suffice to perturb global climate on decade to century time-scales (EDDY et al., 1982; FOUKAL and LEAN, 1990). The reader is referred to PITTOCK (1978, 1983) for critical reviews of postulated solar effects on weather and climate, and for an overview of the efforts made over the past couple of decades to develop quantitative measures to explain those effects. Since the 11-year sunspot cycle is so regular, along with the 22-year cycle of solar magnetic polarity reversals, there have been many attempts at finding similar "cycles" in climatic records (CURRIE, 1984; CURRIE and FAIRBRIDGE, 1985; CURRIE and O'BRIEN, 1988 among others). We consider two main areas of solar-climate relationships at the time-scales of interest here. The first deals with drought (or flood) recurrence, usually associated with either the 11-year or 22-year sunspot cycles (MITCHELLet al., 1979; BHALME and MOOLEY, 1981; DIAZ, 1983; STOCKTON and MEKO, 1983). In most cases, studies have concentrated on establishing a statistical association between surface temperature variations and solar (i.e. sunspot) variability. More recently, numerical models have been used to look at the effects of solar variability on the Earth's climate. One line of research has focused on changes in ocean temperatures and its coupling via energy exchanges with the deeper ocean and with the upper troposphere (e.g. GAGE and REID, 1981; REID, 1991). Another area of research has concentrated on the effects of solar variability on internal oscillations of the Earth's climate system such as the Quasi-Biennial Oscillation (QBO) (LABITZKE and VAN LOON, 1990), and the E1 Nifio/Southern Oscillation (ENSO) phenomenon (ENFIELD and CID, 1991). Plausible candidates for coupling mechanisms linking changes in the solar forcing to climatic changes at the surface have centred on resonant excitation of atmospheric phenom-
199
Climatic variability on decadal to century time-scales
ena through wave coupling between the troposphere and the stratosphere (GELLER and ALPERT, 1980; SCHMIDT, 1986), and feedback mechanisms between changes in sea surface (or mixed layer) temperature and atmospheric water vapour (e.g. FLOHN et al., 1992). At time-scales of ~ 100-1000 years, solar variability may be an important source of variability in the climate system. Evidence for solar variability on this time-scale comes primarily from carbon isotopic records (DAMON et al., 1978; STUIVER and QUAY, 1980; JIRIKOVIC and DAMON, 1994). Historical observations of solar activity also suggest that solar activity may have varied over the centuries (EDDY, 1977; EDDY et al., 1977). Recent work suggests that solar irradiance during the so-called Maunder Minimum in sunspot activity in the 17th century may have been lower than present values by about 0.25%, or about 2 W m -2 (LEAN et al., 1992). Estimates of the climatic effect of such a reduction in solar irradiance based on GCM experiments indicate a global cooling of about 0.5~ (LEAN and RIND, 1994; RIND and OVERPECK, 1994). Although changes in the Earth's orbital parameters on decadal to century time-scales are rather small (of the order of 0.2 W m -2, see LOUTRE et al., 1992), they nevertheless add an additional forcing mechanism contributing to climatic variability on the century time-scale. We refer the reader to Chapter 2 by BERGER, which examines the response of the climate system to orbital variations. Recent studies have found some observational support for the hypothesis that solar variability has been a major controlling factor in the observed behaviour of hemispheric and global scale surface temperature variations over the last ~ 130 years. An interesting study by FRIISCHRISTENSEN and LASSEN (1991) obtained a very high correlation (r--. 0.95) between a record of Northern Hemisphere land surface temperature changes and variations in the length of the sunspot cycle, which is known to be related to solar activity. The sunspot cycle length record, however, was highly smoothed, and, because the strength of the solar cycle perturbation is relatively weak, an amplification mechanism is needed to translate these solar signals into the observed surface temperature fluctuations. Based on a study with a onedimensional two-layer ocean model, REID (1991) concluded that solar irradiance variations could have accounted for much of the observed globally averaged sea surface temperature variations. SCHLESINGER and RAMANKUTTY (1992) performed some experiments with a simplified version of a coupled climate model to estimate the magnitude of the contribution of solar cycle radiative changes to the observed "global" temperature record. They concluded, based on best-fit estimates of a number of model parameters, and the available observations, that intercycle solar irradiance changes could have accounted for perhaps up to one-half of the observed surface temperature variations during the past few centuries. In a similar study of the relative effects of solar irradiance variations versus greenhouse gas radiative forcing of the observed "global" surface temperature record, KELLY and WIGLEY (1992) also concluded that solar irradiance variability may have contributed to the observed variability in the instrumental temperature record, although their estimate of the solar effect was somewhat lower (on the order of 20% of the observed temperature variance) than that of SCHLESINGER and RAMANKUTTY(1992). Among the first to perform a careful analysis of available data with regard to solar-climate connections were MITCHELL et al. (1979) who considered the time-scale of drought recurrence in the western United States. In that study the authors used several long-term reconstructions of the Palmer Drought Severity Index (PDSI) (see DIAZ, 1983; KARL, 1986) using
200
Possible causes o f climatic variability on decadal to century time-scales
precipitation-sensitive tree-ring records from different sites. It was shown, through the use of various statistical tests, that there was a significant tendency, "for the amplitude of the 22year drought rhythm to vary systematically in parallel with the amplitude (envelope) of the Hale sunspot cycle" (MITCHELLet al., 1979, p. 125). The variable in question was not a time series of PDSI at a given site, but rather, an index which measured the fractional area of the western United States experiencing a particular magnitude of drought. In a subsequent reevaluation of their earlier results (STOCKTON et al., 1983), the authors restated their finding with regard to the statistical significance of the 22-year drought rhythm in the western United States, but they also found evidence of an 18.6-year variance component in the data, which they indicated might be related to the lunar nodal cycle variation (see CURRIE, 1984). We have calculated the fractional drought area index using US climate division PDSI values from 1895 to 1990. These are labelled as the Palmer Drought Area Index, or PDAI. Two sets of seasonal indices are shown in Fig. 4. One is for the states comprising the Great Plains region (from North Dakota to Texas) and the second is for the region extending from the Rocky Mountains to the Pacific coast (Montana to New Mexico and west). The technique of singular spectrum analysis (SSA) (see VAUTARD and GHIL, 1989; GHIL and VAUTARD, 1991) was used to identify the characteristic temporal scales of variability in the PDAI time series, and made use of maximum entropy spectrum analysis (MESA) to estimate the period associated with oscillatory SSA principal component modes. In particular, we were interested in seeing if any of the leading (statistically significant) principal compo-
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201
Climatic variability on decadal to century time-scales
Dents exhibited periodicities near 22 years. For annual mean values of the PDAI in the time interval from 1895 to 1990 (top curve of Fig. 4), the SSA filtering indicates that approximately 43% of the variance in the Great Plains PDAI is associated with oscillations at -22 years. The Rocky Mountain West index contains longer term components which stretch the characteristic time-scale of drought area variability to something closer to 30 years (bottom curve of Fig. 4). Approximately 33% of the variance of annual mean western US PDAI is associated with oscillations having a time-scale o f - 2 7 years. We note, however, that although a definite pattern of temporal variability in drought extent, tuned to a timescale of ,-20 to 30 years, is evident in the western United States, there are clearly other factors at play which modulate the occurrence and recurrence of drought in that part of the United States. An important consideration with regard to climatic variability-solar relationships at the timescales of interest here, is whether these relationships withstand the test of time (see RAMAGE, 1983). PITTOCK (1983) points out that three of the thirteen droughts documented in the drought study of MITCHELL et al. (1979) were clearly out of phase with respect to the 22year Hale sunspot cycle. Although a number of hypothesis have been advanced to offer an explanation of such phase drift (e.g. CURRIE, 1981), replication of the effects of solar variability on regional climatic variability has yet to be reproduced with general circulation models of the Earth's climate system. One of the more interesting associations between solar phenomena and climatic variations is an apparent connection between the 11-year solar cycle and atmospheric circulation anomalies modulated by the phase of the quasi-biennial oscillation (QBO) in the stratosphere (LABITZKE and VAN LOON, 1988, 1989, 1990; VAN LOON and LABITZKE, 1988). The QBO itself is unique in that it is by far the most regular atmospheric oscillation not directly related to a periodic external forcing mechanism, such as the diurnal or annual cycle (see HOLTON, 1992). The oscillation affects primarily the low latitude winds in the lower stratosphere, and is associated with a reversal in the sign of the zonal wind at a given level every 2430 months. The signal of zonal wind of one sign propagates downward, starting at about 50 km, at a rate of about 1 km per month, until a height of about 20 km is reached. This is followed by the downward phase propagation of a signal of opposite sign, the oscillation having an amplitude of about 20 m s-1. This signal is zonally symmetric and present around the globe with an approximately Gaussian distribution of about 12 ~ latitude half-width centred on the equator. The QBO was first documented by REED (1965) and has been reconstructed back to 1953 by NAUJOKAT (1986). It is seen that, although its period varies somewhat, the oscillation is extremely regular and possesses a high degree of predictability. Thus, any observable association between the QBO and the reasonably regular solar cycle has potential to account for regular oscillations of the climate system on longer time-scales. An important feature of the association between the QBO and the solar cycle is that correlations between any of a number of atmospheric elements with the 11-year solar cycle display opposite signs depending on the QBO phase. Hence, correlations between these atmospheric variables with solar activity without regards for the phase of the QBO nearly always yield negligible values. Among the critical observations highlighting the above-noted relationship is the high correlation (r > 0.75) between 30 mb January-February temperatures throughout the Arctic and the 10.7 cm solar flux (a good measure of solar activity). To illustrate the changes, Fig. 5,
202
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203
Climatic variability on decadal to century time-scales
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Fig. 6. Association between surface air temperature (~ and 10.7 cm solar flux during west QBO phase. Map shows lines of equal correlation coefficient between local January-February mean surface temperature in the Northern Hemisphere and the 10.7 cm solar flux. Period of record varies between 16 and 19 years. Taken from VANLOONand LABITZKE(1988). east QBO phase, sub-tropical and mid-latitude SLP tend to be low in the North Pacific in January-February, and SLP in sub-polar latitudes tends to be higher than normal. The changes in atmospheric circulation associated with these different SLP patterns are reflected in January-February surface temperature variations in areas experiencing the most pronounced circulation changes. Figure 6, taken from VAN LOON and LABITZKE (1988) illustrates the association between solar flux changes and surface temperature modulated according to the phase of the QBO. BARNSTON and LIVEZEY (1989) have carefully evaluated the association between solar flux variation, the QBO and Northern Hemisphere 700 mb and extratropical surface temperature in North America. They found statistically significant correlations (measured against strict field significance tests) during the fall and winter seasons for both North American temperature and the 700 mb geopotential height field during years of west QBO phase. The principal 700 mb height anomaly patterns associated with the solar activity-tropospheric circulation relationship appear to be the Tropical/Northern Hemisphere (TNH) described in Mo and LIVEZEY (1986) and BARNSTON and LIVEZEY (1987), and the North Atlantic Oscillation (NAO) modes (VAN LOON and ROGERS, 1978; WALLACE and GUTZLER, 1981). The NAO pattern represents a seesaw in pressure between northern and central portions of the North Atlantic Ocean, whereas the TNH pattern, as well as the Pacific-North American or PNA pattern described by HOREL and WALLACE (1981), are part of a quasi-stationary wave-train configuration linked to tropical variations.
204
Possible causes of climatic variability on decadal to century time-scales
In the absence of a physical hypothesis that explains these statistical relationships, and given the fact that the observed record of stratospheric wind reversal which comprises the QBO is less than 40 years long, investigators have been cautious in accepting the apparent relationship as real. For instance, HAMILTON (1990) performed a series of experiments using a very large number of plausible sequences of the QBO phase in the stratosphere to test the stability of the statistical relationships present between solar activity and selected station time series of barometric pressure and temperature in the Northern Hemisphere. The results indicate the possibility that the associations evident in the modern observational record could have been substantially weaker in the past. Clearly, confirmation of a cause-and-effect linkage must await improved knowledge of the physical basis of these associations. In the absence of testable hypotheses, additional years of observation will continue to provide a means to verify the relationship. Volcanism and climate
The notion that explosive volcanic eruptions had an impact on the Earth's climate has been around for some time. For example, an account of the 1783 Laki eruption by SIGURDSSON (1982) contains an excerpt from the writings of Benjamin Franklin, in which he conjectures that "volcanic fogs" may be responsible for unusually cold weather in Europe during that time. The 1883 eruption of Krakatoa in present-day Indonesia was noted by many observers of the time due to its spectacular sunsets and by the relative coolness of the mid-1880s which followed (see LAMB, 1970). The volcanic explosivity index (VEI) (NEWHALL and SELF, 1982) is now used as an index of eruption strength. A VEI of 5 (considered a major eruption) is defined as an eruption with a volume of ejecta exceeding 109 m 3, and an eruption column height greater than 25 km. Early work on a connection between large volcanic eruptions and climatic cooling at the surface (for instance, LAMB, 1970; TAYLOR et al., 1980; SELF et al., 1981) generally agreed that a hemispheric-scale cooling on the order of 0.5~ was plausible in the 12-36 months following a large volcanic eruption. More recent evaluations of the surface temperature effect of large volcanic eruptions (e.g. BRADLEY, 1988; MASS and PORTMAN, 1989) have suggested that the magnitude of the response of hemispheric-scale surface temperature to volcanic eruptions with a VEI of 5 or greater is of the order of 0.2-0.4~ and that the climate response is fairly rapid, with maximum cooling occurring within 6 months to 2 years following the eruption. Early theoretical studies (e.g. POLLACKet al., 1976) emphasised that it was the magnitude of the sulphur dioxide (SO2) loading of the eruption that was important from the point of view of its radiative effects, and hence, its potential impact on climate. Recent modelling and observational work has improved our estimate of the climatic impact of volcanic aerosols (DUTTON and CHRISTY, 1992; HANSEN et al., 1992; LACIS et al., 1992). The 1991 eruption of Mount Pinatubo in the Philippines, which qualifies as at least a VEI-5 volcanic eruption, provided an unprecedented opportunity to observe global scale climatic changes associated with a large volume of stratospheric volcanic aerosol. Using the microwave sounding units (MSU 2R) aboard National Oceanic and Atmospheric Administration (NOAA) satellites (SPENCER and CHRISTY, 1990, 1992), Dutton and Christy estimated that a temperature drop in the lower troposphere of ~0.7~ for the Northern Hemisphere and 0.5~ for the globe had 205
Climatic variability on decadal to century time-scales
been observed by September 1992, approximately 15 months after the eruption. This value appears to be somewhat larger than the above cited estimates of volcanic effects on surface temperatures for the last century or so, possibly because stratospheric loading of SO2 is known accurately only for the most recent eruptions. The estimated reduction in clear-sky daily integral solar irradiance at the surface for various sites is of the order of 3-5% (~610 W m -2) within about 10 months of the eruption (DUTTON and CHRISTY, 1992).
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206
Possible causes of climatic variability on decadal to century time-scales
A global climate model simulation of the possible effect of Mount Pinatubo aerosols on global surface temperature anomalies using radiative forcing profiles consistent with the above measurements projected a global cooling of about 0.5~ (HANSEN et al., 1992). This agrees with the MSU-2R measurements (Fig. 7). The model results indicated that the maximum cumulative temperature effect would peak in late 1992, with a slow decay in the response for another couple of years. Hence, the response of global surface temperature in the model to a volcanic aerosol perturbation of the size of Mt. Pinatubo extended over approximately a 3-year period, in rough agreement with the empirical studies. It is difficult to separate the direct volcanic effect from the other factors that affect global temperature, such as ENSO, internal feedbacks, and cryospheric changes. Figure 7 illustrates the available record of monthly lower tropospheric temperature anomalies derived from the MSU-2R data. A smoothed curve has been fitted to the data to highlight lower frequency fluctuations. We have split the globe into a tropical band and the two extratropical regions for comparison. The ENSO time-scale is strongly represented in the tropical record (see section on ENSO below), whereas temperature variability in the extratropics is dominated by longer time-scale changes. The temperature falls during 1992 as a result of the Mt. Pinatubo eruption, and to a lesser extent after the 1982 E1 Chich6n eruption, are clearly evident for the Northern and Southern Hemispheres. The occurrence of several large volcanic eruptions within a short period of time may result in substantial temperature declines, lasting for a decade or two, depending on the timing of the eruptions. Such was apparently the case in the early part of this century, when several large eruptions (Pel6e/Soufri~re/Santa Mafia during 1902, Kamchatka in 1907, and Katmai in 1912) may have perturbed the climate enough to produce a relatively cool period prior to the rapid rise in Northern Hemisphere surface temperature evident in the observational record (JONES et al., 1986). It was noted earlier that internal variability of the climate system, meaning the non-linear interactions in the energy exchanges between the oceans, the cryosphere and the land surface, might be largely responsible for large-scale (~ 107-108 km 2) climatic variability at decadal to century time-scales. In the following two sections we consider some of these aspects, paying special attention to such important large-scale features of the climate system as the E1 Nifio/Southern Oscillation, followed by a consideration of cryospheric variability (snowcover and sea-ice variations) and extratropical air-sea interaction mechanisms. El Nifio and the Southern Oscillation
The E1 Nifio/Southern Oscillation (ENSO) phenomenon is perhaps, next to the stratospheric QBO discussed in the section on solar influences, the most obvious example of quasiperiodic internal climate variability on interannual time-scales. The term E1 Nifio (or "the child") was originally used by Peruvian fishermen in the 19th century (see ENFIELD, 1988) to refer to a Christmas-time warming of coastal sea surface temperature (SST), often associated with an abrupt decrease in productivity of the local fisheries (JORDAN, 1991). The Southern Oscillation (SO) portion of ENSO describes the global-scale surface pressure oscillation documented by workers around the turn of the century and first studied in detail by Sir Gilbert Walker (see RASMUSSON and CARPENTER, 1982; various chapters in GLANTZ et al., 1991; DIAZ and MARKGRAF, 1992, for historical reviews). It was not until the 1960s that 207
Climatic variability on decadal to century time-scales
Jacob Bjerknes linked the two processes and began to describe the complex interplay between the ocean and atmosphere which comprises ENSO and can lead to dramatic perturbations of the global climate system. Here we are concerned with the implications of climatic change on ENSO, as well as a consideration of the possible importance of ENSO itself for low frequency climatic variability. What is ENSO ?
The root of ENSO lies in the tropical Pacific, although its influences eventually spread far beyond that ocean basin. To begin to understand the ENSO cycle and its role in climate variability, the mean oceanic and atmospheric conditions over the eastern Indian and Pacific sectors are briefly described first (see also STRETEN and ZILLMAN (1984) in Volume 15 of this series for a more complete overview). This is followed by a discussion of the climatic anomalies worldwide that result from the development of the tropical anomalies, and finally by a consideration of possible changes in the ENSO system recorded in the past and potential future modifications due to global climate changes. Mean conditions
The South Pacific high pressure system is the primary atmospheric circulation feature of the eastern South Pacific Ocean. This semi-permanent surface high is associated with equatorward flow along the coast of South America, and strong southeasterly trade winds over the tropical eastern Pacific. These southeasterlies cross the equator and merge with the northeasterly trades of the North Pacific Subtropical High at a latitude of about 8~ giving rise to a zone of surface convergence and heavy rainfall known as the Intertropical Convergence Zone (ITCZ). Further west, the southeasterly trades weaken and recurve into northeasterlies in the tropical southwest Pacific, merging with southeasterlies from surface high pressure systems moving eastward from the region of Australia. This produces another northwestsoutheast oriented rainfall maximum called the South Pacific Convergence Zone (SPCZ; STRETEN, 1973; TRENBERTH, 1976; VINCENT, 1994). The distribution of rainfall in the tropical Pacific is closely related to the SST pattern, which in turn can be understood to be driven by the surface wind stress and associated ocean currents (see PICKARD and EMERY, 1982). One result of the Earth's rotation is to cause surface water to flow to the right of the wind in the Northern Hemisphere and to the left of the wind in the Southern Hemisphere. Thus, easterly trade winds along the equator result in a divergence of water away from the equator, which leads to the "upwelling" of relatively cooler water from depth to conserve mass. Similarly, equator-ward wind stress along the western coast of South America leads to divergence of water away from the coast and strong upwelling along the steep subsurface continental margin. Regions of upwelling comprise productive fisheries areas, as the subsurface waters are often rich in nutrients. This effect, along with the northward transport of cold water in the Peru current, gives rise to the rich fisheries and relatively cold SST for its latitude along the coast of Peru and the Galapagos Islands. A direct consequence of the coastal and equatorial upwelling is to increase the vertical stability of the atmospheric boundary layer by the cooling effect of the SST. This, along with the reduced evaporation over colder water, leads to the strong suppression of rainfall in
208
Possible causes o f climatic variability on decadal to century time-scales
these regions. As a result, the coasts of southern Peru and northern Chile are the driest deserts on Earth. Similar effects are observed along the Kalahari desert of southwest Africa in connection with the Benguela Current, and during the summer along the California coast. Anomalously dry climates are also experienced along the so-called "equatorial dry zone" in the central and eastern Pacific as a result of the strong upwelling there. As one moves westward, equatorial SST increases gradually as the trades and upwelling weaken, eventually giving way to the "warm pool" west of the dateline. This region is the largest area of high SST in the world's oceans, averaging greater than 28~
The warm pool extends westward
from the western Pacific through the seas surrounding Indonesia and into the eastern Indian Ocean, and is associated with high precipitation over these regions. The ITCZ and SPCZ are located well off the equator until they merge over the westernmost Pacific, to the east of New Guinea. This is because, over the tropical oceans, the strongest surface convergence and highest evaporation rates, and thus the heaviest rainfall, tend to occur over the regions of maximum SST (e.g. LINDZEN and NIGAM, 1987). Although SSTs above about 28~ generally support the development of the deepest convection (GRAHAM and BARNETT, 1987), the relationship is not a simple one-to-one correspondence since SST gradients can also influence moisture convergence (e.g. TRENBERTH, 1991). Away from the warm pool and oceanic convergence zones, the other wet regions of the tropics are associated with continental land masses. Strong heating of equatorial land surfaces results in moisture convergence and heavy year-round convective precipitation over the rain forests of the Congo and Amazon basins in Africa and South America. Straddling these equatorial regions are the seasonal rainy climates which experience heavy precipitation during the summer half of the year and dry conditions during the season of low Sun angle. This effect is most pronounced over the monsoon zones of southern Asia and northern Australia, where virtually rainless dry seasons are followed by heavy rains during the wet seasons. Although monsoon circulations are complex in detail, their root cause lies in the ability of land surfaces to heat and cool much more rapidly than the adjacent ocean (see WEBSTER, 1987). The resulting strong land-sea contrasts lead to surface pressure gradients and moist low-level flow into the continents during summer and out of the continents during winter. Along with the potential for flooding, coastal monsoon regions are also plagued by the occurrence of tropical storms (known as typhoons in the Pacific and hurricanes in the Atlantic), which are most prevalent during the latter part of the rainy season, when SST is at its highest. Apart from the SST distribution, there are subsurface oceanic manifestations of the geographic variations in wind stress across the Pacific. The strength of oceanic upwelling is strongly correlated to the depth of the thermocline or the region of maximum vertical temperature gradient at depth. The thermocline forms a boundary between the relatively wellmixed upper layer of the ocean and deeper water, much as the trade wind inversion caps the atmospheric boundary layer in the tropics. The equatorial Pacific thermocline slopes downward towards the west from a depth of only a few meters (it sometimes reaches the surface) in the strong upwelling region near South America to up to 200 m near New Guinea (PHILANDER, 1990). Along with a downward slope of the thermocline, easterly wind stress also causes water to be transported westward in the North and South equatorial currents. This results in a "piling up" of water along the western boundary of the Pacific, leading to a slope in the ocean surface such that, on average, sea-level is higher by 50 cm in the western
209
Climatic variability on decadal to century time-scales
compared to the eastern Pacific. Somewhat analogous to geopotential thickness in the atmosphere, there is in general an inverse relationship between sea-level and thermocline depth, with higher heat content and SST associated with a thicker mixed layer. Since zonal gradients in water temperature become small much below the thermocline, zonal oceanic heat content variations are due primarily to changes in the mixed layer depth, with the western Pacific having higher heat content than the equatorial upwelling zone to the east. Almost everywhere in the tropics there is a positive net annual mean heat flux into the ocean due to the high receipt of solar radiation (ESBENSEN and KUSHNIR, 1981). Locally, this radiative flux is offset by heat loss due to evaporation, especially over regions of high SST such as the warm pool. The net longwave flux also accounts for a smaller but not insignificant loss, with the contribution due to sensible heating and diffusion apparently negligible (WYRTKI, 1965; PICKARD and EMERY, 1982). The excess of heat gained by the tropical oceans is ultimately exported to higher latitudes to balance the heat losses there (W'EBSTER,1994). When the heat balance of the tropical Pacific Ocean is considered, it is seen that, despite the relatively low SST there, the eastern Pacific is a region of much higher heat gain than the warm pool (WYRTKI, 1975). This is a consequence of the large receipt of shortwave solar radiation at the surface under the relatively clear skies of the dry zone. Much of this energy is transported both meridionally and westward by the equatorial currents (e.g. WEARE, 1983). Thus a portion of the large energy reservoir of the much cloudier warm pool is due to westward advection by the equatorial currents. The high rate of flux of this energy to the atmosphere over the warm pool region takes place primarily through evaporation and then subsequent release of latent heat in precipitating cloud systems. Much as land-sea contrasts can create seasonal monsoonal wind fluctuations, the SST distribution in the Pacific helps to maintain its surface wind flow. Cooling of the lower atmosphere by the low SST of the eastern Pacific results in higher surface pressure than over the warm pool. The resulting pressure gradient helps to maintain the easterly trades which in turn help maintain the SST distribution. Thus the mean conditions of the tropical Pacific are self-sustaining to a certain degree. As it turns out, this "equilibrium" is in delicate balance, and slight perturbations can lead to the generation of a "coupled instability" between the ocean and atmosphere which leads to ENSO. In fact, near-mean conditions in the Pacific are seldom realised at any given time. ENSO perturbations
ENSO fluctuations are associated with marked deviations from the mean atmospheric and oceanic conditions just described. In the eastern Pacific Ocean, its most obvious manifestation is an increase in SST along the equator and coast of South America, with an associated increase in sea-level and depth of the thermocline. This results from a decrease in upwelling due locally to a weakening of the South Pacific High and associated trade wind flow, as well as the eastward propagation of equatorially trapped Kelvin modes in the ocean which suppress the thermocline (PHILANDER, 1990). The weakening of the South Pacific High is the eastern component of Walker's Southern Oscillation and is associated with an increase in surface pressure over Australasia. Figure 8 illustrates how the surface pressure varies inversely between Tahiti (Papeete) and Darwin, Australia on time-scales of several months and greater. Various indices of the SO have been
210
Possible causes o f climatic variability on decadal to century time-scales
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Nifio 3 region (RASMUSSONand CARPENTER, 1982). The correlation between the Tahiti minus Darwin SLP difference and the Nifio 3 SST is quite high (r = - 0 . 8 at zero lag). The three most recent warm events can be seen on these plots, namely 1982-1983, 1986-1987 and 1991-1992, along with the cold event of 1988-1989. Clues to the workings of ENSO can be obtained from an examination of its composite behaviour (RASMUSSON and CARPENTER, 1982), along with study of individual cases which deviate markedly from this mean view (Fu et al., 1986). One interesting aspect of ENSO is its tendency for phase locking to the annual cycle. ENSO extremes often first develop during northern spring, when the trade winds are weakest and SST is highest on average over the eastern equatorial Pacific. The fundamental instability involved concerns a relationship between SST anomalies and atmospheric convection. In the majority of events, a positive equatorial SST anomaly develops initially near the dateline. Since SST in this region is on average about 28~ any positive anomaly in this region will create conditions conducive to anomalously active atmospheric convection. The convection itself will induce an anomalous surface wind and thus moisture convergence. In simple coupled models of this instability, a key ingredient of the convergence is the development of surface westerly wind anomalies to the west of the convection (e.g. BATTISTI and HIRST, 1989; CANE and ZEBIAK, 1985; PHILANDER, 1985; ZEBIAK, 1986; HIRST, 1988). These equatorial westerlies generate oceanic Kelvin waves which propagate eastward along the equator (HARRISON and SCHOPF,
211
Climatic variability on decadal to century time-scales
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1984). These waves depress the thermocline and raise sea-level as they travel eastward, and are thus associated with an increase in SST along the equator to the east of the convection (e.g. CHAO and PHILANDER,1993). Another feature of the anomalous westerly wind stress is the advection of warm water eastward (or the reduction of cold water advection westward), associated with a weakening of the equatorial currents. Part of this behaviour may be related to a release of the potential energy associated with the slope in sea-level (WYRTKI, 1975). As SSTs rise to the east, anomalous convection is also displaced farther eastward. This positive feedback is believed to be the primary factor in the development of E1 Nifio conditions. Although the largest SST anomalies often occur at about 120~ the eastward extent of the convection itself is determined by the absolute SST and is usually just to the east of the dateline. The development of ENSO events tends to peak in late summer/early autumn of the Northern Hemisphere. Notable exceptions occurred in the warm events of 1982, 1986 and 1991, which developed late in the calendar year and peaked during northern winter-spring. The feedback leading to ENSO development is believed to be arrested by the seasonal development of the strong trade wind regime of northern autumn, as well as the depletion of heat energy in the warm pool. Much of this energy is apparently transferred to the atmosphere through anomalously high rates of evaporation, and portions of it may also be transferred to 212
Possible causes o f climatic variability on decadal to century time-scales
higher latitudes by the oceanic meridional circulation. Once the heat content of the ocean is depleted, the stage is set for the transition to the opposite phase of ENSO, the so-called "La Nifia" or cold event (e.g. PHILANDER, 1985, 1990; VAN LOON and SHEA, 1985). During cold events the climatological conditions of easterly trade winds and relatively cool SST over the eastern equatorial Pacific appear to be amplified. In this state the Pacific Ocean gains heat energy in the east and transports it poleward and westward, replenishing the heat supply of the warm pool. Cold events also involve an unstable interaction as described above for warm events, except in reverse, since cold SST in the eastern Pacific help maintain a strong westward pressure gradient and trade winds, in turn favouring the sustainment of the SST pattern itself. An interesting aspect of ENSO is the observation that warm events tend to be followed by cold events in the following year, and vice-versa (VAN LOON and SHEA, 1985; MEEHL, 1987). This so-called "biennial tendency" of ENSO (not to be confused with the stratospheric QBO, described above) suggests that one extreme of the SO sets up the conditions in the ocean/atmosphere system for the transition to the opposite extreme in the next year. The biennial signal is complicated by the fact that the system also can linger in one phase or the other for more than 1 year, and that there are longer (decadal) periods when ENSO fluctuations are relatively low amplitude (TRENBERTHand SHEA, 1987). The temporal variability of various indices of the SO contain broad spectral peaks in the range of 3-7 years, with little power at 2 years but a secondary peak at about 28 months (TRENBERTH, 1976; CHEN, 1982; RASMUSSON and CARPENTER, 1982; TRENBERTH and SHEA, 1987). Nevertheless, if one considers the variance spectrum of monthly SST, sea-level pressure and surface winds in the eastern equatorial Pacific, one finds significant power at the biennial time-scale (MEEHL, 1987; RASMUSSONet al., 1990). GRAY et al. (1992) make a case that the stratospheric QBO might play a role in the forcing of ENSO. They reason that the QBO could alter the vertical wind shear in the tropical upper troposphere, which would either enhance or suppress thunderstorm activity over Australasia. This, they argue, could lead to a modulation of the frequency and amplitude of ENSO, depending on the initial state of the ocean-atmosphere system. MEEHL (1987) pointed out that ENSO can be interpreted as a modulation of the seasonal cycle, such that the seasonal cycle is suppressed during warm events and amplified during cold events. Thus, during warm events SSTs remain warm along the equator during their normal seasonal cooling period (northern fall) and the Pacific convergence zones remain closer to the equator than they would otherwise during their respective winter seasons. In addition, the weakening of the convection in the eastern Pacific ITCZ during northern winter is much reduced. The time involved for the depletion of the heat energy stored in the ocean and its subsequent replenishment is a likely factor in setting the time-scale between ENSO events, as well as the amplitude of individual events. This relates in part to the internal wave dynamics, such as the time involved for equatorial Kelvin waves to traverse the Pacific basin, as well as radiative processes, which determine the time needed to replenish the heat content of the ocean. The occurrence of biennial behaviour in the SST and low-level wind field in the equatorial Pacific suggests that two seasonal cycles is sufficiently long to "recharge" the system from one extreme to the other. The fact that ENSO tends to be phase locked to the seasonal cycle strongly suggests that the system must be in a particular state, regardless of 213
Climatic variability on decadal to century time-scales
heat content, to develop into an alternate state. The strong seasonal dependence of the success of both dynamical and statistical models in forecasting ENSO (CANE and ZEBIAK, 1985; GRAHAM et al., 1987; CANE, 1991) is another indication that the fluctuations are tied to the base state and time-scale of ocean dynamics. Teleconnections
Much of Walker's early work was geared towards prediction of Indian rainfall, and the SO was of great interest since it was known that the strength of the monsoon was inversely proportional to the surface pressure over southern Asia. In his investigations WALKER (1923) established that high pressure over the Australasian region was accompanied by drought over India and Australia and cool, wet winters over the southeastern United States. Surprisingly, little work on atmospheric teleconnections was undertaken until nearly a half a century later, when BJERKNES (1966) uncovered evidence that El Nifio conditions were associated with a strengthening of the storm track over the North Pacific. Since then, a wealth of research has been done on the temperature and precipitation signals associated with ENSO. Much of the synopsis to follow has been taken from the work on large scale ENSO signals of RASMUSSON and CARPENTER (1982), ROPELEWSKI and HALPERT (1986, 1987), LAU and SHEU (1988), KILADIS and VAN LOON (1988) and KILADIS and DIAZ (1986, 1989). The signals to be discussed here are those which are the most highly statistically significant results of these studies. Other studies relating to specific signals are given in reference lists from these papers, and also in the discussion below for individual regions. The most pronounced signals occur during the year that an ENSO extreme first develops (here called "Year 0") into the following year (Year + 1), following the convention of RASMUSSON and CARPENTER (1982). Figures 10 and 11, taken from KILADIS and DIAZ (1989), show regions of statistically significant differences in temperature and precipitation between cold and warm events for selected seasons, and are used as a basis for the following discussions. Precipitation
Although the term "El Nifio" was first used to describe the annual warming of the waters along the Peruvian coast, in the 1960s it became synonymous with the concurrence of abnormally high SST and heavy rains in the usually hyperarid Peruvian coastal plains. BJERKNES (1969) noted that anomalously heavy rains during E1 Nifio also occurred at Pacific island stations such as Canton and Christmas in the equatorial dry zone. As mentioned above, this signal is one manifestation of the equator-ward shift of the convergence zones during equatorial warming of the SST associated with ENSO. As a result, the regions normally under the influence of these convergence zones, such as the Caroline and Marshall Islands, Fiji and New Caledonia experience drier than normal conditions (Fig. 10c). ENSO appears closely tied to the Asian and Australian monsoon circulations, which are notably weaker during warm events (see WEBSTER and YANG, 1992). Figures 10 and 12 illustrate the effect of ENSO on precipitation in the region of India and around northern Australia. While precipitation increases in the central and equatorial Pacific during warm events, it becomes markedly drier over regions bordering the western Pacific and eastern Indian 214
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216
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Fig. 12. Precipitation variations in the Indian monsoon region (10~ to 30~ 70~ to 110~ for June-August, top curve) and in the region of northern Australia (0 ~ to 25~ 120~ to 170~ for December-February). Data are averages of individual station totals in units of mm. Warm (El Nifio) and cold (La Nifia) events, as defined by KILADISand DIAZ (1989), are highlighted. PARTHAsARATHY et al., 1988). The Australasian signal is more evident during the northern autumn of year 0, and persists over the monsoon region of northern Australia into the December-February rainy season (Figs. 10 and 12). However, during strong ENSO events, the entire continent of Australia can be affected by severe drought conditions (ALLAN, 1991).
217
Climatic variability on decadal to century time-scales
Since the Indian rainfall signal is so prevalent during the early stages of warm events, this suggests that the monsoon is an important component to the triggering of ENSO (MEEHL, 1987). Several studies have shown that the surface pressure signal associated with the SO appears to propagate out of the Indian Ocean into the Pacific over a period of several months prior to the development of an event (BARNETT, 1985; GUTZLER and HARRISON, 1987; KILADIS and VAN LOON, 1988), so that the oscillation is not purely standing in character. This has led to some studies of the possibility that the actual origin of ENSO might be over Asia, and related to snowcover of the Tibetan plateau (YASUNARI, 1987; BARNETT et al., 1989, 1991a). It should be emphasised that, while warm events can result in devastating precipitation deficits over monsoon regions, these areas are generally still receiving a large amount of precipitation in all but the most extreme cases. Over certain regions of the data sparse Indian Ocean, there is some suggestion that warm events actually see above normal precipitation in phase with that over the central Pacific. Sri Lanka, the Seychelles Islands and coastal stations of equatorial Africa are certainly wetter than normal during their normal SeptemberNovember rainy season (Fig. 10b), and satellite data from the three most recent warm events (1982, 1986 and 1991) support the occurrence of enhanced rainfall over the southern Indian Ocean during northern winter of those events. If so, this means that the main focus of precipitation over Australasia is actually not so much shifted eastward, but distributed more evenly across the equatorial Pacific and Indian Oceans. As warm events evolve towards their "mature" phase during the northern winter season (DJF + 1), drier than normal conditions continue in the region of the western Pacific ITCZ from the Philippines eastward (Fig. 10b), and east of Australia in the normal position of the SPCZ (KILADIS and VAN LOON, 1988). Similarly, a large region of southeastern Africa, including parts of Zimbabwe, Mozambique and South Africa, has a marked tendency for drought during DJF + 1 of warm events. Precipitation in this region is highly seasonal, so this signal can have an especially large impact since it occurs during the normal southern summer rainy season. Consistent with the biennial tendency of ENSO, Y e a r - 1 of warm events tends to be wetter than normal, leading to a detectable biennial tendency in the southern Africa precipitation record (NICHOLSON and ENTEKHABI, 1986). Farther north in Africa, there are indications that warm events favour drought conditions from the Sahel eastward to the highlands of Ethiopia during the normal summer rainy season of JJA 0 (Fig. 10a) (see also JANOWlAK, 1988; QUINN, 1992). This signal has been used by Quinn to reconstruct a proxy ENSO record based on the Nile River runoff record, which has its headwaters in Ethiopia. However, it should be emphasised that the Sahel region experiences rainfall variability at a higher amplitude and lower frequency than that associated with long-term fluctuations in ENSO (LAMB and PEPPLER, 1991; DIAZ and PULWARTY, 1992, 1994). While coastal Ecuador and northern Peru often experience flooding during warm events, other regions of the Americas often register large rainfall anomalies. A consistent dry signal is found from JJA 0 to DJF + 1 over northern South America (see Fig. 11) (see also ROGERS, 1988). Over northeast Brazil, the periodic occurrence of severe drought in the agriculturally rich "Nordeste" region in connection with E1 Nifio events has resulted in severe economic hardship and occasional famines in this region (HASTENRATH and HEELER, 1977; CHU, 1991). Widespread and severe famine was reported during the great E1 Nifio of 1877-
218
Possible causes of climatic variability on decadal to century time-scales
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219
Climatic variability on decadal to century time-scales
above normal, and this contrasts with the relatively dry rainy season on the Pacific Ocean side of Central America. Figure 13 shows two other areas where the signals are generally reliable from event to event. These two regions in South America (Patagonia in the south, and the northern third or so of the continent) were identified in KILADIS and DIAZ (1989) as regions with a statistically significant ENSO signal in precipitation. The signals over South America are related to an enhanced westerly flow regime in the Southern Hemisphere jet streams (see ACEITUNO, 1989) apparently forced by the anomalous tropical precipitation occurring over the central and eastern Pacific during warm events. Temperature
The temperature signals associated with ENSO are quite significant on a global scale, particularly in the tropics and thus can interfere with efforts to detect climatic change (ANGELL, 1991). NEWELL and WEARE (1976) were the first to identify the zonal mean warming in the tropics associated with warm events. This signal generally peaks 3-6 months after the peak in tropical Pacific SST, and has since been shown to affect the entire tropical troposphere (HOREL and WALLACE, 1981; ANGELL, 1981) including surface temperature (BRADLEY et al., 1987; ROPELEWSKI and HALPERT, 1987; KILADIS and DIAZ, 1989; DIAZ and KILADIS, 1992). These relationships can be noted by comparing Figs. 7 and 9, with tropical air temperatures lagging SST by several months. Figures 10d and 1 ld show that the surface temperature signal is widespread throughout the tropics during DJF + 1. Lower tropospheric temperature for the global tropics has been derived from microwave instruments aboard polar-orbiting satellites since the late 1970s. An ENSO temperature signal was detected for the 1982, 1986 and 1991 warm events and the 1984 (weak) and 1988 cold events (see SPENCER and CHRISTY, 1990). Typical tropical temperature anomalies during ENSO are of the order of 0.5-1~ and these tend to exacerbate the impact of warm events in the monsoon regions affected by drought conditions. Higher temperatures along with an
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220
Possible causes of climatic variability on decadal to century time-scales
increase in solar radiation under less cloudy conditions can greatly increase evaporation, further stressing crops already suffering from moisture deficit. Likewise, cooler temperatures during cold events will favour the water budget, even if precipitation is not unusually high. Figure 14 shows the large spatial extent of the anomalous surface temperature pattern during DJF + 1. Virtually the entire tropics of both hemispheres are affected. This signal persists into MAM + 1 (not shown), with the Indian and Atlantic basins in phase with, but again lagging the central and eastern Pacific by 3-6 months (WRIGHT et al., 1988; KILADIS and DIAZ, 1989). Cold event temperature signals are equally as strong as those during warm events, but in the opposite sense (KILADIS and VAN LOON, 1988; KILADIS and DIAZ, 1989; ROPELEWSKI and HALPERT, 1989). The signal typically disappears by the following JJA + 1. The zonal mean annual surface temperature difference in the tropics between warm and cold ENSO events is about 0.6~ (see DIAZ and KILADIS, 1992, Fig. 2.5). The origin of the tropical temperature signal during ENSO is a particularly interesting problem in interannual climatic variability. The anomalously high air temperatures along the west coast of South America and the eastern equatorial Pacific are certainly a direct respo~se to the elevated SST in that region. An explanation for the remote warming of the Eastern Hemisphere and Atlantic sector is, however, more problematic. Since the signal in these regions is in phase with the SST over the same area, this would imply that the warming of the ocean is critical. It seems likely that increased solar radiation due to decreased cloudiness is the primary mechanism here, since sensible heating of the ocean by the atmosphere and a transfer of warm water into remote basins from the Pacific by the ocean circulation can be ruled out. Local changes in ocean currents forced by an altered atmospheric circulation is one possibility, although this mechanism would not be likely to affect an entire basin, such as the Indian Ocean. Another possible cause may be related to a basin-wide decrease in wind stress, which would tend to reduce mechanical mixing of cool water to the surface from depth, and result in lowered sensible and latent heat transfers. As satellite monitoring of future ENSO events improves, this topic will certainly become a fruitful area for future research. Although the best correlations between ENSO and temperature are observed in the tropics and subtropics, the Americas can experience large mid-latitude temperature anomalies during ENSO events. Strong and relatively mild westerly flow from the Pacific into North America during warm events is responsible for a large region of positive temperature departures from southern California northwards along the west coast to Alaska, then inland across western and central Canada (Figs. 11 and 14). This signal over northwest North America is one of the most reliable in the extratropics from event to event (see KILADIS and DIAZ, 1989; DIAZ and KILADIS, 1992). Cold events are equally reliable in being associated with anomalously cold winter seasons in this region. In those years, a tendency towards a weak jetstream over the central Pacific leads to atmospheric "blocking" patterns in the Gulf of Alaska, which in turn are associated with anomalous northerly flow over northwestern North America. The increased warm event storminess over the southeast US mentioned earlier is also accompanied by cooler temperatures in that region. Similar enhanced zonal flow over subtropical South America leads to above normal temperatures along the west coast; as in North America, this signal is most extensive during winter (JJA 0, not shown). 221
Climatic variability on decadal to century time-scales ENSO variability over time
It is known that the ENSO phenomenon has been operating since at least the Little Ice Age, and probably for a considerably longer period, but documentation for events prior to the instrumental record is generally inadequate, and relies on less than perfect correlations between ENSO and proxy or historical records. Nevertheless, several attempts have been made to document ENSO and, in particular warm, events, through at least the last millennium (ENFIELD, 1989; DIAZ and MARKGRAF, 1992; DIAZ and PULWARTY, 1994). One of the first attempts to catalogue past ENSO events was that of QUINN et al. (1978). This work was extended back to 1525 by HAMILTON and GARCIA (1986) and QUINN et al. (1987). These compilations were based primarily on historical records of flooding by the Spanish colonisers in Peru, and thus strictly reflect the occurrence of the E1 Nifio phenomenon. An attempt was also made to classify the strength of events based on the severity and duration of the impact of the flooding. As pointed out by ENFIELD (1992), it is important to realise that the record of E1 Nifio is not necessarily a record of the global scale ENSO phenomenon; the two are only loosely linked (e.g. DESER and WALLACE, 1987). Another problem with this approach is that it cannot detect cold events, since "drought" in coastal Peru is a normal state of affairs even without La Nifia conditions. Despite these problems, the record of Peru flooding can at least provide a minimum estimate of the number of E1 Nifio events, since there is an excellent correspondence between heavy rainfall and high SST in this region. As it turns out, the statistics of the recurrence interval of Quinn's E1 Nifio compilation, without regard to intensity, are broadly similar both prior to and following the beginning of adequate instrumental records of the phenomenon in the 1870s (ENFIELD, 1988, 1992; ENFIELD and CID, 1991; ANDERSON, 1992; DIAZ and PULWARTY, 1992), although there is a low frequency trend towards more frequent E1 Nifio episodes over the period of record covered by the Quinn compilation (DIAZ and PULWARTY, 1994). Most investigators have concluded that there has been little change in the frequency of E1 Nifio itself between the Little Ice Age and recent times (see also MICHAELSEN and THOMPSON, 1992). However, there does appear to be a century-scale oscillation in the frequency of E1 Nifio which is independent of changes in global temperature, and may be related to periods of high and low solar variability on similar time-scales (see ENFIELD and
CID, 1991; ANDERSON, 1992; ENFIELD, 1992). This is corroborated by spectral analysis of the historical data, which suggests that E1 Nifio was relatively more frequent during the periods 1680-1770 and 1820-1930 (DIAZ and PULWARTY, 1992; DIAZ and PULWARTY, 1994), consistent with proxy records of tree-ring width over the southwestern United States and northern Mexico (MICHAELSEN, 1989) and other climate indicators in regions sensitive to ENSO. In addition, when the intensity of E1 Nifio is carefully taken into account, there are distinct differences in the recurrence interval of stronger events (ENFIELD, 1992). The proxy record of ENSO can be extended back even farther by utilising time series data from such indicators as tree-ring records (e.g. LOUGH, 1992) and ice-core data (e.g. THOMPSON et al., 1984). QUINN (1992) has also utilised a record of Nile River flood levels to infer ENSO fluctuations back to A.D. 622. The success of these reconstructions depends heavily on the robustness and stationarity of ENSO teleconnection patterns as described above. There is evidence that these relationships do vary substantially over time. For example, KILADIS and DIAZ (1989) and DIAZ and PULWARTY (1992) noted that warm events were 222
Possible causes of climatic variability on decadal to century time-scales 101_1 I I i I I i I i I I I I [ I I I [ l
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associated with drier than normal conditions at some stations in Ethiopia and southern Sudan, near the headwaters of the Nile. QUINN (1992) and DIAZ and PULWARTY (1992) indeed show a reasonably good correspondence between the stronger E1 Nifio events and deficient Nile flow for the 1824-1973 period (Fig. 15). However, the most recent portion of the Nile data has been affected by persistent drought conditions in the Sahel region of Africa since, 1972, which may or may not be influenced by the decadal scale behaviour of ENSO. Despite these problems, DIAZ and PULWARTY (1992) and ANDERSON (1992) concluded that the low frequency structure of Nile River flow is likely to be a useful proxy for long-term changes in the Southern Oscillation. If we accept this, then it appears that ENSO fluctuations were most frequent around A.D. 800, became much less pronounced during the Medieval Warm Period, as indicated by the dearth of reports of low Nile River flows, and returned to near modern levels around A.D. 1300. There appears to be no simple relationship between estimated changes in the amplitude and frequency of ENSO and fluctuations in global or hemispheric mean temperature, such as the Little Ice Age (THOMPSON et al., 1992). This suggests that the ENSO phenomenon is robust to recent shifts in global temperature of the order of 0.5~
(see ENFIELD, 1992; NICHOLLS, 1992; DIAZ and PULWARTY,
1994). On even longer time-scales, assessments of the frequency of ENSO are hampered by an inability to resolve individual events (DEVRIES, 1987). At this point the determination of
223
Climatic variability on decadal to century time-scales
whether ENSO was operational at all prior to 2,000 B.P. becomes the main question. This in itself is an important problem, since we are dealing with much larger climatic shifts associated with the end of the last major glaciation. Again, proxy evidence, along with the assumption of the stationarity of teleconnections, becomes crucial. Archeological evidence from Peru, based on an investigation of prehistoric shell midden species, suggests that the coastal waters underwent a cooling down to near present values of SST at around 5,000 B.P. (ROLLINS et al., 1986). Geological evidence for the onset of E1 Nifio events at around this time includes indications of periodic coastal flooding (SANDWEISS, 1986; WELLS, 1987, 1990) and a general increase in environmental variability over South America and Australasia (MCGLONE et al., 1992). NICHOLLS (1988, 1992) points out that ENSO is responsible for a large portion of the year-to-year variability in rainfall over northern and eastern Australia. He argues that the time-scale involved for adaptations of Australian flora and fauna to this enhanced variability strongly suggests that ENSO has been operable over at least several thousand years (NICHOLLS, 1989). While evidence shows that the types of climate signals that can be associated with modern ENSO have operated for millennia, it is still impossible to say whether these signals were related to ENSO as we know it today. Since the mean climate state has undoubtedly varied substantially during the Holocene, it is quite likely that the character of ENSO teleconnections has varied as well. Further evidence of this changing relationship is considered below. Future climate change and ENSO
When speculating on the relationship between ENSO and future climate change, two possible interactions need to be considered: that a change in the frequency of ENSO could in fact alter climate, or that a change in the climate could alter ENSO. As we have seen above, warm and cold events are associated with large signals of temperature and precipitation anomalies over various regions of the globe. This suggests that a change in the frequency of warm or cold events could conceivably change the climatic means in regions strongly affected by ENSO. More specifically, a change in the frequency of warm versus cold events, or in the relative magnitudes of these events, might be enough to significantly affect climatological mean temperatures in the tropics. This effect must certainly be taken into account when assessing recent changes in global mean temperature due to anthropogenic or other sources (e.g. ANGELL, 1991). Although the frequency and intensity of ENSO have varied somewhat over the last millennium or so, the ratio of cold versus warm events may not have changed much on longer time-scales, at least in the last 500 years. If anything, the available proxy data suggest a decrease in the frequency of warm events during the Medieval Warm Period, which would favour a lowering of temperature in regions such as the northern Great Plains in the US and Canada and upwelling areas in the tropics. Thus, the second scenario, in which a change in the mean climate alters the character of ENSO and its teleconnections, seems more likely. Recent modelling work on the effect of increasing CO2 on ENSO has brought the subject of future ENSO variability out of the realm of speculation. A global coupled oceanatmospheric GCM (WASHINGTON and MEEHL, 1989) was shown by MEEHL (1990) to reproduce an ENSO-like oscillation, with warming of the SST and lowering of surface pressure in the eastern Pacific, an increase in pressure over Australasia, and a weakening of the 224
Possible causes of climatic variability on decadal to century time-scales
trades. Shortcomings of the model include a propensity for SST anomalies to evolve primarily from east to west, rather than vice versa as is frequently observed, and an unrealistic simulation of processes over the western Pacific. MEEHL (1990) concluded that the model was capturing only a subset of the coupled instabilities associated with ENSO, yet the timescale of model warm and cold events and the teleconnection patterns once an ENSO extreme was established were remarkably like those observed. MEEHL and BRANSTATOR (1992) ran the NCAR model in several different configurations associated with a doubling of CO2. As in atmosphere-only GCM simulations, global tropospheric temperature was seen to increase in the coupled simulation, which was accompanied by an increase in SST over the bulk of the tropics and extratropics when compared to the control run. In addition, the extratropical atmospheric circulation was greatly altered, which is thought to be due to a change in tropical heat sources between the two runs. Despite these large differences in the base state, the ENSO-like oscillation in the model continued unabated, with the SST oscillations continuing about a tropical mean SST elevated about 1~ compared to the control run. MEEHL and BRANSTATOR (1992) show further that the ENSO teleconnection patterns between the 1 x CO2 and 2• CO2 runs are not much different in the tropics, but are significantly different in the extratropics. For example, warm event conditions in the 1 x CO2 run are associated with above normal temperatures over Alaska and western Canada and below normal temperatures over the southeastern United States, as is generally observed (see above). In the 2 x CO2 run, this pattern is reversed. This result suggests that, while the existence of the tropical ENSO itself may not be as sensitive to changes in the climatic base state, its associated teleconnections may be highly sensitive. This underscores the need for care in interpreting ENSO proxy records from regions far removed from the phenomenon itself, as these relationships may not be stable over time. Finally, it is worth considering the most recent climate record of the tropics with regard to base state shifts and ENSO. In Fig. 9 an upward trend is seen in central and eastern tropical Pacific SST from the mid-1970s to the present. This period is also characterised by a number of warm events, including the extreme 1982-1983 event, along with a lack of strong cold events except for 1988-1989. Given that fluctuations since 1976 appear to be occurring about an elevated mean SST with respect to the prior period, one wonders how much this reflects a true climatic shift or, independently, a lack of cold ENSO phases. Perhaps it is not simply a matter of one or the other alternative, but a combination of both circumstances. As climate monitoring is now a highly integrated multinational activity, the future should provide answers to these questions. Other sources of internal climate variability
We noted at the outset that the climate record exhibits a variance spectrum characterised by increasing power towards lower frequencies. During the past decade, increased emphasis has been placed on understanding mechanisms that lead to decadal-scale climate variability, and in particular, those factors that may be associated with ocean-to-atmosphere forcing. The role of the ocean as a source of climatic variability at decadal and longer time-scales has long been recognised. Notable among early proposers of strong air-sea interactions as mechanisms for seasonal and longer term atmospheric variability are J. Bjerknes and J.
225
Climatic variability on decadal to century time-scales
Namias (BJERKNES,1961, 1964, 1969; NAMIAS, 1972, 1978a, 1978b; NAMIAS and CAYAN, 1981; DOUGLAS et al., 1982). Because of its large heat capacity and inertia, the oceans' response to atmospheric forcing displays an inherently longer time-scale, and these, in turn, influence the atmospheric circulation on the longer time-scales (KUSHNIR, 1994). Fluctuations in ocean-atmosphere heat exchange can generate large-scale SST anomalies whose decay time is much longer than the time-scale of the atmospheric perturbation which may have initially given rise to them (FRANKIGNOUL, 1985). SCHLESINGER and RAMANKUTTY (1994) have proposed such a mechanism to explain a 65-70-year oscillation in surface temperature in the North Atlantic Ocean and adjacent continental regions. For example, sea-ice changes in the polar regions resulting from, say, variations in storm-track positions, act to amplify temperature fluctuations in the atmosphere. Salinity changes associated with variations in continental runoff and in the balance between evaporation and precipitation over the oceans will modify the density stratification and lead to changes in the strength of the meridional circulation. Such variations in air-sea interactions can be expected to have a strong influence on climatic patterns at decadal and longer time-scales in high latitudes (see AAGAARD and CARMACK, 1989; MYSAK and LIN, 1990; DELWORTHet al., 1993; WEBSTER, 1994). Observational and modelling studies of ocean circulation suggest that the oceanic response to perturbations in the climate system can be both large and rather abrupt. At time-scales of a thousand to tens of thousands of years characteristic of glacial cycles, the record of stable oxygen isotopes found in benthic foraminifera in the different ocean basins indicate the presence of pronounced cooling and warming of the deep ocean water over a relatively short time span (LABEYRIE et al., 1987). Recent evidence obtained from deep ice cores on the Greenland Ice Cap (DANSGAARD et al., 1993; GRIP MEMBERS, 1993), and to a lesser extent from Antarctica (JOUZEL et al., 1993), demonstrate that rapid fluctuations in climate are possible at century or even shorter time-scales. An important current topic of research seeks to establish the rates of temperature and associated atmospheric and ocean circulation changes near the polar ice margins. BROECKER (1987, 1991) has shown that the thermohaline circulation of the North Atlantic is prone to rather abrupt reversals (on the order of a few decades) between a mode of operation where the production of North Atlantic Deep Water is strong, and one in which it virtually disappears (see HELD, 1993). There have been few coupled ocean-atmosphere GCM experiments designed to model this potentially important feature of the coupled climate system. However, those that have been performed seem to indicate the possibility that more than one stable ocean thermohaline circulation mode could exist under essentially the same external forcing conditions (BRYAN, 1986; MANABE and STOUFFER, 1988; GORDON et al., 1992). The potential effects of doubling or quadrupling the concentration of atmospheric greenhouse gases, like carbon dioxide, also include substantial (even radical) changes in the thermohaline circulation of the ocean, with potentially rapid and devastating effects in many parts of the globe, particularly in the North Atlantic sector (MANABE and STOUFFER, 1993). STOCKER and MYSAK (1992) have evaluated the spectral signatures of several climate indicators and suggest that the characteristic time-scales of variability in these records (in the range of 50--400 years) are indicative of low-frequency ocean-to-atmosphere heat flux variations, and they point to the North Atlantic as a potential major source of this variability (see also SCHLESINGER and RAMANKUTTY,1994). A number of authors have documented 226
Possible causes of climatic variability on decadal to century time-scales
recent decadal-scale changes in upper ocean characteristics, including large-scale salinity anomalies (DICKSON et al., 1988), basin-wide variations in sea-level pressure, surface winds and SST in the North Atlantic (DESER and BLACKMON, 1993; KUSHNIR, 1994), changes in biological activity like phytoplankton or chlorophyll (VENRICKet al., 1987; EBBESMEYER et al., 1991) and atmospheric circulation changes that are possibly tied to sea surface temperature changes in the tropical Pacific (TRENBERTH, 1990; CHEN et al., 1992). Long-term changes in tropical climate should be strongly coupled to variations in the ENSO phenomenon (see previous section). Although there are comparatively fewer historical and paleoclimatic records in the tropics, the subject is receiving increased attention (ENFIELD and CID, 1991; COLE et al., 1992; DIAZ and MARKGRAF, 1992; THOMPSON, 1992), given the large influence the ENSO phenomenon exerts in the global climate system. There are, perhaps, four large decadal-scale climate changes evident in the Northern Hemisphere surface temperature record of the last 100 years: a relatively cool period in the decades prior to about 1920, a rapid warming to a relative peak in the 1930s and 1940s, a cooling episode to a minimum in the early 1970s and a rapid rise in the mid-1970s to the current high values (see IPCC, 1990; Fig. 3 and Chapter 9 by WANG et al.). The Southern Hemisphere surface temperature record exhibits a more monotonic increase, so that instead of a pronounced cooling from the 1930s to the 1960s, temperatures display little change during that time (Fig. 3). As discussed previously, any number of internal and external factors, alone or in conjunction with one another, could be invoked to explain the observed climate behaviour of the last century. One might expect that decadal scale temperature variability at very large spatial scales might be reflected in changes in the cryosphere: snowcover and sea-ice extent. Conversely, an increase in the coverage of snow and/or sea-ice would be expected to increase the albedo of the surface, leading to further cooling. This so-called albedo feedback effect is believed to operate on glacial time-scales (see Chapter 2 by BERGER), but may also be important at the interannual and seasonal time-scales. CHAPMAN and WALSH (1993) have reviewed the available record of sea-ice extent and conclude that arctic sea-ice variations during the last four decades are compatible with corresponding variations in surface air temperature. In contrast, they note that there is no significant trend in sea-ice extent around Antarctica. It is difficult to say whether the sea-ice anomalies are the result of changes in the atmospheric circulation that are "externally" forced, or whether initial perturbations in sea-ice coverage have, through albedo feedback, modified the atmospheric circulation patterns in order to perpetuate or enhance the resulting sea-ice anomalies. Certainly, the changes are not monotonic, and linear trend differences exist for different seasons (CHAPMANand WALSH, 1993). Northern Hemisphere snowcover values show a decline from the late 1980s to the early 1990s (IPCC, 1992), but higher values have been recorded since the winter of 1991-1992. The increase of the last few seasons may be a response to the eruption of Mt. Pinatubo (see section on Volcanism and climate), amplified through feedback mechanisms between lower temperatures and increased snowcover. As with other climatic indicators, cryospheric variables exhibit strong interannual and decadal scale variability, which makes the task of climate change detection all the more difficult. In the tropics, feedback effects at decade and longer time-scales may be strongly related to changes in atmospheric water vapour concentration and its direct and indirect (through dy227
Climatic variability on decadal to century time-scales
namical adjustments) radiative properties (RAMANATHANet al., 1989; FLOHN et al., 1992). RAMANATHAN and COLLINS (1991) argue for a self-regulating mechanism associated with increases in highly reflective cirrus shields which might develop in response to enhanced deep convection due to higher tropical SST induced by an enhanced greenhouse effect. WALLACE (1992), however, questions whether the increase in high-level cirrus clouds would, in itself, be sufficient to prevent SST from exceeding the maximum values of around 305~ (32~ observed in some open ocean areas in the tropics. The available paleoenvironmental records do not support the occurrence of maximum SST in the tropics much above present levels during previous geological epochs when climates were significantly warmer in high latitudes (see a review by CROWLEY,1993). The role of clouds in regulating and modifying the radiative effects of increased atmospheric greenhouse gas concentrations is seen as one of the most critical issues in climate modelling today (IPCC, 1992). Atmospheric humidity changes may constitute an important factor in the evolution of future climate, because of the high infrared-absorbing capacity of water vapour. Most GCMs project both a warming and moistening of the lower troposphere under increasing greenhouse gas concentrations in the atmosphere. Recent observational studies indicate that both temperature and humidity have been increasing for the past few decades in the tropics (HENSE et al., 1988; FLOHN and KAPPALA, 1989; GAFFENet al., 1991; GUTZLER, 1992) and at high latitudes (BRADLEY et al., 1993). Although observational records of tropospheric humidity are relatively short for the purposes of evaluating decadal and longer time-scale variability, they offer a good opportunity to monitor the climate system for signs of climatic change. This is because the long-term changes in humidity, including its vertical distribution, are likely to respond in a more predictable way to greenhouse forcing compared to changes arising from natural variability (GUTZLER, 1992). The development of a persistent Northern Hemisphere circulation pattern in recent years (see TRENBERTH,1990), principally during the winter months, in the form of a greatly enhanced Aleutian low pressure trough (Figs. 16 and 17), suggests that changes in the tropics, dynamically coupled to the extratropics, may be involved in the development of relatively warm conditions in the 1980s (see Fig. 3, and the previous chapter by JONES). Certainly the
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228
Possible causes of climatic variability on decadal to century time-scales
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Fig. 17. Time series of sea-level pressure departures for rectangular area highlighted in Fig. 16 (4560~ 180-150~ Average departure for 1976-1992 is illustrated by the dotted line. ENSO phenomenon is part of the answer, since it represents a fundamental non-seasonal mode of variation in both SST and tropospheric temperature (NEWELLand WEARE, 1976; HSIUNG and NEWELL, 1983; PARKER and FOLLAND, 1991). It remains to be seen whether GCMs may be able to tell us something consistent about possible changes in the ENSO system. The few calculations that have been performed (e.g. MEEHL and BRANSTATOR, 1992) suggest that major changes are possible primarily in the extratropics, as the changed atmospheric circulation interacts differently with the anomalous convective features in the tropics during E1 Nifio (see previous section). One of the largest and most persistent regional climate anomalies during this century is the three-decades long Sahelian drought. Several hypotheses have been proposed to explain this feature, including desertification (GLANTZ, 1987) and ENSO. However, a link to Atlantic SST appear to be the most promising (FOLLAND et al., 1986; WOLTER, 1989; HASTENRATH, 1990). The study by FOLLAND et al. (1986) showed that much of the variance of Sahel rainfall during this century at interannual to decadal time-scales could be explained by SST variations in the Atlantic and elsewhere. At present, it is not clear whether these changes are part of the highly variable nature of precipitation in sub-Saharan Africa (NICHOLSON and ENTEKHABI, 1986), or whether these changes represent a semi-permanent shift towards greater aridity in this region. As noted above, the climatic record of recent decades has exhibited considerable persistence in a number of different regions, ranging from the ENSOsensitive areas of tropical eastern Pacific, the Aleutian Low region of the North Pacific and the Atlantic Ocean, where SST in the northern sectors have been typically colder than the long-term mean, whereas the South Atlantic, including portions of the equatorial North Atlantic, have tended to be warmer than normal. In the final section below, we review some of the important issues associated with anthropogenic influences on climate and examine some possible climate-change scenarios based on current climate-model projections. The reader is encouraged to read the Intergovernmen229
Climatic variability on decadal to century time-scales
tal Panel on Climate Changes Reports (IPCC, 1990, 1992) for a comprehensive review of these issues.
Climates of the future Changes from anthropogenic sources
It has become increasingly apparent that human beings have the capacity to change the Earth's climate. Evidence to that effect is found in the observation that carbon dioxide (CO2) concentration in the atmosphere has been rising inexorably since regular measurements were begun at Mauna Loa Observatory, Hawaii in the late 1950s (BOLIN and BISCHOF, 1970; KEELINGet al., 1976). Since about the mid-1970s, first with the application of simple energy-balance models (EBMs) (SELLERS, 1974; BUDYKO, 1977) and then through the use of more complex general circulation models, the study of the so-called "greenhouse effect" has grown greatly (see reviews by SCHLESINGER, 1984, 1991 and Chapter 9 by WANG et al.). The use of these sophisticated tools, relying on ever-expanding computational power, have led to a global awareness that human beings are likely to modify not just regional-scale climates, but the global environmental "commons" as well. The publication of Understanding Climatic Change (NRC, 1975) provided an early rationale for the development of coherent national and international climate research programs. In the ensuing two decades, the World Climate Research Program sponsored by the World Meteorological Organization (WMO), the International Oceanographic Commission (IOC) and the International Council of Scientific Unions (ICSU), together with a host of national climate programs (e.g. COMMITTEEON EARTH SCIENCES, 1989) have been established to address a multitude of issues related to climate change with emphasis on the understanding of both natural and human-induced variations and their impact on human society (see also IPCC, 1990). Most scientific assessments of the potential impact of growing concentrations of CO2 and other radiatively active trace gases in the atmosphere (primarily methane, nitrous oxide and chlorofluorocarbons) have been consistent in projecting a global temperature rise o f - 2 3~ in the next century, with greater warming in the polar regions relative to the tropics (NRC, 1979, 1982, 1983; IPCC, 1990, 1992 and many others). There is considerable paleoclimatic evidence which indicates that relatively large variations in CO2 accompanied the growth and decay of the latest Pleistocene glaciation (e.g. STAUFFER et al., 1984; BARNOLAet al., 1987). The most reliable information on past carbon dioxide concentrations in the atmosphere is obtained by the analysis of air bubbles trapped in Antarctic and Greenland ice sheets. Ice-core samples for about the last 160,000 years have been obtained, which show that, in general, there is a remarkable similarity between polar temperature changes, as deduced from the 6180 ratio (see earlier), and CO2 concentrations. However, the interpretation of causal mechanisms between the recorded changes in CO2 and global temperature changes remains unclear at present. Methane (CH4) also appears to have undergone large oscillations in connection with the build-up and decay of continental ice sheets. It is now widely accepted, based on a variety of paleoenvironmental climate indicators, that the principal forcing mechanisms associated with glacial/interglacial cycles in the last million years are varying amounts of solar insolation with latitude received at the 230
Climates of the future top of the atmosphere due to the Earth's orbital variations - the so-called Milankovitch mechanisms (BERGER, 1978; IMBRIE and IMBRIE, 1980; see also Chapter 2 by BERGER). Increasing the atmospheric concentration of "greenhouse gases" is not the only climatic impact of human activities. Two other important perturbations of the global environment have taken place which are relevant to the subject of anthropogenic climate change- increases in the tropospheric aerosol loading (e.g. CHARLSON et al., 1992; PENNER et al., 1992; see also Chapter 10 by ANDRAEA) and modifications of the land surface cover (HENDERSONSELLERS, 1987; HENDERSON-SELLERS et al., 1993; see also Chapter 12 by HENDERSONSELLERS). The possibility that atmospheric particulates of human origin may be capable of affecting the climate at regional and larger space scales has been a consideration for at least two decades (SCHNEIDER, 1972; BRYSON, 1974; MITCHELL, 1975; SAGAN et al., 1979; CHARLSON et al., 1992). Recent calculations of the effect of anthropogenic sulphate aerosols in the troposphere on the surface radiation balance (KIEHL and BRIEGLEB, 1993) indicate a net cooling effect, which, averaged globally, is about one-seventh the magnitude of the net greenhouse gas forcing. In some regions, such as the eastern United States and central Europe during summer, these authors estimate that the sulphate aerosol cooling effect is about equal to the radiative warming contributed by the increase in greenhouse gas concentrations. Another feature associated with sulphate aerosol screening of shortwave solar radiation is the hemispheric asymmetry introduced by the much greater industrial activity in the Northern compared to the Southern Hemisphere. KIEHL and BRIEGLEB (1993) calculate more than a factor of three difference in the anthropogenic sulphate radiative forcing for the two hemispheres. The difficulty in evaluating a greenhouse gas climate signal in the observational record stems from the fact that, whatever the greenhouse signal, it will be embedded in a background of high natural variability which will tend to mask and distort the anthropogenic signal (KARL, 1988; KARL et al., 1991a; DIAZ and BRADLEY, 1994). Control simulations by various coupled ocean-atmosphere GCMs show multidecadal internal variations on the order of--0.4~ for hemispherically averaged surface temperature and --0.3~ for global means (IPCC, 1992). Various statistical techniques are being applied to the observed climate record in attempts to separate greenhouse gas-induced climate change signals from "climatic noise" or its natural variability (see BARNETT et al., 1991b; BLOOMFIELD, 1992; RICHARDS, 1993). Some of these tests are being framed in the context of both transient (where greenhouse gas concentrations in the atmosphere are allowed to increase slowly, as observed in the real world), as well as equilibrium (where the atmospheric concentration of carbondioxide, for instance, is suddenly doubled) coupled GCM experiments, which provide a three-dimensional picture of expected climate changes. Nevertheless, the spatial patterns of observed climatic variation at decadal time-scales, including those inferred from paleoenvironmental climate indicators, such as tree-rings and ice-cores, may also resemble the characteristic patterns of variations obtained from the climate models. If so, it may take longer to separate a greenhouse climate change signal from the background of natural variability. An important consideration with regard to the impact of increasing oceanic and tropospheric temperatures in response to increasing greenhouse gas forcing deals with rising sea-levels, both in terms of the absolute changes, as well as the rate of change. Over about the past century, global mean sea-levels have risen about 10 cm, at a more or less uniform rate of - 1 - 2 mm/year (BARNETT, 1988; WARRICK and OERLEMANS, 1990; GORNITZ and SOLOW,
231
Climatic variability on decadal to century time-scales
1991). This represents primarily a eustatic (or volumetric) change, after having taken into account the effects due to land movements in response to both glacial rebound and land subsidence or emergence. The IPCC (1990) report concludes that there is "no firm evidence of accelerations in sea level rise during this century .... " Hence, the future evolution of this important variable in relation to global warming is unclear at the present. Complicating the assessments of the climatic responses to increasing atmospheric concentrations of "greenhouse gases" is the presence in the instrumental, historical and proxy record of strong decadal scale temperature and precipitation variability (see previous sections). There is considerable observational and theoretical background to suggest that climate behaviour in the 20th century may not differ appreciably from that in past centuries and that "natural fluctuations", intrinsic to the coupled atmosphere-ocean system, could have accounted for the bulk of the changes in the observational record (see LORENZ, 1991 and Chapter 5 by JONES). Statistical techniques have recently been developed which attempt to establish, in a causeand-effect manner, the recent evolution of the observed temperature field to greenhouse gas forcing as predicted by GCMs, and to develop a monitoring strategy aimed at early climate change detection (BARNETT et al., 1991b). Two of the critical variables identified on the basis of the compatibility of model versus observational signal-to-noise ratios are surface and lower tropospheric temperature and water vapour mixing ratios in the upper troposphere. The three-dimensional structural changes in the temperature field, compared with transient and equilibrium GCM climate change simulations, may offer the best hope of achieving some degree of consensus in the shorter term about the causes of global and regional scale climatic behaviour. Some recent studies which show that day and night time temperatures have changed at different rates in most of the large continental regions of the globe (KARL et al., 1991b) perhaps point towards some unexpected consequences of global climatic change. Questions regarding changes in cloudiness remain unanswered, partly because of the difficulty in assessing what spurious effects exist in cloudcover data (see, for instance, HENDERSON-SELLERSand MCGUFFIE, 1989; KARL and STEURER, 1990; PLANTICO et al., 1990), and partly because truly global coverage of cloud amount is available only for a relatively short period of time (a couple of decades). New observing platforms promise to increase our knowledge and understanding of climatic processes and variability in the oceans and how such changes affect atmospheric circulation patterns. These new observing systems include microwave sounders on board satellites (SPENCER and CHRISTY, 1990), long-term monitoring of the oceans from unmanned buoys and through such cooperative efforts as the Expendable Bathythermograph (XBT) program aboard merchant ships, and improved ocean models run in near-real-time to assimilate these data and provide a dynamically consistent four-dimensional picture of the world oceans (LEETMAA and JI, 1989). Certainly, some tantalising, but equally disconcerting, results are appearing in the literature regarding possible major changes in the oceanic circulation that may arise, a few centuries from now, in response to climatic changes forced by the ever increasing greenhouse gas loading of the atmosphere (e.g. MANABE and STOUFFER, 1993 and Chapter 14 by PENG). Such changes could be irreversible on the time-scale of many human generations, and may have incalculable impacts on society. The level of "natural" climatic variability still remains to be fully determined. This lack of a complete understanding of long-term variability complicates the assessment of the major 232
References factors responsible for a lack of convergence between the historical record of climate and the predictions of climate models (see Chapter 5 by JONES). Natural variability could be responsible for most or all of the observed climatic record on decade-to-century time-scales, and could well be the principal factor for future climates.
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Chapter 7
Satellite systems and models for future climate change R. E. DICKINSON
Introduction Relationship of satellite observations to the climate system Both modelling and observing future changes of climate require global observations of uniform coverage and quality, unrestricted by national boundaries or the technological limitations of individual countries. Orbiting satellite systems have such a capability. Satellite remote sensing detects fluxes of electromagnetic radiation that are also involved in some of the more crucial physical processes of the climate system. Satellite instruments can now provide precision measures of the energy output of the sun (WILLSON, 1993). Other instruments show the distribution by season and geography of the reflected solar radiation and terrestrial thermal emission (e.g. BARKSTROM and SMITH, 1986). Emissions at thermal and microwave wavelengths give considerable information regarding distributions of atmospheric and surface temperatures and composition. Precise measures of time of travel and amplitude of reflected signals by various satellite instruments reveal heights of the ocean surface and its wave state. Exploitation of the various technological opportunities available to take quantitative observations of the climate system from space will increase our knowledge of the climate system and consequently improve models of the climate system and its changes. Global observations are also required for the detection of climate trends. This chapter primarily addresses the application of satellite observations to improving model projections of climate change. For that purpose, data sets of limited accuracy and duration may still be useful if they are improvements over what would otherwise be available. Trend detection, on the other hand, requires considerable attention to precision and long-term continuity of the data. Inferences as to long-term future climates from present trends require uniform climate records over decades to centuries. Satellite records, on the other hand, normally provide records of a few years in length or, with large efforts, records of up to a decade (cf. Chapter 5 by JONES and Chapter 6 by DIAZ and KILADIS). Thus satellite data alone are best used to characterize interannual variations in climate. However, they need to be merged with many other kinds of data to examine trends of longer than a decade.
Some of the key satellites and their instruments Although satellite systems have been in place for several decades, they have shortcomings
245
Satellite systems and models f or future climate change that have limited their usefulness for quantitative applications to climate modelling. Weather satellites have used visible and infrared radiances operationally to obtain imagery of clouds and vertical temperature profiles. Other products have been developed recently, including microwave estimates of atmospheric humidity and rainfall, ocean surface temperatures and indices of land vegetation. Earth resource satellites have examined, in fine detail but infrequently in time, selected areas over the land surfaces (e.g. to study Amazon deforestation; SKOLE and TUCKER, 1993). Until recently, attempts to derive precise averages of surface radiation and cloud properties from satellite radiances have been confounded by errors and drifts in instrumental calibration and by the complicated geometries of satellite viewing. Besides the more obvious dependencies on season, latitude and longitude, significant dependencies on time of day, sun angle and viewing angle require measurements to sample in multiple angular dimensions and in time. Typical low-altitude Sun-synchronous orbits take satellites over the poles every two hours or so as the Earth rotates beneath them (Fig. l a). With such orbits, instruments see only a limited range of Sun angles, times of day and viewing angles. Geostationary orbits (in which the satellite rotates with the Earth, Fig. l b) provide diurnal sampling, which is especially important for clouds and precipitation. However, because of their high altitude, geostationary orbits give reduced instrumental spatial resolution and, because of their lack of global coverage, at least several satellites are needed to see most of the Earth. Tables I and II (OHRINGet al., 1989) summarize the instruments on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting and geostationary satellites. Satellite research has begun to provide major dividends for improvement of climate models with recent efforts to calibrate the satellite radiances and to model diurnal cycles and angular distributions of the satellite radiances. Important observations include inference of cloud properties, precipitation rates and surface solar radiation. The most widely used polar orbiter systems have been the US NOAA weather satellites. These have temperature sounding units that measure outward fluxes of infrared and microwave thermal emissions over narrow spectral channels from specific atmospheric layers. Vertical profiles of temperature and humidity are determined by the inversion of the emissions from thick layers centred at various altitudes. While sounding emphasizes vertical profiles, imaging refers to instruments whose emphasis is on spatial coverage, like a TV image. The NOAA satellites have provided the Advanced Very High Resolution Radiometer (AVHRR), an imaging system that looks at 1 km pixels and covers most of the Earth every day. It measures upward radiation in three channels for reflected solar radiation and in two channels for thermal emission. Originally intended to provide primarily qualitative pictures of cloud cover, this instrument has been expanded to provide much of the quantitative information on clouds, land properties, and ocean temperatures. The Land Remote-Sensing Satellite (LANDSAT) series of satellites (originally developed by the National Aeronautics and Space Administration (NASA)) also does imagery, but with higher spatial resolution (30-80 m) and with further spectral channels. These capabilities have made possible detailed classifications of land covers for mineral surveys and descriptions of vegetation cover and land use. However, individual scenes are repeated only every few weeks. After the loss of land imagery because of clouds, this infrequent repeat cycle means that a given land scene may be sampled as little as a few times a year. Regular cover-
246
Introduction
a
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Fig. 1. (a) The geostationary satellite moves through space at the same rate that the Earth rotates, so it remains above a fixed spot on the equator and monitors one area constantly. (b) Polar orbiting satellites scan from north to south and on each successive orbit the satellite scans an area further to the west. From AHRENS, 1991.
age of a particular scene would be available only by special arrangement. LANDSAT is currently operated commercially in the US through the Earth Observation Satellite Company (EOSAT). The United States Geological Survey (USGS) at its Earth Resources Observation System (EROS) data centre provides archiving and dissemination capabilities for historical LANDSAT data. Recently Japan and Europe have been developing large satellite programmes to complement and supplement US capabilities. Of the new systems already employed, the commercial French Syst~me pour l'Observation de la Terre (SPOT) satellite provides similar, but somewhat higher resolution, capabilities to those of LANDSAT. European and Japanese (and soon Canadian) Synthetic Aperture Radars (SARs) provide detailed imagery of sea ice and, potentially, some land properties. In addition to the operational satellites, the US flies Department of Defense (DOD) military satellites and NASA research satellites. The DOD satellites overlap considerably in the
247
t~ 4~ c~ TABLE I NOAA ADVANCEDTIROS-N (ATN) WEATHERSATELLITESa Objectives of mission: meteorological observations, measurements of sea-surface temperature, sea-ice and snow cover, assessment of the condition of vegetation. Orbit characteristics" polar, 833-870 km altitude, 0700 h and 1400 h equator crossing times. Sensor
Applications
AVHRR/2 (Advanced Very High Resolution Radiometer)
Cloud temperature, seasurface temperature, land temperature, vegetation index
HIRS/2 (High-Resolution Infrared Sounder)
Temperature and moisture profiles
SSU (Stratospheric Sounding Unit)
Atmospheric sounding, temperature profiles
3
MSU (Microwave Sounding Unit)
Atmospheric sounding
4
SBUV b (Solar Backscatter viewing UV Experiment)
Solar spectrum, ozone profiles, earth radiance spectrum
12
aFrom OHRING et al..(1989). bSBUV is on p.m. satellite only.
Number of channels/ frequencies 5
Spectral range/ frequency range
0.58-12.5/~m
Resolution (km)
Swath width (km)
1.1 2700
20
3.80-15.0/~m
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TABLE II GEOSTATIONARYOPERATIONALENVIRONMENTALSATELLITE(GOES) a Objectives of mission: operational weather data, cloud cover, temperature profiles, real-time storm monitoring, severe storm warning, sea-surface temperature. Orbit characteristics" ~eostationary at east and west lon~;itudes. Sensor
Applications
VAS (Visible and Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder)
Imaging-day/night cloud cover
aFrom OHRINGet al. (1989).
Sounding-temperature and water content
Number of channels/ frequencies
Spectral range/ frequency range
Resolution (km)
5
0.55-0.75/~m 11.2/~m
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12
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14
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Limb to limb
Limb to limb
Satellite systems and models f or future climate change capabilities provided by civilian satellites, but they emphasize specific details over selected areas. Some DOD instruments have been operated in global survey modes. In particular, data from the Special Sensor Microwave Sounder and Imager (SSM/I) have been made available to the research community and are widely used for quantitative measurement of atmospheric water vapour, liquid water, and precipitation, and also of snow and ice cover. Finally, NASA, Europe and Japan have emphasized development of new experimental and operational satellite systems. The current operational systems have evolved from such past instruments. NASA has recently completed the Earth Radiation Budget Experiment (ERBE), which gives quantitative details on the spectrally integrated fluxes of reflected solar and upward thermal emission. Furthermore, NASA is now providing international leadership in the application of satellites to climate studies as a part of its "Mission to Planet Earth". The first systems in this effort are: (1) the Upper Atmosphere Research Satellite (UARS) launched in 1991 for detailed analyses of stratospheric dynamics and chemistry to further elucidate mechanisms and properties of stratospheric ozone; and (2) the Ocean Topography Experiment TOPEX-Poseidon joint NASA and French oceanographic satellite launched in 1992 for global measurements of the height of the ocean surface. New capabilities now advancing in the US are the Tropical Rainfall Measuring Mission (TRMM), being done jointly with Japan and to be launched in 1997, and a large suite of new instruments of the Earth Observing System (EOS). The first EOS platform will fly in 1998 (see Table III). Past satellite data have been of limited usefulness for scientific studies because of inadequate resources to ensure their quality or to make them reasonably accessible. Presently, Federal agencies in the United States are putting considerable effort into the development of archiving, dissemination and distribution systems for providing satellite data in convenient forms. The largest effort is NASA's EOS Data and Information System (EOSDIS), which is distributed to many centres. These data systems, and the new data from future new instrument flights, will allow modellers to make fundamental improvements in climate models. Parallel developments are occurring in other technologically advanced nations. Japan is developing the Advanced Earth Observing System (ADEOS). Its first platform is to be launched in early 1996 with a follow-up in 1999. Europe has the Polar-Orbit Earth Observation Mission (POEM) programme comprised of two series of satellites, the Environmental Satellites (ENVISAT) and the Meteorological Operational (METOP) Satellites.
Current climate models: limitations, outstanding questions and satellite paths to improvement Climate models span a wide range of complexity and realism. The most comprehensive are built upon atmospheric General Circulation Models (GCMs). These models are the primary tools for projecting future climate change. They include all the processes of weather and climate incorporated into simple models and can simulate them on time-scales of up to a century or more. Their only limitations are computational costs and a lack of understanding of some processes. To provide a basic computational framework, the atmosphere, oceans and land surface are divided into vertical layers. Horizontal variations of the climate system are represented on a 250
to
TABLE III EOS MISSIONSPLANNEDTO THE YEAR 2005 Launch
Spacecraft
Lifetime
Instrument complement
1998 2003 1998 2000 2003 2000 2005 2002 2002
AM1 AM2 COLOR AER01 AER02 PM1 PM2 ALT1 CHEM1
5 5 3 3 3 5 5 5 5
MODIS MISR MODIS MISR SeaWiFS-Type SAGE III SAGE III MODIS AMSU MODIS AMSU GLAS TMR HIRDLS SOLSTICE II
CERES (2) CERES
MOPITF EOSP
ASTER TES
MOPITF
MIMR MIMR SSALT ACRIM
AIRS AIRS DORIS MLS
MHS MHS
CERES (2) CERES
SAGE III
TBD(J)
Satellite systems and models f or future climate change sphere by either a spatial mesh or some other basis. The GCMs are integrated in time with steps of under an hour, so that they generate details not only of weather systems but of the diurnal cycle. The atmosphere and the oceans are described by continuum equations of fluid dynamics; these include equations for trace species, especially water vapour, motions and thermodynamic balances, with the potential for including other important constituents. The geometry of the Earth's surface is prescribed, including location of land masses and ice sheets. The elevations of mountains are adjusted and smoothed to match the model resolution. The incident solar radiation and the rate of rotation of the Earth are also specified. Except for water vapour, atmospheric composition has generally also been fixed. Current research is addressing how to incorporate interactively such important species as carbon dioxide, ozone and methane. The solutions to these models are highly dependent on how the details of hydrological and energy cycles are included. Only the processes that occur on the spatial scales of the models (currently 200 km or larger for models used for multi-year integrations) are treated well. The realism and adequacy of the models is weakest in the area of "parameterization", that is, in the treatment of the effects of processes whose underlying physics occur on spatial scales smaller than can be included explicitly by the model. Parameterizations are limited by both a lack of derivation from sound physical principles and by inaccuracies in their implementation resulting from an inadequate observational basis. Much of the parameterization in GCMs involves important aspects of hydrological and energy cycles and their interactions. Particularly crucial are the modulations of solar and thermal infrared fluxes at the surface and top of the atmosphere. These are caused by clouds, the spatial and temporal distributions of water vapour, and the details of precipitation reaching the surface. Clouds and precipitation in the models are related to the distribution of water vapour; this, in turn, depends on convective processes occurring on horizontal spatial scales of 1-100 km. The determination of oceanic and land processes as part of a climate model is sensitive to the correctness of the atmospheric inputs of energy and precipitation. The oceanic thermohaline circulation is driven by inputs of fresh water (precipitation and runoff) and by energy exchanges with the atmosphere. The distributions over land of runoff and evapotranspiration likewise are largely determined by precipitation and energy inputs. Satellite observations directly measure radiative energy fluxes at the top of the atmosphere and can estimate surface solar radiative fluxes from the measured energy that is reflected by clouds. Depending on adequate calibration and on details of the spectral information, satellite observation can provide estimates of the opacity of the clouds to radiation and possibly the individual contributions to these estimates of the cloud liquid water and drop sizes. Through extending such observations over a wide range of weather conditions, latitudes and seasons, satellites give both detailed validations of model performances and insights into underlying physical processes.
Global radiation balance and the role of clouds Solar constant
The solar radiation crossing a surface normal to it above the atmosphere varies over an an-
252
Global radiation balance and the role of clouds nual cycle because of variations of the Earth-Sun distance. The solar flux after correction for that variation is referred to as the "solar constant". Measurement of variations of this "constant" has long been attempted. Prior to satellites, such measurements were made at the tops of high mountains and were unsuccessful because of an inability to adequately correct for atmospheric attenuation processes and for inaccuracies in instrumentation. The use of satellite platforms has overcome the former difficulty and active cavity radiometer instruments were sufficiently advanced by the early 1980s to overcome the latter (cf. the review by WILLSON, 1993). Average fluxes have since been shown to vary over the solar cycle from minimum fluxes of about 1367 W m -2 to maximum values of about 1369 W m -2 (WILLSON and HUDSON, 1991). These values are divided by 4 (ratio of the area of a sphere to a circle) to get approximately 342 W m -2 as the solar flux incident on the Earth, averaged over latitude, season and time of day. The measured 11-year solar cycle variation of incident solar flux of about one-half of a W m -2 is too small and too rapid to have a measurable climatic effect, but longer period variations with magnitudes of as much as 1 W m -2 (LEAN et al., 1992) could explain some past climate variations such as the "Little Ice-Age" of the 17th and 18th centuries. The effective rate of energy addition implied by increasing greenhouse gases from pre-industrial time up to the present is about 2 W m -2. Hence, careful monitoring of the solar constant is necessary to maintain a record of total system forcing.
Relating global temperature to global radiative balance Global average temperature is used as a measure of global climate change because interpretations of its variations can be given in relatively simple terms. That is, its change is found to be proportional to the net radiative input to the troposphere-surface system. Global temperature in ~ changes by between 0.3~ and l~
or so for each W m -2 change of radiative
input. The actual change is uncertain because of uncertainties in climate radiative feedbacks, especially those from clouds. A global average of 1 W m -2 is at the limit of observational detectability for long-term climate change. For comparison, global cloud cover reflects incident solar radiation and reduces thermal emission of the planet, both by a few tens of W m -2. Global aerosol cover reflects up to several W m -2 of solar radiation. The greenhouse effect of atmospheric water vapour is even larger. It reduces net thermal emission by an order of 100 W m -2. Relatively small changes in atmospheric or surface radiative properties can have effects of large magnitude compared to the effects of direct forcing from solar variations or even those from the addition of greenhouse gases. These changes in atmospheric or surface properties, if occurring as a consequence of global temperature change, are part of the system feedbacks. Even more important, they will determine the regional climate change from the global forcing. Errors in absorbed solar radiation are largely manifested at the surface. Over oceans they lead to erroneous inputs to the ocean component of climate models, and over land they lead directly to errors in local surface temperature and evapotranspiration. Therefore, the processes within climate models that lead to such changes must be carefully constructed and validated. Global average analyses are sufficient to demonstrate which atmospheric radiative processes are likely to be more important. Detailed descriptions of the seasonal and geographical aspects of climate processes, however, are required for determina-
253
Satellite systems and models for future climate change tion of both the global averages and the distributions needed to determine regional realism of models. Earth Radiation Budget Satellite measurements Earth Radiation Budget (ERB) missions (as reviewed by HARRISON et al., 1993) make measurements of the integrated energy reflection and emission by the Earth system (no resolution into individual wavelengths except for a separation between solar and terrestrial radiation). These measurements are made with absolute calibration. The most ambitious such effort has been the ERBE experiment, carried out by three satellites launched in the mid-1980s (BARKSTROM and SMITH, 1986). The data from ERBE, beginning in early 1985, currently comprise the most comprehensive and best resolved source of ERB data. The ERBE system consisted of a mid-inclination (57 ~ inclination of orbit) Earth Radiation Budget Satellite (ERBS) and two Sun-synchronous polar-orbiting NOAA spacecraft (NOAA-9 and NOAA-10), so that sampling was both global and over the diurnal cycle for a given month. The instrumental package consisted of both a scanning and a larger field-ofview non-scanning radiometer. The more widely analysed scanning instrument data give 40 km fields of view (FOV). The scanners on NOAA-9 and NOAA-10 failed in January 1987 and May 1989 and that of ERBS in 1990. Thus, there is an approximately 5-year data series; these data are of varying quality because of the changes in the number of instruments simultaneously operating. A method was developed to distinguish clear-sky scenes of scanner data from those involving clouds. Ancillary data from geostationary satellites were used to improve the averaging over the diurnal cycle. The Earth radiation balance depends on fluxes in all directions. However, satellites see radiative fluxes over only one direction at a given time. Data from the previous ERB scanner on Nimbus-7 provided models of the angular distributions of the radiation to help evaluate these integrals. Remaining inaccuracies of these angular models are a major source of error in the ERBE results. The future Clouds and Earth's Radiant Energy System (CERES) instrument will develop its own improved angular models. ERBE data have now become a standard against which GCMs are checked to see how well they determine top of the atmosphere (TOA) radiative fluxes (HARTMANN et al., 1986; KIEHL and RAMANATHAN, 1990; RANDALL and TJEMKES, 1991; BONY and LE TREUT, 1992), and the implications of these fluxes for cloud properties (e.g. SLINGO and SLINGO, 1991). Doing so helps both the validation and the adjustment of properties of model clouds and surface albedos. The partitioning of the ERBE data into clear-sky and cloudy-sky as well as the incremental effect of clouds on fluxes has been especially useful for that purpose. Figure 2 compares zonal mean albedos from ERBE for April 1985 with a climate model simulation. The variable components of the models for clear-sky are surface temperatures, albedo and atmospheric water vapour and, with a lesser contribution to variation in fluxes, surface emissivity in the thermal infrared and atmospheric ozone. The cloud contribution to the ERBE TOA fluxes depends on cloud amounts. It also depends, for visible wavelengths, on cloud albedos and, for the thermal infrared, on cloud-top temperatures. A precise measure of the cloud contribution requires good "clear-sky" estimates of TOA fluxes, both in the observations and in the models. CESS et al. (1992) discuss approaches to estimating this quantity in models.
254
Global radiation balance and the role of clouds
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Fig. 2. KIEHLand RAMANATHAN(1990) compare zonal mean albedos at the top of the atmosphere for ERBE with those calculated by the NCAR Community Climate Model (CCM): (a) over ocean and land; (b) over ocean only; (c) and (d) same as (a) and (b) but for clear (cloud-free) sky. Satellite cloud climatology The International Satellite Cloud Climatology Project (ISCCP) has been developed as an alternative and independent approach for obtaining in more detail global cloud properties from operational satellites. ISCCP (Rossow and SCHIFFER, 1991; ROSSOW, 1993) has used radiances for a visible (near 0.6/tm) and thermal infrared (near 11/tm) channel of the global network of geostationary satellites (the US Geostationary Operational Environmental Satellite (GOES), European Meteorology Satellite (METEOSAT), and Japanese Geostationary Meteorological Satellite (GMS) series) to monitor diurnally varying global cloud cover for more than a decade. The radiances vary in time at a point mostly because of the presence and properties of clouds. The primary instruments on the geostationary satellites sense radiances whose values drift as the instruments degrade with time. Relative calibration is maintained for comparable channels on the AVHRR instrument of the NOAA polar orbiters. Hence, ISCCP uses scenes viewed by both the geostationary and polar orbiters to calibrate the geostationary satellite data over the lifetime of the polar orbiter (several years). Calibration over more than one polar orbiter has been obtained through cross-calibration of newer polar orbiters with the preceding ones over a period of a few months when data from both are available. Even with this calibration, a spurious upward trend of cloud optical depth of 2 about a mean of 4.6 has been reported by KLEIN and HARTMANN (1993) to have occurred over a 7 year period. The normalized and calibrated radiances of ISCCP are archived on a 30 km grid and with 3 h time resolution. Individual points whose radiances differ sufficiently from those expected for clear-sky are labelled cloudy. Cloud properties are derived from these points using a radiative transfer model which is inverted for the parameters that give agreement with
255
Satellite systems and models f or future climate change
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Fig. 3. Distributions of total cloud optical thickness averaged over 1984 and longitude (TSELIOUDISet al., 1992). the radiances. The clouds are divided into high, middle and low, according to thermal radiances, with the divisions between these categories being placed at 440 and 680 mb, respectively. During the daytime, the visible radiances are used to infer, in addition, cloud optical depths. These optical depths are proportional to the product of the cloud liquid water and the average droplet size and are used to further subdivide the cloud classification into 9 subclasses. Figure 3 shows the ISCCP-derived annual zonal-mean distribution of optical thickness and top temperature for all clouds in 1984. The detailed ISCCP global cloud data are useful to validate statistics of climate-model cloud properties.
Cloud
feedbacks
Just as clouds are a primary cause of variations in the radiances detected by satellites both at the TOA and the surface, they are also potentially major perturbers of global radiation balance. The ERBE observations have established that overall (global and annual average) clouds increase the reflection of solar radiation by about 49 W m -2 and reduce the thermal emission to space by about 31 W m -2 (HARRISON et al., 1990; STEPHENS and GREENWALD, 1991). That is, the cooling by solar reflection is substantially larger than the warming by greenhouse trapping of terrestrial radiation, so that clouds have a net cooling effect on climate. Thus, an increase of cloudiness everywhere by the same fractional amount would promote global cooling. However, there is no reason to expect that clouds would ever change in such a uniform fashion, either in space and time or in their radiative properties. The processes that lead to their formation operate much more on the mesoscale (1-100s of km) than on global scales. The effect of changing the amounts of cloud cover on solar radiation will vary with solar fluxes, depending on time, latitude and season (e.g. no effect during the night and maximum effect near summer noon) and on the difference between cloud albedo and that of the underlying surface (e.g. cloud over snow has relatively little effect). The net effect of clouds on thermal emission depends on the difference between effective radiating temperatures of the
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A number of cloud-related questions are now being studied as crucial for improved understanding of observed and modelled climate change. These include: How do aerosols affect the distribution of cloud droplet sizes and their removal rates and how might these have
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258
Global radiation balance and the role of clouds cloud optical properties? How will amounts of cloud liquid water be affected by changes in global temperature? These questions are being addressed by process studies including use of future (e.g. as reviewed by KING et al., 1991) satellite measurements. Figure 6 shows how reflected solar radiation at two different wavelengths is used to infer an average cloud drop radius. One of the standard "scenarios" that has been used for testing the capabilities of climate models to project future climate change is the steady-state response of the model to a doubling of the concentration of atmospheric carbon dioxide. The first such simulations assumed that the model clouds remained fixed and derived overall temperature increases in the range of 2-3 K. As soon as "interactive clouds" were introduced into the models, the projected warming increased to 4-5 K (NATIONAL RESEARCH COUNCIL, 1979), a result of both reductions in cloudiness and increases in model cloud-top heights for the warmer climates. These initial simulations assumed fixed optical properties for their clouds.
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259
Satellite systems and models f or future climate change Later model studies have examined possible mechanisms for changing cloud optical properties with global warming and have suggested that these mechanisms might reduce the global warming to as little as 1 K (SOMERVILLE and REMER, 1984; MITCHELL et al., 1989). Hence, our estimates of global warming may be uncertain by up to a factor of 5 because of the potential for poorly understood cloud feedbacks. A recent international intercomparison of a large number of GCMs has indicated this range of model sensitivities (CESS et al., 1990). Current work towards validating the climate models against satellite data is beginning to reduce these uncertainties. The possibility that changing cloud optical properties could substantially reduce global warming has depended on theoretical arguments and on some limited aircraft evidence that cloud liquid water, and hence cloud albedos, would increase with increasing temperatures. The essence of the arguments is that warmer air is capable of holding more water vapour and plausibly might lead to greater amounts of condensed water. However, an analysis of 10 years of ISCCP data summarized in Fig. 7 (TSELIOUDIS et al., 1992) indicates that this increase of condensed water with a temperature increase may happen only at cold temperatures. At warmer temperatures, other mechanisms, such as faster removal rates or a larger sub-grid fraction of clear-sky elements of convective systems, evidently can decrease the effective cloud liquid water as temperatures further increase. This question will undoubtedly be pursued further, but it is evident that little can yet be concluded as to what will be the sign and magnitude of the net effect of cloud feedbacks on global warming. Additional cloud albedo questions are: How do cloud drop sizes depend on the distribution of cloud condensation nuclei and how does the drop size distribution affect albedo (CHARLSON et al., 1992)? Small drops are brighter for a given total amount of cloud liquid water. Larger drops also fall out substantially faster (ALBRECHT, 1989).
Precipitation Precipitation (rain and snow) defines atmospheric release of latent heat and, averaged in time and over the globe, should be balanced by surface evaporation. These terms are, respectively, dominant mechanisms for addition of energy to the atmosphere and for nonradiative surface cooling. Atmospheric structure and dynamics would be totally different without latent heat release. Numerical simulations have also shown that, in the absence of evaporative cooling, continental land surfaces in summer would be at least 10 K warmer than they are (SHUKLA and MINTZ, 1982). Detailed distributions of precipitation in time and space over continents are important for the determination of what fraction of this water is distributed into runoff rather than immediately evaporated or stored in the soil for future evapotranspiration. The frequency and distribution of intensities of rainfall at a point are as important as are the monthly rates. Current climate models provide reasonable overall average spatial patterns on the scale of continents. However, even monthly average rates and regional details still differ substantially from observed values (e.g. as reported on a 1~ global mesh by LEGATES and WILLMOTT, 1990). The model distributions of intensities and frequencies of precipitation differ widely
260
Precipitation from observed values. There has been neither adequate observational characterization of these distributions nor satisfactory model parameterization. Over oceans, where rain gauge information is much sparser, the validity of even monthly means of model precipitation is difficult to judge with present data. Improved measurements are, thus, a high priority. Rainfall in the tropics has been estimated primarily from cloud-top temperatures as measured by infrared imagery (reviewed by ARKIN and JANOWIAK, 1993). The "threshold method" (RICHARDS and ARKIN, 1981) estimates rainfall over large areas (at least 1.5 ~ x 1.5 ~ as simply 3 mm h -1 x fraction of area covered by cloud with temperatures less than 235 K. This approach was calibrated to the GARP (Global Atmospheric Research Programme) Atlantic Tropical Experiment (GATE) observations of precipitation in 1979 and is less certain elsewhere, especially over land and outside the tropics. Microwave emissions are alternatively used (WILHEIT et al., 1991; PRABHAKARA et al., 1992) and the two approaches are being combined (ADLER et al., 1991). Figure 8 shows for July 1990, as derived from the threshold method and GOES, the mean and diurnal components of precipitation over northwestern Mexico. The diurnal component is as large as the mean because most of the precipitation occurs in the afternoon, as is typical of tropical convection. Infrared and microwave estimates of oceanic precipitation are being archived over a multi-year period through the Global Precipitation Climatology Project (GPCP) (ARKIN and ARDANUY, 1989). These data are especially useful for determining spatial and temporal patterns, e.g. the interannual variations resulting from occurrences of E1 Nifio events. They are not reliable for small space scales and short time-scales and there is no way to validate the monthly average climatologies for many parts of the world where the extent of "ground truth" data is minimal. This situation will be remedied in the future through spacecraft flights of rain radars, the first of which is the TRMM, to fly in 1997 (SIMPSONet al., 1988). Over the relatively nar-
0.5
MEAN R A I N R A T E (mmlh)
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Fig. 8. Hourly rainfall rates inferred from the temperatures of cloud tops by the GOES satellite and summarized in terms of mean and first harmonic (diurnal) rates in month. (NEGRIet al., 1993).
261
Satellite systems and models f or future climate change
row swaths seen by the radar, rainfall estimation will be considerably improved from past approaches and the infrared and microwave estimates available from other instruments on TRMM or from other satellites also will be improved through calibration with this orbiting radar. Measurements of precipitation are required for validation of climate model precipitation. How good are the absolute amounts, the spatial patterns, and the interannual variations? Interannual variability of precipitation, especially in the tropics, is closely linked to variations in sea surface temperatures (SSTs). Hence, climate models using measured time series of SSTs should produce the measured time series of precipitation, at least over large enough time- and space-scales. The E1 Nifio Southern Oscillation (ENSO) phenomenon (e.g. LAU and BUSALACCHI, 1993) provides much of this variability. Observations from satellite and other means are also needed to better establish an understanding of the mechanisms producing the precipitation. Current questions include the following: How do surface boundary conditions (land and ocean) affect the presence and intensity of precipitation? What are the effects of cloud radiative processes and cloud microphysical processes on precipitation? Hypotheses relating tropical SSTs to extratropical climate anomalies include a suggested explanation for the US drought of 1988 (TRENBERTH et al., 1988).
Atmospheric dynamic and thermodynamic fields Atmospheric temperatures, winds and water vapour concentrations have traditionally been provided through radiosondes (vertically ascending instrumented balloons). These observations are required on a daily basis for initialization of weather prediction models. Assimilation procedures are used that add information from earlier observations to the current data. Archives of the results are maintained as climate data. Over the past two decades, satellite instruments have been developed to provide additional temperature and water vapour soundings to those obtained with balloons (as reviewed by SUSSKIND, 1993). These measurements depend on thermal (infrared and microwave) emissions coming from different atmospheric layers at different wavelengths. Infrared provides the best vertical resolution, but microwave is less affected by clouds. Use of non-vertical paths to the satellite, especially viewing of the limb, improves the vertical resolution; limbscanning is most successful in the upper troposphere and above, where cloud obscuration is minimal. Where available, radiosonde temperatures from balloons are still substantially more accurate than are present satellite soundings, but the satellite temperature soundings provide data over the oceans, where no other temperature measurements are made. The data for temperatures have been obtained primarily from the NOAA sounders. SPENCER and CHRISTY (1992) have introduced climatological analyses directly using radiances from the microwave unit on the NOAA satellite. Considerable improvements in accuracy and vertical resolution of temperature are expected with the Atmospheric Infrared Sounder (AIRS) instrument being developed for EOS and for water vapour from this and microwave instruments. Geostationary satellites now add to balloon measurement of wind a limited amount of additional information by tracking of cloud movements (e.g. RUTLEDGE et al., 1991).
262
Atmospheric dynamic and thermodynamicfields Additional measurement of water vapour has been made possible from microwave data (e.g. CHANG and WILHEIT, 1979; TJEMKES et al., 1991). SODEN and BRETHERTON (1994) compare direct satellite estimates of water vapour with the spatial distributions of water vapour in two climate models. The largest source of error in temperature measurement may be not in the satellite data but in the algorithms used to invert them for temperature. For example, HURRELL and TRENBERTH (1992) correlate monthly means of Channel 2 of the Microwave Sounding Unit (MSU) of the NOAA satellites with monthly means from the European Center for MediumRange Weather Forecasting (ECMWF) archives for optimally assimilated data. Strangely enough, the MSU fields are more highly correlated with the ECMWF analyses over regions where the model is initialized by radiosonde data than over regions where the primary temperature measurement is inversion from the NOAA satellite (which includes the MSU data). They find correlations of greater than 0.95 over extratropical continents of the Northern Hemisphere, whereas, at comparable latitudes in the Southern Hemisphere, correlations are between 0.8 and 0.9. Current research is working towards more direct methods of assimilating the satellite radiance data (e.g. EYRE, 1989; EYRE et al., 1993). An alternative approach to use of model forecasts as a first-guess input to the inversion of temperature and humidity profiles from the NOAA satellites has been reported by SUSSKIND et al. (1984) and CHAHINE and SUSSKIND (1991). Their approach is evolving into algorithms for analysis of the AIRS data on future EOS platforms.
Data assimilation issues
Atmospheric fields are continuous in time and space, whereas satellite and radiosonde measurement systems provide limited samples. This limitation is largely overcome through use of 4-dimensional data assimilation approaches using dynamical models (e.g. HARMS et al., 1992; SCHUBERT et al., 1993). This approach has been developed as part of numerical weather prediction (NWP). Weather prediction models start with present observed conditions and are integrated forward in time for up to several weeks to derive future weather. Because the equations of atmospheric dynamics are chaotic, the initial conditions are eventually "forgotten", and a model simply begins to provide a realization of its climate (random departures from mean conditions). In principle, NWP models describe the same physical system as climate models. In practice, NWP models are integrated at much higher spatial resolutions, whereas climate models use additional physical parameterizations and system components, important on longer time-scales. Over the first day or two of a weather forecast, the predicted winds and temperatures are largely determined by the observationally based initial conditions. Hence, these predicted fields provide an observationally based estimate of the actual winds and temperatures at that time. Direct measurements made concurrently provide another estimate. An improved estimation can be made by combining these independent estimates. If observations can be characterized statistically as an actual value plus random noise, then multiple estimates can be optimally combined. This approach is used at a point to combine direct observations with model forecasts derived from previous observations. Observations are extended spatially by use of information on spatial "influence" functions, derived from auto-
263
Satellite systems and models for future climate change correlation statistics. For parameters that are not measured, or for locations far from sites of direct measurement, the forecast determinations are themselves optimal estimates. For example, it would be possible to obtain winds and temperature everywhere with this procedure from simply the radiosonde observations over land. Hence, in order to be useful, satellite measurements over oceans must be of comparable or greater accuracy than the forecast values available in their absence. Atmospheric fields at a given time are, in addition, constrained by various dynamical balances. The time integrations eventually impose these balances. However, direct observational estimates of fields will have errors initially that do not satisfy the known dynamical balances. These imbalances can introduce spurious waves or instabilities in a forecast, so that "balancing" has become part of the initialization of atmospheric fields.
Inclusion of diabatic processes
Initialization procedures, as just described, are most advanced in the context of a hypothetical, dry, frictionless and adiabatic system. The question of how to initially couple this system to surface processes and to moist processes including convection, clouds, precipitation and radiation (referred to collectively as "diabatic"), is just beginning to be addressed. Measurements from satellite systems are crucial components of the methods being developed to do diabatic data assimilation. The linkages to diabatic processes are less dominant for shorter time-scales than they are for climate. They also have been neglected in the past because of a dearth of observations to specify them at a given time in the system. Wind analyses in the tropics still have significant errors (e.g. HOLLINGSWORTHet al., 1989), especially in the divergent component. Divergent winds are largely determined by diabatic heating and so are not adequately provided through the normal mode initialization scheme. Use of rainfall rates derived from infrared (IR) estimates of latent heating provides substantial improvements in estimating tropical winds (KASAHARAet al., 1988; HECKLEY et al., 1990). Future satellite observations are seen as critical for providing sufficient observations to include moist and radiative processes in four-dimensional initialization procedures. Global data sets from model assimilation are made available to research scientists as byproducts of operational forecasting systems.
Land surface properties for climate models
The land components of climate models depend on atmospheric inputs, land property data sets and on land surface parameterizations. The most direct inputs are incident solar and thermal radiation and precipitation. Improved global observational descriptions of these from the surface and satellite remote sensing are needed to evaluate the realism of these terms in climate models and so to promote needed improvements in the models. Likewise, climate models require uniform descriptions of land surface properties available only from satellites. Advances in land surface parameterizations are through field programmes with substantial satellite components.
264
Land surface properties for climate models
Radiative forcing There are now quite a few surface sites that have maintained climatological records of surface incident radiation for more than a decade. The World Climate Research Programme (WCRP) and NASA have promoted the Surface Radiation Budget (SRB) project to establish methods for inferring surface incident solar radiation from the ISCCP data. Two algorithms that give good agreement with surface measurements have been selected for development of long-term data sets (DARNELL et al., 1992; PINKER and LASZLO, 1992). Both use physically based approaches that require information on surface albedos, atmospheric water vapour, and models of bidirectional reflectance. Fluxes for July 1987 are shown in Fig. 9. These approaches provide monthly average solar fluxes with an uncertainty of 10-20 W m -2. Global data sets of monthly mean solar fluxes have been developed for four annual cycles (WHITLOCK et al., 1993). PINKER and LASZLO (1992), in their Appendix B, show that considerably more accurate daily values can be obtained by use of the initial GOES data at its full temporal and spatial resolution. The solar radiation absorbed at the Earth's surface is highly dependent on the TOA reflection of solar radiation by clouds and other scatterers (CESS and VULIS, 1989). For example, Fig. 10 shows that the "cloud forcing", i.e. the decrease in absorbed solar radiation because of the presence of clouds, is highly correlated and nearly the same at the top of the atmosphere as at the surface, i.e. these two parameters have a correlation coefficient of 0.98. Atmospheric absorption of solar radiation is evidently insensitive to the thickness of clouds, although somewhat dependent on their height. Consequently, comparisons between measurements and model results for top of the atmosphere cloud forcing over land surfaces should provide validation for cloud effects on surface radiation. LI and LEIGHTON (1993) have developed an algorithm for relating monthly reflected solar fluxes measured by ERBE to the solar radiation absorbed at the surface. The incident surface longwave radiation is more difficult to infer from space, as it is not physically linked to TOA fluxes as are solar surface fluxes. GUPTA et al. (1992) have described an algorithm using NOAA Sounder data that gives good agreement with detailed radiation transfer measurements. Wu and CHANG (1991) show, however, that estimates of surface downward longwave fluxes can vary by 20 W m -2 or more as a result of uncertainties in cloud properties, as well as in humidity and temperature profiles in the lower troposphere. The fraction of incident solar radiation that is reflected, referred to as the albedo, must also be known in order to determine net radiative heating. Land surface albedos currently used in climate models are largely based on a limited number of point surface measurements. Satellite data can potentially provide much more convincing spatial and temporal descriptions of land surface albedos. The parameters of simple analytic models for canopy bidirectional reflectance can be obtained by satellite radiances with an adequate distribution of angular directions. Such models can then be integrated over view angles to provide models of surface albedo (DICKINSON et al., 1990; AHMAD and DEERING, 1992; STARKS et al., 1992). Ideally, this would be done over the spectral intervals used to represent the radiation in a GCM. Past satellite estimates of surface albedo have been of low accuracy as a result of sampling and calibration limitations. The application of satellite sensors to estimate the fraction of
265
Satellite systems and models f or future climate change
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266
Land surface properties for climate models solar radiation reflected from the surface has suffered from one or more of the following: (i) use of a narrow spectral band to estimate total solar spectrum; (ii) inaccuracies in determining the atmospheric contributions from clouds and aerosol to reflected radiation; (iii) use of radiation reflected from the surface with a particular directional path to the satellite to estimate the angular distribution of radiation reflected in all directions. Instrumentation on the EOS satellite promises to overcome these difficulties. The first EOS satellite includes the following: (1) the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, which provides a large number of narrow channels spanning the solar spectrum, with sufficient spatial resolution to adequately remove atmospheric effects and determine spectral variation; (2) the Multi-angle Imaging SpectroRadiometer (MISR) instrument, which uses 8 view angles and 4 spectral channels to provide the directional dependencies of surface reflectances; and (3) the CERES instrument, which provides broad-band reflected fluxes with very good calibration. With observations from EOS, it should become possible for the first time to determine not only seasonally varying land albedo, but also any long-term trends (RUNNING et al., 1994a). Changing surface albedo is a common ingredient of hypotheses of land surface-climate interactions ( e.g. CHARNEY et al., 1977). Since climate model albedos are usually determined from information on land-cover characteristics, the concurrent measurement by EOS of these properties (discussed in the section on Land cover properties) will allow further improvements in climate-model specification of albedo.
Latent heat atmospheric forcing Coupling of surface hydrological and energy processes to the overlying atmosphere is a key ingredient of modelling surface processes. Besides radiative fluxes and precipitation, atmospheric wind, temperature, and humidity profiles are needed to determine this coupling. Climatological measures of this coupling process are needed for model validation. Besides the climatologies of the individual fields just mentioned, large-scale diagnostics derived from mass and energy conservation integrals provide valuable information as to model performance. In particular, over a long enough period of at least a month, atmospheric storage of water will be small; then, over a continent or other large land surface with average mass rates of precipitation P and evapotranspiration E, the convergence of water vapour flux by the atmosphere will be nearly balanced by P-E times the surface area. The power of this relationship is that the water vapour flux convergence can be evaluated from atmospheric or model data to provide the net supply of water to the surface from the atmosphere. This net supply should balance continental runoff, averaged over years or longer. An estimate of E-P can be used with observational data including precipitation to infer evapotranspiration E over a region, and the E-P estimate can be used with runoff measurement to infer the time history of continental soil moisture (e.g. RASMUSSON, 1968). On a global land average, the net latent heating from water flux convergence represents about half the total rainfall and is about 30 W m -2. Over tropical continents in the rainy sea-
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son, it exceeds 100 W m -2, which must be compensated by some combination of dry energy lateral fluxes and radiative response. Similar analyses are useful for energy, namely, if R is the average net radiative energy input over some such large land area, as measured by satellites at the top of the atmosphere, then R must be balanced by the divergence of moist static energy flux (i.e. flux of latent heat of the water vapour flux plus flux of sensible heat and potential energy) and net surface energy flux (i.e. over land, the energy used for soil heat storage, melting of snow or permafrost). The balance requirements just outlined have been studied for several decades (cf. PEIXOTO and OORT, 1992), but only now are global meteorological data and climate model simulations becoming of sufficient quality to allow reasonable success in their evaluation. For example, FORTELIUS and HOLOPAINEN (1990) have studied continental energy balances using ECMWF First GARP (Global Atmospheric Research Programme) Global Experiment (FGGE) data for February and July 1979, along with ERB data from the Nimbus-7 satellite. The substantial imbalance they find suggests that this analysis is still not easily applied. TRENBERTH (1991) has estimated water fluxes from more recent ECMWF data for May 1988. As he discusses, the available data archives are inadequate for this task because of unresolved diurnal components and low vertical resolution in the lower troposphere.
268
Land surface properties for climate models Whereas diagnostic balance relationships can be quite useful, they may by themselves not be sufficient to establish an understanding of causes and effects. The strongest interactions between precipitation and land usually occur in the tropics or during summer, when precipitation is predominantly convective. Under these conditions, interpretations in terms of changing stability of the atmospheric column to moist convection can provide extremely valuable additional insights (SUD et al., 1993; BETTS et al., 1994; FU et al., 1994). From this viewpoint, land processes (as a boundary condition to the atmospheric model) control rainfall through determining the moist static energy and hence the relative stability of boundary layer air to ascent as parcels in moist convection. Fu et al. (1994) have established with ISCCP data, over the tropical oceans, that stability of boundary layer air is a more fundamental and certain predictor of convective clouds than the other more commonly used criteria of SSTs.
Land cover properties
A large number of properties of the land surface are required as part of the land process representations of climate models. Besides albedo, many of these other properties are also inferred in the model, either as numerical values specified from a given land cover, or in terms of parameterizations whose numerical values depend on the land cover. At present, this information is available from global data sets derived from national atlases of land cover and land use. The quality of these data varies from country to country and the data cannot be used to infer changes with time. The output of instruments on EOS will make possible for the first time a uniform description of global land cover and land cover change. RUNNING et al. (1994b) propose to first classify vegetation according to three properties: (i) the seasonality of above-ground biomass, essentially the separation between forests or shrublands and all other vegetation; (ii) evergreen versus deciduous canopies; (iii) needleleaf or broadleaf or grass. This information, to be obtained globally at 1 km resolution, together with characterizations of the sparseness of the vegetation through leaf area indices (e.g. GOWARD et al., 1991) and specification of wetlands, should provide climate models with much more complete information on land cover than is now available. Other key ingredients of current land surface parameterizations derived from land cover are the extent of the green-leaf surface leaf-area index (LAI) available for transpiration and of the absorption of photosynthetically active radiation (PAR), as represented by how much is incident (IPAR) and the fraction of that incident radiation that is absorbed by the canopy (FPAR). Satellite instruments provide estimates of the effective "greenness" of the Earth's surface related to LAI and FPAR through various vegetation indices (VI). These are determined from measurement of relative differences in the amplitudes of radiation reflected in the visible versus near infrared part of the spectrum. Such differences result from the strong absorption bands of chlorophyll in the visible. This property complicates determinations of spectrally integrated surface albedos, but provides the basis for remote sensing of vegetation cover. Currently, global VIs have been determined through use of Channels 1 and 2 of the AVHRR instruments of the NOAA operational satellites at 4 km resolution. Multiple spectral chan-
269
Satellite systems and models f or future climate change nels and reflectance directions and better spatial resolution would provide more detailed descriptions of vegetation cover. More spectral channels and better resolution have been provided at some locations through use of LANDSAT data and should be possible globally and with further detail using the EOS MODIS and MISR instruments, with the latter providing reflectances at multiple viewing geometries.
Surface parameterizations and field programmes Establishing the usefulness of satellite data to specify surface conditions requires programmes relating direct local measurements to remotely sensed data. The most ambitious such programme to date was the International Satellite Land Surface Climatology Project's (ISLSCP's) First ISLSCP Field Experiment (FIFE), carried out largely in the summer of 1989. Many of the results of this effort were reported in a special issue of the Journal of Geophysical Research in 1992 (SELLERS et al., 1992a). One important finding (SELLERS et al., 1992b) is a near linear relationship between VIs and "surface conductance". This conductance results from the integrated effect of plant stomates in controlling evapotranspiration. The linearity is interpreted in terms of a photosynthesis model. The plant canopy assimilates more carbon with more visible radiation and, in doing so, transpires more water. Accordingly, remotely sensed measurements of VI provide estimates of unstressed canopy conductance. Because of the linearity, this result is scale invariant, that is, small-scale surface heterogeneity will not invalidate use of remotely sensed measurements that average over a large area (i.e. have large pixels). HALL et al. (1992) discuss the overall conclusions from FIFE regarding remote sensing of surface properties. Considerable effort has also been devoted to the development of satellite approaches to inference of surface sensible and latent energy fluxes (e.g. as reviewed by DICKINSON, 1990). The principles used are: (i) to infer surface skin temperature from satellite radiances, and use this with measured radiative forcing and atmospheric properties to infer sensible and latent fluxes, and (ii) to infer surface soil moisture from passive microwave data and, with models, relate that to root zone soil water and surface fluxes. HALL et al. (1992) report difficulty in applying the skin temperature approach with the FIFE data set, including radiometric temperatures from a helicopter platform. They argue that, on the small scale of their observational radiometric temperatures, those differ enough from the canopy temperature to render direct estimates of sensible fluxes highly inaccurate. The question remains open as to whether larger scale temperature estimates from satellite platforms would give better direct estimates of surface sensible fluxes as reported in previous studies. An alternate approach to use of remote sensing to infer surface fluxes is reported by SMITH et al. (1993) and CROSSON et al. (1993). They use AVHRR skin temperatures to estimate the slowly varying component of canopy resistance. Their method requires temperature variations to be controlled primarily by evapotranspiration and so may be site and season/latitude specific. The requirement of all the flux estimation methods that surface atmospheric properties are available suggests that surface flux inversion must be done either where there are adequate surface air measurements or in a framework of 4-D data assimilation with atmospheric models. Only the latter approach has any potential for providing fluxes on regional and global scales. Perhaps the most sensible approach would be to use the satellite data for
270
Oceans and cryosphere model validation by comparing directly modelled and observed climatological skin temperatures (e.g. SUSSKIND, 1993) and surface soil moisture (e.g. CHOUDHURY, 1991) provided the model quantities can be formulated to adequately resemble what satellites can measure.
Oceans and cryosphere Oceans Oceans in liquid state are the major thermal reservoirs of the climate system. Ice and snow, especially in the form of sea-ice, act as surfaces of high albedo and thermal insulation. The basic ocean processes in a climate model are the energy exchanges across the oceanic surface, the horizontal and vertical redistributions of thermal energy and the phase changes to sea-ice. In the context of climate models, ocean surface energy fluxes can be estimated from observations in two ways. Given observed ocean surface temperatures, the atmospheric model can calculate net fluxes into the ocean that are internally consistent with those temperatures. Alternatively, given observed atmospheric surface meteorology (winds, humidity and temperatures), an ocean climate model will generate the net surface fluxes that it requires to be consistent with these fields. Coupled ocean-atmosphere models allow surface temperatures to adjust to this atmosphere-ocean energy exchange. Modelling groups have found coupled model approaches to give unrealistic surface temperatures unless supplemented by empirically derived "flux corrections" that are added to the model determined fluxes. These corrections have been comparable in magnitude to the fluxes. Evidently surface fluxes in current climate models have large errors that degrade the application of the models to climate change questions. However, the source of error is currently unresolved because of the relatively poor state of observations of the individual contributions to surface energy fluxes. We need to know the error fields of model-derived surface solar and longwave fluxes, sensible and latent heat. Additional validation is needed of the ocean circulations that provide the horizontal heat transports and of the model sources (evaporation) and sinks (precipitation and river runoff) of salinity which, with the temperature, contribute to ocean buoyancy. Data from satellites are becoming sufficiently accurate to provide many of the observational constraints needed to ascertain the current causes of model errors and to otherwise validate ocean-atmosphere coupling. Conservation integrals, as already described for land, can be equally informative over the oceans. Differencing energy supply by atmospheric transport from top of the atmosphere net radiative fluxes gives the net surface energy flux into the ocean. Indeed, estimation of this flux over ocean latitude belts provides an estimate of the large-scale latitudinal energy transport required by the oceans (PEIXOTO and OORT, 1992; MICHAUD and DEROME, 1991). Global data sets from present programmes and with major improvements expected in the EOS era should start answering the following questions over the model oceans: (i) How well do the models determine incident surface solar radiation (highly dependent on model simulation of clouds and their radiative effects)? (ii) How well do the atmospheric models simulate surface sensible and latent energy fluxes? (iii) How well do the atmospheric models
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Satellite systems and models f or future climate change
simulate surface winds and momentum stress? (iv) How well do the ocean models simulate the barotropic current systems? (v) How well do the models simulate seasonal and interannual variability of sea ice? (vi) How well do the atmospheric models provide oceanic salinity inputs? Satellite observations of surface solar fluxes and precipitation have been previously described. Unique to the oceans are various microwave measurements at the ocean surface. Oceanic emissivity/reflectivity of microwave depends on the presence of capillary waves responding directly to the wind stress. The current generation of SSMI passive microwave instruments is being used to estimate surface winds (e.g. WENTZ, 1992). Improved measurements have been demonstrated with active systems, with the optimized instruments referred to as "scatterometers". Other active systems, optimized to give precise heights of the ocean surface, are referred to as altimeters. These provide measurement of geostrophic surface ocean currents (e.g. KOBLINSKY, 1993). Transient ocean currents are measured by looking at changes in the height of the ocean surface in time. For example, the details of equatorial Rossby and Kelvin waves in the ocean, responsible for the oceanic component of the ENSO phenomena, are now being revealed by TOPEX-Poseidon, which provides ocean height measurements to an accuracy of 2-3 cm. Evaporative fluxes are inferred from surface winds and specific humidity. The latter is estimated on a climatological basis by satellite measures of column water vapour (e.g. LIU et al., 1992; LIU, 1993). Satellite measurements (thermal and microwave) of spatial and temporal variations of ocean surface temperatures are combined with surface observations (REYNOLDS, 1991). The Atmospheric Model Intercomparison Project (AMIP) of WCRP and the US Department of Energy (DOE) is currently using such ocean temperatures from 1979 to 1988 to intercompare and test the current generation of GCMs with realistic prescribed ocean forcing.
Cryosphere Snow, sea-ice, the continental ice sheets (Antarctica and Greenland), and glaciers all are high-albedo objects comprised of water in its solid form and are collectively referred to as the "cryosphere". These objects are often closely associated. Overlying snow determines the albedo of sea-ice and ice sheets much of the time. Figure 11 shows the summertime monthly surface albedos of the Arctic sea-ice as inferred from visible imagery (ROBINSON et al., 1992). Because of the cold temperatures, evaporative fluxes are small, and so surface temperatures are largely controlled by a balance between net solar and thermal radiation. Cryospheric elements hence provide strong positive climate feedbacks through their reflection of solar radiation to maintain the cold temperatures that they, in turn, require to exist. Arctic sea ice is regarded as relatively sensitive, that is, its extent may shrink drastically with global warming; reduction in the water storage by glacier and ice sheets with global warming is a serious concern because of the accompanying rises in sea level. Satellites are an ideal tool for examining many aspects of the cryosphere. Passive microwave systems have been proven valuable in mapping distributions and areas of snow cover depth (e.g. CHANG et al., 1987; FOSTER and CHANG, 1993). Visible reflectances have also 272
Oceans and cryosphere
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Fig. 11. Mean monthly surface albedo (percent) for the Arctic Ocean for (a) May, (b) June, (c) July and (d) August (1-15 only), based on analysis of visible band satellite imagery (from ROBINSONet al., 1992). Values include the effects of open water in the ice cover. been quite useful for looking at global variations of snow cover (e.g. MATSON, 1991). All these properties must be validated in climate models for snow. ROBINSON et al. (1993) review global snow measurements from satellites. Sea-ice cover is observed by similar techniques to those used for snow on land (e.g. as reviewed by BARRY et al., 1993; PARKINSON and GLOERSEN, 1993). Higher spatial resolution measurements, such as by SAR, can provide information on leads, i.e. ice-free areas, or on the drift velocities of the ice. Measurement of mass balance is a key issue for studies of glaciers and ice sheets. Satellite measurements of surface height (altimetry) can be used to estimate changes in accumulation of snow and ice, and other techniques can look for rates of iceberg calving, areas of melting snow and velocities of large ice streams (as reviewed by THOMAS, 1993). Remote sensing
273
Satellite systems and models for future climate change research on many of these questions is contributing primarily to technique development and to basic process descriptions. Climate models are not yet sufficiently advanced to be able to use such information. Satellite measurement of snow and ice extent has now made available long enough records to start looking at long-term trends. Other cryospheric measurements are in their initial stages of development, and questions such as whether it will be possible to separate interannual variability from long-term trends have not yet been addressed.
Satellites and future climate
Satellites are becoming an increasingly important source of observation of the elements of the global climate system and are needed to improve models for assessing and projecting future climate change. Satellites are most powerful in depicting spatial patterns, e.g. of weather, clouds, vegetation, ocean surface temperature, and in providing quantitative estimates of properties directly related to reflection of solar radiation and to thermal emission in the infrared or to reflection or emission in the microwave. Many of these measurable quantities are major elements of global climate models and are closely linked to the forcing of future climate changes. Important aspects of radiative energy balance, in particular, are both addressed by climate models and measured by satellites, opening the door to answering many questions. For example" How do clouds form and modify solar and thermal radiative fluxes? What is the extent of snow and sea ice and the consequent effect on surface albedo? What is the spatial distribution of different vegetation covers and their most important properties? What is the distribution of rainfall over the oceans? Future climates will be both assessed and projected using four-dimensional syntheses of satellite data and results from numerical models. The volume of data provided by satellites on these issues is, in many cases, large enough to be at or beyond the limit of what can be managed by current technologies. Many new measurement capabilities will become available in the future with the next generation of satellite platforms and instruments. Consequently, governments and operational and research institutions are currently putting considerable effort into upgrading their data systems to facilitate the analysis and exchange of current and future satellite data. Satellite data are used for climate research to validate or reveal deficiencies in climate models, examine physical processes, or look at year-to-year variations and long-term climate change. This chapter has focused on the use of satellite data to improve climate models so that they can project future climates better. The urgent issue of direct observational determination of long-term climate trends (cf. Chapter 5 by JONES and Chapter 6 by DIAZ and KILADIS) requires longer data records than are now readily available from satellites. An immediate approach is to seek ways to use other longer instrumental records to extend the length of time considered. A more systematic approach, as envisaged by the EOS programme, would be to obtain uniform satellite observations over decadal time-scales. Several decades of such high-quality data, much of it assimilated and synthesized into real-time climate and forecast models, will provide new and enhanced capabilities in climate analysis and projection. In particular, the type of "fingerprinting" of climate change described by JONES in Chapter 5 will use such data.
274
Acknowledgements
Acknowledgements The author would like to acknowledge support of this work under Department of Energy Grant DE-F602-91ERG1216 and National Aeronautics and Space Administration LOS Interdisciplinary Scientific Research Programme UPN 429-81-22 and UPN 428-81-22. The final manuscript was edited by M. Sanderson-Rae.
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Chapter 8
Dynamics of future climates BRYANT J. MCAVANEY AND GREG J. HOLLAND
Introduction
Our climate system results from complex, non-linear interactions across many scales in response to a combination of external and internal forcing. The dominant external input is solar energy. Occasionally volcanic eruptions and impacts by extraterrestrial bodies can cause major disruptions, indeed complete changes to the climate, but these are not of concern for this chapter (see Chapter 4 by RAMPINO). The atmosphere is largely transparent to shortwave solar radiation, some of which is reflected back to space, especially from clouds and snow cover. Generally, the solar heating of the surface is maximum in the tropics and minimum near the poles, but the distribution of different types of land and water surfaces causes considerable regional variations. Some of the surface energy goes into long-term storage in the form of heat and biological processes, such as plant growth, but the major proportion is redistributed by longwave radiation, by direct heating of the overlying atmosphere and by evaporation of water. Water vapour, other atmospheric gases and clouds trap some of the outgoing longwave radiation to provide a natural greenhouse effect, so that the atmosphere is substantially warmer than it would be without an atmosphere (as described in Chapter 1 by HENDERSONSELLERS). Nevertheless, the atmosphere cools radiatively at around 1-2~ per day. This cooling, combined with the equator-pole temperature gradient, is the major forcing mechanism of the climate system. The meridional temperature gradient both drives large-scale circulations, such as the tropical Hadley circulation, and provides a local store of baroclinic energy that can be released to form extratropical storms. Water vapour provides the fuel and can be transported over large distances before releasing enormous bursts of energy in small regions. The form of the atmospheric response is modulated by the Earth's rotation, by regional distributions of surface conditions (cf. Chapter 12 by HENDERSON-SELLERS),and by the types and forms of perturbations that can be sustained. These perturbations take the form of combinations of wave types which, for their maintenance, variously depend on the vertical and horizontal temperature stratification, the meridional gradient of Earth vorticity and the presence of barriers such as mountain ranges. The types and scales of response vary enormously, from local convective clouds to millennial changes in deep ocean circulations. These scales interact in complex and non-linear ways. For example: (1) perturbations developed in one part of the atmosphere may propagate over large distances before transforming into a local storm system, a phenomenon often referred to as teleconnections; (2) a local wind burst over the ocean may induce a long-lived pertur-
281
Dynamics offuture climates bation of the ocean surface and thermocline, which subesquently effects the atmosphere months or even years later (e.g. the ENSO cycle). Given the variety and complexity of these interactions, the surprising feature of the climate is its inherent stability. The development of mathematical expressions for the physical principles that govern the climate s y s t e m - the laws of thermodynamics and Newton's laws of motion - has encouraged and sustained great progress in our understanding of the climate system. Scaling of the governing equations provides specific solutions that help us build a physical picture of the major components. Mathematical climate models running on supercomputers allow experimentation with climate mechanisms and enhance our capacity to diagnose the appropriate solutions objectively. Diagnostic methods applied directly to raw observations, or to fields from advanced analysis and numerical data assimilation schemes, provide insight into the teleconnections and scale-interactions that occur. Application of these techniques has provided rapid progress in our understanding over the past decade of the mechanisms responsible for maintaining and changing climate. In this chapter, we do not attempt to present a comprehensive discussion of all aspects of climate dynamics; such a daunting task would require a complete book in itself. Rather, our intent is firstly to highlight particular current issues and recently developed diagnostic techniques. Since many of the tools and techniques discussed are only suitable for use with large comprehensive data holdings from global data assimilation centres, the use of data from these sources will be highlighted. Much of our discussion is centred around the diagnosis of the current climate although Section 5 does attempt to raise questions and present hypotheses regarding future climates.
Diagnostic methods Diagnostic models The full thermodynamic and motion equations are complex and difficult to work with directly. Fortunately, the governing equations can normally be simplified by an appropriate scaling of each of the terms relative to the problem at hand (CHARNEY, 1947). Such scaling forms the basis of all diagnostic approaches to understanding all atmospheric processes, including climate. Examples of such an approach may be found in almost all standard text books (e.g. HALTINER and WILLIAMS,1979; GILL, 1982; HOLTON, 1992).
Climate models For both atmospheric and oceanic general circulation models, prognostic equations governing the conservation of momentum, heat, mass and water substance (or salt in the case of the ocean) are solved numerically over the globe at a set of discrete levels in the vertical. Current atmospheric models use two alternative approaches to approximating the horizontal structure" one stores the prognostic variables on a horizontal grid of discrete "grid points" and solves the equations using finite difference techniques; the other technique represents all prognostic variables by a series of spherical harmonic "waves" and uses the spectral technique for solution. When integrations over a few decades to a century are contemplated,
282
Diagnostic methods
limitations due to computer resources mean that only a relatively coarse resolution is possible in current climate models. Typically a resolution of about 10-20 vertical levels is chosen with a grid length of 300 km for models using finite difference techniques or about 30-40 spectral waves for models using the spectral technique. The book by TRENBERTH (1992) contains more details. Oceanic models (usually employing finite difference techniques) often have greater horizontal resolution. The largest source of uncertainty with such models is that associated with the requirement to parametrize those physical processes that are not resolvable by the grid chosen (e.g. clouds, radiation, convection and surface processes). For a process such as radiative transfer, parametrization is possible through the underlying mathematical theory. However, for many processes the underlying mathematical development is missing and hence parametrizations are developed from a combination of observational studies, laboratory experiments and numerical sensitivity experiments. The parametrization of physical processes for an oceanic model is also required, but can be more straightforward.
Climate analysis The fields that characterise the atmospheric state are quite variable in time so that the climate is normally described in terms of a time-mean state of the atmosphere together with its temporal fluctuations. Conventionally (e.g. PEIXOTO and OORT, 1984) a time-average operator is defined as A-(I/~)
IO
Adt
and A' its deviation so that A = -A+A'
(1)
and {A'} = 0, and the product of two arbitrary quantities A and B is AB = A B + A ' B '
(2)
With this formalism the balance equations for time-averaged conditions are readily derived (e.g. BOER, 1982; PEIXOTO and OORT, 1992 ) from the equations of motion in forms well suited to detailed analysis. Analysis of the global time-averaged atmospheric circulation proceeds using fields derived either from station observations directly (e.g. OORT and PEIXOTO, 1983; PEIXOTO and OORT, 1992) or from data assimilation schemes (e.g. TRENBERTH and OLSON, 1988; HOSKINS et al., 1989). The direct approach outlined by OORT (1983) uses only surface and radiosonde observations and neglects satellite and aircraft data. Hence this analysis (especially for the transient eddies) may be unreliable in data sparse areas such as the Southern Hemisphere oceans. Modern global data assimilation systems are capable of combining data from a great variety of sources in a coherent manner (BENGTSSON and SHUKLA, 1988). Sophisticated methods of data quality control are used to ensure that the subsequent analyses are as reliable as possible. A problem with the use of global data produced by data assimilation systems at major operational centres is the fact that these systems are undergoing continual improvements. This means that it is quite possible for such improvements to introduce a spurious interannual
283
Dynamics of future climates variability in the analysed data. Furthermore, the performance of any data assimilation system is ultimately limited by the availability and quality of raw observations. Discrepancies between analyses produced by different operational centres will continue to be largest in areas where data are limited and the analysis depends on the quality of the first guess produced by the specific model in use. At least two global centres (ECMWF and NMC, Washington) have plans for extensive re-analysis for the period since 1979 using the most recent data assimilation schemes and incorporating more data than were available at the time of the earlier operational products. The problem for the future will be that further re-analysis will be required as data assimilation schemes are improved still further. Despite these caveats, modern data assimilation systems now provide estimates of fields never previously available, in particular those of divergence, vorticity, vertical motions and moisture. It is now possible to construct, with some degree of confidence, horizontal and vertical fluxes of heat, momentum and moisture and hence infer further, more detailed, aspects of the baroclinic flow. Most diagnostic studies of the large-scale behaviour of the atmosphere have been conducted in isobaric coordinates since data are most readily available on constant pressure surfaces and the equations of motion have a relatively simple form in that coordinate system. However, as BOER (1982) has pointed out, this apparent simplicity is somewhat illusory when averages and integrals of the equations are required. The main complication arises from the variation of the lower boundary condition, since the simple time-averaging operator in equation (1) is clearly not defined on an isobaric surface that is pierced by topography. BOER (1982) overcomes this difficulty by extending the domain of definition of an isobarically defined variable to the region 0 < p < P0 where P0 is some large fixed value of pressure (Po > Ps) which is never exceeded. Atmospheric variables are then defined in this extended domain with appropriate extrapolation when p > Ps; all equations of motion apply to the extended domain provided that they are all multiplied by a factor fl, where fl = 0 for P > Ps and fl = 1 for p ___Ps- In the more usual case of discrete pressure levels, the definition of fl given above for the continuous case has been extended by TRENBERTH (1991 b) and becomes
for P j-1 < Ps
O,
for Pj+I > Ps
Ps --Pj+I
(3)
for P j-1 > Ps > Pj+I
Pj-1 --Pj+I
With these definitions the time average of fl then reflects the portions of time for which Ps < P and an appropriate definition (BOER, 1982) for the "representative" time mean of variable A (denoted by the superscript R) is
AR =
,
t X, 284
fl~:O
,8=o
(4)
Diagnostic methods
Decomposition of A into mean and transient components and the evaluation of variance and covariance terms follow naturally with A'=A-A
R
(5)
fla" = fl---A- -fiA R = 0 ~ R
t~AB = t~(A R B R + A ' B '
)
Naturally for points well away from the surface (fl = 1), the definitions are the same as given previously. The modified definitions have no imaginary contributions from subterranean points. Many of the commonly available "diagnostic processing" software packages used by climate modellers and climate diagnosticians have this basic discrete fl formalism already incorporated although some care still needs to be taken since the approximation that fl can be replaced by its time average fl is often made in order to reduce data handling. The traditional budget equations in isobaric coordinates are approximations to the more complete equations of BOER (1982) which have some similarities to the mass weighted averaging approach of JOHNSON and DOWNEY (1975) and the more general coordinate independent approach of JOHNSON (1980). For the most part, traditional views of the atmospheric circulation and its maintenance and forcing have been founded upon isobaric results. An alternative viewpoint developed using isentropic coordinates has been promulgated by JOHNSON (1989) and his colleagues. At issue in these two approaches is the different physical interpretation of mean and eddy processes among different coordinate systems which imply different averaging domains. Recently, links have been established between the isentropic view of the mean circulation and the time averaged residual meridional circulation in isobaric coordinates (TOWNSEND and JOHNSON, 1985). With the rapid emergence of appropriate analysis tools and the relative ease of access to archives of global data from an expanding base of national and international global assimilation systems, it is expected that the use of isentropic analysis will become more widespread. We should soon see whether such studies will indeed provide greater insights into the most challenging problem of the coming century: the extent to which climate is determined by external forcing, internal forcing, non-linearity and other processes (JOHNSON, 1989). The main objective of much of climate analysis is inferring the balance of mass, angular momentum, energy and water vapour from observations. Since these balance conditions constitute the constraints that must be fulfilled by a general circulation model, detailed resuits from climate analyses are essential for validation of such models (cf. Chapter 7 by DICKINSON). In some cases validation is being done from both the isobaric framework and the isentropic framework (e.g. TOWNSEND and JOHNSON, 1985). This approach should be applied systematically across a range of models. However, because the isobaric framework is much more extensive in the published literature, most of the discussion in this chapter is centred around the isobaric interpretation. Until comparatively recently, one limitation of the global data sets that are currently available has been the difficulty of balancing local budgets. Errors in the analyses and subsequent processing have often dominated the signal. One particular vexing question has been 285
Dynamics of future climates the problem of apparent mass imbalances in archived global data. Even though the original data assimilation system may formally conserve mass, loss of accuracy arising from the use of "packed data" and vertical interpolation to the archived pressure levels as well as the number and distribution of the pressure levels can give rise to residual errors in the equation of continuity in pressure coordinates. The normal strategy for correcting any overall mass imbalance is to assume that any errors are confined to the divergent wind. TRENBERTH (1991) and TRENBERTH and SOLOMON (1993) discuss correction techniques where the error is assumed to be barotropic in character. More formal variational approaches are also possible. Other refinements in data handling are discussed in TRENBERTH et al. (1993). With suitable corrections and careful processing techniques, estimates of the diabatic heating, plus sources and sinks of energy, moisture and momentum as residual terms from the budget equations, are becoming more accurate (e.g. BOER, 1982; FORTELIUS and HOLOPAINEN, 1990). Some investigators (e.g. BOER and SARGENT, 1985) have attempted to avoid the consequences of the current unreliability of estimates of vertical velocity by concentrating upon the spatial distribution of vertically integrated terms in the budget equations. Using this methodology, it is possible to determine how energy, momentum and water are transported from source to sink regions and to evaluate the location and size of these sources and sinks. In vertically integrated form, the necessary corrections that must be applied to ensure conservation of mass products of data assimilation systems (TRENBERTH, 1991b) are relatively easy to apply. It should also be noted that, formally, the vertically integrated isentropic and isobaric results are equivalent (JOHNSON, 1989) and the degree to which the two approaches actually agree is a valuable test of the consistency of the analyses. The vertically integrated equations serve as a convenient way to illustrate the method of decomposition of a flux into its rotational and divergent parts, following BOER and SARGENT (1985). In isobaric coordinates a prototype budget equation for some atmospheric constituent M can be developed from consideration of continuity as dM dt
= S
(6)
where S is a source-sink term and the derivative is a Langrangian form. i.e. for a frame of reference following a inifintesimal mass of "tagged" fluid particles (see HOLTON, 1992 for more details). Using the extended pressure coordinate formalism of BOER (1982), this equation is rewritten in the form dflM = flS dt
(7)
where extended variables M and S have been used. This prototype budget equation for a variable M can now be written in the more usual Eulerian form (BOER, 1982) as
Ot
v. flMv
Op
=
where v is the horizontal wind velocity and ~o is the vertical velocity (in isobaric coordinates). All variables in this equation are considered to be defined everywhere on an isobaric surface; there are no "holes" due to the penetration of the surface topography. For pressure
286
Diagnostic methods levels well away from the surface fl = 1 and the equation reduces to the more usual form of a budget equation in isobaric coordinates. Upon vertical integration over the extended pressure domain, the prototype budget equation becomes
1 0 poflMdp+_V, got ~o g1
~0'~ flMVdp=--1~0'~ flSdp
g
(9)
where the vertical derivative term has disappeared upon application of the boundary conditions ~o-" 0,
p-0
(10)
p=p0
(11)
and fl=0,
The resulting time averaged equation becomes
10 fo'o flMdp+lV.foO flMVdp=l~oO fl-Sdp got g g
(12)
For most climatic purposes the time averaging interval is such that the time rate of change term can be neglected so that the budget equation becomes 1 V. ~o'~flMVdp=lfo g g
~fl-'--Sdp
(13)
which can written more compactly in the form V.F =S
(14)
which is a simple statement that the divergence of the integrated horizontal flux vector F is in balance with the integrated sources and sinks S =--1 fo~ fl-Sdp g
(15)
The flux vector F = 1 f,o g J0
flMV dp
(16)
may be readily decomposed into its mean and transient eddy components and becomes
F= FM + FT where
FM - I ~o~~"flM R V R g F T = l~o'~ g
287
flM'V'dp
(17)
Dynamics offuture climates The prime denotes the deviation from the time average and equation (5) has been used to manipulate the representative time means (equation (4)). Decomposition of the flux vector into its rotational and divergent parts is accomplished through the use of Helmholtz theorem so that
v=v
+ v x =kxV
+Vx
= k xV,/,
(18)
F,=Vx The stream and potential functions are calculated from the Laplacian equations
V2~p=k.V• V2Z=V.F
(19)
This decomposition permits separation of the flux vector into a component that is associated with the distribution of sources and sinks of M from that part of the flux vector which is not directly connected with the source-sink term. Thus V.Fv, = 0 and V.Fx = S and it is the divergent component of this flux vector which connects sources and sinks. Thus if the divergent component of the flux vector can be accurately determined, the distribution of sources and sinks can be inferred. It is of course possible to split each of the mean and transient flux vector components into its rotational and divergent component giving a total of four components of the flux vector. BOER and SARGENT (1985) discuss an alternative decomposition of the flux related to the rotational and divergent components of the flow itself since this is a very common method of characterising meteorological processes. This method is not necessarily equivalent to the method outlined above and does not appear to be popular amongst climate diagnosticians.
Large-scale dynamics Atmospheric waves The atmosphere contains perturbations on many scales and of a range of types. The types of waves are normally defined by their type of restoring mechanism and include sound waves, gravity waves, Rossby waves, Kelvin waves and various combinations. Sound waves are of no interest on climate time scales. Pure gravity waves propagating on density gradients or discontinuities and are locally of little consequence, but they develop balanced circulations over scales of the Rossby deformation radius. Vertically propagating gravity waves from major mountain ranges and from transient systems such as cold fronts can have a marked effect on climate scales through a phenomenon known as "gravity-wave drag" where there is increased drag on the atmosphere that is caused by vertically propagating and breaking internal gravity waves. Furthermore, vertical propagating gravity waves in the stratosphere have been related to the quasi-biennial oscillation (QBO), which is associated with largescale changes in weather parameters (HOLTON, 1992). Rossby waves contain vorticity, are in a balanced state with the mass field, and depend on the background vorticity gradient to propagate (GILL, 1982; HOLTON, 1992). Kelvin waves are of importance to low-frequency
288
Large-scale dynamics fluctuations in the tropical atmosphere (WEBSTER, 1972; GILL, 1982). These waves propagate as gravity waves in the zonal direction, but are trapped near the equator by the change of sign of the Coriolis parameter. The generation of, partitioning between and interaction between various wave types depends on the basic state of the atmosphere, which varies substantially from the tropics to high latitudes (HOLLAND, 1994). The generation of Rossby modes depends on the degree of background rotation (HOLTON, 1992) which can be approximated by the Coriolis parameter. This varies from a low value in the tropics to a maximum at the pole. Once formed, Rossby waves are highly dispersive, i.e. their propagation speed is a function of wavelength, so that the longer waves move fastest and "disperse" away from the shorter waves. The propagation speed and degree of dispersion are determined by the background gradient of vorticity, which to first order comes from the meridional gradient of the Earth vorticity, which varies as a cosine from a maximum at the equator to zero at the pole, so that Rossby waves propagate fastest and are most highly dispersive in equatorial regions. The degree of vertical stratification of Rossby modes is defined by the Rossby-Burger depth scale (HOSKINS et al., 1985): H =
fL N
(20)
where L is the characteristic horizontal scale and N is the Brtint-V/iis/il~i frequency. Thus vorticity perturbations are more stratified in the tropics than in the higher latitudes. A good example is the manner in which wave trains emanating from the tropics typically commence with much of the energy in the first internal mode, but become equivalent barotropic at higher latitudes (HOSKINS et al., 1985; SARDESHMUKHand HOSKINS, 1988).
Wave generation Rossby waves can be generated by baroclinic or barotropic instability, by mountain torques and by diabatic heating.
Barotropic and baroclinic instability One of the basic flow patterns encountered in meteorology is a jet stream that has shears in both the vertical and horizontal directions. Barotropic instability is associated with a jet embedded in a horizontal shear whereas baroclinic instability is associated with vertical shear. Barotropic instabilities grow by extracting kinetic energy from the basic mean flow. Baroclinic instabilities grow by converting available potential energy to kinetic energy; the horizontal temperature gradient associated with vertical shear of the mean flow is the source of this available potential energy. Examples of the traditional method of instability analysis are to be found in HOLTON (1992). This method is a classical perturbation analysis and determines the normal modes of the flow. An alternative method relies upon the use of three-dimensional models. HOSKINS (1983) and HOSKINS et al. (1985) have developed this initial value approach to quite a high level of sophistication allowing a much greater degree of complexity in the initial disturbance.
289
Dynamics offuture climates Mountain torques Gravity waves can be excited by stratified flow over irregular terrain. Depending upon the atmospheric static stability and the vertical wind shear these waves can propagate vertically to great heights unless absorbed or reflected by critical layers. HOLTON (1992) gives a brief discussion of the meteorologically significant orographically induced waves. The potential for these mountain induced waves to "break" has meant that a representation of this process as "gravity wave drag" has been included in atmospheric general circul~.tion models. These simplified representations have had a large impact on the simulated wintertime climatology in the Northern Hemisphere with details of the relative strength of the drag between upper and lower troposphere determining the precise character of the changes to the simulated circulation.
Diabatic heating The degree of response of the atmosphere to diabatic forcing is determined by the Rossby deformation radius 2R, which is defined by Cg /~R "- ~
(21)
f where Cg is the group speed of the relevant gravity mode, which is primarily the first internal mode (SCHUBERT et al., 1980). The deformation radius provides both an indicator of the degree of partitioning of a transient forcing between inertial and gravity modes (e.g. SCHUBERT et al., 1980; SILVA DIAS et al., 1983) and an indicator of the scale of inertial response to small-scale convective heating (WEBSTER, 1972). The maximum deformation radius for the first internal mode is approximately 2000 km at the equator and its value drops sharply with latitude to less than half this value by 30~ (HOLLAND, 1994). Since the size of cloud clusters is essentially independent of latitude (being defined by the atmospheric scale height, diurnal time scales and local boundary-layer conditions, the response of the atmosphere to diabatic heating is very different between the tropics, where large, weak circulations tend to be produced, to the mid-high latitudes, where more constrained and intense systems result. HOLLAND (1994) has described the different responses in the upper and lower troposphere using the single-level vorticity equation formulation of SARDESHMUKH and HOSKINS (1988): + V~" V ~a = -V)~' V~a - ~a D + f
(22)
where V~, and Vx are the rotational and divergent components of the horizontal wind, V; ~a is the absolute vorticity; D is the divergence and F represents the effects of tilting/twisting and vertical vorticity advection, which we neglect for this discussion. This equation indicates that a local source of divergence (second term on the right-hand side), such as is associated with deep convection, will act as a Rossby wave source; but the atmospheric response will be modified by advection of vorticity by the divergent wind (first term on the right-hand side), which generally will be perpendicular to the vorticity contours. In the upper tro-
290
Large-scale dynamics posphere, divergence provides an increase of anticyclonic vorticity which is advected outwards by the divergent wind. Convergence in the lower troposphere, by comparison, generates cyclonic vorticity, which is advected inward by the divergent wind. Thus diabatic heating induces a large, weak and diffuse region of upper-tropospheric anticyclonic vorticity and a localised, intense region of cyclonic vorticity in the lower troposphere. Energetic constraints on the general circulation
PEIXOTO and OORT (1992) have given a comprehensive exposition of angular momentum and energy balance requirements based upon upper air soundings for the period 1963-1973 alone. Because of the very limited number of observing sites in the Southern Hemisphere and the absence of any augmenting satellite sounding data there remains some uncertainty on the full global scale picture (cf. Chapter 7 by DICKINSON).
Angular momentum Consideration of the requirement of conservation of angular momentum for the climate system leads to some important general conclusions regarding the mechanisms involved in the transport of atmospheric angular momentum. Based upon analyses of their radiosonde based observational network, PEIXOTO and OORT (1992) have presented a detailed account of the distribution and transport of angular momentum. Despite the limitations imposed by the sparsity of data in the Southern Hemisphere, OORT and PEIXOTO (1983) show that transient eddy activity is much stronger in the Southern Hemisphere than in the Northern whereas the standing eddy activity is much weaker. Overall the total flux of angular momentum appears to be larger in the Southern Hemisphere than in the North. The resultant transport of atmospheric momentum between the hemispheres may be an important component of the angular momentum budget on longer time-scales. Problems associated with the necessity to apply mass corrections to the output from global data assimilation systems has limited the use of these analyses in more detailed investigations of the transport of atmospheric angular momentum. Consideration of the asymmetry between the Northern and Southern Hemispheres and the role of the high Antarctic plateau in the angular momentum budget awaits further analysis. Recently it has become feasible to compare estimates of atmospheric angular momentum from daily analyses obtained from global data assimilation systems with direct daily estimates of the length of day. Figure 1 from ROSEN et al. (1990) shows the time series of daily values of the relative westerly angular momentum of the atmosphere based upon analyses from NMC, Washington and values of the length of day for the years 1976-1988. There is quite a remarkable correspondence between these two independent data sets over a 13-year period. Except for a slight, as yet unexplained, downward trend in length of day measurements, the curves show correspondence at all time scales. Similar comparisons with global analyses produced by other operational centres show a similar high degree of correspondence. ROSEN et al. (1991) have proceeded to separate the variability in the observed relative angular momentum into three frequency bands and have attempted to localise the sources of the frequency band-dependent fluctuations in angular momentum. The variations are controlled by behaviour in the tropics. More recently, as part of the Atmospheric Model
291
Dynamics offuture climates
.4
0.5
.2
0
0
0.5
-'~
Iq76
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
Fig. 1. The westerly relative angular momentum of the global atmosphere integrated from 100 hPa to 100 hPa based upon NMC, Washington analyses in units of 109.6kg m2 s-1 (heavy solid line) and values of the length of day (LOD) in units of 10-3s (thin solid line) for the years 1976-1988 (from ROSENet al., 1990).
Intercomparison Project (AMIP), HIDE et al. (1994) have shown that many atmospheric general circulation models when forced by observed sea surface temperatures are also capable of simulating interannual fluctuations in atmospheric angular momentum in close agreement with length of day measurements. An example taken from the Bureau of Meteorology Research Centre (BMRC) model (MCAVANEY and COLMAN, 1993) is shown in Fig. 2. In a steady state, meridional transport of angular momentum has to compensate for the dissipation of momentum due to the torques due to friction at the surface and the torque due to mountains. The role of the oceans in the transfer of angular momentum between the solid Earth and the combined ocean-atmosphere fluid envelope is not clear although the notable contemporaneity of changes in the length of the day and of the atmospheric angular momentum suggests that oceans play only a minor part. Separation of the frictional torque into its land and ocean components is necessary in order to provide more information. Unfortunately a complete investigation of the role of these torques in the angular momentum budget has proved difficult because of limitations imposed by the lack of complete data coverage. BOER (1990) has combined output from model simulations with observations from the First GARP Global Experiment (FGGE) year of 1979 to provide some reasonable guidance to the spatial distribution of the torques especially the relative role of the land and ocean friction torque terms. BOER (1990) finds from his atmospheric general circulation model results that short-term variations in the torque over the oceans are much less than over land. At longer time-scales the relative importance of the ocean torque appears to increase and the role of angular momentum transfer from the ocean to the solid Earth via the oceanic bottom topography may become important. More complete analyses from global assimilation data over the past decade should provide interesting information on the interannual variation in these torques.
292
Large-scale dynamics
I
'
I
I
'
I
I
I
,i:,h ,I l;
,.
CO
'
II
I
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A
IIIII
I
i
t
04
t I I
tom
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......... ................
C)
I
80
,
I
82
~
t.O 0
,
!
84
,
I
,
86
I
0
88
YEAR
Fig. 2. The westerly relative angular momentum of the global atmosphere integrated from 1000 hPa to 100 hPa from the Atmospheric Model Intercomparison Program (AMIP) experiment of the Australian Bureau of Meteorology Research Centre in units of 1026 kg m2 s-1 (heavy solid line) and from NMC, Washington analyses (dash dot line) and length of day (LOD) in units of 10-3 s for the years 19791988. Since the seasonal variation in the atmospheric angular momentum is so strong it should be of interest to investigate changes in model simulations of palaeoclimates, especially around 9000 years BP when the hemispheric distribution of the seasonal variation in solar insolation was quite different to the present (cf. Chapter 2 by BERGER).
Thermodynamic energy While the major features of the zonally averaged transports of atmospheric energy have been known for some time, the geographical distribution of energy fluxes and the related distribution of sources and sinks has not been as relatively well known due to problems with data coverage from conventional sources as detailed by PEIXOTO and OORT (1992). Attempts at producing more reliable geographic distributions have been made by BOER and SARGENT (1985) and BOER (1986) using data from the single FGGE year and more recently by TRENBERTH and SOLOMON (1994) using the more extensive global assimilation data from ECMWF. Using the prototype budget equation above (equation (6)), the vertically integrated energy budget equation can be reduced through use of equation (10) to the form
V.H-S
293
(23)
Dynamics o f future climates
where the horizontal energy flux vector H is given by H = _1 ~0'o f l ( c p T + O + L q ) V d p g
(24)
and the source sink term S is
(25)
S = R T - R s + H s + LE
Thus S represents the net radiative flux of energy into the atmosphere at the top and out of the atmosphere at the surface, and the sensible and latent energy fluxes into the atmosphere at the surface. The energy flux vector H can be further decomposed into its mean and transient parts as (as in equation (12)) where HM
= _1 fo'O fl(Cp T + ~ + L'~)V dp g
(26)
and H T = lifo'~ fl(cpT'+ ~ ' + L q ' ) V ' g
dp
(27)
Further decomposition of the flux vector into its rotational and divergent components then provides H = Hw + H x (as in equation (13)) where the divergent component H x is related directly to the distribution of sources and sinks. Figure 3, taken from TRENBERTH and SOLOMON (1994), shows the divergent component of the net energy flux vector and its associated potential function for the month of January. The flow of energy between sources and sinks is clearly shown. Energy source regions are asso-
90N t ,
Jan 1988 , I ,
,
Total Div Energy Transport ~, ' , ' . ~ . ' . ' I .,., I.,
l_2,,~j..
~ o',',
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60N
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0
30E
60E
90E
""
' " -
120E
150E
180
150W
120W
90W
60W
30W
0
Fig. 3. The total energy flux and potential function for the month of January 1988 (from TRENBERTH
and SOLOMON,1994).
294
Large-scale dynamics ciated with the tropical oceans and with the summer hemisphere land masses in general whereas sink regions are associated with cold land and ocean regions particularly in the winter hemisphere. This distribution of sources and sinks is compatible with the expression for the source sink term above, where source regions should correspond to regions of positive surface heat flux and evaporation and sink regions should correspond to negative radiative flux contributions. The primary region of energy divergence is located in the heatsource region of the western Pacific. Energy divergence is also apparent over Brazil, equatorial Africa and along the ITCZ of the Indian Ocean. Centres of energy divergence are also evident just off the east coast of Asia and North America. Divergence in these regions is associated with the strong sensible and latent heat fluxes occurring in cyclogenetic areas over the relatively warm ocean currents. These findings are consistent with those of JOHNSON (1989) for the FGGE period. The divergent energy flux can be decomposed separately into its mean and transient parts. Figure 4 (from TRENBERTH and SOLOMON, 1994) shows the transient part of the divergent energy flux and the associated potential functions. The transient component of the divergent energy flux is an important part of this net energy flux. The transient mode of energy divergence shows a local dominance in extratropical latitudes whereas the stationary component (not shown) is more global in character. In the Northern Hemisphere, transient energy convergence tends to occur in the region of troughs in the mass stream function field (not shown) whereas transient energy divergence occurs over the ridges. In the Southern Hemisphere, the transient energy transport is generally convergent in a meridional belt extending from 45 to 70~ whereas the total transport is divergent over this region. Equatorward of this transient energy convergence belt is another nearly continuous belt of transient energy divergence which stretches from South America through the South Atlantic, across the Indian Ocean, Australia and the South Pacific. Throughout this systematic distribution of energy exchange in the baroclinic region of the Southern Hemisphere, the component of the transient energy transport is directed pole-
Jan 1988 90N
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Transient Div Energy Transport
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9 i ,
30W
, 0
Fig. 4. The transient component of the energy flux and potential function for the month of January 1988 (from TRENBERTHand SOLOMON,1994).
295
Dynamics of future climates ward whereas the stationary component (not shown) is directed equatorward. In the Northern Hemisphere between 30 and 60~
the poleward and equatorward meridional transports
by the two components have the same sense. However, there is substantial zonal variation of the pattern of energy exchange in association with the longwave structure in this winter hemisphere. JOHNSON (1989) has provided an explanation for the inverse relationship between the transient and stationary components of the energy divergence. Divergence of the total energy transport by geostrophic motion is primarily restricted to the advection of enthalpy. Consequently, for the middle latitudes of a hydrostatic atmosphere, to maintain the ratio of geopotential to internal energy, any increase in temperature in the lower troposphere through convergence of enthalpy transport requires a corresponding increase of geopotential energy in and above the level of transient enthalpy convergence. In turn, the adjustment to hydrostatic balance drives a divergent component of geopotential energy transport directed out of the region. This divergence of energy transport is reflected as a stationary component of the energy transport because it occurs through the mass circulation. In regions of transient energy divergence in isobaric layers the stationary component of geopotential energy at upper levels is convergent.
Water vapour From the generalised time-averaged prototype budget equation of BOER (1982) (equation (6)) discussed in the section on Climate analysis, we can write the vertically integrated moisture budget equation as
So
1 0 pOflqdp+_V, got g1
flqVdp=E-P
(28)
The vertically integrated flux vector for moisture is often termed the "aerial run-off" and is conventionally written as Q _ 1
g
So o flqV dp
The total amount of water vapour is conventionally written as
g
So~flq dp
so that the more usual form of the moisture budget equation emerges
OW Ot
~+V.Q
= E-P
(29)
Decomposition of modes of transport of the aerial run-off into mean, eddy, rotational and divergent components follows naturally using the formalism presented in the section on Climate analysis. Analyses of the aerial run-off in order to gain a better understanding of the mechanisms involved in the maintenance of the local atmospheric water vapour content have been limited. Because of severe data limitations, PEIX6TO and OORT (1983, 1992) concentrated on zon-
296
Large-scale dynamics 90N
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Fig. 5. The global distribution of the annual mean aerial run-off determined by PEIXOTOand OORT (1983) together with corresponding stream lines. Each barb represents 2 g kg-i m s-1.
ally averaged distributions of water vapour transport although as shown in Fig. 5, they were able to deduce global distributions of the mean aerial run-off which support reasonable expectations regarding the sources and sinks of moisture. Using global data assimilation analyses for a single year (FGGE), CHEN (1985) found that the stationary non-divergent mode shown in Fig. 6(a) describes most of the total water vapour transport. The stationary divergent mode composed of a combination of local Hadley circulation and the local Walker circulation, is responsible for the maintenance of high regional values of the water vapour content in equatorial regions. In mid-latitudes, the transient divergent mode shown in Fig. 6(b) is an important component of the poleward transient water vapour transport in the storm tracks. Problems associated with difficulties in moisture analysis, especially over the Southern Oceans, suggest some caution is necessary in assessing the reliability of these computations of water vapour transport. Further analysis is needed over a longer time period. It is interesting, however, to note that many of the models used in AMIP show quite large interannual variations in the stationary divergent mode of water vapour transport in the tropics which is strongly linked to the E1 Nifio-Southern Oscillation (ENSO). An example from the BMRC model is shown in Fig. 7. Large
scale
interactions
Teleconnections across the globe are a fundamental component of the climate system. Canonical examples include the ENSO phenomenon (PHILANDER, 1983, 1990); the PacificNorth American (PNA) pattern (HOREL and WALLACE, 1981; HOSKiNS and KAROLY, 1981; WALLACE and GUTZLER, 1981) and the Madden Julian Oscillation (MADDEN and JULIAN,
297
Dynamics
of future
climates
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EQ 30S 60S MAX VECTO~ ~o~"~-m!'Ims I Fig. 6. (a) T h e stationary n o n - d i v e r g e n t c o m p o n e n t o f the aerial r u n - o f f for D e c e m b e r - F e b r u a r y 1979 d e t e r m i n e d b y CHEN ( 1 9 8 5 ) the units o f the plotted vectors are k g m -1 s -1 and the m a x i m u m p o s s i b l e v e c t o r is 2 0 0 k g -1 s - l ; (b) the transient d i v e r g e n t m o d e o f the aerial run-off, the units are k g m -1 s -1 and the m a x i m u m p o s s i b l e vector is 2 00 k g m -1 s -1.
1972). Recent reviews of these mechanisms may be found in WEBSTER and CHANG (1988), and SARDESHMUKHand HOSKINS (1988). Simplified dynamical modelling studies have indicated that substantial Rossby wave interaction between the tropics and extratropics should be restricted to regions of westerly flow extending from the mid-latitudes well into the tropics ( W E B S T E R and H O L T O N , 1982; Z H A N G and W E B S T E R , 1991). Using cross-correlation techniques, K I L A D I S a n d W E I C K M A N (1992) have showed that, in the boreal winter, the tropical upper tropospheric westerly flow over the central and eastern Pacific and over the Atlantic is associated with frequent wave activity propagation from the extratropics into low latitudes. The two dimensional quasi-vector E of HOSKINS (1983) defined as E - ( v '2
298
p - - U t 2 ) I - - U
p~, V
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Large-scale dynamics
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-4o
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-120
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0
Fig. 7. The anomalous transient potential function and its associated anomalous transient divergent flow, of the aerial run-off for the period December 1982 to February 1983 as simulated by the Australian Bureau of Meteorology Research Centre AGCM. The contour interval is 20 kg m-1 s-1 with negative contours dashed. The maximum possible vector length is 10 kg m-1 s-1.
is a convenient method of displaying the anisotropy and group velocity associated with transient eddies. A westerly E vector indicates meridionally elongated eddies propagating eastward relative to the mean flow whilst an easterly E vector indicates zonally elongated eddies propagating westward relative to the mean flow. A divergent pattern of E vectors indicates a westerly acceleration of the time mean flow by the transient eddies whilst a convergent pattern of E vectors indicates an easterly acceleration. KILADIS and FELDSTEIN (1994) show convincing evidence of wave activity propagation from the E vectors derived from time filtered observational fields. Figure 8, taken from KILADIS and FELDSTEIN (1994) shows the January mean time-filtered 200 hPa E vectors computed from NMC, Washington global assimilation data for the years 1987-1991. In the observations there are two active regions, one showing eastward propagation from the area slightly poleward of the Asian jet towards North America and the other southeastward into the tropical eastern Pacific. There is convergence of the vectors in the area of the intertropical convergence zone (ITCZ) which is strongest at about 160~
10~
This region with convergence of E vectors implies that
the eddies are decelerating the local (westerly) mean zonal wind. SARDESHMUKH and HOSKINS (1988) have considered a formulation of the one-level vorticity equation that gives some insight into the connection between the upper level divergence associated with tropical convection and the remote stream function response in the midlatitude circulation. They define a Rossby wave source term as (see equation (17)) S---V
X
.V~a - ~ a V ' V
-- -V" (Vz~a)
(30)
where Vx represents the divergent component of the horizontal wind vector V and ~a is the absolute vorticity. This Rossby wave source is balanced by the term V~'V~a which represents the advection of absolute vorticity by the rotational component of the flow.
299
Dynamics offuture climates
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Fig. 8. The January mean time-filtered (fluctuations less than 14 days) 200 hPa Eliassen-Palm flux vectors computed from the NMC, Washington analyses for 1987-1991. The contours (contour interval of 10 m s-1) represent the mean zonal wind with negative contours dashed, the longest vectors represent 100 m2 s-2 (taken from KILADISand FELDSTEZN,1994). Using NMC analyses at 200 hPa for the period 1986-1989, Mo and RASMUSSON (1993) have calculated the Rossby wave vorticity source and have shown the advection of absolute vorticity by the divergent local Hadley circulations into the austral winter hemisphere from three major boreal summer hemisphere regimes of convection (Africa, central South America and the Indian monsoon). Figure 9 (taken from Mo and RASMUSSON, 1993) shows that the Rossby wave source term is relatively small in the tropics but relatively large in the subtropical summer hemisphere in regions where convection is active. These source regions are then connected to the winter hemisphere by the divergent Hadley circulation. Using the output from the BMRC AMIP simulation. FRASER (1994) has demonstated that a modern atmospheric general cirulation model can produce a quite credible simulation of the mean Rossby wave source. Figure 10 (which should be compared to Fig. 9) illustrates the main features of the observed geographical distribution in the Rossby wave are well captured by the BMRC simulation.
Regional-scale interactions Whilst reasonably consistent results are being obtained for future climates by integration of current climate models, considerable uncertainty exists on the regional scale responses. The uncertainty partially evolves from the poor resolution and physical parametrizations in current models (see section on Climate models), but there are also substantial unknowns and valid questions on what constitutes the full range of scale interactions that lead to regional-
300
Regional-scale interactions
9
60N
If
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Fig. 9. The mean January-February-March Rossby wave source term deduced from the NMC, Washington 200 hPa analyses from 1987-1989. The contour interval is 6 x 10-11 s-2 and negative contours are dashed (taken from RASMUSSON and Mo, 1993). scale climate. Whilst a full debate on this topic is beyond the scope of this chapter, we illustrate some of the problems by way of a discussion of the synoptic climatology of storm tracks and a brief s u m m a r y of the interactions that contribute to maintenance of the s u m m e r m o n s o o n circulation in the western North Pacific. AMIP R31 KU0 -180
-
ENSEMBLE MEAN DJF ( 8 0 - 8 7 ) ROSSBY S 2 0 0 h P a
-1120
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-60
o I=
-90
-180
-120
-60
0
60
120
180
-90
Contour f r o m - 4 8 0 to 600 by 60 (x 10 -12)
Fig. 10. The mean of the Rossby wave source at 200 hPa for December-January-February for 19801987 from the Australian Bureau of Meteorology Research Centre AMIP experiment. The contour interval is 60 x 10-12 s-2 and negative contours are dashed. Negative areas are also shaded.
301
Dynamics offuture climates Storm tracks
The synoptic climatology of storms, cyclone and anticyclone tracks, fronts and "storm tracks" (i.e. regions of maximum variance in geopotential at synoptic time scales less than a week) are important components of climate, especially because of their social and economic impacts on affected populations. The interesting "weather" experienced in mid-latitudes is primarily associated with "storminess" due to the passage of cyclones, anticyclones and their accompanying fronts. The usual interpretation of such systems is that they are a manifestation of the conversion of the potential energy associated with the north-south temperature gradient into the energy of atmospheric eddies through the process of baroclinic instability. The more traditional synoptic approach of "storm track" analysis usually only considers the low centres when individual "storms" are tracked (e.g. MURRAY and SIMMONDS, 1991; KONIG et al., 1993). As TRENBERTH (1991a) argues, it is probably more meaningful to include both highs and lows since "weather" events are associated not only with the approach of low pressure systems but also with the withdrawal of high pressure systems. WALLACEet al. (1988) present a good summary of the relationships between traditional indicators of storm activity (tracks of cyclones and anticyclones) and the distribution of time-filtered geopotential height. Figure 11, from TRENBERTH (1991a), illustrates the link between the storm track and the mean flow through the polar jet streams; Figure 11 (a) shows the zonal mean of the standard deviation of the geopotential height at 300 hPa as a direct measure of the storm track activity over the annual cycle, Fig. 1 l(b) shows the zonal average of the zonal wind at 300 hPa to illustrate the annual cycle of the subtropical and polar jet streams and Fig. 11 (c) shows the meridional gradient of temperature at 700 hPa as a direct measure of baroclinicity in the lower troposphere. One of the most striking things about storm track activity is the persistent storminess in the Southern Hemisphere throughout the year compared to the Northern Hemisphere where the storminess shows a considerable seasonal variation in both intensity and location. The local meridional temperature gradient is a reasonable indicator of the location and strength of the storm track. There is also a strong relationship between the storm track and the major tropospheric jet streams. In the Southern Hemisphere, there is a noticeable semiannual variation with a slight shift of the polar jet and the storm tracks towards the pole during the transition seasons and is most probably related to the existence of the strong heat sink of Antarctica. TRENBERTH (1991a) has demonstrated that the observed relationships amongst bandpass filtered eddy quantities can be understood in terms of geostrophic theory and perturbation analysis applied to baroclinic systems. A detailed study of the interannual variability of storm tracks and relations with the mean flow must await the emergence of global data from data assimilation "re-analysis projects". However, since large interannual variations in the mean flow are well documented and these variations have a profound influence on high frequency storms, it is to be expected that there will be significant interannual variations in storm tracks. TRENBERTH (1991a) has also investigated the question of the impact of the storm track eddies on the mean flow itself using a localised Eliassen-Palm flux. He finds that baroclinic effects from the poleward heat flux dominate in winter and the eddies act so as to decelerate the mean westerlies in the upper troposphere. The barotropic effect due to the flux convergence of meridional momentum contributes to the maintenance of the mean
302
Regional-scale interactions
90N
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9
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m
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JAN FEB MAR APR MAY JUN
.-..
4
JUL AUG SEP OCT NOV DEC JAN Month
U Zonal Average 1979-1989 =t 500 mo
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/
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905 JAN
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Fig. 11. The seasonal variation in monthly mean zonal means for the years 1979-1989 from ECMWF analyses. (a) Time filtered zonal average of the standard deviation in 300 hPa geopotential, contour interval 10 m, values greater than 80 m are stippled; (b) zonal mean of the zonal component of the wind at 300 hPa, contour interval 5 m s-1, values greater than 25 m s-1 are stippled and negative values (easterlies) are dashed; (c) meridional temperature gradient at 700 hPa, contour interval 2 x 106 K m -1, magnitudes grater than 6 x 10 -6 K m -1 are stippled and negative values are dashed ( f r o m TRENBERTH, 1991).
303
Dynamics offuture climates westerlies by accelerating the main polar jet in the upper troposphere. The role of eddy-induced diabatic heating in offsetting the effects of eddies on the mean flow is not resolved. HOSKINS and VALDES (1990) and HALL et al. (1994) have related the storm tracks to the baroclinicity of the mean flow and have also gone on to show how the mean equator-to-pole temperature gradient which is producing the baroclinicity can be maintained by local eddyinduced diabatic heating despite its continual erosion by the baroclinic instability process itself. S u m m e r monsoon circulation in the western North Pacific
A regular feature of the western North Pacific is the presence of a summer-monsoon circulation with a monsoon trough and a broad belt of equatorial westerly flow extending eastwards several thousand kilometres from the Asian subcontinent (Fig. 12). This circulation lies between broad low level easterlies in the central Pacific and westerlies associated with the Asian monsoon and is noted for its stable nature once established (TANAKA, 1992; HOLLAND, 1994). It is an active region of extratropical interaction, lying at the western end of the Pacific subtropical-storm track identified in the previous section, and in a region of regular subtropical transition by intense tropical cyclones. Whilst the convection has a transitory nature, it is located for sufficient time to have an impact by the non-linear rotational-flow response discussed by SARDESHMUKH and HOSKINS (1988) and is the origin of the Pacific-North American (PNA) teleconnection (HOREL and WALLACE, 1981; HOSKINS
)
) SUBTROPICAL
ASIAN MONSOON
~/ i \ DEPRESSION /
_
PACIFIC EASTERUES
Fig. 12. Schematic of the major lower-tropospheric components of the western North Pacific summer monsoon. Diabatic heating by moist convection is maintained in the confluence zone east of the monsoon depression and, in turn maintains the overall flow pattern. Complex scale interactions also occur and lead to development of tropical cyclones.
304
Regional-scale interactions and KAROLY, 1981). The region also is west of the major, upper-tropospheric accumulation zone of wave energy identified by WEBSTER and CHANG (1988) and directly in a potential lower-tropospheric accumulation region. HOLLAND (1994) describes the establishment of the monsoon as a result of enhanced convection over the warm western Pacific Ocean. The convective region provides a Rossbywave response at the scale of the Rossby deformation radius (section on Diabatic heating). The non-linear phase propagation in the lower troposphere is poleward and westward (e.g. FIORINO and ELSBERRY, 1989) so that a well-defined monsoon gyre is established to the northwest of the region of enhanced cloudiness. Rossby waves at this scale also have strong eastward group speed (GILL, 1982). The associated energy propagation develops the anticyclonic gyre northeast of the monsoon gyre and the equatorial eddy to the southeast. The response in the upper troposphere is similar, although of opposite sign and considerably more diffuse due to the processes discussed in the previous section. The confluence of the low-level flow east of the monsoon gyre enhances the potential for sustained moist convection in this region, thus leading to a stable feedback cycle and maintenance of the overall circulation (Fig. 2). This convective enhancement may arise from extratropical forcing, or eastward movement of a Madden Julian Oscillation (MJO1 MADDEN and JULIAN, 1972), both of which are within the capacity of climate models. However, it is highly likely that the convective organisation also is strongly influenced by interactions between gravity modes (YAMASAKI, 1984, 1988, 1989; MAPES, 1993), by coalescence of mesoscale complexes (SIMPSONet al., 1993) and by the development of long-lived mesoscale clusters identified for the vertical windshear conditions in this region by YAMASAKI (1984). Westward travelling Rossby modes, often referred to as easterly waves (REED and RECKER, 1971), can be expected to slow down and accumulate in the confluence zone (FARRELL and
WATTERSON, 1985; WEBSTER and CHANG, 1988; CHANG and WEBSTER, 1990). The result will be short-term enhancements of convection, which may produce one of the tropical cyclones that frequently develop in this region (BRIEGEL, 1993). HOLLAND (1994) further shows that phase locking between the energy dispersion from one tropical cyclone with subsequent easterly waves moving into the confluence region may substantially enhance the potential for secondary cyclone development several days later. Vortex-vortex interaction, which is known to be highly chaotic under many conditions occurs regularly in this region, indeed, interacting tropical cyclones were first identified here (FuJIWHARA, 1921). Recent studies have shown that this interaction is complex and highly non-linear (HOLLANDand DIETACHMAYER, 1993; LANDER and HOLLAND, 1993; RITCHIE and HOLLAND, 1993; WANG and HOLLAND, 1995). Mesoscale vortices can be expected to occur frequently in the vicinity of long-lived mesoscale convective clusters (RAYMONDand JIANG, 1990) and RITCHIE et al. (1993) have suggested that merger and growth of these vortices may be associated with formation of tropical cyclones in this region. HOLLAND and LANDER (1993) and WANG and HOLLAND (1995) also indicate that the movement and development of tropical cyclones may be substantially affected by the presence of other mesoscale vortices in their vicinity. Of considerable importance to climate conditions is the manner in which a small vortex may rapidly merge with the large monsoon gyre to produce a breakdown of the overall monsoon circulation (HOLLAND, 1994). The presence of tropical upper tropospheric troughs (TUTTS) (SADLER, 1978) provides an upper-tropospheric influ-
305
Dynamics offuture climates ence on the monsoon region that is considered to be of importance by forecasters in the region, but is poorly defined. Identifying future regional climates requires a consideration of scale interactions such as those identified in previous paragraphs. Of particular importance is the identification of stable processes and those that are likely to produce unstable conditions, which are inherently difficult to forecast adequately. Unfortunately, our detailed knowledge of the full range of interactions is still far from complete. Furthermore, current climate models are capable of capturing only some of the known mechanisms, other processes, such as mesoscale vortex interaction, being neglected. Special problems arise from the impact of convective and mesoscale processes on the larger scales. For these reasons, objective specification of future regional climates is not at present possible except in the most general and uncertain of terms.
Future climate dynamics We conclude this overview of climate dynamics by examining the potential changes that might occur in climate over the next millenium. Barring major catastrophes, such as an impact by a large extraterrestrial object (Chapter 4 by RAMPINO), we expect that the basic dynamics of future climates will be essentially the same as those described here for the current climate. For example, substantial changes should not be expected in the rotation rate of the Earth, the basic moist thermodynamics, the energy balance of solar warming at the equator and cooling at the poles, and the related baroclinic processes (but cf. Chapter 14 by PENG). As a result, the tropics will remain a region of significant moist convection, but with weak mass-wind balance and high dispersion of Rossby modes. Hadley and Walker circulations and equatorially trapped systems, such as the Madden-Julian Oscillation, will remain. Higher latitudes will continue to be dominated by baroclinic processes, with strong mass wind balance. The separation of scales, and resulting complex interaction between ocean and atmospheric processes, will continue as will the basic dynamics of interaction with both the ocean and land surfaces. Changes can be expected in the climate system response to the underlying dynamics, some of which will be subtle, others substantial. For example, significant changes in the composition of atmospheric gases and particulates will occur from both anthropogenic (e.g. CO2 emissions) and natural (e.g. changes to frequency of volcanic eruptions) causes (Chapters 9 by WANG et al. and Chapter 10 by ANDREAE); the distribution of the major land masses and orographical features and the magnitude of solar heating will evolve over millennia (cf. Chapter 3 by BARRON). The climate system response may be stable or it may involve positive feedback and evolution to a new, or substantially different climate. The types of climate that may result are difficult to predict, but we know that the climate has evolved through major cycles in the past and can be expected to continue to do so in the distant future (cf. Chapter 15 by KUMP and LOVELOCK). We draw on three examples of the types of detailed response that can occur to illustrate the complexity of future climate responses to subtle changes in the dynamical and thermodynamical balance and forcing. The linkage of the meridional temperature gradient to the extra-tropical atmospheric eddies that dominate the transport of heat and momentum is a fundamental part of tropospheric dy-
306
Future climate dynamics namics. From studies of baroclinic instability, any increase (reduction) in this temperature gradient should cause these eddies to grow (shrink) and the associated transport to increase (decrease). Many different Atmospheric General Circulation Models have been used to determine the equilibrium response of climate to a doubling of the CO2 concentration in the atmosphere. These models generally show a warming which is larger at high latitudes than at the equator (this effect is due primarily to the positive feedback from the overall retreat of snow and ice). Thus the pole to equator temperature gradient is weakened in both hemispheres and a change in the behaviour of baroclinic eddies is to be expected. However, the situation is made more complicated because the models all show an enhanced warming in the tropical upper troposphere (this is a consequence of the fact that warmer and moister air parcels lifted upwards from the surface have more latent heat to release in the upper troposphere) thus increasing the equator to pole temperature gradient in the upper troposphere. This behaviour is illustrated in Fig. 13 where the equilibrium response in annual mean temperature simulated by the Australian Bureau of Meteorology Research Centre (BMRC) Atmospheric General Circulation Model (AGCM) is shown (MCAVANEY et al., 1994). It is not clear whether the baroclinic eddies are more sensitive to the decreased lower tropospheric temperature gradient or the increased upper tropospheric temperature gradient. Further complications ensue if we consider the results from transient CO2 modelling experiments. In this case, most coupled ocean-atmosphere models show a very much reduced surface warming in the Southern Hemisphere due to oceanic mechanisms that promote cooling of the ocean in high southern latitudes (HOUGHTON et al., 1992; HELD, 1993), while the tropical upper
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troposphere is still warmed. This slightly modified behaviour is illustrated in Fig. 14 which shows the annual mean temperature response at the time of doubling in the transient CO2 increase experiment conducted by BMRC (POWER et al., 1993). This transient experiment, and other similar experiments conducted by other modelling groups, indicates that the response in the baroclinic eddies may be different between the two hemispheres in enhanced greenhouse conditions. HELD (1993) suggests, on the basis of linear instability theory, that the temperature gradient in the lower troposphere should dominate the response under greenhouse warming and hence eddies in the Northern Hemisphere should transport less energy while those in the Southern Hemisphere should transport more. However, as HELD (1993) points out, no definitive statement can be made since, even if the eddy transport of heat responds more to changes in the temperature gradient in the lower troposphere, it may be that the eddy transport of momentum is also sensitive to the gradient in the upper troposphere resulting in eddies with a larger fraction of their total energy in the middle and upper troposphere. Further complications arise due to consideration of the role of moist processes in conjunction with the growth and decay of the baroclinic eddies. Any warming of the atmosphere will tend to increase the moisture holding capacity in the eddies. The intensity of the resulting storms will depend on the balance between the competing effects of direct enhancement of the energy of eddies by latent heat release versus the determination of the size and strength of the eddies through the balance between the poleward transport of energy by the eddies and the gradient in the heating (HELD, 1993). Much further work is required before a more complete
308
Future climate dynamics understanding of what controls the size and strength of the eddies in mid-latitudes. A further issue that requires further study is the relationship between the cloud field that is associated with regions of high eddy activity and the temperature gradient which is responsible for their formation. Consideration of potential changes in the distribution of the rainfall associated with a movement of mid-latitude depressions is also of great importance since in most regions much of the rain falls from the equatorward edge of these depressions. The way in which the latitudinal distribution of eddy activity is affected by changes in the horizontal temperature gradient is not clear. Preferred regions for the growth and decay of depressions exist through zonal asymmetries of the large scale temperature and flow fields. These asymmetries arise in turn from major asymmetries in the lower boundary either through topographic features or contrasts between the heating over land compared to an adjacent ocean. Linear stability analyses of realistic planetary scale flows (e.g. FREDERIKSEN, 1985) and sensitivity studies with AGCMs are gradually leading to a better understanding of the factors which control the location of the tracks of depressions. However, because of the fundamental non-linearities involved, it is very difficult to predict how the dominant planetary-wave pattern and associated storm tracks might change in response to a given change in forcing. The potential changes in the circulation of the Atlantic Ocean due to changes in freshwater input at high latitudes are discussed in Chapter 14 by PENG. The stability of North Atlantic deep water formation and the possibility of different modes of oceanic circulation have been the subject of much recent research using ocean only models. In most of these studies, feedback mechanisms involving salinity operate. The robustness of distinct climatic ocean states remains to be fully explored with three-dimensional coupled ocean-atmosphere models. However, in the context of global warming, it is possible that, with higher temperatures, a modest freshening of high latitude waters is possible due to increased moisture convergence producing enhanced excess of precipitation over evaporation (a requirement of moisture balance). Any freshening of polar water would weaken vertical overturning in the ocean and thereby increase the time that the surface waters were exposed to the freshening, reducing the overturning still further. Such a weakening in the overturning is found in many coupled ocean-atmosphere experiments. Whether an irreversible transition to a state where there is no deep-water formation will occur remains an open question. Extensive public discussion on climatic changes to severe weather systems, such as hail storms, mid-latitude wind storms and tropical cyclones have engendered much debate because of the potentially catastrophic consequences to the global insurance industry and economies of individual countries. Much of the discussion is conjectural as it is difficult to consider regional-scale changes let alone changes in very rare severe weather events, for which there is often not even suitable records available for current climate (HOLLAND, 1981; NICHOLLS, 1992). We therefore examine the potential for changes associated with tropical cyclones, as an example of the problems and solutions to be applied. Some studies have shown skill in climate model predictions of systems that have some of the large-scale characteristics of tropical cyclones (BENGTSSENet al., 1994). However, we have shown that tropical cyclone development is fundamentally linked to complex scaleinteraction processes at the regional scale. Since these scale interactions cannot be confidently predicted in future climate scenarios, and since climate models cannot resolve the cyclone core and actual intensity, we need to utilise some other measure for estimating cli-
309
Dynamics of future climates
mate changes. Whilst there are some creative attempts at applying climatic indices to model fields (e.g. RYAN et al., 1992), most methods have relied on application of thermodynamic approximations, such as by EMANUEL (1988) to tropical cyclones or to extrapolating current SST relationships (GRAY, 1968) to changes in ocean temperatures. These methods were investigated in a review paper by LIGHTHILL et al. (1994), who concluded that there were no consistent statistical relationships between cyclone numbers and SST changes. For example the study of E1 Nifio effects by HOLLAND et al. (1988) showed that the direct effects of SST changes were negligible and that it was the subtle circulation changes, and scale interactions that were responsible for any observed relationship. A careful study by LANDSEA and GRAY (1994) also found no relationship between the proportion of intense cyclones and surface temperature anomalies over the entire northern hemisphere. The thermodynamic model predictions of maximum potential intensity (EMANUEL, 1987) indicate quite strong sensitivity to small ocean changes at the very intense cyclone stage. The observational evidence for such changes is equivocal, with some conclusions of no change (EVANS, 1993) and other evidence of some change (DEMARIA and KAPLAN, 1994), albeit with less amplitude than predicted from purely thermodynamic considerations. Other theoretical studies of the impact of spray and ocean energy transfers (FAIRALL et al., 1994) indicates that there may be counteracting processes occurring for extreme cyclones. The best conclusion for future climates is that the regional characteristics can be expected to change in manners that are difficult to predict with current knowledge and techniques. We support the conclusions by LIGHTHILL et al. (1994), that SST changes of a few degrees will have negligible direct effect on tropical cyclones. Any small changes in cyclones are likely to be difficult to ascertain above the high natural variablity that occurs. However, substantial indirect changes in tropical cyclones at a regional level can be expected, and have been observed over recent decades. These changes arise from readjustments in the regional response to the global climate system.
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314
Chapter 9
The greenhouse effect of trace gases WEI-CHYUNG WANG, MICHAEL P. DUDEK AND XIN-ZHONG LIANG
Introduction The impact of humans on the atmosphere is now widely recognized: the enhanced greenhouse effect resulting from emissions of CO2 and other gases, such as CH 4, CFCs and N20 and the observed 03 depletion in the lower stratosphere and increase in the upper troposphere in the middle to high latitude of the Northern Hemisphere are two important features. This chapter discusses the enhanced greenhouse effect associated with increasing greenhouse gases with focus on the potential climate change in the next few decades. The first section provides a description of the factors related to the greenhouse effect and the approaches to assess the climatic effects. The following section summarizes the studies of the greenhouse effect due to the projected increases of uniformly mixed gases CO2, CH4, CFCs and N20. Then model simulations of the climatic effect due to observed lower stratospheric 03 depletion during the last few decades are presented and the radiative forcing due to tropospheric 03 increase is described. A brief summary and discussion about future greenhouse effect is given. Extensive documentation about the greenhouse effect can be found in HOUGHTON et al. (1990, 1992), WMO (1991, 1994) and also in this book (e.g. Chapter 2 by BERGER; Chapter 10 by ANDREAE; Chapter 11 by BRASSEUR et al.).
The greenhouse effect The Sun provides the Earth's only external source of heat, the solar radiation in the visible and near-infrared spectra. The Earth also radiates energy back into space and, because of a much colder temperature than the Sun, the energy is in the form of infrared radiation. A balance between solar radiation and infrared radiation yields the mean temperature of the Earth, about-18~ The thermal structure of the atmosphere of the Earth is influenced by the presence of trace gases, which modulate the solar radiation and thermal emission. The principal gaseous absorbers of solar radiation are water vapour (H20) in the troposphere and ozone (03) in the stratosphere. H20 absorbs primarily in the near-infrared spectral region while 03 is most effective in the ultraviolet and visual regions. About 100 W m -2 of the 340 W m -2 incident solar radiation at the top of the atmosphere are reflected back to space mainly by clouds and surface while about 80 W m -2 are absorbed by the atmosphere and the rest absorbed by the surface. In the infrared, H20 effectively blocks thermal emission from the surface except for the "window" region between 7 and 12/~m where CO2, 03, CH4, CFCs and N20 with strong ab-
317
The greenhouse effect of trace gases
G(Wm -z)
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(April; Global Ocean) 300
(1987,total)
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200
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/ ,
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Fig. 1. The greenhouse effect, G (W m-2), as a function of sea surface temperature for clear and total (mixed clear and cloudy) sky conditions derived from Earth Radiation Budget measurements. Values of G, calculated by subtracting the outgoing longwave radiation at the top of the atmosphere from the sea surface blackbody emission, reflect the trapping of the longwave radiation by atmospheric gases and clouds.
sorption bands contribute additional atmospheric opacity. Absorption of the outgoing thermal radiation in the atmosphere, followed by re-radiation at local temperature can lead to an increase of the surface temperature, the so-called greenhouse effect (MANABE and STRICKLER, 1964; RAMANATHAN, 1975, 1988; WANG et al., 1976, 1986; HANSEN and LACIS, 1990). Fig. 1 shows the outgoing longwave radiation at the top of the atmosphere measured by the Earth Radiation Budget satellite. Clearly, the atmospheric gases can trap up to 100-200 W m -2 of longwave radiation, thus keeping the global mean surface air temperature at a habitable 15~
The 1990 annual mean concentrations for these gases are shown in
Table I. It should be pointed out here that, because of the different absorption characteristics, different gases absorb and trap infrared radiation from the surface at different levels of efficiency; for example, on a per molecule basis, CFzC12 has the same effect as about 25,000
318
Introduction
TABLE I CONCENTRATIONS OF WELL-MIXEDGREENHOUSEGASES (AFTER HOUGHTON ET AL., 1990)
Gas
Pre-industrial
1980
1990
Present rate(%)
2050a
CO2 CH4 N20 CFC13 CF2C12
280 0.8 288 0 0
337 1.57 302 173 295
354 1.72 310 284 485
0.5 0.9 0.25 4 4
539 3.24 369 546 1070
Concentration is ppmv (parts per million by volume) for CO2 and CH4, ppb(billion)v for N20 and ppt(trillion)v for CFC13 and CF2C12. alPCC Business-as-Usual scenario (SA90) is used here.
CO 2
molecules. Consequently, despite the small concentration of CF2C12 in the atmosphere,
its effect on infrared radiation is quite substantial. The presence of clouds will further increase the magnitude of the trapping of longwave radiation, about 30 W m -2 on the global mean basis. Note however that, in contrast to the greenhouse gases which warm the climate, clouds also reflect large amounts of solar radiation, about 48 W m -2 and thus cause a net cooling of the climate system (RAMANATHAN et al., 1989; CESS et al., 1992). Consequently, the present inadequate understanding of cloud and its response during climate change are believed to cause large uncertainty in model prediction of the enhanced greenhouse effect. In the last 160,000 years the magnitude of mean temperature variations has been deduced from Antarctic ice cores to be about 6~
The temperature fluctuation correlates very well
with the variations of the CH 4 and CO2 concentrations derived from the air trapped in the Antarctic ice core, suggesting some linkage between the surface temperature and concentrations of these gases (HOUGHTON et al., 1990; see also Chapter 2 by BERGER). The current concern over global warming is related to the following three areas of observations. First, the greenhouse gases of CO2, CH4, CFCs and N20 have been increasing over the past few decades and the trend of increase is most likely to continue. In addition, recent findings suggest that depletion of 03 caused by the presence of CFCs is occurring in the lower stratosphere in the middle and high latitudes (WMO, 1991; MCCORMICK et al., 1992) and that tropospheric 03 may be increasing through increased amounts of 03 precursor gases (CO, NOx and hydrocarbons; ISAKSEN, 1988; FISHMAN, 1991; THOMPSON, 1992). Changes in 03 vertical distribution can perturb the solar and longwave radiative forcing with subsequent climatic implications (WANG et al., 1980; LACIS et al., 1990; RAMASWAMY et al., 1992; MOHNEN et al., 1993; WANG et al., 1993; HAUGLUSTAINEet al., 1994). Second, the global mean surface air temperature has increased by 0.3-0.6~ over the past 100 years (see HOUGHTON et al., 1992). Third, the observed surface warming and lower stratospheric cooling are broadly consistent with model simulations (HOUGHTON et al., 1992; MILLER et al., 1992; MCCORMICK and HOOD, 1994). However, large uncertainties exist about the future surface warming effect especially about the regional climate changes because of the inadequate understanding of the climate feedbacks due to clouds and oceans and the physical and chemical processes affecting O3.
319
The greenhouse effect of trace gases
Radiative forcing The climatic effects due to increasing atmospheric greenhouse gases CO2, CH4, CFCs and N20, and changes of atmospheric 03, are initiated by a perturbation to the radiation energy balance of the Earth-atmosphere climate system, the radiative forcing, and subsequently affected by climate feedbacks such as due to changes in moisture and clouds in response to the radiation energy perturbation (HOUGHTON et al., 1990). Because of the strong dynamical coupling between the troposphere and surface, the radiative forcing of the climate system is generally defined as the net solar and longwave radiation flux at the tropopause, with altitude at 16 km in the tropics to around 8 km at high latitudes during winter. Given a temperature distribution, the radiative forcing depends on the concentration change and the absorption characteristics of the constituents; both are reasonably known. Therefore, uncertainties associated with model calculated radiative forcing are much smaller than the climate feedbacks which involve complex interactions between dynamics, physics and chemistry of the climate system. Because the stratospheric temperature will most likely be affected by changes in 03 through changes in absorption of solar radiation and by the increase of CO2 through enhanced longwave radiative cooling, two approaches have been used to calculate the radiative forcing: the first uses fixed-temperature treatment and the second uses adjusted-temperature according to an assumption of fixed-dynamical heating. The first provides the instantaneous perturbation to the radiative forcing due to increases of gas concentration while the second gives the forcing allowing for the rapid adjustment of stratospheric temperature. Fixeddynamical heating means the heating due to large-scale dynamics remains unchanged when climate is perturbed by changes in the concentration of greenhouse gases. Because of the decreases of lower stratospheric temperature in response to local 03 depletion (see Chapter 11 by BRASSEUR et al.) and increases of CO2, the second approach will include a contribution to changes in longwave radiative forcing associated with temperature changes; the contribution is calculated to be a negative radiative forcing and the magnitude is particularly large for 03 depletion (WMO, 1991; RAMASWAMYet al., 1992; WANG et al., 1993). The radiative forcing has been used to rank the relative importance of the greenhouse effects between CO2 and other gases mainly because earlier model studies have indicated that, for a number of forcing mechanisms, the linear relationship between the global-mean radiative forcing and global mean surface temperature change is relatively unaffected by the nature of the forcing (e.g. solar constant changes versus increases of CO2 (HOUGHTONet al., 1992); for example, a doubling of the pre-industrial CO2 concentration is calculated to provide radiative forcing of about 4 W m-2. However, the adequacy of radiative forcing for application to atmospheric 03 and sulphate aerosols has recently been questioned because these two constituents are highly variable both horizontally and vertically and thus may induce different global climate responses than the greenhouse gases which are more uniformly distributed. Consequently, the global mean radiative forcing should be used with caution.
Approaches for studying climate change Study of the climatic effect due to increasing greenhouse gases is largely done through the use of general circulation models (GCMs), which are based on the numerical solution of the
320
Introduction fundamental equations governing the dynamical and physical processes of the Earthatmosphere climate system. It is believed that GCMs are the best scientific tools available to understand the climate system and to assess future global climate change due to the greenhouse effect (HOUGHTON et al., 1990, 1992). Recent studies indicate that the GCMs have the skill of simulating the observed large-scale climate features, such as tropical interannual variability (ENSO-like events) and large-scale tele-connection patterns. Comprehensive model-observation comparisons have also been conducted for NCAR community climate models (HURRELL et al., 1993) and among a variety of GCMs (GATES, 1992) for identifying and understanding the model deficiency. As documented in HOUGHTON et al. (1992), continued GCM improvement is actively underway, in particular in model resolution and physical parameterizations. Two types of GCMs have been used to study the climatic effects of increasing atmospheric greenhouse gases: the first type is an atmospheric GCM (AGCM) coupled with a mixedlayer ocean, while the second type is based on an AOGCM which couples an AGCM with an oceanic GCM (OGCM). So far, the available GCM climate simulations of the greenhouse effect have been obtained using either the first type to study the equilibrium climate responses between 1 and 2 times pre-industrial CO2 concentration or the second type to study the transient climate response based on a 1%/year increase in CO2; for the transient experiments, about half of the 1%/year increase in CO2 was used as a surrogate to mimic the radiative effects of CH 4, N20 and CFCs. In AGCM with a mixed-layer ocean, the horizontal and/or vertical transports of heat and salt are prescribed from climatology and therefore they were not allowed to change in response to a climate change (see HOUGHTON et al., 1990). On the other hand, the AOGCM allows the simulation of the effects of increased CO2 on ocean circulation and the storage of heat in the deep ocean which have been found to be important in climate simulations (GATES et al., 1993). In recent years, concerns have been focused on the assessment of regional climate changes, and the effect and policy implications on the social and economic activities; for example, these latter issues are being addressed by the Intergovernmental Panel on Climate Change (IPCC). To do this will demand developing the capability for regional climate simulations. However, because of the coarse grid size of the order of 5 x 104 km 2 and larger in current GCMs, the information cannot be used directly for regional impact study which requires much higher resolution of the order of 103 km 2. GIORGI and MEARNS (1991) have reviewed the approaches to the simulation of regional climate change. Three broad categories were generally adopted for construction of future regional climate change scenarios: (1) purely empirical approaches using available instrumental and paleoclimate data; (2) semi-empirical approaches using GCM simulated largescale climate change together with the empirically derived information; and (3) modelling approaches using high spatial resolution. The first two categories have the advantage of less computational effort, but are limited by the empiricism and by the data quality. The third category is physically based but computationally heavy especially for uniform high resolution GCMs; although the approach of a nested GCM-limited area model in which the GCM simulations are inputted onto limited area models as a boundary condition shows promising results (see Chapter B of HOUGHTON et al., 1992; MCGREGOR and WALSH, 1993), there still exists theoretical problems such as feedbacks between the regional climate and the largescale climate are not included.
321
The greenhouse effect of trace gases Uniformly mixed gases Emission and concentration of recent years
Atmospheric CO2, CH4, N20, CFC13 and CF2C12, because of their long life times in the atmosphere, are uniformly mixed in the troposphere; their corresponding 1990 annual mean concentrations, as indicated in Table I, are 354 ppmv, 1.72 ppmv, 310 ppbv, 284 pptv and 485 pptv, respectively. These values are much larger than the levels of the pre-industrial period. The recent observed rate of growth for these gases is large, particularly for CFCs, about 4%/year (WMO, 1991). CO2 is exchanged naturally between huge reservoirs of carbon in the atmosphere, oceans, and the living world. The trend of increase directly observed since 1958 onwards can be attributed, at least in part, to industrial emissions. However, interactions between the atmosphere, the ocean, especially the upper layers and the terrestrial biosphere (including vegetation, and soils), must be considered to explain the observed changes; for example, the loss of tropical forests may have contributed significantly to the observed increases (cf. Chapter 12 by HENDERSON-SELLERS). Active carbon cycle modelling is on-going to study the changes in atmospheric CO2 resulting from the interplay of relatively small imbalances in large natural fluxes, and the large anthropogenic injection of CO2. One critical issue is the difficulty of defining a single lifetime to account for the sources and sinks for CO2 with response times ranging from a few years to millennial. CH 4 is emitted by a large number of natural sources (wetlands, termites and oceans) and anthropogenic sources (fossil fuel related activities, waste disposal, biomass burning and rice paddies). The removal of atmospheric CH 4 involves mainly reaction with OH and to a lesser extent the microbial uptake in soils. Atmospheric CH 4 has changed considerably over time. The ice core data showed a factor of two increase over the last two centuries. During the past decade, the rate of increase is declining, particularly in the last few years. Recent observations show that the trend of increase appears to be much smaller for CH 4, about 4.7 ppbv during 1992 which is significantly smaller than the value of 17 ppbv in 1990 (DLUGOKENCKY et al., 1994). The most likely explanation for the decrease in growth is a change in anthropogenic sources such as fossil fuel exploitation. In any case, the decreasing trend for CH 4, if continued, will have significant implications for future climate. N20 is emitted predominantly by biological sources in soils and water; most of them are small and therefore difficult to evaluate. The major sink is photodissociation by sunlight of wavelengths 180-230 nm in the stratosphere. The observed increase is thought to come from fossil fuel consumption and from agriculture. CFCs are human-made compounds containing chlorine, fluorine and carbon and are used as aerosol propellants, as refrigerants and insulators. Because of the long lifetime in the atmosphere, the observed growth rate of about 4%/year during the past few years will continue. The total anthropogenically released surface emissions of the greenhouse gases have recently documented by SUBAK et al. (1993) and Table II shows the emissions according to the individual regions. The total annual CO2 emission is about 6.4 billion tons of which the United States contributes about 20%. On the other hand, almost 15% of the total CH 4 emission, 0.35 billion tons, is attributed to China, partly due to the emissions from the rice paddies. The numbers for N20, CFC13 and CF2C12 are relatively small, but their climatic effects
322
Uniformly mixed gases TABLE II TOTALGREENHOUSEGASEMISSIONS(AFTERSUBAKET AL., 1993)a Region
CO 2 (kt C)
CH4 (kt)
N20 (kt)
CFC13 (kt)
CF2C12 (kt)
North America Canada USA. Europe CIS (formerly USSR) Centrally Planned Asia China South and East Asia Hong Kong Taiwan Middle East Africa Latin America JANZ (Australia, Japan, New Zealand) Total
1,277,925 32,250 1,245,675 1,192,206 829,486 577,290 494,048 791,473 10,942 28,312 183,009 445,210 795,817 339,446
38,357 3,218 32,739 38,025 33,350 60,655 52,396 90,484 91 617 6,237 33,642 40,722 10,925
901 37 756 381 260 299 228 399 3 8 80 596 749 119
69.6 4.2 65.4 123.9 22.5 3.1 2.0 17.6 0.2 0.6 2.8 17.1 11.0 22.9
101.2 6.1 95.1 115.9 47.5 7.1 5.8 19.7 0.2 0.5 3.3 16.1 15.4 33.8
6,431,861
352,398
3,783
290.6
359.9
5.8-8.8 X 106 5.5-6.5 • 106 5.95 x 106 (6.19 x 106)
215-550 • 103
0.9-7.7 • 103 314.5 (188.3)
392.8 (271.6)
HOUGHTONet al. (1990) HOUGHTONet al. (1992) ORNLb
aData are mainly based on the 1988 information. bThe estimates are based on 1988 information while the 1991 values are specified in parentheses (T. BODEN, 1993, personal communication).
are not small because the strengths of their absorption bands in the thermal infrared are large relative to CO2 and CH 4 (HOUGHTON et al., 1990).
Future atmospheric concentrations Emission scenarios To conduct the assessment of future climatic changes due to the enhanced greenhouse effect, GCMs need inputs of their future atmospheric concentration. These concentrations depend on the magnitude of human-made emissions and how changes in climate and environmental conditions may influence the biospheric processes that control the exchange of natural greenhouse gases between the atmosphere, oceans and terrestrial biosphere (see WMO, 1991, 1994; Chapter 12 by HENDERSON-SELLERS). Ideally, GCMs should include all these components and their interactions. However, at present, GCMs can only calculate the climate responses with specified concentrations, which are estimated based on net greenhouse gas emissions and atmospheric lifetimes. In the climate assessment studies, the net greenhouse gas emissions for the future are usually based on a set of assumptions, the so-called
323
The greenhouse effect of trace gases scenarios, while the atmospheric lifetime depends on the sources and sinks for these gases in the atmosphere. The scenarios illustrate the effect of a wide range of socio-economic assumptions which are highly dependent on the demography and population growth. Therefore, scenarios are not predictions of future changes. Rather, they show how the different factors affect the future emissions. Consequently, the scenarios need to be used carefully and periodic revisions are required. The atmospheric lifetimes of these gases are determined by their sources and sinks in the oceans, atmosphere and biosphere. Carbon dioxide, CFCs and N20 are removed only slowly from the atmosphere while CFC substitutes and CH 4 have relatively short atmospheric lifetimes. Consequently, the responses to human-made emissions will also be different among these gases. Models which incorporate the effects of chemical reactions in the atmosphere are employed to study the lifetime of these gases. However, large uncertainties exist in these models because of inadequate understanding of some of the sources and sinks in the climate system. Therefore, revisions of the scenarios and improving knowledge about the lifetime have been the focus of the IPCC and WMO assessment reports during the past few years and most likely of the future activities. Four scenarios of future human-made emissions were developed by IPCC (HOUGHTON et al., 1990). The first set, known as the business-as-usual condition (Scenario A, SA90), assumes that few or no steps are taken to limit the greenhouse gas emissions. The other three scenarios assume that progressively increasing levels of controls reduce the growth of emissions. These scenarios take into consideration the growth of the economy and population and details can be found in HOUGHTONet al. (1990). The SA90 was revised based on new information relating to the underlying assumptions. Six alternative IPCC Scenarios (IS92a-e) were published (HOUGHTONet al., 1992) by including the following factors: the London Amendations to the Montreal Protocol; revision of population forecasts by the World Bank and United Nations; publication of the IPCC Energy and Industry Sub-group scenario of greenhouse gas emissions to 2050; political events and economic changes in the former USSR, Eastern Europe and the Middle East.; re-estimation of sources and sinks of greenhouse gases; revision of preliminary UN Food and Agriculture Organization; and new scientific studies on forest biomass. For CO2 emissions, IS92a is slightly lower than SA90 while IS92e has the highest and IS92c has the lowest values. These scenarios are again being revised in the ongoing 1994-1995 IPCC processes by incorporating new developments.
Concentration level A number of different types of models have been developed to relate emissions of greenhouse gases and greenhouse gas precursors to future concentrations of greenhouse gases. These models include carbon cycle models and atmospheric gas phase chemistry models. The models incorporate the key components and processes influencing the sources and sinks for these gases. The concentration levels of CO2, CH4, N20, CFC13 and CF2C12 for SA90 and IS92a are shown in Fig. 2. In general, the levels for IS92a are smaller than those for SA90, in particular for the CFCs because of the international control strategy. However, it should be noted that the uncertainties associated with these model calculations are substan-
324
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tial due to the inadequate understanding of some of the processes such as those controlling the uptake and release of CO 2 from the oceans and terrestrial ecosystems and the 0 3 precursor gases.
Table I gives the concentration levels at 2050 calculated based on the IPCC SA90; by that time, the CO2 concentration will be almost twice the pre-industrial value. Other radiatively
important gases include the major halogenated source gas CHC1F2, the halons, CH3CC13 and CC14 and the fully fluorinated species, CF4, C2F6 and SF 6. The sources and sinks for these gases are discussed in HOUGHTON et al. (1992) and WMO (1991). The production of most of these gases, however, has decreased significantly in recent years because of the international agreement to scale down the production and eventually eliminate some of these gases. Climatic effects
As mentioned above, evaluating the climatic effect of the greenhouse gases involves two parts, the radiative forcing and the climate feedbacks. It is much more straightforward to study the radiative forcing than the climate feedbacks because the former requires the radiative transfer calculations while the latter requires GCM experiments.
325
The greenhouse effect of trace gases There have been many calculations of the radiative forcing due to observed increases of greenhouse gases since the pre-industrial era and its potential increase during the next few decades. The radiative forcing values for the individual gases have been used not only to rank the relative contribution of the individual gases to past climate change but also to provide guidelines for policy considerations such as the decision to phase out the CFCs from both climate warming and 03 depletion viewpoints. HANSEN and LACIS (1990) have calculated the radiative forcing due to the added greenhouse gases CO2, CH4, N20 and CFCs for the periods 1850-1957 and 1958-1989. For the first period, the net forcing is calculated to be 0.87 W m -2 with contributions mainly from CO2 (0.58 W m -2) and CH 4 (0.24 W m-2). However, for the second period, the calculated contributions are CO2 (0.66 W m-2), CFCs (0.25 W m -2) and CH 4 (0.24 W m -2) with a total net forcing of 1.17 W m -2. The total radiative forcing of--2 W m -z since the industrial era is consistent with several other calculations documented in HOUGHTON et al. (1992). Estimates of the future radiative forcing for the period 1990-2100 were conducted by WIGLEY and RAPER (1992) using the IPCC scenarios IS92a-e. The calculated range of the forcing values is between 3.38 and 8.48 W m -2 with a value of 6.68 W m -2 for IS92a. In recent years, GCMs have been used to evaluate the global climate change and its regional distribution due to the greenhouse effect. In general, there are two types of GCM experiments" equilibrium simulations using twice the pre-industrial CO2 concentration and transient simulations with a gradual increase of CO2, usually a 1% increase per year (see HOUGHTON et al., 1992). The equilibrium simulations allow scientists to study the climate feedbacks which represent an important source of uncertainty in climate prediction. For example, a warming climate directly caused by CO2 increase can increase the atmospheric capacity of holding more water vapour which itself is a greenhouse gas. Model results indicate that the increase in water vapour can further enhance the CO2-induced warming by 50%. Changes in temperature and moisture are likely to change cloud amount and cloud altitude. Changes in cloud cover would also play an important role in affecting the initial warming. However, the feedback is very complex since an increase in low clouds tends to reflect solar radiation and thus to cool the surface, but an increase in high clouds will warm the surface by trapping more infrared radiation. Model results suggest that a warming climate tends to increase the amounts of high clouds, but to decrease the low cloud, both contributing to an additional warming effect. However, increases in atmospheric moisture will tend to increase the amount of water in clouds and allow less solar radiation to pass through, thereby reducing the surface warming. Thus the magnitude of climatic change due to the greenhouse effect will depend significantly on the climate feedbacks. The transient experiments are needed to take account of the response of ocean and a gradual increase of the greenhouse gases' concentration. The ocean plays a predominant role in regulating the climate change. The ocean circulation and its change associated with changes in the atmosphere through atmosphere-ocean coupling are the fundamental issues related to the use of models for prediction of the magnitude and timing of climatic change due to the greenhouse effect in the future. Table III summaries several transient CO2 experiments conducted using AOGCM. The globally averaged annual mean increase of surface air temperature at the time of effective CO2 doubling is between 1.3 and 2.3~
These values are about 60% of the individual
models' equilibrium warming with doubled CO2 calculated with a mixed-layer ocean. The
326
Uniformly mixed gases TABLE III CONTROL AND TRANSIENT C O 2 SIMULATIONS WITH COUPLED OCEAN-ATMOSPHERE GENERAL CIRCULATION MODELS (AFTER GATES ET AL.,
AGCM OGCM CO 2 (ppmv) CO2 (time) Simulation length (year) Time for CO2 doubling (year) Warming (~ at 2x CO 2 2 x CO2 sensitivity (~
1993)
GFDL
MPI
NCAR
UKMO
R15 L9 4.5x3.75 ~ 300 l%/year (compound) 100
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lower values of the surface warming reflect mainly the large thermal inertia of the oceans which have not reached equilibrium at the time of effective CO2 doubling. Comparisons between the equilibrium and transient experiments show that the patterns of the transient response are similar to those in an equilibrium responses, except over the high-latitude southern ocean and northern North Atlantic ocean where the delayed warming is caused by the oceanic thermohaline circulation. Here, we discuss in more detail the changes in large-scale climate using the equilibrium experiments of WANG et al. (1992) and the transient experiments of MANABE et al. (1991, 1992) and GREGORY (1993).
Equilibrium experiment WANG et al. (1992) describe the only GCM experiments to treat all the individual greenhouse gases using the IPCC SA90 (see Table I for concentration values) in the simulations while most of the other GCM studies use CO2 as a surrogate (see HOUGHTON et al., 1992). The main difference between CO2 and the trace gases CH 4, N20, CFC13 and CF2C12 lies in their difference in distribution of the longwave radiative forcing perturbations which may lead to different climate response
(WANGet al., 1991).
Fig. 3 shows the latitude-altitude distribution of the longwave radiative heating rates between 1990 and 2050 for two cases: CO 2 alone and all the gases included. During this period, the concentration changes will provide a tendency for the stratosphere to cool and the troposphere to warm. In the stratosphere, CO2 uniformly cools the temperature while the other gases further enhance the stratospheric cooling. However, these gases induce a warming effect in the lower stratosphere and upper troposphere, which is a unique characteristic distinguishing these gases from CO2 despite the fact that all these gases are also uniformly
327
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CO 2
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The changes of radiative forcing (W m-2) are calculated based on the January climatology for the stratosphere (STS; <150 mb), the upper troposphere (UTS' 150-500 mb), the lower troposphere (LTS; 500 mb-surface) and on the surface (SFC) as well as in the troposphere-surface system (TSS).
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other hand, the decrease of low level clouds has a much broader spatial distribution during summer, extending from 50~ to 60~
The patterns of the decrease in middle level cloud
are similar for both seasons. Both the increase of high level clouds and decreases of low and middle level clouds tend to warm the surface, although the effect depends greatly on the optical properties of the clouds. The changes in the surface air temperature for both seasons are shown in Fig. 6. For the Northern Hemisphere during summer, there are four centres with surface warming larger than 7~
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On the other hand, the surface warming is much larger
for the Northern Hemisphere during winter mainly, as pointed out in HOUGHTON et al. (1990), because of the snow/ice albedo feedback and changes of soil moisture. Changes in the global and annual mean key climate statistics are summarized in Table V. The model simulations suggest that the global and annual mean surface air temperature can be warmed by ~4~ during the period of 1990-2050. Accompanying this surface warming, 330
Uniformly mixed gases TABLE V
GCM SIMULATED CHANGES OF GLOBAL AND ANNUAL MEAN SURFACE AIR TEMPERATURE T S (K), PRECIPrrATIONP(MM/DAY), CLOUDCOVERC (%) ANDCOLUMNWATERVAPORQ (MM). (AFTERWANGET AL., 1992) Case
Ts
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Transient response experiments Note that the results presented above are the equilibrium responses of the climate to an instantaneous increase in the radiative forcing caused by the increases in gas concentrations. Consequently, the simulations did not consider the transient climate response caused by a gradual increase of greenhouse gases, and the effects of the oceanic general circulation and the storage of heat in the deep ocean; the latter effects have been found to be important in simulating the climate (GATES et al., 1993). MANABE et al. (1991, 1992) have conducted experiments to study how the oceans affect the response of climate to a change of atmospheric CO2. Two types of experiments were carried TABLE VI
GCM
SIMULATED WINTER
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PRECIPITATION ( P IN %), SOIL MOISTURE (S IN %) AND TOTAL CLOUD COVER ( C IN %) BETWEEN
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Central North America South Asia Sahel Southern Europe Australia China
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332
Uniformly mixed gases out: the transient experiment was run using a coupled AGCM and OGCM with a 1%/year increase of CO2 and the equilibrium experiment was run using the same AGCM coupled to a mixed layer ocean with twice the normal CO2. Note that the 1% increase in CO2 was adopted to account for the observed increases of CO2 and other greenhouse gases (see Table I). For each experiment, two (a control and a perturbed) simulations were run, each for 100 years. Fig. 7 shows the annual mean and the geographical distribution of the changes in surface air temperature for the transient experiment and for the equilibrium experiment as well as the ratio between the transient and equilibrium temperature changes. Note that the transient temperature change was averaged over the 60th to 80th model year when the CO2 concentration is comparable to the doubled CO2 amount used in the equilibrium experiment. The transient response is particularly slow over the northern North Atlantic and the Circumpolar Ocean of the Southern Hemisphere, where the deep vertical mixing of water predominates and the effective oceanic thermal inertia is very large. The equilibrium surface warming shows polar amplification in both hemispheres, similar to the results shown in Fig. 6. The magnitude is large along the coast of the Antarctic Continent, enhanced by the poleward retreat of sea ice. Thus the ratio of the transient to equilibrium response of surface air temperature falls below 0.4 in the northern North Atlantic and is near zero in the Circumpolar Ocean of the Southern Hemisphere. In middle latitudes of the Northern Hemisphere, note that the land-sea contrast in warming is also shown in the equilibrium response. The model simulated annual mean transient (equilibrium) surface temperature is 2.76~ the Northern Hemisphere and 1.86~ (4.04~
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Fig. 8. Decadal mean changes in globally averaged sea level change (cm) from several coupled oceanatmosphere GCM experiments (after HOUGHTON,et al., 1992; GREGORY, 1993). GFDL, Geophysical Fluid Dynamics Laboratory; UKMO, United Kingdom Meteorological Office; 1992 and 1993 refer to the citations from HOUGHTONet al. (1992) and GREGORY(1993), respectively; MPI, Max Planck Institute (IPCC scenarios A and D were used).
333
The greenhouse effect of trace gases 90N L
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Atmospheric ozone
Ozone acts as a greenhouse gas by absorbing outgoing longwave radiation. It also absorbs the solar radiation, in particular, the UV-B radiation (Chapter 11 by BRASSEUR et al.). Ozone is of major importance in maintaining the thermal structure in the stratosphere through its absorption of solar radiation in the UV by the Hartley (200-290 nm) and Huggins (290-340 nm) bands and in the visual by the Chappuis (500-700 nm) band. Because of the exponential attenuation of solar radiation at each wavelength, the Hartley band is practically saturated for a nominal amount of 03, while the visual absorption remains nearly proportional to the 03 amount. Changes in the UV flux at the surface of the Earth are confined to the spectral region around 300-340 nm. Stratospheric 03 is largely responsible for the existence of the tropopause, a nearly isothermal region separating the radiatively equilibrated stratosphere from the more dynamically controlled troposphere.
334
Atmospheric ozone Chapter 11 in this book deals with ozone depletion. This section focusses on the effects of ozone in its capacity as a greenhouse gas. Two considerations make 03 distinctly different from other greenhouse gases, which is of major concern in quantifying their climatic impacts. First, ozone is a secondary constituent formed by chemical reactions in the atmosphere. The relation between ozone and its precursors NOx, hydrocarbons and CO depend on the oxidation process in the atmosphere. This process varies strongly with time and space and depends, in addition to the precursors, on several hydrogen radicals like OH and HO2. It is obvious that calculation of changes in 03 and the climatic effects have larger uncertainties than the calculation of changes and the direct climatic effect of greenhouse gases that are emitted into the atmosphere. Second, anthropogenically induced changes in the ozone show large spatial and temporal variations in the atmosphere. The impact from 03 is in striking contrast to the impact from other greenhouse gases of which the concentration changes in most cases are uniform throughout the troposphere. The large spatial and temporal variations in 03 are a result of their short chemical lifetimes in the atmosphere. In the troposphere, lifetimes are days to weeks, where as in the lower stratosphere, 03 lifetimes are of the order of months. The climate forcing from 03 will therefore be highly non-uniform and the impact on temperatures more difficult to assess than for the well-mixed greenhouse gases. Changes in 03 vertical distribution can perturb the solar and longwave radiative forcing of the troposphere-surface climate system (WMO, 1991; HOUGHTON et al., 1992). The effects on the solar and longwave radiative forcing due to changes in atmospheric 03 are sensitive to the altitudes where 03 changes. For example, a decrease in stratospheric 03 acts to provide the troposphere-surface system with: (a) a warming effect due to increased available solar radiation for absorption and (b) a cooling effect due to decreased downward longwave radiation. The net effect will depend on the location and time of year. On the other hand, an increase in tropospheric 03 can warm the troposphere-surface system through increases in absorption of both the solar radiation and longwave radiation. It is only in recent decades that global 03 observation has become available. Satellites provide the total column 03 amount (STOLARSKIet al., 1991) and its stratospheric distribution (MCCORMICK et al., 1992) while for 03 vertical distribution in the troposphere we have to rely on measurements from ozonesondes. Satellites provide global coverage and long-term ozonesonde data are available only at a limited number of stations in middle and high latitudes of the Northern Hemisphere (WMO, 1991). Because the GCM with interactive chemistry is still in the early stage of development, study of the effect of atmospheric 03 on climate is limited to examining the effect using observed 03 changes. Some of the results are presented here to provide quantitative comparisons of the effect with those due to increasing other greenhouse gases in the last few decades. Clearly, an assessment of future effects of 03 changes needs to employ a GCM with coupled climate-chemistry using realistic scenarios for future emissions.
Stratospheric ozone depletion The Total Ozone Mapping Spectrometer (TOMS) and Stratospheric Aerosol and Gas Experiment (SAGE) measurements show a significant reduction in the stratospheric 03 over the middle and high latitudes of both hemispheres since 1979 (WMO, 1991; MCCORMICK et
335
The greenhouse effect of trace gases al., 1992). This change in 03 will affect both the solar and longwave radiative forcing with climatic implications. RAMASWAMY et al. (1992) show that the observed decadal decreases in lower stratospheric 03 produce a substantial negative radiative forcing at middle and high latitudes and that the magnitude of the forcing is sensitive to both the amount of column 03 and the altitude distribution of the 03 depletion. SCHWARZKOPFand RAMASWAMY(1993) have further examined the sensitivity of the radiative forcing to changes in the specification of the decadal 03 depletion profile observed by SAGE. The results suggest that the radiative forcing at the tropics and the mid-latitudes depends strongly on the 03 changes in the lower stratosphere where 03 change can produce larger effect on the radiative forcing than changes in other altitudes (WANG et al., 1980; LAClS et al., 1990). In addition, it is anticipated that decreases in stratospheric temperature are expected from a decreased 03 absorption of the solar radiation. A cooler temperature will decrease the longwave radiation emission, thus further enhancing the magnitude of the decrease in radiative forcing directly attributed to 03 depletion. One-dimensional model studies (RAMASWAMYet al., 1992; WANG et al., 1993; SHINE et al., 1995) indicate that the effect of 03 changes on the radiative forcing depends strongly on the magnitude of the decreases in lower stratospheric temperature. The use of the fixed dynamical-heating assumption discussed earlier yields a negative radiative forcing due to observed stratospheric 03 depletion. Because of the consistent treatment of radiation and dynamics (and recently the chemistry), multi-dimensional models are more appropriate for use in studying the climatic effect of observed stratospheric 03 depletion. HAUGLUSTAINEet al. (1994) used a two-dimensional radiative-dynamical-chemical model to simulate changes in atmospheric composition since pre-industrial times. A small warming due to stratospheric 03 depletion is calculated mainly because a smaller magnitude of 03 decrease (versus observations) is calculated in the lower stratosphere. MAHLMAN et al. (1994) have recently used a three-dimensional chemicalradiative-dynamical model to investigate the climatic effects due to the Antarctic 03 losses. The Antarctic region shows cooling exceeding 8~ in the lower stratosphere. However, the middle and the upper stratosphere in the same region show warming up to 6~ resulting from heating caused by increased convergence of dynamical motions. In addition, the results indicate that the decreases of the lower stratospheric temperatures in the Southern Hemisphere are also consistent with the observed trend. When an observed 03 loss in the lower stratosphere is imposed, the GCM simulations by HANSEN et al. (1993) indicate a cooling in the lower stratosphere that is qualitatively consistent with the observed decadal global mean trend of-0.4~ The global mean radiative forcing is computed to be about-0.2 W m -2 between 1970 and 1990. HANSEN et al. (1992, 1994) have conducted several GCM simulations to compare the surface temperature changes between changes in observed 03 and increases of other greenhouse gases. The resuits indicate that the 03 depletion during 1970-1990 can reduce the greenhouse warming of 0.35~ for the same period by about 15%. DUDEK et al. (1994) have also conducted GCM simulations to study the climatic effect of lower stratospheric ozone depletion and compare the effect with that due to observed increases of CO2, CH4, N20, CFC13 and CF2C12 for the period 1980-1990. Two sets of equilibrium experiments are conducted using the gas concentration levels at 1980 and 1990 shown in Table I. For 1990, they have included a modified 03 distribution which reflects the
336
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337
The greenhouse effect of trace gases sphere with a second order polynomial to retain the column 03 shown in Fig. 10. A climatologically derived tropopause height is used for this calculation and for the radiative forcing calculations. Fig. 11 shows the vertical distribution of the percentage change in 03 mixing ratio used in the model experiments. In January a maximum 03 loss occurs between 10 and 16 km poleward of about 30 ~ The structure is similar in July, but more diffuse in the Northern Hemisphere, while not extending to the pole in the Southern Hemisphere. These computed changes are applied to the model zonal 03 distribution. Table VII shows the change in the globally averaged radiative forcing, which is dominated by the longwave radiative forcing of 0.55 and 0.5 W m -2 in January and July, respectively. Ozone changes increase the solar flux into the troposphere while slightly reducing the longwave flux, resulting in a net warming of 0.14 and 0.08 W m -2 for January and July, respectively. These changes are comparable to the warming due to the increase of CFCs. Note that the radiative forcing calculations are based on the fixed-temperature treatment mentioned above. Fig. 12 shows the zonal distribution of change in radiative forcing, both for 03 and other gases. Changes in 03 forcing are dominated by the solar forcing changes, so the summer hemispheres show the largest O3 effect, being larger than the non-O3 forcing at middle and high latitudes. The model calculated changes in the zonal mean temperature due to 03 changes are shown in Fig. 13. In January, the largest temperature change occurs at high latitudes and is the result of the dynamical response of the polar night stratosphere to the perturbed heating. The temperature is also reduced 1-2~
in the lower stratosphere south of 40~
within the region of
maximum 03 loss. The lower stratosphere in the tropics warms about 1~ In July, there is a more general temperature reduction in the lower stratosphere of 0.5-1~ In both months the troposphere is generally slightly warmer, which is consistent with the enhanced net radiative forcing shown in Table VII. Note that the small magnitude of the surface warming is also caused by the fixed sea surface temperatures in the two perpetual-mode experiments.
Tropospheric ozone Tropospheric
03,
which accounts for about 10% of the total column, plays an important role
in the radiation balance of the troposphere-surface system. However, reliable data on free tropospheric 03 are scarce, partly due to the fact that the focus has been put on the changes in the stratosphere and near the surface. LOGAN (1995) and SPIVAKOVSKYet al. (1990) have examined the tropospheric 03 measured at the ozonesonde stations. As shown in ISAKSEN TABLE VII COMPARISON OF CHANGES IN THE GLOBAL MEAN RADIATIVE FORCING (W M-2) CAUSED BY INCREASES OF GREENHOUSE GASES, CFCS ONLY AND O 3 CHANGES BETWEEN 1980 AND 1990 (SEE TABLE I FOR THE CONCENTRATION LEVELS AT 1980 AND 1990)
January
All gases CFCs 03
338
July
LW
SW
Total
LW
SW
Total
0.434 0.117 -0.040
0.114 0 0.175
0.548 0.117 0.135
0.438 0.119 -0.042
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0.504 0.119 0.081
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339
The greenhouse effect of trace gases
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(see QUADRENNIALOZONE SYMPOSIUM, 1992). Here, to illustrate the importance of tropospheric 03, the results from WANG et al. (1993) are used to show the observed changes of tropospheric 03 and the associated effect on radiative forcing. WANG et al. (1993) used soundings at seven middle and high latitude stations to study the variations of 03 in the last few decades and evaluate the radiative forcing in the context of increasing other greenhouse gases CO2, CH4, CFC13, CF2C12 and N20. These stations in north-south orientation include Resolute (75~ 95~ Churchill (59~ 94~ Edmonton (54~ 114~ Goose Bay (53~ 60~ Payerne (47~ 7~ Hohenpeissenberg (47~ 11~ and Tateno (36~ 140~ The vertical distributions of the linear trend over the period of records are shown in Fig. 14 for Hohenpeissenberg and Payerne, and in Fig. 15 for the other stations. It is quite clear that there is a trend of 03 decrease in the lower stratosphere at the stations in nearly all seasons, which is consistent with the satellite data (WMO, 1991). For tropospheric 03, the increasing trend is evident in Hohenpeissenberg and Payerne throughout the year. The trend is particularly large in the upper troposphere with values of 2-2.5%/year during Spring and Autumn. The trend for other stations is somewhat smaller, generally about 1%/year, but is still significant. In addition, the seasonal variation is also large. Note that since the tropospheric 03 amount is about 10% of the total column, the trend of the total 03 is dominated by stratospheric decreases; for example, at Hohenpeissenberg, the total 03 over the whole period shows a decline of 2.3% per decade (WMO, 1991). These station data clearly indicate the characteristics of 03 decreases in the lower stratosphere and increases in the troposphere. Changes in the vertical distribution of 03 can perturb the radiative forcing, with ensuing climatic implications. WANG et al. (1993) further examined the relative importance of these observed 03 changes to increases of the greenhouse gases C Q , CH 4, N20 and CFCs in affecting the climate. For comparison purposes, they have also evaluated the contributions from tropospheric 03 increase alone. Table VIII summarizes these radiative forcing calculations. For the fixedtemperature treatment, the total radiative forcing at Hohenpeissenberg is calculated to be 0.79 and 1.05 W m -2 for January and July, respectively, while the effect due to 03 changes contributes 0.41 and 0.57 W m -2, respectively. For fixed-dynamical heating treatment, the
340
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Fig. 14. Monthly mean vertical distribution of 0 3 trends (%/year) for Payerne (PY) and Hohenpeissenberg (HP). total radiative forcing for January and July is calculated to be 0.71 and 1.03 W m -2, respectively. The values are slightly smaller than those using fixed-temperature treatment, mainly due to a cooler stratospheric temperature associated with local 03 decreases. For both treatments, it is quite clear that the tropospheric 03 increase contributes substantially to the total radiative forcing. For Payerne, the results also indicate that the 03 changes can provide a large positive radiative forcing. For fixed-dynamical heating treatment, the effect of stratospheric temperature decreases associated with a local 03 decrease is much larger than that calculated for Hohenpeissenberg. Consequently, despite an increase in tropospheric 03, the calculated radiative forcing for July is-0.17 W m -z, thus reducing the total radiative forcing from 0.88 to 0.62 W m -2. Table VIII also shows the changes in winter and summer radiative forcing calculated for Resolute and Goose Bay between 1971-1980 and 1981-1990. The following features are noted here. First, as discussed above, the fixed-dynamical heating treatment, which decreases the stratospheric temperature due mainly to stratospheric 03 depletion, calculates a substantially smaller total radiative forcing than does the fixed-temperature treatment. Second, the effect of 03 changes on the total radiative forcing is either an enhancement for fixed-temperature treatment (e.g. at Resolute) or a reduction for fixed-dynamical heating treatment (e.g. at Goose Bay) to the warming due to the greenhouse gases CO2, CH4, N20 and CFCs.
341
The greenhouse effect of trace gases
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Future climates
It is quite clear that emissions resulting from human activities are substantially increasing
342
Future climates TABLE VIII COMPARISON OF THE CHANGES IN RADIATIVEFORCING (W M-2) BETWEEN 0 3 CHANGES AND THE COMBINED O 3 CHANGES AND INCREASES OF GREENHOUSE GASES CO2, CH4, CFCL3, CF2CL 2 AND N20 (AFTER WANG ET AL., 1993)
03 Changes
Combined 03 and other gases
Total FT Hohenpeissenberg January July Payerne January July Resolute Winter Summer Goose Bay Winter Summer
Troposphere FD
FT
FD
FT
FD
0.410 0.570
0.327 0.548
0.222 0.490
0.136 0.467
0.794 1.050
0.710 1.027
0.356 0.397
0.190 0.136
0.242 0.097
0.074 -0.167
0.797 0.879
0.630 0.617
-0.038 0.194
-0.085 -0.009
0.012 0.052
-0.036 -0.153
0.230 0.620
0.183 0.415
-0.066 -0.218
0.013 --0.153
0.012 -0.415
0.379 0.497
0.288 0.235
0.025 0.043
The calculated changes in radiative forcing are between 1971-1980 and 1981-1990. Concentration increases for other gases also correspond to the indicated periods. FT and FD refer to fixedtemperature and fixed-dynamics treatments in the radiative forcing calculations. the atmospheric concentrations of the greenhouse gases. Since pre-industrial times the radiative forcing of these greenhouse gases has increased by about 2 W m -2, which is consistent with observed surface warming. The trend of increased emissions will continue for at least the next few decades, which will enhance the greenhouse effect. It is calculated that the rate of increases in radiative forcing is about 1 W m -2 in each 20-year period. The continued increase in the radiative forcing will likely further warm the global climate. As summarized in Fig. 16, the few available coupled atmosphere-ocean general circulation models all predict a warming of the surface of about 2.5~
at year 70 when CO2 doubling is occurring.
Presently, the issue of great concern is the magnitude and timing of the regional climate changes in a globally warming environment and the subsequent effect and impact of such climatic changes. On the other hand, increasing tropospheric sulphate aerosols at mid-latitudes in the Northern
Hemisphere (CHARLSONet al., 1992; KIEHL and BRIEGLEB,1993; Chapter 9 by ANDREAE) may induce a cooling effect which certainly needs to be addressed within the context of establishing the total effect on radiative forcing due to increases of the greenhouse gases. Observations have clearly indicated that stratospheric 03 is decreasing around the globe and scientific evidence suggests that the phenomenon is caused by the use of chlorofluorocarbons. In addition, from limited ozonesonde measurements, there is an increasing trend for tropospheric 03 at the middle and high latitudes of the Northern Hemisphere. Although the causes for such an increase remain to be understood, there are reasons to believe that human activities in the future will continue affecting the 03 in similar fashion as observed in the last few decades. In addition, extensive aircraft fleet may be in operation in the lower stratosphere and upper troposphere in the coming decades. The emissions from aircraft in these
343
The greenhouse effect of trace gases 4 ~--
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Year Fig. 16. Decadal mean changes in globally averaged surface temperature (~ in several coupled atmosphere-ocean general circulation models (see Table III for model designation and experiment descriptions; after HOUGHTONet al., 1992). regions will likely affect the 0 3 concentration with serious consequences on climate. Radiative forcing calculations suggest that changes of the vertical O 3 distribution may have large climatic effect, but much work is needed, in particular general circulation model studies with interactive chemistry, physics and dynamics. Global numerical models of the climate which include chemistry of trace gases are, as yet, rather poorly developed and there are too few results to permit any confidence to be placed on the predictions. Nevertheless, chemical changes will play a vital part in future climate changes and their regional distribution. As summarized by WANG and ISAKSEN (1994, 1995), international collaborative research in general circulation model studies of climatechemistry interaction are urged and recommended.
Acknowledgement This study is supported by grants from the Environmental Sciences Research Division of the Department of Energy and the Climatic Dynamics Section of the National Sciences Foundation.
References BOJKOV, R. D., BISHOP, L., HILL, W. J., REINSEL, G. C. and TIAO, G. C., 1990. A statistical trend analysis of revised Dobson total ozone data over the Northern Hemisphere. J. Geophys. Res., 95: 9785-9807. CESS, R. D., HARRISON, E. F., MINNIS, P., BARKSTROM,B. R., RAMANATHAN,V. and KWON, T. Y., 1992. Interpretation of seasonal cloud-climate interactions using earth radiation budget experiment. J. Geophys. Res., 97: 7613-7618. CHARLSON, R. J., SCHWARTZ,S. E., HALES,J. M., CESS, R. D., COAKLEYJR., J. A., HANSEN, J. E. and HOFMANN,D. J., 1992. Climate forcing by anthropogenic aerosols. Science, 255: 423-430. DLUGoKENCKY, E. J., MASAIRE, K. A., LANG, P. M., TANS, P. P., STEELE, L. P. and NISBET, E. G., 1994. A dramatic decrease in the growth rate of atmospheric methane in the northern hemisphere during 1992. Geophys. Res. Lett., 21" 45-48.
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Future climates DUDEK, M. P., WANG, W.-C. and LIANG, X.-Z., 1994. A general circulation model study of the climatic effect of observed stratospheric ozone depletion between 1980 and 1990. Proceedings of the Quadrennial Ozone Symposium, June. University of Virginia, VA, pp. 433-436. FISHMAN, J., 1991. The global consequences of increasing tropospheric ozone concentrations. Chemosphere, 22: 685-695. GATES, W. L., 1992. AMIP. The atmospheric model intercomparison project. Bull. Am. Meteorol. Soc., 73: 1962-1970. GATES, W. L., CUBASCH, U., MEEHL, G. A., MITCHELL, J. F. B. and STOUFFER, R. J., 1993. An intercomparison of selected features of the control climates simulated by coupled ocean-atmosphere general circulation models. WMO/TD-574. World Meteorological Organization, 51 pp. GIORGI, F. and MEARNS, L. O., 1991. Approaches to the simulation of regional climate change: a review. Rev. Geophys., 29:191-216. GREGORY, J. M., 1993. Sea level changes under increasing atmospheric CO 2 in a transient coupled ocean-atmosphere GCM experiment. J. Climate, 6: 2247-2262. nANSEN, J. and LACIS, A. A., 1990. Sun and dust versus greenhouse gases, an assessment of their relative roles in global climate change. Nature, 346: 713-719. HANSEN, J., RIND, D., DELGENIO,A., LACIS, A., LEBEDEFF, S., PRATHER, M., RUEDY, R. and KARL, T., 1991. Regional greenhouse climatic effects. In: M. E. SCHLESINGER (Editor), Greenhouse-GasInduced Climatic Change. A Critical Appraisal of Simulations and Observations. Elsevier, Amsterdam, pp. 211-229. HANSEN, J., ROSSOW, W. and FUNG, I., 1992. Long-term monitoring of global climate forcing and feedbacks. NASA Conference Publications 3234. Washington, DC, 89 pp. HANSEN, J., LACIS, A., RUEDY, R., SATO, M. and WILSON, H., 1993. How sensitive is the world's climate ? Res. Explor., 9: 142-158. nANSEN, J., SATO, M., LACIS, A. and RUEDY, R., 1994. Climate impacts of ozone change. Proceedings of IPCC Hamburg Meeting, May. HAUGLUSTAINE, D. A., GRANIER, C., BRASSEUR, G. P. and MAGIE, G., 1994. The importance of atmospheric chemistry in the calculation of radiative forcing on the climate system. J. Geophys. Res., 99:1173-1186. HOUGHTON, J. J., JENKINS,G. J. and EPHRAUMS,J. J. (Editors), 1990. Climate Change. The IPCC Scientific Assessment. Intergovernmental Panel on Climate Change, United Nations Environmental Programme/World Meteorological Organization, Cambridge University Press, 364 pp. HOUGHTON, J. T., CALLANDER, B. A. and VARNEY, S. K. (Editors), 1992. Climate Change 1992. The Supplementary Report to the IPCC Scientific Assessment. Intergovernmental Panel on Climate Change, United Nations Environmental Programme/World Meteorological Organization, Cambridge University Press, 200 pp. HURRELL, J., HACK, J. J. and BAUMHEFNER, D. P., 1993. Comparison of NCAR Community Climate Model (CCM) Climates. NCAR/TN-395+STR, 335 pp. ISAKSEN, I. S. A. (Editor), 1988. Tropospheric Ozone. Regional and Global Scale Interactions. NATO Advanced Science Institutes Series, D. Reidel, Dordrecht, 425 pp. KIEHL, J. T. and BRIEGLEB, B. P., 1993. The relative roles of sulfate aerosols and greenhouse gases in climate forcing. Science, 260:311-314.. LACIS, A. A., WUEBBLES, D. J. and LOGAN, J. A., 1990. Radiative forcing of climate by changes in the vertical distribution of ozone. J. Geophys. Res., 95: 9971-9981. LOGAN, J. A., 1985. Tropospheric ozone. Seasonal behavior, trends, and anthropogenic influences. J. Geophys. Res., 90; 10463-10482. MAHLMAN, J. D., PINTO, J. P. and UMSCHEID,L. J., 1994. Transport, radiative and dynamical effects of the Antarctic ozone hole. A GFDL "SKYHI" model experiment. J. Atmos. Sci., 51: 489-508. MANABE, S. and STRICKLER,R. F., 1964. On the thermal equilibrium of the atmosphere with a convective adjustment. J. Atmos. Sci., 21:361-385. MANABE, S., STOUFFER, R. J., SPELMAN,M. J. and BRYAN, K., 1991. Transient responses of a coupled ocean-atmosphere model to gradual changes of atmospheric CO 2. Part I: Annual mean response. J. Climate, 4:785-818. MANABE, S., SPELMAN, M. J. and STOUFFER, R., 1992. Transient responses of a coupled oceanatmosphere model to gradual changes of atmospheric CO 2. Part II: Seasonal response. J. Climate, 5: 105-126. MCCORMICK, M. P. and HOOD, L. L., 1994. Relationship between ozone and temperature trends in the lower stratosphere: latitudinal and seasonal dependence. Geophys. Res. Lett., 21:1615-1618.
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The greenhouse effect of trace gases MCCORMICK, M. P., VEIGA, R. E. and CHU, W. P., 1992. Stratospheric ozone profile and total ozone trends derived from the SAGE and SAGE II data. Geophys. Res. Lett., 19: 269-272. MCGREGOR, J. L. and WALSH, K., 1993. Nested simulations of perpetual January climate over the Australian region. J. Geophys. Res., 98: 23283-23290. MILLER, A. J., NAGATANI,R. M., TIAO, G. C., NIU, X. F., REINSEL, G. C., WUEBBLES, n. and GRANT, K., 1992. Comparisons of observed ozone and temperature trends in the lower stratosphere. Geophys. Res. Lett., 19: 929-932. MOHNEN, V. A., GOLDSTEIN,W. and WANG, W.-C., 1993. Tropospheric ozone and climate change. J. Air Waste Manage. Assoc., 43: 2-14. QUADRENNIALOZONE SYMPOSIUM, 1992. University of Virginia, Charlottesville, VA (proceedings in print in 1994). RAMANATHAN,V., 1975. Greenhouse effect due to chlorofluorocarbons: climatic implications. Science, 190: 50-52. RAMANATHAN, V., 1988. The greenhouse theory of climate change. A test by inadvertent global experiment. Science, 240: 293-299. RAMANATHAN, V., CESS, R. D., HARRISON, E. F., MINNIS, P., BARKSTROM, B. R., AHMAD, E. and HARTMANN, D., 1989. Cloud radiative-forcing and climate. Results from the Earth's radiation budget experiment. Science, 243: 57-63. RAMASWAMY, V., SCHWARZKOPF,M. D. and SHINE, K. P., 1992. Radiative forcing of climate from halocarbon-induced global stratospheric ozone loss. Nature, 355:81 0-812. SCHWARZKOPF, M. D. and RAMASWAMY,V., 1993. Radiative forcing due to ozone in the 1980s. Dependence on altitude of ozone change. Geophys. Res. Lett., 20: 205-208. SHINE, K. P., BRIEGLEB, B. P., GROSSMAN, A., HAUGLUSTAINE, D., MAD, H., RAMASWAMY, V., SCHWARZKOPF, M. D., VAN DORLAND, R. and WANG, W.-C., 1995. Radiative forcing due to changes in ozone-a comparison of different codes. In: W.-C. WANG and I. S. A. ISAKSEN(Editors), Atmospheric Ozone as a Climate Gas. NATO ASI Series, 132, Springer-Verlag, Berlin, in press. SPIVAKOVSKY, C. M., YEVICH, R., LOGAN, J. A., WOFSY, S. C. and MCELROY, M. B., 1990. Tropospheric OH in a three-dimensional chemical tracer model: an assessment based on observations of CHaCC13. J. Geophys. Res., 95: 18441-18471. STOLARSKI, R. S., BLOOMFIELD,P., MCPETERS, R. D. and HERMAN,J. R., 1991. Total ozone trends deduced from Nimbus-7 TOMS data. Geophys. Res. Lett., 18:1015-1018. SUBAK, S., RASKIN, P. and HIPPEL, D. V., 1993. National greenhouse gas accounts: current anthropogenic sources and sinks. Clim. Change, 25: 15-58. THOMPSON, A. M., 1992. The oxidizing capacity of the Earth's atmosphere: probable past and future changes. Science, 256:1157-1165. WANG, W.-C. and ISAKSEN, I. S. A., 1994. A report on workshops: general circulation model study of climate-chemistry interaction. Bull Am. Meteorol. Soc., 75:1671-1675. WANG, W.-C. and ISAKSEN, I. S. A. (Editors), 1995. Atmospheric Ozone as a Climate Gas. NATO ASI Series, 132, Springer-Verlag, Berlin, in press. WANG, W.-C., YUNG, Y. L., LACIS, A. A., MO, T. and HANSEN, J. E., 1976. Greenhouse effects due to man-made perturbations of trace gases. Science, 194: 685-690. WANG, W.-C., PINTO, J. P. and YUNG, Y. L., 1980. Climatic effects due to halogenated compounds in the Earth's atmosphere. J. Atmos. Sci., 37: 333-338. WANG, W.-C., WUEBBLES, D. J., WASHINGTON,W. M., ISAACS, R. G. and MOLNAR, G., 1986. Trace gases and other potential perturbations to global climate. Rev. Geophys., 24:110-140. WANG, W.-C., DUDEK, M. P., LIANG, X.-Z. and KIEHL, J. T., 1991. Inadequacy of effective CO2 as a proxy in simulating the greenhouse effect of other radiatively active gases. Nature, 350: 573-577.. WANG, W.-C., DODEK, M. P. and LIANG, X., 1992. Inadequacy of effective CO 2 as a proxy to assess the greenhouse effect of other radiatively active gases. Geophys. Res. Lett., 19: 1375-1378. WANG, W.-C., ZHUANG,Y.-Z. and BOJKOV, R. D., 1993. Climatic implications of observed changes in ozone vertical distribution in the middle and high latitudes of the Northern Hemisphere. Geophys. Res. Lett., 20:1567-1570. WIGLEY, T. M. L. and RAPER, S. C. B., 1992. Implications for climate and sea level of revised IPCC emissions scenarios. Nature, 357: 293-300. WORLD METEOROLOGICALORGANIZATION,1991. Scientific Assessment of Ozone Depletion. WMO Report No. 25. WORLD METEOROLOGICALORGANIZATION,1994. Scientific Assessment of Ozone Depletion. WMO Report No. 37.
346
Chapter 10
Climatic effects of changing atmospheric aerosol levels MEINRAT O. ANDREAE
Introduction
Concern about the potential climatic influence of changing atmospheric aerosol loadings was first voiced in the 1960s, when MCCORMICK and LUDWIG (1967) suggested that increasing atmospheric aerosol concentrations would scatter more sunlight back into space, thereby increasing planetary albedo and cooling the Earth. This effect was even proposed as an explanation for the observed decline in worldwide average temperatures over the preceding two or three decades. Speculation in the early 1970s went as far as suggesting that increasing anthropogenic aerosols were sending the Earth into an ice age (RASOOL and SCHNEIDER, 1971; BRYSON, 1974). A possible climatological impact of anthropogenic sulphur emissions due to light scattering by sulphate aerosols was predicted by BOLIN and CHARLSON (1976). A more detailed analysis showed that the climatic effect of aerosols depended on their composition since light-absorbing components (e.g. soot carbon) would actually absorb solar energy and thus produce a heating of the atmosphere. The net effect of aerosols on the radiation balance thus depends on the relative magnitude of the amount of light scattered back to space (expressed by the aerosol backscatter coefficient) versus the amount absorbed by the aerosol (expressed by the absorption coefficient) (CHARLSON and PLEAT, 1969; ENSOR et al., 1971; MITCHELL, 1971). These and subsequent authors also pointed out that the influence of aerosols on albedo depends on the albedo of the underlying surface and on the presence of clouds in the atmosphere since the presence of aerosols over highly reflective surfaces (snow, clouds) actually leads to a decrease in the local albedo (MITCHELL, 1971; MORIYAMA, 1978). The limited amount of data available at the time (mostly from urban or industrially influenced areas) suggested that anthropogenic aerosol particles had absorption/backscatter ratios within the range where their cooling and heating effect would approximately cancel out on a global scale. Furthermore, relatively high aerosol loadings were thought to exist as a "natural background aerosol" so that the anthropogenic increase of global aerosol levels was felt to be of no great significance. KELLOGG (1980) concludes "... that anthropogenic aerosols (a) can hardly have a significant effect on the overall radiation balance of the Earth as a whole; (b) probably cause a warming of the lower atmosphere over land in or near the source region, and therefore can influence climate regionally; and (c) when over the ocean they may cause a small cooling in cloud-free areas, but in cloudy areas they also cause a warming over the ocean." A significant climatic role for atmospheric aerosols was attributed only to the cataclysmic consequences of volcanic eruptions or nuclear war (CRUTZEN and BIRKS, 1982). An even
347
Climatic effects of changing atmospheric aerosol levels more dramatic event, the impact of a major asteroid or comet on the earth and the resulting dust cloud, may have caused or contributed to the mass extinction at the end of the Cretaceous; this issue is discussed in detail in Chapter 4 by RAMPINO. However, concurrent with the rising trend in global temperatures observed in the 1970s and 1980s, the general public and scientific interest shifted away from aerosol cooling and focussed on the global warming effect of the greenhouse gases (HOUGHTON et al., 1990 and references therein). Interest in the climatic effect of aerosols was rekindled by discussion of their indirect radiative effects, i.e. the effects due to their influence on cloud optical properties. TWOMEY (1977) had already pointed out that an increase in the concentration of cloud condensation nuclei (aerosol particles which can act as nuclei for the formation of cloud droplets) would lead to higher number concentrations of cloud droplets in a given cloud, accompanied by a decrease in cloud droplet radius. Given constant liquid water path in a cloud, its reflectance thus increases with CCN concentration. A global increase of aerosol particles which can act as CCN would thus increase the albedo of clouds, and consequently the average planetary albedo. A linkage between biogenic sulphur emissions, CCN consisting of sulphate aerosol, and cloud albedo was suggested by NGUYEN et al. (1983). Independently, CHARLSON et al. (1987) formulated a hypothesis (often referred to as the CLAW hypothesis after the initials of the authors' surnames: Charlson, Lovelock, Andreae and Warren) which suggested that marine phytoplankton influences global climate via the emission of dimethylsulphide (DMS) to seawater. DMS escapes across the air/sea interface to the atmosphere, is oxidized to sulphate aerosol which acts as CCN, and thus increases cloud albedo. Since the resulting change in climate would in turn influence phytoplankton concentrations and speciation, a feedback loop is established. The geophysiological aspects of this feedback system are discussed in detail in Chapter 15 by KUMP and LOVELOCK. The cloud effect acts to cool the Earth, and thus amplifies the direct cooling effect produced by biogenic sulphur aerosols. SHAW (1983) had already proposed that aerosols derived from biogenic sulphur emissions could be involved in global temperature control due to their direct radiative effect; cloud-amplification of scattering by as much as a factor of 20 relative to the effect of dry aerosol would make this climatic feedback operate under more realistic perturbations of the global sulphur cycle than those Shaw had to assume in order to obtain a significant effect. Discussions about the CLAW hypothesis (SCHWARTZ, 1988; CHARLSON et al., 1989) eventually led to a re-examination of the climatic role of anthropogenic aerosols. Present estimates suggest that the cooling effect of the aerosol (directly by light backscattering and indirectly through the enhancement of cloud albedo) dominates over the warming effects caused by light absorption, and that the combined effects of anthropogenic aerosols from the combustion of fossil fuels and biomass may be of a similar magnitude as the effect of the greenhouse gases, albeit with opposite sign (WIGLEY, 1989, 1991; CHARLSON et al., 1991; PENNER et al., 1992). The aerosol effect may thus have masked the greenhouse gas heating effect over the past decades at least in the Northern Hemisphere where most of the SO2 is released (WIGLEY,1989). This chapter discusses the various sources of atmospheric aerosols, their potential change in the future, and the effects that aerosols have on climate through perturbation of the radiation balance and through modification of cloud properties.
348
Aerosol sources Aerosol sources
Aerosol particles can be produced by two distinct mechanisms: the direct injection of particles into the atmosphere (e.g. dust, sea spray) resulting in so-called "primary" aerosols, or the production of "secondary" aerosols by the conversion of gaseous precursors into liquid or solid particles. Primary aerosols dominate the "coarse" fraction of the aerosol (the particles with diameters greater than 1/tm), while secondary particles constitute most of the "fine" aerosol (particle sizes typically below 1/tm). Table I summarizes the various sources of aerosol particles and presents estimates of their magnitude. Soil dust Tremendous amounts of dust are mobilized by high winds in the desert regions of the globe, especially the Sahara and Gobi deserts and the Australian deserts. The dust plumes originating from these large deserts are the most conspicuous features in maps of the global distribution of atmospheric haze obtained from satellite data (HUSAR and STOWE, 1994). While much of this material, due to the relatively large size of the particles, falls out again fairly close to its source, substantial amounts are transported over great distances. The mass me-
TABLE I ESTIMATES OF PRESENT-DAY GLOBAL EMISSION OF MAJOR AEROSOL TYPES (IN TG/YEAR)
Source
Present flux Low
High
Best
1,000 1,000 4 26
3,000 10,000 10,000 80
1,500 1,300 33 50
60 4 40 10
110 45 200 40
90 12 55 22
40 10
130 30
100 20
120 50 20 5 2,390
180 140 50 25 24,000
140 80 36 10 3,450
Natural
Primary Soil dust (mineral aerosol) Sea-salt Volcanic dust Biological debris Secondary Sulphates from biogenic gases Sulphates from volcanic SO2 Organic matter from biogenic NMHC a Nitrates from NOx Anthropogenic
Primary Industrial dust etc. Black carbon (soot and charcoal) Secondary Sulphates from SO 2 Biomass burning (w/o black carbon) Nitrates from NOx Organics from anthropogenic NMHC a Total aNMHC, non-methane hydrocarbons.
349
Climatic effects of changing atmospheric aerosol levels dian diameter of this aerosol (away from immediate sources) is of the order of 2/tm, but even "giant" particles, with diameters of 50/tm or more have been found over the remote oceans, at distances of thousands of kilometres away from their continental sources (BETZER et al., 1988). Dust from the Gobi desert is easily detected in the Hawaiian Islands, and Saharan dust is consistently observed on the island of Barbados, across the Atlantic Ocean. In fact, a large part of the marine sediment in areas remote from the continents is thought to consist of wind-blown dust (FERGUSON et al., 1970; PROSPERO, 1981; UEMATSU et al., 1985). Even in the middle of the Amazon Basin during the wet season, dust events from the Sahara have been observed (ANDREAE et al., 1990; ARTAXO et al., 1990; TALBOT et al., 1990; SwaP et al., 1992). The amount of dust emitted is difficult to estimate, especially since it is not obvious how this "emission" should be defined: obviously a grain of sand that is only displaced a few centimetres should not be counted, while aerosols that are transported across oceans should be. However, there is a continuous range between these extremes, with the largest masses mobilized having the shortest atmospheric lifetimes, so that the definition of the cut-off is of great consequence for the size of the resulting estimate. As a result, estimates of the magnitude of the global flux of soil-dust aerosol vary over a wide range: values as low as 100 Tg/year (SMIC, 1971) and as high as 8000 Tg/year (PETRENCHUK, 1980) can be found in the literature. DUCE et al. (1991) present a careful analysis of the amount of mineral aerosol deposited to the world ocean; their estimate of 910 Tg/year represents a lower limit to the global flux because much of the soil dust aerosol is redeposited on land and does not reach the oceans. SCHUTZ (1987) estimates that the Earth's deserts export a minimum of 2000 Tg of mineral dust per year into the atmosphere, about 20% of which is in a size range small enough to be subject to long-range transport and to contribute to the "global background aerosol". In Table I, a range of 1000-3000 Tg/year is proposed as a reasonable estimate for the global flux of mineral aerosol, and a "best guess" estimate of 1500 Tg/year is suggested. This value agrees with the model results of WEFERS (1990), who simulated the emission and transport of mineral aerosol using a threedimensional model (MOGUNTIA), and, at a total source strength of ca. 1500 Tg/year, obtained reasonable agreement between predicted and observed concentrations of mineral aerosol in the remote atmosphere. The size of the desert regions and the intensity of the winds over them obviously have a great influence on the amounts of dust mobilized, and on the heights to which it is lofted. The desertification of large regions of the African Sahel, the conversion of tropical forests into barely vegetated, degraded lands, and the use of inappropriate agricultural and grazing practices in many regions have opened considerable soil surface to aeolian erosion and must have resulted in an increase in the amounts of dust injected into the atmosphere (for a discussion of desertification and land-use change see Chapter 12 by HENDERSON-SELLERS in this volume). That such an increase in mineral dust flux due to desertification is already taking place is shown by the concentrations of Saharan dust sampled on Barbados, which show a strong increase from 1965 to 1984, reflecting the drought in the Sahel (PROSPERO and NEES, 1986). Changing mineral aerosol burdens have also been associated with climatic change in the past. Analysis of the mineral aerosol content of Antarctic ice cores shows elevated levels of soil dust during the ice ages, when large areas on the continental shelves were open to erosion by intense winds over the Southern Hemisphere continents (PETIT et al., 1981; DE
350
Aerosol sources
ANGELIS et al., 1987). Such an enhanced aerosol burden would contribute to intensified cooling during an ice age. Sea-salt
In estimating the amount of sea-salt aerosol emitted, we face the same problem as with the dust aerosol. The largest sea spray droplets, containing most of the mass injected in the air, are so large that they return to the ocean almost immediately. Smaller droplets may stay airborne long enough to dry out and shrink, whereby they then can remain airborne even longer. This inverse relationship between mass and atmospheric lifetime has also resulted in a large range of estimates in the amount of these aerosols being injected into the atmosphere (1,000-10,000 Tg/year: SMIC, 1971; BLANCHARD, 1983). The mass median diameter of sea-salt aerosol near the sea surface is of the order of 8/tm, and, because of their short atmospheric lifetime and inefficient light scattering, the largest particles are of little importance to climate change. Therefore, in Table I a value of 1300 Tg/year is suggested as representative for that fraction of the sea-salt aerosol which can be transported throughout the lower marine troposphere (PETRENCHUK, 1980; ANDREAE, 1986). The rate of production of sea-salt particles large enough to act as CCN is relatively small; CIPRIANO et al. (1987) estimate that this mechanism could account for about 18 cm -3 (i.e. particles per cm 3) at a wind speed of 10 m s-1 in a marine boundary layer of 1 km thickness. While substantial changes in the amount of sea surface available for the production of seasalt aerosols are not to be expected over the time-scale of a few hundred years, future climates with significantly altered wind regimes may have a noticeable influence on the production of sea-salt aerosols. LATHAM and SMITH (1990) have proposed that increased wind speeds resulting from global warming may increase the number of sea-salt particles which can act as CCN from its presently insignificant value to levels of 50 cm -3 or more. At these concentrations, sea-salt particles would have a significant influence on the albedo of marine stratus. This prediction is supported by the observations of O'DOWD and SMITH (1993), who found sea-salt particle concentrations up to about 50 cm -3 over the northeastern Atlantic during autumn. At the same time, biogenic sulphate was very low, and consequently sea-salt particles dominated the CCN population in unpolluted air masses. Volcanic aerosols
Explosive volcanic eruptions can inject vast amounts of gaseous and particulate material into the atmosphere within a brief period. The 1815 eruption of Tambora (Indonesia) produced a total ejecta volume of about 30 km 3, corresponding to a mass of about 100,000 Tg, of which 200 Tg is thought to have entered the stratosphere. E1 Chichon injected about 20 Tg of primary aerosol into the stratosphere, Mount St. Helens about 0.3 Tg. In the case of explosive volcanoes, the ejection of primary mineral aerosol particles usually dominates over the production of sulphuric acid aerosol from the oxidation of the emitted SO2. However, very large eruptions of non-explosive, basaltic volcanoes or fissure systems can release huge amounts of SO2. For example, the largest historic basaltic eruption, Skaft~ireldar (Laki) in southern Iceland, is thought to have resulted in the production of ca. 80 Tg of H2SO4 aerosols, much of which must have remained in the troposphere for a considerable length of 351
Climatic effects of changingatmosphericaerosol levels time and may have caused a Northern Hemisphere cooling of about 1~ (for a detailed discussion see Chapter 4 by RAMPINO). Obviously, it is problematic to assign average levels to such sporadic fluxes. The values for volcanic dust in Table I represent fluxes of material small enough to be transported over long distances for "quiescent" (low estimate) and extremely "active" years (high estimate), and a long-term average of 33 Tg/year ("best" estimate; WARNECK, 1988). The estimates of sulphate aerosol derived from volcanigenic SO2 are based on an estimate of 6.5 (2-25) Tg S(SO2) being released annually by volcanoes, of which about 2 Tg come from explosive eruptions (BLUTH et al., 1993 and references therein). It is assumed that about half of the SO2 is converted to sulphate, and that the aerosol is converted to ammonium bisulphate due to uptake of ambient NH 3. While the climatic effect of individual large eruptions is considerable (a global cooling of about 0.5~ lasting for about 2 years in the case of the eruption of Mt. Agung in 1963 and a similar effect from the Pinatubo eruption in 1991 (HANSEN et al., 1992, 1993; MINNIS et al., 1993; Chapter 5 by JONES; Chapter 6 by DIAZ and KILADIS), they are too far apart in time to have produced significant climate change during the Quaternary. Fig. 1 shows a comparison between the forcing by greenhouse gases alone and that of volcanic plus greenhouse forcing (based on HANSEN and LACIS, 1990). Evidently, volcanic forcing may at times partially or totally offset greenhouse gas forcing (e.g. the clustering of eruptions between 1902 and 1912 (Chapter 6 by DIAZ and KILADIS), but the latter clearly dominates the long-term trend. Due to the inertia built into the climate feedbacks, relatively short changes in forcing have much less effect on climate than sustained ones. It would require a profound alteration in the frequency and intensity of volcanic emissions worldwide to offset the greenhouse forcing by a significant amount. These model predictions are supported by the absence of a clear correlation between long-term climate data and indices of volcanic activity (Chapter 5 by JONES).
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Fig. 1. Climate forcings in the past century owing to changes of greenhouse gases and stratospheric aerosols. Aerosol forcing after 1883 is based on atmospheric transmission measurements; for 18501883 the three largest volcanoes identified are included, with optical depth scaled relative to AGUNG (1963), in proportion to the volume of ejecta. Aerosol optical depth for 1883-1960 is based on atmospheric transmission measurements at astronomical observatories; subsequently it is based on the transmission of sunlight through the stratosphere as recorded by approximately annual lunar eclipses. Zero point of aerosol forcing is the 1850-1989 mean (from HANSENand LACIS, 1990).
352
Aerosol sources Industrial dust
A number of human industrial and technical activities produce primary aerosol particles: transportation, power plants, cement manufacturing and metallurgy, waste incineration, etc. These sources account for a total emission of about 130 Tg/year, of which only about 30 Tg are in the form of particles smaller than 2.5/tm diameter (WARNECK, 1988). This aerosol source is responsible for the most conspicuous impact of anthropogenic aerosols on environmental quality, and has been widely monitored and regulated. As a result, the emission of industrial dust aerosols has been reduced significantly, particularly in developed countries. For this reason, and considering that most of this material is deposited fairly close to its source regions and is present in an optically not very active size fraction, it is probably not of importance for global climatic change. Black carbon
Black carbon particles consist of nearly pure elemental carbon with some oxygen and hydrogen bound into layered, hexagonal structure which corresponds to a somewhat disordered graphitic crystal structure. Black carbon may be formed either by carbonization (charring) of organic matter during combustion (charcoal particles) or by condensation from the gas phase in reducing flames (soot particles). It is the only common substance in aerosols which strongly absorbs visible light and is therefore listed separately in Tables I and II. Since about 10 Tg/year of black carbon are from biomass burning (ANDREAE, 1993), the emission estimate for aerosol from biomass burning in Tables I and II has been reduced by this amount. Biomass burning
The combustion of biomass (e.g. in forest and savanna fires, agricultural burning, and the production of domestic energy) produces primary aerosols in the form of ash, soot and charcoal particles, and secondary aerosols in the form of tar condensates, and photochemically produced organic, sulphate and nitrate aerosols. Ammonia emitted from the fires is taken up in the aerosol and neutralizes acidic constituents (ANDREAEet al., 1988; TALBOT et al., 1988). The type of aerosol produced in biomass fires depends to a great extent on the combustion characteristics: hot, flaming fires emit relatively small amounts of aerosol with a high soot carbon content, while smoldering fires emit large amounts of tar condensates with relatively little black carbon (PATTERSONand MCMAHON, 1984; WARD, 1986; CACHIER et al., 1989; EINFELD et al., 1991; WARD and HARDY, 1991). Consequently, forest fires and domestic burning, where smoldering predominates, release large amounts of particulate matter compared to savanna fires, which are dominated by flaming combustion. The emission of gases and aerosols from biomass burning has been reviewed recently (ANDREAE, 1993). Changes in the amount of biomass burned over the last 100-150 years are difficult to estimate. It is clear that burning in connection with tropical deforestation has grown from almost nil in the 19th century to its present value of some 1.3 billion tonnes (dry matter) per year. In temperate forests, less stringent fire control policies now prevail in some regions 353
t.n q~
c~ TABLE II SOURCE STRENGTH, ATMOSPHERIC BURDEN, OPTICAL EXTINCTION, AND DIRECT RADIATIVE FORCING DUE TO THE VARIOUS TYPES OF AEROSOLS c~
Source
Flux
Lifetime
(Tg year-1)
(days)
Global burden (Tg)
Column burden (mg m -2)
Mass extinc. coeff. (hyd.) (m2 g-l)
Optical depth
Forcing (direct) (W m -2)
Natural
~,,t~
o~
Primary Soil dust (mineral aerosol) Sea-salt Volcanic dust Biological debris
1,500 1,300 33 50
4 1 4 4
16.4 3.6 0.4 0.5
32.2 7.0 0.7 1.1
0.7 0.4 2.0 2.0
0.023 0.003 0.001 0.002
-0.75 -0.09 -0.05 -0.07
90 12 55 22 3,060
5 5 7 4
1.2 0.16 1.1 0.24 24
2.4 0.3 2.1 0.5 46
8.5 8.5 8.0 2.0
0.021 0.003 0.017 0.001 0.070
-0.68 -0.09 -0.55 -0.03 -2.3
100 20
4 6
1.1 0.3
2.1 0.6
2.0 10.0
0.004 0.006
-0.14 -0.21
140 80 36 10 390
5 8 4 7
1.9 1.8 0.4 0.19 5.7
3.8 3.4 0.8 0.4 11.1
8.5 8.0 2.0 8.0
0.032 0.027 0.002 0.003 0.075
-1.06 -0.91 -0.05 -0.10 -2.5
0.144 52
--4.8 52
I~,,~
Secondary Sulphates from biogenic gases Sulphates from volcanic SO2 Organic matter from biogenic NMHC a Nitrates from NOx
Total natural
Anthropogenic Primary Industrial dust, etc. Black carbon (soot and charcoal)
Secondary Sulphates from SO2 Biomass burning (w/o black carbon) Nitrates from NOx Organics from anthropogenic NMHC a
Total anthropogenic Total Anthropogenic fraction (%) aNMHC, non-methane hydrocarbons.
3,450 11
29 19
57 19
r~
Aerosol sources (e.g. North America), on the other hand, improved technical means of control may have reduced fires in other regions over the last century (e.g. in Russia). Especially in the tropics, domestic use of biomass energy must have grown with the size of the population relying on biomass fuel. Savanna fires appear to have become more frequent but smaller amounts of biomass per fire may be being burnt. Agricultural burning may be practised less frequently now in developed countries, but may have grown with increasing population and crop demand in the developing world. On this basis, it is estimated that the amount of biomass burned has increased worldwide by a factor of two to three since the early 19th century. This view is supported by a study of the isotope composition of methane in ice cores, which concludes that the amount of methane released by biomass burning must have increased strongly since that time (CRAIG et al., 1988), and by an analysis of charcoal deposition in sediments which shows an increase in charcoal flux over the last century
(SUMAN,
1991).
Future change in the amount of biomass burned is equally difficult to predict. There may not be much incentive to further increase the frequency of savanna burning, and more frequent fires may not burn much more biomass due to the shorter periods for fuel accumulation. Growing populations will increase demand for biomass fuel, which will put increasing pressure on fuel resources, but practical limitations will probably prevent substantial growth in this sector. The burning of tropical forests for clearing may be reduced by political action, but even if it continues unchecked, it will reach a limit due to the elimination of the tropical forests. As a reasonable upper limit for the rate of growth of biomass combustion we can take the growth of the human population which may reach double its present size by the middle of the 21st century. If a pronounced shift towards the use of biomass fuel as a replacement for fossil fuels should occur, emissions are likely to be subject to relatively stringent controls. In their standard scenario, the Intergovernmental Panel on Climate Change (IPCC) predicts a rather modest growth in biomass burning, which is reflected in the growth in pyrogenic aerosol emissions plotted in Fig. 2.
Organic particles Plants, especially those in the tropics, represent a very large source of organic matter to the atmosphere. They release gaseous hydrocarbons, e.g. isoprene and terpenes, which are Aerosol Emissions Past and Future 300
em 2 0 0 O 9~
Biomass burning 100
Sulphate ~ --- ~ _ ~ ~ - - ~ ~~176176 ~ ~ ~ " __ ~ ~ - - . . .o.
0
..o" . . . . . . . . . . . . . . .
. . . . . . . " . . . . . ~'"
1850
1900
........
I
Biomass burning
o*
,
a
1950
i
2000
t
i
2050
t
2100
Year AD Fig. 2. Estimated aerosol emissions from biomass burning and anthropogenic sulphur emissions from pre-industrial times to the year 2100. Estimates are expressed in total aerosol mass; for sulphate aerosol, conversion efficiencies from gaseous precursors are discussed in the text.
355
Climatic effects of changing atmospheric aerosol levels photochemically oxidized in the atmosphere. The oxidation products of isoprene, which makes up about one-half of the biogenic non-methane hydrocarbons emitted worldwide, are volatile and do not form aerosols (PANDIS et al., 1991). However, many of the terpene oxidation products are relatively involatile and condense into organic aerosol particles (PANDIS et al., 1991; ZHANG et al., 1992; FEHSENFELD et al., 1992 and references therein). Forest vegetation also sheds organic particles in the form of waxy leaf cuticles etc. and ejects droplets in a process called guttation which also results in aerosol formation (CROZAT, 1979). This type of material appears to make up a large fraction of the aerosol over tropical forests, e.g. the Amazon forest (ARTAXO et al., 1990), but has received relatively little study so far. It has been difficult to characterize this material chemically and physically, since it is rarely present without contamination from biomass burning and other anthropogenic materials (TALBOT et al., 1988, 1990; ANDREAE et al., 1988). This aerosol source must be expected to decline as tropical forests are reduced since the grasslands and degraded lands which replace the forests appear to produce little biogenic aerosol. The estimate for this source in Table I is based on a global biogenic non-methane hydrocarbon (NMHC) emission of ca. 700 Tg/year (of which 50% is isoprene and does not form aerosols), an aerosol yield of ca. 10% from the non-isoprene fraction, and a carbon content of ca. 66% in the partially oxidized organic material. Anthropogenic NMHC can presumably also be oxidized to organic particulate matter. However, the release rate of anthropogenic NMHC is much lower than the natural emissions (ca. 100 Tg/year; EHHALT et al., 1986) and their conversion efficiency to particulates is probably quite low. This is supported by the observation that even in a highly urbanized area with strong sources of anthropogenic NMHC like the Los Angeles Basin (California), about 50% of the secondary organic aerosol is of natural origin (PANDIS et al., 1991). The estimate of 10 Tg/year for the anthropogenic organic aerosol reflects a NMHC source of 100 Tg/year and a conversion yield of 6% (Table I).
Nitrate aerosols Nitrogen oxides are emitted from a variety of natural and anthropogenic sources among which lightning discharges, soil microbes, fossil fuel combustion and biomass burning are the most important (LOGAN, 1983; WARNECK, 1988). About 50% of this NOx becomes oxidized to nitric acid, HNO3. Nitric acid can be removed by wet and dry deposition, or can become associated with the aerosol phase. The fraction of HNO3 which becomes nitrate aerosol is highly uncertain, and varies as a function of the amount and composition of the aerosol particles already present. If they consist mostly of sulphuric acid droplets, little HNO3 is incorporated. If, on the other hand, a substantial amount of alkaline material, such as soil dust or sea-salt aerosols, is present, HNO 3 is adsorbed onto these particles. In the presence of elevated concentrations of ammonia, ammonium nitrate aerosol can be formed. For the purposes of estimating the source flux of nitrate aerosol in Table I, annual NOx emissions from natural and anthropogenic sources of 20 and 32 Tg N, respectively, a HNO3 yield of 50% from NOx oxidation, and a conversion of 50% of HNO3 into the aerosol have been assumed. While this estimate is rather uncertain, it is also not very critical for the present discussion, since the amount of nitrate aerosol is relatively small in comparison to the amounts produced by SO2 oxidation and biomass burning,
356
Aerosol sources
and since the uptake of HNO3 onto pre-existing coarse aerosol particles has a negligible optical effect. Sulphate aerosols
Before the industrial revolution, which was fuelled by the availability of cheap and abundant energy from the combustion of fossil fuels, the atmospheric sulphur cycle was dominated by the emission of biogenic reduced sulphur compounds, especially dimethylsulphide (DMS), from marine plankton and land biota (ANDREAE, 1990; ANDREAE and JAESCHKE, 1992). These emissions account for about 50 Tg S/year, of which about 75% are from the oceans. Lower marine emissions of DMS (8-32 Tg S/year) have been proposed by BATES et al. (1987) based on extrapolation from a different data set. Since ocean and land areas emit roughly the same amount of biogenic sulphur gases per unit area, the biogenic sulphur source is more or less evenly divided between the Northern and Southern Hemispheres. In addition to their ejection of mineral dust, volcanoes also emit about another 6.5 Tg S/year (of course with a big year-to-year variation; BLUTH et al., 1993), so that the total natural sulphur source is about 50-60 Tg S/year. By 1960, the natural emissions of sulphur to the atmosphere were exceeded by anthropogenic SO2 emissions, predominantly from fossil fuel burning (CULLIS and HIRSCHLER, 1980, MOLLER, 1984). In the Northern Hemisphere, where some 90-95% of the anthropogenic sulphur sources are located, man-made emissions already exceeded the natural ones in the 1930s (Fig. 3). Estimates of "present-day" anthropogenic SO2 emissions vary: M611er extrapolates a 1990 value of 95 Tg S/year from an estimate of 75 Tg/year for 1977, SPIRO et al. (1992) give a 1980 emission rate of 78 Tg/year, while Cullis and Hirschler estimated the anthropogenic sulphur flux to have reached 104 Tg/year as early as 1976. LANGNER and RODHE (1991) suggest a lower anthropogenic sulphur source, 70 Tg/year for 1980, with little growth up to the present. Given the extensive deployment of emission controls in the developed countries over the last 10-20 years, a reasonable estimate for the present-day (early 1990s) anthropogenic sulphur source is 80 _+ 10 Tg/year. Projections into the future are ob-
200
100 Natural Sources 1 Natural Sources, N. Hemisphere 0
L-''~'~'---
1850
I
1900
t
I
I
1950
2000
I
I
2050
I
I
2100
Year Fig. 3. Estimated global emissions of sulphur to the atmosphere from anthropogenic sources from preindustrial times to the year 2100. Natural sources (global and northern hemispheric) are indicated for comparison.
357
Climatic effects of changing atmospheric aerosol levels viously highly dependent on assumptions about the further implementation of emission controls and about the rate of technological development in the developing world. Assuming a rapid increase of coal consumption in Asia, especially China, and a modest level of industrialization elsewhere in the developing world, GALLOWAY (1989) expects sulphur emissions to reach some 240 Tg by the year 2020. In the 1992 supplement to the IPCC Report, HOUGHTON et al. (1992) present a more optimistic view, suggesting that anthropogenic sulphur emissions will reach about 120 Tg/year by 2025 and will level out at about 150 Tg/ year around the year 2050 (Fig. 3). Aerosol production from precursor gases involves oxidation of DMS and other reduced sulphur gases to SO2 and other intermediate species, among them methane sulphonic acid (MSA), dimethyl sulphoxide (DMSO), and dimethyl sulphone (DMSO2). SO2 and some of the other species can then be further oxidized photochemically to sulphuric acid which then forms sulphate aerosol. These usually incorporate gaseous ammonia, in the remote atmosphere typically at a mole ratio of about 1:1. Methane sulphonate appears to become associated with pre-existing aerosols rather than forming new aerosol particles, while for sulphate both pathways are used. LANGNER et al. (1992) have modelled the atmospheric transformations of biogenic DMS and anthropogenic SO2, and estimate that about 50% of DMS is converted to sulphate. In the case of anthropogenic SO2, about 50% is thought to be removed by wet and dry deposition before it can be oxidized to sulphate. For DMS, deposition losses of the intermediate, SO2, probably play a lesser role, since DMS has a lifetime of about 2 days in the remote troposphere and can therefore be mixed away from the Earth's surface. The SO2 formed from its oxidation is thus less likely to be immediately redeposited in the vicinity of the source than anthropogenic SO2, which is injected close to the ground surface. On the other hand, in the case of DMS there are additional sinks, especially the wet and dry deposition of intermediates like MSA, DMSO, and DMSO2, which lead to a loss of biogenic sulphur before it can become incorporated into aerosol. In Table I, we therefore use a yield of 50% for the transformation of both biogenic DMS and anthropogenic SO2 to sulphate (or MSA) aerosol. In both cases, it is assumed that the final product has an ammonium-tosulphate ratio of 1:1. The total global aerosol source flux is about 3.5 Pg/year (1 Pg = 1015 g) (Table II). This is near the high end of the range of estimates by other authors, which typically fall between 2 and 4 Pg/year (JAENICKE, 1988; WARNECK, 1988; PREINING, 1991). The uncertainty in the total mass flux of aerosols is dominated by the uncertainties in the dust and sea-salt sources, both of which are difficult to assess and to define. Furthermore, as we will show below, these uncertainties do not influence our assessment of the role of anthropogenic aerosols in climate forcing very strongly, because they relate to the fraction of the aerosol which is optically the least efficient.
Climatic effects As mentioned above, aerosols interact with the Earth's radiation budget both directly by scattering and absorbing radiation, and indirectly by modifying the extent and radiative properties of clouds. Unfortunately, neither effect is related in a straightforward, linear fashion to a single variable, such as the total mass burden of atmospheric aerosol. Instead,
358
Climatic effects the effects are dependent on the size spectrum of the aerosol particles, on their chemical composition, on their spatial and temporal distribution etc. This makes an assessment of their climatic effects much more difficult than that of the long-lived and relatively evenly distributed greenhouse gases C Q , CH 4, and N20. The following paragraphs discuss the resuits of recent efforts to estimate the effects of changing atmospheric aerosol levels on climate. The discussion focuses on climate forcing, defined as an imposed change that modifies the planetary radiation balance and thus acts as the driving force of climate change. Climate forcing is expressed in terms of a change in energy input into the climate system (in W m-2). Using climate forcing rather than climate change makes the discussion of aerosol effects more straightforward, since it eliminates the numerous feedback processes, including changes in clouds, water vapour, ice and snow cover etc., which introduce a high degree of uncertainty into the discussion on climate effects of anthropogenic emissions. Thus, while the forcing due to a doubling of CO2 can be predicted quite precisely to be about 4-4.5 W m -2, the resulting global warming may lie somewhere in the range of 1.5-5.5~
depending
on the parameterization of the various feedback mechanisms. We will therefore use the estimate of present-day greenhouse gas forcing (about +2.0-2.5 W m-2; HANSEN and LACIS, 1990; HOUGHTON et al., 1990, 1992) as a yardstick against which we can measure aerosol climate forcings without having to address the complications of climate feedbacks. Direct radiative effects
The net effect of atmospheric aerosols is the sum total of the scattering and absorption of incoming solar (shortwave) radiation and outgoing (longwave, IR) radiation. In principle, only
Wavelength ( lxm ) 10 6.7
20
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\ 294 K \ kk
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3 x _= kr.,
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0
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500
",.
~,
1 "..
l
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1000
1500
2000
~ I..-, --i.....
2500
Wavenumber ( cm -1 ) Fig. 4. Infrared radiation emission from the Earth. The dashed lines show the emission from a black body (W m-2 per 10 cm-1 spectral interval) across the thermal infrared for temperatures of 294 K, 244 K and 194 K. The solid line shows the net flux at the tropopause (W m-2) in each 10 cm-1 interval, using a standard narrow-band radiation scheme and a clear-sky mid-latitude summer atmosphere with a surface temperature of 294 K. In general, the closer this line is to the dashed line for 294 K, the more transparent the atmosphere (from HOUGHTONet al., 1990).
359
Climatic effects of changing atmospheric aerosol levels the back-scattering of incoming radiation has a cooling effect, while the absorption of incoming radiation and the trapping of outgoing radiation all act in the direction of warming. The latter effect is, however, usually relatively minor, since particles interact most strongly with light which has a wavelength close to their physical size. Since most of the outgoing IR radiation is at wavelengths above 7/zm (Fig. 4), only the sea-salt aerosol and some desert dust aerosols have the potential to absorb significant amounts of outgoing radiation. Furthermore, most of the aerosol, especially the coarse particle aerosol, is present in the lowest kilometres of the troposphere, where its temperature (and therefore its radiational spectrum) is close to that of the Earth's surface. We can therefore ignore this term for most environmental situations. This view is supporte~l by the model calculations of C O A K L E Y et al. (1983) who find that the longwave effect (warming) is less than 2% of the shortwave radiative effect (cooling). However, some model calculations of the radiation balance over the Sahara desert do suggest that longwave absorption may play an important role in this environment (GRASSL, 1988 and references therein).
The effect of particle size The efficiency of scattering and absorption of visible light by aerosol particles is highly dependent on their size. Fig. 5 (from COVERT et al., 1980) shows the dependence of the mass extinction, scattering and absorption cross sections as a function of aerosol particle diameter for light with a wavelength of 550 nm and a particle complex refractive index, m = (1.50.02i), i.e. a moderately scattering and fairly weakly absorbing aerosol. Comparison between this figure and the typical size distribution of atmospheric aerosols (Fig. 6) shows that, by a remarkable coincidence, there is a maximum in the aerosol/mass size distribution at about 0.4/~m diameter, very close to the maximum of scattering efficiency (SHAW, 1987). This maximum is caused by the fact that aerosols with a diameter below 0.1/tm are effectively removed by diffusion and coagulation, while aerosols with diameters above 1/tm are rapidly deposited by impaction and precipitation. As a result, atmospheric turbidity is, under most circumstances, dominated by the effect of the particles in the range of 0.1-1/zm diameter (SHAW, 1980). This is clearly evident in Fig. 7 (from COVERT et al., 1980) which 10
,
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8
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m -- 1 95 - 0 9021"
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~1
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(~
6
~
t3"
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0.1
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Particle Diameter, D ( gm ) Fig. 5. Particle extinction, scattering and absorption cross-sections per unit of aerosol volume, as calculated from Mie theory (from COVERTet al., 1980).
360
Climatic effects 70 60
'
'
|
i
'
'
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'
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0.01
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10
50
Fig. 6. Typical bimodal atmospheric aerosol volume-size distribution (from COVERTet al., 1980). shows the extinction and scattering resulting from a typical particle size population. Ninety percent of the extinction is due to particles with diameters <2 ktm.
Global-mean radiative forcing perturbation by direct effect As a first step in the analysis of the climatic effect of changing atmospheric aerosol levels, we appraise their effect on global-mean radiative forcing. It must be emphasized here that this is a very crude way of looking at the problem, since the distribution of aerosols in the atmosphere is highly uneven due to their short lifetime and therefore their effects on radiative forcing are even more variable in space and time than the effects of the relatively evenly distributed greenhouse gases. The fact that even the radiative forcing due to the greenhouse gases is highly variable regionally is often little appreciated. This variability is due to the
32
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Diameter ( gm ) Fig. 7. Particle extinction and scattering-size distributions as calculated from cross-sections and size distributions in Figs. 5 and 6. The integral of dbext= 1.9 x 10-4. The integral of dbsp = 1.7 x 10 -4 m -1. Measured bsp = 1.7 x 10-4 m-1 on the occasion that the above distribution was made. In the calculation of bext, it is assumed that the absorption coefficient of the coarse mode is zero. It can be seen that about 90% of the extinction is due to particles <2/zm in diameter (from COVERT et al., 1980).
361
Climatic effects of changing atmospheric aerosol levels variations in solar zenith angle as a function of latitude, the regional differences in the water vapour content in the atmosphere and the average cloudiness, and the differences in surface albedo and surface temperature (KIEHL and BRIEGLEB, 1993). Surface temperature plays an especially important role since the outgoing infrared radiation flux, and thus the amount of energy that is available for trapping by the atmosphere, increases with the fourth power of the temperature (in Kelvin). The global-mean forcing due to the anthropogenic increase in the level of greenhouse gases by the year 1990 is estimated to be of the order of 2-2.5 W m -2 (HANSEN and LACIS, 1990; HOUGHTON et al., 1990, 1992). In the following discussion, an analogous parameter, the global-mean forcing due to the increase in anthropogenic aerosols, is used to assess the importance of the aerosol effect relative to the greenhouse gas effect. But it must be emphasized again, that due to the differences in regional and temporal distribution and in the physical characteristics of the aerosol effects, they should not be looked at as a simple subtractive compensation of greenhouse gas forcing. The magnitude of the direct effects of anthropogenic sulphate and biomass burning aerosols on climate has been estimated by CHARLSON et al. (1991, 1992) and PENNER et al. (1992), respectively. Initially, we will only consider the effect of scattering alone; effects related to light absorption and changes of convective stability will be discussed in later sections. The following discussion is based on the approach of CHARLSON et al. (1991, 1992). The globalmean change in shortwave radiative forcing is the product of the change in the global-mean albedo (i.e. the amount of radiation that is reflected back into space) and the global-mean solar radiation which impacts on the top of the Earth's atmosphere. Due to the spherical shape of the Earth, the mean solar energy flux through the top of the atmosphere is one quarter of the solar flux FT (1370 W m -2) through a plane perpendicular to the direction of propagation of the solar radiation. In order to estimate the direct radiative effects of aerosols, we also have to correct for the part of the Earth which is covered by clouds, Ac, since there is little effect from an aerosol enhancement above clouds (actually, there is a small amount of warming under most circumstances, but it is small enough to be ignored here (MORIYAMA, 1978). Thus, the global-mean shortwave forcing 6FA due to increased aerosol concentration is t~FA = - 8 8FT (1 - A e )t~Aa
(1)
where t~Aa is the change in planetary albedo resulting from increased aerosol concentration (the negative sign indicates cooling). The magnitude of A c can be obtained relatively accurately from global statistics on cloud coverage and is about 0.6 (WARREN et al., 1986, 1988). The problem thus is reduced to estimating the change in albedo caused by the introduction of aerosol to the atmospheric column. As long as the amount of aerosol present is relatively small and thus scatters only a modest amount of solar radiation, its optical depth t~a is much smaller than 1, and the planetary albedo changes in linear fashion with an increase in aerosol optical depth. (Aerosol optical depth ~a is defined using the Beer-Lambert law for the transmission of radiation as t~a =
-ln(I/lo), where I is the intensity of light transmitted through an aerosol-laden atmosphere and Io the intensity for an aerosol-free atmosphere). The requirement that t~a << 1 is fulfilled under most circumstances in the atmosphere, except in the presence of very high levels of
362
Climatic effects pollution. A value of 0.12 has been commonly assumed to be representative for the "background atmosphere", but recent assessments (CHARLSON et al., 1992) suggest that this value already represents a significant anthropogenic contribution. Thus, the albedo change due to an optically thin aerosol layer can be expressed as t~Aa = 2 T 2 ( 1 - A s ) 2 flt~ a
(2)
where T is the fraction of incident light transmitted by the air above the aerosol layer, As the mean albedo of the underlying Earth's surface, and fl the fraction of radiation scattered upward by the aerosol (LANGNER and RODHE, 1991; CHARLSON et al., 1991). Inserting equation (2) into equation (1), we obtain for the mean aerosol shortwave forcing, 6 F r = - f f F r T 2 (1 - A c)(1- A s )2 flt~a
(3)
In order to evaluate this expression, we need to obtain the optical depth of the anthropogenic contribution of the atmospheric aerosol. It is derived from the column aerosol burden by t~a "- a a f a (RH)B a
(4)
B a is the aerosol burden per unit area, a a the mass scattering cross section of "dry" aerosol
and fa(RH) the relative increase in scattering due to the increase in particle size associated with the uptake of water with increasing relative humidity (CHARLSON et al., 1984, 1991; COVERT et al., 1980). These parameters ultimately reflect the size distribution and refractive index of the aerosol, which is related to its scattering cross section based on Mie scattering theory. For sulphate aerosol in industrial regions, a a and fa(RH) have been studied in considerable detail; a a is typically about 5 m 2 g-1 SO42- and fa(RH) follows the deliquescence curves for various mixtures of ammonium sulphate and sulphuric acid (COVERT et al., 1980; TANG, 1980; WHITE, 1986; TEN BRINK et al., 1987; WAGGONER et al., 1981). For dry smoke
from biomass burning, very similar values of a a have been computed (4.5 m 2 g-l; FERRARE et al., 1990) and measured (5 m 2 g-l; RADKE et al., 1988). Aerosols from biomass burning also appear to be reasonably hygroscopic, so that a fa(RH) adjustment similar to that for urban aerosol is probably appropriate. Therefore, PENNER et al. (1992) estimate an extinction cross section of 8.0 m 2 g-1 for smoke under ambient conditions; this value is used in Table II.
Relative importance of aerosol sources Based on the preceding discussion, we can now make a first-order estimate of the relative climatic importance (with respect to the direct radiative effect) of the various types of aerosols listed in Table I. First, we need to consider that the lifetimes, and therefore the atmospheric burden of different aerosol types vary with size. In Table II, we assign lifetimes of 1 day to sea-salt (mass median diameter 8/tm), 4 days to mineral dust and nitrate (1-3/tm), and 5 days to sulphate (<1 m) aerosol (WARNECK, 1988; LANGNER and RODHE, 1991). Since the smoke from biomass burning is mostly released in the tropics during the dry season when precipitation removal is at a minimum, it should have a longer lifetime than the
363
Climatic effects of changing atmospheric aerosol levels sulphate aerosol, most of which is generated in the northern temperate regions, where the precipitation removal rate is highest. Therefore, a lifetime of 8 days is assumed for pyrogenic aerosols. Summing up the various aerosol types, one obtains a total global aerosol burden of 29 Tg, of which 24 Tg are natural and 5.7 Tg (19%) anthropogenic. Other authors have given somewhat lower estimates of the global aerosol burden, about 15 Tg (WARNECK, 1988; JAENICKE, 1988). It must be noted, however, that most of the discrepancy is due to mineral dust and sea-salt for which source estimates are highly uncertain. In terms of column aerosol burdens, a global burden of 29 Tg corresponds to a global mean value of 57 mg m -2, and an anthropogenic component of 11 g m -2. The significance of this apparently modest anthropogenic increase in global aerosol loading is amplified, however, because most of the anthropogenic component is in the submicrometre size fraction. The anthropogenic part of the submicrometre aerosol column burden amounts to about 7.4 g m -2 out of a total submicrometre burden of 17 g m -2, or about 43%. When the column aerosol burden values are multiplied with appropriate extinction cross sections, one obtains a global-mean aerosol optical depth of 0.14, of which the anthropogenic component is 0.075, or 52%. Or, looking at it from another perspective, anthropogenic influences have slightly more than doubled the global aerosol extinction from its natural value! Scattering accounts for most of the extinction represented by this optical depth, since only black carbon has a high enough absorption cross section to influence the global mean optical depth significantly. The natural aerosol component of optical depth is strongly influenced by the estimated magnitude of the mineral aerosol burden. If, for example, we were to adopt PROSPERO et al.'s (1983) estimate of mineral dust flux (250 Tg year-l), the natural optical depth would be reduced to 0.05, and the anthropogenic perturbation would result in much more than a doubling of the global-mean aerosol optical depth. However, in their very careful review, DUCE et al. (1991) estimate a dust flux of 910 Tg year -1 to the oceans alone, so that it appears very difficult to accept a global dust flux of less than 1000 Tg year -1, even if this amount is intended to represent only the optically most active fraction of the mineral dust (<2/tm diameter). The optical depths given in Table II may appear somewhat high, but are actually consistent with observations. Over the remote oceans, DURKEE et al. (1991) obtained optical depths typically in the range of 0.05-0.25 from analysis of NOAA satellite data. High values, up to 0.6, were found in regions influenced by dust storms and smoke from biomass fires. Consistent with the source distribution, values over the Northern Hemisphere oceans were typically higher (0.15 and above) than over the Southern Hemisphere oceans (0.10 or less). Sunphotometer measurements of optical depth at the Cape Grim observatory (Tasmania) also show annual mean values of ca. 0.05-0.10 in the rather pristine atmosphere of the Southern Hemisphere mid-latitude oceans (ETHRIDGE et al., 1984; FORGAN, 1990). Dominant among the anthropogenic components are sulphate aerosols and biomass smoke. For these components, the optical depth values in Table II are similar to those estimated by other authors (6(SO42-) = 0.04, CHARLSON et al. (1991); 6(smoke)= 0.03, PENNER et al. (1992); minor discrepancies are mostly due to slightly different source estimates and lifetimes. Finally, when we convert the aerosol optical depths to contributions to global-mean aerosol forcing, we obtain a value o f - 4 . 8 W m -2 resulting from the total aerosol loading, with an anthropogenic component of-2.5 W m -2, or about 52%. Note that this anthropogenic aero-
364
Climatic effects sol forcing term is practically identical to the present anthropogenic greenhouse forcing, albeit with opposing sign! Among the natural sources, mineral dust, biogenic sulphur, and organic aerosols from hydrocarbon oxidation appear to be the dominant contributors to aerosol radiative forcing. The source terms of all of these components may be subject to considerable change as a result of human activity and/or global climate change. Among the anthropogenic components, sulphate aerosol and biomass smoke have the strongest influence on radiative forcing. Further growth in the source strength of these aerosol types must be expected, and will probably lead to a situation in the not-too-distant future, in which anthropogenic particles dominate aerosol radiative forcing, at least in the Northern Hemisphere. It must be re-emphasized at this point that this is a very crude estimate which ignores all the complex interactions present in the system, and which assumes that optical effects are additive. But, as pointed out above, this is at least approximately true for thin aerosol layers, i.e. the remote atmosphere. The uncertainty in many of the parameters that are incorporated into these estimates is of the order of 10-50% for the relatively well-studied sulphate aerosol
(CHARLSONet al., 1992) but it is considerably higher for many of the natural aerosol types, especially the mineral dust and organic aerosols. If anything, the assessment made here probably overemphasizes the effect of the natural aerosols since it does not consider the fact that most of the scattering by coarse particles is in the forward direction, and that therefore at a given optical depth the large dust and salt particles reflect much less light back to space than the fine sulphate and smoke particles. Furthermore, the spatial and seasonal variability of the aerosol burden has been ignored in this discussion. Given the non-linearity of the scattering effects at higher dust loadings and corresponding higher optical depths, this probably also results in an overestimate of the global mean effect from mineral dust. The resolution of these problems will require detailed analyses using a combination of observations and general circulation models. Some recent model calculations (KIEHL and BRIEGLEB, 1993) result in much lower values for the absolute magnitude of aerosol radiative forcing. The overall uncertainty of the global mean aerosol burden and optical depth estimates given here is probably close to a factor of two. This does not, however, change the relative importance of the various components. The point of the estimates in Table II is mostly to show that (1) the types of aerosols which are predominantly in the size fraction below 1/tm have a climatic importance well beyond that expected simply based on their source strength in mass units, (2) that anthropogenic aerosols have a significant effect on atmospheric radiation when compared to natural aerosols, and (3) that the climatic effect of anthropogenic aerosols is significant relative to the effect of the greenhouse gases.
Warming effects resulting from absorption of radiation by aerosols As already mentioned above, aerosols not only scatter radiation, but also absorb certain amounts of short-wave and long-wave radiation. Both scattering and absorption of light result in a loss of radiation arriving at the earth's surface, and therefore lead to negative forcing at the surface. But light absorbed by aerosols still enters the Earth's radiation budget and produces a warming effect in the atmosphere. Siliceous materials, i.e. soil and desert dust, absorb strongly in the thermal infrared region (8-14/tm wavelength), and dense dust clouds can therefore lead to a trapping of infrared radiation in the same way as the trace gas green-
365
Climatic effects of changing atmospheric aerosol levels house effect. This may be an important consideration in assessing the climatic impact of increasing atmospheric dust loads resulting from desertification and changing wind intensities in the World's arid zones. In most cases, however, longwave absorption by aerosols is negligible, whereas the effect of shortwave absorption may be large enough to deserve consideration. During the first phase of the debate on the climate effect of aerosols, this phenomenon was the subject of considerable discussion, since the then prevailing data sets on the optical properties of aerosols were considerably biased towards urban, relatively strongly absorbing aerosols. In the recent discussions, this effect has been largely ignored. Fig. 8, modified by KELLOGG (1980) from a diagram by MITCHELL (1971), can serve as a basis for an assessment of the relative importance of scattering and absorption. It reflects the basic idea that aerosols lead to cooling if they have an albedo higher than the underlying surface, and to warming if they are darker. The absorbing versus scattering efficiency of aerosol particles can be expressed by the ratio
a/b of their absorption and backscattering coefficients, or by the related single scattering albedo to s, which is defined as b/(a + b). While industrial and urban aerosols tend to have a/b ratios of about 1-5 (~Os< 0.5), aged "rural" and remote aerosols of the Northern Hemisphere typically have a/b ratios below 0.2, corresponding to single scatter albedos >0.85. In a series of measurements at the Mauna Loa observatory, CLARKE and CHARLSON (1985) found a mean to s of 0.93 for the remote mid-tropospheric aerosol over the Pacific. They suggested soot particles at a concentration of some 10 ng m -3 to be the light-absorbing component of this aerosol, levels similar to those measured over the remote oceans by ANDREAE (1983) and ANDREAE et al. (1984). The single scattering albedo of smoke particles from forest fires in North America has been reported to be relatively low (0.83 _+0.11; RADKE et al., 1991),
him 0.005 0.01
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Fig. 8. The relationship between absorption-to-backscattering ratio (a/b) and the critical surface albedo (a) (lower scale), and between a/b and the imaginary index of refraction (nim, upper scale) for a given radius of particle (dashed line). Calculations are for real part of index of refraction equal to 1.5, and for a solar zenith angle of 65 ~ (an average value taking the globe as a whole). Shaded area indicates locus of some critical values when infrared radiation was taken into account along with solar radiation (from KELLOGG,1980).
366
Climatic effects while smoke from biomass burning in Brazil had single scattering albedos around 0.90 (KAuFaVIAN et al., 1992). Remote sensing studies have suggested even higher albedos (near 0.97) for biomass smoke (KAU~AN et al., 1990a,b). Overall, most aged anthropogenic aerosols seem to have ~os values >0.90 (a/b < 0.11). Combinations of aerosol a/b and surface albedo a which plot to the left of the dividing line in Fig. 8 lead to cooling, those on the right to warming. It is evident from this figure that only some very dark urban aerosols can lead to warming, and that anthropogenic aerosols remote from their sources with typical ~os values in the range of 0.85-0.95 will have a cooling effect unless they are over clouds, snow or ice. Soil dust aerosols typically have even higher ~os (0.97-0.99; CLARKE and CHARLSON, 1985), although very low values of 0.86 have been reported for the highly absorbing red Saharan dust (CARLSON and CAVERLY, 1977). Thus, most soil dust aerosols will also result in cooling, especially if they are blown over the oceans or over vegetated areas. Fig. 8 shows that dust aerosols over desert regions are near the dividing line between warming and cooling. The strong size dependence of aerosol optical properties can introduce a large degree of uncertainty into calculations of the radiative effect of such aerosols (GRASSL, 1988). For example, CARLSON and BENJAMIN (1980) suggested that Saharan dust aerosols would have a warming effect on the net local radiation balance, whereas FOUQUART et al. (1987a,b) point out that they could lead to a net energy loss, i.e. cooling, depending on the amount of submicrometre-size particles present. It is obvious from this discussion that there is a great need for additional measurements of the size distributions and size-dependent optical properties of atmospheric aerosols. As we have shown, while the net effect of aerosols on the global radiation balance is, in most cases, in the direction of cooling, there is a significant amount of radiation absorbed by atmospheric aerosols, so that the locus of some of the solar energy absorption is shifted from the Earth surface to the atmosphere. For example, PENNER et al. (1992) estimate that biomass smoke aerosols absorb about 0.5 W m -2 (globally averaged and adjusted for cloud cover). The absorption of radiation leads to reduction of about 0.3 W m -2 in the solar radiation absorbed at the ground (adjusting for ground albedo and cloud cover). This leads to a net increase of 0.2 W m -2 in the heating of the surface/atmosphere system due to the absorbing component of the smoke. At the same time there is a 0.8 W m -2 shift of energy absorbed at the ground to energy absorbed within the atmosphere. Here, it leads to a local warming aloft, which influences the thermal stratification of the troposphere, as noted already by CHARLSON and PILAT (1969). This effect is particularly relevant in situations characterized by optically thick aerosol layers, e.g. dust storms. In general, warmer air aloft results in more stable stratification, less convection and consequently also a reduction in the likelihood of precipitation from afternoon convective clouds. Furthermore, a reduction in the amount of heating at the ground (which results from the presence of any kind of aerosol, regardless of its COs) reduces the amount of water evaporated from the surface due to a reduction in the amount of energy available for latent heating. This in turn results in less cloudiness and precipitation, which, in principle, should act to reduce the cooling effect of clouds. MITCHELL (1971) estimated that this effect could lead to reductions in evaporation by some 1-3%, an amount which, if it resulted in a reduction of cloud cover by a similar percentage, would have a pronounced climatic significance. He concludes: "Further investigations of this and other possible hydrometeorological effects of
367
Climatic effects of changing atmospheric aerosol levels an atmospheric aerosol are clearly warranted", a statement which remains valid after 22 years.
Modelling the direct radiative effect of aerosols While no complete global models incorporating the temporal and spatial distribution of the various aerosol types have yet been assembled, some more sophisticated calculations have been made for specific cases. COAKLEY et al. (1983) used assumed aerosol optical properties and a latitudinally varying distribution of "natural background aerosol" in a latitudedependent climate model. They conclude that this background aerosol leads to a cooling of about 3 K, with the highest cooling rates at high latitudes (up to 5-6 K), and "that the present background aerosol exerts a rather substantial influence on the present climate ... comparable in magnitude but opposite in sign to what would be expected for a doubling of atmospheric CO2". It should be noted that their calculations are based on an assumed "natural background aerosol" which is, however, based on data from anthropogenically influenced regions in the Northern Hemisphere, and that their model actually "is representative of a symmetric planet for which both hemispheres correspond to the Earth's Northern Hemisphere". If we take into account that in the present view the submicrometre aerosol loading in the Northern Hemisphere may be about twice the natural level, it follows that anthropogenic aerosols could be cooling the Earth by about 1-2 K at present by the direct radiative effect alone. First attempts to introduce aerosol effects into three-dimensional models at fixed aerosol loads and unchanged cloud properties also showed cooling (TANRg et al., 1984). GRASSL (1988) discussed the combined direct and cloud-optical effects of anthropogenic aerosol input using 2-D model calculations with assumed aerosol size distributions and refractive indices. Based on calculations by NEWIGER (1985), REHKOPF (1984) and GRASSL and LEVKOV (1984), he concluded that in cloudless areas aerosol can lead to zonal-average negative forcings up to -7 W m -2 in the northern mid-latitudes, while the increase in cloud albedo leads to a forcing up t o - 3 . 0 W m -2, with a global mean forcing of about -(0.7-1.0) W m -2 by the combined effects. Effects were significantly greater in summer than in winter. CHARLSON et al. (1991) obtained a global distribution of sulphate aerosol from the threedimensional chemical-transport model of the sulphur cycle by LANGNER and RODHE (1991). They used the radiation calculations described above to obtain a global distribution of sulphate aerosol radiative forcing by natural and anthropogenic sulphates. They estimated that natural sulphate aerosols produce a global mean forcing of-0.42 W m -2, and that anthropogenic sulphates add 0.11 W m -2 in the Southern and 1.07 W m -2 in the Northern Hemisphere. Peak anthropogenic forcings (up to 4 W m -2) were predicted over the eastern US, southeastern Europe, the Near East, and China (Fig. 9).
The most detailed modelling study on the direct effect of aerosols to date was made by KIEHL and BRIEGLEB (1993), who investigated the influence of greenhouse gases and natural and anthropogenic sulphate aerosols on radiative forcing in a three-dimensional diagnostic climate model. They also obtained the abundance and distribution of the sulphate aerosol from the chemical-transport model of LANGNER and RODHE (1991). While they find a geographical distribution of the anthropogenic radiative forcing similar to that of CHARLSON et
368
Climatic effects , t l l i l l i l l i l t i l l i l , , l , , l , , l , , l , , l , ,
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al. (1991), the magnitude is generally less by a factor of 2. About half of this difference is because CHARLSON et al. (1991) did not account for the wavelength dependence of the extinction coefficient for sulphate aerosol. Much of the remaining discrepancy is due to differences in the asymmetry parameter (the ratio between upward and downward scattered radiation) used by the two groups. KIEHL and BRIEGLEB (1993) estimate a global mean anthropogenic sulphate forcing of 0.3 W m -2, and a Northern Hemisphere forcing of 0.43 W m -2. They find that over considerable areas of the Northern Hemisphere the negative forcing from aerosols nearly compensates the greenhouse gas forcing. In some regions of Europe, the eastern United States and China, aerosol negative forcing even exceeds the positive forcing by the gases and results in negative net forcing. The preceding studies only include the effect of sulphate aerosols and do not account for other anthropogenic aerosols, particularly those from biomass burning. Inclusion of these sources can be expected to roughly double the sulphate aerosol effect (PENNER et al., 1992). A 3-D modelling study including aerosols from other sources is highly desirable, and must take into account the differences in the source distributions and optical properties of sulphates, biomass burning smoke, and other materials. Overall, we can estimate that the direct radiative forcing from anthropogenic aerosols falls somewhere between 0.6 and 2.5 W m -2, with a best guess probably near 1 W m -2. Indirect
effects through
perturbation
of cloud properties
A substantial fraction of incident solar radiation (some 27%) is reflected by clouds, which cover on average about 60% of the Earth. Satellite measurements show that the average albedo of clouds is about 0.45, and that most clouds have albedos in the range 0.25-0.65 (COAKt.EY and DAVIES, 1986). The albedo of a cloud depends on a number of properties: its thickness, liquid water content, droplet number concentration and size distribution, and solar elevation. Obviously, other things being equal, the more liquid droplets that lie in the path of the radiation, the higher the likelihood is that photons get scattered backwards and leave the Earth towards space rather than being transmitted to the Earth's surface. Thus, everything else being constant, the albedo of a cloud increases, and its transmittance decreases
369
Climatic effects of changing atmospheric aerosol levels with its thickness. On the other hand, if we keep the cloud thickness constant, but increase the liquid water content (LWC, the amount of liquid water per volume air), albedo also increases and transmittance decreases. Finally, at constant liquid water path (LWP, the vertically integrated liquid water content), cloud albedo also depends on the droplet size distribution. Since the scattering interactions, which result in the backscattering of light by clouds, happen at the liquid-gas interface of the droplets, an increase in the interface area in the light path leads to an increase in the amount of light scattered. At constant liquid water path, this can be effected by a reduction in the average drop size, which results in the presence of more droplets within a given air volume. Liquid water content (L), droplet number concentration (N), and effective radius (re) are related by
L= 4 ~re3N
(5)
The relationship between cloud albedo (ACT), sun angle and cloud optical properties can be summarized by the following equation:
ACT =
fl(#o)6c //~o 1 § fl(~o)Sc / IZo
(6)
where/t o is the cosine of the solar zenith angle, fl(/t0) is the fraction of light scattered in the upward direction for sunlight incident on the cloud at angle/t o (for single scattering), and 6c is the optical depth of the cloud (COAKLEY and CHYLEK, 1975; CHARLSON et al., 1992). The upward fraction fl is a slowly varying function of/~o and 6c (STEPHENS, 1978). Cloud optical depth is dependent on the effective radius (re) of the cloud droplet population, the number concentration of droplets (N), cloud thickness (Zc), and the average extinction efficiency of the droplets (Qext) which for cloud droplets of a radius much larger than the wavelength of visible light can be approximated by a constant value of 2 (CHARLSONet al., 1992): c = ~r2 QextZc
(7)
or, inserting equation (5),
0 C = ~QextZc
N 113
(8)
so that, at constant LWC, the cloud optical depth depends on the cube root of the droplet concentration. The number of cloud droplets in a cloud is regulated by the concentration of cloud condensation nuclei (CCN), i.e. aerosol particles which are soluble enough and large enough to serve as nuclei for the growth of water droplets from supersaturated water vapour. The presence of CCN is critical, since the formation of droplets purely from gaseous water molecules requires that an energy barrier associated with the very small radius of curvature of the in-
370
Climatic effects cipient droplet must be overcome. This would only happen at supersaturations of some 300%, which are never reached in the real world since the condensation of water vapour on a pre-existing particle involves a much lower energy threshold, and thus happens at much lower supersaturations (some tenths of a percent). Consequently, when a rising air mass exceeds the water vapour saturation level (i.e. a relative humidity of 100%) by a certain critical level, condensation of water begins on the largest and most soluble aerosol particles. This critical supersaturation level is a function of the mass of soluble material in a given aerosol particle (Fig. 10). Below this level, the particle remains stable as a hydrated aerosol particle, above it the nucleus grows rapidly into a cloud droplet. The fraction of particles which become involved in the formation of cloud droplets depends on the size spectrum of the aerosol, the chemical composition (solubility) of the particles, the rate of ascent of the air mass, and the total number of CCN present. CCN number concentrations vary over a wide range, from a few tens per cm 3 over the remote oceans, especially during the winter season, to about 100-200 cm -3 over warmer ocean areas, to hundreds and thousands per cm 3 in continental areas, depending on the level
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Fig. 10. Typical marine aerosol size distribution. Both (a) and (b) are based on three overlapping, log normally distributed particle populations with volume mean diameters D of 3.0, 0.3 and 0.03/zm; geometric standard deviations of 2.0, 1.6 and 1.5; and total numbers (per cm 3) of 0.4, 100 and 200 for the coarse, accumulation and nuclei modes, respectively. The data are displayed so that the area under each curve is proportional to total particle volume (a) or number (b). Also shown at the bottom of (b) is the critical supersaturation corresponding to each particle size (assuming a composition of pure ammonium sulphate). The vertical lines show the range of typical maximum supersaturations for marine stratiform clouds (from ANDERSONet al., 1992).
371
Climatic effects of changing atmospheric aerosol levels of pollution (WARNERand TWOMEY,1967; HOBBS et al., 1970; BRAHAM, 1974; SCHMIDT, 1974; TWOMEY et al., 1978; HOPPEL, 1979; SAX and HUDSON, 1981; HUDSON, 1983; GRAS, 1990; HUDSON, 1991; HUDSON and FRISBIE, 1991; ANDREAE et al., 1994, 1995; ANDREAE, unpublished data). Sea-salt particles make up only a small fraction of CCN in the marine boundary layer; their number concentration is typically between 1 and 10 cm -3 (RADKE, 1968; HOBBS, 1971; PRUPPACHER and KLETT, 1978). The rest is predominantly made up of sulphate particles, which over pristine ocean areas are produced from the photooxidation of DMS (ANDREAE,1990; CHARLSONet al., 1987). At CCN concentrations of up to a few hundred per cm 3, a large fraction of the CCN present develops into cloud droplets (BIGG, 1986), while at higher concentrations (> 1000 cm -3) the competition for available water vapour limits the number of particles which are activated to grow into cloud droplets (LEAITCH et al., 1986). Unfortunately, there are few studies which provide simultaneous measurements of CCN and droplet concentrations in stratus clouds. Most of the early work (e.g. TWOMEY and SQUIRES, 1959; TWOMEY and WARNER, 1967) was done in convective clouds, where changing droplet number concentrations would have relatively little climatic effect. But where such measurements have been made, they confirm the influence of CCN concentrations on cloud droplet numbers. HUDSON (1983), for example, found good agreement between CCN and cloud droplet concentrations in marine stratus off the California coast. Similarly, HEGG et al. (1991) observed a highly significant correlation between cloud droplet numbers in marine stratus and CCN concentrations in the boundary layer in the range of 25-120 cm -3. PUESCHEL et al. (1986) investigated the presence of cloud droplets and interstitial aerosol particles in relation to air mass origin at Whiteface Mountain, New York State. In clean marine air masses from the North, 50% of a total of 130 particles per cm 3 had been activated, in background continental air 37% of 350 cm -3, and in polluted air masses 17% of 4350 cm -3. (The non-activated particles measured in this experiment were in the size class >0.2/tm diameter, and would probably have been registered as CCN by a CCN counter.) Thus, while there is no simple linear relationship between the CCN concentration present in a given air mass and the number of cloud droplets that will form if it becomes supersaturated, it is obvious that an increase in CCN will lead to higher cloud droplet concentrations, in this case from 64 to 750 cm -3 when going from clean to polluted air masses. Similar conclusions were drawn by LEAITCH et al. (1992), who investigated the relationship between cloud water sulphate concentration (as an indicator of the degree of anthropogenic pollution) and cloud droplet number over Ontario, Canada, and found highly significant, but far from linear correlation. In these relatively polluted air masses with droplet number concentrations typically in the range 110-510 cm -3, droplet number increased approximately with the 1/5 power of cloud water sulphate concentration. Clearly, cloud optical properties are most sensitive to variations in CCN concentrations in relatively clean areas of the world, especially the remote oceans, while in highly polluted areas cloud droplet numbers are nearly saturated and further addition of aerosol will have much less consequence for cloud properties. Besides changing the albedo of clouds, variations in CCN concentrations and the resulting changes in droplet size also influence the probability that raindrops can form from the cloud droplets. A cloud containing a large number of small droplets is likely to persist longer and eventually evaporate again without producing rain than a cloud in which the same amount
372
Climatic effects of water is distributed over a smaller number of larger droplets. Thus, an increase of CCN concentration increases the lifetime of clouds, and consequently the fraction of the Earth that is covered by cloud (BRAHAM, 1974; FITZGERALD and SPYERS-DURAN, 1973; ALBRECHT, 1989; TWOMEY,1991). This would also lead to an increase in the Earth's albedo, and cause cooling. Since the probability of precipitation is also changed, enhanced cloud stability would also influence the distribution of water vapour in the atmosphere. This effect can be illustrated by SIMPSON and WIGGERT's (1969) model calculations for clouds with "virtually identical dynamics" but differing CCN concentrations: At N = 50 cm -3 the cloud produced 1.5 g m -3 of rainwater, whereas at N = 2,000 cm -3 it precipitated only 0.19 g m -3. Such a range in CCN concentrations is typical for the present-day atmosphere, with the lower values being typical for clean marine areas, and the higher values characteristic of mildly polluted continental regions. Water vapour is the most important greenhouse gas, and is responsible for a large fraction of the infrared radiation retained by the atmosphere. Consequently, a large-scale change in the horizontal and vertical distribution of water vapour has the potential for significant changes in the energy budget. These effects are so complex, however, that they are beyond our current modelling capabilities. In the case of marine stratus, an increase in CCN should reduce drizzle production, resulting in higher cloud LWC. Drizzle is very commonly associated with marine stratus clouds, especially under conditions of very low CCN concentrations, as for example during winter at Cape Grim, Tasmania (E. K. BIGG, personal communication, 1987). In addition to regulating the LWC of stratus clouds, drizzle also has an important effect on the diurnal cycle of marine clouds due to the cooling effect of evaporating drizzle droplets underneath the cloud (NICHOLLS, 1987). This evaporation may create a stable layer below the cloud and thus uncouple the cloud from the fluxes of heat and water vapour from the sea surface. As a result, the cloud evaporates more easily due to solar heating, and only forms again in the evening. A reduction of drizzle due to increased CCN would disrupt this cycle and stabilize daytime marine stratocumulus, enhancing cloud cover and consequently albedo. Drizzle is the dominant sink of CCN at low CCN concentrations, since other sink mechanisms (coagulation and coalescence) are not effective at low particle densities. Thus, the CCN concentration in clean marine air may be controlled by the relationship between particle production and removal by drizzle (BAKERand CHARLSON,1990). At higher rates of CCN production and consequently higher CCN levels, drizzle production is suppressed, and CCN concentrations must rise until they are limited by coagulation and coalescence removal. These relationships may explain the tendency for CCN numbers to fall into two distinct ranges, one around 20-200 cm -3 and another around 1000 cm -3. Field evidence that the inhibition of drizzle production by elevated CCN may have an important influence on the LWC in marine stratus comes from an analysis of the enhancement of cloud albedo due to ship's emissions (RADKEet al., 1989; ALBRECHT, 1989). Not only were cloud droplets smaller in the ship tracks, but liquid water concentration was higher by 40-100%. This LWC increase had a two times greater effect on cloud reflectivity than that of the change in droplet size. Clouds interact not only with the incident shortwave radiation, but also with the infrared radiation emitted by the Earth. For this reason, they also have a greenhouse function. Therefore, an increase in cloud density or fractional cloud cover should, in principle, also have a warming component in addition to their cooling effect. However, this warming effect is very
373
Climatic effects of changing atmospheric aerosol levels small, since tropospheric clouds are nearly opaque to infrared radiation already, and a further increase in absorbance has little additional effect. A fractional increase in low clouds caused by increased CCN concentrations would result in a proportional increase in longwave absorption, but for low clouds with temperatures relatively close to that of the Earth's surface, the cooling component dominates.
Estimating indirect radiative forcing The effect of changing CCN concentrations on global climate was assessed quantitatively by CHARLSON et al. (1987) in connection with the discussion of a hypothesis which linked the production of biogenic sulphur gases by marine phytoplankton to the concentration of sulphate aerosol in the atmosphere, and thus to climate (Fig. 11). These authors used the relationships between droplet concentration, effective droplet radius, and cloud thickness given in equations (5) to (8) above to predict the changes in cloud albedo resulting from changes in CCN, and showed that under the conditions of the clean marine atmosphere, modest changes in CCN concentrations would significantly influence cloud albedo. This is summarized in Fig. 12, which shows the change of cloud albedo as a function of the original albedo of the reference cloud and the change in CCN number density. These results indicate that cloud-top albedo is most sensitive to change in cloud droplet number (N) when the original albedo of the cloud is in the range 0.2-0.7, i.e. for clouds of average and below-average al-
Radiation budget
1-
Cloud condensation nuclei
Global temperature
C- -3
Sulfate aerosol
Climate feedbacks
+
S02 DMS
I
DMS
d, + o r - ?
+ or-
Phytoplankton abundance and speciation
~
9 "
e Ocean
Marine ecology
Fig. 11. Climatic feedback loop linking oceanic phytoplankton, emission of DMS, atmospheric sulphur chemistry, cloud albedo and climate. The plus and minus signs indicate the sign of the feedback.
374
Climatic effects
1.0
Relative number-density of cloud droplets N/N o 6 4 3 2 1.5 1.00.8 0.6 0.4 0.3 0.2 0.15 +0.(
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Relative effective radius of droplets reff/reff o Fig. 12. Change (Aa) of visible albedo (0.6-/tm wavelength) at cloud top caused by changing droplet number-density N while holding vertically integrated liquid water content (liquid water path, LWP) constant. Aa is plotted as a function of the albedo of the reference cloud and the effective radius (reff, the surface-area-weighted mean radius) of the dropsize distribution relative to that of the reference cloud (reff0) (from CHARLSONet al., 1987). bedo, such as stratus clouds. For such clouds, an increase in N by 1% would increase cloudtop albedo by about 0.08%. CLAW estimated that a change in CCN concentration over the oceans by +30% would result in a decrease in the effective droplet radius by 10%. This would change the albedo of low stratus and stratocumulus clouds (the type of cloud most sensitive to this effect) by +0.020 (2%) at the top of the cloud and for the wavelength region 500-700 nm. Adjusting for the absorption in the 0.6/tm band of ozone in the layer of air between the top of the cloud and the top of the atmosphere reduces this albedo change to +0.018 (WISCOMBE et al., 1984). Finally, when the entire solar spectrum is considered, the increase in top-ofatmosphere (TOA) albedo over the cloud is reduced to 0.016, since cloud albedo is lower in the near-infrared than in the visible part of the spectrum (SHINE et al., 1984; WISCOMBE et al., 1984). On the basis of a more accurate method of resolution of the radiative transfer equation than the simplified approach used by CLAW, FOUQUART and ISAKA (1992), come to essentially the same estimate of the effect of a 10% change in effective radius on TOA albedo. When the area covered by the type of cloud modelled here is taken into account, an average albedo change for the total surface area of the Earth of +0.005 is calculated. As discussed above for the case of the direct effect of aerosols, there is a linear relationship between a change in global mean albedo and the resulting change in radiative forcing: c~Fc = 1
375
FTOAGM
(9)
Climatic effects of changing atmospheric aerosol levels Consequently, an albedo change of +0.005 would lead to a negative radiative forcing of -1.7 W m -2, or change in global-average surface temperature o f - 1 . 3 K. This assumes, of course, that a change in CCN and N does not alter the average area covered by clouds, i.e. effects on cloud lifetime are ignored here. Following the publication of the CLAW hypothesis, SCHWARTZ (1988) argued that, if this hypothesis were correct, the production of sulphate aerosol from anthropogenically released SO2 would have already led to a pronounced increase in CCN concentrations in the Northern Hemisphere. Based on an assessment of the rather uncertain database presently available on the concentrations of sulphate aerosol over the world oceans, and assuming that number concentration would be proportional to mass concentration, he postulated that CCN in the Northern Hemisphere were greater by 30% than in the relatively unpolluted Southern Hemisphere, and that therefore there should be a radiative forcing o f - 2 W m -2 due to the indirect effect from anthropogenic sulphate aerosols in the Northern Hemisphere. Schwartz's assumption that the enhancement in CCN number concentration is the same as the enhancement in mass concentration is probably not justified, since the particle number density decreases faster during transport than the mass concentration. CHARLSONet al. (1992) assume a 15% global mean enhancement in N, and obtain a global mean forcing o f - 1 W m -2 from cloud effects. They emphasize that there is a great amount of uncertainty (at least a factor of 2; KAUFMAN et al., 1991) related to the enhancement of CCN number concentrations and to the resulting enhancement of cloud-droplet number density. Most authors have considered only the anthropogenic sulphate aerosol as a source of increasing CCN concentrations. However, other aerosol sources, especially biomass burning, also release large amounts of aerosols which may act as CCN (WARNER and TWOMEY, 1967; HOBBS and RADKE, 1969; DI~SALMAND, 1987; RADKE, 1989; CRUTZEN and ANDREAE, 1990; HUDSON et al., 1991; ROGERS et al., 1991; PENNER et al., 1992). Smoke particles from biomass burning appear to be effective CCN in spite of the fact that they consist predominantly of organic material (HALLET et al., 1989; HUDSON et al., 1991). This is because soluble materials, like nitric, ammonia, and short-chain organic acids, are rapidly incorporated from the gas phase of the smoke into the aerosol and thus render it hygroscopic (ANDREAE et al., 1988, TALBOT et al., 1988). RADKE et al. (1991) estimated the global production rate of CCN from biomass burning to be in the range of 102~
particles per sec-
ond, which corresponds to a global average pyrogenic CCN concentration of 102-103 cm -3, assuming a CCN lifetime of 5 x 105 s and a scale height of 1 km. In laboratory combustion experiments with Guinean savanna vegetation, PHAM-VAN-DINH et al. (1994) found CCN (at 0.1% supersaturation) emission factors around 2 x 1011 g-1 dry matter, with the highest emission factors observed during the smoldering stage. This corresponds to a CCN production rate of (3-6) x 1019 s-1 for biomass burning in the African savannas. Based on airborne measurements over savanna fires in southern Africa, the global production of CCN from biomass fires is estimated to be about 2-4 x 102~s-1 (M. O. ANDREAE, unpublished data). Most of these CCN will be present over the continents, and a considerable concentration decrease must be expected during transport over the remote oceans, where they would have the strongest effect on climate. However, maps of the distribution of aerosol optical depth over the oceans clearly show plumes extending over thousands of kilometres from the biomass burning regions (HUSAR and STOWE, 1994). Therefore, PENNER et al. (1992) have estimated that the cooling effect of smoke aerosols from biomass burning via the enhancement
376
Climatic effects of cloud albedo is about 1 W m -2, if a mean pyrogenic CCN concentration of 10 cm -3 prevails over the remote oceans. This forcing due to biomass burning is of a magnitude similar to the cooling due to sulphate CCN. The soot content of smoke and industrial aerosols adds a light-absorbing component to cloud water, which in principle could reduce the albedo of clouds and counteract the whitening effect of larger droplet numbers (TWOMEY, 1977). The resulting increased absorption would have the strongest effect in the case of optically thick clouds, which have a high initial albedo and are not appreciably brightened by increasing droplet number. This prediction is confirmed by satellite observations made on Amazonian cumulus clouds, which showed that in spite of a reduction of droplet size from 15 to 9/zm due to dense smoke from biomass burning, cloud reflectance decreased from 0.71 to 0.68 (KAUFMANand NAKAJIMA, 1993). On the other hand, the albedo of warm, relatively thin clouds with an initial albedo of 0.30.4 increased by 0.08-0.15 in the presence of smoke aerosols (Y. J. KAUFMAN, 1993, personal communication). On a global scale, the effect of increasing albedo is thought to dominate over that of increased absorption (TWOMEYet al., 1984). This is supported by the observation of increased albedo in marine stratus clouds which have incorporated stack effluents from ships at sea (COAKLEY et al., 1987; KING et al., 1993). Radiative transfer calculations based on the measurement of light absorbing substances in cloud droplet nuclei in marine clouds impacted by polluted continental air also suggest that light absorption from soot does not significantly influence the cloud optical properties under normal circumstances (TWOHYet al., 1989). Direct evidence for a net cloud-brightening effect of aerosols is also found in satellite observations, which show higher cloud reflectance in areas with elevated aerosol loadings (DURKEE, 1994). However, in a satellite study of low-level cloud albedo over the North Atlantic, FALKOWSKI et al. (1992) was able to observe increased cloud albedo due to anthropogenic sulphate only over the area immediately adjacent to the North American coast. Marine sulphur emissions appeared to govern the variability in cloud albedo over most of the North Atlantic. As in the case of the direct aerosol effects, the cloud effect is very unevenly distributed in space and time. Obviously, it is limited to cloudy regions, while the aerosol effect is significant only in cloud-free areas. However, an assessment of the regional distribution of the impact of the enhancement of cloud albedo is made extremely difficult by the very strong dependence of the albedo increase on the absolute CCN concentration. Figure 13 shows the dependence of albedo susceptibility (dA/dN, the increase in albedo per unit increase in CCN concentration) on CCN concentration and cloud albedo. This figure shows that the strongest effect would result from an even relatively slight increase in CCN in the cleanest and most remote parts of the world. Since the aerosol or its precursors can travel over considerable distances (thousands of kilometres) from their sources, especially in the free troposphere, the effects could be on a hemispheric scale. While the mass concentration of anthropogenic aerosols at such large distances might be low, an addition of even some 10-20 CCN cm -3 into a clean marine air mass with some 50 CCN cm -3 would have a considerable effect on cloud albedo. At the present time, it is usually suggested that the impact of increasing CCN is felt predominantly in the Northern Hemisphere, although the effect of smoke from biomass burning as well as SO2 emissions from increasingly industrializing regions in the developing world may already significantly impact the Southern Hemisphere. Smoke from
377
Climatic effects of changing atmospheric aerosol levels
0.3
100 1000
Albedo
Fig. 13. Susceptibility of albedo to change in cloud droplet concentration (dA/dN) for different conditions. The vertical unit is per cent reflectance per additional droplet cm -3 (from TWOMEY, 1991). The horizontal axes are droplet concentration (N, in cm-3) and initial cloud albedo. biomass burning is detectable almost everywhere over the remote oceans, especially in the areas downwind from Africa and South America. Evidence for this is the presence of soot aerosols and correlated levels of submicrometre potassium-rich particles over the remote oceans (ANDREAE, 1983; ANDREAE et al., 1984; CLARKE, 1989). Given the low CCN numbers typical of the remote marine atmosphere, an addition of only 10 pyrogenic CCN per cm 3 would be enough to cause a global cooling forcing of 1 W m -2 (PENNER et al., 1992). Cloud optical effects of aerosols through changes in droplet size and increased cloud stability have not yet been modelled in the necessary detail. Some calculations with different versions of the NCAR CCM model suggested strong effects resulting from relatively high increases in droplet concentrations. SLINGO (1990) suggested that a greenhouse forcing of ca. +4 W m -2 could be counterbalanced by an increase of 80-185% in the droplet concentration of low clouds, or by a 40% droplet increase in clouds at all levels. GHAN et al. (1990) increased the droplet concentration of marine clouds from 50 to 200 cm -3 and kept continental clouds at a constant droplet concentration of 200 cm -3, which resulted in a negative forcing o f - 6 W m -2. Their simulation suggests that this cooling effect would be reinforced by a concomitant increase in cloud fraction of 3.5%.
Estimate of total (direct plus cloud) anthropogenic climate forcing by aerosols Our estimate for the present-day direct forcing by anthropogenic aerosols ranges between -0.6 W m -2 (based on the Kiehl and Briegleb approach, with aerosol sources other than sulphate added) to -2.5 W m -2 (Table II, based on CHARLSON et al., 1991, radiation equations). The biomass burning term may have to be discounted by one-third, based on the argument that while at present practically all biomass burning is anthropogenic, there was about 1/3 of the present level of emissions already present around 1850 (ANDREAE, 1993). This reduces the range of estimates for the direct effect to -(0.5-2.0) W m -2. The cloud-optical effects of sulphate and pyrogenic aerosols have each been estimated to be of the order o f - 1 W m -2 (CHARLSON et al., 1991; PENNER et al., 1992). Discounting for pre-1850 biomass burning,
378
Evidence for the climatic impact of anthropogenic aerosols and considering that these estimates are uncertain by at least a factor of two, we obtain a range o f - ( 0 . 8 - 3 . 3 ) W m -2. Finally, adding direct and indirect terms yields a range of -(1.3-5.3) W m -2 for the total aerosol effect. Using a two-dimensional climate model and rather conservative assumptions, KAUFMAN and CHOU (1993) estimate a value o f - 0 . 4 5 W m -2 for the total radiative forcing due to aerosols from anthropogenic SO2 emissions. Given that sulphate accounts for about one-half of the anthropogenic forcing, the total effect based on the KAUFMAN and CHOU (1993) model would be about-0.9 W m -2, slightly below the lower limit of the range proposed here. It is clear, however, that even the lowest estimates are of significance relative to a present-day greenhouse forcing of 2.3 W m -2, especially considering that we have ignored the possibility of a LWC increase in our estimate of cloudoptical forcing, which may enhance this effect considerably.
Evidence for the climatic impact of anthropogenic aerosols Unfortunately, the influence of changing aerosol levels on climate cannot at this time be documented based on direct measurements of trends in global albedo, cloud albedo, or cloud area (CHARLSON, 1988). While there is a clear record of increasing cloud area by as much as 10% in North America (HENDERSON-SELLERS and MCGUFFIE, 1988, 1989), this could be explained by increasing CCN levels as well as by a number of other factors. Planetary albedo has been measured from satellites for three decades, but trends at the required resolution cannot be extracted from these data due to changes in sensor characteristics and calibration. Possibly, detailed analysis of data from the Earth Radiation Budget Experiment may provide some insight into the relationships between clouds, aerosols and climate, but this remains to be accomplished. For the time being, we are limited to more circumstantial evidence for an examination of the linkage between aerosols and climate.
Aerosol trends The growth of anthropogenic aerosol sources over the last 150 years is indisputable, but direct evidence for a global increase in aerosol concentrations in the atmosphere is rather scarce. Due to the large variability of aerosol concentrations in space and time, secular time trends are much more difficult to observe than for the long-lived and relatively evenly distributed greenhouse gases. Measurements of optical depth at remote mountaintop sites over several decades have not shown any significant trends (ELLIS and PUESCHEL, 1971; ROOSEN et al., 1973; CHARLSON, 1988). There is, however, a clear change evident in some statistical analyses of aerosol or haze occurrence in more directly polluted areas (YAMAMOTO et al., 1971; HUSAR et al., 1981). For example, HUSAR and WILSON (1993) document a considerable increase in haze over the US over the last three decades. Satellite measurements of light-scattering over the North Atlantic have shown that this haze can be transported for great distances over the oceans and still produce an easily detectable impact on the scattering properties of the atmosphere (FRASER et al., 1984; HUSAR and STOWE, 1994). One of the most salient predictions from recent model studies of the global sulphur cycle is the pervasive sulphate pollution in the troposphere over the North Atlantic and Pacific (LANGNER et al., 1992; TARRASON and IVERSEN, 1992). Field measurements of aerosol
379
Climatic effects of changing atmospheric aerosol levels chemistry in remote regions confirm the influence of anthropogenic emissions in areas far from continental sources (LAWSON and WINCHESTER, 1979; ANDREAE et al., 1984; WARNECK, 1988; SAVOIE and PROSPERO, 1989; CHURCH et al., 1991; DUCE et al., 1991). Based on aircraft measurements, ANDREAE et al. (1988) showed that mid-tropospheric sulphate concentrations over the North Pacific off the west coast of the United States were dominated by long-range transport from Asia. This was established by air-mass trajectory analyses and supported by radon measurements. Analyses of the interrelationship between ozone, nitrate and sulphate concentrations in North Atlantic air masses sampled at Barbados also showed pervasive influence of anthropogenic sources (SAVOIE et al., 1989, 1992b). Shipboard measurements of aerosol and precipitation chemistry over the Atlantic document widespread enhancement of sulphate levels above the biogenic background (CHURCH et al., 1991). Long-term ground-level measurements of non-sea-salt sulphate concentrations at island stations also show clearly elevated concentrations over the Northern Hemisphere oceans relative to those in the Southern Hemisphere at corresponding latitudes (Table III). This hemispheric difference is also clearly seen in the relatively few airborne measurements available in remote areas (Table IV). The increase in CCN due to anthropogenic emissions is well documented in industrialized regions (WARNER and TWOMEY, 1967; HOBBS et al., 1970; BRAHAM, 1974; SCHMIDT, 1974; TWOMEY et al., 1978). That elevated sulphate levels over the North Atlantic cause an increase in CCN is suggested by the data of HOPPEL (1979), who finds that CCN concentraTABLE III ANNUAL AVERAGESURFACECONCENTRATIONOF Nss-SO4 2- IN AIR (PMOL/MOLAIR) (MODIFIEDFROM
LANGNERANDRODHE, 1991) Location
Latitude
Longitude
76~ 79~ 52~ 32~ 30~ 20~ 13~ 12~ 8~ 3~
87~ 20~ 174~ 65~ 175~ 158~ 60~ 144~ 133~ 160~
210 168 155 455 133 119 175 119 147 154
BARRIE and HOFF(1985) HEINTZENBERGand LARSSEN(1983) PROSPEROet al. (1985) WOLFFet al. (1986) SAVOIEand PROSPERO(1989) SAVOIEand PROSPERO(1989) SAVOIEet al. (1989) SAVOIEand PROSPERO(1989) SAVOIEand PROSPERO(1989) SAVOIEand PROSPERO(1989)
15~ 22~ 30~ 40~
170~ 166~ 168~ 144~
68~
61~
84 98 56 21 b 26c 21 20
SAVOIEand PROSPERO(1989) SAVOIEand PROSPERO(1989) SAVOIEand PROSPERO(1989) AYERSet al. (1991) ANDREAEet al. (1991) SAVOIEet al. (1992a) TUNCELet al. (1989)
nss-SO42-
References
Northern Hemisphere Canadian Arctic a Spitsbergen Shemya Bermuda Midway Oahu Barbados Guam Belau Fanning
Southern Hemisphere Am. Samoa New Caledonia Norfolk Island Cape Grim Cape Grim Mawson South Pole
aMean for stations Alert, Mould Bay and Iglooik. bSubmicrometre fraction. tin fraction <2.0 mm diameter. Coarser particles contain an additional 39 pmol mo1-1 nss-SO42-.
380
Evidence for the climatic impact of anthropogenic aerosols T A B L E IV
OBSERVATIONS OF 5042- IN THE TROPOSPHERE(PMOL/MOLAIR) (MODIFIEDFROMLANGNERAND RODHE, 1991) Location
Median
Range
No. of samples
References
Boundary layer (<2 km) Northern Hemisphere NW Europe 2,238 a W Atlantic 290 North Atlantic 424 a North Atlantic North Atlantic Tropical Air masses 213 Air masses from N Am 939 North Atlantic Marine air masses 327 a Continental Influence 905 North Pacific 352 a Pacific, West of USA 95 a Pacific (Eq.-37~ 150 North Pacific W of USA 96 W North America 120 Western USA 182 a Central USA 480 a
<47-1211 89-963 150-2600
597 18 26 23
128-280 181-2500
16 6
+-316 __.437 43-717 60-906 45-130 60-1148 -
35 30 26 13 13 13 16 23 24
150 90 30 7
110-376 60-906 40-193 18-358 19-54 5
12 10
125a 72a
+_50 +_56
41 45
OEDC (1977) WHELPDALE et al. (1987) CHURCH et al. (1991 ) BORGERMEISTER and GEORGII (1991) GALLOWAYet al. (1990)
BERRESHEIM et al.(1991)
QUINN et al. (1990) GILLETTE and BLIFFORD (1971) HUEBERT and LAZRUS (1980) ANDREAE et al. (1988) HUEBERT and LAZRUS (1980) GILLETTE and BLIFFORD (1971 ) BOATMAN et al. (1989)
Southern Hemisphere South Atlantic Pacific (57 ~ S-Eq.) Equatorial Pacific South Pacific Tasmania Southern Ocean Amazonia Dry season Wet season
18 19 12 9
BURGERMEISTER and GEORGII (I 99 I) HUEBERT and LAZRUS (I 980) QUINN et al. (1990) BATES et al. (I 992) BERRESHEIM et al. (1990) BERRESHEIM et al. (1989) BINGEMER et al. (1990)
Middle troposphere (2-7 km) Northern Hemisphere Greenland 50 North Atlantic 66 North Atlantic Tropical air masses 67 Air masses from N Am 1,470 Western USA 67a W North America <45b Central USA 251a Pacific, W of USA 31a North Pacific, W of USA 180 Pacific (Eq.-37 ~ N) <45b
24-155 20-450
12 21
FLYGER et al. (1976) FLYGER et al. (1976) GALLOWAY et al. (1990)
38-78 396-1560 <45-332 130-200 <46-230
3 3 22 28 24 ll 9 29
GILLETTE and BLIFFORD (1971 ) HUEBERT and LAZRUS (1980) BOATMAN et al. (1989) GILLETTE and BLIFFORD (1971 ) ANDREAE et al. (1988) HUEBERT and LAZRUS (1980)
15--45 7c
11 16 32
BERRESHEIM et al. (1990) HUEBERT and LAZRUS (1980) BINGEMER et al. (1990)
Southern Hemisphere Tasmania Pacific (57 ~ S-Eq.) Amazonia
381
33 <45b 14a
Climatic effects of changing atmospheric aerosol levels TABLE IV (continued) Location
Median Range
No. of samples
References
Upper troposphere (above 7 km) Northern Hemisphere Western USA Pacific, West of USA Continental USA
64a 30a 45 + 51
16 9
GILLETTEand BLIFFORD(1971) GILLETTEand BLIFFORD(1971) LEZBERGet al. (1979)
a Mean. bDetection limit. cStandard deviation. tions over the North Atlantic are typically three or more times greater than over the Southern Hemisphere oceans (TWOMEYet al., 1984). Soot carbon, a tracer of combustion-derived aerosols, has also been found at significant concentrations over many remote marine and continental areas (HEINTZENBERG, 1982; ANDREAE, 1983; ANDREAE et al., 1984; CLARKE, 1989; OGREN and CHARLSON, 1983; WARREN and CLARKE, 1990; HANSEN et al., 1990). O'DOWD et al. (1993) showed that particle number concentration over the northern North Atlantic is strongly correlated with soot carbon concentration. Their data suggest that longrange transport dominates particle number concentration in this region, at least outside of the summer months, when biogenic sulphate particles are abundant. CLARKE and CHARLSON (1985) interpreted the presence of light-absorbing material in the mid-tropospheric aerosol at Mauna Loa, Hawaii, as evidence for the long-range transport of soot and other anthropogenic aerosols, which results in a pervasive anthropogenic haze in the Northern Hemisphere. Strong evidence for a large-scale increase in the atmospheric burden of anthropogenic aerosols can also be found in the record of atmospheric composition preserved in glacier ice cores. In the Greenland ice sheet, non-sea-salt sulphate and nitrate show a pronounced increase (from about 20 to over 100 ng/g in the case of sulphate) over the last century (Fig. 14; MAYEWSKI et al., 1986, 1990).
Hemispheric asymmetry of global temperature change A statistical analysis of global temperature trends from 1861 to 1987 shows that while temperatures have been increasing in both hemispheres, there was a pronounced decrease in Northern Hemisphere temperatures between 1940 and 1970, which did not occur in the Southern Hemisphere (JONES et al., 1986; JONES, 1988; Chapter 5 by JONES). JONES et al. (1986) conclude from this analysis that, over the entire period, the global temperature increase is consistent with greenhouse warming, but that the lack of a global temperature increase in the 1930s to the 1970s which results from the diverging trends in the Northern and Southern Hemispheres "requires either the existence of some compensating factor or a lower sensitivity to greenhouse gases than is generally accepted". Given the conclusion reached above, i.e. that the impact of anthropogenic aerosols on climate predominantly affects the Northern Hemisphere, it is tempting to attribute the cooling of the Northern Hemisphere relative to the Southern Hemisphere to sulphate aerosols (Chapter 5 by JONES), especially since this period coincides with the time in which sulphur emissions exceeded natural levels in the Northern Hemisphere (Fig. 3) and grew rapidly before being checked by emission
382
Evidence for the climatic impact of anthropogenic aerosols 160
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Fig. 14. (a) Concentration of non-seasalt sulphate (solid line) in ice from the Greenland ice cap compared with the anthropogenic global SO2 (dotted line) and US. SO2 (dashed line) emissions. The sharp peaks, e.g. in 1783 and 1815, result from volcanic eruptions. (b) Concentration of nitrate (solid line) compared with the anthropogenic US NOx emission (dashed line) (from MAYEWSrdet al., 1990).
controls. This interpretation is supported by the model of KAUFMAN and CHOU (1993), which predicts that, in the absence of aerosol forcing, the Northern Hemisphere should have warmed more rapidly than the Southern Hemisphere. However, when aerosol forcing is included, a delayed warming in the Northern Hemisphere results, in agreement with the observed trends. Based on model simulations of Northern Hemisphere and Southern Hemisphere temperature trends resulting from the growth of greenhouse gases and sulphate aerosol in the atmosphere between 1900 and 1985, WIGLEY (1989) concludes that the observed interhemispheric temperature differences are consistent with a sulphate forcing of-0.5 W m -2 or a CCN increase by 10% in the Northern Hemisphere. Even values up to three times these amounts would still be compatible with observations. He cautions, however, that there are alternative explanations for diverging trends in hemispheric-mean temperatures.
383
Climatic effects of changing atmospheric aerosol levels Using a statistical approach, SLINN (1991) fitted the hemispheric temperature trends in the Northern Hemisphere using the growth in greenhouse gases, the emission of SO2, the southern oscillation index, and the injection of volcanic dust as independent variables, and found that the introduction of SO2 emissions made it possible to obtain a much better fit to the Northern Hemisphere temperature record than is possible with the other variables alone. A similar regression calculation done separately on temperature trends and sulphur emissions in North America gave analogous results. In contrast, and as expected from the discussion above, anthropogenic sulphur was not a significant variable in a regression analysis of Southern Hemisphere temperatures. ENGARDT and RODHE (1993) compared regional patterns of trends in surface temperature and sulphate aerosol pollution. They found that in regions heavily impacted by anthropogenic sulphate aerosols (southeastern Europe, the northern North Atlantic and China) summer temperatures had decreased from the 1940s to the 1980s. They caution, however, that, while these observations are qualitatively consistent with models of aerosol cooling, their statistical significance is low due to the large natural variations in the temperature records.
Reduced diurnal temperature variation Since aerosols interact much more strongly with visible (sun-)light than with infrared radiation, they act mostly by decreasing daytime heating and have little influence on nighttime heat loss. The greenhouse gases, on the other hand, are transparent to visible light, and act by trapping infrared radiation, independent of day or night. HUSAR and WILSON (1986) showed in an analysis of climatic trends in the United States from 1950 to 1980 that the diurnal amplitude, i.e. the difference between noon and midnight temperatures, had decreased by 1-2~ in the Eastern US, while it had remained constant in the Western US. This change was caused by both a decrease in midday temperature and a rise in nighttime temperature. Since this climatic trend agreed in its geographic pattern with the observed increase in aerosol density, they suggested that the increased aerosol levels had caused daytime cooling. Investigating a global data set, KARL et al. (1991) found that the observed global warming has taken the form of higher nighttime minimum temperatures, with practically constant daytime maxima. The reduction of diurnal amplitude observed in both studies is consistent with a significant reduction of daytime warming due to aerosols, and lends strong support to the significance of the climatic effect of anthropogenic aerosols.
The effect of atmospheric aerosols on future climate scenarios
The inclusion of a negative climate forcing due to increasing aerosols has a significant influence on our interpretation of the results of climate predictions from general circulation models. These models predict a climate sensitivity (i.e. the amount of warming caused by a doubling of CO2) of 1.5-4.5 K, with a consensus "best estimate" of 2.5 K (SCHLESINGER and MITCHELL, 1987; HOUGHTONet al., 1990, 1992; HANSEN et al., 1993). Analysis of temperature trends over the last one-and-a-half centuries, however, suggests that temperature has increased at a rate close to the low end of this range. Calibrating temperature increase against the known history of greenhouse gas increase yields climate sensitivities around 1.3-
384
The effect of atmospheric aerosols on future climate scenarios 2.5 K (Chapter 5 by JONES). It must be noted that the consensus "best estimate" already takes the observed climate record into account, and therefore is lower than what most GCMs predict. WIGLEY (1989) points out that even a modest sulphate aerosol forcing o f - 0 . 7 W m -2 in the Northern Hemisphere would make the observed temperature history consistent with a climate sensitivity of 4 K for a doubling of CO2. HANSEN et al. (1993) have included aerosol-induced cooling in climate model simulation, and obtain a greatly improved match between model and observations compared to model runs involving the greenhouse gases alone. Thus, the existence of SO2-derived forcing may help to explain the apparent inconsistency between earlier GCM results and observations, and dispel our misgivings about the greater climate sensitivities predicted by the models. This is of great consequence for the degree of confidence we place in the prediction of future temperature growth by these models, especially for the time in the future when the "aerosol mask" comes off, as discussed in the following paragraphs. The most important difference between greenhouse gases and the "anti-greenhouse" aerosols with regard to their role in the evolution of climate in the future is their vastly different lifetime in the atmosphere. All the major greenhouse gases (with the exception of tropospheric ozone) have lifetimes measured in decades to centuries. Aerosols, on the other hand, are removed from the atmosphere within a few days. As a consequence, the amount of greenhouse gases present in the atmosphere represents an accumulation over decades to centuries, and can be approximated as the integral of the source strength over time. In the case of the aerosols, on the other hand, the amount present in the troposphere is only that which has been emitted over the last week or so. Therefore, the atmosphere responds almost immediately to any change in aerosol source strength, while it retains a long memory of greenhouse gas source flux. In most scenarios of future emissions of greenhouse gases, a reduction in the presently rapid growth of fossil fuel combustion is anticipated in the 21st century. In particular, the reduction of SO2 emissions has been the declared goal of environmental policy in the developed countries. Eventually, a levelling out and even a decrease in the rate of emissions of greenhouse gases and aerosol precursors is sought. Under these circumstances, aerosol levels should soon stabilize or even decrease, while the atmospheric concentrations of the longlived greenhouse gases will continue to increase over a long time, until their rates of removal become equal to their rates of emission (Fig. 15 from CHARLSON et al., 1991). For example, if we were to begin reducing CO2 emissions by 2% per year today, atmospheric CO2 levels would only begin to decrease some 60 years from now. Sulphate levels, on the other hand, would immediately fall in proportion to the emission reductions. As a consequence, the most likely result of simultaneous reductions in the rate of CO2 and SO2 emissions would be a sharp increase in the net (gas minus aerosol) global greenhouse forcing, and therefore an increase in the rate at which global warming occurs (WIGLEY, 1991; KAUFMAN and CHOU, 1993). Only over longer timespans will the climatic benefits of greenhouse gas reductions be evident (Fig. 16). Policies which result in a preferential reduction in aerosol emissions over CO2 emissions, e.g. reduction in the use of high-sulphur fuels or installation of sulphur-selective emission controls, would exacerbate this effect. On the other hand, policies which would reduce CO2 emissions from non-fossil fuel sources, or sequester atmospheric CO2, would benefit from the full CO2 climate sensitivity of as much as 4 K with no discount due to the aerosol effect. Such measures, e.g. the elimination of de-
385
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forestation in the tropics, and large-scale reafforestation, would therefore be most effective for the near-term mitigation of greenhouse-induced climate change. However, since the release of CO2 from deforestation is only about 20-30% of the release from fossil fuel burning, and since a reafforestation programme would have to be very large to be effective, even these measures can produce only limited near-term results. If sulphate aerosols have a significant climate effect, as has been argued in this chapter, the global warming due to CO2 from fossil fuel burning could in principle be eliminated by continued exponential increase in fossil fuel use. Such a scenario would lead, however, to a nightmarish situation where, when fossil fuel resources are finally depleted in a world choked by smog and drenched in acid rain, greenhouse warming would take off unchecked towards a huge rise in global temperature. Aerosol cooling should therefore not be used as an argument to delay or abandon reduction policies aimed at fossil-fuel combustion. Besides the obvious advantage of avoiding a large unrealized greenhouse effect, the reduction in the emission of SO2 and other aerosol precursors provides immediate benefits to environmental health. It is also likely, that due to the non-linearities involved in climate forcing by aerosols, this effect will become saturated much earlier than the greenhouse gas effect (maybe as early as 2020), limiting the potential of aerosol emissions to offset future global warming (KAUFMAN and CHOU, 1993). Furthermore, while on a global-mean basis aerosol-induced cooling could offset greenhouse heating, such a course would lead to an ever-widening difference in the climate forcing between the Northern and Southern Hemispheres, which is
386
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potentially even more disruptive to the climate system than a uniformly distributed greenhouse effect (WIGLEY, 1991). There is some debate about the effect of increasing pollutant emissions on CCN and cloud droplet concentrations and on cloud optics and microphysics. It is well recognized that the production of particles is a highly non-linear and relatively poorly understood process. Not much mass is needed to produce the CCN present in the atmosphere: TWOMEY (1991) suggests that some 10 Tg of material per year could account for the global budget of cloud nu-
387
Climatic effects of changing atmospheric aerosol levels cleating particles. It may therefore be argued that the production of CCN is not limited by the mass of pollutants injected into the atmosphere. Yet some field studies have shown pronounced enhancements of CCN number in air that has passed over urban areas and received inputs of aerosols from anthropogenic sources. For example, BRAHAM (1974) found an increase of 500 cm -3 in air downwind of St. Louis, MO, which resulted in an increase in the droplet number concentration in low stratus clouds by about the same number. HUDSON'S (1983) observations in stratus clouds off the California coast and PUESCHEL et al.'s (1986) measurements at Whiteface Mountain also support a close connection between CCN and droplet numbers. It is therefore indisputable that the increase in overall pollutant emissions, which accompanies the expected continued increase in greenhouse gas emissions, will also lead to growing CCN number concentrations, albeit not necessarily in linear proportion. We can therefore predict with some confidence that clouds in the future will contain more droplets per unit volume and, other things being equal, these droplets must become smaller. Besides the increase in albedo, other cloud microphysical effects will result from such a change. The most important could be a change in precipitation efficiency which has a cooling effect if it leads to higher cloud amounts and longer cloud lifetime, but may also have a warming component if the result is an overall increase of the amount of water vapour present in the atmosphere. It is clear that the many interacting and non-linear effects in this system can only be satisfactorily considered by using rather complex climate models which are still in the process of being assembled at this time. In addition to increased emissions of substances which lead to the formation of submicrometre aerosols, human activities and the resulting climate change may strongly influence the amount of mineral dust present in the atmosphere. Desertification in Africa, "dust bowl conditions" in China, increasing erodibility of land due to deforestation in the Amazon Basin and equatorial Africa, and increasing storm intensities resulting from rising atmospheric temperature gradients, all may lead to an enhanced mineral dust load in the atmosphere, and a resulting albedo increase. These effects may be regionally very pronounced; for example, African dust outbreaks over the Atlantic can produce optical depths of about 1.0 over areas of 106 km 2 (CARLSON and CAVERLY, 1977; CARLSON and BENJAMIN, 1980; PROSPERO and NEES, 1986). Evidence for a dramatic increase in the dust flux from Africa in the last two decades is presented by PROSPERO and NEES (1986). Another potential feedback mechanism is the influence of global change on marine DMS emissions. As we have discussed above, biogenic DMS is the dominant source of sulphate aerosol, and consequently CCN, in the natural atmosphere. A modest change in this source, which could be effected by shifts in phytoplankton speciation, food-web structure etc., would have considerable influence on the albedo of clouds over large ocean areas, with obvious climatic consequences. Such ecological changes are likely to occur as a result of a change in ocean temperatures or an increase in the flux of UV radiation to the ocean surface, but their consequences on the biogenic sulphur emissions cannot be predicted at this time due to unsatisfactory knowledge about the linkages between plankton ecology and DMS emission. In this chapter, the effects of possible increases in stratospheric aerosols on climate have not been considered. Early studies, performed during the first phase of concern about the impact of a stratospheric aircraft fleet, have suggested that significant cooling at the Earth's surface
388
References may result, especially at higher latitudes (HERMAN et al., 1976). Due to light absorption by these aerosols, which would certainly contain soot carbon, stratospheric warming would result. More significant may be the indirect effects on climate resulting from the reduction of stratospheric ozone catalysed by increasing stratospheric aerosols. Lower ozone concentrations would cause a reduction in the amount of radiative energy absorbed by stratospheric ozone, and thus a stratospheric cooling (see Chapter 9 by WANG et al.). Numerous feedbacks exist in this system, which will have to be analysed by comprehensive models. This appears to be especially pertinent in view of the observation that stratospheric aerosol levels appear to have been increasing over the past decade (HOFMANN, 1990). Some words of caution are necessary at the end of this chapter. The effect of non-linearities in the aerosol effects on direct and cloud-amplified forcing have already been pointed out above. These effects are superimposed on the climate system, which itself is described by a system of coupled non-linear differential equations. The chaotic behaviour characteristic of such systems results in unpredictable fluctuations at all time-scales and a tendency to jump between highly disparate states of the system, e.g. ice-ages and interglacials, or different modes of ocean circulation (BROECKER et al., 1985; BROECKER, 1987; Chapter 14 by PENG, 1994). The tendency for the Earth's climate system to undergo fast jumps at time-scales of decades to centuries has been recently documented in ice cores obtained from Greenland (GRIP (GREENLAND ICE-CORE PROJECT) MEMBERS, 1993). This study suggests that the stable climate of the present interglacial is a rather unusual case, and that previous interglacials were characterized by frequent, short-term oscillations between considerably warmer and colder states. Temperature changes of up to 10~ in a couple of decades appear to be possible in interglacials, making human and ecological adaptation to climate change highly unlikely. The internal noise of the system makes the real-time observation of externally induced changes quite difficult, viz. the discussions in recent years about the question "are we seeing the effects of global warming?". Our present "global experiment", which we conduct by imposing various forcings on the climate system and seeing if we can discern their effect above the intrinsic fluctuations, is therefore a rather hazardous one. We may only obtain satisfactory answers, if ever, at the point when the system jumps into another state, quite different from the present one, and quite unpredictable in its consequences for our and the planet' s well-being.
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398
Chapter 11
Ozone depletion GUY P. BRASSEUR, JOHN C. GILLE AND SASHA MADRONICH
Introduction
The chapter reviews the photochemical cycles responsible for the formation and destruction of ozone in the stratosphere and mesosphere. The specific processes affecting ozone in the polar regions are discussed. Observations of ozone, mainly from space platforms are briefly presented. Model simulations of ozone depletion in the recent past and in the future are described. Finally, effects of ozone changes on the climate system and on the level of UV-B radiation at the surface are presented. The thermal and dynamical structure of the Earth's atmosphere is, to a large extent, governed by the presence of trace gases which absorb solar or terrestrial radiation. Among them, ozone (O3), an allotropic form of oxygen, plays a key role. In spite of its small abundance (typically 5 ppmv in the stratosphere and 30 ppbv in the troposphere), it absorbs a large fraction of the solar ultraviolet radiation in the wavelength region of 200-310 nm and protects the biosphere from harmful effects. For example, UV-B radiation (280-320 nm) is capable of altering DNA in living cells, of causing skin cancers and of producing eye cataracts. Phytoplankton in the surface waters, and hence the food chain in the ocean, are also susceptible to damage by UV-B. By absorbing solar ultraviolet radiation, ozone also affects - in fact, causes - the thermal structure of the stratosphere and hence the general circulation of the atmosphere. The fact that, on average, the temperature increases with height between 15 and 50 km, and hence that the stratosphere exists, is a direct consequence of the presence of ozone in the middle atmosphere. Also, through its strong absorption band in the infrared at 9.6/~m, ozone contributes to the greenhouse effect of the atmosphere and consequently affects the radiative forcing of the climate system. Ozone depletion in the stratosphere could also increase photochemical activity in the troposphere (MADRONICH and GRANIER, 1992) and modify the overall oxidizing capacity of the atmosphere. Since the early 1970s, there has been some concern that the stratospheric ozone layer could be partly destroyed as a result of human activities, leading to enhanced UV-B fluxes at the Earth's surface and changes in the thermal structure of the stratosphere. Substantial changes in the ozone abundance have been observed over the last decade (WMO, 1991), particularly in Antarctica where an ozone hole has developed each spring since the late 1970s (FARMAN et al., 1985). In the Northern Hemisphere, the vertically integrated ozone density (called the ozone column abundance) has been reduced by approximately 5% since the 1980s with the largest depletion (10%) observed during the winter months at mid-latitudes. At the same time, the concentration of ozone in the troposphere appears to have increased, at least in the
399
Ozone depletion
Northern Hemisphere. Because available observations are limited and due to the strong spatial inhomogeneity in the chemistry of the troposphere, mean ozone trends cannot be easily estimated, even if figures such as 1-2% per year are reported for industrialized regions (see FEHSENFELD and LIU, 1993 for a review). The potential causes for long-term trends in the ozone concentration have been widely discussed in the literature. They involve the emission in the atmosphere of anthropogenic gases such as nitrogen oxides (NOx), chlorofluorocarbons (CFCs) etc. The observed trends in carbon dioxide (CO2), methane (CH4), nitrous oxide (N20), methyl bromide (CH3Br) etc. are also expected to affect the ozone layer. Nitrogen oxides are released at the surface as a result of combustion processes and, when hydrocarbons are present, contribute to the formation of ozone in the troposphere. If injected in the lower stratosphere, for example by high altitude aircraft, they are expected to destroy ozone. However, by recombining with chlorine oxides present in the lower stratosphere, they also reduce the detrimental action of anthropogenic chlorofluorocarbons. CFCs and other halocarbons, which are commonly used as refrigerant products, solvent and foam blowing agents, are believed to be a major threat to the ozone layer and to be responsible for the observed ozone depletion in the stratosphere. The purpose of this chapter is to summarize our knowledge on the photochemical and dynamical processes governing the observed distribution and evolution of the ozone layer. The causes and effects of long-term changes in stratospheric and tropospheric ozone are discussed. The photochemical cycles responsible for the formation and destruction of ozone are reviewed in the next section. Then the specific processes affecting ozone in the polar regions are discussed. Observations of ozone in the middle atmosphere, mainly from space platforms, are presented, followed by a report on model simulations of the ozone evolution. Finally, the effect of ozone changes on the climate system and on the level of UV-B radiation at the Earth's surface are discussed in the last two sections.
Ozone photochemistry The formation of ozone in the middle atmosphere results from the photolysis of molecular oxygen (02) by solar ultraviolet radiation at wavelengths less than 242 nm: (1)
0 2 + hv --o 0 + 0
where hv represents a photon. Oxygen atoms recombine by the three-body reaction: (2)
0 + 0 2 + M --) 0 3 + M
where M is a molecule of air (N 2,
02, Ar .... ) which
removes the excess of energy released
by this exothermic reaction. In the troposphere, where no shortwave ultraviolet radiation is available (due to the strong absorption of these wavelengths by ozone in the stratosphere), reaction (1) is very slow, so that other mechanisms have to be involved to explain the presence of this molecule at these low levels. Intrusions of ozone from the stratosphere provide a partial, but insufficient explanation. In situ formation can result from the photolysis of NO2: 400
Ozone photochemistry
NO 2 + hv ~ NO + O
(3)
followed by the recombination of atomic oxygen through reaction (2). However, this photochemical reaction cannot be regarded as a net production of ozone, since NO, which is formed by (3), reacts rapidly with ozone: NO + 03 --~ NO2 + 02
(4)
to reproduce NO2. Thus, for ozone, reactions (3) and (4) should be viewed as a null cycle. Conversions of NO to NO2, without ozone consumption, would, however, provide a mechanism for net ozone production. An example of such processes is provided by the following reaction: NO + HO 2 ~ NO 2 + OH
(5)
where the hydroperoxy radical (HO2) is produced as a result of the oxidation of methane (CH4) or carbon monoxide (CO). Similar reactions involve other peroxy radicals (RO2) produced by the degradation of non-methane hydrocarbons. The chemical formation of ozone in the troposphere is therefore large when high levels of nitrogen oxides and hydrocarbons are observed, i.e. in urbanized and industrialized areas. Large quantities of ozone are also produced in hydrocarbon-rich forested areas such as the southeastern US and the tropics, if the level of nitrogen oxides (produced by combustion or biomass burning) is sufficiently high. Ozone can be photolyzed by solar radiation in the ultraviolet and in the visible: 0 3 4" hv ~
(6)
0 2 4" O
but, since the oxygen atom is rapidly reconverted into ozone by reaction (2), this latter process cannot be regarded as a net ozone loss. However, the direct recombination of ozone and atomic oxygen 0 3+ O ~
(7)
0 2+ 0 2
represents a net destruction for odd oxygen (ozone and atomic oxygen taken globally), but is too slow to explain the observed ozone concentrations in the stratosphere and mesosphere. The self-recombination of atomic oxygen O+O+ M
-----)0 2 +
M
(8)
is another destruction process for odd oxygen, but plays a significant role only above the mesosphere. Laboratory studies have shown that reaction (7) can be catalyzed (accelerated) in the presence of chemical radicals associated with the hydrogen, nitrogen, chlorine and bromine families in the atmosphere. A typical catalytical cycle leading to the net destruction of odd oxygen can be written as (BATES and NICOLET, 1950; CRUTZEN, 1971; STOLARSKI and
CICERONE, 1974; WOFSY et al., 1975)
401
Ozone depletion 80
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0 3 + X ~ XO + 0 2
(9a)
O + XO "-') X + 0 2
(9b)
Net: 03 + O ~ 202 where X can be H, OH, NO, C1 or Br. Figure 1 shows the destruction rate of odd oxygen in the stratosphere due to different possible cycles. It clearly appears that reaction (7) plays a minor role in the destruction of ozone except in the upper stratosphere. The largest loss of ozone in the mesosphere results from the catalytical action of the hydrogen compounds (H and OH). Note that the following cycle (BATES and NICOLET, 1950) OH+O--)H+O H + 0 2+ M ~
2 HO 2 + M
HO 2 + O --4 OH + 02 Net:
O + O ~
0 2
provides another efficient cycle to catalyze the destruction of odd oxygen.
402
(10)
Ozone photochemistry
In the stratosphere, the most efficient destruction cycle of ozone is provided by (9a,b) in which X = NO. The contribution of the chlorine cycle (X = C1) has become larger over the last decades, because the source of chlorine atoms in the stratosphere, provided by the photolysis of industrially manufactured chlorofluorocarbons (CFCs), has been increasing since the early 1960s. The largest ozone destruction by chlorine through cycle (9a,b) is occurring near 45 km altitude. In the lower stratosphere and in the troposphere, the efficiency of catalytic cycle (9a,b) is significantly lower than at higher altitudes due to the low concentration of oxygen atoms in these layers of the atmosphere. The only destruction mechanisms identified until recently were associated with the presence of hydrogen compounds and involved for example the following cycle: 03 + HO 2 ---) 202 + OH 03 + OH --~ 202 + H H + 02 + M --~ HO 2 + M Net: 203 ~ 302
(11)
Another mechanism, very efficient in the humid regions of the lower troposphere, is related to the formation of the electronically excited oxygen atom O(1D), produced by the photolysis of ozone at wavelengths less than 310 nm: 03 + hv ---) O(1D) + 02 O(1D) + H20 ~ 2OH Net: 03 + H20 + hv ---) 2OH + 02
(12)
None of these cycles is sufficiently efficient to explain the ozone depletion observed since the late 1970s in the lower stratosphere (15-25 km). Observational studies have shown that, under specific circumstances, the concentration of C10 can be abnormally high and that large quantities of ozone could be destroyed by the following cycle, in which the presence of atomic oxygen is not required: 2(C1 + 03 ---) C10 + 02) C10 + C10 ~ C1202 C1202 + hv ~ C1 + C1OO
C1OO + M ~ CI + 02 + M Net: 203 ~ 302
403
(13)
Ozone depletion With concentrations of C10 reaching 1 ppbv, ozone can be almost entirely destroyed in approximately 1 month. It is believed that cycle (13) plays a key role in the formation of the Antarctic ozone hole where C10 abundances exceeding 1 ppbv are observed (see next section). The presence of ozone-depleting radicals in the stratosphere results from the oxidation or photolysis of source gases such as water vapour (H20), molecular hydrogen (H2), methane (CH4), nitrous oxide (N20) and the chlorofluorocarbons (CFCs). These chemical compounds are produced at the Earth's surface as a result of physical or biological processes, or in relation to human activities. For example, the presence of nitrogen oxides is related to the emission into the atmosphere of nitrous oxide and its oxidation in the stratosphere, while that of inorganic chlorine is related to the release in the atmosphere of industrially manufactured chlorofluorocarbons. The destruction of reactive radicals results from their chemical conversion into long-lived reservoirs which are transported to the troposphere where they are removed, for example by dissolution in water droplets and precipitation to the Earth's surface. The global chemical cycles affecting the production and destruction of ozone in the stratosphere are shown schematically in Fig. 2. The chemical lifetime (e-folding time) of odd oxygen calculated for observed concentrations of H, OH, NO, and C10 radicals, varies greatly with altitude (Fig. 3). It is of the order of 1 h near 60 km altitude and increases towards lower levels to reach approximately 1 day at 40 km, 1 month at 30 km and 1 year at 20 km (mid-latitude conditions). It is of the order of days at 90 km and becomes larger than a few months above 100 km altitude. A comparison of these chemical lifetimes with characteristic time constants for atmospheric transport indi-
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404
Ozone photochemistry OXYGEN ls
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~ 109
L I F E T I M E (s)
Fig. 3. Chemical lifetime of ozone (03), atomic oxygen (O) and odd oxygen (Ox = 03 + O) in the middle atmosphere, compared to characteristic transport time (advection by the zonal (u), meridional (v) and vertical (w) winds and eddy diffusion (D)). From BRASSEURand SOLOMON(1986). cates that in the upper stratosphere and mesosphere, the distribution of ozone and atomic oxygen is controlled mainly by photochemistry, while below 30 km and above 85 km altitude, transport plays a dominant role. Because most of the ozone molecules in a vertical column are found between 15 and 30 km altitude, transport by the general circulation of the atmosphere can play an important role in determining the global distribution of this chemical constituent. This explains why, although most of the stratospheric ozone is produced at low latitudes, its total column abundance increases with latitude, and is largest during winter polewards of 60 ~ (see Fig. 5 below). The hemispheric asymmetry is also presumed to be due to differences in the dynamics of the two hemispheres. Ozone is also present in the troposphere, but its abundance in this region of the atmosphere is significantly lower than in the stratosphere (typical mixing ratio of 10-100 ppbv below 10 km altitude). For many years, it has been believed that the presence of ozone in the troposphere was due to the intrusion of ozone-rich air masses from the stratosphere, since the photochemical production mechanism represented by reaction (1) is not operative below 15-20 km altitude since the shortwave UV radiation is entirely absorbed above these levels. Although the injection of stratospheric ozone, as well as its deposition at the Earth's surface are important processes, the overall ozone budget in the troposphere (especially in the Northern Hemisphere) is dominated by photochemical production and destruction mechanisms. Ozone is formed through the following cycle involving the presence of nitrogen oxides (NO and NO2, also called NOx)
405
Ozone depletion
NO2 + hv ~ NO + O
(14a)
NO + HO 2 -+ NO 2 + OH
(14b)
O + 0 2 + M --~ 03 + M
(14c)
The rate-limiting process is reaction (14b) which involves the hydroperoxy radical (HO2). Similar reactions with organic peroxy radicals (RO2 where R is CH 3, C2H5, C3H7 etc.) are also contributing to the conversion of NO to NO2 (without consumption of 03) and hence to the formation of ozone. The presence of peroxy radicals results from the oxidation of methane, non-methane hydrocarbons and carbon monoxide. These latter compounds, as well as the nitrogen oxides are released in the atmosphere as a result of human activities (e.g. industrial combustion, transportation, biomass burning etc.). The control of nitrogen oxides and of hydrocarbons and CO are key measures to reduce unacceptable levels of ozone observed, for example, in industrialized regions during summer and under stable meteorological conditions. The type of strategy to be implemented (NOx versus hydrocarbon limitations) varies with background conditions and with the relative importance of natural versus anthropogenic emissions of the ozone precursors. The photochemical destruction of tropospheric ozone is provided by the reaction 03 + HO 2 "-~ OH + 202
(15)
as well as by the photolysis of ozone and subsequent reaction between the electronically excited oxygen atom and a water molecule.
Ozone in the polar regions The development of an ozone hole in Antarctica since the late 1970s (FARMAN et al., 1985) has perhaps been the most spectacular geophysical event of the 20th century. Observations made by space-borne and ground-based instrumentation have revealed that nearly 90% of the ozone is destroyed during August and October ("polar dawn") in a region extending from 15 to 22 km altitude (Fig. 4) and covering an area nearly as large as the Antarctic continent. In November, as the polar vortex breaks down and ozone is transported towards the pole, ozone concentrations are restored to near their pre-hole values. The commonly accepted explanation for the formation of the ozone hole is that chlorine reservoirs (HC1, C1ONO2), which sequester a large fraction of inorganic chlorine in the lower stratosphere, are converted into reactive chlorine on the surface of ice particles in polar stratospheric clouds (PSCs) observed in cold air masses. When the temperature decreases below a thermodynamic threshold of approximately 193 K, small solid particles containing a mixture of nitric acid and water are formed and produce the so-called type I PSCs. At temperatures below 187 K, pure ice crystals are produced and the so-called type II PSCs are formed. Typical diameters for type I and type II PSC particles are 0.5 and 10/tm, respectively. The heterogeneous conversion mechanisms which have been identified in the laboratory are the following (see e.g. WMO, 1991):
406
Ozone in the polar regions 35
i
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03 PARTIAL PRESSURE (nb)
Fig. 4. The formation of the Antarctic ozone hole: vertical distributions of the ozone partial pressure as a function of altitude on 23 August 1989 and 20 October 1989. From DESHLERet al. (1990).
C1ONO2 (g) + H20 (s) ---) HOC1 (g) + HNO 3 (s) N205 (g) + H20 (s) ~ 2 HNO 3 (s) C1ONO2 (g) + HC1 (s) ---) C12 (g) + HNO3 (s) HOC1 (g) + HC1 (s) ~ C12 (g) + H20 (s) N205 (g) + HC1 (s) ---) C1NO 2 (g) + HNO 3 (s) where (g) and (s) refer to the gas phase and the solid solutions, respectively. The gravitational sedimentation of the largest particles (e.g. type II crystals) can produce a substantial denitrification and dehydration of the lower Antarctic stratosphere during winter and early spring. As a consequence, the concentration of NOx ( = NO + N Q ) is low and the C10 radical produced after photolysis of C12, HOC1 and C1NO 2 does not recombine with NO 2 to reproduce C1ONO 2, but accumulates to reach concentrations close to 1 ppbv. C10 radicals remain therefore available for destroying large quantities of ozone and for producing the Antarctic ozone hole. Similar chemical processes are observed in the Arctic in winter. For example, the Microwave Limb Scanner (MLS) instrument on board the Upper Atmosphere Research Satellite detected in January 1992 C10 mixing ratios close to 2 ppbv (WATERS et al., 1993). Observations made during several airborne and ground-based Arctic expeditions have provided evidence for limited denitrification in air masses processed by polar stratospheric clouds. There are, however, several differences which explain why no ozone hole is formed during
407
Ozone depletion the spring season, even if appreciable quantities of ozone seem to be destroyed inside (or in the vicinity of) the Arctic polar vortex. The dynamical situation of the Arctic is significantly more perturbed than in the Antarctic, so that the mean polar temperatures are approximately 5-15 K higher at the north pole than at the south pole. As a consequence, the Arctic vortex breaks down much earlier in the season than the Antarctic vortex. The period during which PSCs are produced is therefore much shorter. In addition, with few exceptions, only type I PSCs are observed. Because the presence of cold air masses processed by PSCs (in January and February) does not coincide with the availability of solar radiation over the Arctic region (March and after), the probability for the formation of an ozone hole in the Northern Hemisphere is low, but this possibility should not be completely ruled out, especially during exceptionally stable winters. It has also been suggested (AUSTIN et al., 1992) that higher abundances in atmospheric CO2 in the future could create dynamical conditions more favourable to the formation of a springtime ozone hole in the Arctic.
O z o n e observations
HARTLEY'S (1881) measurement of the spectrum of ozone in the laboratory led him to suggest that the observed cut off of UV radiation at the Earth's surface was due to absorption by atmospheric ozone. This was later confirmed, and FABRY and BUISSON (1921) used UV measurements to make the first quantitative measurements of the ozone overburden from the ground. Subsequently DOBSON (1931) developed this technique into a standard instrument for obtaining observations of one of the main quantities of interest, the total amount of ozone in a column above the observer. The other information that is needed is the vertical distribution of the ozone, often (and here) termed the vertical profile. Clearly the two are related, as the integral of the profile yields the column amount. However, they are important for different reasons. The total column is the quantity of importance in estimating the total amount of biologically damaging solar UV radiation that will reach the surface, while the profiles provide diagnostic information on the processes, dynamical and chemical, that maintain or modify the ozone distribution. In addition, the vertical distribution of ozone is important for its effect on the radiative balance of the stratosphere, and is now also recognized for its importance to the radiative budget of the surface, since ozone is also a radiatively active gas. In the following sections, we briefly outline the primary methods that have provided the existing observational data base, and describe the present state of knowledge. Total c o l u m n ozone
The most common method for measuring ozone column amounts from the ground is based on measurements of the UV absorption spectrum. DOBSON (1931) developed an ingenious UV double monochromator that for many years was the only method for measuring the total ozone overburden, and is still in widespread use today. It is based on the measurement of the ratio of the UV radiance at pairs of wavelengths for which the ozone absorption coefficient has different values, allowing an ozone determination that is independent of a number of instrumental factors which may drift with time. Usually two pairs of closely spaced wave-
408
Ozone observations lengths are used, to reduce the effects of aerosol scattering as well. The column ozone amount is now usually given in Dobson Units, equal to 10-3 cm of ozone at STP or 2.69 • 1016 molecules cm -2. There are now about 31 Dobson spectrometers in use around the world that have continuous measurements since the IGY in 1957, and another 40 with more limited data records (WMO, 1988). Several other instruments based on the UV spectrum, but with different implementations, have also been used. These are also reviewed in WMO (1988). Extensive work is being carried out to evaluate how well the various data sets can be placed on a common basis. Satellite-based measurements of the spectrum of backscattered solar UV radiation can also be used to derive the ozone column at any latitude that is illuminated (SEKERA and DAVE, 1961; HEATH et al., 1978). In this case, many of the same absorption line pairs are used, to facilitate comparison with the ground-based observations. Such measurements were obtained in a directly down-looking mode by the Backscattered UltraViolet (BUV) experiment on the Nimbus 4 spacecraft in 1970, and continued by the Solar Backscattered UltraViolet (SBUV) experiment on Nimbus 7. The approach was significantly extended by the Total Ozone Mapping Spectrometer (TOMS) instrument on Nimbus 7, which had a side-scanning capability, allowing it to obtain complete global coverage each day with a spatial resolution of 50 km at the nadir point. TOMS was launched in October 1978, and continued to operate until May 1993, or almost 15 years, providing long-term data which, after suitable reprocessing, has allowed studies of global trends of total ozone. Ground-based and satellite measurements are compared on a continuing basis. There is a small offset between the two data sets, but after reprocessing, using TOMS observations to determine a correction for instrumental drift, the differences in their time tendencies are small, and explainable if it is noted that TOMS has less sensitivity to tropospheric ozone, and thus may be failing to fully observe increases in tropospheric ozone to which the network of Dobson stations is sensitive. The observed distribution of column ozone is displayed in Fig. 5, in which the longitudinally averaged total ozone observed by TOMS on a given day is displayed as a function of latitude and season. Several characteristic features are immediately evident. Although the equilibrium between photochemical production and destruction (referred to as photochemical equilibrium) predicts largest values in the tropics, that is in fact a region of minimum column ozone, emphasizing the importance of dynamical processes in maintaining the ozone distribution. At middle and high latitudes there is a pronounced seasonal variation, with minima near the fall equinox, and maxima occurring in the Northern Hemisphere (NH) at the end of the winter or beginning of spring, and slightly later in the SH. The largest values are found at high latitudes, with higher values being found at higher latitudes in the NH. These variations reflect the seasonal variations of the mean meridional circulation, which transports air from regions in which the ozone is produced into high latitude, low altitude regions in which it is conserved. There are other features that are not shown in a plot like Fig. 5. Long-term averages show stationary longitudinal features, such as higher concentrations at the eastern boundaries of continents, again reflecting the mean wind systems in the lower stratosphere. In addition to the seasonal variations illustrated above, at any given location there are also large day to day variations, which are larger at higher latitudes. There are also significant
409
Ozone depletion 0 3 COLUMN (Dobson units)
TOMS - 1987
90
60
30 iii D i--< _1 -30
-60
-90
O
F
M
A
M
O
O
A
S
O
N
D
MONTH
Fig. 5. Variation with latitude and month of the ozone column abundance in DU (Dobson Units) measured by TOMS in 1987.
interannual variations, due to the influence of the quasi-biennial oscillation (QBO) and the 11-year cycle of the solar output. These variations make it more difficult to detect small, long-term trends in ozone. The long-term measurements of global total ozone that began with the launch of TOMS on Nimbus 7 are continuing with a series of TOMS instruments on Russian, Japanese and US satellites through the 1990s, after which time it is expected to become an operational instrument. Quality control and checks on accuracy will be carried out by continuing comparisons with ground- and space shuttle-based instruments. These data have been providing the detailed pictures of the ozone hole over Antarctica in recent years, and continuing to show the decrease in total ozone over mid-latitudes that is not fully understood at this time. Their continuation is thus very important. Vertical ozone distribution
Although some of the earliest measurements of the vertical ozone distribution were made by balloon-borne instruments
(CRAIG,
1965), the earliest extensive set of data is again based on
UV observations, usually by the Dobson spectrophotometer. Measurements of the ratios of intensities at wavelength pairs, as a function of solar zenith angle, show a characteristic reversal (Umkehr in German) at zenith angles --85-88 ~ which can be inverted to provide information on the vertical distribution of ozone from 2-32 mb, or approximately 24-45 km altitude (MATEER, 1964; WMO, 1988). These analyses also indicate that there are no more than 3-4 independent pieces of information in the Umkehr observations. This is consistent with the practice of providing information in layers spanning a factor of 2 in pressure, or about 5 km in thickness.
410
Ozone observations More recently, active sounding measurements using laser radars (lidars) have begun to be used to provide information on the vertical ozone distribution. With suitable equipment, they can provide ozone profiles with high vertical resolution (from one to a few kilometres) from close to the surface to ,-50 km. At present there are not many of these sounders, but their use is expanding, and they will be more widely distributed as the Network for the Detection of Stratospheric Change (NDSC) is extended. Again, these local ground-based measurements have been extended in the last two decades by a variety of satellite techniques. The most extensive data set is that obtained by the B UV and SBUV experiments, which measured the spectrum of backscattered UV at wavelengths from 255 to 300 nm. At these wavelengths the UV does not reach the surface, but is scattered by molecules in the atmosphere and absorbed by ozone. This provides ozone profiles with a vertical resolution of 8-10 km from 16 to 1 mb, or approximately 28-48 km (WMO, 1988). Coverage with better vertical resolution (-5 km) from 15 to 65 km has been provided by infrared (IR) and microwave limb scanning instruments (LRIR and especially LIMS, GILLE and RUSSELL, 1984), CLAES (ROCHE et al., 1993), ISAMS (TAYLOR et al., 1993) and MLS (BARATH et al., 1993). These instruments measure the thermal radiation emitted by ozone, which allows measurements at all observable latitudes, day and night. Because of the technology for cooling the detectors and mechanical problems, the first four lasted for limited periods of time. MLS is still operating. Another extensive data set is being obtained by the SAGE and SAGE II experiments (MCCORMICK et al, 1979), which derive the vertical ozone distribution from measurements of solar occultation in the visible part of the spectrum. While this technique only obtains -28 profiles per day, 14 at each of two latitudes, the data are characterized by high vertical resolution (~ 1-2 km), and coverage from as low as 7 km to 50 km. The observed vertical distribution of ozone is displayed in the latitude height cross-sections shown in Fig. 6. These illustrate that ozone is characterized by an approximately layered distribution, with a maximum ozone mixing ratio of approximately 10 parts per million by volume (ppmv) in the tropics, near 10 mb (-30 km altitude). The ozone isopleths are ap-
a
b
0.2
60
60 55
55
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1
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35
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,vv -60
-30
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LATITUDE
30
60
90
-90
-60
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0
30
60
90
LATITUDE
Fig. 6. Average zonal mean ozone mixing ratios (ppm) for (a) December 1978 and (b) May 1979. Data have been extended to the South Pole with the aid of SBUV observations as described by GILLE and LYJAK(1986).
411
Ozone depletion proximately horizontal in the upper stratosphere reflecting photochemical dominance there, but slope downward from the tropics into high latitudes below about 20 km. Between 20 km and the upper stratosphere isopleths can be regarded as showing ozone decreasing towards the pole on horizontal surfaces. At lower levels, and latitudes in winter darkness, dynamical processes shape the ozone distribution. The mean meridional Lagrangian circulation, consisting of upward motions in the tropics, poleward drifts in the mid stratosphere and from summer pole to winter pole in the upper stratosphere and mesosphere, and downward motion at the poles, especially strong in the winter pole, plays a major role in the transport of ozone and other trace gases. This acts with quasi-horizontal wavelike motions on isentropic surfaces to create the polewarddownward shape of the isopleths in the lower stratosphere, and to create conditions that allow the transport of ozone from the stratosphere into the troposphere. Ozone in the lower stratosphere and upper troposphere is of great importance for the radiative budget of the surface, and thus for climate change (see section on Ozone changes and the climate system, below). Two sets of observations of vertical profiles are being collected on a continuing basis at this time. An improved SBUV instrument is one of the complement of instruments on the operational satellites of the US National Oceanic and Atmospheric Administration (NOAA). This is the beginning of NOAA's plan to observe the vertical ozone distribution on a longterm basis. A change to an infrared limb scanning instrument, to allow coverage to lower altitudes, better vertical resolution, and to facilitate the measurement of other species of interest, is being considered for the future. In addition, the US National Aeronautics and Space Administration (NASA) is continuing to obtain measurements from the SAGE II occultation instrument. Several instruments are also under development for the international Earth Observing System, which will begin to launch instruments in 1998. These include improved versions of the instruments mentioned above, and should provide the capability to monitor short-term changes, and continue the observations that improve our ability to measure long-term trends.
Ozone depletion Trends in the ozone column abundance over the last decades have been deduced from observations performed by ground-based as well as space-borne instrumentation. The Total Ozone Mapping Spectrometer (TOMS) has provided an estimate of changes in total ozone between 1979 and 1992, as a function of latitude and season. As shown by Fig. 7, the ozone column over a 10-year period has been reduced by more than 30% over Antarctica in spring (October). The change in ozone has been insignificant in the tropics, but has been as large as 8-10% at mid-latitudes in the Northern Hemisphere during winter. Models do not reproduce adequately this mid-latitude ozone reduction in the Northern Hemisphere. One possible explanation for this discrepancy is the dilution of air masses processed in the polar regions by stratospheric clouds. Another plausible explanation is that heterogeneous reactions on the surface of aerosol sulphate particles reduce the abundance of nitrogen oxides and activate chlorine:
412
Ozone
depletion
03 C O L U M N D I F F E R E N C E (%) T O M S (1989 + 1 9 9 0 ) - (1979 + 1980) 90
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Fig. 7. Variation during the 1980s of the ozone column abundance as a function of latitude and month, deduced from the measurements of TOMS (STOLARSKI,private communication).
C1ONO2 + H20 (sulphate aerosol) --->HOC1 + HNO 3 N205 + H20 (sulphate aerosol) --->2 HNO 3 These mechanisms play a role analogous to those described in the case of polar stratospheric clouds, but with lower efficiency because the surface area available is usually much lower. The background aerosol layer in the lower stratosphere is believed to result from the photodissociation of carbonyl sulphide (COS) (CRUTZEN, 1976) produced at the Earth's surface (ocean and human activities). The sulphur atoms released are converted into sulphate particles over a time period of approximately 1 month. The aerosol load can be enhanced by one or two orders of magnitude after large volcanic eruptions. Recent observations (MANKINet al., 1992, GRANT et al., 1992) and model calculations (BRASSEUR and GRANIER, 1992) have suggested that the chemistry of the stratosphere was substantially perturbed after the eruption of Mount Pinatubo (The Philippines, June 1991). A coupled chemical-radiative-dynamical model (BRASSEUR et al., 1990) has been used to analyze the evolution of ozone during the last decade. The model used is two-dimensional (latitude-altitude) and extends from pole to pole and from the surface to 85 km altitude. The formulation of dynamical processes is expressed in the Eulerian mean framework. The momentum deposition and mixing associated with the absorption of upward-propagating Rossby and gravity waves is parameterized as a function of the zonal mean state of the atmosphere (BRASSEUR and HITCHMAN, 1988; HITCHMAN and BRASSEUR, 1988). The scheme for radiative transfer (terrestrial radiation) is from BRIEGLEB (1992). The model includes
413
Ozone depletion
OZONE VARIATION (Percent) 1980-1990 90~ 60~ 30~ EQ. 30~ 60~ 90~ 90~ 60~
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DATE Fig. 8. Relative variation (percent) in the ozone column abundance calculated as a function of latitude and season. (a) Only gas phase chemistry is taken into account; (b) heterogeneous reactions on the surface of particles in polar stratospheric clouds are included in the chemical scheme; (c) same as (b) but heterogeneous reactions on the surface of sulphate aerosol particles (background conditions) are also taken into account.
414
Ozone depletion approximately 60 species and 120 chemical reactions. The scheme for heterogeneous processes on PSCs and aerosol particles is described by GRANIER and BRASSEUR (1992). The model was used to simulate the trends in the ozone column abundance between 1980 and 1990. If only gas phase chemistry is included in the formulation of chemical processes, the calculated depletion of ozone, as shown in Fig. 8a, is significantly smaller than that observed during the same period of time. If heterogeneous reactions on PSCs particles are added to the chemical scheme, a large ozone depletion is calculated at high latitudes in the southern hemisphere in September and October and the formation of the Antarctic ozone hole is reproduced (Fig. 8b). Little change, however, is predicted in the Northern Hemisphere. The agreement between calculated and observed trends is significantly improved when the effects of heterogeneous reactions on sulphate aerosols (non-volcanic situation) are taken into account (Fig. 8c, compare with Fig. 8a,b). However, the simulated ozone depletion in the Northern Hemisphere is smaller and located closer to the pole than suggested by the observations. Because of the limitations in the formulation of dynamical transport in two-dimensional models, especially near the polar vortex, conclusive comparisons between theory and observations should involve high resolution three-dimensional calculations. The calculated variations in ozone and temperature between October 1980 and October 1990 are represented in Fig. 9a,b as a function of latitude and height. The ozone depletion in
OCTOBER 0 3 D I F F E R E N C E (%) 1 9 8 0 - 1 9 9 0
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Fig. 9. Calculated variation in (a) ozone concentration (percent) and (b) temperature (Kelvin) between 1980 and 1990 calculated as a function of altitude and latitude for October conditions.
415
Ozone depletion
0 3 50 ]~
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Fig. 10. Calculated evolution of the ozone density as a function of height calculated at 80~ between 31 July and 29 October. The formation of an ozone hole is reproduced by the model.
the upper stratosphere, associated mainly with an increase in the abundance of chlorine compounds, reaches a maximum near 40 km altitude with values ranging from 5% at the equator to approximately 18% near the poles. Nearly 90% reduction in the ozone concentration is derived south of 75~ in a layer between 16 and 22 km altitude (ozone hole). The change in the mean temperature between October 1980 and October 1990 (Fig. 9b) is negative in most of the stratosphere. The largest cooling is found near the stratopause where it reaches 2.2-3.4 K. Inside the ozone hole region, the calculated cooling is approximately 1.4 K. The evolution in the vertical profile of the ozone density calculated at 80~ from July, 31 to October, 29, shown in Fig. 10, illustrates the formation of the Antarctic ozone hole. Similar reductions in the ozone concentration were reported over the McMurdo station in Antarctica in the late 1980s (see Fig. 5; DESHLER et al., 1990). The relationship between the destruction of ozone south of 60~ and the presence of chlorine monoxide is illustrated by Fig. 1 l a,b. On August 15, although enhanced concentrations of C10 are predicted in a narrow region where sunlight is available, no significant ozone destruction has yet occurred. Two months later, on October 15, ozone has been significantly depleted south of 70~ where high concentrations (750 pptv) of C10 are predicted. The same type of anticorrelation between C10 and 03 mixing ratios has been measured from the NASA-ER2 aircraft during the Airborne Antarctic Ozone Expedition (AAOE) in 1987 (ANDERSON et al., 1989). Numerical models are also used to predict future changes in the chemical composition of the atmosphere and are frequently adopted for assessment studies. Figure 12 shows for example the calculated change in global total ozone between 1960 and 2060 for different scenarios of CFCs production, as calculated by the NASA Goddard Space Flight Center two-dimensional
416
Ozone depletion 21 km
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LATITUDE
Fig. 11. Mixing ratio of C10 (pptv) and 03 (ppmv) calculated as a function of latitude in the vicinity of the Antarctic vortex on (a) 15 August and (b) 15 October (21 km altitude).
0 _
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Fig. 12. Change (percent) in globally integrated ozone as a function of time (between 1960 and 2060) calculated for different CFC production scenarios: lower curve: no cutback in production of CFCs and halons from 1986 levels; middle curve, 50% cutback; lower curve, 95% cutback.
417
Ozone depletion model (KAYE and JACKMAN, 1993). The solid line corresponds to a case in which the productions of CFCs and halons remain constant at their 1986 level. The effect of the 50% and 95% cutbacks in the production of CFCs and halons is also shown by the dashed and dash-dotted lines, respectively. The ozone decrease in year 2060 reaches 8% when the first scenario is adopted but is reduced to 4 and 2%, respectively, when the second and third scenarios are adopted. Note that, because the atmospheric lifetime of the CFCs and halons is of the order of decades to more than a century, the effects of the decrease in the CFCs and halons emissions will only be noticeable after a relatively long period of time.
Ozone changes and the climate system It is now well established that the observed changes in the concentration of CO2 and other "greenhouse" gases have produced perturbations in the radiative forcing of the climate system. Figure 13 shows, for example, the magnitude of this radiative perturbation at the tropopauseas a function of latitude for the period 1850-1990, as estimated by HAUGLUSTAINE et al. (1993). Although the contribution of CO2 is the largest (1.5 W m -2 on the global average), the radiative perturbations associated with the change since 1850 in the abundance of methane, nitrous oxide, and the CFCs (0.7, 0.2 and 0.35 W m -2, respectively) are also substantial. The increase in the radiative forcing resulting from the increasing concentrations of tropospheric ozone is estimated to be 0.55 W m -2 on the global average, with a maximum of 0.9 W m -2 at mid-latitudes in the Northern Hemisphere. The relative contributions of the various gases to the global enhancement (since pre-industrial times) in the radiative forcing at the tropopause are, according to the model of HAUGLUSTAINE et al. (1993), 45% for CO2,
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418
Ozone changes and the climate system
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20% for CH 4, 17% for tropospheric ozone, 13% for the CFCs, 4.9% for N20, and 0.2% for stratospheric water vapour. As pointed out by RAMASWAMY et el. (1992), the depletion of stratospheric ozone resulting from elevated concentrations of CFCs in the stratosphere produces significant perturbations in the radiative budget (ultraviolet and infrared) of the atmosphere. This chemically induced perturbation of ozone has to be compared to the direct radiative forcing of the CFCs. The ozone depletion produced in the upper stratosphere, near 45 km altitude, reduces the absorption of solar ultraviolet, so that more solar energy is provided to the troposphere-surface system (warming). As suggested by Fig. 14, the latitudinal dependence of this radiative effect is weak. Similarly, the ozone depletion in the lower stratosphere contributes to the warming of the troposphere-surface system by solar radiation, but in this case, the effect becomes more pronounced with increasing latitude, since most of the ozone is chemically destroyed in the polar regions. Note, however, that the local radiative heating, and hence the temperature of the lower stratosphere, is reduced near the tropopause as a result of the ozone depletion in this region of the atmosphere. As a consequence, the emission of longwave radiation towards the troposphere is reduced (RAMASWAMY et al., 1992) and an additional cooling mechanism for the troposphere-surface system (curve labelled "temperature" in Fig. 14) needs to be considered. In the model of HAUGLUSTAINE et el. (1993), the net effect of ozone changes (associated with the chemical action of the CFCs) is to slightly amplify the primary forcing of the CFCs (see Fig. 14) even when including the temperature effect. In the tropics, the indirect effect is produced by the ozone depletion in the upper stratosphere, while at high latitudes all the different effects included in the analysis have to be taken into account. As noted recently by SCHWARTZKOPF and RAMASWAMY (1993), the magnitude and the sign of the ozone forcing are critically dependent on the vertical profile of the ozone perturbation near the tropopause.
419
Ozone depletion Increases in ultraviolet radiation due to ozone depletion
An expected consequence of stratospheric ozone reductions is the increase in solar ultraviolet (UV) radiation reaching the lower atmosphere and the surface of the Earth (WMO, 1991; UNEP, 1991). Oxygen and ozone molecules combine to remove all UV-C (200-280 nm) and shorter radiation, but some UV-B (280-320 nm) does penetrate, the amount depending sensitively on the ozone column amount (UV-A, 320-400 nm, is only weakly affected by ozone). For example, a 10% ozone depletion increases the radiation by 3% at 320 nm, and by 11% at 310 nm (solar zenith angle of 45 ~ 300 DU). The UV-A and UV-B energy ranges have the potential to induce significant amounts of photo-chemical activity, variously expressed as changes in tropospheric chemistry, as perturbations to terrestrial and aquatic ecosystems, and as potential health effects on humans and animals (UNEP, 1991). Many of these effects have been studied in detail, and in some cases quantitative sensitivity studies of the effect can be made (MADRONICH et al., 1991). The effectiveness of UV radiation with regard to inducing specific photo-chemical processes is shown in Fig. 15. Such plots are commonly dubbed monochromatic action spectra, and can be exceedingly difficult to determine. Most are found to decrease with increasing wavelength, and the steepness of this fall-off largely determines the sensitivity to ozone depletion. Atmospheric transmission, on the other hand, increases with wavelength as shown in Fig. 16, so that the active radiation peaks at some intermediate wavelength. Combining
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420
Increases in ultraviolet radiation due to ozone depletion
the spectral effectiveness and the atmospheric transmission at each wavelength leads to the following definitions: spectral dose rate = F(2) B(A,) dose rate = f F(2) B(2) clA, dose = f f F(2) B(2) d2 dt where F(2) is the spectral irradiance at wavelength 2, B(;I,) is an action spectrum, and t is any integration time (MADRONICH, 1993a,b). Daily doses for DNA damage caused by UV-B radiation are illustrated in Fig. 17, for clear sky conditions, and recent average ozone column as measured by the Total Ozone Mapping Spectrometer (TOMS) from the Nimbus 7 satellite (STOLARSKI et al., 1992). Trends in the daily doses are shown in Figs. 18 and 19, and are based on TOMS total ozone values between January 1979 and December 1989. No significant change is seen in the tropics, but relative trends (Fig. 18) generally increase towards the polar regions while the energy increments (Fig. 19) are shifted in the direction of the summer and the sub-solar tropics. Comparable increases in UV doses can be computed for many different action spectra. Table I summarizes the results for three different spectra, and for the incidence of nonmelanoma skin cancer. The relative sensitivity to a 1% ozone depletion is shown for a number of biological and chemical processes in Table II. The large variation of these factors and possibly large uncer-
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421
Ozone depletion
DNA DALLY DOSE, J m -2 Day -1 (1979 - 1989 Average) 90l_
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422
Increases in ultraviolet radiation due to ozone depletion DNA DALLY DOSE CHANGE, J m -2 Day -1 Per Decade (1979 - 1989) 90 ~...:....~..................~..~..li::!:.i~:. ~
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TABLE I EXPECTED INCREASES (PERCENT) a IN ANNUAL U V DOSES AND SKIN CANCER INCIDENCE DUE TO STRATOSPHERIC OZONE DEPLETION FROM 1 9 7 9 TO 1 9 9 2
Latitude
Total ozone
85 75 65 55 45 35 25 15 5 5 15 25 35 45 55 65 75 85
-8.8 -9.0 -7.4 -7.4 -6.6 -4.8 -2.7 -1.5 -0.6 -1.1 -1.9 -2.6 -4.0 -5.6 -9.0 -15.0 -19.5 -21.1
N N N N N N N N N S S S S S S S S S
_+ 3.2 _+ 2.9 _+ 1.7 _+ 1.3 _+ 1.2 _+ 1.4 _+ 1.5 _+ 1.1 _+ 1.6 _+ 1.4 _ 1.3 _+ 1.6 _+ 1.6 _ 1.4 +_ 1.5 _+ 2.0 _+ 2.6 _+ 3.0
Erythema induction dose
DNA damage dose
Skin cancer dose
Basal cell carcinoma incidence b
Squamous cell carcinoma incidence b
7.1 7.6 7.6 7.2 6.5 5.0 3.0 1.7 0.7 1.2 2.2 3.1 4.8 7.2 10.9 16.3 24.1 31.0
14.8 14.9 14.1 12.9 10.9 8.2 4.8 2.6 1.2 2.0 3.5 5.0 7.9 12.5 19.7 30.5 49.8 72.0
10.6 10.8 10.3 9.5 8.1 6.1 3.5 1.9 0.8 1.4 2.5 3.6 5.7 8.9 14.2 21.9 34.0 46.5
15.1 15.4 14.7 13.5 11.6 8.6 5.0 2.7 1.2 2.0 3.6 5.1 8.1 12.7 20.4 31.9 50.6 70.6
28.5 29.1 27.7 25.4 21.6 16.0 9.0 4.8 2.1 3.6 6.5 9.2 14.9 23.9 39.3 64.0 107.7 159.6
_+ 1.7 _+ 1.7 _+ 1.7 _+ 1.7 _ 1.7 _+ 1.8 _ 1.9 _+ 1.4 _+ 1.9 _+ 1.7 _ 1.5 _+ 1.7 _ 1.6 _+ 1.6 _+ 2.0 _+ 3.0 _+ 5.4 _+ 6.8
+_ 3.6 _+ 3.3 + 3.2 +_ 3.2 _+ 3.0 _+ 3.0 __.3.1 _+ 2.3 _+ 3.0 +_ 3.0 _+ 2.4 _+ 2.4 _+ 2.6 __.2.7 _+ 3.6 _ 5.8 _+ 12.0 _ 17.6
_+ 2.5 +_ 2.4 _+ 2.3 _+ 2.3 _+ 2.2 _+ 2.2 +_ 2.2 __. 1.6 __ 2.2 _+ 2.0 _ 1.7 __. 1.9 _+ 1.9 _+ 1.9 _+ 2.6 _+4.1 _+7.7 +_ 10.5
_+ 5.6 _+ 5.8 __. 5.6 _+ 5.3 _ 4.7 _+4.0 _ 3.5 + 2.4 _.+3.1 _+ 2.8 _+ 2.6 _+ 3.1 _+ 3.6 _+4.8 _+ 7.4 +_ 12.2 _+ 21.4 _+ 31.2
_ 11.2 _+ 11.5 _+ 11.0 _+ 10.3 __.9.0 _+ 7.6 _+ 6.4 +_4.4 +_ 5.5 _+ 5.2 _+4.8 _ 5.8 _+ 6.8 _ 9.2 _+ 15.1 _+ 26.6 _+ 52.0 +_ 83.6
aEvaluated over the 14-year data record, expressed as percent relative to the 1979 intercept. Uncertainties are one standard deviation. bBased on skin cancer dose increase and relevant biological amplification factors.
423
Ozone depletion
TABLE II RADIATION AMPLIFICATIONFACTORS (RAFs) AT 30~
Effect
DNA related Mutagenicity and fibroblast killing Fibroblast killing Cyclobutane pyrimidine dimer formation (6-4) photoproduct formation Generalized DNA damage HIV- 1 activation DNA damage in alfalfa Plant effects Generalized plant spectrum Inhibition of growth of cress seedlings Isoflavonoid formation in bean Inhibition of phytochrome induced anthocyanin synthesis in mustard Anthocyanin formation in maize Anthocyanin formation in sorghum Photosynthetic electron transport Overall photosynthesis in leaf of Rumex patientia Membrane damage Glycine leakage from E. coli Alanine leakage from E. coli Membrane bound K+-stimulated ATPase inactive Skin Elastosis Photocarcinogenesis, skin oedema Erythema reference Skin cancer in SKH-1 hairless mice
RAF January
July
[1.71 2.2 0.3 [2.0] 2.4 [2.3]2.7 1.9 [0.1 ] 4.4 0.5
[2.71 2.0 0.6 [2.1] 2.3 [2.3]2.5 1.9 [0.1 ] 3.3 0.5
2.0 [3.6] 3.8
[0. I ] 2.7 1.5 0.2 1.0 0.2 0.2
0.2 0.4 [0.3] 2. I
1.6 3.0
[0.1 ] 2.3 1.4 0.2 0.9 0.2 0.3
0.2 0.4 [0.3] 1.6
1.1 1.6 1.1 1.4
1.2 1.5 1.1 1.3
Damage to cornea Damage to lens (cataract)
1.2 0.8
1.1 0.7
Movement Inhibition of motility in Euglena gracilis
1.9
1.5
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Other Immune suppression Robertson-Berger meter 03 + hv ---) O(1D) + 0 2
[0.4] 1.0 0.8 1.8
[0.4] 0.8 0.7 1.6
Values in brackets show the effect of extrapolating original data to 400 nm with an exponential tail, for cases where the effect is larger than 0.2 RAF units. From MADRONICHet al. (1991). 03 photolysis from MADRONICHand GRANIER (1992), DNA damage in alfalfa estimated by similar calculation using action spectrum from QUArrE et al. (1992).
424
Policy strategies to protect the ozone layer tainties should be noted. The photodissociation of tropospheric ozone, with a relatively high sensitivity, is of some interest because it is the main source of the hydroxyl radical (OH), which in turn determines the lifetime for a number of tropospheric chemicals including methane, carbon monoxide, and nitrogen oxides. This reaction therefore provides an interesting and possibly important link between stratospheric ozone depletion and tropospheric chemistry (MADRONICH and GRANIER, 1992). Atmospheric optical characteristics other than stratospheric ozone also affect surface UV radiation, as illustrated in Fig. 6. Some of these factors are quite difficult to model on the local-to-global scale, and direct measurements of UV trends would be preferable. Unfortunately, as of 1993, the UV measurement database is less than adequate. Outside the polar regions, the expected changes in UV are still smaller than the variability due to other factors such as clouds and tropospheric pollutants. In the Northern Hemisphere, several studies have claimed detection of a long-term trend, albeit in opposite directions: increased UV in the Swiss Alps (BLUMTHALERand AMBACH, 1990) and in Washington, DC (CORRELL et al., 1992), but decreased in Moscow (GARADZHA and NEZVAL, 1987) and in various other US locations (SCOTTOet al., 1988). In addition to the obvious potential bias from urban locations (GRANT, 1988), questions have been raised about the calibration of the broadband instruments used in some of these studies (DELuIsI, 1993). The ground-based Dobson ozonemonitoring network does, however, provide clear evidence for a long-term shift in the ratio of different UV wavelengths, as these are used for the ozone determinations (STOLARSKIet al., 1992). Detailed spectroscopic monitoring in the UV-B region has begun only recently, and at only a few sites. Although the data record is still not long enough to detect long-term trends, early measurements (see Fig. 21) shows that UV-B trends due to ozone reductions can be detected above other putative trends in other factors such as clouds and local pollutants. In polar regions, too, there is no reliable long-term UV record. However, polar ozone depletion in the southern hemisphere is so severe that the UV increases are clearly visible in association with the ozone hole (see Fig. 20), and parcels of ozone poor air and increased UV have been detected at mid-latitudes following the springtime break-up of the polar vortex (ROY et al., 1990; STAMNES et al., 1990; LUBIN et al., 1992; SECKEMEYER and MCKENZIE, 1992). One study reported a 6-12% reduction phytoplankton productivity due to the UV-B increase under the ozone hole (SMITH et al., 1992). The future of the UV environment is closely tied to the future of stratospheric ozone and tropospheric pollution. The first is not expected to recover for at least decades (WMO, 1991), while the second is more complex and known to be increasing in some regions while decreasing in others. Cloudiness changes may also be an issue. Direct, reliable monitoring of UV levels over this transitional time remains a highest priority.
Policy strategies to protect the ozone layer Over the last two decades, several measures have been implemented to help protect the ozone layer. For example, in 1979, after it became evident to the public that chlorofluorocarbons were suspected of depleting ozone, the US, Canada and Sweden decided to ban the use of CFCs in aerosol cans. A few years later, in March 1985, a global framework conven-
425
Ozone depletion
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Fig. 20. Top panel: DNA-damaging radiation, computed from the spectral irradiance measured at the South Pole and at Barrow, Alaska, for same solar zenith angle. The UV-B enhancements due the Antarctic ozone hole are clearly visible. Bottom panel: simultaneous comparison of visible radiation (400-600 nm), showing much smaller differences than in the top panel and supporting the hypothesis that the measured UV-B enhancements are due to ozone depletion, rather than changes in other factors such as cloud cover, aerosols, or surface albedo (from MADRONICH, 1993a, data courtesy R. BOOTH). tion was signed in Vienna and set a precedent: it acknowledged that the ozone question was a global problem that required international action and accelerated scientific research. It led to the Montreal Protocol concluded in September 1987, which called the signatory parties to reduce by year 1992 the emission of CFCs and of halons by 50% of their 1986 levels. Access to the controlled substances was, however, provided for a "grace period" to developing countries. The Montreal Protocol is regarded as a landmark for the protection of the global environment. As the scientific community demonstrated the urgency of the problem and the need for additional regulatory measures (as the observed ozone depletion was larger than predicted by
426
Policy strategies to protect the ozone layer 60
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Fig. 21. Trends in UV-B radiation measured in Toronto, Canada between early 1989 and early 1993. The wavelength-dependence of the trend parallels the ozone absorption cross section, as expected from theory (from KERR and McELRou 1993). atmospheric models), the protocol was amended. At a meeting of the signatory parties held in London (June, 1990), control measures were introduced for additional halocarbons and a total phase-out of CFCs and halons by the year 2000 was decided. A second revision implemented in Copenhagen in November 1992, called for a phase-out of halons by 1994 and
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Fig. 22. Atmospheric chlorine load (ppbv) as a function of time (years 1960-2080) in response to the emission of halocarbons as limited by the Montreal Protocol (1987), the London amendments (1989) and the Copenhagen revisions (1992). The critical level of 2 ppbv above which the Antarctic ozone hole is formed during springtime is indicated.
427
Ozone depletion CFCs by 1996. Control measures were also introduced for substances such as the hydrochlorofluorocarbons which are used as substitutes for the CFCs. Figure 22 shows how the atmospheric chlorine loading for the period 1960-2080 is expected to be modified in response to recent international agreements. It is interesting to note that, even with the rapid phase-out of ozone depleting substances, as decided in Copenhagen, the level of inorganic chlorine in the stratosphere should remain above the critical level of 2 ppbv until the year 2060. The 2 ppbv level is considered as critical because it corresponds to a threshold above which the springtime ozone hole in Antarctica has been produced. The slow recovery of the stratosphere is a direct consequence of the long atmospheric lifetime of the chlorofluorocarbons.
Issues for research pertaining to future climates It is clear from the foregoing sections that ozone depletion is a complex phenomenon with far reaching consequences. Areas of future research can conveniently be divided into those related to an improved understanding of the depletion itself and those related to a clearer understanding of its effects.
Improved observation and understanding of ozone depletion The discovery of the polar ozone depletion (FARMAN et al., 1985) concentrated attention on the lower stratosphere, with emphasis on altitudes from 12 to 20 km. The concentration of ozone (molecules per unit volume) is largest in this region, which consequently provides a large part of the total ozone column. Significant ozone loss in the lower stratosphere, therefore, immediately translates into an appreciable reduction in the total ozone column. As noted, lower stratospheric ozone is also important for radiative forcing of the climate at the surface. Future progress requires that we continue to observe the global ozone field, including the vertical distribution, from at least the upper troposphere to the mesosphere, as well as the total column integral. This is necessary to determine the size and characteristics of its changes and to develop the ability to separate those changes that are natural and cyclical from those that are indicative of long-term change, especially change due to human activities. One of the major issues is to understand the causes for the lower stratospheric ozone depletion in middle latitudes. This may be due in part to chemical processes. Future efforts to refine the knowledge of the role of gaseous chemistry will take place, but greater emphasis on the sources and role of sulphate aerosols is clearly required. The relationship between the mid-latitude ozone decrease and the large ozone losses in polar regions must also be clarified. This is directly connected to the controversy over the way in which the polar vortex functions in the ozone depletion process. One view holds that the vortex wall effectively isolates the air in its interior, so that all the depletion takes place in a "containment vessel". This low-ozone air is mixed with the surrounding atmosphere when the vortex breaks up. The opposing view is that air continuously flows through the vortex, where its ozone is depleted and inorganic chlorine is converted to active forms. It will be
428
Conclusion necessary to resolve this issue. In any case, it is important to understand how ozone destruction in polar regions may influence its global distribution. Finally, further refinement of our understanding of the processes, physical and chemical, involved in polar ozone loss is required to improve the capability of models (including 3-D models) to predict ozone loss with confidence.
Improved assessment of the effects of ozone depletion Improved assessment of the effects of ozone depletion on climate requires further development of models, preferably 3-D models, with high vertical resolution to predict and represent perturbed ozone profiles with better realism and for comparison with observation. Radiative calculations in the lower stratosphere are difficult, because there are a number of effects of similar size that must all be computed with good accuracy to obtain a trustworthy result. It seems likely that further attention to radiative transfer models, both in the UV and IR, will be required. In particular, interactions between radiation fields and changing cloud characteristics with changing atmospheric temperature will need to be addressed. Clouds (and to a lesser extent aerosols) are of major importance when estimating the penetration of solar UV-B to the surface. Models that use observed cloud parameters need to be improved and validated, in order to be able to predict changing UV dosages at the surface. Calculations from models exhibiting different levels of complexity and parameterization will need to be validated through comparison with well calibrated ground-based measurements at a number of well chosen locations, over a long period, preferably at least 2 solar cycles (22 years). Finally, further work must be done to reduce the uncertainties in the response functions for different biological damage mechanisms.
Conclusion Very large ozone depletions have been observed every year in the late 1980s and early 1990s over Antarctica. All evidence indicates that these result from the anthropogenic release of chlorine-containing compounds over the previous several decades. Smaller ozone decreases have been observed over the extratropics for the past 10-13 years. Large advances have been made in understanding the natural processes that define the undisturbed ozone distribution and the ways in which human activities perturb them, but several questions still require answers. We are just beginning to understand the climatic effects, the increases in surface UV and the consequent biological damage, that result from ozone depletion. Many problems remain to be solved before we can confidently predict the size, distribution, and effects of ozone depletion.
Acknowledgements The National Center for Atmospheric Research is sponsored by the National Science Foundation.
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431
Ozone depletion MCCORMICK, M. P., HAMILL, P., PEPIN, T. J., CHU, W. P., SWISSLER, T. J. and MCMASTER, L. R., 1979. Satellite studies of the stratospheric aerosols. Bull. Am. Meteorol. Soc., 60: 1038-1046. MCKINLAY, A. F. and DIFFEY, B. L., 1987. A reference action spectrum for ultra-violet induced erythema in human skin. In: W. F. PASSCHIERand B. F. M BOSNJAKOVIC(Editors), Human Exposure to Ultraviolet Radiation: Risk and Regulations. Excerpta Medica, International Congress Series 744, Amsterdam. MOLINA, L. T. and MOLINA, M. J., 1986. Absolute absorption cross sections of ozone in the 185- to 350-nm range. J. Geophys. Res., 91:14501-14508. QUAITE, F. E., SUTHERLAND,B. M. and SUTHERLAND,J. C., 1992. Action spectrum for DNA damage in alfalfa lowers predicted impact of ozone depletion. Nature, 358: 576-578. RAMASWAMY, V., SCHWARZKOPF,M. D. and SHINE, K. P., 1992. Radiative forcing of climate from halocarbon-induced global stratospheric ozone loss. Nature, 355:810-812. ROCHE, A. E., KUMER, J. B., MERGENTHALER, J. L., ELY, G. A., UPLINGER, W. G., POTTER, J. F., JAMES, T. C. and STERRIT,L. W., 1993. The Cryogenic Limb Array Etalon Spectrometer (CLAES) on UARS: experiment description and performance. J. Geophys. Res., 98: 10763-10775. RoY, C. T., GIES, H. P. and GRAEME, E., 1990. Ozone depletion. Science, 347: 235-236. SCHWARZKOPF, M. D. and RAMASWAMY,V., 1993. Radiative forcing due to ozone in the 1980's: dependence on altitude and ozone change. Geophys. Res. Lett., 20: 205-208. SCOTTO, J., COTTON, G., URBACH, F., BERGER, D. and FEARS, T., 1988. Biologically effective ultraviolet radiation: surface measurements in the United States, 1974 to 1985. Science, 239: 762-764. SECKMEYER, G. and MCKENZIE, R. L., 1992. Elevated ultraviolet radiation in New Zealand (45~ contrasted with Germany (48~ Nature, 359:135. SEKERA, Z. and DAVE, J. V., 1961. Diffuse transmission of solar ultraviolet radiation in the presence of ozone. Ap. J., 133: 210-227. SETLOW, R. B., 1974. The wavelengths in sunlight effective in producing skin cancer: a theoretical analysis. Proc. Natl. Acad. Sci., 71: 3363-3366. SMITH, R. C., PREZELIN,B. B., BAKER, K. S., BIDIGARE,R. R., BOUCHER, N. P., COLEY, T., KARENTZ, D., MACINTYRE, S., MATLICK, n. A., MENZIES, D., ONDRUSEK,M., WAN, Z. AND WATERS, K. J., 1992. Ozone depletion: ultraviolet radiation and phytoplankton biology in Antarctic waters. Science, 255: 952-959. STAMNES, K., SLUSSER, J., BOWEN, M., BOOTH, C. and LUCAS, T., 1990. Biologically effective ultraviolet radiation, total ozone abundance and cloud optical depth at McMurdo Station, Antarctica September 15 1988 through April 15 1989. Geophys. Res. Lett., 17: 2181-2184. STOLARSKI, R. S. and CICERONE,R. J., 1974. Stratospheric chlorine: a possible sink for ozone. Can. J. Chem., 52: 1610-1615. STOLARSKI, R. S., BOJKOV, R., BISHOP, L., ZEREFOS, C., STAEHELIN,J. and ZAWODNY,J., 1992. Measured trends in stratospheric ozone. Science, 256: 342-349. TAYLOR, F. W., RODGERS, C. D., WHITNEY, J. G., WERRETT, S. T., BARNETT, J. J., PESKETT, G. O., VENTERS, P., BALLARD, J., PALMER, C. W. P., KNIGHT, R. J., MORRIS, P., NIGHTINGALE, T. AND DUDHA, A., 1993. Remote sensing of atmospheric structure and composition by pressure modulator radiometry from space: the ISAMS experiment on UARS. J. Geophys. Res., 98:10799-10814. UNEP, 1991. In: J. C. VAN DER LEUN, M. TEVINI and R. C. WORREST (Editors), Environmental Effects Panel Report- 1991 Update. United Nations Environmental Programme, Nairobi, Kenya. URBACH, F., BERGER, D. and DAVIES, R. E., 1974. Field measurements of biologically effective UV radiation and its relation to skin cancer in man. In: A. J. BRODERICK and T. M. HARD (Editors), Proceedings of the Third Conference on Climatic Impact Assessment Program. US Dept. of Transportation, February. WATERS, J. W., FROIDEVAUX,L., READ, W. G., MANNEY, G. L., ELSON, L. S., FLOWER, D. A., JARNOT, R. F. AND HARWOOD,R. S., 1993. Stratospheric C10 and ozone from the Microwave Limb Sounder on the Upper Atmosphere Research Satellite. Nature, 362: 597-602. WMO, 1988. Report of the International Ozone Trends Panel- 1988. World Meteorological Organization, Global Ozone Research and Monitoring Project, Report No. 18, Vol. 1, Geneva, Switzerland, 441 pp. WMO, 1991. Scientific Assessment of Ozone Depletion: 1991. World Meteorological Organization, Global Ozone Research and Monitoring Project, Report No. 25, Geneva, Switzerland. WOFSY, S. C., MCELROY, M. B. and YUNG, Y. L., 1975. The chemistry of atmospheric bromine. Geophys. Res. Lett., 2:215-218.
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C h a p t e r 12
Human effects on climate through the large-scale impacts of land-use change A. HENDERSON-SELLERS
Introduction People and land-use change The human population of the world is growing very rapidly. More people demand additional food, water for drinking and cleaning, and shelter. Human pressure is altering the global environment and the changes are most extreme at the continental surface: farm fields replace forests, reservoirs flood valleys and cities sprawl ever more widely. Human activities cause, or contribute to, desertification, deforestation, salinization and soil erosion but also reforestation, irrigation and landscape "management". Human-induced land-use change (the process), and consequent land-cover change (the outcome), is an inescapable feature of current and future environments. The total ice-free land area of the world is about 13,382 million ha 1 of which around 11% is under permanent cultivation, 24% is pasture, 31% is forest and woodland and the remaining 34% includes tundra, desert, degraded land, built-up areas and parks. About half the world's continental surface has already been modified by human activities (UNEP, 1992) although it remains uncertain whether these landscape changes will be an important factor in affecting the future climate. In this chapter, the relationships between climate and the present, and likely future, land-use and land-cover of the continents are explored. Most of the discussion is about the effects which people may have on future climates. People have already become a major environmental agent (cf. CLARK and MUNN, 1986). It seems likely that the largest impact of land-use/land-cover change on future climate will be as a result of greenhouse gas emissions (see Chapter 9 by WANG et al. and the section on Land-cover changes and global climate). Other land-cover dependent factors which may augment or reduce climatic impacts include the emission of aerosols (both particulates and droplets) which might modify the atmospheric transmissivity or augment natural changes in
1 Notes on units of area and weight used in this chapter. Dealing with global land-use change involves large quantities. Here we use a million hectares (1 million ha) as the base unit of area and a Petagram (Pg) as the base unit of weight. These are related to other quoted areas and weights as follows: 1 hectare (1 ha) = 104 m2; 1 billion ha=1000 million ha; lkm 2=106m 2=102 ha=10 -4 million ha; ltonne=106g; 1Pg (petagram)= 1015g=1012kg=lGt (gigatonne); 1Tg (teragram)=1012g=109kg=0.001Pg; 1 ppmv=l.9 M 1011 kg = 0.19 M Pg (where M is the molecular weight); 1 ppbv = 1.9 M 108 kg = 0.00019 M Pg. (The factor 1.9 comes from a combination of changing ppv to mass per volume and then integrating over the atmospheric column on Earth.)
433
Human effects on climate through the large-scale impacts of land-use change cloud amount and type (e.g. Chapter 10 by ANDREAE;PENNERet al., 1992); changes in surface reflectivity and disturbances to the hydrological cycle (e.g. MCGUFFIE et al., 1995). People now "consume" about 10 tonnes of minerals per person annually, the total (50 Pg) exceeding by a factor of three the 16.5 Pg of sediment transported each year to the sea by rivers (APSIMON et al., 1990) which, itself, already contains a significant additional burden due to human activities. Catastrophic erosion of many centimetres of tropical soil following deforestation can undo hundreds, even thousands of years of soil formation. Even the slower, globally averaged, soil erosion rate of about 0.5-2.0 tonnes per ha per year is a critically important aspect of current continental change (UNEP, 1992). RICHARDS (1986, 1990) has studied world changes in land-cover over the past three centuries. Of the 13,382 million ha of ice-free land, he calculates that woodlands and forests have decreased in area by 1,200 million hectares; that croplands have increased by 1,200 million hectares while grasslands and pasture have declined in area by 560 million hectares. Over the 15 years from 1973 to 1988, FAO (1990) estimates that croplands have increased by 57 million ha, pastures decreased by 11 million ha and woodlands and forests decreased by 141 million ha. These estimates and Fig. 1 indicate that land-use/land-cover changes are accelerating. Not only do land-use/land-cover changes vary with time, but also they are not uniform around the world: expanding empires in Europe, North America, Africa, Australia and New Zealand and, more recently, population pressure in many tropical countries cause different changes at different times. Future projections of land-use change and, thus, land-cover change will be a function of population change but also of affluence, technological development, world economics and dietary requirements (e.g. vegetarian versus omnivory). Moreover, the climatic impacts of
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TABLE I ESTIMATED AND PROJECTED POPULATION SIZE BY REGION, 1950, 1990 AND 2025 (PERCENTAGE SHARE OF WORLD POPULATION GIVEN IN PARENTHESES)
Region World total Industrialized countries Developing countries Africa North America Latin America Asia Europe Oceania Former Soviet Union
1950 2,516 (100) 832 (33.1) 1,684 (66.9) 222 (8.8) 166 (6.6) 166 (6.6) 1,377 (54.7) 393 (15.6) 13 (0.5) 180 (7.2)
1990 5,292 (100) 1,207 (22.8) 4,086 (77.2) 642 (12.1) 276 (5.2) 448 (8.5) 3,113 (58.8) 498 (9.4) 26 (0.5) 289 (5.5)
2025 8,504 (100) 1,354 (15.9) 7,150 (84.1) 1,597 (18.8) 332 (3.9) 757 (8.9) 4,912 (57.8) 515 (6.1) 38 (0.4) 352 (4.1)
Source: United Nations Population Division, Worm Population Prospects 1990 (UNITEDNATIONS, New York, 1991), pp. 226-233,244-245, 252-255, 264-265, 274-275, and 582-583. Modified from WORLDRESOURCES1992-1993 (1992).
human-induced land-use change may be critically dependent upon the location as well as the nature of the change; in the next century the greatest pressure on the land will be in the tropics (BILSBORROW and OKOTH-OGENDO, 1992). Table I lists a recent UNITED NATIONS (1991) projection of population increases by world region. These estimates, which depend crucially on assumptions made about life expectancy and, particularly, fertility rates, translate to a global population increase 10% larger than the 1982 evaluations by the same agency. An assumption of fertility stabilizing at a replacement level of about 2.06 indicates that the global population will reach 10 billion by 2050, 11.2 billion by 2100 and will, ultimately, stabilize at 11.6 billion soon after 2200 (UN, 1991; see also EL-BADRY, 1992). These massive increases in the number of people the planet has to support will greatly modify many aspects of the environment including the climate. Climatic sensitivity to land-cover It is often claimed that land-cover change has a significant impact on climate (e.g. SAGANet al., 1979; MYERS, 1992). No such impact has yet been detected on a global scale (e.g. DICKINSON, 1986; HENDERSON-SELLERS, 1990a), although there is persuasive evidence from observations and from modelling studies that local-scale climate changes can follow land-cover change (e.g. ECKHOLM and BROWN, 1977; DICKINSON, 1980; OTTERMAN, 1982; NOBRE et al., 1991; CHANGNON, 1992) and global climate model studies have shown that massive, unrealistic land-cover changes, such as comparing fully irrigated continents with a situation in which all land is totally arid, do alter features of the global climate (e.g. SHUKLA and MINTZ, 1982). On the other hand, modelling of extreme, but more realistic, land-cover changes across all continents, such as extensive desertification or the total removal of all tropical forests, has not produced detectable global responses (e.g. CHARNEY, 1975; HENDERSON-SELLERS et al., 1993). 435
Human effects on climate through the large-scale impacts of land-use change Land-cover changes can affect some of the factors critical to the global-scale climate, particularly the absorption of solar radiation and the greenhouse gas loading, but their importance relative to other controlling features including the planetary rotation rate and the ocean circulation is yet to be determined. Although the practical importance of studying climate and climate change derives from human dependence upon benign conditions for agriculture, water collection and habitation, meteorological (and indeed land-use change) records do not extend very far into the past. Therefore many claims of land-use and land-cover change impacts cannot be fully quantified. For example, MYERS (1992, page xxii) cites examples in SE Asia and India where deforestation is believed to have changed the local climate and so disrupted rainfall in Penang and Kedah in Malaysia that 20,000 ha of rice paddy fields were abandoned and a further 72,000 ha yielded significantly smaller crops than usual. These claims of close relationships between land-cover and climate are balanced by recent reviews (e.g. LE HOUEROU, 1992) of possible mechanisms for desertification which have not favoured bio-climatic feedback (see section on Model studies of deforestation). Indeed, even the expansion of the Sahel has been questioned (e.g. HELLDEN, 1991; TUCKER et al., 1991). There are two possible effects of human-induced land-cover change on the Earth's climate:
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Fig. 2. Human-induced land-use changes are responsible for the four major causes of soil degradation: (a-d) after MIDDLETONand THOMAS, 1992; (e) after UNEP, 1992): (a) deforestation; (b) agriculture; (c) overgrazing; (d) overexploitation of vegetation for domestic use; (e) processes and causes of land degradation.
436
Introduction (i) immediate impacts which are local to the land-use change and (ii) larger-scale impacts which disturb the general circulation and/or the global mean climate. It is more difficult to envisage how the latter can occur since the continents extend over only about 30% of the Earth's surface and probably less than half of this total area is, as yet, affected by human activities (e.g. Fig. 2). One possible trigger of global climatic change is the increase in greenhouse gases in the atmosphere (e.g. HANSEN et al., 1981; HOUGHTON et al., 1990, 1992) (see Chapter 9 by WANG et al.) or an increase in aerosols (see Chapter 10 by ANDREAE) or a nuclear war (Chapter 4 by RAMPINO). To date, however, modelling studies of land-cover change have only shown it to produce local-scale climatic impacts (e.g. CHARNEY, 1975; SUD and SMITH, 1985; LAVAL, 1986; DICKINSON and HENDERSONSELLERS, 1988; SHUKLA et al., 1990) except when the altered region is an important contributor (source), or absorber (sink), of greenhouse gases. Even in this case the total enhanced greenhouse signal has yet to be isolated from natural climatic variability (e.g. FOLLAND et al., 1990) while the contribution due to land-cover changes is not confirmed. The impact of doubling the amount of greenhouse gases in the atmosphere is to increase the net surface energy budget by about +4 W m -2 (e.g. HOUGHTON et al., 1990). If one-quarter to one-third of that greenhouse gas increase is due to land-cover change (cf. HOUGHTON, 1991 and section on Land-cover change influences on climate), this means an impact of about + 1 W m -2. As will be described later, the possible effect of aerosols from both humaninduced and natural biomass burning is of a similar magnitude but the opposite sense: a cooling of-1 W m -2 (PENNER et al., 1992 and Chapter 10 by ANDREAE). A plausible increase in continental albedo of +5% (say from forest albedos of 15% to grassland albedos of 20%) gives a decrease in absorbed solar radiation of around -3 W m -2. By contrast, while urban energy expenditure is an important contributor to the urban heat island effect (e.g. DABBERDT and DAVIS, 1978; OKE, 1982, 1987; CHANGNON, 1992 and Chapter 13 by
CLEUGH), heat released by human activities is small when compared to natural sources of energy. MUNN and MACHTA (1979) estimate that 1970's human energy use, distributed globally, equalled +0.016 W m -2, cf. the geological energy flow globally from the Earth's interior of +0.06 W m -2. These simplistic calculations imply that the large-scale effect of land-cover change through surface albedo increases combined with possible aerosol cooling could very roughly compensate projected greenhouse warming due to land-cover and other anthropogenic activities. In the following sections, the possible impacts of land-cover change on future climate are assessed. Comparisons are also drawn between the likely large-scale effects of land-cover change and other human-induced and natural impacts on future climate described in other chapters of this book. The goal of this chapter is to offer a framework within which possible large-scale impacts on climate of human-induced land-cover change can be quantified. The emphasis on the large-scale is intentional but in no way denies the local climatic and hydrological impacts caused by land-cover changes. The latter are clearly of importance in the location itself but remain somewhat difficult to measure on anything but very small scales. For example, in the recent text on human transformations of the Earth (TURNER et al., 1990), while the chapter on urbanization (BERRY, 1990) quantified the impact of cities on their local climate (and see Chapter 13 by CLEUGH) those on Amazonia (SALATIet al., 1990) and the USA's Great
437
Human effects on climate through the large-scale impacts of land-use change Plains (RIEBSAME,1990) did not and that on Nigeria (UDOet al., 1990) described primarily the impact of the Sahelian drought. Moreover, small-scale climatic changes cannot impact other regions unless their effect is "transmitted" by the atmosphere or oceans. To date, such remote impacts have only been shown to occur for relatively large-scale land-use changes (e.g. BONAN et al., 1992). This chapter therefore focusses on possible large-scale climatic impacts and on the physical mechanisms underpinning the response to likely human-induced land-use change. Firstly, a review of all types of land-use change (see next section) and of the mechanisms by which these changes can affect climate (section on Land-cover change influences on climate) is given. Then the possible impacts of tropical land-use changes, especially deforestation and desertification, are considered in the section on Regional-scale impacts of landcover change on climate. This acts as a prelude to an assessment of future climates in the final section.
Human-induced land-use change The major types of human-induced land-use change are deforestation (and reforestation), desertification (which often includes overgrazing and excessive exploitation of vegetation), agricultural expansion and soil erosion. These changes are widespread and prompt other responses such as soil degradation and salinization (Fig. 2). Dam-building, reclamation and erosion of coastal zones, irrigation of arid land, urbanization and industrialization are often very important locally but seem unlikely to cause anything other than local climatic changes (e.g. CHANGNON,1992). Their secondary importance is partly because of their smaller spatial extent which also exacerbates the other reason: their smaller feedbacks into the climatic system.
Agriculture and engineering Food demand will increase as populations increase and diet patterns change. In the remaining years of this century, about 1.3 billion people will be added to the global population (see Introduction and Table I); rising incomes, however, may account for 30-40% of the increased demand for food in developing countries and about 10% in industrial nations. Thus over the next few decades, the global food system must be managed in order to increase food production by 3-4% every year. Table IIa compares the extent of land areas converted to agricultural crops in two periods: 1860-1919 and 1920-1978. Despite the increasing population, RICHARD's (1990) estimates of conversion rates do not differ much between the two periods, in agreement with the estimates listed in Table IIb which shows a decrease in the per capita gross cropped area but a considerable increase in fertilizer use on agricultural land. Increases in cropped areas in recent decades have often extended cultivation on to marginal lands prone to degradation and erosion (e.g. MYERS, 1984; GLANTZ, 1994). For example, expansion of agricultural areas encompasses increased use of irrigation and hence the possibility of salinization. In 1984, HENDERSON-SELLERS and GORNITZ estimated that the extent of irrigation in 21 arid countries increased by 37 million ha over the preceding 30 years
438
Human-induced land-use change TABLE IIa LAND AREASCONVERTED INTO REGULARCROPPING(106 HA) FROM 1860 TO 1978 (AFTERRICHARDS, 1990; REPRINTEDWITHTHE PERMISSIONOF CAMBRIDGEUNIVERSITYPRESS)
World region
Africa North America Central America and the Caribbean South America Middle East South Asia Southeast Asia East Asia Europe (excluding Soviet Europe) Former Soviet Union Australia/New Zealand TOTAL Net area converted to crops
First period ( 1860-1919)
Second period (1920-1978)
To crops
To crops
15.9 163.7 4.5 35.4 8.0 49.9 18.2 15.6 26.6 88.0 15.1 440.9
From crops 2.5 0.2 6.0 8.7 432.2
90.5 27.9 18.8 65.0 31.1 66.7 39.0 14.5 13.8 62.9 40.0 470.2
From crops 29.4 0.4 8.4 12.7 50.9 419.3
(FRAMJI and MAHAJAN, 1969; F A O Production Yearbooks). However, salinization of irrigated fields destroys up to 125,000 ha year -1 (UNCOD,
1977), or 3.75 million ha in
30 years. By the late 1970s, soil erosion was estimated to exceed soil formation on about a third of US cropland primarily in the midwestern agricultural heartland (BROWN, 1987). In TABLE IIb AGRICULTURALDEVELOPMENTFROM 1964 TO 1984 (AFTERBRUNDTLAND, 1987)
Region
World North America Western Europe Eastern Europe and former Soviet Union Africa Near East a Far East b Latin America CPEs of Asia c
Per capita gross cropped area (ha)
Per hectare fertilizer use (kg)
1964
1984
1964
1984
0.44 1.05 0.31 0.84
0.31 0.90 0.25 0.71
29.3 47.3 124.4 30.4
85.3 93.2 224.3 122.1
0.74 0.53 0.30 0.49 0.17
0.35 0.35 0.20 0.45 0.10
1.8 6.9 6.4 11.6 15.8
9.7 53.6 45.8 32.4 170.3
Source: Based on FAO data and modified from BRUNDTLAND, G. H. (1987) Our Common Future, by permission of Oxford University Press. BAn FAO grouping that includes West Asia plus Egypt, Libya and Sudan. bAn FAO grouping that covers South and South-East Asia excluding the centrally planned economies of Asia. CAn FAO grouping of centrally planned economies of Asia that covers China, Kampuchea, North Korea, Mongolia and Vietnam.
439
Human effects on climate through the large-scale impacts of land-use change Canada, soil degradation has been estimated as costing farmers $1 billion a year (OTTAWA, 1984). In the former Soviet Union, massive extension of cultivation was a major plank of agricultural policy, but now it is believed that much of this land is marginal (BROWN, 1987). In India, soil erosion affects 25-30% of the total land under cultivation (BRUNDTLAND, 1987). Without conservation measures, the total area of rainfed cropland in developing countries in Asia, Africa and Latin America seems likely to shrink by 544 million hectares over the long term because of soil erosion and degradation, according to a Food and Agriculture Organization (FAO) study (FAO, 1984 cf. Table II). Large-scale engineering works, such as reservoir construction, coastal reclamation and urbanization, can impact land-use and consequently land-cover. From 1950 to 1984, the construction of dams had flooded 10.9 million ha in the 41 largest artificial lakes of greater than 1000 km 2 (one-tenth of a million hectares) area (FEES and KELLER, 1973). Although coastal engineering can alter land-use, the continental area modified is about 3 orders of magnitude less than the areas affected by clearance for agriculture (DOUGLAS, 1990). The rate of global urbanization is very difficult to estimate but seems likely to be at least 2 million ha per year (SAGAN et al., 1979; HENDERSON-SELLERSand GORNITZ, 1984). Soil erosion and land degradation
Soil erosion, a natural process indicating land surface instability, is often greatly accelerated by human disturbances of the natural vegetation (through deforestation and cultivation). Surprisingly, evidence from regions with long-term agriculture (between 8 and 10 centuries) is equivocal whether accelerated erosion is correlated with human-induced land-use changes or with changes of climate. In the Near East, there is persuasive historical and archaeological evidence that expansion of agriculture into desert margins was more closely correlated to the establishment of stable governments than to climatic ameliorations. In addition, accelerated erosion is more closely tied to dry periods resulting in vegetation change than to intensification of agriculture. However, in the United States and Australia large-scale removal of vegetation has resulted in accelerated erosion and severe soil degradation (salinization of lowlands, some waterlogging, etc.) (e.g. HENDERSON-SELLERS and PITMAN, 1991; GRAETZ et al., 1992). The International Soil Reference Information Centre in Wageningen in the Netherlands has recently categorized land and soil degradation into four classes and described the extent of these classes of degradation globally (ISRIC, 1988, 1990; WORLD RESOURCES, 1992-1993, 1992, p. 113). The major causes of soil degradation (deforestation, agriculture, overgrazing and overexploitation of vegetation), and where they occur, are shown in Fig. 2. Most of the world's degraded land (910 million hectares) is moderately degraded resulting in poor water retention and lack of deep root penetration. Worldwide, ISRIC (1988) estimates that 300 million hectares have become severely degraded in the past 45 years. In tropical areas with poor soils, severe nutrient depletion occurs where all biomass has been cleared and crops grow poorly or not at all. About 9 million hectares of extremely degraded soils can be found where deforestation, overgrazing or other causes of degradation have occurred on soils with inherently poor parent materials. Here, no crop growth occurs and restoration is impossible. Only the remaining 750 million hectares are lightly degraded, with shallow, widely spaced rills or hollows and retention of native perennials.
440
Human-induced land-use change Desertification
The areal extent of irreversible desertification is highly uncertain and the indicators are still debated (MABBUTT, 1986). The United Nations Conference on Desertification (UNCOD, 1977) reports a global desertification rate close to 5.4 million ha year -1, representing a loss of 125,000 ha year -1 of irrigated land to salinization and/or waterlogging, and deterioration of 1.7 million ha year -1 of rainfed cropland, and 3.6 million ha year -1 of rangeland. DREGNE (1977) estimates that 1,380 million ha (28.4% of all arid land area) are severely affected by degradation of vegetation, sand drifting, salinization and spreading of undesirable forbs and shrubs (Fig. 3). However, desertification may be reversible under favourable ecological conditions (LE HOUI~ROU, 1977): when local weather conditions ameliorate (HENDERSONSELLERS and GORNITZ, 1984); when anthropogenic pressures are reduced (OTTERMAN, 1977, 1981); or may be compensated for by increased use of fertilizer (Table IIb). In 1984, the world's drylands supported some 850 million people, of whom 230 million lived on lands judged to be affected by severe desertification (UNEP, 1984). About 80% of the people moderately affected and 85% of the people severely affected by desertification live in Africa's arid and semi-arid lands (UNEP, 1984; BRUNDTLAND, 1987). The process of desertification affects almost every region of the globe (Fig. 3), but it is most destructive in the drylands of South America, Asia and Africa; for these three areas combined, 18.5% (870 million hectares) of formerly productive lands are now believed to be severely desertifled. Of the drylands in developing countries, Africa's Sudano-Sahelian zones and, to a lesser extent, some countries south of this zone suffer the most. In addition, about 1.5 million ha of irrigated land are lost every year to desertification (UNEP, 1991, 1992). Since the United Nations Conference on Desertification in 1977, there have been many national studies of land degradation processes and many "calls for action" (see also UNITED NATIONS, 1978). The region most studied over the subsequent decade was the Sahel, although even in this drought-stricken period, assessment of the rate (or even the fact) of encroachment was debated as was the definition of the term "desertification" (VERSTRAETE and SCHWARTZ,1991). The Sahelian drought, which began in 1972-1973, produced many adverse environmental consequences, and fears of the southward extension of the Sahara Desert, first expressed in 1921 (BOVILL, 1921) were repeated. The extreme northern parts of Nigeria were greatly affected with the deaths of over 1.3 million domestic animals, massive declines in crop yields and large migrations of rural people into urban centres (FRANKEand CHASIN, 1980; WATTS, 1983). Despite these acknowledged changes, there are considerable discrepancies between e.g. LAMPREY'S (1988) claim of a southward expansion rate of the Sahara of--5.5 km year -1, HELLDEN'S (1984) assertion that there was no evidence of expansion, and TUCKER et al.'s (1991) study of satellite data which showed that between 1980 and 1990 the desert area was largest in 1984 and smallest in 1988 (Table III). At present, it appears that the accuracy with which the human-induced process of desertification can be measured is open to debate. Deforestation
Agricultural expansion, urbanization and industrialization, a growing world timber trade and wood fuel demand have all combined to decrease the total area of forests and decrease bio-
441
Human effects on climate through the large-scale impacts of land-use change (a) Irrigated areas of drylands ( in million ha) Af d ca ( 10.4 ) . . . . . . . . . . . . . . . .
: .......
' " "~'~'~'~'~
. ' . ' . ' . ' . ' . ' . .::.'.'.'.'.'.'." .i[. [. [. [. ~X-x~x~. ~
Asia (92.0)
Australia (1.9) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Europe (11.9) N.
a m e~ i c a (
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S. America (8.4) .-.-.-.-.-.-.- -:.-.-.-.-..-.-.-:.-i-i'~-~-~-~ i:~-i-~,,",x",x",,~" ~ ] 0
25
50
75
100
Percentage desedified (b) R a n g e l a n ' d s within d r y l a n d s ( in million ha) Africa (1342.3)
.....
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.......
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25 50 75 Percentage desert~f~ed
100
(c) R a i n f e d c r o p l a n d s w~thJn drylands ( in million ha) Africa (79.8)
.
.
.
.
.
.
.
.
.
.
.
.
.
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Asia (218.2) Australia (42.1)
9 " : " : : "
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9
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S. America (21.3)
-
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25 50 75 P e r c e n t a g e desertafled
i': -'-] none to sl,0tlt !
.-.
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__1 severe
100
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moderate
~
very ~ovo~o
(d) P e r c e n t a g e of drylands affected by desedJf~cat~on 100 ~-.,~~ ra,nled cropland
irrigaled land 80
[T.-~
rangeland
.........................................................................................
60
_-! . ..............
-
~_ 4O
ol II
Africa
ii,iii i Asia
Australia
Euro ~e
N America
S. America
Fig. 3. Desertification (after UNEP, ].992): (a) in irrigated areas of drylands; (b) in rainfed croplands within do, lands; (c) in [angelands within drylands; (d) percentage of do, land affected.
442
Human-induced land-use change TABLE III AREA OF THE SAHARA DESERTAND THE SAHARAN-SAHELIANTRANSITIONZONEFROM 1980 TO 1990 WITHTHE ESTIMATED100 MM YEAR-1 PRECIPITATIONISOLINEAS THE SOUTHERNBOUNDARY Year
Saharan
Change relative
Mean latitude
area (km 2)
to 1980 (km 2)
and range of the 200 mm year-1 isoline (deg)
8,633,000 8,942,000 9,260,000 9,422,000 9,982,000 9,258,000 9,093,000 9,411,000 8,882,000 9,134,000 9,269,000
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
0 308,000 627,000 789,000 1,349,000 625,000 460,000 778,000 248,000 501,000 635,000
16.3 15.8 15.1 15.0 14.1 15.1 15.4 14.9 15.8 15.4 15.1
(0.9) (1.1) (0.9) (0.9) (1.0) (0.9) (0.8) (0.9) (0.8) (1.3) (1.1)
14.3 to 14.1 to 12.9 to 13.3 to 12.1 to 13.3 to 14.0 to 13.3 to 14.2 to 12.8 to 12.8 to
17.9 17.6 16.7 16.7 17.0 17.3 17.1 16.8 17.3 17.6 17.4
In the central Sahara, the Adrar des Iforas, Air, and Tibesti mountain areas were included as were the desert areas for the Easter Desert of Egypt and the Nubian Desert of Sudan. The northern boundary of the Sahara was the line running from Wadi Draa (29~ 10.5~ on the Atlantic coast along the Saharan Fault to Figuig (32~ 2~ Morocco, from there to Biskra (35~ 6~ Algeria, and from there southward through Tunisia to the Gulf of Gabes (34~ 10~ Areas of cultivation on the Mediterranean coast were excluded as was the Nile delta and river valley. The mean latitude position error is estimated to be +_15km. The error associated with the total Saharan area is estimated to be +_90,000 km 2 and is the product of the north-south error (__.15km or __.0.14~ of latitude) and the length of the southern boundary (6,000 km). The standard deviation appears in parentheses. (Reprinted with permission from TUCKER, C. G., DRAGNE, H. E. and NEWCOMB, W. W., Expansion and contraction of the Sahara desert in 1980 and 1990, Science, 253: 299-301, 9 1991, American Association for the Advancement of Science. 120 -m [3 II r-!
1 0 0 --
pre 1650 I 1650-1749 1750-1849 1850-1978 ~ _ _ -
.
.
.
.
.
n
80--
60--
40--
I
20--
0
I
I
Fig. 4. Estimated areas of forests cleared from pre-1650 to 1978 in million ha (modified from WILLIAMS, 1990).
443
Human effects on climate through the large-scale impacts of land-use change diversity (SKOLE and TUCKER, 1993). Figure 4 illustrates WILLIAMS' (1990) estimates of the total areas deforested globally from pre-1650 to 1978 although these estimates are highly uncertain. Although deforestation in temperate forests in North America and Europe has slowed, if not halted altogether, so that changes in their areal extent can be assumed to be negligible (ARMENTANO and RALSTON, 1980; EUROPEAN TIMBER TRENDS and PROSPECTS, 19502000), tropical deforestation continues. Tropical forests, which still cover almost 800 million ha, are being cleared in a number of different ways: for shifting cultivation; conversion to new, permanent agriculture; clearing for cattle grazing; logging and because of increased demand for fuel-wood (WRI, 1986). Combined, these effects were estimated in the mid-1980s as resulting in tropical deforestation of between 9 and 15 million ha year -1 (SELLERand CRUTZEN, 1980; LANLY, 1982) and 24.5 million ha year -1 (MYERS, 1980a,b). Recently, there have been some attempts to clarify and update these rates of tropical deforestation. In particular, the United Nations' Food and Agriculture Organization conducted a "Forest Resources Assessment Project" in 1990 (Table IVa) which was the basis for the IPCC re-evaluation of CO2 fluxes from tropical forests (HOUGHTON et al., 1992 and section on Land-cover changes and global climate). MYERS (1991) notes that the area deforested in
TABLE IVa PRELIMINARY ESTIMATES OF TROPICALFOREST AREAS AND RATE OF DEFORESTATIONFOR 87 TROPICALCOUNTRIES, 1981-90 (MILLIONHA) (REPRINTEDBY PERMISSIONOF KLUWER ACADEMIC PUBLISHERS)
Regions/subregions
No. of countries studied
Total land area
Forest area 1980
Forest area 1990
Area deforested annually 1981-90
Latin America Central America and Mexico Caribbean Subregion Tropical South America Asia South Asia Continental Southeast Asia Insular Southeast Asia
Africa West Sahelian Africa East Sahelian Africa West Africa Central Africa Tropical Southern Africa Insular Africa Total
1,675.7 245.3 69.5 1,360.8 896.6 445.6 192.9 258.1
923.0 77.0 48.8 797.1 310.8 70.6 83.2 157.1
839.9 63.5 47.1 729.3 274.9 66.2 69.7 138.9
8.3 1.4 0.2 6.8 3.6 0.4 1.3 1.8
-0.9 -1.8 -0.4 -0.8 -1.2 -0.6 -1.6 -1.2
40 (7) 8 (8) 6 (9) 8 (10) 7 (11) 10 (12) 1
2,243.4 5,228.0 489.6 203.2 406.4 557.9 58.2
650.3 41.9 92.3 55.2 230.1 217.7 13.2
600.1 38.0 85.3 43.4 215.4 206.3 11.7
5.0 0.4 0.7 1.2 1.5 1.1 0.2
-0.8 -0.9 -0.8 -2.1 -0.6 -0.5 -1.2
87
4,815.7
1,884.1 1,714.8
16.9
-0.9
(1) (2) (3) (4) (5) (6)
32 7 18 7 15 6 5 4
Annual rate of change 1981-90 (%)
Source: Forest Resources Assessment 1990 Project, FOODand AGRICULTUREORGANIZATIONof the United Nations, "Second Interim Report on the State of Tropical Forests", paper presented at the 10th World Forestry Congress, Paris, September 1991 (rev. October 15, 1991), Table 1 from WORLDRESOURCES 1992-1993 (1992).
444
Human-induced land-use change TABLE IVb TROPICAL FOREST EXTENT AND DEFORESTATIONRATES AS IN 1991 (MODIFIEDFROM Myers, 1991) (REPRINTED BY PERMISSIONOF KLUWER ACADEMIC PUBLISHERS)
Country (with region from Table IV(a))
Original extent of forest cover (million ha)
Present extent of forest cover (million ha)
Current amount of annual deforestation Million ha p.a.
Bolivia (3) Brazil (3) Cameroon (10) C. America (1) Colombia (3) Congo (10) Ecuador (3) Gabon (10) Guyanas (French Guiana, Guyana and Suriname) (2) India (4) Indonesia (6) Ivory Coast (9) Kampuchea (5) Laos (5) Madagascar (12) Malaysia (6) Mexico (1) Myanma (Burma) (5) Nigeria (9) Papua New Guinea (?6) Peru (3) Philippines (6) Thailand (5) Venezuela (3) Vietnam (5) Zaire (10)
%
9.00 286.00 22.00 50.00 70.00 10.00 13.20 24.00
7.00 220.00 16.40 9.00 27.85 9.00 7.60 20.00
0.15 5.00 0.20 0.33 0.65 0.07 0.30 0.06
-2.1 -2.3 -1.2 -3.7 -2.3 -0.8 -4.0 -0.3
50.00 160.00 122.00 16.00 12.00 11.00 6.20 30.50 40.00 50.00 7.20 42.50 70.00 25.00 43.50 42.00 26.00 124.50 1,362.60 a
41.00 16.50 86.00 1.60 6.70 6.80 2.40 15.70 16.60 24.50 2.80 36.00 51.50 5.00 7.40 35.00 6.00 100.00 778.35 b
0.05 0.40 1.20 0.25 0.05 0.10 0.20 0.48 0.70 0.80 0.40 0.35 0.35 0.27 0.60 0.15 0.35 0.40 1.386
-0.12 -2.4 - 1.4 -15.6 -0.75 -1.5 -8.3 -3.1 -4.2 -3.3 -14.3 -1.0 -0.7 -5.4 -8.4 -0.4 -5.8 -0.4 - 1.8
a97% of estimated total original extent of tropical forests, around 1,400 million ha. b97.5% of present total extent of tropical forests, viz. 800 million ha. 1989 amounted to 14.2 million hectares is nearly 90% more than the 7.5 million ha deforested in 1979. The rates of tropical deforestation listed in the two parts of Table IV are in reasonable agreement; especially when it is recognized that MYERS (1991) samples only 26 countries whilst FAO (1991) includes 87. The 1990s' global, annual removal rate of tropical forest falls towards the centre of the 1980s' estimates with the rate for the decade 1981-1990 being given as 16.9 million ha year -1 by the FAO (1991) and as 13.9 million ha year -1 by MYERS (1991). The best estimates of the current rates of the two major land-use changes, desertification and tropical deforestation, are around 5 - 6 million ha year -1 and around 15-17 million ha year -1, respectively, with tropical deforestation being more widely believed to be a permanent dis-
445
Human effects on climate through the large-scale impacts of land-use change turbance. Other land-use changes are at least an order of magnitude less extensive than these activities although all estimates suffer from poor data and inadequate definition (e.g.
VERSTRAETE, 1986). Even if sound and agreed definitions of human-induced land-use change and unambiguous information about current and future rates of change were available, the consequences for the future climate would remain very difficult to determine for the reasons discussed in the next three sections.
Land-cover change influences on climate Land-cover changes and global climate
Greenhouse gases The atmospheric concentrations of three important greenhouse gases, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N20), are known to be affected by human-induced landcover changes. In this context, carbon dioxide is emitted into the atmosphere when carbon (in vegetation or soils) is oxidized either by burning or decay. Methane is primarily the result of anaerobic decay and also a product of biomass burning, the latter also being a source of nitrous oxide along with denitrification of anaerobic soils. In addition, growing vegetation is an important sink for CO2 so that altering land-use from, say, forestry to grazing land could constitute a CO2 sink removal (i.e. a decrease in the net uptake (sink) of CO2) even though removing tropical forests does not constitute the removal of a sink because these forests are in carbon equilibrium (i.e. on average they release approximately as much CO2 as they absorb). Thus deforestation specifically, and biomass burning generally, are sources of CO2; rice cultivation, biomass burning, and to a lesser extent cattle grazing, are sources of CH4; and other land-use changes can also modify both the sources and sinks of other atmospheric greenhouse gases including N20. The global CO2 budget is more fully understood than those of CH 4 and N20 but even for this budget the best estimates are not yet able to balance the sources and sinks. However, it is well established that CO2 in the atmosphere is increasing rapidly (Fig. 5a). It is also clear that since the middle of the 20th century the predominant source of CO2 has been the combustion of fossil fuel (Fig. 5b). However, the contribution of human-induced land-use changes to the atmospheric CO2 budget is not fully understood. WATSON et al. (1992) in the update to the IPCC Science Assessment (HOUGHTON et al., 1992) gave the global, annual fossil fuel emission total as 6.0 _+0.5 Pg C and chose not to revise the original IPCC (HOUGHTON et al., 1990) estimate of the contribution due to tropical deforestation of 1.6 _+ 1.0 Pg C. They state that (i) the small net addition of carbon to the atmosphere from the equatorial region, a combination of outgassing of CO2 from warm tropical waters and a terrestrial biospheric component, is the residual between large sources (deforestation) and sinks; (ii) the strong Northern Hemisphere sink contains both oceanic and terrestrial biospheric components and there is a weak Southern Hemisphere sink; (iii) an ocean sink of 2.0 _+0.8 Pg C per year is reasonable; and (iv) terrestrial biospheric processes are sequestering CO2 due to forest regeneration and carbon and nitrogen fertilization (WATSON et al., 1992).
446
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Fig. 5. Historical trends in concentrations of greenhouse gases known to be affected by humaninduced land-use changes: (a) CO 2 (ppmv) from ice cores (solid circles) and, recently, direct measurements (open circles) after HOUGHTONet al., 1990); (b) annual flux of carbon (Pg) to the atmosphere from land-use changes as compared to fossil fuel emissions (after HOUGHTON and SKOLE, 1990; reprinted with the permission of Cambridge University Press); (c) CH 4 (ppbv), from ice cores (data from PEARMAN and FRASER, 1988 and ETHERIDGEet al., 1988); (d) N20 (ppbv), from ice cores (dots), direct measurements (solid line) and model interpolated (dashed line) (PEARMAN et al., 1986, GRAEDEL and CkUTZEN, 1990; reprinted with the permission of Cambridge University Press); (e) Simulations of net flux of carbon (Pg) to the atmosphere based upon three projections of tropical deforestation (population-based, a linear model and an exponential model) and one projection of reforestation. The Myers estimate is his calculation of net flux between 1980 and 1990 (after HOUGHTON, 1991; reprinted with permission of Kluwer Academic Publishers).
447
Human effects on climate through the large-scale impacts of land-use change HOUGHTON (1991) evaluates the uncertainties associated with estimating the annual carbon release from tropical deforestation. He believes that the probable range is between 1.1 and 3.6 Pg C per year with his preferred values being 1.6-2.7 Pg C, slightly greater than the IPCC preferred estimate. The main, and roughly equal, causes of uncertainties are: the rates of deforestation, the fate of the deforested land and the carbon stock of the forests. The terrestrial sources, and sinks, of CO2 have changed over time: before 1900 the land-use change emissions of CO2 were larger than those due to fossil fuel combustion (Fig. 5b and HOUGHTON and SKOLE, 1990). The expansion of croplands at the expense of forests in Europe, Russia and North America was a major source of CO2 in the 19th century (cf. Table II and Fig. 1). Since about 1900, temperate deforestation has been slowed, and in some countries reversed, by forest plantation, while tropical deforestation began to accelerate in about 1945. The estimation of carbon fluxes from the continents is difficult because the sources and sinks due to land-cover change are roughly two orders of magnitude smaller than the global photosynthesis and respiration rates of 100-120 Pg C per year (HOUGHTON et al., 1985). Thus a 1-2% alteration in these natural processes could constitute a source as large as that due to tropical deforestation. Although there is, as yet, no direct evidence of such changes in photosynthesis/respiration, the potential for disturbances due to increased atmospheric CO2 and changed climatic conditions is great. In addition to these direct changes to the "natural" carbon budget of the continents, there is also the possibility that changing climatic conditions might modify the natural (and agriculturally based) vegetation and soils. This possibility is considered in the section on Future land-use change and future climate. Biomass burning contributes many greenhouse gases to the atmosphere, particularly CO2, CO, N20 and CH 4 (KELLER et al., 1990). ANDREAE et al. (1988) estimated that between 5 and 20% of the carbon in material burned in a tropical forest becomes CO which is, ultimately, oxidized to CO2. This oxidation depends upon the abundance of the OH radical and, by competing for it, causes an indirect extension of the atmospheric lifetimes of other greenhouse gases: CH 4 and the CFCs (HARVEY, 1991). The present-day atmospheric concentration of nitrous oxide is approximately 310 ppbv, about 8% greater than in the pre-industrial era (Fig. 5d). Atmospheric N20 seems to be increasing at about 0.2-0.3% per year (WMO, 1992) representing an annual atmospheric growth rate of between 3 and 4.5 Tg N. Human-induced land-use change contributes only to the sources of N20 (Table Va), particularly through denitrification of soils and biomass burning. WATSON et al. (1992) deduce the globally, annually averaged source strength of N20 to be between 10 and 17.5 Tg N from the known atmospheric accumulation rate and the best available estimates of the strengths of the identified sinks. It is not even known whether tropical deforestation increases the source of atmospheric N20 (WATSON et al., 1992) or decreases it (SANHUEZAet al., 1990; KELLER,1992). SCHLESINGER et al. (1990) argue that an important consequence of desertification is a considerable, and probably rapid, loss of soil nitrogen. They studied the processes which remove nitrogen from soil during a transition from grassland to desert shrubland, including volatilization, denitrification and wind erosion, and concluded that the process of desertification includes an implicit positive biochemical feedback in which nitrogen loss from arid soils favours desert plants over grasses. Thus, if desertification increases (cf. section on Human-induced land-use change) the soil source of N20 may increase (cf. Table Va).
448
Land-cover change influences on climate TABLE Va ESTIMATED SOURCES AND SINKS OF NITROUS OXIDE (TG N PER YEAR, I.E. 0.001 P 6 N PER YEAR) (AFTER WATSON ET AL., 1992; REPRINTED WITH THE PERMISSION OF CAMBRIDGE UNIVERSITY PRESS)
Sources
Natural Oceans Tropical soils Wet forests Dry savannas Temperate soils Forests Grasslands
Amount
1.4-2.6 2.2-3.7 0.5-2.0 0.05-2.0 ?
Anthropogenic Cultivated soils Biomass burning Stationary combustion Mobile sources Adipic acid production Nitric acid production
0.03-3.0 0.2-1.0 0.1-0.3 0.2-0.6 0.4-0.6 0.1-0.3
Sinks Removal by soils Photolysis in the stratosphere Atmospheric increase
? 7-13 1--4.5
The concentration of methane in the atmosphere currently is about 1.72 ppmv, more than twice its pre-industrial level, and concentrations are increasing (Fig. 5c) although the rate of increase is less in the 1990s than in the late 1970s (12-13 ppbv per year; cf. the earlier rate of increase of 20 ppbv) (WATSON et al., 1992; WMO, 1992). The sources and sinks of atmospheric CH 4 are poorly understood. Methane emission from wetlands is its largest natural source (Table Vb). Emissions from rice paddies and enteric fermentation (in ruminants) combine to exceed all other anthropogenic sources of CH 4. Thus land-use changes which entail draining/reclaiming wetlands and marshes, developing rice cultivation areas or increasing numbers of grazing cattle will all affect the atmospheric content of CH 4. The area needed for cultivation of rice, a year-round crop with at least two and usually three harvests each year, under cultivation, was 147.5 million ha in 1984 (FAO, 1985), and is increasing. Thus the sources are large but strengths are poorly known; e.g. estimates range from 0.005 g CH 4 m -2 day -~ to 0.69 g CH 4 m -2 day -1 (MATTHEWSet al., 1991; WATSON et al., 1992). Another possible enhancement to the natural sources of atmospheric CH 4 has been noted by ZIMMERMAN et al. (1982). They consider the effects of increased populations of termites (one source of CH4) in newly desertified land. The soil sink for CH 4 (Table Vb) is believed to be being reduced by land-use changes and/or enhanced nitrogen fertilizer input (KELLER et al., 1990; SCHARFFE et al., 1990) and is likely to be sensitive to soil moisture changes implying further changes in the future (HOUGHTON et al., 1990; WATSON et al., 1992). Overall, it is exceedingly difficult to quantify, even for the present day, the contribution that human-induced land-use change is making to the increasing atmospheric concentration of a number of important greenhouse gases. Roughly, land-use change may contribute between
449
Human effects on climate through the large-scale impacts of land-use change TABLE Vb ESTIMATEDSOURCESANDSINKSOFMETHANE(TG CH4 PERYEAR,I.E. 0.001 PG PERYEAR)(AFTER WATSONETAL., 1992; REPRINTEDWITHTHEPERMISSIONOFCAMBRIDGEUNIVERSITYPRESS) Sources
Natural Wetlands Termitesa Ocean Freshwater CH 4 hydrate
Anthropogenic Coal mining, natural gas and petroleum industry a Rice paddies a Enteric fermentation Animal wastesa Domestic sewage treatmenta Landfills a Biomass burning Sinks Atmospheric tropospheric + stratospheric removala Removal by soils Atmospheric increase
Amount
Range
115 20 10 5 5
100-200 10-50 5-20 1-25 0-5
100
70-120
60 80 25 25 30 40
20-150 65-100 20-30 ? 20-70 20-80
470
420-520
30 32
15-45 28-37
alndicates revised estimates since HOUGHTONet al. (1990). 20 and 30% to the observed gaseous increases. The uncertainties identified here and the synergism between land-use, social evolution and climate make it, at present, virtually impossible to predict the future contribution of human-induced land-use change to greenhouse warming. At the least, however, other impacts of land-use change on climate will have to be judged against the background of greenhouse warming. Figure 6 shows regions where a crude measure of statistically significant change in selected climatic parameters is evident following a doubled CO2 simulation. This figure is included in this chapter in order to permit at least a first order comparison of the possible impacts of two types of land-cover change (tropical deforestation and desertification), which are considered in the section on Regional-scale impacts of land-cover change on climate, with the impacts of greenhouse-gas induced warming. The Student's t statistic is used throughout, although it is recognized that some difficulties hamper overzealous or detailed interpretation of these maps (e.g. PREISENDORFER and BARNETT, 1983). For a full description of the climatic effects of green-
house gas increases see Chapter 9 by WANG et al. Here it is important only to note the global extent of surface temperature increases even in the case of the annual mean (Fig. 6a), the large regions affected by surface pressure changes (Fig. 6d), the noisy but widespread response in evaporation (Fig. 6b) and the relatively weak significance associated with the increase in precipitation (Fig. 6c). Only the surface temperature field was statistically significant in the annual average; for other parts of Fig. 6, the month of July was selected for comparability with figures later in the chapter.
450
Land-cover change influences on climate
increase
~
decrease
Fig. 6. Statistically significant regions of climatic change following an instantaneous doubling of atmospheric CO2 as measured by a Student's t statistic at the 95% confidence level for (a) annually averaged surface temperature; (b) July evaporation; (c) July precipitation; (d) July mean sea-level pressure.
Atmospheric aerosols Particulates and droplets, termed atmospheric aerosols, result from sea spray, volcanic and industrial emissions (ISAKSEN et al., 1992) (dealt with in other chapters in this book e.g. Chapter 10 by ANDREAE and Chapter 4 by RAMPINO) and from land-use. Their impact is to cool (COAKLEYet al., 1983) in most locations, although they can cause a warming when they occur over high albedo surfaces such as snow and ice (BLANCHET, 1989). Sources of the short-lived sulphur gases, which comprise the bulk of these aerosols, include land-use (such as biomass burning, soil and plant disturbance e.g. ANDREAE, 1993 but cf. CACHIER and DUCRET, 1991) together with oceanic, industrial and volcanic emissions. The latter three sources are believed to be about an order of magnitude greater than the combined effects of land-use change (WATSONet al., 1992 and Chapter 10 by ANDREAE). PENNER et al. (1992) estimated the probable impacts of aerosols caused by land-use changes which include burning of forests and savannas for shifting agriculture and for colonization, use of fuel wood and combustion of agricultural wastes. Carbon (C) released by deforestation, savanna burning and shifting agriculture is estimated to be 1.3 to 3.3 Pg C (e.g. HAO et al., 1990). They estimate the carbon burned per year globally to be 2.6-5.0 Pg. For an intermediate value of 3.8 Pg C burned per year, PENNER et al. (1992) estimate that 0.114 Pg of smoke will be produced and this estimate agrees to within the range of uncertainty with the value of 0.09 Pg per year suggested in Chapter 10 by ANDREAE. These estimates are comparable with the global annual anthropogenic (industrial) sulphate production of 0.110 Pg, claimed, by CHARLSON et al. (1992), to be capable of cooling the Earth by -1 to - 2 W m -2
451
Human effects on climate through the large-scale impacts of land-use change although KIEHL and BRIEGLEB (1993) report a lower value o f - 0 . 3 W m -2. For the smoke aerosol loading proposed by PENNER et al. (1992), the increase in planetary albedo is 0.003, leading to a cooling o f - 1 . 0 W m -2. In addition, they examine the effect of these aerosols acting as cloud condensation nuclei (CCN) and hence changing the radiative properties of clouds. They relate the cloud albedo to the concentration of aerosols and assume a globally averaged relationship between CCN and smoke giving a cooling of the global climate by an additional-1 W m -2, i.e. an upper limit on the total effect due to biomass burning could be a possible cooling of the Earth by up to -2 W m -2. This impact is potentially comparable to the cooling by sulphate aerosols and of similar magnitude but opposite sign to increased emissions of greenhouse gases over the last century which now warm the planet by approximately +2 W m -2.
Surface albedo HENDERSON-SELLERS and GORNITZ (1984) tabulated the rate of human-induced land-cover change over the preceding 30 years. From these estimates they used a simple formulation devised by SAGAN et al. (1979) to permit evaluation of the potential impact on the global climate caused by the surface albedo changes estimated as following from the land-cover changes. The review in the section on Human-induced land-use change indicates the need to update their figures: in particular, the two largest disturbances to the global surface albedo, tropical deforestation and desertification, may require revision in opposite directions. Recent studies indicate that tropical deforestation is probably accelerating, the annual rate being closer to 15-17 million ha than the 11 million ha per year assumed by HENDERSON-SELLERS and GORNITZ (1984) (cf. Table IV). On the other hand, the substantial rates of desertification (~5-6 million ha year -j) claimed in the early 1980s are now being disputed (e.g. HELLDEN, 1991; TUCKER et al., 1991). The changes in temperate forests should probably become an increase in forest area caused by reforestation in northern mid-latitudes and the albedo change (at least in winter) is also negative since high latitude forests mask snow much more than tundra, crop fields or bare soil (e.g. HENDERSON-SELLERS and WILSON, 1983). In a recent global modelling study, BONAN et al. (1992) found winter surface albedo increases of more than 0.1 when they replaced boreal forests by bare soil. These albedo changes prompted cooling of the nearsurface air of 5~ (July) to 12~ (October) as a result of the snow-albedo feedback. For forest replacing deforested land, decreased albedos and zonal warming might be anticipated. Overall, the final totals in HENDERSON-SELLERS and GORNITZ (1984) should, probably, be increased because of tropical deforestation; decreased because of uncertainty surrounding claims of enhanced desertification; and decreased because of temperate reforestation; the global impact on their proposed numbers is likely to be small. However, the simplicity of the relationship they employed between surface albedo change and global temperature renders their results, at best, incomplete in the light of more recent modelling studies, as reviewed in the section on Regional-scale impacts of land-cover change on climate. Local land-cover factors implicated in climatic disturbance Land-cover change generally involves modification of the surface albedo (as discussed ear-
452
Land-cover change influences on climate
lier) and can also involve an alteration in the roughness of the vegetation/soil surface. In particular, the removal of trees decreases the roughness quite significantly. These two factors are probably the most important controls on the response of the local to regional climate (e.g. HENDERSON-SELLERS,1993). In addition, there is likely to be an alteration in the canopy area and perhaps in the resistance of the vegetation to transpiration. Finally, land-use change may also alter the soil state and characteristics, perhaps affecting drainage through, or evaporation from, the soil and hence feeding back on to climate (e.g. CHAHINE, 1992). Although all these factors may be important for local conditions and local climatic response, it is generally believed that albedo and roughness (often called roughness length) changes predominate. Two types of land-use change, deforestation and desertification, have been simulated in a number of global climate models (GCMs). When deforestation is simulated, both albedo and roughness length changes occur whilst for desertification usually only the surface albedo is modified because any roughness length change is assumed to be small although the ratio of old to new roughness lengths is roughly commensurate in the two cases. Albedo
The albedo increases typically imposed in land-use change experiments simulating either tropical deforestation or desertification might range from 0.01 to 0.10. Potential effects are summarized in Fig. 7a. At levels of annual incoming solar radiation of 300 W m -2 typical in the tropics, the absorbed solar radiation could be reduced by up to 30 W m -2 (process A1) (e.g. SHUTTLEWORTHet al., 1984; MYLNE and ROWNTREE, 1992). If net surface longwave radiation remains unchanged, there is less energy available for latent or sensible heat flux from the surface and for transfer into the ground and the primary effect is for temperatures to be decreased (process A2). Secondary effects that may arise include a decrease in evaporation (process A3), arising directly from the reduction in available energy and a decrease in precipitation resulting from this (process A4). The decrease in net radiative heating of the total (atmosphere plus surface) column leads (CHARNEY, 1975) to a reduction in ascent (process A5), moisture convergence and rainfall (process A6). These are likely to prompt changes in the moisture budget and hence soil moisture content (process A7). If the decrease in precipitation exceeds that in evaporation, drying out of the soil occurs, thus promoting a further decrease in evaporation (process A8) which might lead to an increase in sensible heat flux and surface temperature despite the increase in albedo (i.e. even though the initial impact was to decrease absorbed energy, the surface might warm). On the other hand, the combined impact of processes A3 and A8 may be sufficient to cause a larger decrease in evaporation than in precipitation. This, in turn would result in a negative feedback (process A9) tending to increase soil moisture content. The reduction in precipitation will tend to further increase albedo as vegetation and soils dry (process A10): a positive feedback effect. The overall result of increasing albedo will depend crucially on the relative strengths of these processes, the strengths of the identified feedbacks, the time periods over which each operates and other impacts, such as a reduction in cloudiness which could follow processes A5 and A6. Less cloud is likely to cause increased insolation and thus increase the net radiation so acting as a negative feedback on the imposed albedo
453
Human effects on climate through the large-scale impacts of land-use change increase itself. In particular, it is not clear whether surface temperatures will increase or decrease.
Roughness length The roughness decrease imposed in deforestation experiments is usually an alteration from a forest roughness length of around 2 m to one more appropriate to a grassland of, say, 0.05 m. For desertification, the decrease would be somewhat less. Imposing a decrease in
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Fig. 7. Schematic representation of some of the climatic responses to prescribed land-surface changes: (a) following an albedo increase; (b) following a roughness length decrease. The numbered processes are described in the text. In desertification experiments, those processes in part (a) might be anticipated. In the case of deforestation, processes in both (a) and (b) might occur. (Part (a) was modified from MYLNE and RowWrREE, 1992; reprinted by permission of Kluwer Academic Publishers).
454
Land-cover change influences on climate roughness (Fig. 7b) acts to reduce the turbulent fluxes of sensible and latent heat and of momentum between the continental surface and the atmosphere (process R 1). This reduction in the fluxes tends to cause an increase in the surface temperature (process R2). The temperature increase prompts a negative feedback (R3) since it will tend to cause an increase in sensible flux and also in latent heat. The effect of an increase in surface temperature (process R2) and thus increased longwave radiation from the surface is decreased net radiation (process R4) prompting decreased ascent (process R5). In addition to the reduction in evaporation due to the reduced roughness length (process R1), there is an additional reduction due to the reduction in the transpiration from the (prescribed) reduction in biomass. This combined reduction in evaporative flux acts to reduce precipitation (process R6) as will the reduction in ascent (or increased descent) (process R7). The decrease in surface roughness decreases the turbulent momentum flux which decreases the surface drag and increases the wind strength in the planetary boundary layer (process R8). Decreased drag results in decreased cross-isobaric flow and hence decreased moisture convergence (process R9). This will contribute further to the reduction in ascent and hence the decrease in precipitation (reinforcing process R7). The decrease in precipitation will tend to cause a decrease in soil moisture (process R10) although this will be balanced by the tendency to increase soil moisture amounts caused by the decrease in evaporation (process R11). Not only is the outcome of these two effects uncertain but there is also the potential for a positive feedback on evaporation caused by a decrease in soil moisture (this would follow the arrow of process R11 but in the other direction). As in the case of the prescribed albedo increase, there are ambiguities over the direction of change in some climatic parameters as a result of feedbacks and differing magnitudes of changes. In addition, it is not clear how to relate these local impacts to regional changes such as convergence which is also controlled by larger-scale circulation characteristics (cf. SUD et al., 1988; ROWNTREE, 1991). In tropical deforestation, of course, both major disturbances in Fig. 7 occur: albedo is increased and roughness length decreases. As can be surmised from Fig. 7, it is very difficult to anticipate either the resulting direction or the magnitude of changes in many climatic parameters. The imposition of an albedo increase might cool the surface and thus prompt descent in the atmospheric column. The imposition of a reduced roughness length is likely to reduce evaporation, and hence warm the surface, but also to prompt descent or at least decreased ascent in the air column. Global climate model experiments designed to assess the effects of land-use and landcover change might then be expected to reveal local surface climatic changes and, perhaps, more widespread dynamical responses including disturbances in the regionalscale moisture convergence (e.g. SUD et al., 1988; NOBRE et al., 1991). The possibility of regional-scale atmospheric responses to land-cover change has been noted by, for example, HENDERSON-SELLERS and GORNITZ (1984) and SHUKLA et al. (1990) with reference to tropical deforestation and by CHARNEY et al. (1977) and LAVAL and PICON (1986) with reference to desertification. Major atmospheric features worthy of detailed investigation are the Hadley and Walker circulations and the tropical jets. These are included in the assessment of the climate model sensitivity studies in the next section of this chapter.
455
Human effects on climate through the large-scale impacts of land-use change Regional-scale impacts of land-cover change on climate Model studies of desertification OTTERMAN (1974) and CHARNEY (1975)drew attention to the importance of an increase in surface albedo in semi-arid regions; the latter proposing a regional-scale feedback mechanism to explain, in part, the droughts that occur in desert border regions when the vegetation cover decreases, because of overgrazing or wood cutting, and the surface albedo increases. The cooling of the atmosphere will induce sinking motion (or less ascent) and this leads to a decrease of precipitation (Fig. 7a). If precipitation is lower, vegetation will decrease again: a hypothesized positive feedback mechanism. Although generally introduced in terms of increased albedo, it is important to recognize that the CHARNEY et al. (1977) experiments also included changes in evaporation. When appreciable evaporation was allowed to occur, increasing the surface albedo prompted a decrease in precipitation in all the locations tested but when evaporation was negligible, it was only in the Sahel that increasing albedo caused a decrease in precipitation. The Charney desertification hypothesis has been tested with a number of global climate models (CHARNEYet al., 1977; WALKER and ROWNTREE, 1977; CHERVIN, 1979; SOD and FENNESSY, 1982; LAVAL, 1986). At the same time, however, some researchers have challenged the mechanism by which this bio-climatic feedback might work (e.g. LE HOUEROU, 1992) and it has been shown that the Charney mechanism does not operate in all atmospheric regimes (HART, 1990). Table VI compares the responses obtained for the Sahel in the month of July from five different GCM experiments. Desertification in all but the most recent simulation was simulated TABLE VI EFFECTS OF NUMERICAL MODEL SIMULATIONSOF DESERTIFICATIONOF THE SAHEL REGION (REPRINTED BY PERMISSION OF KLUWER ACADEMIC PUBLISHERS)
Differences are generated by subtracting low albedo (0.14) from "desertified" high albedo (0.35) (modified from LAVAL, 1986). Charney Charney Sud and et al. et al.a Fennessy b (high evap.) (low evap.) Precipitation (mm day-1) Evaporation (mm day-1) Convective clouds (%) Total cloudiness (%) Solar flux (W m-2 ) Net radiational heating (W m-2) Surface air temperature (~ Temperature in the lowest model layer (~
-3.4 -0.9 -15.0 -23.7 8 82 -0.3
-1.3 0.20 -0.2 -5.3 -47 -47 5.9
-1.46 -0.71 -4 -10 -18 -
Laval and Picon
-0.8 -0.5 -45 -47 -
HendersonSellers c
-0.7 -0.40 -4.1 2 -8 1.2
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aCHARNEYet al. (1977) conducted two experiments with high and low prescriptions of evaporation in the desertified region. bSUDand FENNESSYused a smaller albedo of 0.30 rather than 0.35. CHENDERSON-SELLERS'experiment was not a simple albedo change: the ecotype was altered to desert and the soil colour made lighter by two classes.
456
Regional-scale impacts of land-cover change on climate by changing a low (0.14) surface albedo to a higher (0.35) value. The numerical experiments all generate precipitation and cloudiness decreases and all but the CHARNEY et al. (1977) high evaporation simulation also exhibit net radiative heating decreases. LAVAL (1986) examined the reasons for this difference noting that high evaporation prompts a larger precipitation decrease, by about a factor of 3, than for the low evaporation case. The specified increase in albedo causes an increase of upward solar flux but reduced cloud cover increases the downward solar flux. In the case of the CHARNEY et al. (1977) high evaporation experiment, the cloud effect seems to predominate over the effect of the surface albedo change. In the low evaporation case, there are very few clouds so their variation does not greatly affect the solar flux. The result is a decrease in absorbed solar radiation and in radiative heating also. Several authors have noted that during the 1970s' drought in the Sahel, changes occurred in the regional circulation of the atmosphere. KANAMITSUand KRISHNAMURTI(1978), comparing the circulation at 200 hPa for 1967 and 1972, reported a decrease in the strength of the tropical easterly jet during 1972, while KIDSON (1977), NEWELL and KIDSON (1979, 1984) and DZIETARA and JANICOT (1980) also find that the tropical easterly jet is weaker but the African easterly jet is stronger during a Sahel drought. It is less clear, however, how these regional changes might interact with the tropical circulation. KIDSON (1977), referring to the angular momentum budget of the atmosphere, suggests that if the tropical easterly jet is weaker, the meridional circulation must be weaker, further noting that rainfall and vertical velocity are correlated. NEWELL and KIDSON (1979) conclude that dryness must be associated with a weaker vertical velocity and weaker Hadley cell. On the other hand, KANAMITSU and KRISHNAMURTI (1978), analyzing velocity potential at 200 hPa, concluded that, during drought years, convergence is enhanced in humid regions and this must be the result of a stronger Hadley circulation. General circulation models manifest stronger subsidence (or weaker ascent) when the albedo is increased in a desertification experiment (LAVAL, 1986 and cf. Fig. 7 et seq.). Assessing the sensitivity of the Sahel climate, LAVAL and PICON (1986) consider changes to the atmospheric flow over Africa: at 200 hPa they obtain a decrease of easterly jet over Africa and the Atlantic Ocean while the 700 hPa easterlies strengthen. Their differences in the zonal wind at 200 hPa correspond quite well with the observed changes reported by NEWELL and KIDSON (1984). More complete desertification experiments give rise to generally similar results. In one such experiment, conducted with a version of the NCAR Community Climate Model (CCM1-Oz; HENDERSON-SELLERS et al., 1993) and incorporating a mixed layer ocean and the Biosphere-Atmosphere Transfer Scheme (BATS), 8 semi-desert and 13 tall grass locations in Africa (inset in Fig. 8) became desert. This "desertification" involves increasing surface albedo; decreasing the leaf area and fractional vegetation cover; making the soil more like a coarse sand (lighter in colour and coarser in texture- the latter change imposed because of increased trampling) at all desert locations. The July responses in the desertified Sahel region (18.25~ to 48.25~ and 22.25~ to 10.00~ are listed in Table VI: precipitation, evaporation, total cloud and net radiation all decrease but surface air temperature increases marginally. Figure 8 shows the areas of the globe that exhibit statistically significant responses to the Sahel desertification in the month of July. The impacts are much less extensive, and less
457
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Fig. 8. July global maps of statistically significant climatic responses to Sahel desertification across region shown in inset. Statistics as in Fig. 6 for: (a) surface temperature; (b) mean sea-level pressure; (c) precipitation; (d) evaporation. significant, than doubling the greenhouse gas absorbers in the atmosphere of the same GCM (Fig. 6b,c,d). There are no statistically significant responses for the annually averaged fields although there is a significant increase in mean sea-level pressure which extends across southern Asia and might therefore modify the Asian, African and perhaps even the Australian monsoons. Figure 9 shows the responses over Africa in ground surface temperature, evaporation, precipitation and the zonal wind at 200 hPa for the month of July (chosen to be comparable with the earlier studies reported above). It can be seen that surface temperature and evaporation both decrease although neither signal is statistically significant over an extensive area (insets in Fig. 9a,b). Precipitation also decreases a little (Fig. 9c) but this response is not significant against the normal variability in the modelled climate. The easterly tropical jet (as represented by the zonal wind at 200 hPa) is also decreased by the imposed desertification but the magnitude of the decrease (Fig. 9d) is less than 1.5 m s-1 as compared to the 510 m s-1 decrease found by LAVAL (1986). There is also a statistically significant decrease in surface temperatures in most other months and an increase in surface pressure throughout the year in the desertified region (cf. Fig. 9b). This response, in line with the Charney hypothesis of decreased surface and column energy causing decreased ascent, is not manifested as statistically significant changes in vertical velocities over the region. In summary, GCM experiments have been conducted to try to assess the probable climatic impact of desertification by imposing an albedo increase (typically of about 20% absolute) (e.g. SUD and FENNESSY, 1982; LAVAL, 1986) and sometimes also a range of evaporative
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regimes (e.g. CHARNEY et al., 1977). Locally, precipitation and evaporation decrease, the former hypothesized as prompting further degeneration in the vegetation: a process which is not yet represented in climate models. So far, there is little or no evidence that Sahel desertification has any impact external to the desertified region itself except perhaps disturbances to the easterly jet.
Model studies of tropical deforestation Tropical forests comprise over 7% of the continental surface, constitute an important natural resource and are rapidly being depleted (see section on Human-induced land-use change; GORNITZ, 1985; HENDERSON-SELLERS, 1987; RAMAKRISHNAN, 1992). There have been at least ten recent attempts to predict the likely climatic impact of tropical deforestation over the last decade (Table VII). While most of these experiments have been concentrated on the Amazon forest (e.g. HENDERSON-SELLERS and GORNITZ, 1984; LEAN and WARRILOW, 1989; SHUKLAet al., 1990), there have also been attempts to assess impacts in other tropical regions (MYLNE and ROWNTREE, 1992; HENDERSON-SELLERSet al., 1993). Locally to the deforestation, experiments suggest that the albedo increase (tending to cool) and roughness length decrease (tending to warm) roughly compensate giving a resultant change in surface temperature that is dependent upon the relative magnitudes of the imposed
459
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TABLE VII COMPARISON OF
Ref. a
GCM Surface Ocean
Time b con. exp. A7 c AP AE A E - AP d
GCM
SIMULATIONS OF TROPICAL DEFORESTATION
M &R
D&K
L&R
P&L
P &L
(1989)
Shukla et al. (1990)
(1992)
(1992)
(1992)
(1994a)
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UKMO 2.5• Canopy
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UKMO 2.5• Bucket
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UKMO 2.5• Canopy
Fixed SST
Fixed SST
Dec. e SST
Fixed SST
mlo f poor q-flux
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3 1 +3 0 -200 -200
3 3 +2.4 -490 -310 180
1 1 +2 -640 -500 140
3 0.75 -0.11 -335 -176 159
10 3 +0.6 -511 -255 256
H-S & G (1984)
D& H-S (1988)
L&W
GISS 8• 10 2-layer Hydro. Fixed trans.
20 10 0 -220 -164 56
1 3 +2 -295 -200 95
(1994b)
H-S et al. (1993)
McG et al. (1995)
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LMD 2.0x5.6 SECHIBA
CCM 1 R15 BATS
CCM 1 R15 BATS
not known
Fixed SST
mlo poor q-flux
mixed layer ocean
6 1 +2.5 +390 -985 -1375
1 1 +0.14 -184 -126 58
14 6 +0.6 -588 -232 356
14 6 +0.3 -437 -231 206
Climatic changes are given for the Amazon region. aReferences are: HENDERSON-SELLERS and GORNITZ (1984); DICKINSON and HENDERSON-SELLERS (1988); LEAN and WARRILOW (1989); SHUKLA et al. (1990); NOBRE et al. (1991); MYLNE and ROWNTREE (1992); DICKINSON and KENNEDY (1992); LEAN and ROWNTREE (1992); POLCHER and LAVAL (1994a); POLCHER and LAVAL (1994b); HENDERSON-SELLERS et al. (1993); MCGUFFIE et al. (1995). bTime given as length of control (con.) integration in years and length of deforestation integration (exp.) in years. CAT (~ AP (mm) and AE (mm) are the annually averaged changes over Amazon Basin. dGives changes in moisture convergence: a negative value shows an increase in convergence. EDIRMEYER (1992) has reran these simulations with correctly specified SSTs and an interactive cloud scheme. He finds a much smaller precipitation change. f"mlo" indicates the use of a mixed layer ocean submodel; "q-flux" is a correction often used to stop model climates drifting.
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Regional-scale impacts of land-cover change on climate TABLE VIII REGIONAL RESPONSE, ANNUAL (GIVEN AS A MONTHLY MEAN) AND LARGEST MONTH, TO TROPICAL DEFORESTATION (AFTER MCGUFFIE ET AL., 1995)
Region
Differences Temperature (K)
North Amazon year: month: Apr. South Amazon year: month: Oct. Amazon year: month: Nov. SE Asia year: month: Mar. Africa year: month: Mar.
-0.05 -0.77 0.51 1.28 0.30 0.76 -0.69 -1.59 -0.09 -0.76
Precipitation (mm)
May Apr. Apr. Oct. Jan.
-38.2 -97 -31.8 -60.7 -36.4 -66.5 -4.0 -50.3 -9.0 -35.9
Conversion (mm)
Sept. Apr. Apr. May Mar.
24.7 82.4 12.2 40.8 17.2 45.8 -6.7 -38.4 1.6 -33.4
albedo and roughness changes (e.g. HENDERSON-SELLERS et al., 1993, cf. DICKINSON and HENDERSON-SELLERS, 1988; LEAN and WARRILOW, 1989); on the induced atmospheric circulation changes; and on the location of the disturbance as well as its characteristics. Table VIII lists the sensitivities of five regions to tropical deforestation obtained from one GCM experiment (MCGUFFIE et al., 1995). This result, possibly due to differences in the decreases in ascent (Fig. 7, cf. HENDERSON-SELLERS and GORNITZ, 1984), has some similarities with the different regional dependence that CHARNEY et al. (1977) identified. Figure 10 shows four sampled month/region impacts of imposed tropical deforestation which extended throughout the tropics (inset global map in Fig. 11). The largest impacts occurred in South America which is where the most areally extensive surface changes were prescribed (deforestation includes replacing forest by scrub grassland, lightening soil colour and making the soil texture finer). October differences are shown for the Amazon for surface temperature (Fig. 10a) and total precipitation (Fig. 10b). The rainfall decreases across the basin but temperatures increase to the northeast and decrease to the southwest (cf. Table VIII). Surface temperature in October in the deforested region of Africa (Fig. 10d) shows no statistically significant increase (inset maps). Indeed, the annual mean result (Table VIII) is a decrease in local surface temperatures. The surface temperatures in SE Asia decrease throughout most months including June, shown in Fig. 10c. DICKINSON and KENNEDY (1992) model the regional disturbances due to Amazon deforestation. The responses they find (Table VII) are initiated by changes in the surface energy balance prompted by the albedo increase and roughness length decrease. However, cloud feedback effects are found to be more important than in the desertification experiment of LAVAL and PICON (1986) described in the section on Model studies of desertification. Here, the reduction in solar radiation absorbed at the surface (-3 W m -2 ) is much smaller than the increase in net longwave radiative loss (-15 W m -2) which c o m p r i s e s - 8 W m -2 from warmer surface temperatures and -7 W m -2 from reduced downward flux caused by fewer clouds. However, DICKINSON and KENNEDY (1992) caution that, in view of the poor parameterization of clouds, little confidence can be placed in these feedbacks.
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Figure 11 shows changes in global atmospheric circulation statistics and in the surface climate following tropical deforestation for the month of October. October was selected because changes are largest in May and October. In these two months, the ITCZ is located over deforested regions so that deforestation has the largest impact on the Hadley and Walker circulations. Figure 1 l a shows regions of statistically significant changes in surface temperature. Ground surface temperature exhibits large changes far outside the deforested regions including large areas of decreased surface temperature which are statistically significant in the north of North America and in Siberia. At the same time, in the northeast and southeast Pacific Ocean, sea surface temperatures are decreased by small, but still statistically significant, amounts. The latter could be related to the weakening of the high pressure systems in both the north and south Pacific Ocean (Fig. 1 l b). Alternatively, these ocean temperature decreases might be associated with disturbances to the atmospheric jets which commonly flow from the tropical Amazon and from SE Asia or the increase in evaporation in the south Pacific Ocean. Most other evaporation changes are confined to the deforested regions (Fig. 1 lc). Total tropical deforestation causes increased convergence over SE Asia and the west Pacific Ocean (shown in maps of velocity potential, Fig. 1 l d), the convergent flow over South America is decreased and the divergent flow over the Atlantic Ocean is also decreased. Moisture convergence is also seen to decrease over the Amazon in all experiments except
462
Regional-scale impacts of land-cover change on climate
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those of DICKINSON and HENDERSON-SELLERS (1988) and POLCHER and LAVAL (1994a) (last line of Table VII) and decrease over the Amazon and Africa but increase over SE Asia (Table VIII). Student's t-tests show that changes over the west Pacific Ocean, South America and also a small area to the south of Greenland, are statistically significant. From this, it appears that the ascending branches of the Walker circulation in the SE Asian and African regions are moved eastward while ascending motion from 20~ to 40~
and over the west
Pacific Ocean is strengthened. Overall, tropical deforestation, like desertification, prompts considerable climatic responses local to the disturbance (Fig. 10 and Tables VII and VIII). As might be expected, since the imposed tropical deforestation is both more geographically extensive and more pervasive (both albedo and roughness length change) than the desertification, the effects are intermediate between those seen in Figs. 6 and 8. However, many effects remain too small to be detectable above the natural variability of the simulated climate (e.g. no discernible precipitation changes occur except over the Amazon (Fig. 10)). In both types of land-use changes, the effects are very much smaller and more localized compared to those likely to occur as the result of greenhouse-gas warming (Figs. 8 and 1 l, cf. Fig. 6 and Chapter 9 by WANG et al.). The effects of possible synergistic alterations in atmospheric dynamics are discussed in Chapter 8 by MCAVANEY and HOLLAND.
463
Human effects on climate through the large-scale impacts of land-use change Future land-use change and future climate So far in this chapter human-induced land-cover change has been treated as if it were an external force on the climate system: capable of causing disturbances but independent of induced change. To some degree this is a reasonable assumption since anthropogenic activities, including land-use change, are the result of a wide range of factors amongst which climate is often secondary. On the other hand, land-use changes, such as forest clearance for agriculture and reclamation of wetlands for building, are themselves likely to be dependent upon the future climate: crops may fail, be modified or changed if climate changes, and coasts and deltas may be inundated by rising sea-level. The state of the continental surface, particularly the biomes it will support, cannot be divorced from the climate. Natural vegetation and climate are two components of the same interactive system (e.g. DICKINSON, 1992 and Chapter 15 by KUMP and LOVELOCK). For example, the rates and types of land-use changes, both anthropogenic and in response to climate, are likely to modify the sources and sinks of greenhouse gases. Human prescription of land-use is sometimes only loosely coupled to the climate but is rarely fully independent of it. In this section, the future inter-relationships between climate and continental land-cover will be explored. However, because of the complexity of these issues, the topic will be reviewed primarily by means of the example of tropical deforestation. Future greenhouse gas releases: the case of tropical deforestation HOUGHTON (1990a) estimates that tropical deforestation accounts for 26-33% of the CO2 released annually, 38-42% of the CH 4 and 25-30% of the N20. As discussed in the section on Land-cover changes and global climate, the net release of carbon to the atmosphere from tropical deforestation seems to be accelerating, from around 0.6 to 2.5 Pg, a total of between 10 and 50% of the emissions of carbon from the combustion of fossil fuels in 1980 to a net flux of 1.3-3.6 Pg C, or 20-65% of the emissions from fossil fuels (HOUGHTON, 1991 and cf. Table IV), in 1989. Thus removal (or regrowth) of tropical forests could be a source (or sink) of atmospheric CO2 commensurate with fossil fuels. HOUGHTON (1991) has evaluated these future sources and sinks by projecting rates of deforestation and reforestation to the year 2100 according to different assumptions (Fig. 5e). Future rates of deforestation extrapolated from the rates given by FAO/UNEP (1981) for the period 1975-1985, using linear and exponential fits and a projection based on population growth, all showed similar (because all forests are eliminated from the tropics before 2100) long-term releases of between 1.25 and 3.35 Pg C per year, the range depending on whether low or high estimates of carbon stocks were used. These total releases (over 100 years), 125-335 Pg C are, respectively, similar to and three times greater than the total biotic release (temperate zones as well as tropics) over the last 100 years. MYERS' (1991) recent estimate of deforestation gave a higher net flux for 1990 than HOUGHTON'S (1991) highest, population-based, projection. HOUGHTON (1991) also considers the effects of reforestation. If deforestation were halted completely and new forests were successfully established on an estimated 865 million ha of climatically suitable abandoned and degraded lands, a net withdrawal from the atmosphere
464
Future land-use change and future climate of as much as 150 Pg C might be possible over the next 100 years (HOUGHTON, 1990b). Thus the releases of carbon from deforestation are larger and faster than the storages of carbon following reforestation: simply halting deforestation has a large benefit; the further incremental benefit from reforestation is not so great. The conclusion of these model simulations is that tropical forests might be destroyed or managed over the next 100 years to release an additional 125-335 Pg of carbon to the atmosphere or to remove about 150 Pg. These estimates include only the fluxes of carbon due to deliberate changes in the area of forests. Changes in the storage of carbon as a result of climatic change or as a result of CO2 "fertilization", not considered in this analysis, may cause release or removal of carbon in addition to these projected amounts. As was discussed earlier, GCMs are not yet able to predict with any certainty which specific locations will warm or cool, become more or less arid (i) as greenhouse gas concentrations increase or (ii) as a result of imposed land-use change. However, there is some consensus about the global impacts of greenhouse gas warming (HOUGHTON et al., 1990, 1992) and about the local effects of land-cover change including reduced precipitation and moisture convergence in the deforested areas (e.g. DICKINSON and HENDERSON-SELLERS, 1988; LEAN and WARRILOW, 1989; NOBRE et al., 1991). Whether the cause of the desertification in the Sahel, northeastern Africa, northeastern Brazil and northern Australia has been population pressure, manifested through the removal of natural vegetation and overgrazing, or whether it has resulted from natural variability in climate, the effects include decreased rainfall, increased erosion and, often, displaced populations prompting further overgrazing and deforestation (GORSE, 1985; HOUGHTON, 1991). The secondary impacts of these stresses associated with human-induced land-cover change could be that the net flux of carbon from tropical regions may become larger (HOUGHTON, 1991). Moreover, it seems that feedbacks can hamper reforestation and revegetation: the local climate may no longer support forests; fire, more common in forests occupied by farmers or loggers (MALINGREAU et al., 1985; UHL and BUSCHBACHER, 1985; WOODS, 1989), can prevent trees regrowing on abandoned lands (HOUGHTON, 1991); erosion can constrain vegetation regrowth (MABBUTT, 1984; DREGNE, 1985; VERSTRAETE, 1986). It seems necessary to consider ways of modelling the response of natural and managed vegetation to climate, if the impacts of human and climate induced land-cover change are to be more completely understood. Land-cover as an interactive component of the future climate
In order to try to assess land-cover as an interactive component of the climate system, it is possible to combine simple vegetation prediction schemes with global climate models with the twofold aims of describing future vegetation states, as climate changes, and also of examining the impact of continental land-cover on climate. Atmospheric circulation patterns and vegetation distributions have been compared at 1 • CO2 (330 ppmv) and 2• CO2 (660 ppmv) by HENDERSON-SELLERS (1992) and SMITH and SHUGART (1993). Differences between simulations illustrate the possible roles of climate in determining vegetation and of an interactive continental land-cover in determining the climate from which, perhaps, the possible impacts on climate of human-induced land-cover change might be inferred.
465
Human effects on climate through the large-scale impacts of land-use change
In an enhanced greenhouse simulation with interactive vegetation, there is a considerable increase in the area predicted as being appropriate for agriculture, whereas the total area of tropical forest (itself a contributor to atmospheric CO2) changes very little. These results must be treated with considerable caution: the scheme is highly simplistic (HOLDRIDGE, 1947, 1964), there is no CO2 fertilization effect on the predicted vegetation distribution nor is there any impact here due to human-induced land-cover change. At the minimum, the results delineate climate zones hospitable to gross vegetation types; the general impact of climate on vegetation being similar to earlier studies (MANABE and HOLLOWAY, 1975; HANSEN et al., 1984; EMANUEL et al., 1985; HENDERSON-SELLERS, 1990a). Even in this mode, some results are in contrast with those of PRENTICE and FUNG (1990), who use a similar vegetation prediction scheme to estimate, post facto, changes in equilibrium vegetation following a doubled-CO2 climate change. Their scheme was tuned to improve the pre-
TABLE IX DIFFERENCES IN CLIMATIC PARAMETERS DERIVED FROM TWO DOUBLED C O 2 SIMULATIONS (5-YEAR ENSEMBLE MEANS) AND A
1 • CO2 CONTROL INTEGRATION (i) AFTER INSTANTANEOUS DOUBLING WITH
THE INTERACTIVE VEGETATION AND
(ii)
AFTER INSTANTANEOUS DOUBLING OF C O 2 BUT RETAINING THE
PRESENT-DAY PRESCRIBED VEGETATION
Interactive vegetation
Constant vegetation
Globe
Land
Globe
+2.5 +6.1 +6.1 -4.6 -2.6 -41.8
+3.0 +6.1 +8.4 -3.7 -2.6 - 16.9
+2.5 +5.6 +5.6 -4.3 -2.4 -39.8
+3.0 +5.2 +5.7 -3.4 -2.1 -2.1
+2.7 +5.5 +5.3 -4.6 -2.8 -55.4
+3.4 +3.1 +8.9 -4.1 -2.8 -17.4
+2.7 +5.6 +5.5 -4.6 -2.6 -54.0
+3.4 +3.6 +4.9 -4.3 -3.5 -1.6
+2.5 +5.8 +5.8 -4.2 -2.8 -41.2
+2.7 +4.6 +7.5 -3.5 -3.0 -17.7
+2.4 +5.7 +5.8 -3.8 -2.0 -41.0
+2.7 +5.7 +4.7 -3.5 -2.1 -2.9
Land
Annual Screen temperature Precipitation Evaporation Planetary albedo Cloud amount Sea-ice/rootzone water
January Screen temperature Precipitation Evaporation Planetary albedo Cloud amount Sea-ice/rootzone water
Ju/y Screen temperature Precipitation Evaporation Planetary albedo Cloud amount Sea-ice/rootzone water
In all cases, the land area is 34.17% of the globe. Screen temperatures are differences in Kelvin and all other parameters are given as % of the 1 x CO 2 values. Cloud amount and rootzone soil moisture are for 00Z only, all other values are diurnal averages. Sea-ice is given for the globe and rootzone and soil water for the land entries in the lowest rows.
466
Future land-use change and future climate diction skill for the present-day climate
(PRENTICE, 1990) and is applied at a much finer
spatial scale than the 4.5 ~ latitude by 7.5 ~ longitude resolution used to derive the results shown in Table IX, although their GCM input is coarser (8 ~ by 10~ PRENTICE and FUNG (1990) estimate that the terrestrial vegetation-only carbon reservoir will increase by between 232 Pg C and 292 Pg C globally as compared with about 6.3 Pg C over the globe calculated with the interactive vegetation scheme. The major reason for the discrepancy seems to be the differences predicted in the area of tropical rainforest. These experiments also allowed investigation of whether climate-induced land-cover changes affect the GCM's simulated climate. Table IX summarizes some climate statistics resulting from the two doubled CO2 experiments as differences from, or percentages of, the 1 x CO2 control (HENDERSON-SELLERS and MCGUFFIE, 1994). The rootzone soil moisture appears to be sensitive to the inclusion of an interactive biosphere but this response is, in part, the result of changes in rootzone soil depth which is itself a function of the vegetation type in the vegetation submodel (DICKINSON et al., 1986, 1993). There is almost no difference in this variable between 1 x and 2x CO2 when the prescribed vegetation is used. Planetary albedo decreases as in most doubled-CO2 experiments, partly as a result of decreased cloud amount, partly because of the snow-albedo feedback and partly because of a decrease in ice-cap area. The evaporation from the continents is noticeably larger when the vegetation is interactive than when it is prescribed at the present-day distribution and in the annual mean the global (oceanic as well as terrestrial) evaporation is greater when the vegetation is interactive (Table IX and cf. HENDERSON-SELLERS, 1992). Analysis indicates that the vegetation changes may be prompting a feedback between the atmosphere and the oceans, via low-level convergence changes in the tropics, which further increases global evaporative flux. In summary, interactive continental land-cover does modify the climatic change due to doubling of atmospheric CO2. The most direct changes are enhanced continental evaporation which prompts intensification of the atmospheric circulation in the tropics and, in turn, enhanced oceanic evaporation. The interactively predicted land-cover change is also likely to modify the carbon reservoir and hence the potential future strengths of greenhouse gas sources and sinks, but these changes will be further, and very likely greatly, affected by human-induced land-use changes. Future climates
The future climate of the Earth will be affected by human activities. The most compelling case for this assertion can be made in relation to the impact on climate of greenhouse gas increases (e.g. HOUGHTON et al., 1990, 1992; Chapter 9 by WANG et al.). Human-induced land-use and land-cover changes contribute directly and indirectly to sources and sinks of important greenhouse gases: perhaps as much as a third of the increase in some trace gases can be attributed to human-induced land-use and land-cover change. However, aerosols released by biomass burning and in combination with aerosols from other sources (Chapter 10
by ANDREAE) cause a, somewhat compensatory, cooling. In the future, land-use policies could also contribute significantly to attempts to manage further greenhouse gas increases. Climate modelling studies suggest that extensive land-cover changes, such as tropical deforestation and regional desertification, do affect climate at the location of the land-cover
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Human effects on climate through the large-scale impacts of land-use change change and may cause effects elsewhere. However, the local climatic effects are not the same in different parts of the globe even when the same land-cover change is imposed, and the confidence with which these climatic changes can be viewed is further reduced by a general lack of quantitative observations against which to evaluate models. Furthermore, the uncertainty about climatic changes distant from the site of the imposed land-cover change is, at present, considerable. Although in some cases (e.g. large albedo increases and additional aerosol loads) land-cover change might be expected to mitigate the warming, climate model studies indicate that the inter-relationships are much too complex for complacency to be a wise management plan. It is not very easy to separate the climatic effects of land-use and land-cover from those of other anthropogenic and natural disturbances. However, in the context of this book, land-use and land-cover changes can be seen as having local- and global-scale impacts on climate. Globally, the most compelling case is for a warming. There are compensating cooling mechanisms but these are probably smaller and are currently less well understood. Locally, the impact on temperatures is less certain than the disturbance to the surface hydrology. Most likely future land-use/land-cover changes tend to reduce evaporation and hence affect runoff and local hydrology and many also increase surface temperatures. The global demands for food, water, housing and development will escalate if the projections of the world's population exceeding 10 billion by 2050 and 11.6 billion by 2200 are correct. Land-use change occurs not only as a result of human activities but also as a consequence of climatic change (e.g. HEATHCOTE, 1991) including that due to greenhouse gas increases. At present, it is impossible to predict the climatic consequences of the massive landuse changes and consequent land-cover changes which these world populations must demand. However, it is clear that there are many non-linear feedbacks in the socialenvironmental-climatic system. The inevitable additional burden of increasing population adds great strain to the Earth's already stretched resources.
Acknowledgements I wish to thank Dr V. Gornitz, Professor R.E. Dickinson, Dr J.G. Cogley, Dr M. Manton, Dr K. Laval, Dr Lu Zhang, Dr D. Graetz, A. Schlosser and P. Irannejad for reviewing and making very helpful input to earlier versions of this chapter. This work has been supported in part by grants from the Australian Research Council, the Model Evaluation Consortium for Climate Assessment and the Department of the Environment, Sport and Territories. This is the Climatic Impacts Centre contribution number 93/3.
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475
Chapter 13
Urban climates H. CLEUGH
Introduction Overview
Within the next decade, and probably by 2000, almost half of the global population will live in cities (HAMMOND, 1992) (Fig. 1). Any discussion of future climates should therefore include a description of the local climate for most of the world's population: the urban climate. As this chapter will show, cities do influence the local and regional climate. The magnitude of urban effects on precipitation and temperature were recently described (CHANGNON, 1992) as being similar to, and maybe even greater than, those changes predicted from global climate models (GCMs) to develop over the next 100 years as a result of greenhouse warming. This chapter describes present-day urban climates and urban climatic processes which provides the basis for a discussion of future urban climates. The exploding urbanisation in Fig. 1 is reflected in increased proportions of agricultural or "natural" landscapes being converted into urban land use. To some degree this has already happened in the highly urbanised developed nations (Fig. 1) where most urban expansion comprises suburban sprawl. The rapid growth of cities in developing and less developed nations, especially those in the tropics, is a much more recent phenomenon that began after World War II (JAUREGUI, 1986) and will continue into the 21st century. There has been a ninefold increase in the number of tropical cities with more than one million inhabitants from 1940 to 1970 (JAUREGUI, 1986). In 1992, the United Nations listed 21 cities that could be classed as megacities - urban agglomerations with current projected populations of 10 million, or more, by 2000. All but three of these were located in developing and less developed nations. Urbanisation initiates one of humanity's most dramatic land use changes: a natural landscape, often containing transpiring vegetation and a pervious surface, is converted to a built, largely impervious landscape made-up of rigid, sharp-edged roughness elements. Exchanges of heat, water vapour and momentum between the new urban "surface" and the atmosphere are modified by the different radiative, thermal, aerodynamic and moisture properties of the urban landscape. The air quality is altered by the input of wastes from urban activities. The natural topography and drainage networks are radically modified during urban development, as well illustrated by the straightened, concrete-lined channels that form the urban drainage system. Fig. 2 provides a useful overview of urban activities and their effects on physical climate processes.
477
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Fig. 1. Urban population growth from 1900 to 2025, expressed both as a percentage of the total population and in total numbers. Note: Figures are actual from 1900 to 1985, and projected from 1985 to 2025 (dashed lines). Based on data from Og~ (1986). "Developed" nations are those nations in North America, Europe, the former USSR, Australia plus Japan; "Less developed" nations are those in Africa, Latin America and Asia (excluding Japan, Melanesia, Micronesia and Polynesia). These are the groupings used in the United Nations report.
In this way cities indirectly modify those atmospheric variables, such as temperature, humidity, airflow and rainfall, whose ensemble averages define the climate
(OKE,
1980). This
happens at local (<1 km horizontally; <100 m vertically) and meso (<100 km horizontally; <~ 1 km vertically) spatial scales. The magnitude and extent of these weather and climate effects cannot be generalised for all cities because they depend on city-specific factors such as the pre-urban land use and the regional climate. Interest in urban climates began in 1833 when Luke Howard (HOWARD, 1833) first documented that cities appeared to be warmer than the surrounding countryside. Many studies in the 160 years since have well established this urban heat island effect; a phenomenon linked to differences in urban/rural cooling rates and best seen at night under clear skies and light winds. Longer term studies show that cities modify climates, at least at the local spatial scale, e.g. KARL et al. (1988) found urban effects on air temperatures in towns with only 10,000 inhabitants. Much research in the last 20 years has been directed towards not only describing the nature of urban climates, but understanding the processes that lead to the observed urban climate. In extrapolating this current knowledge to predict future urban climates, the following questions must be considered: 9
What will be the nature of future cities? Urban climates in the future will be determined by many factors, including: height and spacing of buildings; nature of construction materials; location of city; type and pattern of energy use; transport mode; type and location of industries; amount of greenspace; city layout etc.
478
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Fig. 2. Conceptual flowchart of the effects of urbanisation on the radiation, energy balance and local climate (modified from YAMASHITA and SEKn~, 1990/91). Note that feedbacks between the modified physical processes are not included.
9
9
Will there be an urban influence on the regional and global climate, and how do we separate this effect from that due to global climate changes, such as result from the greenhouse effect?. What will be the nature of the future global climate? Urban effects are superimposed on the regional and global climate, thus the climate of cities in the future has to be considered in light of global climate changes.
The last, and to a lesser extent the second, question can really only be answered using GCMs with an ability to include local scale urban effects, a task beyond the reach of current GCMs. Recent analyses of the US temperature record (e.g. KARL et al., 1988; KARL and JONES, 1989; JONES et al., 1989) have provided observational evidence of the contribution of urban warming to the continental and global temperature signal. The variation between estimates from different studies illustrates that they are by no means definitive. Numerical models potentially have an important role in answering questions about urban effects, comprehensive reviews of urban climate models can be found in OKE (1974, 1979a) and BORNSTEIN (1986, 1989). Many mesoscale numerical models that have been specifically applied to urban meteorology are limited by their crude land surface schemes (ROss and OKE, 1988). Two such examples are the modelling studies of HJELMFELT (1982) and SEAMAN et al. (1989) which are of great interest because they separate urban and topographic effects on mesoscale airflow and thermal features using a series of model "experiments". However, the results are limited by the use of a simple moisture availability factor to partition sensible and latent heat fluxes. Thus far models have helped to elucidate urban processes but at present they are of limited use in predicting future climate change in
479
Urban climates cities or the impact of urban effects at the larger scale. The focus of the chapter is therefore upon explanation of processes that lead to current urban climates which gives a basis for the discussion of future climates. This chapter does not include air pollution. This does not relegate atmospheric pollution to being unimportant in future cities as this is probably the major regional-scale impact of urban/industrial areas, but it is beyond the scope of the chapter. Future cities
Any survey of current urbanisation statistics reveals two facts about future cities. Firstly, much of the current and future urban growth, including the rise of the megacities, will be in the poor and developing nations (Fig. 1). An increase of 750 million people in cities in the developing nations is projected from 1986 to 2000 (UNITEDNATIONS, 1986 cited in OKE et al., 1990). Secondly, in terms of geography, much of the urban growth will be in the tropical latitudes. Of the 23 nations with the highest rates of urbanisation in the period 1980-1985, 18 were in Africa and the remaining five in Asia (UNITED NATIONS, 1989). These nations currently have the lowest level of urbanisation, but their urban population is predicted to grow by 40% per decade from 1990 to 2020 (UNITED NATIONS, 1989). Apart from these rapid urban growth rates in lower latitudes is the projection that, by 2000, 17 of the 26 cities with populations over ten million will be in the tropical latitudes (UNITED NATIONS, 1986, cited in OKE et al., 1990). Of the 20 megacities identified in a 1992 UNEP Report, ten were located between the Equator and 30 ~ and another six between 30 ~ and 35 ~ (South and North) (UNEP, 1992). Quite clearly a discussion of future urban climates must address urban effects in cities in the tropical latitudes, often located in poor nations (such as Africa) or rapidly industrialising nations such as Mexico or Thailand where economic growth and industrialisation will have a major influence on energy use, energy type, city growth and morphology. The dilemma is that most process-oriented knowledge arises from research conducted in mid-latitude cities located in the developed nations of North America, Europe and Oceania (Australia and New Zealand). As noted earlier, most urban growth in the tropical latitudes is post World War II. JAUREGUI (1986) argued that this is why studies of urban climates in tropical cities really only began in the 1970s. Rapid industrialisation in many tropical cities over the same period has led to deteriorating air quality which has also stimulated a demand for meteorological information. Limited financial resources has meant that often the only data available are from standard weather stations. This has prevented detailed process-oriented studies in tropical cities and led to many descriptive studies. This dearth of information on urban climate processes means that our models of urban climate processes have not been evaluated in tropical cites. Often, we can only make some broad generalisations based on a limited number of studies. The larger scale climate in which tropical cities are embedded, by comparison to midlatitude cities, is characterised by much smaller temperature ranges and seasons are marked by variations in humidity, rainfall and cloud rather than temperature (JAUREGUI, 1986). The inter-annual variation in radiation climate in principle will be small, but marked seasonality in cloud cover can modify this. Solar elevation angles are higher than in mid-latitudes.
480
Introduction
Building heights, spacings and construction materials will differ from typical mid-latitude urban morphologies. JAUREGUI (1986) suggested the following differences between tropical and mid-latitude city structure: lower buildings; larger proportion of unpaved streets; small proportion of greenspace and large slum areas. The climate regimes characterising tropical cities (JAUREGUI,1986) fall into the following classes, excluding topographical and continental effects: 9
equatorial humid climate: either wet all year (e.g. Singapore) or alternating dry/wet sea-
son (e.g. Jakarta); prevailing trade winds (easterly) all year; uniformly warm temperatures and high humidity; high radiation only during short dry season; 9
9
tropical/subtropical dry: with a short wet season (may be warm or cold); seasonal tem-
perature variation depends on whether the location is coastal or continental; high radiation all year; seasonal variation in air mass, wind speed and direction; wet and dry season subtropical (humid~sub humid): seasonal changes in air mass and variation in radiation climate (e.g. Mexico City).
It is of interest to note that of the ten megacities identified by UNEP (1992) that are located at latitudes less than 30 ~ (South and North), seven have tropical (either savanna, rainforest or steppe) climate regimes. Annual mean temperatures are greater than 25~
high humidity
and annual rainfall totals exceed 1000 mm (mostly occurring in heavy falls in the wet season) for all seven. The remaining three cities are Karachi (desert or subtropical dry); Mexico City and Sao Paulo. Future urban growth will thus be in the poor or developing nations; located in the humid tropics, wet/dry subtropics or deserts. There will be a continued large influx of rural populations into not only megacities but also small to medium-sized cities. A large portion of this immigrant population will be housed in makeshift shelters in unplanned, densely populated urban slums.
Methodological considerations Interpreting and quantifying the processes that lead to urban climates is complicated by two factors. Firstly, there are few pre-urban measurements, so it is difficult to establish the direction and magnitude of urban-induced changes. Secondly the complex nature of the urban landscape limits the applicability of conventional meteorological theory. Fortunately several methodological frameworks have enabled progress; these are discussed next. LOWRY (1977) proposed a methodology which he believes is necessary to adopt if we are to prove an urban influence on the observed climate. His methodology, in brief, states that an urban influence on a climate element can only be isolated if it is based on observations of that element both prior to and following urbanisation. Furthermore, any effects due to largescale climate change or landscape effects (e.g. topography) must be removed from the measurements and the data should be stratified by weather type. This methodology is all but impossible to adhere to, hence most empirical studies only approximate this ideal. In particular weekend/weekday comparisons and urban/rural comparisons will be flawed. A recent study by GRIMMOND et al. (1993) illustrates the importance of the "rural" land-cover in comparisons of urban and rural climate processes. They compared energy balances and microclimates between suburbia and two rural sites, one of which was irrigated and the other unirrigated. The size and direction of the urban effect depended on whether the comparison 481
Urban climates
was made between suburban and "dry" rural, or suburban and "wet" rural. Their study is a good reminder that "rural" land use is often just as likely to be influenced by human activities as urban land use and is not an appropriate surrogate for pre-urban land use and climates. CLEUGH and OKE
(1986) avoided this dilemma by using energy balances measured
simultaneously at a suburban site and a "control" site. This control site was flat with short grass which eliminated the complexity introduced by buildings and surface types that characterise suburban land use and enabled urban effects on atmospheric processes to be clarified. Unless such measurements are conducted over a long term, this methodology does not allow for an assessment of urban effects on climate, only on atmospheric processes. That this approach is not a substitute for Lowry's methodology illustrates the difficulty in proving urban climate effects - a point that should be borne in mind throughout this chapter. This methodological difficulty also illustrates the important role that physically based models have in understanding and detecting urban effects. There is an urgent need for development and validation of appropriate urban surface parameterisation schemes that can be linked to current generation mesoscale models and embedded into GCMs. Scales
A key to interpreting and/or modelling urban effects on atmospheric processes is to develop a methodology or conceptual framework that accounts for the heterogeneity of the urban "surface". As with any natural landscape, this heterogeneity is scale-dependent and OKE (1976) developed such a framework that took advantage of the natural range of scales present in urban morphology. Table I shows these scales and their spatial dimensions. Oke divided the urban surface and atmosphere into urban canopy and urban boundary-layers as shown in Fig. 3. The urban canopy layer (UCL), which lies below the mean roof level, is made up of an array of vertical, horizontal, sloping and multi-level surface elements. These surface elements each have varying thermal, moisture-holding, radiative and aerodynamic properties which, in turn, lead to a range of microclimates within the UCL. The urban
TABLE I SPATIAL SCALES IN THE URBAN ENVIRONMENT
Urban units
Urban features
Spatial dimensions (m) Width
Building Canyon Block Land use zone
City
Single building, 10 tree or garden Urban street and 30 bordering buildings City block, park, 500 factory complex Residential, 5000 commercial, industrial etc. Urban area 25,000+
Adapted from Oga~(1984).
482
Scale
Atmospheric layer
Micro
UCL including roughness or wake layer
Local
Surface, or constant flux, layer
Length 10 300 500 5000 UBL including surface layer 25,000+
Meso
Introduction
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boundary-layer (UBL) extends from mean roof level upwards. The UBL is derived from the concept of an internal boundary-layer growing with distance downwind from the leading edge, which in this case is the surface transition from upwind "rural" to urban land use (Fig. 3). The air flowing over the city becomes modified by, and adjusted to, the new surface, starting with the lowest air layers. If the horizontal extent of the city is sufficiently large, this urban-influenced boundary-layer (the UBL) will occupy the entire PBL. The constant flux layer (also referred to as the surface layer) lies at the base of the UBL and above the roughness layer (also known as the wake layer) where flow is influenced by individual buildings. Areally averaged turbulent fluxes from the underlying canopy are assumed to be constant with height in the surface layer, whose depth may reach ca. 100 m by day.
Nature of the urban surface Although we can identify many individual urban surface elements, Oke's approach treats these as simply facets of an integrated urban surface, which is actually a volume. Fig. 4 is a conceptualisation of this urban canopy volume, containing roughness elements such as trees and buildings; horizontal surfaces such as roads, pavements and rooftops; and the air contained within the canopy layer. Turbulent exchanges between the urban surface and atmosphere are represented by areally averaged fluxes flowing across the plane ABCD in Fig. 4a, into/out of the urban canopy volume. Provided our perspective is from some location at a distance above the top of the UCL, the urban canopy volume can be conceptualised as a two-dimensional "surface" representative of a larger spatial scale, e.g. a land use zone (Table I). We can then begin to note some characteristic features of this urban surface.
483
Urban climates
T
B
i
Boundary layer
(iBL) Canopy (UiL) layer
Fig. 4. (a) The urban canopy volume (after Or~, 1987). (b) The urban canyon with height (H) and width (W).
In suburban land use the dominant roughness elements are buildings (mostly houses and commercial buildings) and trees whose heights are typically of order 10 m. These roughness elements are sparsely distributed, spacings of ca. 20-50 m were identified for a suburban, North American city (Vancouver, SCHMID, 1988; SCHMID and OKE, 1992). This roughness element spacing is strongly influenced by the street pattern and hence can be anisotropic. The surface is also aerodynamically rough, buildings act as bluff bodies which extract momentum from airflow via skin friction and form drag. Roughness parameters vary with roughness element height and spacing. Suburban land use has typical roughness lengths of 0.5-1 m while urban roughness lengths may be as large as 4 m (OKE, 1980). The open canopy structure and the "patchy" array of horizontal surfaces with contrasting properties (e.g. dry roads and wet lawns) leads to active horizontal exchanges of heat and mass via microscale advection. It is important to realise that the atmospheric feedbacks and interactions that occur within the UCL mean that we cannot simply sum individual surface elements to determine the ef-
484
Urban climate processes fect of the entire urban surface on atmospheric processes and climates. Likewise, horizontal pavements or lawns cannot be used as surrogates for the urban surface. Rather, we have to understand the way that the entire UCL functions. Thus, we recognise the urban canyon (Fig. 4b) as a fundamental unit of the built landscape that is replicated throughout the UCL. The urban canyon is simply two building walls, with height H, separated by a road of width, W. The aspect ratio (H/W) describes building spacing and is an important descriptor of the UCL. Radiative exchanges and airflow characteristics depend on the size of the aspect ratio.
Urban climate processes
Fig. 2 shows the connections between urban activities and climatic processes, this section explains these connections and so addresses the question of "how do urban areas modify these physical processes?" The magnitude and direction of these urban-induced changes are quantified by reviewing the current state of knowledge, most of which has derived from a combination of observational and modelling studies. Radiative effects
The incoming shortwave radiation (K,[,) exerts a first order forcing on the climate of any location, as has been shown in earlier chapters. When discussing the radiation balance for the UCL, K,[, refers to the radiation impinging on a plane extending across the top of the UCL (plane ABCD in Fig. 4a). Shortwave radiation comprises both direct beam and diffuse components, the latter refers to radiation reflected and scattered by atmospheric particulates and gases. The amount of shortwave radiation absorbed within the UCL volume depends on the latter's albedo (a). Cities also affect the longwave radiation budget; downwelling longwave radiation from the urban atmosphere impinging on the plane ABCD in Fig. 4a is defined as L$. We begin by discussing atmospheric effects on downward shortwave and longwave radiation and then discuss the influence of the urban canopy on shortwave and longwave absorption. Readers are referred to Chapter 1 by HENDERSON-SELLERS which describes the pathways for radiative transfer in the atmosphere. A depletion in K,], would be one of the most obvious examples of the effect of cities on radiation. This reduction is expected because the polluted urban atmosphere will reduce the atmospheric transmissivity for shortwave radiation. Unfortunately observational studies find this hard to prove (OKE, 1979a) because nearby rural measurements may well be contaminated by downwind transport of these urban pollutants. Table II (from OKE, 1988) shows typical reductions in incoming shortwave radiation. These values tend to fall into two groups: (a) large reductions for those cities with a sizeable industrial base where SPM (suspended particulate matter) is common; here reductions of up to 30% in K,[, on individual days have been observed with typical annual reductions of around 10%; (b) other cities where SPM levels are low, but photochemical smog exists, reveal much smaller reductions in incoming shortwave radiation, typically less than 5%. Observations show that the reduction in K,[, is variable both spatially (i.e. from city to city) and temporally (i.e. diurnally and seasonally). Causes of these variations include (OKE, 1979a):
485
Urban climates
TABLE II ATTENUATION OF INCOMINGSHORTWAVERADIATION(FROM OKE, 1988)
Author (Year)
City
Data Period
Attenuation
(%) PASZYNSKI(1972) PROBALD(1974) HESS et al. (1978) HAY (1984) SANDERSONet al. ( 1 9 7 3 ) ROUSEet al. (1973) YAMASHITA(1979) SEKIHARA(1973) PETERSONand STOFFEL(1980) METHODand CARLSON(1982) CHOWand CHANG( 1 9 8 1 ) WANG and LIU (1982) ESTOURNELet al. (1983) PETERSONet al. (1978)
Upper Silesian industrial district Budapest, Hungary Cracow, Poland Vancouver, Canada Detroit-Windsor, USA Hamilton, Canada Tokyo, Japan Tokyo, Japan St. Louis, USA St. Louis, USA Shanghai,China Hangchow, China Toulouse, France Los Angeles, USA
1955-1968 1976-1978 1979-1981 1970-1971 1970-1972 1967-1968 1961-1971 1975-1977 1975-1976
1979 1973
12 9 12 1-2 9 12 12-14 10-15 3 7 15 9 3 6-8
Note: based on studies since 1970 only; includes data for studies with very different periods of observation (3 months-13 years) and cloud conditions (some only use clear skies).
9
geographical location and time of day/year (determine the optical pathlength);
9 9
averaging period; industrial and manufacturing activities and mode of transport;
9
wind direction in relation to the location of industries, major highways, etc.;
9
sky cover (viz. cloudy or clear).
Examples of such variability are found in the studies presented in Table II. A recent study by STANHILL and KALMA (1993) reported an annual decline in KS of 1.08% over the 35 years of measurements at Kowloon (Hong Kong). They attributed most of this to reduced direct beam radiation resulting from increased emissions of aerosols from fossil fuel combustion. This follows the results of STANHILL and MORESHET (1992) who showed the influence of vehicle pollution on depletion of KS in Israel. Cities with a large, old and inefficient vehicle fleet are likely to find similar reductions in KS. Such variability means that it is impossible to generalise about the size of the reduction in shortwave radiation in cities. In terms of future climates, cities in rapidly industrialising nations will likely have the greatest reductions in K,I, if fossil fuels remain the major primary energy source. Warmer UBL temperatures, resulting from greenhouse warming, have the potential to increase photochemical smog formation which may further reduce KS. These studies refer to the receipt of shortwave radiation at UCL level. Atmospheric constituents (including water vapour, aerosols and SPM) will selectively absorb radiation which further alters the radiation budget both of the UCL and the UBL, as described for the globe in Chapter 10 by ANDREAE. Some studies suggest that radiative heating from absorption within the UBL is important. Others agree with LYONS and FORGAN (1975) who noted that atmospheric pollutants tend to scatter, rather than absorb, the solar beam. Diffuse radiation, rather than radiative heating of the UBL, is then increased and accounts for 60-80% of the attenuated direct beam radiation (OKE, 1988). METHOD and CARLSON (1982) found that
486
Urban climate processes
maximum heating rates due to absorption by aerosols were more than 3~
near the sur-
face, but averaged over the day were only 1~ near the ground and closer to zero at the top of the urban convective boundary layer. They concluded that heating effects due to aerosols were not large and any heating was slightly less than the cooling that resulted from increased longwave emissions (see below). Numerical simulations (YOSHIDA, 1991) showed that the UBL temperature structure was influenced by aerosols during the daytime only. Under calm conditions, where radiation scattering is dominant, urban temperatures were lowered and the urban-induced thermal circulation (see below) weakened. This had the effect of enhancing the aerosol concentrations even further. Urban-induced circulations were not affected when radiation absorption, rather than scattering, dominates. In these conditions near surface temperatures decreased and upper temperatures either increased or were unchanged. Ultraviolet (UV) radiation is readily absorbed by ozone which is created in the UBL as a part of the photochemical smog cycle. Thus we would expect to find reduced levels of UV radiation beneath urban atmospheres, but estimates are highly variable in space and time; 10-15% reductions in Tokyo (Japan) and up to 50% on individual days in Los Angeles (USA) in the autumn (OKE, 1976, 1979b). While aerosols may reduce K,[,, they can increase the emission of longwave radiation because of their effect on UBL temperature and emissivity; an urban-induced "greenhouse effect" is created. As with the depletion of shortwave radiation, this effect varies from city to city, e.g. WHITE et al. (1978) found no difference in L,[, between urban St. Louis (USA) and the surrounding rural area whereas ROUSE et al. (1973) observed large daytime differences in the industrial city of Hamilton (Canada). There is evidence from many of these studies that a reduction in KS due to aerosol absorption yields an increase in L,],, hence there is little change to the total incoming radiation (OKE, 1988). Increases in L$ are not always due to aerosol effects on atmospheric emissivity, however, but result from a warmer urban atmosphere arising from the heat island effect (e.g. ESTOURNEL et al., 1983; OKE and FUGGLE, 1972; SUCKLING, 1981). The general consensus is that urban values of L,[, are larger, primarily because of the warmer atmosphere (OKE, 1988) but atmospheric aerosols may also play a role. Large downwelling longwave fluxes are often offset by increases in emitted longwave radiation from the UCL (i.e. LI") hence differences between urban and rural net longwave radiation will be small. Cities therefore influence the receipt of radiation because of the composition and temperature of the urban atmosphere. The factors discussed, plus the variability of pollution emissions (amount, type and timing) both between cities and within individual cities, means that it is difficult to generalise an urban effect. In general, the shortwave radiation received at the UCL may be reduced in intensity, be more diffuse and be depleted in some wavelengths. Reductions in KS will be offset by increases in L,l,. The altered nature of the urban surface also has a strong influence on the receipt and absorption of radiation because its convoluted, three-dimensional nature can result in shading and multiple reflection of the solar beam once it enters the urban canyon. Multiple reflections lead to greater shortwave trapping and absorption and so the albedo of the UCL is reduced. Urban albedos are also lower because of the dark nature of many materials used in urban construction (e.g. asphalt), however radiative trapping means that any threedimensional surface will absorb more radiation than a horizontal one constructed of the same material. AIDA (1982) found this difference to be of the order 20% based on an ex487
Urban climates
TABLE III ALBEDOS OF URBAN AND NON-URBAN SURFACES AND LANDSCAPES
Surface type/landscape
Mean albedo
Range
Asphalt Concrete Corrugated iron Suburban landscape Commercial/industrial land use Urban land use Pasture (short grass) Pine forest Wheat crop
0.12 0.27 0.13 0.15 0.27 0.14 0.25 0.10 0.22
0.05-0.20 0.10-0.16 0.10-0.18 0.11-0.16 0.05-0.15 0.18-0.25
From Ord~ (1987); ARNFIELD(1982); STEYNand OKE (1980). perimental arrangement of blocks; TAKAMURA (1992) also observed an overall decrease in the spectral reflectance (0.475-0.75/zm) over urban land use because of this altered urban canopy structure. Table III shows that urban albedos are typically 14-15%, ca. 10% smaller than pasture but little different from tall grass or forest. Longwave radiation emitted from surfaces within the UCL is absorbed and re-emitted by other surfaces and the air volume within the UCL. Thus we refer to longwave radiation "trapping" in the UCL. The sky view factor (SVF) for a point in an urban canyon is a measure of the relative amount of radiation emitted by each element occupying the point's hemispherical field of view that is intercepted by that point. More simply, the SVF is the percentage of a point's field of view that is occupied by sky, as opposed to buildings, trees or any other object in the landscape. Canyons with a large aspect ratio will have a small SVF; flat fields with an unobstructed horizon will have a large SVF. Because buildings emit greater amounts of longwave radiation than the cool sky, an urban canopy with a small SVF will yield a larger net longwave radiation (L*). Nocturnally, this larger L* will reduce radiative cooling and maintain a warmer UCL. Fig. 5, from OKE et al. (1991) illustrates this influence of SVF on surface temperatures. Despite these urban effects on the individual components of the radiation budget (equation (1), below), urban-rural differences in the net all-wave radiation (Q*) are often less than 5% (see AUER, 1981; OKE and MCCAUGHEY,1983; OKE and CLEUGH, 1986). Q* = K,,[,(1 - a ) + (L,[, - L'[') = K* + L*
(1)
This arises because of the negative feedbacks that exist between albedo/shortwave radiation absorption and surface temperature/emitted longwave radiation: surfaces with a low a and thus high shortwave absorption will also have very small longwave radiation gains because of their high surface temperature. Similarly, the reduction in KS is countered by an increase in L$. OKE (1979a) describes this conservative behaviour as a "fortuitous" offsetting of radiative effects. This may also explain observations of very limited spatial variability of Q* within the urban landscape (e.g. WHITE et al., 1978; SCHMID et al., 1991). Thus differences in net all-wave radiation are unlikely to cause changed urban climates. While changes in individual terms in equation (1) may lead to greater heating or cooling in components of the
488
Urban climate processes 171~,
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Fig. 5. Modelled nocturnal cooling of surface temperatures (simulations use SHIM; see text) from an equivalent temperature at sunset (17~ for four different urban canyon aspect ratios and a flat rural surface (from OrE et al., 1991). Sky view factors (SVF) are for the canyon floor midpoint. urban canopy-atmosphere "system", the amount of radiative energy available in the UCL for subsequent heating is little changed by cities. Surface energy balance in cities
An understanding of the processes that contribute to an altered urban climate must include an analysis of the energy balance at an appropriate scale. The energy or heat balance simply shows the way that radiative energy (the energy source by day) is partitioned between various forms of heating: sensible (QH), which leads to a rise in air temperature; latent (QE) which leads to the phase change of liquid water at the surface into water vapour, and its subsequent transfer into the atmosphere; and conducted (Qc) sensible heating which leads to warming of the soil. The urban energy balance can be written as Q* + QF = QH + QE + AQs + AQA + AQp
(2)
Using this sign convention, all fluxes on the left-hand side are inputs and those on the righthand side are outputs. Readers should be aware that some authors use reversed signs; others define all output fluxes as negative and inputs as positive (i.e. all the terms in (2) sum to 0). The turbulent heat fluxes (QH and QE) refer to the fluxes emerging from the UCL and crossing the plane ABCD in Fig. 4a. The conductive sensible heat flux (Qo) has been replaced by a heat storage flux (AQs) which includes not only heat conducted into the UCL floor and walls, but the change in heat content of the air volume contained within the UCL. If the "box" illustrated in Fig. 4a (i.e. the UCL) extends for large distances up and downwind and the land use inside the "box" is homogeneous, then the net horizontal transfer of heat (AQA, the advective flux) will tend to zero. QF and AQp are the anthropogenicgenerated and photosynthetic heat fluxes, respectively. The terms on the right-hand side of equation (2) can be considered to be sinks or output fluxes. Obviously energy exchanges within the UCL will be exceedingly complex because of the many surfaces with differing moisture contents, geometry (especially their slope and aspect) and thermal properties. Albedo, shading, slope and aspect will exert the primary influence on the net radiative gain or loss for individual surface elements such as roads, walls and
489
Urban climates rooftops. The net all-wave radiation will be partitioned into either sensible or latent forms, depending upon the surface moisture status. Impervious surfaces will partition all their available energy into sensible heat. Microscale advection will also be dominant if the surfaces are moist, as shown by OKE's (1979b) measurements of evaporation and available energy (Q* - QG) in a well-watered suburban lawn. He observes a downward flux of sensible heat as a result of horizontal heat transfer from the warm paved surfaces to the moist lawn. Sensible heat transport towards the moist surface maintains an evaporation rate that exceeds the available energy. The array of surface elements within the UCL is so complex that we restrict our attention to either the scale of a complete urban canyon or the entire UCL to enable a more general understanding of urban energy partitioning. The urban canyon is a common feature in the urban landscape. Modelling and measurement studies of the urban canyon recognise that processes operating within this fundamental "unit" will be replicated across the UCL. NUNEZ and OKE (1977) instrumented a nonvegetated urban canyon in Vancouver (Canada) to measure all the energy balance components (Q*, Qrt, QE, AQs). Their results showed the influence of canyon geometry which perturbs the radiation regime for each of the canyon facets. When summed for the entire urban canyon, the diurnal course of the energy balance components showed features typical of fiat, "ideal" surfaces (Fig. 6). Similar features have been noted in other canyon energy balance studies (MILLS and ARNFIELD, 1993; YOSHIDA et al., 1991).
600
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Fig. 6. Measured diurnal variation of energy balance components at the top of an urban canyon (upper figure, from NUNEZ and Or~, 1977) compared to energy balance components measured over a smooth, dry surface (lower figure, measurements from a semi-arid site near Alice Springs in Central Australia) with no available surface moisture. QG is the heat flow into the sandy surface and replaces AQs in the urban energy balance.
490
Urban climate processes From a local and regional scale climate perspective, it is better to consider the UBL, where we write the "surface" (viz. the UCL) energy balance as presented in equation (2). This, combined with logistical constraints on measurements within urban canyons, has resulted in a greater number of studies focusing on the UBL. In the last 10-15 years, the first direct measurements of the terms on the right-hand side of equation (1) have appeared from cities in locations ranging from mid-latitude to tropical (including: Adelaide, Australia; Vancouver, Canada; Sacramento, St. Louis, Tucson, USA; Mexico City, Mexico). The following discussion reviews the salient points from these energy balance studies. The anthropogenic heat flux (QF) is a source of energy in cities that is absent from most rural energy balances and is often cited as one of the main reasons for elevated air temperatures in cities. The source for the anthropogenic heat flux is the energy released from domestic heating, combustion in the automotive and industrial sectors, and other forms of industrial energy. Estimates of the size of this flux are available in the studies by YAP (1973), GRIMMOND (1988) for Vancouver (Canada) and KALMA (1974) for Sydney (Australia). These studies indicate a peak value of--25 W m -2 at noon on an anticyclonic, summer day. A first order estimate of --15 W m -2 for daily QF appears appropriate, however the flux is extremely variable across cities and temporally (KALMA, 1974). Table IV presents annual average anthropogenic fluxes compiled by OKE (1988). These data plus results from other modelling and measurement studies reveal that QF depends on overall climate, population density and energy consumption. Although the magnitude appears relatively small in comparison to the other components of the energy balance, under some conditions (such as at night or in the winter) this source of energy can become very important especially in proportion to the size of Q* as illustrated by the results of GRIMMOND (1992). For daylight hours, QF exceeded 10% of Q* only in the winter months (January and February). However for the daily (i.e. 24 h) energy balance, QF was 46% of Q* in January and February, 12% and 9% for March and April and then dropped to ca. 5% through May and June. These data are from a mid-latitude city with a temperate climate, in more extreme climates QF will be an important energy source.
TABLE IV ANNUAL AVERAGE NET RADIATION AND ANTHROPOGENIC HEAT FLUX DENSITIES
City (latitude)
Studied years
Per capita energy use (GJ year-1)
Per capita energy use (W)
QF (w m-2)
Q* (w m-2)
QF/Q*
Fairbanks (64~ Moscow (56~ West Berlin (52~ Vancouver (49~ Budapest (47~ Montreal (45 ~ Manhattan (40~ Los Angeles (34~ Hong Kong (22~
1967-1975 1970 1967 1970 1970 1961 1967 1965-1970 1971
314 530 67 112 118 221 169 331 28
9,957 16,806 2,125 3,551 3,742 7,008 5,359 10,496 888
6 127 21 19 43 99 159 21 33
18 42 57 57 46 52 93 108 110
0.33 3.02 0.37 0.33 1 1.9 1.71 0.19 0.19
From OKE (1988).
491
Urban climates Given these sizes of QF, it is interesting to note the modelling results from SWAID and HOFFMAN (1990). Adding a daily mean anthropogenic heat flux of 54 W m -2 into an urban cluster with an aspect ratio of 0.5 created a diurnal air temperature increase of 1-2.5~ The maximum increase occurred at 2000 h, the minimum at 0600 h, and the daily average temperature excess was 1.8~ It is important to note, however, that these temperature increases are modelled values with no allowance for the site of energy release. An increased storage of sensible heat in the urban fabric and canopy air volume (AQs) is often cited as a means by which urban climates are modified. Such assertions are based on the belief that urban construction materials have a higher thermal conductivity and specific heat than natural surfaces. Oke suggests that the thermal admittance (Ps) is a more appropriate property for comparison as it combines both the specific heat and conductivity terms. The thermal admittance is defined as (ksCs)~ where ks is the thermal conductivity and Cs is the volumetric heat capacity of the material of interest. It is a measure of the temperature change resulting from some change in heat flux across the surface (OKE, 1987). In fact, as OKE (1987) points out, thermal admittance is a surface property; surfaces with a low /t s will show a large surface temperature change for a given heat flux across that surface. Typical/t s values fail to show a trend towards larger values among urban materials. However such comparisons neglect the role of the three-dimensional active surface and hollow buildings that feature in urban land use. DABBERDT and DAVIS (1978) and CARLSON et al. (1981) attempted to evaluate the thermal admittance at a landscape scale using satellite imagery. CARLSON et al. failed to identify any obvious urban-rural differences in thermal admittance while DABBERDT and DAVIS found higher values of thermal admittance in wooded sites, not urban areas. These landscape thermal admittance estimates may be biased because the satellite mainly "sees" rooftops which have characteristically low values of/t s (GOWARD, 1981). Landscape estimates of/~s compiled by OKE (1988) are: 800-1700 (suburban); 1200-2100 (urban); 1600 (farmland); 1600-3000 (mixed woods, swamp and farm) J m -2 S1/2 C -1. Urban heat storage fluxes can be derived as the residual in equation (2), if all other components of the energy balance are measured. Clearly there are limitations to this approach because all errors arising from measurement techniques, or from neglecting advective, photosynthetic and anthropogenic fluxes, are accumulated into the heat storage term. Table V illustrates typical magnitudes of AQs, in proportion to net radiation. All heat storage fluxes fall between 20 and 30% of net radiation (daytime fluxes only), with the exception of Mexico City (Mexico) and Tucson (USA). This ratio is larger than in rural areas (Table V), confirming the important role that this heat storage term must have in urban energy balances. Nocturnal values of AQs often balance the all-wave net radiation (NUNEZ and OKE, 1977). Nonetheless, most of the estimates for heat storage are based on models or are derived as residuals in equation (2). Accurate values of this term are still needed. Table V summarises the main features of urban energy balance partitioning and the Bowen ratio (fl = QH/QE) from published measurements. Although urban Bowen ratios are larger than in well watered, rural landscapes, they are not as extreme as many early studies assumed. In winter, when moisture is freely available, the Bowen ratio is less than unity but, in general, net radiation is preferentially channelled into sensible heat forms (AQs and QH). About 40% of the net radiation is partitioned into QH, with the following exceptions: Oke and McCaughey's anomalous results; urban (as opposed to suburban) land use; Tucson
492
Urban climate processes TABLE V TYPICAL ENERGY FLUX PARTITIONINGIN SUBURBANLANDUSE
Location/season
fl
AQs/Q* QE/Q* QH/Q*
H/W
Adelaideg: March Vancouver Summer Summer Spring (March, April, May) Summer (June only) Winter (January, February) St. Louis: Summerd Tucson: Summer Mexico City: end of dry season Sacramento: Summer Typical urban: Summer Typical suburb.: Summer Rural Wet Dry Ideal
2.5
N/A
N/A
N/A
10-15 m b N/A
COPPIN (1979)
0.16 1.28 c
0.23 f 0.22 f
0.67 0.34
0.11 0.44
0.34 0.34
64 a 64 a
OKE and MCCAUGHEY (1983) CLEUGH and OKE (I 986)
1.14
0.27 f
0.34
0.39
0.34
64 a
GRIMMOND (1992)
1.4
0.29 f
0.30
0.42
0.34
64 a
GRIMMOND (1992)
0.8 2.12 1.13 1.12
0.19 f 0.24 0.52 0.36
0.45 0.24 0.22 0.30
0.36 0.52 0.26 0.34
0.34 2stories b 5.8 mb 0.51
64 a 10 N/A 21 a
GRIMMOND (1992)
CHING et al., pers. commun. GRIMMOND and OrE (1990) OrE et al. (1992)
1.39 1.5 1
0.26 0.27 0.22
0.31 0.29 0.39
0.43 0.44 0.39
1 storeyb N/Ap N/Ap
N/A 15a 50 a
GRIMMONDet al. (1993) OrE (1988) OrE (1988)
22.23 0.46
0.07 e 0.12 e 0.04 e
0.63 0.04 0.66
0.11 0.80 0.30
0.05 b 0.5 b 0.15 b
N/Ap N/Ap N/Ap
GRIMMONDet al. (1993) GRIMMONDet al. (1993) CLEUGH and OrE (1986)
% gs
Author
Key: unless stated, all values are for suburban land use; the averaging period varies from several days to continuous monthly data; all values are daytime only. gs, greenspace; N/A: not available; N/Ap: not appropriate. aUsing plan area only; bbuilding height only, spacing not given; Clatent heat fluxes are estimated as a residual; ddata from St. Louis study are from 1000 to 1300 h only, obtained over 4 days; eat rural sites this is QG/Q* and is measured; fAQs is modelled, otherwise it is computed as a residual; gAdelaide study reported daily data only.
and Mexico City. The latter two cities are located at lower latitudes (subtropical and tropical) than any other city in Table V. Sensible heat fluxes are low and more energy is partitioned into latent heat and heat storage fluxes in these two cities. Fig. 7 illustrates the essential differences in partitioning between a suburban and an "ideal" site located respectively within and near to a mid-latitude city in summer. The sensible heat fluxes are the dominant diurnal energy sinks in the urban environment, Qn is a sink even after sunset and sometimes throughout the evening. The storage component is an energy source in the late afternoon and through the evening. This suggests that the sensible heat flux must be an important component in maintaining elevated air temperatures in the early evening in urban areas. QH has an asymmetric diurnal path, it peaks in the afternoon and remains positive until ca. 2000 h. Such behaviour was also observed by CHING et al. (1983) who noted that the late peak in QH is a feature which becomes magnified with increasing urbanisation. The results from Mexico City (ORE et al., 1992) are the first measured in a tropical city and illustrate some surprising features, such as the low Bowen ratio (the suburb had only 21% greenspace, Table V) which is smaller than for suburbs in mid-latitude cities where there is 64% greenspace. The latent heat flux appears to be maintained at the expense of Qn. The preferential channelling of energy into heat storage (AQs) possibly arises from the high
493
Urban climates
&'~ 100 I" "~ 'F E
,,,
A QSs-r
0
O
sss"""".~_~
sS
50 I-
= (t)
~-.
. . . . . . . . . . .
I
,/~~~,,
. . . .
.t
)
....
"
N
-I
"
|
-I
~-\ \
,.
E:~
I
Q
/%~ ~ H s - r
%**
/ -"
Es-r
-150 I 0
~
~
04
J
J
.'"
08
12
~
16
20
~
24
Local solar time
Fig. 7. Measured differences between suburban and rural energy balance components (from CLEUGH and OKE, 1986). S, suburban; r, rural. building density and high occurrence of concrete rooftops which intercept large amounts of solar radiation at this tropical latitude (ca. 19~ In general urban latent heat fluxes are smaller than their rural counterparts, in proportion to the reduction in vegetation. However, even in drought conditions QE can still act as an important energy sink, by day, in suburban areas. These non-trivial latent heat fluxes are maintained by external water use (irrigation of gardens, lawns and parks). Considerable dayto-day variability in fl is also a common feature in suburban land use (e.g. KALANDA et al., 1980; OKE and MCCAUGHEY, 1983; CLEUGH and OKE, 1986; GRIMMOND et al., 1993). Some of this arises from variations in rainfall and irrigation and hence surface moisture availability (GRIMMOND and OKE, 1986). OKE and MCCAUGHEY (1983) suggested that variability in fl could be related to differences in incoming radiation, however neither of these factors provides a complete account. CLEUGHand OKE (1986) noted that such temporal variability was absent at their "control" site and argued that the turbulent flux partitioning is also linked to changes in the saturation deficit (i.e. dryness) of the overlying UBL. This is enabled by the roughness of the urban surface which enhances turbulent mixing and thus strong "coupling" between the UBL and surface fluxes. Aerodynamically rough surfaces, such as forest canopies and cities, are better coupled to the UBL because turbulence is enhanced. CLEUGH and OKE (1986) and GRIMMOND et al. (1993) suggest that this coupling enables synoptic control on turbulent flux partitioning which could explain their observed day-to-day variability of ft. Smoother surfaces, such as pasture in flat terrain, are not so well coupled to the PBL so surface turbulent fluxes are primarily determined by moisture supply and available energy (i.e. the net radiation minus the heat storage). Airflow
Modified surface heating and increased friction lead to perturbations in the mean wind velocity vectors and the turbulence within the UCL and UBL. This section describes the perturbations to mean flow in the UCL and UBL first, followed by a brief overview of changes in turbulence. The mean wind and its turbulent structure influence the sizes of the turbulent fluxes and the diffusion and dispersion of atmospheric pollutants released into the UBL. Within the UCL, the presence of buildings dominates the pattern of flow. The nature of airflow around individual buildings has been well documented in the literature (e.g. MERONEY, 1982). The introduction of sharp-edged and inflexible buildings into a moving airstream decreases the velocity of the approach flow. The streamlines are displaced and converge above
494
Urban climate processes
a
Isolated roughness flow
b Wake interference flow
r
Skimming flow
IOl lOF Fig. 8. Hypothesised effects of building spacing on airflow. The airflow is from left to right across the page and the urban canyons are assumed to be infinitely long in the cross wind direction (after Ord~, 1987). the building, yielding a jet of high velocity air above and a recirculating eddy located to the lee of the building. Airflow approaching from other wind directions will complicate this basic flow regime. The effect of an agglomeration of buildings will depend on their orientation and spacing. In the UCL, the important scaling variables for flow are thus the aspect ratio, the ratio of canyon length to height and building orientation to the airflow. The overall morphology of the city, in terms of the building height, length and spacing, determines the airflow patterns in the UCL plus its effectiveness as a momentum sink. These also affect the interaction between the UCL and the UBL and the microclimate within the UCL which is where people live and breathe. Fig. 8 depicts the types of flow and, by extrapolation, the microclimate which could be expected for a variety of building densities where the approach flow is oriented normal to the long axis of the urban canyon. The circulating vortex within the urban canyon exchanges scalars from within the canyon to the atmosphere above. Its strength depends on the speed and direction of the approach flow and the aspect ratio of the urban canyon. Note that airflow oriented along canyons is usually accelerated, with frictional slowing and uplift at the canyon walls. There are three mechanisms which alter mesoscale airflow in the UBL (AUER, 1981). Firstly, the changed density and characteristics of the roughness elements alter the friction of the urban surface and its effectiveness as a momentum sink. These surface modifications lead to, secondly, variations in the vertical transport of momentum via thermal and mechanical mixing. Lastly, the altered thermal state of the UBL leads to pressure and stability changes. Which of these effects dominates depends on the regional flow regime, atmospheric stability and the scale of interest. Calm conditions and/or increased distance from the aerodynamically-rough urban surface favour the influence of buoyancy, free convection and thus thermal effects. Closer proximity to the rough urban surface and/or stronger airflow allow frictional influences to dominate. When winds are light, the urban heat island produces a low pressure area at ground level and hence convergent flow (SHREFFLER, 1979). This is accompanied by uplift in the UBL 495
Urban climates
and hence subsiding and diverging air at the urban periphery. This uplift combines with enhanced vertical velocities (see below) from the increased turbulent activity and results in the UBL "doming-up", e.g. SHEA and AUER (1978) observe the UBL to be 300 m deeper over downtown St. Louis. This pattern of convergence and uplift tends to be stronger during the day, when the UBL is unstable and QH is large. The pattern of convergence also creates the potential for acceleration and turning of near-surface winds. In winds of moderate strength (>5 m s-l), thermal effects are overwhelmed by friction effects: large downward momentum fluxes, flow deceleration and uplift result (BRYANT et al., 1978). This is consistent with the barrier effect, following an abrupt change in surface roughness in the absence of a thermal influence. The uplifted airmass can form a "plume" of ascending air which will be advected downwind. In the lee of the city, another change in roughness is experienced by the airflow (rough to smooth) sometimes resulting in descending, diverging air and enhanced momentum transfer. Sometimes a local windspeed maximum at ground level is found, as a result of this greater downward transport of horizontal momentum. A decrease in horizontal wind velocities at any height in the UBL is accompanied by an increase in Zg, the altitude at which the geostrophic wind speed is reached. The urban-induced deceleration perturbs the balance between the pressure gradient forces and the Coriolis force leading to cyclonic turning of the flow (BORNSTEIN and JOHNSTON, 1977; BRYANT et al., 1978). This feature was observed by ANGELL et al. (1973) over Oklahoma City, where tetroon balloons turned cyclonically upon entering the built-up area of the city, then turned anticyclonically in the lee of the urban area. An extensive study of turbulence in the urban surface layer was conducted by CLARKE et al. (1982). Turbulent intensities exceeded rural values by 50% as a result of the frictiongenerated shear stress at the rough urban canopy/air interface and the effects of buoyancy. Increased shear stresses over the urban land use were observed both during the day and extending into the night. The instability of the nocturnal UBL maintains turbulent exchange of momentum between the UCL and UBL. Other studies report similar enhancement of turbulent intensities in the UBL plus increased momentum fluxes and friction velocities (e.g. BOWNE and BALL, 1977; HOGSTROM et al., 1982; STEYN 1980, 1982; HILDEBRAND and ACKERMAN, 1984; YERSEL and GOBLE, 1986; ROTH et al., 1989a; ROTH and OKE, 1993). A recent analysis of surface layer turbulence structure by ROTH and OKE (1993) and ROTH (1993) are among the most complete and include the first published urban moisture spectra. Their turbulent wind results reveal many of the features discussed above. The vertical wind speed (w) spectra peak was shifted to lower frequencies, in agreement with other turbulent studies (CLARKE et al., 1982; HOGSTROM et al., 1982; STEYN, 1982). The shape of the ucomponent spectrum showed the influence of building wakes with the peak energy being at higher frequencies (smaller spatial scales) with a relatively faster roll-off. The co-spectra of w'T' and u'w' (e.g. COPPIN, 1979) and the turbulent velocity statistics all conform to MOST
(Monin Obukhov Similarity Theory), in agreement with other studies. The turbulent moisture spectra showed influences from larger scale structures, in particular surface evaporation appeared to be driven by downdrafts of dry air. These findings suggest non-similarity between heat and moisture transport processes. Many of these basic effects on turbulence are propagated into the convectively dominated UBL. GODOWITCH (1986) found that vertical velocities were larger in the UBL compared to
496
Current and future urban climates a rural boundary layer and variances in urban vertical velocities were 50% greater than their rural counterpart. The UBL was characterised by a greater production of vertical turbulent energy across a wide frequency range with the dominant length scales of the updrafts and downdrafts being comparable to the depth of the UBL. All these observations also suggest that the UBL obeys convective similarity scaling. In summary, this overview of urban airflow and energy exchange processes reveals that the combination of an aerodynamically rough surface, the juxtaposition of wet and dry surface elements within the UCL, and an increased active surface area, yields an environment that has the potential for large heat or moisture fluxes. If the urban canopy is wet, then large evaporation rates can prevail, even larger than in well-watered rural environments. Under dry conditions, however, most net radiation is channelled into turbulent or stored sensible heat fluxes. The division into "wet" and "dry" surfaces is linked to anthropogenic control of surface watering, hence sizeable latent heat fluxes can be maintained long after rainfall has ceased. Large turbulent sensible heat and momentum fluxes lead to large vertical velocities and turbulent intensities throughout the UBL. By day, this can lead to enhanced entrainment from the stable atmosphere aloft, which can increase the thermal anomaly in the UBL (see below). Surface turbulent fluxes are therefore strongly influenced by mesoscale advective effects through coupling between the UCL and the UBL. The partitioning of net radiation into sensible heat depends also on canyon geometry, canyon construction materials and solar angle. Limited evidence from tropical energy balance studies suggests that high solar elevation angles may enhance AQ s.
Current and future urban climates In this section we address the way that these fundamental atmospheric processes lead to characteristic urban climates. The focus is deliberately at the local (viz. land use) and UBL (viz. meso-) spatial scale and the diurnal to annual temporal scale. The climate elements include temperature, humidity, rainfall and severe weather. Wind is also an important "climate" variable, but urban effects on airflow were covered in the previous section.
Temperature Temperature anomalies associated with urban areas have long been recognised. Luke Howard first observed elevated air temperatures in cities in 1833. The existence of this "urban heat island" has now been well documented in human settlements ranging from villages to megacities and in geographical locations from the high latitudes (Fairbanks, USA) to the tropics (including, among many others, cities in Nigeria, Mexico, India and Malaysia). Urban thermal anomalies have been observed both during short-term, intensive measurement campaigns (e.g. OKE and EAST, 1971) and in longer term climatological studies (e.g. CAYAN and DOUGLAS, 1984; ACKERMAN, 1985, 1987; BALLING and BRAZEL, 1987a; FENG and
PETZOLD, 1988; KARL et al., 1988; CHOW, 1992). Many of these longer term studies (e.g. CAYAN and DOUGLAS, 1984; KARL et al, 1988) report a decrease in daily maximum tem497
Urban climates peratures in all seasons except winter and increases in daily minimum and mean temperatures as a result of urbanisation. Most urban heat island studies conform to a common methodology: the temperatures are near-surface air temperatures measured in the UCL; the reported heat island strength (ATu_r) refers to urban-rural temperature differences either at a specific time, or in terms of the daily maximum, minimum and mean temperatures. The rural temperatures are measured at a site presumed to be uninfluenced by the nearby city. Intensive studies would involve a mobile temperature survey across the city and out to the rural periphery, and urban heat island strengths would refer to the almost simultaneous difference between urban and rural temperatures. Longer term, climatological studies (such as those mentioned above, e.g. by KARL et al., 1988) may simply use just two sites, one representing rural and one urban, and only use daily or monthly maximum, minimum and mean temperatures. Other studies use just an "urban" site, where such a site may well be located at the nearest airport, raising the question of whether it is urban or rural. For example, BALLING and BRAZEL (1987a) found little evidence of a temperature increase in Tucson (USA) because, they suggest, of the type of land-cover that urban growth is replacing. The so-called "urban" station for this study was in fact a nearby airport, removed from the city of Tucson. The suburban/rural energy balance comparison for Tucson (GRIMMONDand OKE, 1990) indicated that local climate differences should develop between suburban Tucson and its rural periphery. Most studies of the UCL (air temperature) heat island have been conducted in mid-latitude cities with temperate climates. From these, a fairly consistent picture of the UCL heat island has emerged; the reader is referred to Landsberg's text (LANDSBERG,1981) and the review papers by OKE (1982) and OKE (1979a) for details of these studies. The thermal anomaly that exists in the UCL is propagated upwards, leading to a warmer UBL. The UCL heat island is best expressed at night during stagnant synoptic conditions, such as exist with an anticyclone. Thus with light winds and clear skies where radiative cooling is optimal and turbulence is damped, and in flat terrain with minimal mesoscale flows, the spatial and temporal pattern of the UCL heat island would be similar to the hypothetical pattern shown in Fig. 9. Embedded in the general pattern of increasing temperatures from the rural periphery to the urban core are microscale variations associated with differences in land-cover: parks appear as cool "ponds" and commercial districts as warm "islands". Other variations in the temporal and spatial structure of the UCL heat island arise because of heating variations due to topography or the presence of water bodies. Measurements show that the heat island results from differential cooling rates between urban and rural land use, where rural really means well-watered, short vegetation (see below). Most studies agree that the UCL heat island reaches its maximum strength 3-5 h after sunset. Apart from wind speed and cloud cover, heat island strength could be expected to depend on specific features of individual cities, such as their size, density, etc. OKE (1973) used urban population as a surrogate for city size and found a log-linear relationship between population and heat island strength. Subsequent observations from outside North America revealed different log-linear relationships for European, Japanese and tropical cities (Fig. 10) that arise because of differences in building materials, building densities and building heights. Plotting heat island strength versus sky view factor reveals that heat island strength also strongly depends on the urban geometry.
498
Current and future urban climates
(D
E _
A
B -
City core
1
_
I Built-up
I
area
B 1/'"
A ...-"""
v
Built-up
area
Fig. 9. Temperature structure in an urban heat island (after Ord~, 1982). The upper figure shows nearsurface temperatures along transect A-B, while the lower illustrates isotherms of heat island strength. The modelling work by OKE (1981), VOOGT and OKE (1991) and OKE et al. (1991) provides insight into the processes involved in urban heat island development. These studies represent three approaches to simulating urban heat islands: a scale model (OKE, 1981); a model canyon in a real boundary layer (VOOGT and OKE, 1991) and a numerical simulation model (Surface Heat Island Model, SHIM) (JOHNSON et al., 1991; OKE et al., 1991). OKE (1981) showed the role of canyon geometry in determining the UCL heat island by using a scale model of an urban canopy. OKE et al. (1991) used a numerical model (validated by JOHNSON et al., 1991) with various combinations of sky view factor, urban and rural thermal admit-
o 16
o
I
I
~ 14
.~ if) E
~
I
I
NorthAmerican J / ~ o o"" e"/'E~r~ .../~/~ f _ . ~ o o'~
12
c-
-o 10 c-" ~ 8 ~
I
-
-
6
r-
E E ~
4 2 0
9 et
Tropical
9
I
1
I
I
-
9149
I
I
10 100 1000 10000 Urban population ( thousands )
Fig. 10. Relationship between city size and UCL heat island strength (after JAUREGUI, 1986) for North American (closed circles); European (open circles) and tropical (triangles) cities.
499
Urban climates
tances, enhanced downward longwave radiation and anthropogenic heat fluxes to determine which factors are more important for urban heat island development. Their results highlight not only the influence of geometry on urban heat island development, but also the importance of urban thermal admittance, compared to rural, values. They suggest that some of the heat island strengths and temporal patterns observed in arctic and tropical cities can be explained by the contrast in thermal admittance between the surrounding landscape and the city. This is well illustrated by the results of JAUREGUI et al. (1992) where the strength of the urban heat island in Guadalajara (Mexico) had a seasonal dependence on the urban-rural contrast in thermal admittance. These contrasts will be largest in the dry season and smallest in the wet season. These results clearly show that urban thermal anomalies based on urban-rural intercomparisons depend on the nature of the rural surface. Recalling LOWRY (1977), the rural site is a surrogate for the pre-urban landscape. The different interpretations that result when using urban/rural as a surrogate for urban/pre-urban intercomparisons were illustrated by GRIMMOND et al. (1993). Their study compared suburban and rural air temperatures in and around Sacramento (USA), where the farmland surrounding the city is both irrigated and unirrigated. A maximum heat island strength of 4~
was observed in the comparison of the
suburban and irrigated rural site, but the suburban site appeared as a "cold" island by day (i.e. ATu_r was negative) when the unirrigated temperatures were used for "rural". The actual urban climate effect is probably better represented by the suburban-unirrigated comparison. TABLE VI HYPOTHESISED CAUSES OF THE URBANHEAT ISLAND(FROM OKE, 1987)
Feature of urban land use and urban activity
(a) Urban canopy layer heat island Canyon geometry - increased surface area and multiple reflection Air pollution and warmer UBL Canyon geometry - reduced sky view factor Domestic, industrial and traffic heat emissions Urban construction materials - increased thermal admittance Reduction in vegetation and increase in impervious surfaces Canyon geometry - increased aspect ratio and sheltering (b) Urban boundary-layer heat island Chimney and stack releases of heat UCL heat island- increased heat flux from roofs and canopy layer Increased sensible heat flux, effect of heat island and roughness Air pollution- increased aerosol absorption
500
Effect on atmospheric process, leading to a positive thermal anomaly
Increased absorption of shortwave radiation Increased radiative absorption and reemission of longwave radiation Increased longwave radiation from UCL building walls Increased anthropogenic heat source Increased sensible heat storage Reduced latent heat flux Reduced total turbulent heat transport
Anthropogenic heat source Increased sensible heat input from below Increased convective and mechanical turbulence hence entrainment of warm and dry air from above the UBL Increased absorption of shortwave radiation
Current and future urban climates The two "rural" sites yield quite different urban climate anomalies. The factors involved in the genesis of the urban heat island (both at the UCL and UBL scales) are summarised in Table VI, these were initially based on OKE's proposal (1982). As the preceding discussions have shown, many of these hypotheses have since been confirmed. Far fewer studies have been conducted outside of the mid-latitudes, viz. in the tropics or higher latitudes. We expect that urban climate processes will be different outside the midlatitudes because, firstly, the basic climate can be quite different. Seasons are determined primarily on the basis of rainfall, wind direction and cloudiness rather than temperature, hence the seasonal variation in the urban climate will differ from mid-latitude cities. Secondly, some subtropical cities are located in arid landscapes where irrigation of the surrounding lands is frequent (e.g. Phoenix, Sacramento, USA) or the landscape is desert or semi-desert (e.g. Kuwait City, Kuwait; Karachi, Pakistan; Cairo, Egypt). The nature of the urban effect will vary drastically between such locations, especially because of variations in the thermal admittance. In desert areas dust can raise the atmospheric turbidity, and lower K,I, in both rural and urban locations. Thirdly, the solar zenith angle is smaller at tropical latitudes, hence radiation absorption by rooftops becomes important and solar penetration into urban canyons is increased. Finally, artificial heating is not required, however in the wealthier cities or suburbs, artificial cooling demand will be high and anthropogenic heat fluxes potentially large (recall Table IV). Urban climate studies in the tropical latitudes are important because this is the region of future urban expansion. Thermal comfort may already be compromised in many tropical cities where the combination of an already warm and humid climate is exacerbated by excess urban heating. Increased illness and mortality plus excess energy consumption are just two of the potential impacts from the heat island effect in cities whose regional climates already predispose them to be close to the limits of thermal comfort. Unfortunately, the issue of urban climate does not rank particularly highly in many developing, tropical nations where the struggle to provide food, shelter and clean water is of more immediate importance. Nonetheless studies are emerging which describe the urban climate of tropical, urban cities. Some of these are reviewed next. ADEBAYO (1987) compared rural, suburban and urban temperatures in Ibadan (Nigeria), a low latitude, humid city. He found that urbanisation led to increased minimum and mean temperatures, and slightly reduced daytime maximum temperatures. Heat island strengths were larger during the dry season. These results are similar to other tropical locations, including Guadalajara, Delhi, Mexico City, Nairobi and cities in Malaysia. JAUREGUI (1987) compared urban and rural cooling rates for four cities in Mexico (three in inland valleys and one on the coast) using mean monthly temperature data. Although some results were broadly similar to mid-latitude cities, there were some important differences in the urban heat island timing: peak heat island strengths were observed at sunrise or shortly thereafter and cool islands developed in the afternoon. As reported in many studies, maximum heat islands were observed in the dry season. NASRALLAHet al. (1990) reviewed 23 years of annual mean, maximum and minimum temperatures in and around Kuwait City. They found only a "modest" urban heat island; increased minimum temperatures were not confined to sites within Kuwait City and so no significant differences between urban and desert minimum temperatures could be found. Differences in maximum temperatures between subur-
501
Urban climates
ban and desert sites were significant; the authors suggest that this could be the result of a growing urban heat island. In comparison to other arid cities, Kuwait City's heat island is very small. The authors argue that this is a result of the lack of trees; the similarity of thermal properties of construction materials between the city buildings and the desert; lower building heights; and the moderating influence of the Arabian Gulf. These studies show that urban heat islands exist in tropical cities, but they are less pronounced and the timing of the peak heat island strength is altered compared to mid-latitude cities. Heat island strengths and occurrence are greater in the dry season. Changes to surface energy partitioning in urban land use should be reflected in surface temperatures. For this reason, plus the wealth of spatial information provided, several studies (e.g. PRICE, 1979; VUKOVXCH, 1983; ROTH et al., 1989b) have investigated the spatial expression of the urban heat island using surface temperatures measured from satellites. GALLO et al. (1993), for example, found a linear relationship between the normalised difference vegetation index (NDVI) and observed urban-rural minimum air temperature differences for 37 cities in the USA. Satellite-derived temperatures, however, do not always reveal the same spatial and temporal patterns as air temperature surveys. Several common features found in satellite studies were summarised, and confirmed, by ROTH et al. (1989b). They noted, firstly, that heat island intensities were largest by day and smallest by night, almost the reverse of the diurnal cycle of the UCL air temperature heat island. Secondly, the spatial temperature structure was closely linked to the land use patterns (i.e. features such as parks, shopping centres) during the day, but not at night. ROTH et al. found that the warmest urban surfaces (by day) were not in the city core but in areas with large fiat-topped buildings or extensive pavement. Some of these discrepancies may simply be linked to the difference between a radiative surface temperature and near-surface air temperatures where the latter depend on the surface energy balance plus heating and cooling in an air volume. Satellites may also preferentially view horizontal surfaces such as pavements, rooftops and treetops. The amount of the three dimensional active urban surface "viewed" or sampled by a satellite sensor then depends on its view angle and the ratio of active to plan area of the urban landscape being sampled. GOWARD (1981) showed that rooftops have much lower thermal admittance values and thus will show a greater surface temperature amplitude which may explain the satellite thermal patterns. The discrepancy between the UCL air temperature heat island and that viewed from a satellite simply illustrates our limited knowledge of urban processes. But it also means that satellitebased observations of urban climate processes must be interpreted with care.
Humidity Much less is known about urban effects on humidity. Humidity is expected to differ between urban and rural locations because of the following factors: 9
smaller input of vapour as a result of a reduction in vegetation in the UCL and hence smaller transpiration rates (but note that the reduced atmospheric stability at night may allow transpiration and evaporation to continue into the night);
9 9
emissions of water vapour by industry and transport; intercepted water on impervious surfaces may lead to enhanced evaporation following rainfall;
502
Current and future urban climates * 9
anthropogenic control of water application; juxtaposition of wet and dry surfaces means microscale advection can enhance evapo-
ration. Like the thermal anomaly, urban humidity effects need to be separated into the UCL and UBL effects. Cities are often asserted to have lower relative humidities because of the misconception that urban areas are devoid of water. Most measurements of relative humidity in the UCL support these assertions but only because the relative humidity index depends both on atmospheric water vapour content and temperature. In fact, relative humidity is more sensitive to temperature changes than to humidity changes, so lower relative humidities often simply reflect the extra warmth of cities. Studies comparing actual humidity show that cities are often drier than their surroundings but there is a diurnal and seasonal dependence. HAGE'S (1975) study found, in summer, that urban areas were drier than rural by day and more moist by night. Seasonally, HAGE found that the vapour density was always greater in winter. Similar results (see OKE, 1979a) have been reported from other cities, e.g. in Chicago, ACKERMAN (1987) found lower vapour pressures and dew point temperatures in the forenoon and on spring afternoons. Urban-rural humidity differences, like temperatures, were found to be very sensitive to wind speed and cloud cover. For tropical Ibadan, ADEBAYO (1991) observed slightly reduced vapour pressures, especially in the afternoon, based on 2 years of data.
The UBL climate These thermal and moisture anomalies are not restricted to the UCL. The UCL warm, dry "island" extends upwards into the UBL and can be advected downwind. The temperature and humidity in the UBL also result from entrainment, advective influences and the effects of radiative heating and cooling. Measurements conducted in St. Louis in summer daytime conditions also showed a thermal excess and a specific humidity deficit in the UBL temperature profiles (ACKERMAN and MANSELL, 1978; TAPPER, 1990) which were displaced downwind. These thermodynamic anomalies varied inversely with wind speed
(SHEAand
AUER, 1978) and extended to heights of 500-1000 m (AUER, 1981); they also resulted in higher convective condensation levels. The deeper UBL slightly dilutes and reduces the heating impact. These observations were in summertime, anticyclonic conditions. In wintertime, or nocturnally, the UBL can be more moist. The drier UBL is due to both a decreased surface evaporation flux and enhanced entrainment of dry air from the stable inversion layer above the UBL, as demonstrated by HILDEBRAND and ACKERMAN (1984). They found that QH decreased with height in both urban and rural boundary-layers, but urban QH fluxes were always larger. Note that these large fluxes, accompanied by large vertical velocities in the UBL, enhance the entrainment process. Their urban/rural comparison found large rural QE fluxes at the surface which decreased with height in contrast to the large QE flux at the top of the UBL. Evaporation in the UBL thus increases with height and leads to a drying of the UBL.
Precipitation Two of the basic ingredients for raindrop formation; condensation nuclei and strong up-
503
Urban climates
drafts, are prevalent above and downwind of cities. It is therefore no surprise that cities have long been suspected of creating positive rainfall anomalies. CHANGNON (1968) identified the La Porte rainfall anomaly; HARNACK and LANDSBERG (1975) also observed enhanced summer rainfall over Washington, USA; HUFF and CHANGNON (1973) showed anomalies in precipitation and storm conditions for cities with populations greater than 1 million. Furthermore, the results of AYERS et al. (1982) show the potential for urban modification of rainfall. They found that the fluxes of cloud condensation nuclei (CCN) from Australian cities were an order of magnitude greater than the CCN fluxes generated by the continental landmass. The METROMEX study in St. Louis aimed to identify and explain links between summer rainfall anomalies and urbanisation. Summer rainfall was observed to increase from west to east across St. Louis, reaching a maximum northeast of the Mississippi River and the locus of the St. Louis urban heat island. Climate studies showed that although there was a peak in rainfall totals at this location, there was no observed shift in the diurnal pattern of rainfall. The rainfall maximum occurred at the site with the largest incidence of severe weather phenomena such as thunder and lightening. The major finding of the METROMEX project was that a precipitation anomaly arose from altered UBL dynamics that resulted from a range of urban influences, the most important including: 9 modified inputs of latent and sensible heat from the urban surface into the UBL; 9 input of cloud condensation nuclei from urban activities; 9 increased convergence and updrafts throughout the UBL due to perturbations in momentum and heat exchange across the city; 9 enhanced moisture input from industrial sources (BRAHAM, 1981, cited in CHANGNON, 1991). These combined influences enable cumulus clouds to grow taller and shift the droplet size spectrum to smaller median droplet diameters. The input of giant nuclei from industry, plus stronger updrafts, enhance the collisioncoalescence process with a resulting increase in rainfall. Nocturnal rainfall increases in St. Louis (CHANGNONand HUFF, 1986) were linked to urban influences on already heavy rainfall events. There are other studies that report the existence of "rain islands" in association with urban areas, including several from tropical cities. BALLING and BRAZEL (1987b) observed both increased rainfall amounts from, and frequency of, late afternoon and early evening storms in Phoenix (USA). They suggest rainfall anomalies may be linked to the urban heat island whose existence in Phoenix is well documented. However the failure to find any statistical significance in these observed differences highlights the difficulties in ascribing anomalies in rainfall occurrence and amount to an urban influence. Nonetheless, there is agreement that in some cities, positive rainfall anomalies exist. ELSOM and MEADEN (1982) examined the distribution of tornadoes in the Greater London district in the period 1830-1980 and found that the inner city shows a much smaller occurrence of tornadoes. They argue that the increased roughness of cities and excess heating combine to either dissipate weak tornadoes or suppress their formation altogether. They believe that the coincidence of an area of reduced tornado activity with the most densely populated area of London is significant. Similar tornado-free zones have been observed in Chicago and Tokyo (FUJITA, 1973, cited by ELSOM and MEADEN). Increased thunder activity was found over London (ATKINSON, 1969, 1971), St. Louis and other cities (CHANGNON
504
Future urban climates et al., 1977). ELSOM and MEADEN argue that the same factors that lead to enhanced convective precipitation and thunderstorm activity could also lead to a reduction in tornado activity and cite FUJITA's (1973) studies that show urban heating and frictional effects prevent tornadoes from forming. The thermodynamic anomalies in the UBL which influence convective and severe storms also have the potential to modify the passage of fronts. A classic study in New York City (LOOSE and BORNSTEIN, 1977) found that frontal movement was accelerated with a well developed urban heat island and retarded by the city's frictional influence if an urban heat island was absent. A series of observational and modelling studies in Tokyo have revealed that the movement of the seabreeze front through the Central Business District and suburbs is modified. The elevated air temperatures lead to local low pressures over Tokyo's Central Business District. The increase in pressure gradient found between the city core and the outer suburbs prevented the seabreeze from advancing through the city (YOSHIKADO, 1992).
Future urban climates
The previous sections have provided a general picture of urban effects on those atmospheric processes (radiation, heat, mass, momentum exchanges) that determine weather and climate. The urban influence on the atmosphere can extend vertically to the top of the PBL and, by day, can enhance the entrainment of air into the UBL. The regional wind advects this "plume" of warm, dry and polluted air downwind, enabling cities to "export" their atmospheric impacts to neighbouring areas. There is thus an urban "footprint" extending ca. 100 km downwind of a city. This does not include long range transport of atmospheric pollutants (which may extend to many thousands of kilometres). At the local scale, the urban temperature regime is characterised by higher daily minimum temperatures with no consistent change in maximum temperatures, thus daily mean temperatures are also elevated. The local scale climate tends to be warmer and drier, especially at night. There is a slight to medium reduction in the quantity and quality of solar radiation received at the top of the UCL, however these reductions are offset by enhanced longwave radiation. Within the UCL shading and specular radiation will dominate the microscale radiation regime. Wind speeds and directions are modified both within the urban canopy, where perturbed flow around buildings dominates, and in the UBL depending on the regional wind speed. Turbulence, and hence turbulent exchanges, are modified because of the altered thermal and mechanical properties of the urban surface. Cities tend to store more heat within their fabric, and in dry conditions heat is preferentially channelled into sensible rather than latent forms. These climate effects are primarily local to mesoscale in extent. The extra friction and heating generated by the UCL also modifies the occurrence and amount of rainfall, thunder and lightening, tornadoes and frontal movements. These effects may extend to regional scales. What will be the nature of future urban climates? Some have queried whether ongoing urban expansion will begin to modify continental and global scale climates. The total area of land in "urban use" was estimated as 1 million km 2 in 1980, growing at a rate of 2 • 104 km 2 year -1 (OKE, 1980). Thus in 1993 the total land area occupied by cities will be 505
Urban climates (very approximately) only 0.25% of the total surface area of Earth. It seems very unlikely that global-scale climate change could result from the modifications to albedo, roughness and moisture availability as a result of such a small fraction of urban land use. It is instructive here to review our current knowledge of the effect of cities on climates at this larger scale. The search for a greenhouse-induced signal in the near-surface air temperature record for the globe has focused considerable attention on the issue of urban warming and its large scale impacts. The US has the longest and most spatially comprehensive measurement network and so most understanding relates to urbanisation in the US. In 1986 KUKLA et al. analysed the US temperature record from 1941 to 1980 using paired urban/ rural meteorological sites and found that urban stations showed an average temperature increase of order 0.11 ~
Eliminating those station pairs suspected of introducing er-
rors made little difference to this urban warming figure, except for the small subset of stations that had no change in instrument or station location over the data record. These showed a warming trend of 0.34~
This range (i.e. 0.11-0.34~
encom-
passed that found in their survey of other studies of long-term urban warming. KARL and JONES (1989) suggested that the urban warming bias present in the entire US climate record was between 0.1 and 0.4~ in the 84 years from 1901 to 1984; JONES et al. (1989) estimated a similar-sized urban bias for the US which they extrapolated to 0.01-0.1 ~ in 84 years for the global temperature record. These studies show that in the period of rapid urban expansion in the US (1901-1984), urban areas may have warmed by between 1 and 3 ~ been estimated to have yielded a 0.1-0.4~ entire US.
This has
rise in the near surface air temperature for the
JONES et al. (1989) extrapolated their estimates of urban warming for the US to the globe, yielding a 0.01-0.1 ~ warming in 84 years for the global temperature record. This is an order of magnitude less than the observed warming, suggesting that urban impacts on the global temperature are not important. In summary, there is clearly some suggestion that a portion of the increased temperatures observed in the US is attributable to urban warming, however there is no evidence of a similar affect at the global scale. At the local scale, however, urban dwellers in the US have undergone "climate change" of a similar order to that being predicted by current GCMs to result from enhanced greenhouse warming. People living in cities in developed nations probably are exposed to a climate that has elevated minimum and mean temperatures; is potentially less humid; the sunlight they receive may be more diffuse, contain less UV radiation and be less intense; nocturnal temperatures are warmer; and rainfall and storm patterns may be altered. CHANGNON(1992) notes, interestingly, that this climate change has occurred by and large without comment. A social attitude assessment conducted in St. Louis (FARHAR, 1979, cited in CHANGNON, 1992), found that residents in that part of the city shown to have an altered climate were either unaware of the changed climate, or were unconcerned. While urban-induced climate change does not appear to be directly important to urban dwellers, it does affect their lives and environment in many indirect ways. Cities located in cold regions are slightly warmer during winter which saves heating costs at both the personal and environmental level; conversely more energy will be consumed in those cities already located in warm climate regimes. Microclimate effects within the UCL influence the level of pollutants, radiation and turbulent gusts to which pedestrians are exposed. In warm climates the thermal stress resulting from urban heating superimposed on pre-existing heat-wave conditions (which may be
506
Future urban climates
heightened even further due to global warming) can contribute to illness and premature mortality (MATZARAKIS and MAYER, 1991). It is unlikely that there will be any further, sizeable change in the urban climates of cities in developed nations because the period of rapid urbanisation is over. These cities will continue to grow and encroach on the surrounding landscape but they are unlikely to continue increasing their population and, if anything, urban consolidation may slow down this encroachment. There will therefore be some expansion of the urban footprint, but this is unlikely to greatly increase urban climate effects. SEAMAN et al. (1989) simulated the effects on mesoscale airflows of doubling the size of St. Louis. Surprisingly, they found an amelioration of urban effects, namely a reduction in the urban generated convergence and vertical velocities. Future changes in local and meso scale urban climates may arise from efforts to reduce urban sprawl and energy consumption in developed nations. Calls by governing bodies to increase building densities in urban areas through urban consolidation will lead to larger aspect ratios, greater sheltering and reduced SVF in the UCL. Using the relationship developed by OKE (1987), a doubling in H/W ratio from 1 (common for European, Australasian and North American cities, OKE, 1987) to 2 (towards the upper end for some North American cities) leads to a decrease in SVF from ca. 0.5 to 0.3. This would be accompanied by a 3~ increase in the maximum heat island strength. As Fig. 8 illustrates, an increase in aspect ratio may move an urban block or land use zone from a well-ventilated "wake interference flow" landscape to a "skimming flow" landscape. Urban temperatures will be further increased if urban consolidation is accompanied by reductions in greenspace; external water use and pervious surfaces. In cold climates, the resulting warmer temperatures will further reduce heating demand, but urban consolidation will have a real cost in warmer climates, unless other steps are taken to reduce the excess thermal stress. Improved architecture and construction of buildings in cities will enhance passive energy sources and further reduce energy consumption and anthropogenic heating. Reductions in QF potentially mean a reduction in the energy inputs and hence a potential reduction in warming, however these simple considerations ignore the importance of the site and height of the energy release (recall equation (2) and discussion). Future reductions in photochemical smog may arise from improved technology which will increase the receipt of shortwave radiation in those cities where photochemical smog is prevalent. Such increases are more likely, however, in cities such as Shanghai where coal burning is currently the major fuel source. Switching to alternative fuels, likely within the next 20 years, will significantly increase shortwave radiation receipts in such cities. In short, cities in developed nations without a heavy industrial base are unlikely to show any further significant warming at the continental-global scale. As explained in the Introduction, most urban growth will occur in cities in poorer nations, often located in the tropical latitudes. Already, most of the world's megacities are located within either the poor, or rapidly industrialising (e.g. Korea, Thailand), nations. Unlike most developed or industrialised nations, urbanisation is still increasing in many of the poorer nations. A United Nations report in 1989 found that in less developed nations, the urban population has been increasing at a rate of 3.6% per year and this was projected to continue until 2000. By way of comparison, urban populations in the developed world were increasing at or below 1% per year. Urban populations in Asia and Africa were projected to in507
Urban climates
crease by 2.3 billion between 1990 and 2025. To put this in perspective, this is equivalent to the total urban population for the globe in 1990, and represents 82% of the global increase in urban dwellers for the period 1990-2025. Recalling the findings of Karl et al. on the size of the urban warming signal for the US, it is of interest to note that this increase in urban population for Asia alone (1990-2025) is about ten times the increase in urban population in the US from pre-1900 to 1985. Increasing urbanisation in the African and Asian regions is not only concentrated into megacities. The same 1989 United Nations report found that the fastest growing cities (1985-2000) in the less developed nations (and for the globe) were projected to be those with populations less than 7.5 million (in 1985). Small towns will grow into medium-sized towns; middle-sized cities will grow to become megacities. If the urban contribution to the total warming observed in the US from 1901 to 1984 could be generalised (viz. 0.1--0.4~ then these large increases in urban populations and cities have the potential to make a significant contribution to the global temperature. Similarly, if the population-urban heat island relationships developed by KARL et al. (1988) are valid globally, then a large amount of the urban heating will result from this increase in population and size of medium-sized towns. JAUREGUI's (1986) graph of (log) population versus urban heat island strength shows a smaller slope for tropical, compared to mid-latitude, cities (recall Fig. 10). Furthermore KARL and JONES (1989) note that the urban warming apparent in the US record was not evident in the global temperature record. Clearly the observational evidence of global warming due to the urban growth during the 20th century is equivocal. It is thus very difficult to quantify the impact of the enormous increases in urban dwellers and city sizes projected into the 21st century. Regional and local scale climate changes will occur in those regions undergoing large-scale urbanisation. The IPCC (1991) predicted that with doubled CO2, tropical regions will show only small temperature increases but possibly increased rainfall. Urban effects will be superimposed on this backdrop of greenhouse-induced climate change. The projected increases in urban populations discussed above are almost beyond our comprehension, if they are correct then many areas in the Asian and African regions which will have a much different climate than exists today. Many of these changes will be similar to those already experienced by urban dwellers in industrialised and developed nations, and described above. Minimum and mean temperatures could be at least 5~ warmer, using the US data as an example. There will also be some differences: the amount of heating due to the urban heat island may be roughly similar in magnitude, but its strength will depend on the season. Changes in the timing and length of the wet and dry seasons in the tropics will therefore impact on the duration of urban-induced warming. Many cities in the poor and rapidly industrialising nations will have a markedly different radiation climate. Unless alternative fuel technologies are developed rapidly, these cities will experience reductions in the incoming solar radiation; UBL warming may result from radiation absorption or alternatively there will be a large increase in diffuse radiation. Improvements in fuel technology should mean that these cities pass through this "stage" of solar dimming (STANHILLand KALMA,1993) more rapidly than industrialised nations. If current patterns of urban growth in less developed nations prevail, much of the urban land-use will be informal squatter settlements. The effect of this altered land use depends, of course, on the pre-urban land-use. There is insufficient knowledge to quantify the change in energy balance partitioning that would arise from a transition from a
508
References grassland or a forested landscape into a squatter settlement. The results from OKE et al. (1992) would suggest that the convective sensible heat flux is the smallest heat flux in a tropical city energy balance. If so, possibly energy balances will not be altered greatly. The model simulations of SEAMAN et al. (1989) show that rainfall modifications are more likely to occur in those small to medium sized towns that will increase in population and extent. Although these results cannot be generalised, such modifications to rainfall patterns, storms and possible flooding will be of far greater significance. These local scale climate impacts are important, especially in terms of energy consumption, human health and their potential for causing larger scale climate change. Their importance, however, pales in comparison to the likelihood of increased disease and mortality arising from limited air and water quality plus hazards of increased flooding and landslides that will occur in the very poor cities. It can only be concluded that the combined effects of weather and climate changes, possible sea level rise (more than 20% of the world's cities are sited on coasts) and increased climate variability predicted to result from the enhanced greenhouse effect plus urban-induced local climate change and worsening air and water quality will severely limit the quality and sustainability of the urban environment in less developed and poor nations.
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Chapter 14
Future climate surprises TSUNG-HUNG PENG
Introduction
The release of CO 2 and other greenhouse gases to the atmosphere since the industrial revolution two centuries ago has caused a significant increase in the concentration of these gases in the atmosphere. Continuous monitoring of atmospheric CO2 at Mauna Loa Observatory, Hawaii (KEELING et al., 1989) indicates that the concentration of CO2 gas has increased by about 26% over the pre-industrial level. Prediction of the consequences of the build-up of these gases is a major subject of study and debate among scientists. In general, a global warming is expected if the trend of build-up continues. However, because of our lack of basic knowledge regarding the operation of the Earth's atmosphere-hydrosphere-biospherecryosphere system, it is difficult to make a reasonable and useful, detailed prediction. Usually, a large range of uncertainty with respect to possible greenhouse effects is associated with these predictions. In addition, these sophisticated climate model simulations all point to a gradual warming in response to a gradual build-up of greenhouse gases. Can we trust these simulations and feel comfortable with the possibility of coping with the gradual climate change in the next 100 years? We need only to examine how well the climate models incorporate the key interactions of the Earth system into the model structure to find out that, as yet, we do not have these real interactions figured into models, making any predictions questionable. Indeed, the future climate change is uncertain. As pointed out by BROECKER (1987), there may be unpleasant surprises in the greenhouse. Nature herself has conducted large-scale climatic experiments in the past. The climate in the past million years has been characterized by a series of cyclic glaciations (see Chapter 2 by BERGER). The response of the Earth system to these natural experiments is recorded in ocean sediments, peat bogs and polar ice. The results of analyzing the most recent record over the past 100,000 years indicate that the Earth's climate does not respond to forcing in a smooth and gradual way (small change over thousands of years). Instead, it responds with sharp changes (the response time usually is less than a century). For example, results from central Greenland ice cores show large and abrupt climate changes during the late stages of the last glaciation, suggesting that climate is able to reorganize itself rapidly, perhaps within a few decades (DANsGAARD et al., 1993). The warming at the end of the last glaciation was interrupted with a few abrupt returns to glacial climate. The best example is the Younger Dryas event. Based on oxygen isotope data from Greenland ice cores (DANsGAARD et al., 1989; JOHNSEN et al., 1992), the Younger Dryas ended abruptly over a period of about 50 years (ALLEY et al., 1993). If this is correct, the lesson we have learned from the past is that the main responses of the Earth system to greenhouse gas build-up could come in jumps
517
Future climate surprises
whose timing and magnitude are unpredictable. A study by BROECKER and DENTON (1990) indicates that massive reorganizations of the ocean-atmosphere system are key events that link cyclic changes in the Earth's orbit to the advance and retreat of ice sheets. What are the relationships between climate change and the mode of operation for ocean circulation systems? What sorts of surprises might be in store for us if the greenhouse warming is effective in changing the mode of operation of the ocean-atmosphere system? In this chapter, we review lessons learned from the study of climatic changes in the past, the corresponding large-scale reorganization of the mode of operation for the ocean-atmosphere system, and the possible linkage between climate change and ocean circulation. Understanding the mechanism of global ocean circulation is crucial in seeking such linkages. The great ocean conveyor circulation of BROECKER (1991) is reviewed for this purpose. Based on analysis of air bubbles in polar ice cores, the CO2 content in the atmosphere varied significantly with climate changes over the last 100,000 years. We summarize in this chapter the history of atmospheric CO2 variations and review possible causes of atmospheric CO2 variations in relation to the last glacial-to-interglacial climate change.
Changes in climate and ocean circulation in the past
The cyclic climatic changes between warm and cold periods are recorded by oxygen isotope (~180) in foraminifera shells deposited in the deep sea sediments. Fig. 1 shows the marine 6180 record obtained from the benthic foraminifera from a deep sea core raised from the east equatorial Pacific (SHACKLETONet al., 1983). Sharp changes in dl80 128,000 and 12,000 years ago denote the end of the glacial period (Terminations II and I). Slower
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518
Changes in climate and ocean circulation in the past
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Fig. 2. Generalized total change in oxygen isotope (6180) for benthic foraminifera in the deep Pacific Ocean is given in the upper panel. The portion of 6180 signal corresponding to temperature change of deep sea water is shown in the middle panel. The lower panel shows that portion of ~180 change equivalent to ice volume (from BROECKER,1993). changes in between these two terminations represent the cooling of the Earth system until the peak of the last glacial time. The oxygen isotope ratio changes with both ice volume and deep water temperature. The increase in ice volume enriches the heavier oxygen isotope in sea water because the isotope fractionation during the evaporation of sea water preferentially sends the lighter oxygen isotope into the gas phase. This water vapour eventually precipitates from the air as snow and then becomes ice in the high latitude regions. The deep water temperature where benthic foraminifera lived also affects the oxygen isotope composition of carbonate shell, with a general lowering of d180 corresponding to warmer temperature. As shown in Fig. 2, the record given in Fig. 1 can be separated into two records related to these two factors (BROECKER, 1993). The total change in oxygen isotope (Ad180) is shown as a generalized smooth curve in the upper panel. The stratigraphic nomenclature used by quaternary geologists is also shown as marine stages on the top of the figure. The present interglacial (i.e. Holocene) is designated as marine stage 1. The last interval of glaciation is subdivided into three stages (2, 3 and 4). The entire last interglacial is designated as stage 5, which has subsequently been divided into five parts. The warm maxima are stages 5e, 5c and 5a, and the intervening intervals of cooler climate are 5d and 5b. The pe-
519
Future climate surprises nultimate glaciation is designated as stage 6. A sharp decrease in the 6180 value is seen at stages between 6 and 5e, and again between 2 and 1, which represent periods of global warming. The reduction in ice volumes caused by global warming and the corresponding changes in A6180 are shown in the lower panel. This curve is constructed based on the time history of sea level changes (and hence ice volume changes) and the relationship between ice volume and A6180 values. The difference between these two curves represents change in deep water temperature and is shown in the middle panel. A general cooling trend in deep Pacific water is depicted by 6180 increases beginning at stage 5e and ending at stage 2. A total cooling of about 2.5~ is derived from A6180 between stages 2 and 1. However, an estimate of only about 2.0~ is obtained for the period between stages 5e and 5a. So, the remaining 0.5~ of cooling is predicted to take place in between stages 5a and 2. Based on evidence derived from 13C/12C records from high latitude deep sea cores (MIx and FAIRBANKS, 1985) and the record of CaCO2 content for northern Atlantic cores, a sharp change (in the opposite direction) at the stage 4-5 boundary is compatible with sharp glacial to interglacial isotope changes that occurred at terminations II and I. It suggests that a major change in the mode of ocean operation occurred about 75,000 years ago that brought about a temperature cooling of about 0.5~ in deep water. Because the deep water of the world oceans is produced mainly in the northern Atlantic, the change in deep water temperature is consequently controlled to a large extent by the strength of North Atlantic Deep Water (NADW). Based on the distribution of PO4 and O2 in the deep ocean, BROECKER (1991) estimated that about 70% of Pacific and Indian deep waters came from the southern sources related to Antarctic Ocean. Hence, the formation of Weddell Sea Bottom Water (WSBW) in the Antarctic is an important component of deep waters of the world oceans. However, the temperature changes and hence the heat releases required for WSBW formation are not known. It is believed that the temperature changes during the formation of WSBW may be much smaller than the northern Atlantic and hence its effect on climate change is smaller too, because the Antarctic Ocean surrounds an isolated Antarctica continent and there is no known major warm currents with a magnitude similar to the Gulf Stream coming to the Antarctic Ocean. Currently, the deep water produced in the northern Atlantic is about 4~ warmer than that of deep water formed in the Antarctic. This suggests that a weakening of NADW flux would lead to a cooling of all deep ocean water. Based on this reconstruction of the time history for deep Pacific temperature change, the 6180 record suggests that the deep sea warmed by about 2.5~ during terminations II and I, when the strength of NADW formation was at its peak. The intervening cooling between these terminations occurred in two steps: the first, 2.0~ at the close of stage 5e and the second, 0.5~ at the close of stage 5a, when apparently the mode of ocean operation changed so that the formation of NADW was weakened. A wealth of information with regard to the last two major 100,000-year climate cycles is obtained from the Vostok ice core record from Antarctica (BARNOLA et al., 1987; JOUZEL et al., 1987, 1993) and from Greenland ice cores (GRIP, 1993). The air temperature changes reconstructed from hydrogen (6D) and oxygen (6180) isotope data from Vostok ice core, the CO2 and CH 4 gas concentrations in air trapped in the ice, and the dust content of the ice are shown in Figs. 3 and 4. High CO2 and CH 4 contents of air trapped in ice correspond to an interglacial period, whereas high dust content of the air corresponds to a glacial period. Comparison with the oxygen isotope record from deep sea sediments shows that they all
520
Changes in climate and ocean circulation in the past
0 300-'
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100 . . . .
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200 . . . . . . .
ci. 250
200
-2
-4
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7OO .~ 600 r
500 >
400
(3
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Age (kyr 8P)
Fig. 3. Comparison of atmospheric CO 2 and CH 4 variations with temperature changes reconstructed from deuterium and 6180 isotopes measured in Vostok ice core from Antarctica over the last 220,000 years (JOUZEL et al., 1993). The time is in 'extended glaciological time scale' (EGT). The envelope for CO2 and CH4 represents the given measurement accuracy.
0
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50
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Age (kyr sP)
Fig. 4. The variation of dust content in ice with time (EGT) in Vostok ice core (JOUZEL et al., 1993). Comparison with temperature variations shows that the high dust content corresponds to glacial periods.
521
Future climate surprises share a general rhythm of changes. The first-order features indicate that the ice volume of the northern hemisphere, the air temperature in Antarctica, the atmospheric CO2 change, and the CH 4 change proceeded in harmony. Both the ice core and the deep sea sediment record the same climatic cycle that took place in both hemispheres. The key to understanding climate change is the transition from glacial to interglacial (termination), which occurred abruptly. The time history of changes over the last 15,000 years provides most detailed and interesting information on the facts of transition and linkage of climate change to the operation of the ocean-atmosphere system. According to BROECKER (1993), peak glacial conditions prevailed 15,000 years ago, with full glacial values of oxygen isotope ratio and dust content in polar ice. Low values of CO2 and CH 4 content in polar ice bubbles represent full glacial time. The surface waters of the Atlantic off the British Isles were populated by the planktonic foraminifera N. pachyderma (left coiled), now found only in polar waters. The nutrient distribution in the deep sea showed its full glacial pattern. Termination of glacial conditions began rather abruptly about 14,500 years ago when glaciers throughout the world began to retreat, polar temperature began to rise, atmospheric dustiness began to diminish, and CO2 and CH 4 gases in the atmosphere began to rise. In the northern Atlantic region, a major warming event took place abruptly about 12,800 years ago. Then about 11,000 years ago, cold conditions of near full glacial intensity
.-2~C
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TODAY--->-
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-25
s'ao(%~ Fig. 5. Oxygen isotope recorded in the Camp Century Greenland ice core measured by DANSGAARDet al. (1971). The nearly constant temperature is clearly shown after the end of Younger Dryas cold event.
522
Changes in climate and ocean circulation in the past
returned. This is the so-called the Younger Dryas event, which lasted about one millennium. Then, about 10,000 years ago, this cold event came to an abrupt end. After that, full interglacial conditions remained unchanged up to the present. The Younger Dryas cold period is the most pronounced event in the climate record of the northern Atlantic basin. As illustrated in Fig. 5, oxygen isotope measurements for the Camp Century Greenland ice core (DANSGAARD et al., 1971) clearly demonstrate the significant cooling of air temperature. Understanding the cause of the return of the glacial period conditions after the climate cycle had entered into a warm interglacial period could help us predict the future climate change. Fig. 5 also shows that climate in the northern Atlantic region has been extremely quiet since the close of the Younger Dryas event. However, inspection of the 6180 record in the opposite direction back to the glacial period reveals that many Younger Dryas-like events made up most of the climate record. These features are clearly shown in the Dye 3 ice core record from Greenland (Fig. 6). All of these events are characterized by abrupt warming, which produced an di180 increase of 4-5%o, then followed by more gradual coolings, which returned the 6180 to its original value. These events are also depicted by the dust content in ice. Rapid climate changes during the glacial age were the rule rather than the exception. An additional surprise was discovered by STAUFFERet al. (1984), who showed that these events were associated with 50/tatm of atmospheric pCO2 changes. Because the rapid and large CO2 variations could only be brought about by the ocean's biological pump, these Younger Dryas-like events could be closely linked to changes in ocean circulation. There are evidences to show that the flow of warm Atlantic surface water into the Norwegian Sea changes suddenly, involving shifts in sea surface tem-
-
8180 (%0) DUST CONTENT (mg/kg) 38 -36 -34-32 -30 0 I 2 3 I
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Fig. 6. Oxygen isotope and dust content for the Dye 3 Greenland ice core. The depth interval for these records corresponds to the time period between 8,000 and 45,000 years BP (HAMMERet al., 1985). The portion of the ice between 1,860 and 1,890 m deep is enlarged to show oxygen isotope and CO2 content in air bubbles trapped in ice as measured by STAUFFERet al. (1984).
523
Future climate surprises perature of more than 5~ in fewer than 40 years (LEHMAN and KEIGWIN, 1992). BROECKER et al. (1985) suggested that the demise of NADW could be the main cause for the Younger Dryas cold period in the northern Atlantic.
Atmospheric C02 variations in the past Change in atmospheric C O 2 content has a profound positive feedback on climatic change. To understand how the ocean-atmosphere system may respond to the climatic changes and in turn how it causes the atmospheric CO2 concentration to change, we must examine the history of atmospheric CO2 changes and their relationship to climate change, especially at the close of the last glaciation when air temperature began to warm. Understanding of the relationships between climate change and atmospheric CO2 variations will help us predict future climate change resulting from greenhouse warming. The composition of the atmosphere in the ancient past is preserved in air bubbles in the polar ice layer. Since the early 1980s, many polar ice cores have been taken and analysed. BERNER et al. (1980) and DELMAS et al. (1980) reported measurements of the CO2 content in trapped ice bubbles from deep ice cores taken from Camp Century (North Greenland), Byrd Station (West Antarctica), D 10 (East Antarctica) and Dome C (East Antarctica). They concluded that the atmospheric CO2 concentration was substantially lower during the last glaciation than in the Holocene. Following up the new discovery, NEFTEL et al. (1982) used a new dry extraction technique to make further precision measurements of the CO2 concentration in ice bubbles from Camp Century and Byrd Station ice samples. They also made CO2 measurements in ice samples from a colder region (North Central, Greenland) and from a warmer region (Dye 3, Greenland). On the basis of these results, NEFTEL et al. (1982) have estimated the range of atmospheric CO2 variations during the last 40,000 years. They found that the atmospheric CO2 concentration was at its lowest level during the peak of the last glaciation. As the temperature warmed during the postglacial time, the concentration of atmospheric CO2 rose quickly to a relatively constant higher level. Intercalibrating the CO2 measurements in ice bubbles at two laboratories (Bern and Grenoble), BARNOLA et al. (1983) reported that the mean concentration of atmospheric CO2 preserved in the Antarctic ice layer (at Dome C and Byrd Station) for the period 8002,500 years BP was about 260 ppm. The Holocene CO2 level before industrial contamination is considered to be important background information for studying both the global carbon cycle and the sensitivity of climate to increased atmospheric CO2. NEFTEL et al. (1985) reported detailed analysis of an ice core from Siple Station (West Antarctica) that contained air samples from the period between 1734 and 1983 AD. Results of three ice samples overlapping the continuous atmospheric record at Mauna Loa show excellent agreement with CO2 measurements made directly in the atmosphere. Other samples extend back over the past two centuries. NEFTEL et al. (1985) concluded that the atmospheric CO2 concentration before industrial contamination (ca. 1750 AD) was 280 +_5 ppm and that it has increased steadily since then. Results of the analysis of an ice core from station D57 at East Antarctica by RAYNAUD and BARNOLA (1985) indicate that the background CO2 level could have been as low as 260 ppm and suggest that the pre-industrial CO2 concentration was not constant over the few hundred years preceding the 19th century. The ice core taken near the summit
524
Causes of glacial-to-interglacial change in atmospheric C02 320
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TIME (ka BP)
Fig. 7. Calculated band of the atmospheric CO2 concentration based on the analysis of the air trapped in bubbles in a deep ice core from Byrd station in West Antarctica (from NEVrELet al., 1988). of Law Dome in Antarctica also shows an average CO2 concentration of 281 ppm during the 17th and 18th centuries (PEARMAN et al., 1986). For the purpose of investigating the relationship of atmospheric CO2 variations with past climate changes, NEFTEL et al. (1988) used a deep ice core from Byrd Station in West Antarctica to reconstruct the atmospheric CO2 concentration in the time period 50,0005,000 years BP in great detail. As shown in Fig. 7, the transition from glacial to postglacial time (15,000-10,000 years BP) was accompanied by an 80ppm increase in atmospheric CO2 (from 200 to 280ppm). The pre-industrial value of 280ppm was reached at 10,000 years BP. The 40% change in such a short time is certainly significant and is considered to be rapid in comparison with slower changes between 180 and 220 ppm during the glacial period from 15,000 to 50,000 years BP. The observed minimum of 245-255 ppm at ca. 8,000 years B P has been considered real and not the result of artifacts related to the poor quality of the ice core. The lower atmospheric CO2 level during this time may correspond to a cold period in the Holocene.
Causes of glacial-to-interglacial change in atmospheric C02 In their study of the increase in atmospheric C O 2 content from the last glaciation to the Holocene as recorded in the Byrd ice core, NEFTEL et al. (1988) compared the increase with changes in the 6180 record in ice cores covering the same climate transition period. They found that the 6180 started to increase between 200 and 1,200 years before the CO2 concentration started to increase. Based on their calculation, at the time the CO2 began to rise, the 6180 had already risen 20-30% of the total increase at the glacial-interglacial transition. Because the 6180 record is a typical indicator of the climate change, it is therefore unlikely that the atmospheric CO2 had triggered the climatic shift observed in the Byrd ice core. However, NEFTEL et al. (1988) believed that the higher atmospheric CO2 content could have been an important forcing factor in establishing the mild climate of the current interglacial
525
Future climate surprises period. Although we do not have hard evidence to substantiate the fact that lower atmospheric CO2 leads to colder climate and higher CO2 leads to warmer climate, the strong correlation in ice core records between low atmospheric CO2 concentration and cold periods and between high atmospheric CO2 and warm periods suggest that the atmospheric CO2 content must have played an important role in the positive feedback of climate changes. As mentioned in the last section, the increase in atmospheric CO2 content from glacial to interglacial time has been determined to be about 80 ppm (BARNOLA et al., 1987; NEFTEL et al., 1988). The hard question is what caused the glacial to interglacial CO2 change? There are a number of possible explanations, but no one of them by itself can fully explain both CO2 record in ice cores and carbon isotope record preserved in deep sea sediment. The answer must be "We do not yet know". In chapter 12 of this volume, the land-use change has been described as a possible factor affecting climate change. In fact, the amount of carbon residing in living wood and in soil humus at present totalled about four times that in the atmosphere as CO2 (BROECKER and PENG, 1993). Hence, glacial to interglacial changes in the size of the organic carbon reservoir in land biosphere are potential causes for CO2 changes. However, according to the analysis of BROECKER and PENG (1993) based on 13C measurements of benthic and planktonic foraminifera from deep sea sediment, the ocean-atmosphere system had during glacial time 1.4% higher carbon content than interglacial. This is consistent with the fact that most current boreal forests were under the ice sheet during the glacial time. Extra amounts of carbon were transferred from land biosphere to the oceanatmosphere system resulting from massive forest removal. This excess carbon would create a 25 ppm higher glacial atmospheric CO2 content when it is in equilibrium with carbon and carbonate in the ocean. This result is opposite to observations made in ice cores. The ocean contains about 60 times more carbon than the atmosphere. After taking into account the buffer capacity of sea water, the effective amount of carbon in the ocean, which would respond to changes in atmospheric CO2 concentration, is still about six times the amount in the atmosphere (assuming an average buffer factor of 10). Hence, the atmospheric CO2 is controlled to a large extent by the carbon cycle in the ocean. The three most obvious factors that affected the partial pressure of CO2 in ocean waters as global climate changed from glacial to Holocene were temperature, salinity and biological pumping. For each I~ that the surface ocean is warmed, the partial pressure of CO2 is increased by about 4.3%. An increase in the glacial CO2 content of 200 ppm to the interglacial value of 280 ppm would require a 10~ warming. On the basis of the faunal record in deep sea sediments (CLIMAP, 1981) and oxygen isotope ratios from foraminifera (SHACKLETON, 1987; LABEYRIE et al., 1987), the average glacial to interglacial sea surface temperature warming was estimated to be about 2~ In the absence of any other change, a 2~ warming would have introduced a 17 ppm increase in the atmospheric CO2 content (BROECKERand PENG, 1986). Because more fresh water was stored in continental ice caps during glacial time, the sea must have been saltier than it is now. If one assumes a 150-m lowering of sea level, one can estimate the volume of excess continental ice to have been 55 x 106 km 3. Hence, for an ocean volume of 1375 x 106 km 3, the salinity of sea water was about 4% higher during glacial time than it is now. This salinity effect applies to oceanic alkalinity and total CO2 concentration, as well as to concentrations of oceanic major ions (such as Na § and C1-). The salinity decrease at the close of glacial time would have lowered the atmospheric CO2 level
526
Causes of glacial-to-interglacial change in atmospheric C O 2 by about 11 ppm (BROECKER and PENG, 1986). Thus, any salinity-induced C O 2 decrease would cancel out most of the temperature-induced CO2 increase. The biological pump removes surface water CO2 in the form of organic matter (produced by photosynthesis) to the interior, where the organic matter is oxidized and returned to inorganic form. In so doing, the pCO2 in surface waters is less than that in the interior. The efficiency of carbon removal is limited by the nutrient content of surface waters. If all the nutrients were completely extracted from surface waters by photosynthesis, the atmospheric CO2 content would be about 150 ppm. On the other hand, if the ocean were without biology, the atmospheric CO2 would be about 470 ppm. The pre-industrial CO2 content of 280 ppm implies that the nutrients NO 3 and PO 4 were not efficiently utilized in surface waters. The lower CO2 content of 200 ppm in the glacial period could be caused by a more efficient biological pump. In fact, a polar nutrient hypothesis was proposed simultaneously by three research groups (KNOX and MCELROY, 1984; SARMIENTO and TOGGWEILER, 1984;
SIEGENTHALER and WENK, 1984), who showed that the polar seas have an influence on the atmospheric CO2 content far beyond that expected based on their small area. Because warm surface ocean waters are currently free of the nutrients NO 3 and PO 4, the increase in the biological pumping capacity needed to draw down the atmospheric CO2 content could not be attributed to enhanced plant productivity in warm waters. By contrast, because polar surface waters are currently rich in these nutrient constituents, the potential exists for stripping them through enhanced polar biological activity and thereby drawing down the CO2 content of the atmosphere and also the CO2 concentration of the warm surface ocean. Unfortunately, specific predictions made by this hypothesis were not supported by the marine sediment record. For example, the change in PO 4 and NO 3 in polar surface oceans should be recorded in the shells of planktonic foraminifera grown in polar surface waters. BOYLE (1988a,b) found no significant difference between the glacial and the interglacial Cd/Ca ratio in deep sea cores (CO2 and PO 4 are assumed linearly related in the ocean at all times (BOYLE, 1986)) either from the northern Atlantic or from the Antarctic. The polar nutrient hypothesis also predicted an increase in the 13C/12C ratios for polar surface waters during glacial time. Instead, the foraminifera record shows a decrease (LABEYRIE and DUPLESSY, 1985; CHARLES and FAIRBANKS, 1990). Finally, any lowering of atmospheric CO2 content by the biological pumping effect must be accompanied by a significant reduction in 02 in the deep ocean. The absence of anaerobic sediments in the glacial record suggests that the rather large 02 reductions called for by the polar nutrient hypothesis did not occur. On the basis of Cd measurements on benthic foraminifera, BOYLE (1988b) discovered that the maximum nutrient level in the water column shifted from the current shallow depth to a greater depth in the glacial Atlantic. He showed that this downshift, when coupled with a process of returning to a balanced oceanic CaCO 3 budget (i.e. CaCO 3 compensation), would lead to an increase in the alkalinity of the entire ocean. This alkalinity increase would in turn decrease the atmospheric CO2. Under the assumption that the downward shift in the Atlantic nutrients was an ocean wide phenomenon, Boyle's calculation could account for a drop of---40 ppm in atmospheric CO2 content during glacial time. Besides being too small to explain the entire atmospheric CO2 change, the CaCO 3 compensation required by this mechanism has a time constant of several thousand years, making this mechanism too slow to account for the rapidity of the CO2 changes reflected in the Greenland ice core record.
527
Future climate surprises Following Boyle's lead in suggesting that an alkalinity change may have driven the glacial to interglacial change in atmospheric CO2, BROECKER and PENG (1989) proposed a polar alkalinity hypothesis. This hypothesis builds on the basic concept of the polar nutrient hypothesis, namely that the partial pressure of CO2 in polar surface waters, especially in the Antarctic ocean, controls the CO2 partial pressure of both the warm surface ocean and atmosphere. It also requires an increase in the alkalinity of polar surface waters, such as that produced by Boyle's nutrient-deepening hypothesis. Four constraints were obtained for reconstructing the composition of waters in the glacial Antarctic ocean. First, the pCO2 of Antarctic surface waters was 200 ktatm instead of 280 ktatm, according to the ice core data and in line with the fact that Antarctic surface waters dictate the atmospheric CO2 concentration. Second, the NO 3 and PO 4 contents of the Antarctic surface waters remained the same as they are today, according to Boyle's Cd results. Third, in accord with the near constancy of the oceanic lysocline (defined as the depth of ocean at which the rate of CaCO 3 dissolution increases significantly), deep waters in the Antarctic, Pacific and Indian oceans had nearly the same CO32- ion content as they have today. Fourth, in accord with 13C/12C data on benthic forams, the salinity-normalized NCO2 of glacial deep Antarctic water was nearly the same as that in glacial deep Pacific water. The reconstructed composition of glacial Antarctic waters had the salinity-normalized alkalinity of--75 kteq kg -1 higher and the salinity-normalized l~CO2 in deep water of ~ 100 ktmol kg -1 higher than the interglacial time. The alkalinity change is responsible for an 80/tatm change in atmospheric CO2 partial pressure between the glacial time and the Holocene. Unfortunately, this hypothesis also cannot explain the large drop in the dl3C value for the planktonic foraminifera from Antarctic sediments of glacial age. Part of the alkalinity increases that the polar alkalinity hypothesis requires for glacial surface water in the Antarctic could be a natural consequence of the demise of the NADW during glacial time. The cessation of NADW stopped the flow of low-alkalinity deep water into the circumpolar region. Because little CaCO 3 is produced by organisms living in Antarctic surface waters, the alkalinity rise experienced by circumpolar deep water must also have occurred in Antarctic surface water. Coupled with an increase in the degree of utilization of the nutrients brought to the surface by the upwelling in the Antarctic, this alkalinity rise brought about a drop in the pCO2 of surface waters in the Antarctic and hence in the warm surface ocean and atmosphere. What are mechanisms in the ocean-atmosphere system that can cause the turning on and shutting off of the NADW? BROECKER'S (1991) ocean conveyor circulation theory offers some possible answers to this question.
Role of o c e a n c o n v e y o r circulation
The most important feature of the ocean conveyor circulation is the production of deep water in the northern Atlantic. Waters in the vicinity of Iceland are cooled and their density is increased to the point that they sink into the abyss. As shown in Fig. 8, the newly formed deep water, known as NADW, flows southward from Iceland to the tip of Africa with its characteristic property of high salinity, low nutrient content and high 14C/12C ratio. This flow forms the lower limb of the conveyor. In addition, there is the northward flowing wedge of Antarctic Bottom Water (AABW) from southern Atlantic that underrides the
528
Role o f ocean conveyor circulation
Great Ocean Conveyor Belt Sea-to-Air
~2
!
1 Fig. 8. The diagram of the great ocean conveyor (BROECKER,1991).
NADW mass and is mixed upward into NADW, increasing the flow of the lower limb. Southward of 30~
this lower limb joins the rapidly flowing deep Antarctic circumpolar
current, which mixes the NADW exiting the Atlantic with new deep water produced around the Antarctic continent and also with old deep waters recirculated back into the Antarctic from the deep Pacific and Indian oceans. This current is the great mix-master of the world ocean. Some of this lower limb water branches northward into deep Indian and Pacific oceans. The upwelling of these lower branches in the northern Indian and Pacific oceans forms the upper limbs of the conveyor, which returns along the upper ocean through the Indonesian archipelago and around the tip of Africa to the Atlantic Ocean. However, in reality, the upwelling is widely spread, with a large amount taking place in the Antarctic. Hence, there is a significant return flow through the Antarctic via the Drake Passage into the South Atlantic, which is not portrayed in the conveyor diagram shown in Fig. 8. The flux of NADW into the deep Atlantic can be estimated by measuring the radiocarbon in samples of deep water from the Atlantic Ocean. The radiocarbon measurements give the mean residence time of the deep water. The flux is then estimated by dividing the volume of water contained in the deep Atlantic with its mean residence time. Based on radiocarbon measurements made during the GEOSECS programme, corrected for the contribution of radiocarbon made by AABW to the conveyor's lower limb and adjusted for the impact of temporal changes in the laCfiZC ratio for atmospheric CO2, BROECKER (1991) estimated that the current flux of NADW is close to 20 Sv (1 Sv = 1 x 106 m 3 of water per second). This immense magnitude of flux is 20 times the combined flows of all the world's rivers and is even larger than the combined rainfall for the entire globe. BROEcKER (1991) suggested that the conveyor is propelled by the excess salt left behind in the Atlantic as the result of vapour export (BROEcKER et al., 1985). Because of the difference in the circulation patterns, surface waters in the North Atlantic are on average
529
Future climate surprises warmer than those in the North Pacific. As a result, more water is evaporated from the North Atlantic than from the North Pacific and in turn there is a net transport of water vapour through the atmosphere from the Atlantic to the Pacific. Therefore, the North Atlantic water becomes saltier than the North Pacific water. The salinity difference between surface waters in the northern Atlantic and those at comparable latitudes in the Pacific ranges from 2 to 3 g/l. The enrichment of salt in the North Atlantic must somehow be compensated by a flow of salt through the sea from the Atlantic to the Pacific. Formation of NADW by the sinking of dense surface waters as a result of winter cooling of saltier water in the North Atlantic initiates this compensation process. Broecker estimated that the rate of vapour loss from the Atlantic basin is 0.35 _+0.12 Sv. Adopting a 20 Sv NADW outflowing flux and taking the salinity of this lower limb water mass to be ~34.9%o, the combined return flow must have a salinity of-34.3%o (20 • 34.9/20.35). As can be seen, the salinity contrast between seawater (34.9%o) and water vapour (0.0%o) is -60 times that of the waters being traded between the Atlantic and the remainder of the ocean (i.e. 34.9-34.3 or 0.6%o). It is for this reason that only a 0.35 Sv vapour loss can force a mighty 20 Sv deep ocean flow. The important role of conveyor circulation in climate change is the transport of heat from lower latitudes to higher latitudes in the northern Atlantic basin. The warmer surface return flow from lower latitudes has to be cooled and its density has to increase to a point at which it can sink and become the conveyor's lower limb. The amount of heat released into the atmosphere is equal to the product of the conveyor's flux and temperature reductions required for making NADW. The water temperature of the conveyor's upper limb averages -10~ and that of NADW averages -3~
Thus, each cubic centimetre of upper-limb water releases
29.3 Joules to the atmosphere when it becomes the lower-limb deep water. With a 20 Sv deep flow, the formation of NADW gives off 16.7 • 1021 J each year, which is equal to 35% of the heat received from the sun by the Atlantic north of 40~
latitude. This extra heat
is responsible for Europe's exceptionally mild winters. The immediate question is: what would happen if the conveyor ceased to operate? Model simulations (RIND et al., 1986; MANABE and STAUFFER,1988) indicate that a very different temperature distribution pattern would be created and thus a different climate system would result. The temperature of surface waters in the northern Atlantic would become -5~
colder if the conveyor were inop-
erative. One potential threat to the operation of conveyor circulation is the addition of fresh water to the northern Atlantic. Dilution of seawater may potentially weaken the conveyor because of its negative effect on the production of NADW. Continuous dilution of seawater would eventually halt the formation of NADW and, thus, would shut down the conveyor. If this happened, fresh water would pool at the surface of the northern Atlantic and create a severe barrier to deep-water formation. This phenomenon is currently seen in the northern Pacific. Using an oceanic GCM, MAIER-REIMER and MIKOLAJEWICZ (1989) demonstrate that addition of enough excess fresh water to the source region of NADW can kill the model's thermohaline circulation abruptly, on a time scale of about a few decades. BROEcKER (1991) argued that changes in thermohaline circulation in the Atlantic ocean were the main causes for the abrupt and large climatic changes experienced by the northern Atlantic basin during the last glacial period. His conclusion is based on the observation of the oxygen isotope record from Greenland ice cores (DANsGAARD et al., 1971; HAMMER et
530
Future surprises al., 1985), which reflects changes in air temperature. The turning on and off of the conveyor could cause 5-8~ changes in air temperature over Greenland and Europe. As shown in Fig. 6, Greenland air temperature during glacial time varied with magnitude and abruptness expected if the conveyor were to turn on and off on a millennia time scale. BROECKER et al. (1990) show that when the northern end of the Atlantic basin was surrounded by ice sheets during glacial time, stable operation of the Atlantic circulation system was not possible because the ice sheets constitute a tremendous source of fresh water. The heat released during the operation of the conveyor tends to melt the ice, adding a large amount of fresh water to the ocean. In addition, salt is efficiently transported out of this region by the conveyor. Hence, fresh water dilution and salt export reduce the density of waters in the Atlantic. This process continues until the density is too low to produce NADW. Thus, the conveyor stops. Without the conveyor, the salt export and meltwater dilution are reduced to the point at which salt enrichment is once again possible by water vapour export. The increase in salt content leads to a rise in water density, which eventually creates an environment for the generation of NADW and turns on the conveyor. Apparently, this cycle repeats over and over again in glacial time. In contrast, during the nine or ten thousand years after the Younger Dryas cold period, the ever changing glacial conveyor became firmly locked in the 'on' position as demonstrated by nearly constant Greenland air temperature, as shown in the isotope record (Fig. 5). To explain the temperature cycles characterized by abrupt warmings followed by gradual coolings as recorded in the Greenland ice core, BROECKER (1991) offers a salt oscillator hypothesis. The abrupt warmings result from initiation of the conveyor, which runs vigorously at the beginning. The reason for this vigour is that to overcome the freshwater pool present in the northern Atlantic when the conveyor is inoperative, the salinity of the Atlantic water would have to rise above the level required for steady-state operation of the conveyor. Thus, when the conveyor turns on, the buoyancy contrast between deep water produced in the northern Atlantic and that present in the remainder of the world ocean will be extraordinarily large. This excess density will drive the conveyor at an unusually high rate. As a consequence, a greater amount of heat will be released to the atmosphere over the North Atlantic. Hence, the atmosphere warms up abruptly in the beginning. However, once operative, the strength of conveyor will steadily weaken because the combination of dilution with meltwater and export of excess salt by the conveyor will reduce the buoyancy contrast between deep waters inside and outside of the Atlantic. As the strength of the conveyor gradually wanes, the amount of heat given off to the atmosphere over the northern Atlantic also will decrease, causing air temperature to drop accordingly. Eventually the conveyor will shut down and cut off the supply of heat from the ocean. The atmospheric temperature cycle generated in this way resembles that observed in the Greenland ice core record.
Future surprises We have learned from the preceding discussion that the operation of conveyor circulation has played an important role in determining air temperature changes in the northern Atlantic basin. A shutdown of the Atlantic conveyor belt cooled the North Atlantic and its adjacent
531
Future climate surprises lands by 5-8~ This would in turn cause the boreal forest in these areas to give way to tundra shrubs. The sparse vegetation would allow far more dust to be blown into the atmosphere. The atmospheric CO2 partial pressure was about 80/tatm lower than the preindustrial value. All of these changes are recorded in Greenland ice cores. The atmospheric CO2 variations with climate change took place rapidly. The only way we can explain the prompt response of atmospheric CO2 to climate change involves modifications in the intensity and pattern of ocean circulation. One hypothesis, which attempts to reconstruct the glacial ocean carbon chemistry to explain the correlation of atmospheric CO2 increase with global warming after the close of the last glacial period, calls for alkalinity changes accompanying the reorganization of the mode of ocean operation (BROECKER and PENG, 1989). To understand climate change and to be better prepared to predict future changes, attention should focus on climate and oceanography of the northern Atlantic basin. Paleoclimatic evidence indicates that climate in the northern Atlantic region has remained remarkably constant since the transition from cold to warm conditions about 10,000 years ago. Apparently, the climate system has remained firmly locked in its current mode of operation. The critical question is: what is the likelihood that increases in CO2 and other greenhouse gases will shake the ocean-atmosphere system out of its current mode into one which is more suitable to the coming conditions? Unfortunately, 'surprise' is the only answer because nature has not experienced the recent superinterglacial conditions we are about to generate and, hence, does not provide us with any geological record useful for future prediction. However, based on the relationship between vapour transport and conveyor circulation, the coming greenhouse warming would strengthen the thermohaline circulation by increasing the rate of vapour loss from the Atlantic basin. If so, we would expect to remain in the warm period. On the other hand, the greenhouse warming will also increase the transport of fresh water to the northern Atlantic. On a time scale of decades, the salinity dilution created in northern surface waters would be more important than the Atlantic-wide salinity increase caused by increased vapour loss from the whole Atlantic Ocean. On a longer time scale, the increased vapour loss, and hence the increased salinity, would become more important. The reason for the difference in these two time scales is that the replacement time for waters in the northern Atlantic is shorter than that for waters in the upper limb of the conveyor in the Atlantic Ocean. BREWER et al. (1983) found that the salinity of Atlantic deep waters to the north of 50~ decreased between 1972 and 1981. SCHLOSSER et al. (1991) reported that deep ventilation of the Greenland Sea was shut down during the 1980s. These observations point to the fact that changes are taking place. Unfortunately, we do not know whether these changes signal natural fluctuations or anthropogenic interruptions. We must keep in mind that the conveyor circulation is only one of many elements that together constitute the climate system of the Earth. Global climate change in the past cannot be explained solely by the turning-on or turning-off of NADW production. The complex climate system is a result of interactions and linkages between ocean, atmosphere, ice, terrestrial vegetation and soil. We have to begin to formulate means by which these interactions and linkages might be modelled. Until reliable modelling of this complexity is possible, we must consider the possibility that the future climate change resulting from the response of Earth systems to our provocation of the atmosphere would come most likely as abrupt changes whose timing and magnitude are unpredictable- surprises.
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Acknowledgement
Acknowledgement Many thanks to Wally Broecker for his review and valuable suggestions. I also like to thank J. Graham Cogley and an anonymous reviewer for reviewing this manuscript. Research is sponsored by Global Change Research Program, Environmental Sciences Division, Office of Health and Environmental Research, U.S. Department of Energy, under contract DEA C 0 5 - 8 4 O R 2 1 4 0 0 with Martin Marietta Energy Systems, Inc. Publication No. 4149, Environmental Sciences Division, Oak Ridge National Laboratory. Current support is provided by N O A A Atlantic Oceanographic and Meteorogical Laboratories, Miami, Florida.
References ALLEY, R. B., MEESE, D. A., SHUMAN, C. A., GOW, A. J., TAYLOR, K. C., GROOTES, P. M., WHITE, J. W. C., RAM, M., WADDINGTON,E. D., MAYEWSKI, P. A. and ZIELINSKI, G. A., 1993. Abrupt increase in Greenland snow accumulation at the end of the Younger Dryas event. Nature, 362: 527529. BARNOLA, J. M., RAYNAUD,D., KOROTKEVICH,Y. S. and LORIUS, C., 1987. Vostok ice core provides 160,000-year record of atmospheric CO 2. Nature, 329:408-414. BARNOLA, J. M., RAYNAUD, D., NEFTEL, A. and OESCHGER, H., 1983. Comparison of CO2 measurements by two laboratories on air from bubbles in polar ice. Nature, 303:410-413. BERNER, W., OESCHGER, H. and STAUFFER,B., 1980. Information on the CO 2 cycle from ice core studies. Radiocarbon, 22: 227-235. BOYLE, E. A., 1986. Faired carbon isotope and cadmium data from benthic foraminifera: implications for changes in oceanic phosphorus, oceanic circulation, and atmospheric carbon dioxide. Geochim. Cosmochim. Acta, 50: 265-276. BOYLE, E. A., 1988a. Cadmium chemical tracer of deep water paleoceanography. Paleoceanography, 3: 471-489. BOYLE, E. A., 1988b. The role of vertical fractionation in controlling Late Quaternary atmospheric carbon dioxide. J. Geophys. Res., 93: 15701-15714. BREWER, P. G., BROECKER, W. S., JENKINS, W. J., RHINES, F. B., ROOTH, C. G., SWIFT, J. H., TAKAHASHI, T. and WILLIAMS R. T., 1983. A climatic freshening of the deep Atlantic north of 50~ over the past 20 years. Science, 222: 1237-1239. BROECKER, W. S., 1987. Unpleasant surprises in the greenhouse? Nature, 328: 123-126. BROECKER, W. S., 1991. The great ocean conveyor. Oceanography, 4: 79-89. BROECKER, W. S., 1993. The Glacial World According to Wally. A 'Proto' Book, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY 10964. BROECKER, W. S. and DENTON, G. H., 1990. What drives glacial cycles? Sci. Am., 262: 49-56. BROECKER, W. S. and PENG, T.-H., 1986. Carbon cycle: 1985, glacial to interglacial changes in the operation of the global carbon cycle. Radiocarbon, 28: 309-327. BROECKER, W. S. and PENG, T.-H., 1989. The cause of the glacial to interglacial atmospheric CO 2 changes, a polar alkalinity hypothesis. Global Biogeoch. Cycle, 3: 215-239. BROECKER, W. S. and PENG, T.-H., 1993. What caused the glacial to interglacial CO2 change? In: M. HEIMANN (Editor), The Global Carbon Cycle. Springer-Verlag, Berlin, pp. 95-116. BROECKER, W. S., PETEET, D. M. and RIND, D., 1985. Does the ocean-atmosphere system have more than one stable mode of operation? Nature, 315:21-26. BROEcKER, W. S., BOND, G., KLAS, M., BONANI, G. and WOLFI, W., 1990. A salt oscillation in the glacial North Atlantic?-1. The concept. Paleoceanography, 5: 469-477. CHARLES,C. D. and FAIRBANKS,R. G., 1990. Glacial to interglacial changes in the isotopic gradients of southern ocean surface waters. In: U. BLEIL and J. THIEDE (Editors), Geological History of the Polar Oceans. Arctic versus Antarctic. Kluwer, Dordrecht, pp. 519-538. CLIMAP PROJECTMEMBERS, 1981. Seasonal Reconstruction of the Earth's Surface at the Last Glacial Maximum. Geol. Soc. Am., Map and Chart Ser., No. 36. DANSGAARD, W., JOHNSON, S. J., CLAUSEN, H. B. and LANGWAY JR., C. C., 1971. Climatic record
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Future climate surprises revealed by the Camp Century Ice Core. In: K. K. TUREKIAN (Editor), The Late Cenozoic Glacial Ages. Yale University Press, New Haven, CT, pp. 37-56. DANSGAARD, W., WHITEAND, J. W. C. and JOHNSON, S. J., 1989. The abrupt termination of the Younger Dryas climate event. Nature, 339: 532-533. DANSGAARD, W., JOHNSEN, S. J., CLAUSEN, n. B., DAHL-JENSEN, O., GUNDESTRUP,N. S., HAMMER, C. U., HVIDGERG, C. S., STEFFENSEN, J. P., SVEINBJORNSDOTTIR, A. E., JOUSEL, J. and BOND, G., 1993. Evidence for general instability of past climate from a 250-kyr ice-core record. Nature, 364: 218-220. DELMAS, R. J., ASCENCIO, J.-M. and LEGRAND, M., 1980. Polar ice evidence that atmospheric CO 2 20,000 yr BP was 50% of present. Nature, 284: 155-157. GRIP (GREENLANDICE-COREPROJECT) MEMBERS, 1993. Climate instability during the last interglacial period recorded in the GRIP ice core. Nature, 364: 203-207. HAMMER, C. U., CLAUSEN, H. B., DANSGAARD,W., NEFTEL, A., KRISTINSDOTTIR,P. and JOHNSON, E., 1985. Continuous impurity analysis along the Dye 3 deep core. In. C. C. LANGWAY, n. OESCHGER and W. DANSGAARD (Editors), Greenland Ice Core. Geophysics, Geochemistry and the Environment. Am. Geophys. Union, Washington, DC, pp. 90-94. JOHNSEN, S. J., CLAUSEN, H. B., DANSGAARD, W., FUHRER, K., GUNDESTRUP, N., HAMMER, C. U., IVERSEN, P., JOUSEL, J., STAUFFER, B. and STEFFENSEN, J. P., 1992. Irregular glacial interstadials recorded in a new Greenland ice core. Nature, 359:311-313. JOUZEL, J., LORIUS, C., PET1T, J. R., GENTHON,C., BARKOV, N. I., KOTLYAKOV,V. M. and PETROV, V. M., 1987. Vostok ice core: a continuous isotope temperature record over the last climatic cycle (160,000 years). Nature, 329: 403-408. JOUZEL, J., BARKOV, N. I., BARNOLA, J. M., BENDER, M., CHAPPELLAZ,J., GENTHON, C., KOTLYAKOV, V. M., LIPENKOV, V., LORIUS, C., PETIT, J. R., RAYNAUD, D., RAISBECK, G., R1TZ, C., SOWERS, T., STIEVENARD, M., YIOU, F. and YIOU, P., 1993. Extending the Vostok ice-core record of palaeoclimate to the penultimate glacial period. Nature, 364:407-4 12. KEELING, C. D., BACASTOW, R. B., CARTER, A. F., PIPER, S. C., WHORF, T. P., HEIMANN, M., MOOK, W. G. and ROELOFFZEN,H., 1989. A three-dimensional model of atmospheric CO 2 transport based on observed winds. 1. Analysis of observational data. Geophys. Mono. Am. Geophys. Union, Washington, DC, pp. 165-231. KNOX, F. and MCELROY, M., 1984. Changes in atmospheric CO2. influence of marine biota at high latitudes. J. Geophys. Res., 89: 4629-4637. LABEYRIE, L. O. and DUPLESSY, J. C., 1985. Changes in oceanic 13C/12C ratio during the last 140,000 years, high latitude surface water records. Paleogeogr., Paleoclimatol., Paleoecol., 50: 217-240. LABEYRIE, L. D., DUPLESSY, J. C. and BLANC, P. L., 1987. Variations in mode of formation and temperature of oceanic deep waters over the past 125,000 years. Nature, 327: 477-482. LEHMAN, S. J. and KEIGWIN,L. D., 1992. Sudden changes in North Atlantic circulation during the last deglaciation. Nature, 356: 757-762. MAIER-REIMER, E. and MIKOLAJEWICZ, U., 1989. Experiments with an OGCM on the cause of the Younger Dryas. In: A. AYALA-CASTANARES,W. WOOSTER and A. YANEZ-ARANCIBIA (Editors), Oceanography. UNAM Press, Mexico, pp. 87-100. MANABE, S. and STAUFFER, R. J., 1988. Two stable equilibria of a coupled ocean-atmosphere model, J. Climate, l: 841-866. MIX, A. C. and FAIRBANKS, R. G., 1985. North Atlantic surface-ocean control of Pleistocene deepocean circulation. Earth Planet. Sci. Lett., 73: 231-243. NEFFEL, A., OESCHGER, n., SCHWANDER,J., STAUFFER, B. and ZUMBRUNN,R., 1982. Ice core sample measurements give atmospheric CO2 content during the past 40,000 yr. Nature, 295: 220-223. NEFFEL, A., MOOR, E., OESCHGER, n. and STAUFFER, B., 1985. Evidence from polar ice cores for the increase in atmospheric CO 2 in the past two centuries. Nature, 315: 45-47. NEFFEL,A., OESCHGER,n., STAFFELBACH,T. and STAUFFER,B., 1988. CO2 record in the Byrd ice core 50,000-5,000 years BP. Nature, 331:609-611. PEARMAN, G. I., ETHERIDGE, D., DE SILVA, F. and FRASER, P. J., 1986. Evidence of changing concentrations of atmospheric CO2, N20 and CH 4 from air bubbles in Antarctic ice. Nature, 320: 248250. RAYNAUD, O. and BARNOLA, J. M., 1985. An Antarctic ice core reveals atmospheric CO2 variations over the past few centuries. Nature, 315:309-311.
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References RIND, D., PETEET, D., BROECKER,W. S., MCINTYRE, A. and RUDDIMAN,W., 1986. The impact of cold North Atlantic sea surface temperatures on climate. Implications for the Younger Dryas cooling (11-1 Ok). Climatol. Dynam., 1: 3-33. SARMIENTO, J. L. and TOGGWEILER,R., 1984. A new model for the role of the oceans in determining atmospheric pCO 2 . Nature, 308: 621-624. SCHLOSSER, P., BONISCH, G., RHEIN, M. and BAYER, R., 1991. Reduction of deep water formation in the Greenland Sea during the 1980s. Evidence from tracer data. Science, 251:1054-1056. SHACKLETON, N. J., 1987. Oxygen isotopes, ice volume and sea level. Quaternary Sci. Rev., 6: 183190. SHACKLETON,N. J., IMBRIE, J. and HALL, M. A., 1983. Oxygen and carbon isotope record of East Pacific core V19-30: implications for the formation of deep water in the late Pleistocene North Atlantic. Earth Planet. Sci. Lett., 65: 233-244. SIEGENTHALER, U. and WENK, T., 1984. Rapid atmospheric CO 2 variations and ocean circulation. Nature, 308: 624-626. STAUFFER, l . , HOFER, H., OESCHGER, H., SCHWANDER,J. and SIEGENTHALER,U., 1984. Atmospheric CO 2 concentrations during the last glaciation. Ann. Glaciol., 5:160-164.
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Chapter 15
The geophysiology of climate LEE R. KUMP AND JAMES E. LOVELOCK
Introduction
The fossil record provides convincing evidence for the persistence of life for 3.5 billion years of Earth history, a remarkable fact in view of the history of the Earth's physical environment. Consider the implication of the prediction from solar physics, that the luminosity of the Sun has continuously intensified over this interval of time (NEWMAN and ROOD, 1977). As pointed out by SAGAN and MULLEN (1972), an atmosphere like today's would have generated a frozen Earth until about 2 billion years ago. A popular solution to this problem is greater amounts of carbon dioxide in the Earth's early atmosphere (OWENet al., 1979). This presents its own problem, in the sense that a mechanism for removing carbon dioxide from the atmosphere as the Sun increased in luminosity over the aeons is needed; if unregulated, or poorly regulated, large climatic fluctuations would likely have occurred which could have led to uninhabitable conditions. Some argue that a purely abiological mechanism (or one with only indirect biological involvement) involving the geochemical cycle of carbonate and silicate rocks would have incidentally maintained surface conditions within the tolerance limits of organisms (e.g. WALKER et al., 1981). In contrast, LOVELOCK and WHITFIELD (1982) proposed a more active role for the biota in the regulation of long-term climate, pointing out the important role organisms play in mediating the rate of CO2 consumption during terrestrial weathering. Geophysiology, a term first used by LOVELOCK (1986), is the study of the Earth as an intimately coupled system comprised of the biota and the physical world. The field differs from Earth System Science only in that it emphasises the emergent properties of the Earth System, specifically the capacity for self-regulation. Earth scientists and biologists recognise the influence that the environment has on the biota and the influence that the biota have on the environment. Neither clearly dominates the other; the biota apparently do not affect the frequency or size of volcanic eruptions, and thermodynamics cannot prevent the establishment of far-from-equilibrium environments (such as an atmosphere rich in oxygen and with significant quantities of methane) by the biota. This interdependency suggests that feedback loops exist which are capable of some degree of homeostasis. LOVELOCK (1983) used the Daisyworld analogy to emphasise that the operation of such a system is not teleological, but rather a direct consequence of tight system coupling. From a geophysiological perspective, then, we argue that because organisms are typically very sensitive to changes in the environment, in the region of parameter space close to the current state (i.e. the range of surface temperatures, atmospheric compositions, moisture
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The geophysiology of climate supplies, ocean chemistries), that they are likely to be involved to a significant extent in the regulation of those environmental variables, not because they want to be, or necessarily need to be, but because of their innate ability and their sensitivity to the environment. The sensitivity of abiological factors involved in the regulation of the surficial processes to environmental change needs to be better quantified by field observation and modelling before a good comparison can be made to the biological sensitivity. However, it is clear that these processes continue at significant rates both above and below the tolerance limits of most organisms. Thus the relatively monotonous climate record of the last 3.5 billion years (see Chapter 1 by HENDERSON-SELLERS),in which the environment has not strayed beyond these limits, is more likely to be the result of a geophysiological system with influential involvement by the biota, rather than one which was effectively abiological. The aim of this chapter is to provide a geophysiological perspective on climate change, both in Earth history, and in the future. We feel that geophysiology provides unique insights into the problem, and generates questions that otherwise might not be asked. We begin with a description of those parts of the climate system which are likely to involve the biota in the process of regulation. The next section considers the geophysiology of climate in the past (with a focus on the early Earth and the Quaternary Ice Ages). Finally, we speculate about future climates from a geophysiological perspective, drawing upon insights developed in the previous sections.
Climate regulation
As previous chapters in this book have demonstrated, the climate system is extraordinarily complex. Our goal is not to describe the full geophysiology of the climate system, but rather to focus on components of the system which are influenced by the biota. Most fundamental to Earth's climate are those factors which ensure the energy balance of the planet: the greenhouse effect and the albedo. One finds that the biota play important roles in regulating both of these factors. Greenhouse gases and the biota
Gases such as H20, CO 2, 03, CH 4, N20 and the halocarbons have atmospheric abundances affected by the presence of organisms, and are present at concentrations sufficient to influence the planetary heat balance through their absorption of outgoing infrared radiation. CH 4 and N20 have no significant sources other than organisms, and the halocarbons are mostly anthropogenic. Ozone in the unpolluted atmosphere is affected in the stratosphere by the biological production of chlorine and bromine-containing gases and nitrous oxide, and in the troposphere by the emission of terpenes and other hydrocarbons by vegetation (CHATFIELD, 1991). In the long term (hundreds of thousands of years), the partial pressure of CO2 is believed to be determined by the necessity for mass balance between the rates of volcanism, which releases CO2 to the atmosphere, and silicate rock weathering, which consumes CO2 (e.g. WALKER et al., 1981; BERNER et al., 1983). Feedback in this long-term carbon cycle probably resides on the weathering side: weathering rates increase with increasing temperature
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Climate regulation and net precipitation, themselves the result of the enhanced greenhouse effect of increased CO2 partial pressures. The weathering process appears to be significantly mediated by organisms (SCHWARTZMANand VOLK, 1989; BERNER, 1993), suggesting that organisms might be an important part of this long-term regulatory mechanism. On shorter time scales organisms play at least as great a role in the regulation of atmospheric CO2. Changes in marine productivity (Chapter 14 by PENG) and terrestrial biomass (ADAMS et al., 1990) between the glaciated and interglacial states of the Quaternary (from 2 million years ago to the present) probably had a significant effect on atmospheric CO2. And on the scale of human observations it is quite clear that the seasonal oscillations of atmospheric CO2 partial pressures, observed at Mauna Loa (KEELINGet al., 1982) and elsewhere, are due to changes in the balance between primary production and respiration/decay. Water vapour contributes the greatest amount of warming to the gaseous greenhouse (see Chapter 9 by WANG et al.), but the abundance and distribution of water vapour is itself determined by the heat balance of the Earth. The response of the atmospheric water cycle to global warming is complex, and no credible prediction of future climate is possible without an account of the redistribution of water in the environment. Biological systems are known to affect the state and abundance of water in the atmosphere. Over land evapotranspiration affects the water cycle on both local and regional scales. This is perhaps most clearly demonstrated by observation and modelling of the effects of deforestation on the water cycle (see Chapter 12 by HENDERSON-SELLERS). Over the ocean, dimethyl sulphide emission by the biota affects both the number density of cloud condensation nuclei (CHARLSONet al., 1987) and, thus, the distribution and moisture content of clouds (Chapter 10 by ANDREAE). And the oxidation of biogenic methane, together with water vapour transport from the troposphere, represent essentially equivalent, major sources of water vapour in the stratosphere (e.g. WALKER, 1977). The gaseous greenhouse is a property of the geophysiological system, not just part of an inert environment to which organisms merely adapt. Where there is feedback from climate change on the rate of biogenic or biologically mediated removal or production of greenhouse gases, a coupled feedback system exists that inextricably links the evolution of organisms and climate. Climate regulation becomes an emergent property of this system and will tend to seek an equilibrium state that is well within the range of tolerance of the organisms involved. The biota and planetary albedo The Daisyworld model (LOVELOCK,1983; WATSON and LOVELOCK,1983) is the simplest expression of the possibility that albedo regulation may involve the biota in a nonteleological way. Daisyworld is an imaginary planet, similar in many respects to Earth, on which grow only daisies. The daisies have an abundance of nutrients and water. Their ability to spread across the planetary surface depends only on temperature, and the relationship is parabolic, with minimum, optimum, and maximum temperatures for growth. The climate system is correspondingly simple. There are no clouds, and no greenhouse gases. The planetary energy balance is a function only of solar insolation, albedo and surface temperature, and planetary albedo depends only on the areal coverage of the soil (which is grey) by black and white daisies.
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The geophysiology of climate WATSON and LOVELOCK (1983) demonstrated the geophysiology of Daisyworld by applying a continually increasing solar luminosity to the planet (Fig. 1). At first, insolation is insufficient to raise the surface temperature above the lower tolerance limits of the daisies, and their seeds lie dormant. When the temperature reaches this critical value the daisies germinate, and because their petal surfaces are warmer for a given insolation, black daisies spread more rapidly. Thus the albedo of the planet falls, and surface temperatures rise rapidly, approaching, but not reaching, the optimal temperature for black daisy growth. The quasiequilibrium temperature reached is well below the optimal temperature for white daisies because of their higher albedo; they do not have the advantage of elevated tissue temperatures. As solar luminosity continues to increase, however, temperatures actually fall slightly (a good demonstration of homeorrhesis: homeostasis around an evolving set point), because the white daisies begin to spread at the expense of black daisies, and the albedo begins to rise. Eventually white daisies come to dominate the surface of the planet. Further increases in luminosity eventually overwhelm the geophysiological system, daisies go extinct as their temperature tolerance limit is exceeded, and the planetary temperature adjusts to that determined by the albedo of the soil and the planetary energy balance. Are there real-world biotic feedback mechanisms that play a role in albedo regulation? LOVELOCK (1989) discussed several possibilities. One possibility is that mid- to high-
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Solar Luminosity (arbitrary scale) Fig. 1. Response of the Daisyworld model to increasing solar luminosity. Areal extent of dark and light daisies is a function only of their temperatures. Dark daisies are warmer than light daisies for a given surface air temperature because of their relatively low albedo. (a) Fractional coverage of the planetary surface by light and dark daisies. (b) Temperature evolution of the planet in response to increasing luminosity, with biotic feedback and if no daisies were present. After WATSON and
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Geophysiology of paleoclimate latitude coniferous forests influence the regional climate by their dark albedo. It was proposed that the shape of conifer trees had evolved to shed snow readily and this fact, combined with their dark colour, would reduce the albedo of a conifer forest compared with that of an open snow field. Large areas of northern temperate and sub-arctic land masses are densely forested by conifers, and it seems probable that they serve as the dark daisies of the present Earth, warming their surroundings and potentially increasing the productivity of their ecosystem. These ideas were treated quantitatively by BONAN et al. (1992), who used an atmospheric general circulation model to study the importance of boreal forests in regional and global climate. They found that deforestation of the boreal forest and replacement with tundra initiates a positive feedback loop that might prevent the re-establishment of boreal forests. Tundra vegetation is unable to mask the high albedo of snow, so the boreal region cools to temperatures below the lower limit for the forest ecosystem. Albedo modification by terrestrial ecosystems is not limited to high latitudes. In particular, the type of vegetation present in the tropics modifies the regional albedo and thus climate. Tropical grasslands have high albedos relative to tropical rain-forests. Climate simulations of the effects of tropical deforestation have included this effect (see Chapter 12 by HENDERSON-SELLERS). However, as pointed out by LOVELOCK (1989), consideration of these surface albedos alone is misleading. When feedbacks are considered, in particular between evapotranspiration rates and cloudiness, the tropical rain-forests emerge as highalbedo ecosystems (e.g. DICKINSON and KENNEDY, 1992; Chapter 12 by HENDERSONSELLERS) because of the additional cloud albedo they create. In the marine realm, the premier importance of biogenic gases, especially dimethyl sulphide (DMS), in supplying cloud condensation nuclei is well established. The resultant effect on cloud albedo is discussed in Chapter 10 by ANDREAE; theoretically, increased CCN abundance should increase cloud albedo. The geophysiology of DMS is described later in this chapter in our discussion of Quaternary climate regulation. The cooling effect of biogenic DMS emissions is in contrast to the direct effect of phytoplankton on the energy balance of the water column. The opacity of marine and terrestrial waters is often a function of algal density; light penetration is greatest in oligotrophic waters, whereas the productive waters associated with upwelling regions are more opaque due to high concentrations of plant pigments (e.g. HUNTLEY et al., 1987; BRICAUD and STRAMSKI, 1990). MAZUMBER et al. (1990) proposed from experiments and observations in freshwater lakes that the vertical distribution of algal biomass and size influences the degree of light penetration, which in turn can affect the thermal structure of lakes, and through feedback, might contribute to ecosystem homeostasis. SATHYENDRANATHet al. (1991) reported that high abundances of phytoplankton in the surface waters of the Arabian Sea reduce the surface albedo and lead to observable changes in the sea-surface temperature. They noted that phytoplankton growth diminished the cooling that would otherwise have occurred during the upwelling season of early summer, and enhanced the warming during the late summer. The added stability of the thermocline stimulates growth when nutrient concentrations are high, and this then leads to further warming in a positive feedback loop.
Geophysiology of paleoclimate The evolution of life is marked by innovations in the physiological mechanisms organisms
541
The geophysiology of climate use to synthesise and metabolise food, to deal with environmental stresses, to transport themselves to more favourable environs, to avoid being eaten, to develop structural rigidity, etc. and these innovations have in turn affected the environment. The establishment of an oxygen-rich atmosphere some 2 billion years ago (KASTING et al., 1992) is perhaps the most remarkable environmental consequence of a biological innovation, namely oxygenic photosynthesis, but others are nearly as important. The focus here is on one aspect of the environment, climate and its co-evolution with life, a subject well introduced by SCHNEIDER and LONDER (1984). Our approach differs from theirs primarily because, again, we stress climate regulation, a property which emerges from the co-evolution of climate and life. Two intervals of Earth history present interesting examples of climate regulation involving the biota: the Archean/Early Proterozoic (from 3.8 billion years ago to 1.6 billion years ago) and the Quaternary (from 1.6 million years ago to the present).
Archean/Early Proterozoic climate In the Archean, the biota had to deal with two factors: an evolving sun, and enhanced rates of delivery of reducing substances to the Earth surface by volcanoes. LOVELOCK (1989) developed an heuristic, Daisyworld-like model for the Archean to study the response of the biota to these conditions. His model included oxygenic photosynthesisers, aerobic heterotrophs and methanogens. Net photosynthesis was closely matched by decomposition, but as today, a small fraction of the organic matter produced was allowed to leak from this fast recycling system into the sedimentary cycle. This leak (the burial of organic matter in sediments) represented net oxygen production, however for the Archean, the oxygen so produced was overwhelmed by the release of reduced volcanic gases, and virtually no oxygen accumulated in the atmosphere. Parenthetically, although low stratospheric ozone concentrations would not have provided an effective UV screen under these conditions, photochemical decomposition of methane would have generated a hydrocarbon smog that would serve equally well (LOVELOCK, 1989, 1991). Also, hydrogen loss to space would be rapid in an anoxic atmosphere. The amount of water available at the Earth surface today probably owes its existence to the rise of oxygen 2 billion years ago, which effectively shut off this leak of hydrogen to space (LOVELOCK, 1989, 1991). As in Daisyworld, the organisms responded (with parabolic dependence) to a simplified set of environmental variables: temperature, atmospheric oxygen abundance, and the amount of atmospheric CO2. Climate was determined simply from the infrared absorption properties of methane and CO2 and the planetary energy balance, using the Stefan-Boltzmann relationship with a zero-dimension flat Earth. Steady state in the atmosphere was determined by a balance between input of carbon dioxide from volcanoes and of oxygen and methane from organisms, and output due to chemical and photochemical reaction in the atmosphere, and removal of oxygen and carbon dioxide by aerobic respiration and weathering, respectively. The response of the model to increasing solar luminosity (linearly, from 75% of the present value 4.6 billion years ago to today's value) and decreasing volcanic input (linearly, from a factor of three greater at 4.6 billion years ago to the present value) is shown in Fig. 2. The evolution of planetary temperature without biotic feedback is shown as the dashed line in the bottom panel; it increases monotonically in response to the increase in solar luminosity. When biotic feedback is included temperatures are somewhat lower overall, because the bi-
542
Geophysiology of paleoclimate
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Fig. 2. Response of a simplified model of Archean/Early Proterozoic geophysiology to increasing luminosity and decreasing rates of volcanism. (A) Changes in atmospheric composition. (B) Evolution of average surface temperature, with and without biotic feedback. After LOVELOCK(1989). ota are assumed to accelerate rock weathering rates and thus maintain higher rates of CO 2 consumption and lower steady state CO2 values. The climatic effects of this CO2 drawdown are ameliorated somewhat by the high amounts of methane in the Archean and early Proterozoic. According to the model, around 2.3 billion years ago a switch occurred in atmospheric composition; oxygen levels rose rapidly as methane concentrations declined. The trigger for this switch was the reduction in rates of volcanic CO2 degassing. At 2.3 billion years the volcanic supply of reduced gases fell below the rate of oxygen production. The transition to an oxygen-rich atmosphere could have been rapid (a few million years), being solely a function of the magnitude of the imbalance between oxygen production and consumption (e.g. KUMP, 1992). Methane concentrations fell dramatically, in keeping with the result of photochemical models that demonstrate the mutual exclusivity of oxygen and methane (e.g. KASTING et al., 1983). This, together with a fall in carbon dioxide levels induced by enhancements in biologically assisted weathering, caused a global cooling. Interestingly, the early Proterozoic Huronian glacial deposits of Canada are underlain by "reduced" sediments and overlain by "oxidised" sediments. This suggests that the glaciation may somehow have been related to the rise of atmospheric oxygen (WALKER et al., 1983).
543
The geophysiology of climate
Quaternary climates The major contribution of geophysiology to the understanding of Quaternary climates has undoubtedly been the elucidation of the role of dimethyl sulphide (DMS) in climate regulation (CHARLSON et al., 1987; LOVELOCK and KUMP, 1994). In the unpolluted atmosphere, biogenic DMS is the major source of cloud condensation nuclei (CCN; Chapter 10 by ANDREAE). Both terrestrial and marine plants release DMS, but the contribution from marine algae predominates. CHARLSON et al. (1987) introduced the idea (known as the CLAW hypothesis) that marine algal DMS production is linked to climate via a feedback loop that might stabilise climate (Fig. 3a). DMS released to the atmosphere reacts to form both SO2 and methane sulphonate, both of which serve as CCN. As the CCN number density increases cloud albedo also increases, because more, smaller water droplets form (Chapter 10 by ANDREAE). Increased cloud albedo cools the surface, and according to the CLAW hypothesis, this could lead to decreased DMS emission: a negative feedback loop. CLAW em-
global temperature
DMS emission
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Fig. 3. Diagrammatic representation of two hypotheses concerning the role of DMS production in global climate regulation. Arrows with "+" indicate that the response of the component at the arrow's head to the stimulus from the other component is in the same sense (a decrease in component A leads to a decrease in component B), while arrows with "-" indicate that the sense of change is reversed (a decrease in component A leads to an increase in component B). (a) The CLAW hypothesis, presented as a negative feedback loop (CLAW were unsure of the sign of some feedbacks). Shaded boxes are copied into (b). After CHARt.SONet al. (1987). (b) The feedback mechanism proposed by LOVELOCK and KUMP(1994), a positive feedback loop.
544
Geophysiology of paleoclimate phasised that the true sense of this feedback loop remains to be determined. Here, however, only the climate stabilising CLAW hypothesis is considered. Although these relationships may be valid in particular environments, we feel that on a global scale the overall feedback may be positive, except perhaps during the coldest intervals of the Quaternary (LOVELOCK and KUMP, 1994). Where our hypothesis differs from CLAW is in the effect of temperature on DMS emission. The highest productivity regions of the open ocean today are at high latitudes, in the cold-water sphere (NEUMANN and PIERSON, 1966). Here, high productivity is sustained despite cold temperatures, because deep convection transports abundant nutrients to the surface waters (e.g. BERGER et al., 1987). RILEY and CHESTER (1971) found it curious that the optimum temperature for algal growth in the natural habitat is some 5-10~ lower than that in culture. We see this as simply a good example of an ecologically defined optimum temperature which is lower than the physiologically defined temperature (BANNISTER, 1976), a characteristic of ecosystems that operate under a variety of stresses. We thus hypothesise that global cooling associated with the transition to the glaciated state (CLIMAP, 1976) should increase marine productivity, and thus DMS emission, by expanding the areal extent of the cold-water sphere where nutrient supply is high. This mechanism differs from the polar nutrient hypothesis described in Chapter 14 by PENG, because it does not require higher productivity within the cold-water sphere, and thus may be more consistent with geochemical indicators of paleo-productivity (cf. Chapter 14). If cooling does lead to increased DMS emission, a positive feedback loop potentially exists which should tend to amplify the effect of orbital (Milankovitch) forcings on climate (Fig. 3b; Chapter 2 by BERGER). However, the sense (positive or negative) of this loop depends on other assumptions made by CLAW, some of which have since been questioned. SCHWARTZ (1988) argued that if biogenic DMS emission controls cloud albedo in the unpolluted atmosphere, then anthropogenic SO2 emissions should have increased present-day cloud albedos globally (relative to the pre-industrial state) and should have led to differential hemispheric damping of the global warming effect of increased greenhouse gas concentrations. Several weaknesses in Schwartz's arguments were noted (CHARLSONet al., 1989; GAVIN et al., 1989; GHAN et al., 1989; HENDERSON-SELLERS and MCGUFFIE, 1989), most of which focussed on technical issues concerning the anthropogenic effect (see also WIGLEY, 1989), and concluded that the CLAW hypothesis had not been disproved. In general, however, it is important to recognise that if the DMS-cloud albedo feedback loop is part of a geophysiological climate mechanism, then the response to anthropogenic SO2 emission might not be intuitive (cf. ANDERSON and CHARLSON, 1991). Subsequently, FALKOWSKI et al. (1992) have demonstrated that there is a good correlation between chlorophyll concentrations and cloud albedo in the North Atlantic. The ice-core record of high-latitude non-sea-salt (nss) SOa2--aerosol deposition rates potentially contains the information necessary to establish the sense of the relationship between surface temperature and DMS emission rate (Fig. 3). Data from Antarctica (LEGRANDet al., 1988) indicate that nss-SO42- concentrations were greater during glaciations, a trend consistent with our hypothesis (LOVELOCK and KUMP, 1994) but contradictory to CLAW. However, recent observations from Greenland (E. SALTzMANN,personal communication) show no relationship between the temperature and nss-SO42- records. At this stage, then, we see the Antarctic data as a tentative confirmation of our hypothesis, but acknowledge the pos-
545
The geophysiology of climate sibility that subsequent investigations will show the correlation to be hemispheric, rather than global.
Positive feedback and climate regulation The ice-core nss-SO42- records indicate that this part of the Quaternary climate system has been in positive feedback: cooling has been accompanied by increased concentrations of biogenic sulphate aerosols. Many scientists, including those sympathetic to Gaia theory, find it difficult to understand how a system can be self-regulating when it is in positive feedback with respect to the current climate. We argue that it is wrong to conclude that this state of positive feedback is proof of the absence of an active self-regulating system. The sign of the feedback in a geophysiological system regulating temperature depends on the sign of the difference between the system temperature and the optimum temperature for each process. If, for example, the ecologically defined optimum temperature for marine productivity is 8~ the temperature which defines the equatorward boundary of the cold-water sphere (NEUMANN and PIERSON, 1966), then when temperature is less than 8~ an increase in temperature will cause an increase in productivity, and presumably DMS emission. The resulting increase in albedo should cool the planet, thus, the overall feedback loop is negative. However, when the temperature is above optimum an increase in temperature causes a decrease in DMS emission, a positive feedback. We propose that positive feedback is the current state of the climate system, and that it is this state that has predominated during the Quaternary (causing the inverse correlation between temperature and nss-SO42- concentration). However, we have implicitly considered only the zero-dimensional problem. Polar regions of the ocean are below 8~ whereas tropical regions are well above. The planetary response is an ensemble of these regional responses. We argue that, in fact, the fundamental variable is not the globally averaged temperature, but rather the surface area of the cold-water sphere. Our assumption is that this area increases as the planet cools, and this is substantiated by the CLIMAP (1976) interpretations of sea-surface temperature distributions in the glacial and present world. A more thorough analysis is necessary, however, because expansion of sea-ice cover with global cooling will tend to counteract the equatorward shift of the 8~ isotherm. Returning to the issue of whether the presence of positive feedback is inconsistent with the presence of a regulatory mechanism, we suggest that a CO2 regulator is providing negative feedback and climate stability. One immediately wonders how such a claim could be made, given that the ice-core CO2 record (BARNOLAet al., 1987) shows that CO2 levels were lower during the glacials and higher during the interglacials. Clearly cooling has led to CO2 drawdowns, which themselves have furthered the cooling. We maintain that these changes in atmospheric CO2 have been small and rapid enough to occur in the presence of a powerful, but slow to respond, negative feedback loop involving terrestrial weathering. The origin of these CO2 fluctuations has been debated recently in the literature, but there seems to be general agreement that they represent the residual of substantial transfers of carbon between the deep ocean and the terrestrial biomass during deglaciation (Chapter 14 by PENG; ADAMS et al., 1990) and vice versa during the onset of glaciations. Chapter 14 by PENG summarises the argument that changes in the alkalinity and YCO2 of southern hemi-
546
Geophysiology of paleoclimate sphere, polar waters, caused by the cessation of North Atlantic Deep Water formation, led to the CO2 drawdown of glacial intervals. This polar alkalinity hypothesis of BROECKER and PENG (1989) is favoured by PENG (Chapter 13) because it is consistent with more of the geochemical record of oceanic changes during the Quaternary than are the competing hypotheses that invoke changes in marine productivity. Our hypothesis requires globally higher productivity during glacials, due to an expansion of the cold-water sphere. This change is different from those of the polar nutrient hypothesis in that it does not require greater productivity in the region of the current cold-water sphere, but rather an expansion of these high productivity areas. Thus, there need be no change in the Cd/Ca ratio (BOYLE, 1988) or the t~13C (LABEYRIEand DUPLESSY, 1985) of high-latitude surface and deep waters, and the impact on deep-water oxygen contents (Chapter 13 by PENG) would be diffused over a greater area. Given that there is sedimentological and geochemical evidence in support of higher glacial productivities (SHACKLETONet al., 1983; MIX, 1989), our expansion of the cold-water sphere is as consistent with observation as is the polar alkalinity hypothesis. Indeed, the decrease in t~laC in Antarctic surface waters (CHARLES and FAIRBANKS, 1990), problematic to previous productivity-based hypotheses (Chapter 13 by PENG), is in fact predicted by our hypothesis. Surface waters there are suboptimal, so a decrease in temperature should lead to thermal stress and a reduction in productivity.
Negative climate feedback in the carbonate-silicate cycle It is the tenet of most long-term carbon cycling models (e.g. WALKER et al., 1981; BERNER et al., 1983) that atmospheric CO2 levels are determined by the required balance between silicate weathering rates and volcanic CO2 emission (the carbonate/silicate geochemical cycle). Feedback is supplied by the sensitivity of chemical weathering rates to climate change, which responds to changes in atmospheric CO2. The time-scale at which this constraint applies in essentially set by the residence time of carbon in the ocean/atmosphere system with respect to volcanism and silicate-mineral weathering rates. Given that the ocean/atmosphere system contains about 39,600 Gtonnes of carbon, and the rate of volcanism is about 0.07 Gtonnes/year, the response time is about 550,000 years. In other words, the carbonate/silicate geochemical cycle sets the average Quaternary CO2 content, and thus the average ~CO2 and alkalinity of the ocean, but allows for substantial variation in these values in response to Milankovitch time-scale forcing (see Chapter 2 by BERGER). If the carbonate-silicate cycle is providing negative feedback to the climate system during the Quaternary, then the optimum temperature for silicate weathering must be above 15~ (the present, globally averaged temperature). From a purely physico-chemical point of view, there in fact is no optimum temperature; weathering (dissolution) reactions increase exponentially in rate with temperature according to the Arrhenius equation (e.g. LASAGA, 1981). However, there is general agreement that silicate weathering rates are accelerated by the biota (SCHwARTzMANand VOLK, 1989; DREVER and ZOBRIST, 1992; BERNER, 1993) This biotic effect probably has an optimum temperature somewhat below the optimum for plants grown in greenhouses (about 20-25~ BANNISTER, 1976) due to other stresses, especially water and nutrient supply (KUMP and VOLK, 1991). Today there may be regions of the tropics and subtropics that are already supra-optimum (and thus in positive feedback) in terms of this biotic effect. WHITMORE (1990) cautions that the tropical rain-forest may be
547
The geophysiology of climate
assisted
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Temperature (~ Fig. 4. Idealization of the effect of temperature changes on rates of chemical weathering. Solid line: Biologically assisted chemical weathering rate, displaying the characteristic parabolic response of living systems to temperature change. The biota generate high soil pCO2 values and release organic acids to the soil, both of which presumably increase rates of chemical weathering. The biota also play an integral role in the development of soil structure, including its ability to retain water. Dashed line: Weathering rates on an abiotic Earth. The diagram is meant to include both the direct effect of temperature on mineral dissolution rates and the indirect effect of temperature on the intensity of the hydrologic cycle. The magnitude of the biological effect is shown only schematically, but likely ranges from a factor of 10 (BzRNER, 1993) to 1,000 (ScIaWARTZMANNand VOLK, 1989).
metastable; the regional climate changes associated with deforestation (temperature increase, soil moisture decrease) may prevent the re-establishment of the rain-forest ecosystem. Thus the temperature dependency of silicate weathering rates might look something like Fig. 4. Within the range of organism tolerance, biotically enhanced weathering rates are greater than abiotic rates, and the planet is cooled. However, when the system enters positive feedback (above 25~
the regulatory mechanism switches to the abiotic one,
which demands substantially warmer temperatures to sustain a given weathering rate. In the next section we discuss the implications of this hypothesis for considerations of future climates. 548
Geophysiology offuture climates Geophysiology of future climates As in medicine, predictions about the future from geophysiology must be couched in terms of substantial uncertainty. Nevertheless, the physician who has studied the life history of the patient, looking for similar illnesses and reactions in the past, has a basis for making a prognosis. So too does the geophysiologist who has studied the operation of the climate system through Earth history. Perhaps the most important question concerns the consequences of continued and accelerated consumption of fossil fuels and release of CO2 to the atmosphere. HOFFERTand COVEY (1992) have studied the correlation through Earth history between proxy indicators of paleopCO2 and climate, and have concluded that a good correlation exists. Warm climates typically coincide with high pCO2 values. Current estimates are that the amount of carbon dioxide stored in fossil fuels equals about 4200 Gtonnes (IPCC, 1991), or about seven times the pre-industrial atmospheric CO2 content. WALKER and KASTING (1992), using a simple box model of the global carbon cycle, predicted that even with very conservative fossil fuel burning scenarios, the result in all cases will be the same: eventual, complete combustion of the recoverable fossil fuels will lead to an atmospheric CO2 level some six to seven times higher than the pre-industrial value when combustion ceases. The recovery then will take thousands of years. Even after 10,000 years atmospheric pCO2 might be as high as 600 ppm, more than double the pre-industrial level. The onset of the next glacial period may well be delayed, if not altogether prevented. From proxy indicators of ancient CO2 levels (e.g. FREEMAN and HAYES, 1992) it appears that the Earth has not experienced such high levels of atmospheric carbon dioxide (7 • the present level) for 100 million years, a time when the ice-caps were small, if present, globally averaged temperatures were some 10~ greater and sea level was considerably higher (BARRON and WASHINGTON, 1985; Chapter 3 by BARRON). By analogy, the persistence of the fossil fuel CO2 pulse, for time-scales that approach the response time of continental ice sheets, should cause considerable warming and glacial melting. In the transition to this warmer state, sea-ice melting in the North Atlantic might cause temporary shutdowns of North Atlantic Deep Water formation, and thus brief returns to cooler conditions (see Chapter 14 by PENG). Global warming is likely to reduce, at least temporarily, marine algal productivity and thus CCN production, by expanding the warm-water sphere at the expense of the cold-water sphere where vertical mixing is vigorous. This stage will be temporary. Because reduced productivity will lead to reduced sedimentation of the nutrient phosphate with organic matter, this will allow the phosphate content of the oceans to increase. Within a few hundred thousand years, the phosphate content will have risen sufficiently high so that the upwelling flux of phosphate is sufficient to sustain productivities comparable to today, despite lower rates of vertical transport (cf. BROECKERand PENG, 1982). On very long time-scales (tens to hundreds of millions of years) the ineluctable increase in solar luminosity presents the most significant of climate forcings, threatening the existence of life on the planet. For most of Earth history, the increase in solar luminosity has been offset by a regulated decrease in atmospheric CO2 levels, from perhaps 10% 4 billion years ago to the pre-industrial value of 0.028%. During the last glacial period, CO2 levels fell to ! 80 ppm, approaching the region where net photosynthesis by C3 plants is severely limited
549
The geophysiology of climate by CO 2. LOVELOCKand WHITFIELD (1982) calculated that within the next 100 million years,
CO2 levels would have to fall below the compensation point for photosynthesis to maintain an equable climate. CALDEIRA and KASTING (1992) redressed this issue, using more recent CO2-greenhouse effect relationships, and concluded that the biosphere could survive for another billion years before plant growth failed. However, the present temperature of the Earth, 15~ is well below the optimum for plant growth (around 20-25~ It might be argued that there is ample room for warming before the temperatures rise enough to threaten even the contemporary mainstream biota. The capacity of organisms to adapt would suggest that temperatures of even 60~ might not be inconsistent with life. Consider first adaptation. It is true that organisms can adapt to harsh environments. Bacteria live in hot springs at temperatures close to boiling, in saturated salt solutions, and in extremely acidic solutions. Closer examination shows that the ecosystems of these extreme environments are sparse and the price of adaptation has been high in terms of the ability of vigorous growth possessed by the mainstream biota. It could be said that organisms living in harsh environments are rather like the eccentrics within a wealthy society, living a subsidised existence on the benefit of global welfare. A significant evolutionary change would be needed before they could be expected to run the system. The major molecules of organisms, proteins, lipo-protein and lipo-polysaccharide complexes, and nucleic acids, are stable only at temperatures below 50~ The upper temperature limit for even a warm-blooded mammal is below 50~ at 50~ a second degree burn takes only 60~ contact time. Organisms require internal temperatures low enough to permit the survival of significant molecules for days at least. In practice a sustained ambient temperature of 40~ is the upper limit for mainstream life. More important than the temperature and environmental limits of the organisms themselves is the sensitivity of the whole system. We have seen earlier in this chapter that ecological optima are typically different from physiological optima. From this generality it is reasonable to conclude that the climate system operating today, which depends to a large part on the acceleration of chemical weathering rates provided by plants, will fail long before the upper temperature limit for mainstream life is reached. Failure of this system could spell the end for mainstream life if, as we have suggested here, the planet is operating at a cooler global temperature because of the presence of the biota. However, through natural selection, a new mechanism of planetary cooling may evolve to fill the role currently played by C3 plants. Actually, one such mechanism has already evolved, perhaps in response to the decline of atmospheric CO2 levels in the last few tens of millions of years: C4 photosynthesis. C4 plants maintain elevated internal CO2 concentrations and are thus able to continue photosynthesising at very low external CO2 concentrations. The C4 pathway is primarily restricted to grasses today; no algae, bryophytes, ferns, gymnosperms, and few angiosperms utilise it (KREBS, 1978). However, this innovation may become more widely utilised by photosynthesisers in the future (LOVELOCK, 1989). In conclusion, the Earth is approaching a critical point in its climatic and evolutionary history when the mainstream mechanisms for climate regulation will be overcome by external stresses. The climatic oscillations of the Quaternary are viewed from a geophysiological perspective as an indication of this impending failure of the climate system, with positive
550
Acknowledgements feedback in the CO2 and albedo subsystems dominating. The extreme sensitivity of the climate system to weak astronomical forcing should be taken as a warning for the future. Our destruction of the tropical rain-forests, so important to the climate stability of the region and to the diversity of life on the planet (LOVELOCK, 1992), may generate as many surprises for the future as will the injection of mass quantities of carbon dioxide into the atmosphere. Earth history tells us that the planet will survive our tamperings, but it may indeed be a very different world in the future.
Acknowledgements This work was supported by Gaia Charity using funds generously donated by Knut Kloster of the World City Corporation, and to LRK by Shell Research Ltd., UK and the Geologic Record of Global Change Program at the National Science Foundation.
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553
References Index
AAGAARD, K. and CARMACK, E. C., 88, 90, 195, 226, 233 ABRANCHES, M. C., s e e STORETVEDT,K. M. et al. ACEITUNO, P., 220, 233 ACKERMAN, B., 497, 503,509 ACKERMAN, B. and MANSELL,J. W., 503, 509 ACKERMAN, B., s e e HILDEBRAND, P. H. and ACKERMAN, B. ACKERMAN, T. P., s e e TURCO, R. P. et al. ACTA ARCHAEOLOGICA,193,233 ADAMS, J. M., FAURE, H., FAURE-DENARD, L., MCGLADE, J. M. and WOODWARD, F. I., 539, 546, 551 ADEBAYO, Y. R., 501,503,509 ADEM, J., 32, 59 ADEM, J., BERGER, A., GASPAR, PH., PESTIAUX, P. and VAN YPERSELE,J. P., 32, 59 ADHI~MAR,J. A., 30, 59 ADLER, R. F., NEGRI, A. J. and HAKKARINEN,I. M., 261,275 ADLER, R. F., s e e NEGPd, A. J. et al. ADLER, R. F., s e e SIMPSON,J. et al. AFOLAYAN, A. A., s e e UDO, R. K. et al. AHARON, P., SCHIDLOWSKI, M. and SINGS, I. B., 114, 127, 136 AHLQUIST, N. C., s e e COVERT, D. S. et al. AHLQUIST, N. C., s e e WAGGONER,A. P. et al. AHMAD, E., s e e RAMANATHAN,V. et al. AHMAD, S. P. and DEERING, D. W., 265, 275 AHRENS, C. D., 247, 275 AHRENS, T. J., s e e O'KEEFE, J. D. and AHRENS, T. J. AIDA, M., 487, 509 ALBRECHT, B. A., 260, 275,373, 389 ALEXANDERSSON,n., 156, 182 ALEXANDERSSON,n., s e e HOGSTROM,U. et al. ALLAN, R. J., 216, 217, 233 ALLAN, R. J., NICHOLLS, N., JONES, P. D. and BUTTERWORTH,I. J, 174, 182 ALLEN, A. J., s e e YABUSHrrA, S. and ALLEN, A. J. ALLEN, M. R., NICHOLLS, N., JONES, P. D. and BUrrERWoRTH, I. J., 179 ALLEN, M. R., READ, P. L. and SMITH, L. A., 182 ALLEY, R. B., MEESE, D. A., SHUMAN,C. A., Gow, A. J., TAYLOR, K. C., GROOTES, P. M., WHITE, J. W. C., RAM, M., WADDINGTON, E. D., MAYEWSKI, P. A. and ZIELINSKI, G. A., 517, 533 ALLEY, R. B., s e e TAYLOR, K. C. et al.
555
ALPERT, J. C., s e e GELLER, M. A. and ALPERT, J. C., 236 ALT, D., s e e SEARS, J. W. and ALT, D. ALVAREZ, L. W., 115 ALVAREZ, L. W., ALVAREZ, W., ASARO, F. and MICHEL, H. V., 95, 96, 98, 115, 136 ALVAREZ, L. W., s e e ALVAREZ,W. et al. ALVAREZ, L. W., s e e ASARO, F. et al. ALVAREZ, W., 96, 115, 130, 134, 136 ALVAREZ, W. and ASARO, F., 96, 137 ALVAREZ, W., ALVAREZ, L. W., , ASARO, F. and MICHEL, H. V., 115, 137 ALVAREZ, W., ASARO, F. and MONTANARI, A., 137 ALVAREZ, W., s e e ALVAREZ,L. W. et al. ALVAREZ, W., s e e ASARO, F. et al. ALVAREZ, W., s e e HUT, P. et al. ALVAREZ, W., s e e LOWRIE, W. et al. ALYEA, F. N., 35, 59 AMBACH, W., s e e BLUMTHALER,M. and AMBACH, W. ANDERS, E., s e e GILMOUR,I. et al. ANDERS, E., s e e WOLBACH,W. S. et al. ANDERS, E., WOLBACH, W. S. and LEWIS, R. S., 101,137 ANDERSON, B. G., s e e HUGHES,Z. J. et al. ANDERSON, D. L., TANIMOTO, Z. and ZHANG, Y.S., 128, 137 ANDERSON, O. M. and WEBB, R. S., 24, 59 ANDERSON, D. M., s e e HUGHES,T. J. et al. ANDERSON, J. G., BRUNE, W. H. and PROFITT, M. H., 416, 430 ANDERSON, R. Y., 222, 223, 233 ANDERSON, T. L. and CHARLSON,R. J., 545, 551 ANDERSON, Z. L., WOLFE, G. V. and WARREN, S. G., 371,389 ANDERSSON,E., s e e LYRE, J. R. et al. ANDREAE, M. D., s e e CHARLSON,R. J. et al. ANDREAE, M. O., 351, 353, 357, 366, 372, 378, 382, 389, 390, 45 l, 468,541 ANDREAE, M. O. and J AESCHKE,W. A., 357, 390 ANDREAE, M. O., ANDREAE, T. W., FEREK, R. J. and RAEMDONCK,H., 380, 382, 390 ANDREAE, M. O., BERRESHEIM, n., ANDREAE, T. W., KRITZ, M. A., BATES, T. S. and MERRILL, J. T., 353,356, 376, 380, 381,390 ANDREAE, M. O., BERRESHEIM, n., BINGEMER, n., JACOB, D. J., LEWIS, B. L., LI, S. and TALBOT, R. W., 350, 390
References
Index
ANDREAE, M. O., BROWELL, E. V., GARSTANG, M., GREGORY, G. L., HARRISS, R. C., HILL, G. F., JACOB, D. J., PEREIRA, M. C., SACHSE, G. W., SETZER, A. W., SILVA DIAS, P. L., TALBOT, R. W., TORRES, A. L. and WOFSY, S. C., 448, 468 ANDREAE, M. O., DE MORA, S. J. and ELBERT, W., 372, 390 ANDREAE, M. O., ELBERT, W. and ANDREAE, T. W., 380, 390 ANDREAE, M. O., s e e ANDREAE,T. W. et al. ANDREAE, M. O., s e e BERRESHEIM,n. et al. ANDREAE, M. O., s e e BINGEMER,H. G. et al. ANDREAE, M. O., s e e CHARLSON,R. J. et al. ANDREAE, M. O., s e e CHURCH,T. M. et al. ANDREAE, M. O., s e e CRUTZENP. J. and ANDREAE, M.O ANDREAE, M. O., s e e TALBOT, R. W. et al. ANDREAE, T. W., ANDREAE, M. O. and SCHEBESKE, G., 372, 390 ANDREAE, T. W., s e e ANDREAE,M. O. et al. ANDREAE, T. W., s e e BINGEMER,H. G. et al. ANDREAE, T. W., s e e TALBOT, R. W. et al. ANDREE, M., s e e BROECKER,W. S. et al. ANDREWS, J., s e e BOND, G. et al. ANGELL, J. K., 169, 170, 171, 182, 220, 224, 233 ANGELL, J. K. and KORSHOVER,J., 176, 182 ANGELL, J. K., HOECKER, W. H., DICKSON, C. R. and PACK, D. H., 496, 509 ANGELL, J. K., s e e WIGLEY,Z. M. L. et al. ANGIONNE, R. J., s e e ROOSEN, G. R. et al. ANTUNEZ DE MAYOLO, S. E., s e e QUINN, W. H. et al. APSIMON, H., THORNTON, I., FYFE, W., HONG, Y., LEGGETT, J., NRIAGU, J. O., PACYNA, J. M., PAGE, A. L., PRICE, R., SKINNER, B., STEINNES, E. and YIM, W., 434, 469 ARAO, K., s e e YAMAMOTO,G. M. et al. ARAS, N. K., s e e TUNCEL, G. et al. ARDANUY, P. E., s e e ARrdN, P. A. and ARDANUY, P.E. AREOLA, O. O., s e e UDO, R. K. et al. ARIMOTO, R., s e e DUCE, R. A. et al. ARKIN, P. A. and ARDANUY, P. E., 156, 182, 261, 275 ARKIN, P. A. and JANOWIAK,J. E., 261,275 ARKIN, P. A., s e e RICHARDS,F. and ARKIN, P. A. ARKIN, P. A., s e e TRENBERTH,K. E. et al. ARMENTANO, T. V. and RALSTON, C. W., 444, 469 ARMSTRONG, R. L., s e e DENTON, G. H. and ARMSTRONG, R. L. 92 ARNAO, B. M., s e e THOMPSON,L. G. et al. ARNFIELD, A. J., s e e MILLS, G. M. and ARNFIELD, A.J. ARNFIELD, J. A., 488, 509 ARNOLD, M., s e e DUPLESSY,J. CL. et al. ARONSON, J. L., s e e EBINGER,C. J. et al.
556
ARTAXO, P., MAENHAUT,W., STORMS, H. and VAN GRIEKEN, R., 350, 356, 390 ARTAXO, P., s e e BINGEMER,H. G. et al. ARTAXO, P., s e e TALBOT, R. W. et al. ARTHUR, M. A., s e e GERSTEL,J. et al. ARTHUR, M. A., s e e SIGURDSSON,H. et al. ARTHUR, M. A., s e e ZACHOS, J. C. and ARTHUR, M.A. ARTHUR, M. A., s e e ZACHOS,J. C. et al. ARTZ, R. S., s e e HANSEN,A. D. A. et al. ASARO, F., ALVAREZ, L. W., ALVAREZ, W. and MICHEL, H. V., 115, 137 ASARO, F., s e e ALVAREZ,L. W. et al. ASARO, F., s e e ALVAREZ,W. and ASARO, F. ASARO, F., s e e ALVAREZ,W. et al. ASARO, F., s e e LOWRIE,W. et al. ASCENCIO, J.-M., s e e DELMAS,R. J. et al. ASrdN, R. A., 112, 137 ASRAR, G., s e e SELLERS, P. J. et al. ATKINSON, B. W., 504, 509 ATLAS, A. L., s e e DUCE, R. A. et al. ArrREP JR, M., s e e JOHNSON,K. R. et al. Aa~rREPJR, M., s e e ORTH, C. J. et al. ArrREP JR, M., s e e WANG, K. et al. AUBRY, M.-P., s e e CORLISS,B. H. et al. AUER JR., A. H., s e e WagE, J. M. et al. AUER, A. H., 488,495,503, 509 AUER, A. H., s e e BRYANT, H. K. et al. AUER, A. H., s e e SHEA, D. M. and AUER, A. H. AUSTIN, J., BUTCHART, N. and SHINE, K. P., 408, 430 AYERS, G. P., BIGG, E. K., TURVEY, D. E. and MANTON, M. J., 504, 509 AVERS, G. P., IVEY, J. P. and GILLETT, R. W., 380, 390 AYERS, G. P., s e e BERRESHEIM,H. et al. AYOADE, J. O., s e e UDO, R. K. et al. AZMI, R. J., s e e BHANDARI,N. et al. B ACASTON, R. B., s e e KEELING,C. D. et al. B ACKMAN,J., s e e SHACKLETON,N. J. et al. BAERREIS, D. A. and BRYSON, R. A., 194, 233 BAINBRIDGE, A. E., s e e KEELING,C. D. et al. BAKER, D. G., 182 BAKER, D. G. and BLACKBURN,T., 154 BAKER, K. S., s e e SMITH, R. C. et al. BAKER, M. B. and CHARLSON,R. J., 373, 390 BAKSI, A. K., 127, 137 BAKSI, A. K. and FARRAR, E., 127, 137 BALDWIN, B., s e e POLLACK,J. B. et al. BALGOVIND, R. C., s e e KASAHARA,A. et al. BALIUNAS, S., 241 BALIUNAS, S. and JASTROW,R., 199, 233 B ALIUNAS, S. L., s e e RADICK, R. R. et al. BALL, J. H., s e e BETTS, A. K. et al. BALL, J. T., s e e BOWNE, N. E. and BALL, J. T. BALLARD, J., s e e TAYLOR, F. W. et al.
References Index BALLING JR., R. C. and BRAZEL, S. W., 497, 498, 504, 509 BALLINGJR., R. C., s e e NASRALLAH,H. A. et al. B ALME, B. E., 117, 120, 137 BANIC, C. M., s e e LEAITCH,W. R. et al. BANNISTER, P., 545,547, 551 BANTZER, C., s e e FRAEDRICH,K. and B ANTZER,C. BAR, R., s e e MAGARITZ,M. et al. BARATH, F. T., CHAVEZ, M. C., COFIELD, R. E., FLOWER, D. A., FRERKING, M. A., GRAM, M. B., HARRIS, W. M., HOLDEN, J. R., JARNOT, R. F., KLOEZEMAN, W. G., KLOSE, G. J., LAU, G. K., LOO, M. S., MADDISON, B. J., MATTAUCH, R. J., MCKINNEY, R. P., MCKINNEY, R. P., PECKHAM, G. E., PICKETT, H. M., SIEBES, G., SOLTIS, F. S., SUTTIE, R. A., TARSALA, J. A., WATERS, J. W. and WILSON, W. J., 411,430 BARBETTI, M., s e e COOK, E. R. et al. BARD, E., HAMELIN, B., FAIRBANKS, R. G. and ZINDLER, A., 34, 37, 59 BARKER, J., s e e RUNNING, S. W. et al. BARKOV, N. I., s e e DE ANGELIS, M. et al. BARKOV, N. I., s e e GENTHON,C. et al. BARKOV, N. I., s e e JOUZEL, J. et al. BARKOV, N. I., s e e LEGRAND,M. R. et al. BARKSTROM, B. R. and SMITH, G. L., 245, 254, 275 BARKSTROM, B. R., s e e CESS, R. D. et al. BARKSTROM, B. R., s e e HARRISON,E. F. et al. BARKSTROM, B. R., s e e RAMANATHAN,V. et al. BARLOW, N. G., 95, 137 BARNETT, J. J., s e e TAYLOR, F. W. et al. BARNETT, Z. P., 160, 181,182, 218, 231,233 BARNETT, Z. P. and SCHLESINGER,M. E., 181, 182 BARNETT, T. P., DUMEIL, L., SCHLESE, U., ROECKNER, E. and LATIF, M., 218, 233 BARNETT, T. P., LATIF, M., KIRK, E. and ROECKNER, E., 218,233 BARNETT, T. P., SCHLESINGER, M. E. and JIANG, X., 231,232, 233 BARNETT, T. P., s e e GAFFEN, D. J. et al. BARNETT, T. P., s e e GRAHAM, N. E. and BARNETT, T.P. BARNETT, T. P., s e e GRAHAM, N. E. et al. BARNETT, T. P., s e e PREISENDORFER, R. W. and BARNETT, T. P. BARNETT, T. P., s e e WIGLEY, T. M. L. and BARNETT, T. P. BARNOLA, J. M., RAYNAUD, D., KOROTKEVICH, Y. S. and LORIUS, C., 230, 233, 520, 526, 533, 546, 551 BARNOLA, J. M., RAYNAUD, D., NEFI'EL, A. and OESCHGER, H., 524, 533 BARNOLA, J. M., RAYNAUD, Y., KOROTKEVICH, Y. S. and LORIUS, CL., 24, 46, 47, 48, 50, 59 B ARNOLA, J. M., s e e CHAPPELLAZ,J. et al. BARNOLA, J. M., s e e GENTHON,C. et al.
557
BARNOLA, J. M., s e e JOUZEL, J. et al. BARNOLA, J. M., s e e RAYNAUD, D. and BARNOLA, J.M. BARNOLA, J. M., s e e RAYNAUD,D. et al. BARNSTON, A. G. and LIVESEY, R. E., 179, 182, 204, 233 BARRERA, E. and KELLER, G., 103, 105, 110, 137 BARRERA, E., HUBER, B. Z. and WEBB, P. N., 91 BARRERA, E., HUBER, B. T., SAVIN, S. M. and WEBB, P.-N., 73, 108, 137 BARRERA, E., s e e KELLER, G. and B ARRERA, E. BARRIE, L. A. and HOFF, R. M., 380, 390 BARRON, E. J., 17, 71, 72, 74, 79, 84, 91, 93 BARRON, E. J. and PETERSON, W., 73, 85, 91 BARRON, E. J. and WASHINGTON, W. M., 75, 76, 84, 91,549, 551 BARRON, E. J., FAWCETT, P. J., POLLARD, D. and THOMPSON, S. L., 76, 86, 91 BARRON, E. J., PETERSON, W. H., THOMPSON, S. L. and POLLARD, D., 85, 91 BARRON, E. J., s e e SLOAN, L. C. and BARRON, E. J. BARRON, E. J., THOMPSON, S. L. and SCHNEIDER, S. H., 84, 91 BARROW, E. M., s e e WARRICK, R. A. et al. BARRY, R. G., s e e ROBINSON,O. A. et al. BARRY, R. G., s e e WILLIAMS,J. et al. BARRY, R. G., SERREZE, M. C., MASLANIK, J. A. and PRELLER, R. H., 273, 275 BARTHEL, K., s e e SAUSEN, R. et al. BARTHOLIN, T. S., s e e BRIFFA, K. R. et al. BASU, A. R., s e e RENNE, P. R. and B ASU, A. R. BASU, S., s e e GUNST, R. F. et al. BATES, D. R. and NICOLET, M., 401,402, 430 BATES, T. S., CALHOUN, J. A. and QUINN, P. K., 381,390 BATES, T. S., CLINE, J. D., GAMMON, R. n. and KELLY-HANSEN, S. R., 390 BATES, T. S., s e e ANDREAE, M. O. et al. BATES, T. S., s e e QUINN, P. K. et al. BATTISTI, D. S. and HIRST, A. C., 21 l, 233 BAUD, A., s e e MAGARITZ,M. et al. BAUMHEFNER, D. P., s e e HURRELL, J. et al. BAYER, R., s e e SCHLOSSER,P. et al. BEATY, C., 75, 91 BECKER, R. T., HOUSE, M. R., KIRCHGASSER, W. T. and PLAYFORD, P. E., 124, 137 BELCHER, K. M., s e e TALBOT, R. W. et al. BELJAARS, A. C. M., s e e BETTS, A. K. et al. BELOKRYLOVA, T. A., s e e GROISMAN, P. YA. et al. BENBOW, S. M. P., s e e HENDERSON-SELLERS, B. et al. BEND, G., s e e DANSGAARD,W. et al. BENDER, M., s e e JOUZEL,J. et al. BENGTSSON, L. and SHUKLA,J., 283, 310 BENGTSSON, L., BOTZET, M. and ESCH, M., 309, 310
References
Index
BENJAMIN, S. G., s e e CARLSON, T. N. and BENJAMIN, S. G. BENJAMIN, S. G., s e e CARLSON,T. N. et al. BENTON, M. J., 119, 137 BERBERA, J. J., s e e SELF, S. et al. BERGER, A, GALLI~E H., FICHEFET, TH., MARSIAT, I. and TRICOT, C., 44, 45, 47, 60 BERGER, A., 5, 9, 17, 24, 25, 26, 28, 29, 31, 39, 44, 46, 60, 231,233 BERGER, A. and LOUTRE, M. F., 26, 27, 29, 60 BERGER, A., FICHEFET,TH., GALLI~EH., TRICOT, C. and VAN YPERSELE, J. P., 50, 60 BERGER, A., FICHEFET, TH., GALL~E, H., MARSIAT, I., TRICOT,C. and VANYPERSELE,J. P., 44, 45, 60 BERGER, A., GALLI~E, H. and MI~LICE, J. L., 55, 56, 59, 60 BERGER, A., GALLI~E,H. and TRICOT, C., 60 BERGER, A., GUIOT, J., KUKLA, G. and PESTIAUX, P., 42, 49, 60 BERGER, A., LOUTRE, M. F. and TRICOT, C., 29, 50, 60 BERGER, A., s e e ADEM, J. et al. BERGER, A., s e e GALLI~E,H. et al. BERGER, A., s e e IMBRIE, J. et al. BERGER, A., s e e KUKLA, G. et al. BERGER, A., s e e LOUTRE, M. F. et al. BERGER, A., s e e MARSIAT, I. and BERGER, A. BERGER, A., s e e PESTIAUX,P. et al. BERGER, A., s e e SANTER,B. et al. BERGER, m., s e e SHACKLETON,N. J. et al. BERGER, A., s e e TRICOT, C. and BERGER, A. BERGER, A., TRICOT, C., GALLI~E, H. and LOUTRE, M. F., 52, 53, 60 BERGER, D., s e e SCOTTO,J. et al. BERGER, D., s e e URBACH, F. et al. BERGER, W. H., 553 BERGER, W. H., FISCHER, K., LAI, C. and Wu, G., 545,551 BERGGREN, W. A., s e e CORLISS, B. H. et al. BERGSTROM, H., s e e HOGSTROM,U. et al. BERGTHORSSON,P., 193,233 BERNER, R. A., 75, 80, 91, 126, 137, 539, 547, 548, 551 BERNER, R. A., LASAGA, A. C. and GARRELS, R. M., 75, 84, 91,103, 137, 538, 547,551 BERNER, W., OESCHGER, H. and STAUFFER, B., 524,533 BERNSTEIN, R. E., s e e BETZER, P. R. et al. BERNSTEIN, R. L., s e e BETZER, P. R. et al. BERNSTEIN, R. L., s e e COAKLEYJR., J. A. et al. BERRESHEIM, n., ANDREAE, M. O., AVERS, G. P. and GILLETT, R. W., 381,390 BERRESHEIM, H., ANDREAE, M. O., AVERS, G. P., GIELETT, R. W., MERRILL, J. T., DAVIS, V. J. and CHAMEIDES,W. L., 381,390 BERRESHEIM, n., ANDREAE, M. O., IVERSON, R. L. and LI, S.-M., 381,390
558
BERRESHEIM, H., s e e ANDREAE,M. O. et al. BERRESHEIM, H., s e e TALBOT, R. W. et al. BERRIOR, A., s e e HARTMANN,D. L. et al. BERRY, B. J. L., 437,469 BERRY, J. C., s e e TRENBERTH,K. E. et al. BERRY, W. B. N., s e e WILDE, P. et al. BERTRAND, H., s e e SEBAI, A. et al. BESSE, J., s e e COURTILEOT,V. et al. BESSE, J., s e e VANDAMME,D. et al. BETTS, A. K., BALL, J. H., BELJAARS, A. C. M., MILLER, M. J. and VITERBO, P., 269, 275 BETZER, P. R., CARDER, K. L., DUCE, R. A., MERRILL, J. T., TINDALE, N. W., UEMATSU, M., COSTELEO, D. K., YOUNG, R. W., FELLY, R. A., BRELAND, J. A., BERNSTEIN, R. E. and GRECO, A. M., 350, 390 BEVAN, A., s e e PARKER, D. E. et al. BHALME, H. N. and MOOLEY, D. A., 199, 234 BHANDARI, N., SHUKLA, P. N. and AZMI, R. J., 120, 137 BHANDARI, N., SHUKLA, P. N. and CINI CASAGNOEI,G., 134, 137 BHANDARI, N., SHUKLA, P. N. and PANDEY, J., 120, 137 BHRUMRALKAR,C. M., s e e SEAMAN,N. L. et al. BICE, D. M., NEWTON, C. R., MCCAULEY, S., REINERS, P. W. and MCROBERTS, C. A., 115, 119, 137 BICKLE, M. J., s e e MCKENZIE, D. P. and BICKLE, M.J. BIDIGARE, R. R., s e e SMITH, R. C. et al. BIGG, E. K., 372, 390 BIGG, E. K., s e e AVERS, G. P. et al. BILSBORROW, R. E.and OKOTH-OGENDO, H. W. O., 435,469 BINGEMER, H. G., ANDREAE, M. O., ANDREAE, T. W., ARTAXO, P., HELAS, G., JACOB, D. J., MIHALOPOULOS, N. and NGUYEN, B. C., 381, 390 BINGEMER, H. G., s e e ANDREAE,M. O. et al. BIRCHFIELD, G. E., 37, 60 BIRCHFIELD, G. E. and WEERTMAN,J., 31, 60 BIRCHFIELD, G. E., WEERTMANN,J. and LUNDE, A. T., 40, 60 BIRD, T., s e e COOK, E. R. et al. BIRKS, J. W., s e e CRUTZEN,P. J. and BIRKS, J. W. BISCHOF, W., s e e BOLIN, B. and BISCHOF, W. BISHOP, L., s e e BOJKOV, R. D. et al. BISHOP, L., s e e STOLARSKI,R. S. et al. BJERKNES, J., 214, 225,234 BJORN, L. O., s e e MADRONICH,S. et al. BLACKBURN,T., 154, 182 BEACKMON, M. L., s e e DESER, C. and BEACKMON, M.L. BLACKMON, M. L., s e e WALLACE,J. M. et al. BEAD, B. L., s e e STARKS,P. J. et al. BLANC, P. L., s e e DUPLESSY,J. C. et al.
References
Index
BLANC, P. L.,, s e e LABEYRIE,L. D. et al. BLANC, P. L., s e e LOUTRE, M. F. et al. BLANCHARD, D. C., 351,390 BLANCHET, J. P., 451,469 BLANCHET, J. P., s e e CESS, R. D. et al. BLIFFORD, I. H., s e e GILLETTE, D. A. and BLIFFORD, I. H. BLOOMFIELD, P., 231,234 BLOOMFIELD, P., s e e STOLARSKI,R. S. et al. BLUMTHALER,M. and AMBACH, W., 425,430 BLUTH, G. J. S., SCHNETZLER,C. C., KRUEGER, A. J. and WALTER, L. S., 352, 357, 391 BOATMAN, J. F., s e e GALLOWAY,J. N. et al. BOATMAN, J. F., s e e WHELPDALE,D. M. et al. BOATMAN, J. F., WELLMAN, D. L., VAN VALIN, C. C., GUNTER, R. L., RAY, J. D., SILVERING, H., KIM, Y., WILKINSON, S. K. and LURIA, M., 381, 391 BOCLET, D., s e e ROCCHIA, R. et al. BOECKELMANN,K., s e e HOLSER,W. T. et al. BOER, G. J., 283, 284, 285, 286, 292, 293, 296, 310 BOER, G. J. and SARGENT, N. E., 286, 288, 293, 310 BOER, G. J., s e e CESS, R. D. et al. BOER, G. J., s e e GATES, W. L. et al. BOERSMA, A., 112 BOERSMA, A. and SHACKLETON,N. J., 109, 137 BOERSMA, A., s e e SHACKLETON, N. J. and BOERSMA, A. BOERSMA, A., SHACKLETON, N. J., HALL, M. and GIVEN, Q., 109, 112, 137 BOJKOV, R. D., BISHOP, L., HILL, W. J., REINSEL, G. C. and TIAO, G. C., 339, 344 BOJKOV, R. D., s e e WANG, W.-C. et al. BOJKOV, R., s e e STOLARSKI,R. S. et al. BOLIN, B. and BISCHOF, W., 230, 234 BOLIN, B. and CHARLSON,R. J., 347, 391 BONAN, G. B., POLLARD, D. and THOMPSON, S. L., 438,452, 469, 541, 551 BONANI, G., s e e BOND, G. et al. BONANI, G., s e e BROECKER,W. S. et al. BOND, G., HEINRICH, H., BROECKER, W. S., LABEYRIE, L. D., MCMANUS, J., ANDREWS, J., HUON, S., JANTSCHIK, R., CLASEN, S., SIMET, C., TEDESCO, K., KLAS, M.BONANI, G. and IvY, S., 25, 60 BOND, G., s e e BROECKER,W. S. et al. BOND, G., s e e DANSGAARD,W. et al. BONISCH, G., s e e SCHLOSSER,P. et al. BONNEL, B., s e e FOUQuART, Y. et al. BONSANG, B., s e e NGUYEN, B. C. et al. BONTE, P., s e e ROCCHIA, R. et al. BONY, S. and LE TREUT, H., 254, 275 BOOTH, C. R., s e e LUBIN, D. et al. BOOTH, C. R., s e e STAMNES,K. et al. BORNSTEIN, R. D., 479, 510
559
BORNSTEIN, R. D. and JOHNSTON,D. S., 496, 510 BORNSTEIN, R. D., s e e LOOSE, T. and BORNSTEIN, R.D. BOSART, L. F., s e e KESSLER,R. W. et al. BOSTON, P. J., s e e SCHNEIDER, S. H. and BOSTON, P.J. BOTTJER, D. J., s e e SCHUBERT, J. K. and BOTTJER, D.J. BOTTOMLEY, M., FOLLAND, C. K., HSIUNG, J., NEWELL, R. E. and PARKER, D. E., 152, 153, 158, 182 BOTZET, M., s e e BENGTSSON,L. et al. BOUCHER, N. P., s e e SMITH, R. C. et al. BOULTON, G. S., 25, 60 BOULTON, G. S., SMITH, G. D., JONES, A. S. and NEWSOME, J., 47, 60 BOVILL, E., 441,469 BOWEN, M., s e e STAMNES,K. et al. BOWNE, N. E. and BALL, J. T., 496, 510 BOWYER, P. A., s e e CIPRIANO, R. J. et al. BOYLE, E. A., 527, 528, 533, 547, 551 BOYLE, E. A. and KEIGWlN, L., 88, 91 BOYLE, E. A., s e e IMBRIE, J. et al. BRADLEY, R. S., 17, 22, 33, 60, 168, 176, 182, 195,205,220, 234 BRADLEY, R. S. and JONES, P. D., 168, 169, 176, 177, 182, 183, 195, 196, 197, 234 BRADLEY, R. S., DIAZ, H. F., EISCHEID, J. K., JONES, P. D., KELLY, P. M. and GODDESS, C. M., 155, 166, 183 BRADLEY, R. S., DIAZ, H. F., KILADIS, G. N. and EISCHEID, J. K., 174, 183,234 BRADLEY, R. S., KEIMIG, F. T. and DIAZ, H. F., 228, 234 BRADLEY, R. S., KELLY, P. M., JONES, P. D., GOODESS, C. M. and DIAZ, H. F., 154, 183 BRADLEY, R. S., s e e DIAZ, H. F. and BRADLEY, R. S. BRADLEY, R. S., s e e DIAZ, H. F. et al. BRADLEY, R. S., s e e JONES, P. D. and BRADLEY, R. S. BRADLEY, R. S., s e e JONES, P. D. et al. BRAHAM JR., R. R., 372, 373, 380, 388, 391,504, 510 BRAND, U., 125, 137 BRANSTATOR,G. W., s e e MADDEN, R. A. et al. BRANSTATOR, G. W., s e e MEEHL, G. A. and BRANSTATOR,G. W. BRANSTATOR,G. W., s e e TRENBERTH,K. E. et al. BRASS, G., SALTzMAN,E., SLOAN, J., SOUTHAM,J., HAY, W., HOLZER, W. and PETERSON, W., 73, 91 BRASSEUR, G. P. and GRANIER, C., 413,430 BRASSEUR, G. P. and HITCHMAN,M. H., 413,430 BRASSEUR, G. P. and SOLOMON, S., 405,430 BRASSEUR, G. P., HITCHMAN,M. H., WALTERS, S., DYMEK, M., FALISE, E. and PIRRE, M., 413,430
References
Index
BRASSEUR, G. P., s e e GRANIER, C. and BRASSEUR, G.P. BRASSEUR, G. P., s e e HAUGLUSTAINE,D. A. et al. BRASSEUR, G. P., s e e HITCHMAN, M. H. and BRASSEUR, G. P. BRAZEL, A. J., s e e NASRALLAH,H. A. et al. BRAZEL, S. W., s e e BALLING JR., R. C. and BRAZEL, S. W. BRAZIUNAS, Z. F., s e e STUIVER, M. and BRAZIUNAS, Z. F. BRELAND, J. A., s e e BETZER, P. R. et al. BRI~MOND,M.-P., s e e CACHIER, H. et al. BRENCHLEY, P. J., 126, 137 BRESCHER, R., s e e OSTLUND,H. G. et al. BRETAGNON, P., s e e LOUTRE, M. F. et al. BRETHERTON, F. P., s e e SODEN, B. J. and BRETHERTON,F. P. BREWER, P. G., BROECKER, W. S., JENKINS, W. J., RHINES, P. B., ROOTH, C. G., SWIFT, J. H., TAKAHASHI, T. and WILLIAMSR. T., 532, 533 BREZA, J. R., s e e ZACHOS, J. C. et al. BRIAT, M., s e e PETIT, J.-R. et al. BRICAUD, A. and STRAMSKI,D., 541, 551 BRIDGE, D., s e e SIMKIN, T. et al. BRIEGEL, L. M., 305, 310 BRIEGLIEB, B., 413,430 BRIEGLEB, B. P., s e e KIEHL, J. T. and BRIEGLEB, B. P. BRIEGLEB, B. P., s e e SHINE, K. P. et al. BRIFFA, K. R. and JONES, P. D., 183 BRIFFA, K. R., JONES, P. D., BARTHOLIN, T. S., ECKSTEIN, D., SCHWEINGRUBER,F. H., KARLI~N, W., ZETTERBERG,P. and ERONEN, M., 194, 234 BRIFFA, K. R., s e e JONES, P. D. and BRIFFA, K. R. BRISKIN, M. and HARRELL,J., 31, 61 BROCCOLI, A. J. and MANABE, S., 35, 36, 61 BROCCOLI, A. J., s e e MANABE, S. and BROCCOLI, A.J. BROCK, C. A., s e e RADKE, L. F. et al. BROECKER, W. S., 226, 234, 389, 391, 517, 518, 519, 520, 522, 526, 527, 528, 529, 530, 531, 532,533 BROECKER, W. S. and DENTON, G. H., 31, 41, 61, 531,533 BROECKER, W. S. and PENG, T.-H., 524, 529, 533, 547, 549, 551 BROECKER, W. S., ANDREE, M., WOLFI, W., OESCHGERI, H., BONANII, C., KENNETTI, J. and PETEET, D., 37, 43, 61 BROEcKER, W. S., BOND, G., KLAS, M., BONANI, G. and WOLFI, W., 533 BROEcKER, W. S., FLOWER, B. P., TRUMBORE, S., WOLFI, W., KENNETT, J. P., TELLER, J. T. and BONANI, G., 24, 43, 61 BROEcKER, W. S., PETEET, D. M. and RIND, D., 43, 61, 88, 91,195,234, 389, 391,533 BROEcKER, W. S., s e e BOND, G. et al.
560
BROECKER,W. S., s e e BREWER, P. G. et al. BROECKER, W. S., s e e RIND, D. et al. BROGNIEZ, G., s e e FOUQUART,Y. et al. BROOKS, R. R., s e e WOLBACH,W. S. et al. BROWELL, E. V., s e e ANDREAE,M. O. et al. BROWN, J. F., s e e GALLO, K. P. et al. BROWN, J., s e e KUKLA, G. et al. BROWN, L. R., 439, 469 BROWN, L. R., s e e ECKHOLM,E. and BROWN, L. R. BROWN, S., s e e HOUGHTON,R. A. et al. BROWNING, S. R., s e e HERMAN, B. M. et al. BRUGMAN, W. A., s e e VISSCHER, n. and BRUGMAN, W. A. BRUNDTLAND,G. H., 439, 440, 441,469 BRUNE, W. n., s e e ANDERSON,J. G. et al. BRUNELL, R., s e e GUNST, R. F. et al. BRUNNER, J. S., s e e STREET-PERROTT,F. A. et al. BRYAN, F., 88, 91,226, 234 BRYAN, F., s e e MANABE, S. et al. BRYAN, K., s e e GORDON, A. L. et al. BRYAN, K., s e e MANABE, S. et al. BRYAN, K., s e e STOUFFER,R. J. et al. BRYANT, H. K., GLANCY, R. T. and AUER, A. n., 496, 510 BRYSON, R. A., 231,234, 244, 347, 391 BRYSON, R. A. and SWAIN, A. M., 194, 234 BRYSON, R. A., IRVING, W. M. and LARSON, J. A., 194, 234 BRYSON, R. A., s e e BAERREIS, D. A. and BRYSON, R.A. BRYSON, R. A., s e e KUTZBACH, J. E. and BRYSON, R.A. BUAT-MI~NARD,P., s e e CACHIER, H. et al. BUAT-MENARD, P., s e e DUEL, R. A. et al. BUCK, C. F., s e e MAYEWSKI,P. A. et al. BUCKLEY, B., s e e COOK, E. R. et al. BUDYKO, M., 230, 234 BUDYKO, M. and RONOV, A., 75, 91 BUFFETAUT,E., s e e ROCCHIA,R. et al. BUGGISCH, W., 114, 124, 125, 138 BUISSON, M., s e e FABRY, C. and BUISSON, M. BUJA, L. E., s e e TRENBERTH,K. E. et al. BORGERMEISTER,S. and GEORGn, H.-W., 381, 391 BURIEZ, J. C., s e e FOUQUART,Y. et al. BUSALACCHI, A. J., s e e LAU, K.-M. and BUSALACCHI, A. J. BUSCHBACHER,R., s e e UHL, C. and BUSCHBACHER, R. BUTCHART, N., s e e AUSTIN, J. et al. BUTLER, J. L., s e e SANDBERG,C. A. et al. BUTTERWoRTH,I. J., s e e ALLAN, R. J. et al. CABRAL, G. M. R., s e e SHUTTLEWoRTH,W. J. et al. CACHIER, H. and DUCRET, J., 451,469 CACHIER, H., BRI~MOND, M.-P. and BUATMI~NARD, P., 353, 391 CALDEIRA, K. and KASTING, J. F., 550, 551
References
Index
CALDEIRA, K. and RAMPINO, M. R., 104, 105, 132, 133, 138 CALDEIRA, K., RAMPINO, M. R., VOLK, T. and ZACHOS, J. C., 104, 138 CALDEIRA, K., s e e RAMPINO, M. R. and CALDEIRA, K. CALDWELL, M. M., CAMP, L. B., WARNER, C. W. and FLINT, S. D., 420, 430 CALDWELL,M. M., s e e MADRONICH,S. et al. CALHOUN,J. A., s e e BATES,T. S. et al. CALLANDER,B. A., s e e HOUGHTON,J. T. et al. CALVERT, J., s e e FEHSENFELD, F. et al. CAMP, L. B., s e e CALDWELL,M. M. et al. CAMP, W. V., s e e POLLACK, J. B. et al., 241 CAMPBELL, I. H., CZAMANSKE,G. K., FEDORENKO, V. A., HILL, R. I. and STEPANOV,V., 127, 138 CAMPBELL, L. D., s e e STANLEY, S. M. and CAMPBELL, L. D. CANE, M. A., 214, 234 CANE, M. A. and ZEBIAK, S. E., 211, 214, 234 CAO, H. X., 183 CAO, H. X., MITCHELL,J. F. B. and LAVERY,J. R., 164 CAPPETTA, n., s e e COURTILLOT,V. et al. CAPUTO, M., 125, 138 CARDER, K. L., s e e BETZER,P. R. et al. CAREY, S., s e e SIGURDSSON,n. et al. CARISSIMO, B. C., OORT, A. n. and WONDERHAAR, T. H., 85, 91 CARLSON, T. N. and BENJAMIN, S. G., 367, 388, 391 CARLSON, Z. N. and CAVERLY,Z. S., 367, 388, 391 CARLSON, T. N., DODD, J. K., BENJAMIN,S. G. and COOPER, J. N., 492, 510 CARLSON, T. N., s e e METHOD, T. and CARLSON,T. N. CARMACK, E. C., s e e AAGAARD,K. and CARMACK, E.C. CARNEGGIE,D., s e e RUNNING,S. W. et al. CARPENTER, T. n., s e e RASMUSSEN, E. M. and CARPENTER,T. H. CARTER, A. F., s e e KEELING,C. D. CARTLIDGE,J. E., s e e CORFIELD,R. M. et al. CASIER, J-G., s e e CLAEYS, P. et al. CASSINIS, G., 120, 138 CASTILLO, R. C., s e e PUESCHEL,R. F. et al. CAVERLY, T. S., s e e CARLSON, T. N. and CAVERLY, T.S. CAYAN, D. R. and DOUGLAS,A. V., 497, 510 CAYAN, D. R., s e e DOUGLAS,A. V. et al. CAYAN, D. R., s e e EBBESMEYER,C. C. et al. CAYAN, D. R., s e e NAMIAS,J. and CAYAN, D. R. CAYAN, D. R., s e e VENRICK, E. L. et al. CERF, A., s e e FOUQuART, Y. et al. CERLING, T. E., 75, 80, 91 CESS, R. D., 275 CESS, R. D. and VULIS, I. L., 265, 275
561
CESS, R. D., HARRISON, E. F., MINNIS, P., BARKSTROM, B. R., RAMANATHAN, V. and KWON, T. Y., 319, 344 CESS, R. D., POTTER, G. L., BLANCHET, J. P., BOER, G. J., DEL GENIO, A. D., DI~QUE, M., DYMNIKOV, V., GALIN, V., GATES, W. L., GHAN, S. J., KIEHL, J. T., LACIS, A. A., LE TREUT, H., LI, Z.-X., LIANG, X.-Z., MCAVANEY, B. J., MELESHKO, V. P., MITCHELL, J. F. B., MORCRETTE, J.-J., RANDALL, D. A., RIKUS, L., ROECKNER, E., ROYER, J. F., SCHLESE,U., SHEININ, D. A., SLINGO, A., SOKOLOV, A. P., TAYLOR, K. E., WASHINGTON, W. M., WETHERALD, R. T., YAGAI, I. and ZHANG, M. H., 260, 275 CESS, R. D., POTTER, G. L., BLANCHET, J. P., BOER, G. J., GHAN, S. J., KIEHL, J. T., LE TREUT, H., LI, Z. X., LIANG, X. Z., MITCHELL, J. F. B., MORCRETTE, J. J., RANDALL, D. A., RICHES, M. R., ROECKNER, E., SCHLESE, U., SLINGO, A., TAYLOR K. E., WASHINGTON, W. M., WETHERALD,R. T. and YAGAI, I., 39, 61 CESS, R. D., POTTER, G. L., GATES, W. L., MORCRETTE, J.-J. and CORSETTI,L., 254 CESS, R. D., s e e CHARLSON,R. J. et al. CESS, R. D., s e e COAKLEYJR., J. A. et al. CESS, R. D., s e e FALKOWSKI,P. G. et al. CESS, R. D., s e e HARRISON,E. F. et al. CESS, R. D., s e e OWEN, T. et al. CESS, R. D., s e e RAMANATHAN,V. et al. CESS, R., s e e FALKOWSKI,P. G. et al. CESS, R., s e e OWEN, T. et al. CHAHINE, M., 453,469 CHAHINE, M. T. and SUSSKIND,J., 263,275 CHAI, Z., s e e Xu, D. et al. CHAI, Z-F., s e e WANG, J-X. et al. CHAMEIDES, W. L., s e e BERRESHEIM,H. et al. CHAMLEY, H., s e e ROBERT, C. and CHAMLEY, H. CHANDLER, M., RIND, D. and TUEDY, R., 84, 91 CHANDLER, M., s e e RIND, D. and CHANDLER,M. CHANG, A. T. C. and WILHEIT, T. T., 263,275 CHANG, A. T. C., FOSTER, J. L. and HALL, D. K., 272, 275 CHANG, A. T. C., s e e FOSTER, J. L. and CHANG, A. T.C. CHANG, A. T. C., s e e WILHEIT, T. J. et al. CHANG, C. C., s e e CHOW, S. D. and CHANG, C. C. CHANG, H.-R. and WEBSTER, P. J., 305, 310 CHANG, H.-R., s e e WEBSTER, P. J. and CHANG, H.R. CHANG, L. A., s e e Wu, M. L. C. and CHANG, L. A. CHANGERY,M. G., s e e KARL, T. R. et al. CHANGNONJR., S. A, 504 CHANGNONJR., S. A., 477, 504, 506, 510 CHANGNONJR., S. A. and HUFF, F. A., 504, 510 CHANGNONJR., S. A., HUFF, F. A., SHICKEDANZ,P. T. and VOGEL,J. L., 504, 510
References Index CHANGNON, S. A., 435,437, 438, 469 CHANGNON, S., s e e HUFF, F. A. and CHANGNON,S. CHAO, W. C., s e e SUp, Y. C. et al. CHAO, Y. and PHILANDER,S. G. n., 212, 234 CHAOUIROQUAI, M., s e e FOUQUART,Y. et al. CHAPMAN, C. R. and MORRISON, D., 95, 97, 135, 136, 138 CHAPMAN, D. J., s e e GRIFFIS, K. and CHAPMAN, D. J. CHAPMAN, W. L. and WALSH, J. E., 227, 234 CHAPPELL, J. and SHACKLETON,N. J., 23, 61 CHAPPELLAZ, J., BARNOLA, J. M., RAYNAUD, D., KOROTKEVITCH,Y. S. and LORIUS, C., 52, 61 CHAPPELLAZ, J., s e e JOUZEL,J. et al. CHAPPELLAZ, J., s e e RAYNAUD,D. et al. CHARLES, C. O., 527 CHARLES, C. D. and FAIRBANKS, R. G., 533, 547, 551 CHARLOCK, T. P., s e e WHITLOCK,C. H. et al. CHARLSON, R, J., SCHWARTZ, S. E., HALES, J. M., CESS, R. D., COAKLEY, J. A., nANSEN, J. and HOFFMAN, D. J., 231,234 CHARLSON, R. J., 54, 348,379, 391 CHARLSON, R. J. and PILAT, M. J., 347, 367, 391 CHARLSON, R. J., COVERT, D. S. and LARSON, T. V., 363, 391 CHARLSON, R. J., LANGER, J., RODHE, H., LEOVY, C. B. and WARREN, S. G., 164, 178, 183, 348, 362, 363,364, 368,369, 378, 385,386, 391 CHARLSON, R. J., LOVELOCK, J. E., ANDREAE, M. D. and WARREN, S. G., 54, 61,348, 372, 374, 375,391,539, 544, 545,552 CHARLSON, R. J., SCHWARTZ, S. E., HALES, J. M., CESS, R. D., COAKLEYJR., J. A., HANSEN, J. E. and HOFMANN, D. J., 258, 260, 275, 343, 344, 362, 363,365,370, 376, 39 l, 45 l, 469 CHARLSON, R. J., s e e ANDERSON, T. L. and CHARLSON, R. J. CHARLSON, R. J., s e e BAKER, M. B. and CHARLSON, R. J. CHARLSON, R. J., s e e BOLIN, B. and CHARLSON,R. J. CHARLSON, R. J., s e e CLARKE, A. D. and CHARLSON, R. J. CHARLSON, R. J., s e e COVERT, D. S. et al. CHARLSON, R. J., s e e ENSOR, D. S. et al. CHARLSON, R. J., s e e KARL, T. R. et al. CHARLSON, R. J., s e e LEGRAND,M. R. et al. CHARLSON, R. J., s e e OGREN, J. A. and CHARLSON, R.J. CHARLSON, R. J., s e e PROSPERO,J. M. et al. CHARLSON, R. J., s e e QUINN, P. K. et al. CHARLSON, R. J., s e e TWOHY, C. H. et al. CHARLSON, R. J., s e e WAGGoNER, A. P. et al. CHARNEY, J. G., 282, 310, 435,437,453, 456, 469 CHARNEY, J. G., QUIRK, W. J., CHOW, J. H. and KORNFIELD, J., 455,456, 457, 459, 461,469
562
CHARNEY, J. G., QUIRK, W. J., CHOW, S.-H. and KORNFIELD, J., 267, 275 CHASlN, B., s e e FRANKE, R. and CHASIN, B. CHATFIELD, R. B., 538, 552 CHATTERTON,B. D. E., s e e WANG, K. et al. CHAVEZ, M. C., s e e BARATH,F. T. et al. CHEN, T.-C., 297, 298, 311 CHEN, T.-C. VAN LOON, H., Wu, K.-D. and YEN, M.-C., 227 CHEN, T.-C., s e e CHEN, W. Y. et al. CHEN, W. Y., 213, 234 CHEN, W. Y., CHEN, T.-C., VAN LOON, H., Wu, K.D. and YEN, M.-C., 234 CHENOWETH,M., 15 l, 153, 183 CHERRY, B. S. G., s e e JONES, P. O. et al. CHERRY, B. S. G., s e e KELLY, P. M. et al. CHERVIN, R. M., 456, 469 CHERVIN, R. M., s e e WARREN, S. G. et al. CHESTER, R., s e e RILEY, J. P. and CHESTER, R. CHIFANG, C., YAOQI, Z. et al., 120, 138 CHIN, J. F. S., s e e KEELING,C. D. et al. CHING, J. K. S., CLARKE, J. F. and GODOWlTCH, J. M., 493,510 CHING, J. K. S., s e e CLARKE, J. F. et al. CHIU, L. C., s e e WILHErr, T. J. et al. CHOU, C. C., s e e CRAIG, H. et al. CHOU, M.-D., s e e KAUFMAN, Y. J. and CHOU, M.D. CHOUDHURY,B. J., 271,276 CHOW, J. H., s e e CHARNEY,J. G. et al. CHOW, S. D., 497, 510 CHOW, S. D. and CHANG, C. C., 486, 510 CHOW, S.-H., s e e CHARNEY,J. G. et al. CHRISTY, J. R., 236 CHRISTY, J. R., s e e SPENCER, R. W. and CHRISTY, J.R. CHRISTY, J. R., s e e TRENBERTH,K. E. et al. CHU, P.-S., 218, 235 CHU, W. P., s e e MCCORMICK, M. P. et al. CHURCH, T. M., s e e DUCE, R. A. et al. CHURCH, T. M., TRAMONTANO,J. M., WHELPDALE, D. M., ANDREAE, M. O., GALLOWAY, J. N., KEENE, W. C., KNAP, A. H. and TOKOS, J., 380, 381,391 CHYLEK, P., s e e COAKLEYJR., J. A. and CHYLEK, P. CICERONE, R. J., s e e STOLARSKI, R. S. and CICERONE, R. J. CID, S. L., s e e ENFIELD, D. B. and CID, S. L. CINI CASAGNOLI,G., s e e BHANDARI,N. et al. CIPRIANO, R. J., MONAHAN, E. C., BOWYER, P. A. and WOOLF, D. K., 351,391 CLAEYS, P., CASIER J-G. and MARGOLIS, S. V., 115, 124, 138 CLAEYS, P., s e e MARGOLIS, S. V. et al. CLARK, C. O., s e e CORRELL, D. L. et al. CLARK, D. L., 73, 91
References
Index
CLARK,W. C. and MUNN,R. E., 433,469 CLARK,W. C., s e e TURNERII, B. L. et al. CLARKE,A. D., 378, 382, 391 CLARKE, A. D. and CHARLSON,R. J., 366, 367, 382, 391 CLARKE, A. D., s e e TWOHY, C. H. et al. CLARKE, A. D., s e e WARREN, S. G. and CLARKE, A.D. CLARKE, J. F., CHING, J. K. S. and GODOWITCH, J. M., 496, 510 CLARKE,J. F., s e e CHING,J. K. S. et al. CLASEN, S., s e e BOND, G. et al. CLAUSEN, H. B., s e e DANSGAARD,W. et al. CLAUSEN, H. B., s e e HAMMER,C. U. et al. CLAUSEN, H. B., s e e JOHNSEN, S. J. et al. CLAUSEN, H. B., s e e TAYLOR, K. C. et al. CLEMENS,S. C., s e e IMBRIE,J. et al. CLEUGH, H. A. and OKE, T. R., 482, 493, 494, 510 CLEUGH, H. A., s e e GRIMMOND,C. S. B. et al. CLEUGH,H. A., s e e OKE, T. R. and CLEUGH,H. A. CLEUGH,H. A., s e e SCHMID,H. P. et al. CLIMAP, 23, 24, 34, 35, 36, 526 CLIMAP PROJECT MEMBERS, 61, 533, 545, 546, 552 CLINE, J. D., s e e BATES, T. S. et al. CLUBE, S. V. M., 95 CLUBE, S. V. M., s e e NAPIER, W. M. and CLUBE, S. V.M. COAKLEYJR., J. A. and CHYLEK, P., 370, 391 COAKLEYJR., J. A. and DAVIES, R., 369, 391 COAKLEYJR., J. A., BERNSTEIN,R. L. and DURKEE, P. A., 377, 391 COAKLEY JR., J. A., CESS, R. D. and YUREVICH, F. B., 360, 368, 391, 451,469 COAKLEY JR., J. A., s e e CHARLSON,R. J. et al. COAKLEYJR., J. A., s e e RADKE, L. F. et al. COCKS, L. R. M. and RICKARDS, R. B., 126, 138 COFFEY, M. T., s e e MANKIN, W. G. et al. COFIELD, R. E., s e e B ARATH, F. T. et al. COHEN, J. A., s e e KAROLY, D. J. et al. COHMAP, 24, 36 COHMAP MEMBERS,61 COLBATH, G. K., 126, 138 COLE, C., s e e DEGRUIJL,F. R. et al. COLE, J. E., SHEN, G. T., FAIRBANKS, R. G. and MOORE, M., 227,235 COLEY, T., s e e SMITH,R. C. et al. COLLINS, W., s e e RAMANATHAN, V. and COLLINS, W. COLMAN, R. A., s e e MCAVANEY, B. J. and COLMAN,R. A. COLMAN,R. A., s e e MCAVANEY, B. J. et al. COLMAN, R. A., s e e POWER, S. B. et al. COMMELIN, D., s e e PETIT-MAIRE,J. R. et al. COMMITTEEON EARTHSCIENCES, 230, 235 CONRAD, V. and POLLAK, L. D., 152, 156, 183
563
COOK, E. R., BIRD, T., PETERSON M., BARBETTI, M., BUCKLEY,B. and FRANCEY, R., 194, 235 COOPER,H. J., s e e SMITH, E. A. et al. COOPER, H. J., s e e WILBER, A. C. et al. COOPER,J. N., s e e CARLSON,T. N. et al. COPPIN, P. A., 493,496, 510 CORFIELD, R. M., CARTLIDGE, J. E., PREMOLISILVA, I. and HOUSLEY, R. A., 111,138 CORFIELD, R. M., s e e SPICER, R. A. and CORFIELD, R.M. CORLISS, B. H., 118 CORLISS, B. H., AUBRY, M.-P., BERGGREN, W. A., PENNER, J. M., KEIGWINJR., L. D. and KELLER, G., 138 CORLISS, B. H., s e e KEIGWIN, L. D. and CORLISS, B.H. CORNET, l . , s e e OLSEN, P. E. et al. CORRELL, D. L., CLARK, C. O., GOLDBERG, l . , GOODRICH, V. R., HAYES JR., D. R., KLEIN, W. H. and SCHECHER,W. D., 425,430 CORSETTI,L., s e e CESS, R. D. et al. COSTELLO, D. K., s e e BETZER, P. R. et al. COTTON, G., s e e SCOTTO,J. et al. COUGHLAN, M., s e e JONES, P. D. et al. COURTILLOT,V., 129, 131, 132, 134, 138 COURTILLOT, V., BESSE, J., VANDAMME, O., MONTIGNY, R., JAEGER, J.-J. and CAPPETTA, n., 127, 129, 138 COURTILLOT, V., s e e ROCCHIA, R. et al. COURTILLOT, V., s e e VANDAMME,D. et al. COVERT, D. S., s e e CHARLSON,R. J. et al. COVERT, D. S., s e e QUINN, P. K. et al. COVERT, D. S., s e e WAGGONER,A. P. et al. COVERT, D. S., WAGGONER,A. P., WEISS, R. E., AHLQUIST, N. C. and CHARLSON, R. J., 360, 361,363,392 COVEY, C. and THOMPSON, S. L., 85, 92 COVEY, C., GHAN, S. J., WALTON, J. J. and WEISSMAN, P. R., 138 COVEY, C., SCHNEIDER, S. H. and THOMPSON, S. L., 99, 135, 138 COVEY, C., s e e HOFFERT, M. I. and COVEY, C. Cox, D. I., s e e PARKER, D. E. and Cox, D. I. CRADDOCK, J. M., 156, 183 CRAIG, G., s e e LIGHTHILL,J. et al. CRAIG, H., CHOU, C. C., WELHAN, J. A., STEVENS, C. M. and ENGELKEMEIR,A., 355,392 CRAIG,R. A., 410, 430 CROCKET, J. H., OFFICER, C. B., WEZEL, F. C. and JOHNSON, G. D., 134, 138 CROFr, S. K., 100, 138 CROLL, J., 30, 61 CROSSON,W. L., s e e SMrrn, E. A. et al. CROSSON,W. L., SMITH,E. A. and COOPER,H. J., 270 CROWLEY, J. and NORTH, G. R., 22, 33 CROWLEY, J., s e e CROWLEY,T. J. et al.
References Index CROWLEY, T., 80 CROWLEY, T. J., 34, 61, 92, 228, 235 CROWLEY, T. J. and MITCHELL, J. F. B., 33 CROWLEY, Z. J. and NORTH, G. R., 90, 92, 99, 138 CROWLEY, Z. J., CROWLEY, J. and NORTH,G. R., 61 CROWLEY, T. J., KIM, K. Y., MENGEL, J. G. and SHORT, D. A., 34, 61 CROWLEY, T. J., see NORTH, G. R. and CROWLEY, T.J. CROWLEY, T. J., s e e SHORT, D. A. et al. CROWLEY, T., s e e MAIER-REIMER, E. et al. CROZAT, G., 356, 392 CRUTZEN, P. J., 101,102, 138,401,413,430 CRUTZEN, P. J. and ANDREAE, M. O., 376, 392 CRUTZEN, P. J. and BIRKS, J. W., 347, 392 CRUTZEN, P. J., s e e GRAEDEL, T. E. and CRUTZEN, P.J. CRUTZEN, P. J., s e e HAO, W. M. et al. CRUTZEN, P. J., s e e LANGNER, J. et al. CRUTZEN, P. J., s e e SANHUEZA,E. et al. CRUTZEN, P. J., s e e SCHARFFE, D. et al. CRUTZEN, P. J., s e e SEILER, W. and CRUTZEN, P. J. CRUZ, F., s e e JAUREGUI, E. et al. CRUTZEN, P. J., s e e ZIMMERMAN,P. R. et al. CUBASCH, U., s e e GATES, W. L. et al. CULLIS, C. F. and HIRSCHLER, M. M., 357, 392 CUNNINGHAM, G. L., s e e SCHLESINGER,W. H. et al. CURRIE, R. G., 199, 201,202, 235 CURRIE, R. G. and FAIRBRIDGE,R. W., 199, 235 CURRIE, R. G. and O'BRIEN, D. P., 199, 235 CURRY, J. A. and EBERT, E. E., 257, 276 CZAMANSKE, G. K., s e e CAMPBELL, I. H. et al. D'HONDT, S., KELLER, G. and STALLARD, R. F., 118, 139 D'HONDT, S., s e e SIGURDSSON,n. et al. DABBERDT, W. F. and DAVIS, P. A., 437,469, 492, 510 DAHL, J., s e e VENKATESAN, M. I. and DAHL, J. DAHL-JENSEN, D., s e e DANSGAARD,W. et al. DAHL-JENSEN, D., s e e TAYLOR, K. C. et al. DAHNI, R. R., s e e MCAVANEY, B. J. et al. DAHNI, R. R., s e e POWER, S. B. et al. DALRYMPLE, G. B., s e e SHARPTON, V. L. et al. DALU, G., 277 DAMON, P. E., 200 DAMON, P. E., LERMAN, J. C. and LONG, A., 235 DAMON, P. E., s e e JIRIKOVIC, J. and DAMON, P. E. DANARD, M., GRAY, M. and LYv, G., 46, 61 DANSGAARD, W. et al., 226, 235 DANSGAARD, W., JOHNSEN, S. J., CLAUSEN, n. B., DAHL-JENSEN, D., GUNDESTRUP, N. S., HAMMER, C. U., HVLDBORG, C. S., STEFFENSEN, J. P., SVELNBJORNSDOTTIR, A. E., JOUZEL, J. and BEND, G., 25, 58, 61,517, 534 DANSGAARD, W., JOHNSON, S. J., CLAUSEN, n. B. and LANGWAY JR., C. C., 522, 523,530, 533
564
DANSGAARD, W., s e e HAMMER, C. U. et al. DANSGAARD, W., s e e JOHNSEN, S. J. et al. DANSGAARD, W., s e e MAYEWSKI, P. A. et al. DANSGAARD, W., WHITEAND, J. W. C. and JOHNSON, S. J., 517, 534 DAOHAN, C., LINZHONG, L. and JIAQING, Z., 102, 138 DAo-YI, X., QIN-WEN, Z., YI-YIN, S., YAN, Z., ZHI-FANG, C. and JIN-WEN, n., 120, 138 DARRELL, W. L., s e e GUPTA, S. K. et al. DARNELL, W. L., STAYLOR, W. F., GUPTA, S. K., RITCHEY, N. A. and WILBER, A. C., 265, 276 DAUM, P. H., s e e TEN BRINK, H. M. et al. DAVE, J. V., s e e SEKERA, Z. and DAVE, J. V. DAVENPORT, S. A. et al., 102, 139 DAVIDSON, C. I., s e e MAYEWSKI, P. A. et al. DAVIDSON, K. A., s e e TWOMEY, S. et al. DAVIES, R. E., s e e DE GRUIJL, F. R. et al. DAVIES, R. E., s e e URBACH, F. et al. DAVIES, R., s e e COAKLEYJR., J. A. and DAVIES, R. DAVIES, T. D., s e e GOODESS, C. M. et al. DAVIS, P. A., s e e DABBERDT, W. F. and DAVIS, P. A. DAVIS, V. J., s e e BERRESHEIM,H. et al. DE ABREU S,~, L. D., s e e SHUTTLEWORTH, W. J. et al. DE ANGELIS, M., BARKOV, N. I. and PETROV, V. N., 24, 61, 351,392 DE BEAULIEU, J. L., s e e GUIOT, J. et al. DE DILVA, F., s e e ETHERIDGE, D. M. et al. DE GRUIJL, F. R., s e e MADRONICH, S. and DE GRUIJL, F. R. DE GRUIJL, F. R., STERENBORG, H. J. C. M., FORBES, P. D., DAVIES, R. E., COLE, C., KELFKENS, n., VAN WEELDEN, n., SLAPER, n. and VAN DER LEUN, J. C, 420, 430 DE MORA, S. J., s e e ANDREAE, M. O. et al. DE MORALS, J. C., s e e SHUTTLEWORTH,W. J. et al. DE OLIVEIRA, A. E., s e e S ALATI, E. et al. DE PAULA SILVA FILHO, V., s e e SHUTTLEWORTH, W. J. et al. DE SILVA, F., s e e PEARMAN, G. I. et al. DE SILVA, S. L., WOLFF, J. A. and SHARPTON, V. L., 134, 139 DE VRIES, Z. J., 223,235 DEAN, J. S., 194, 235 DEAN, W. E., s e e ZACHOS, J. C. et al. DEBLONDE, G. and PELTIER, W. R., 44, 50, 61 DEERING, D. W., s e e AHMAD, S. P. and DEERING, D.W. DEE GENIO, A. D., s e e CESS, R. D. et al. DEE GENIO, A. D., s e e Fu, R. et al. DELANY, A. C., s e e PROSPERO, J. M. et al. DE LAUBENFELS, M. W., 95, 139 DELGENIO, A., s e e HANSEN, J. et al. DELMAS, R. J., ASCENCIO, J.-M. and LEGRAND, M., 524, 534
References
Index
DELMAS, R. J., s e e LEGRAND,M. R. et al. DELMAS, R. J., s e e RAYNAUD,D. et al. DE LuIsI, J., 425,430 DELWORTH, T., MANABE, S. and STOUFFER, R. J., 226, 235 DEMARIA, M. and KAPLAN, J., 310, 311 DEMARIA, M., s e e SILVADIAS, P. L. et al. DEMURE, W. B., GOLDEN, D. M., MOLINA, M. J., HAMPSON, R. F., KURYLO, M. J., HOWARD, C. J. and RAVlSHANKARA,A. R., 430 DENN, F. M., s e e MINNIS, P. et al. DENTON, G. H. and ARMSTRONG,R. L., 82, 92 DENTON, G. H. and HUGHES, T. J., 61 DENTON, G. H., s e e BROECKER,W. S. and DENTON, G.H. DENTON, G. H., s e e HUGHES, T. J. et al. DENTON,G. H., s e e PORTER, S. C. and DENTON,G. H. DgQUE, M., s e e CESS, R. D. et al. DEQUE, M., s e e ROYER, J. F. et al. DEROME, J., s e e MICHAUD,R. and DEROME,J. DI~SALMAND,F., 376, 392 DESER, C. and BLACKMON,M. L., 227, 235 DESER, C. and WALLACE, J. M., 211,222, 235 DESER, C., s e e WRIGHT, P. B. et al. DESHLER, T., HOFMANN, D. J., HEREFORD, V. and SUTTER, C. B., 407, 416, 430 DETTWlLLER, J., 151, 183 DEWEY, K. F., 278 DIAZ, H. F., 199, 200, 235 DIAZ, H. F. and BRADLEY, R. S., 198, 231,235 DIAZ, H. F. and KILADIS,G. N., 220, 221,235 DIAZ, H. F. and MARKGRAF, V., 207, 222, 227, 235 DIAZ, H. F. and PULWARTY, R. S., 218, 222, 223, 235 DIAZ, H. F., BRADLEY, R. S. and EISCHEID, J. K., 155, 166, 183 DIAZ, H. F., s e e BRADLEY, R. S. et al. DIAZ, H. F., s e e Fu, C. et al. DIAZ, H. F., s e e HUGHES, M. K. and DIAZ, H. F. DIAZ, H. F., s e e JONES, P. D. et al. DIAZ, H. F., s e e KARL, T. R. et al. DIAZ, H. F., s e e KILADIS,G. N. and DIAZ, H. F. DIAZ, H. F., s e e PARTHASARATHY,B. et al. DICKEY, J. O., s e e HIDE, R. et al. DICKINS, J. M., 119, 139 DICKINSON, R. E., 270, 276,435, 464, 469 DICKINSON, R. E. and HENDERSON-SELLERS, A., 437,461,463,465,469 DICKINSON, R. E. and KENNEDY, P. J., 461, 469, 541,552 DICKINSON, R. E., HENDERSON-SELLERS, A. and KENNEDY, P. J., 467, 469 DICKINSON, R. E., HENDERSON-SELLERS, A., KENNEDY, P. J. and WILSON, M. F., 467, 469 DICKINSON, R. E., PINTY, B. and VERSTRAETE, M. M., 265,276
565
DICKINSON,R. E.,
s e e HENDERSON-SELLERS,A. et al. DICKINSON, R. E., s e e PENNER, J. E. et al. DICKSON, C. R., s e e ANGELL, J. K. et al. DICKSON, R. R., 227 DICKSON, R. R., MEINCKE, J., MALMBERG, S.-A. and LEE, A. J., 88, 92, 235 DICKSON, S. M., s e e ERICKSON, D. J. and DICKSON, S.M. DIETACHMAYER, G. S., s e e HOLLAND, G. J. and DIETACHMAYER,G. S. DIFFEY, B. L., s e e MCKINLAY, A. F. and DIFFEY, B.L. DIPASQUALE, R. C., s e e WHITLOCK,C. H. et al.279 DIRMEYER, P. A., 470 DIRMHIRN, I. and EATON, F. D., 46, 62 DLUGOKENCKY, E. J., MASAIRE, K. A., LANG, P. M., TANS, P. P., STEELE, L. P. and NISBET, E. G., 322, 344 DOBSON, G. M. B., 408,430 DODD, J. K., s e e CARLSON, T. N. et al. DOEHNE, E., s e e MARGOLIS, S. V. et al. DUELLING, D. R., s e e MINNIS, P. et al. DONALL, E. G., s e e SEAMAN, N. L. et al. DONESO, L., s e e SANHUEZA,E. et al. DONN, W. L. and SHAW, D. M., 32, 62, 75, 92 DONNELL, C. A., 154, 183 DONOSO, L., s e e SCHARFFE,D. et al. DONOVAN, S. K., 114, 139 DORSEY, H. G., s e e OSTLUND,n. G. et al. DOUGLAS, A. V., CAYAN, D. R. and NAMIAS, J., 168, 183,226, 235 DOUGLAS, A. V., s e e CAYAN, D. R. and DOUGLAS, A.V. DOUGLAS, I., 440, 470 DOUGLAS, R. G., s e e SAVlN, S. et al. DOUROJEANNI, M. J., s e e SALATI, E. et al. DOUTHITT, C. B., s e e RICH, T. H. et al. DOWNEY, W. K., s e e JOHNSON, D. R. and DOWNEY, W.K. DOWSETT, H. J. and LOUBERE, P., 117, 139 DREESEN, R., s e e SANDBERG,C. A. et al. DREGNE, H. E., 441,465, 470 DREGNE, H. E., s e e TUCKER, C. J. et al. DREVER, J. I. and ZOBRIST,J., 547, 552 DRUILHET, m., s e e ESTOURNEL,C. et al. DUCE, R. A., LISS, P. S., MERRILL, J. T., ATLAS, A. L., BUAT-MENARD, P., HICKS, B. B., MILLER, J. M., PROSPERO,J. M., ARIMOTO,R., CHURCH, T. M., ELLIS, W., GALLOWAY, J. N., HANSEN, L., JICKELLS, T. D., KNAP, A. H. and REINHARDT, K. H., 350, 364, 380, 392 DUCE, R. A., s e e BETZER, P. R. et al. DUCE, R. A., s e e PROSPERO, J. M. et al. DUCE, R. A., s e e UEMATSU,M. et al. DUCRET, J., s e e CACHIER, H. and DUCRET, J. DUDEK, M. P., s e e WANG, W.-C. et al.
References
Index
DUDEK, M. P., WANG, W.-C. and LIANG, X.-Z., 336, 337, 345 DUDHA, A., s e e TAYLOR, F. W. et al. DUFFY, A., s e e IMBRIE,J. et al. DULANEY, W., s e e GOWARD, S. N. et al. DUMEIL, L., s e e BARNETT, T. P. et al. DUNN, D.A., s e e MOORE, T. C. et al. DUNNING, G. R. and HODYCH,J. P., 127, 139 DUPLESSY, J. C., LABEYRIE, L. and BLANC, P. L., 43, 62 DUPLESSY, J. C., LABEYRIE, L., ARNOLD, M., PATERNE, M., DUPRAT, J. and VAN WEERING, T. C. E., 47 DUPLESSY, J. C., s e e LABEYRIE, L. D. and DUPLESSY,J. C. DUPLESSY, J. C., s e e LABEYRIE,L. D. et al. DUPLESSY, J. C., s e e PESTIAUX,P. et al. DUPLESSY, J. C., SHACKLETON, N. J., FAIRBANKS, R. G., LABEYRIE, L., OPPO, D. and KALLEL, N., 88, 92 DUPLESSY, J. CL., LABEYRIE, L. D., ARNOLD, M., PATERNE, M., DUPRAT, J. and VAN WEERING, T. C. E., 24, 62 DUPRAT, J., s e e DUPLESSY,J. CL. et al. DURBIDGE, T. l . , s e e HENDERSON-SELLERS, A. et al. DURBIDGE, T. B., s e e MCGUFFIE, K. et al. DURKEE, P. A., 377, 392 DURKEE, P. A., PFEIL, F., FROST, E. and SHEMA, R., 364, 392 DURKEE, P. A., s e e COAKLEYJR., J. A. et al. DUTTON, E. G. and CHRISTY, J. R., 205, 236 DYE, D. G., s e e GOWARD, S. N. et al. DYMEK, M., s e e BRASSEUR, G. P. et al. DYMNIKOV, V., s e e CESS, R. D. et al. DZIETARA, S. and JANICOT, S., 457,470 EAST, C. s e e OKE, T. R. and EAST, C. EASTERLING, D. R., s e e KARL, T. R. et al. EATON, F. D., s e e DIRMHIRN,I. and EATON, F. D. EATON, F. D., s e e WHITE, J. M. et al. EBBESMEYER, C. C., CAYAN, D. R., MCLAIN, D. R., NICHOLS, F. H., PETERSON, D. H. and REDMOND, K. T., 227, 236 EBERT, E. E., s e e CURRY, J. A. and EBERT, E. E. EBINGER, C. J., 127 EBINGER, C. J., YEMANE, T., WOLDEGABRIEL, G., ARONSON, J. L. and WALTER, R. C., 139 ECKHOLM, E. and BROWN, L. R., 435, 470 ECKSTEIN, D., s e e BRIFFA, K. R. et al. EDDY, J. A., 175, 183,200, 236 EDDY, J. A., GILLILAND, R. L. and Horr, D. V., 199, 236 EDDY, J. A., GILMAN, D. L., and TROTTER, D. E., 236 EDDY, J. A., GILMAN, P. A. and TROTTER, D. E., 200
566
EDDY, J. A., s e e SANTER,B. et al. EHHALT, D. H., RUDOLPH, J. and SCHMIDT, U., 356, 392 EHRMANN, W. U., 119 EHRMANN, W. U. and MACKENSEN,A., 139 EHRMANN, W. U., s e e MACKENSEN, A. and EHRMANN, W. U. EINFELD, W., WARD, D. E. and HARDY, C. C., 353, 392 EISCHEID, J. K., s e e BRADLEY, R. S. et al. EISCHEID, J. K., s e e DIAZ, H. F. et al. EISCHEID, J. K., s e e PARTHASARATHY,B. et al. EKDAHL, C. A., s e e KEELING,C. D. et al. EL-BADRY, M. A., 435, 470 ELBERT, W., s e e ANDREAE,M. O. et al. ELLIOT, D. H., s e e HEIMAN,A. et al. ELLIOTT, W. P., s e e GAFFEN, D. J. r al. ELLIS, H. T. and PUESCHEL, R. F., 379, 392 ELLIS, W., 154, 183 ELLIS, W., s e e DUCE, R. A. et al. ELSAESSER, H. W., MACCRACKEN, M. C., WALTON, J. J. and GROTCH, S. L., 158, 183 ELSBERRY, R. L., s e e FIORINO, M. J. and ELSBERRY, R. L. ELSNER, J. B. and TSONIS, A. A., 158, 179, 183 ELSOM, D. M. and MEADEN, G. T., 504, 510 ELSON, L. S., s e e WATERS,J. W. et al. ELSTON, W. E. and TWIST, D., 128, 139 ELY, G. A., s e e ROCHE, A. E. et al. EMANUEL, K. A., 310, 311 EMANUEL, W. R., SHUGART, n. n. and STEVENSON, M. P., 466, 470 EMERY, W. J., s e e PICKARD, G. L. and EMERY, W. J.
EMERY, W. J., s e e ROTH, M. et al. EMILIANI, C., 22, 62, 100, 139 EMILIANI, C., KRAUS, E. B. and SHOEMAKER, E. M., 100, 139 ENFIELD, D. B., 207, 222, 223,236 ENFIELD, D. B. and Clo, S. L., 199, 222, 227, 236 ENGARDT, M. and RODHE, H., 384, 392 ENGELHARDT, W. V., MATTHAI, S. K. and WALZEBUCK,J., 122, 139 ENGELKEMEIR, A., s e e CRAIG, H. et al. ENSOR, D. S., PORCH, W. M., PILAT, M. J. and CHARLSON, R. J., 347, 392 ENTEKHABI, D., s e e NICHOLSON, S. E. and ENTEKHABI, D. EPHRAUMS, J. J., 2, 6, 15 EPHRAUMS, J. J., s e e HOUGHTON,J. J. et al. EPHRAUMS, J. J., s e e HOUGHTON,J. T. et al. EPSHTEYN, O. G., 73, 92 ERICKSON III, D. J., s e e GHAN, S. J. et al. ERICKSON, D. J. and DICKSON, S. M., 102, 139 ERONEN, M., s e e BRIFFA, K. R. et al. ESBENSEN, S. K. and KUSHNIR,V., 210, 236 ESCH, M., s e e BENGTSSON,L. et al.
References Index ESCRITOR, F., s e e HUNTLEY, M. E. et al. ESHET, Y., 117, 120, 121, 139 ESTES, R. and HUTCHISON, J. H., 82, 92 ESTOURNEL, C., VEHIE, R., GUEDALIA, D., FONTAN, J. and DRUILHET, A., 486, 487, 510 ETHERIDGE, D. M., PEARMAN, G. I. and DE SILVA, F., 447,470 ETHERIDGE, D., PATTERSON, G. R. and PLATT, C. M. R., 364, 392 ETHERIDGE, D., s e e PEARMAN, G. I. et al. EUROPEAN TIMBER TRENDS and PROSPECTS, 444, 470 EVANS, J. L., 310, 311 EVANS, J. L., s e e LIGHTHILL, J. et al. EVANS, J. L., s e e RYAN, B. F. et al. LYRE, J. R., 263,276 LYRE, J. R., KELLY, G. A., MCNALLY, A. P., ANDERSSON, E. and PERSSON, A., 263,276 FABRE, J., s e e PETIT-MAIRE, J. R. et al. FABRY, C. and BUISSON, M., 408, 431 FAIRALL, C. W., KEPERT, J. D. and HOLLAND, G. J., 310, 311 FAIRBANKS, R. G., 24, 62 FAIRBANKS, R. G., s e e BARD, E. et al. FAIRBANKS, R. G., s e e CHARLES, C. D. and FAIRBANKS,R. G. FAIRBANKS, R. G., s e e COLE, J. E. et al. FAIRBANKS, R. G., s e e DUPEESSY, J. C. et al. FAIRBANKS, R. G., s e e GUILDERSON,TH. P. et al. FAIRBANKS, R. G., s e e MILLER, K. G. et al. FAIRBANKS, R. G., s e e MIX, A. C. and FAIRBANKS, R.G. FAIRBRIDGE, R. W., s e e CURRIE, R. G. and , FAIRBRIDGE, R. W. FALISE, E., s e e BRASSEUR, G. P. et al. FALKOWSKI, P. G., KIM, Y., KOLBER, Z., WILSON, C., WIRICK, C. and CESS, R., 377, 392, 545, 552 FALL, R., s e e FEHSENFELD, F. et al. FAN, D., YANG, R. and HUANG, Z., 126, 139 FAO, 434, 440, 445,449, 470, 472 FAO/UNEP, 464, 470 FARMAN, J. C., GARDINER, B. G. and SHANKLIN, J. D., 399, 406, 428, 431 FARMER, G., s e e JONES, P. D. et al. FARRAR, E., s e e B AKSI, A. K. and FARRAR, E. FARRELL, B. and WATTERSON, I. G., 305, 311 FASTHOOK, J. L., s e e HUGHES, T. J. et al. FAURE, H., s e e ADAMS, J. M. et al. FAWCETT, P. J., s e e BARRON, E. J. et al. FEARS, T., s e e SCOTTO, J. et al. FEDORENKO, V. A., s e e CAMPBELL, I. H. et al. FELLY, R. A., s e e BETZER, P. R. et al. FEGLEY, B., s e e PRINN, R. G. and FEGLEY, B. et al. FEHSENFELD, F. and LIu, S. C., 400, 431
567
FEHSENFELD, F., CALVERT, J., FALL, R., GOLDAN, P., GUENTHER,A. B., HEWITT, C. N., LAMB, B., LIU, S., TRAINER, M., WESTBERG, H. and ZIMMERMAN, P., 356, 392 FELDSTEIN, S. B., s e e KILADIS, G. N. and FELDSTEIN, S. B. FELLOWS, L., s e e MALINGREAU, J. P. et al. FEES, E. and KELLER, R., 440, 470 FELTON, E. A., s e e RICH, T. H. et al. FENG, J. Z. and PETZOLD, D. E., 497, 510 FENIET-SAIGNE, C., s e e LEGRAND, M. R. et al. FENNER, J. M., s e e CORLISS, B. H. et al. FENNESSY, M., s e e SUD, Y. C. and FENNESSY, M. FERAUD, G., 144 FEREK, R. J., s e e ANDREAE, M. O. et al. FERGUSON, W. S., GRIFFIN, J. J. and GOLDBERG, E. D., 350, 392 FERMAN, M. A., s e e WOLFF, G. R. et al. FERRARE, R. A., FRASER, R. S. and KAUFMAN,Y. J., 363,392 FERRARE, R. A., s e e KAUFMAN, Y. J. et al. FERRIER, B., s e e SIMPSON, J. S. et al. FICHEFET, TH., s e e BERGER, A. et al. FICHEFET, TH., s e e GALLI~E, H. et al. FIORINO, M. J. and ELSBERRY, R. L., 305, 311 FISCH, G., s e e SHUTTLEWORTH,W. J. et al. FISCHER, A. G., 75, 92 FISCHER, K., s e e BERGER, W. H. et al. FISHER, R., s e e GRAETZ, D. et al. FISHMAN, J., 319, 339, 345 FITZGERALD, J. W. and SPYERS-DURAN, P. A., 373, 392 FITZHARRIS, B. B., s e e SALINGER,M. J. et al. FLAGAN, R. C., s e e PANDIS, S. N. et al. FLAGAN, R. C., s e e ZHANG, S.-H. et al. FLEMING, W. n., s e e HEIMAN, A. et al. FLETCHER, J. O., s e e Fu, C. et al. FLINT, S. D., s e e CALDWELL, M. M. et al. FLOHN, H. and KAPALA, A., 228, 236 FLOHN, H., KAPALA, A., KNOCHE, H. R. and MACHEL, H., 200, 236 FLOHN, H., s e e HENSE, A. et al. FLOHN, H., s e e SANTER, B. et al. FLOHN, H.FLOHN, H., KAPALA, A., KNOCHE, H. R. and MACHEL, H., 228 FLOWER, B. P., s e e BROECKER, W. S. et al. FLOWER, D. A., s e e B ARATH, F. T. et al. FLOWER, D. A., s e e WATERS, J. W. et al. FLOWERS, E. C., s e e PETERSON, J. T. et al. FLYGER, H., HEIDAM, N. Z., HANSEN, K., MEGAW, W. J., WALTHER, E. G. and HOGAN, A. W., 381, 392 FOLAND, K. A., s e e HEIMAN, A. et al. FOLLAND, C. K. and PARKER, D. E., 153, 183 FOLLAND, C. K., KARL, T. R. and VINNIKOV, K. YA., 155, 157, 158, 160, 164, 170, 171, 183, 437,470
References
Index
FOLLAND, C. K., KARL, T. R., NICHOLLS, N., NYENZI, B. S., PARKER, D. E. and VINNIKOV,K. YA., 155, 157, 158, 160, 164, 170, 171, 184 FOLLAND, C. K., PALMER, T. N. and PARKER, D. E., 38, 62, 166, 183,229, 236 FOLLAND, C. K., s e e BOTTOMLEY,M. et al. FOLLAND, C. K., s e e PARKER, D. E. and FOLLAND, C.K. FOLLAND, C. K., s e e PARKER, D. E. et al. FOLLAND, C. K., s e e ROWELL, D. P. et al. FONTAN, J., s e e ESTOURNEL,C. et al. FORBES, P. D., s e e DE GRUIJL, F. R. et al. FORGAN, B. W., 364, 393 FORGAN, B. W., s e e LYONS, T. J. and FORGAN, B. W. FORSYTH D., s e e LUYENDYK,B. et al. FORTELIUS, C. and HOLOPAINEN,E., 268, 276, 286, 311 FOSTER, J. L. and CHANG, A. T. C., 272, 276 FOSTER, J. L., s e e CHANG, A. T. C. et al. FOUg~L, P. and LEAN, J., 199, 236 FOUQUART, Y. and ISAKA, H., 375,393 FOUQUART, Y., BONNEL, B., BROGNIEZ, G., BURIEZ, J. C., SMITH, L., MORCRETTE, J. J. and CERF, A., 367, 393 FOUQUART, Y., BONNEL, B., CHAOUI ROQUAI, M., SANTER, R. and CERF, A., 367,393 FOWELL, S. J., s e e OLSEN, P. E. et al. Fox, P. T., s e e JAMES, R. W. and Fox, P. T. FRAEDRICH, K. and BANTZER,C., 194, 236 FRANCS, L. A. and FRANCES, J. E., 73, 92 FRAKES, L. A., FRANCIS, J. E. and SYTKUS, J. I., 71, 73, 92 FRAKES, L. A., s e e HAYES, D. E. and FRAKES, L. A. FRAMJI, K. K. and MAHAJAN, I. K., 439, 470 FRANCES, J. E., s e e FRAKES, L. A. and FRANCES, J. E. FRANCES, J. E., s e e FRAKES, L. A. et al. FRANCEY, R., s e e COOK, E. R. et al. FRANKE, R. and CHASIN, B., 441,470 FRANKIGNOUL, C., 226, 236 FRANKIGNOUL, C. and HASSELMANN,K., 43, 62 FRASER, 447 FRASER, J. R., 300, 311 FRASER, J. R., s e e MCAVANEY, B. J. et al. FRASER, P. J., s e e PEARMAN, G. I. and FRASER, P. J.
FRASER, P. J., s e e PEARMAN,G. I. et al. FRASER, R. S., KAUFMAN, Y. J. and MAHONEY, L., 379,393 FRASER, R. S., s e e FERRARE, R. A. et al. FRASER, R. S., s e e KAUFMAN,Y. J. et al. FREDERICK, J. E., s e e LUBIN, D. et al. FREDERIKSEN, J. S., 309, 311 FREEMAN, K. H. and HAYES, J. M., 75, 92, 549, 552
568
FRERKING,M. A., s e e BARATH,F. T. et al. FRIIS-CHRISTENSEN, E. and LAASEN, K., 175, 179, 184, 200, 236 FRISBIE, P. R., s e e HUDSON, J. G. and FRISBIE, P. R.
FROIDEVAUX, L., s e e WATERS, J. W. et al. FROST, E., s e e DURKEE, P. A. et al. Fu, C., DIAZ, H. F. and FLETCHER, J. O., 211,236 Fu, C., s e e KARL, T. R. et al. Fu, R., DEE GENIO, A. D. and Rossow, W. B., 269, 276 FUGGLE, R. F., 487 FUGGLE, R. F., s e e OKE, T. R. and FUGGLE, R. F. FUGLISTER, F. J., s e e GILMAN, D. L. et al. FUHRER, K., s e e JOHNSEN, S. J. et al. FUJIWHARA,S., 305, 311 FULTON, S. R., s e e SCHUBERT,W. H. et al. FUNG, I. Y., s e e PRENTICE, K. C. and FUNG, I. Y. FUNG, I., s e e HANSEN, J. E. et al. FUNG, I., s e e KAUFMAN,Y. J. et al. FUNG, I., s e e MATTHEWS,E. et al. FYFE, W., s e e APSIMON,H. et al. GAFFEN, D. J., 169, 184 GAFFEN, D. J., BARNETT, T. P. and ELLIOTT, W. P., 228, 236 GAGE, K. S. and REID, G. C., 199, 236 GAL-CHEN, T., s e e TAYLOR, B. L. et al. GALIN, V., s e e CESS, R. D. et al. GALL, R., YOUNG, K., SCHOTLAND,R. and SHMrrz, J., 153, 184 GALLfiE, H., 56, 58, 62 GALLI~E, H., BERGER, A. and SHACKLETON, N. J., 47, 49, 62 GALLfiE, H., s e e BEGGER,A. et al. GALLI~E, H., VAN YPERSELE, J. P., FICHEFET, TH., MARSIAT, I., TRICOT, C. and BEGGER, A., 45, 47, 48, 52, 58, 59, 62 GALLI~E, H., VAN YPERSELE, J. P., FICHEFET, TH., TRICOT, C. and BERGER, A., 45, 58, 62 GALLIMORE, R. G., s e e KUTZBACH, J. E. and GALLIMORE, R. G. GALLO, K. P., MCNAB, A. L., KARL, T. R., BROWN, J. F., HOOD, J. J. and TARPLEY, J. D., 502, 510 GALLO, K. P. s e e KARL, T. R. et al. G ALLO, K., s e e OHRING,G. et al. GALLOWAY, J. N., 358,393 GALLOWAY, J. N., KEENE, W. C., PSZENNY, A. A. P., WHELPDALE, D. M., SIEVERING, H., MERRILL, J. T. and BOATMAN,J. F., 381,393 GALLOWAY, J. N., s e e CHURCH, T. M. et al. GALLOWAY, J. N., s e e DUCE, R. A. et al. GAMMON, R. H., s e e BATES, T. S. et al. GANAPATHY, R., 95, 115, 118, 139 GANOR, E. J., s e e PUEScHEL, R. F. et al. GARADZHA, M. P. and NEZVAL,YE. I., 425, 431
References
Index
GARCIA, R. R.,
see
HAMILTON,K. and GARCIA,R.
R.
GARDINER, B. G., s e e FARMAN, J. C. et al. GARP, 8, 9, 17 GARRELS, R. M. s e e BERNER, R. A. et al. GARSTANG, M., s e e ANDREAE, M. O. et al. GARSTANG, M., s e e SWAp, R. et al. GARSTANG, M., s e e TALBOT, R. W. et al. GASH, J. H. C., s e e SHUTTLEWORTH,W. J. et al. GASPAR, PH., s e e ADEM, J. et al. GATES, W. L., 35, 62, 321,345 GATES, W. L., CUBASCH, U., MEEHL, G. A., MITCHELL, J. F. B. and STOUFFER, R. J., 321, 327, 33 I, 345 GATES, W. L., MITCHELL, J. F. B., BOER, G. J., CUBASCH, U. and MELESHKO, V. P., 33, 62 GATES, W. L., s e e CESS, R. D. et al. GAUDRY, A., s e e NGUYEN, B. C. et al. GAULT, D. E., s e e SCHULTZ, P. H. and GAULT, D. E. GAVIN, J., KUKLA, G. and KARL, T., 545,552 GAVIN, J., s e e KUKLA, G. et al. GAVIN, J., s e e PLANTICO, M. S. et al. GAZA, R. S., s e e KESSLER, R. W. et al. GELDSETZER, H. H. J., GOODFELLOW, W. D., MCLAREN, D. J. and ORCHARD, M. J., 125, 139 GELDSETZER, H. H. J., s e e GOODFELLOW, W. D. et al. GELDSETZER, H. H. J., s e e WANG, K. et al. GELEYN, J. F., s e e TANRE, D. et al. GELLER, M. A. and ALPERT, J. C., 200, 236 GENTHON, C., BARNOLA, J. M., RAYNAUD, D., LORIUS, CL., JOUZEL, J., BARKOV, N. I., KOROTKEVITCH, Y. S. and KOTLYAKOV, V. M., 52, 62 GENTHON, C., s e e JOUZEL, J. et al. GEORGII, H.-W., s e e BORGERMEISTER, S. and GEORGII, H.-W. GERLACH, T. M. and GRAEBER, E. J., 133, 139 GERMAIN, C., s e e LEGRAND, M. R. et al. GERSTEL, J., THUNELL, R. C., ZACHOS, J. C. and ARTHUR, M. A., 110, 139 GERSTL, S. A. and ZARDECKI, A., 98, 139 GEYH, M. A., s e e ROTHLISBERGER, F. and GEYH, M.A. GHAN, S. J., PENNER, J. E. and TAYLOR, K. E., 545, 552 GHAN, S. J., s e e CESS, R. D. et al. GHAN, S. J., s e e COVEY, C. et al. GHAN, S. J., TAYLOR, K. E., PENNER, J. E. and ERICKSON III, D. J., 378,393 GHIL, M. and LE TREUT, H., 41,62 GHIL, M. and VAUTARD, R., 179, 184, 201,236 GHIL, M., s e e LE TREUT, H. et al. GHIL, M., s e e VAUTARD, R. and GHIL, M. GIBSON, G. G., s e e HARRISON, E. F. et al. GIBSON, G. G., s e e MINNIS, P. et al.
569
GIES, H. P., s e e RoY, C. T. et al. GILL, A. E., 282, 288, 305, 311 GILLE, J. C., 431 GILLE, J. C. and LYJAK, L. V., 411, 431 GILLE, J. C. and RUSSELL III, J. M., 411, 431 GILLETT, R. W., s e e AYERS, G. P. et al. GILLETT, R. W., s e e BERRESHEIM,H. et al. GILLETTE, D. A. and BLIFFORD, I. H., 381, 382, 393 GILLILAND, R. L., 175, 184 GILLILAND, R. L., s e e EDDY, J. A. et al. GILMAN P. A., s e e EDDY, J. A. et al. GILMAN, D. L., FUGLISTER, F. J. and MITCHELLJR., J. M., 191,192, 236 GILMAN, D. L., s e e EDDY, J. A. et al. GILMORE, J. S., s e e ORTH, C. J. et al. GILMOUR, I., s e e WOLBACH, W. S. et al. GILMOUR, I., WOLBACH, W. S. and ANDERS, E., 98, 101,139, 140 GIORGI, F., 321 GIORGI, F. and MEARNS, L. O., 345 GIVEN, Q., s e e BOERSMA, A. et al. GLANCY, R. T., s e e BRYANT, H. K. et al. GLANTZ, M. H., 229, 236, 438,470 GLANTZ, M. H., KATZ, R. W. and NICHOLLS, N., 207, 236 GLASS, B. P., 118, 140 GLEN, W., 96, 129, 134, 140 GLOERSEN, P., s e e PARKINSON, C. L. and GLOERSEN, P. GOBLE, R., s e e YERSEL, M. and GOBLE, R. GODINEZ, L., s e e JAUREGUI, E. et al. GODOWITCH, J. M., 496, 510 GODOWITCH, J. M., s e e CHING, J. K. S. et al. GODOWITCH, J. M., s e e CLARKE, J. F. et al. GOETZ, S. J., s e e HALL, F. G. et al. GOLDAN, P., s e e FEHSENFELD, F. et al. GOLDBERG, B., s e e CORRELL, D. L. et al. GOLDBERG, E. D., s e e FERGUSON, W. S. et al. GOLDBERG, R., s e e RIND, D. et al. GOLDEN, D. M., s e e DEMORE, W. B. et al. GOLDMAN, A., s e e MANKIN, W. G. et al. GOLDSTEIN, W., s e e MOHNEN, V. A. et al. GOODESS, C. M., PALUTIKOF, J. P. and DAVIES, T. D., 56, 59, 62 GOODESS, C. M., s e e BRADLEY, R. S. et al. GOODESS, C. M., s e e JONES, P. D. et al. GOODESS, C. M., s e e KELLY, P. M. et al. GOODESS, C. M., s e e SEAR, C. B. et al. GOODFELLOW, W. D., 114 GOODFELLOW, W. D. and MCLAREN, D. J., 125 GOODFELLOW, W. D., GELDSETZER, H. H. J., MCLAREN, D. J., ORCHARD, M. J. and KLAPPER, G., 124, 140 GOODFELLOW, W. D., NOWLAN, G. S., MCCRACKEN, A. D., LENZ, A. C. and GREGOIRE, D. C., 114, 116, 125, 126, 140
References
Index
GOODFELLOW, W. D., s e e GELDSETZER, H. H. J. et al. GOODFELLOW, W. D., s e e MCLAREN, D. J. and GOODFELLOW, W. D. GOODRICH, V. R., s e e CORRELL, D. L. et al. GORDON, A. L., ZEBIAK, S. E. and BRYAN, K., 226, 236 GORE, A., 4, 17 GORNITZ, V., 459, 470 GORNITZ, V. and SOLOW,A., 231,236 GORNITZ, V., s e e HENDERSON-SELLERS, A. and GORNITZ, V. GORSE, J., 465,470 GOUGH, D., 81,92 GOUVEIA, A. D., s e e SATHYENDRANATH,S. et al. GoT, A. J., s e e ALLEY, R. B. et al. GoT, A. J., s e e TAYLOR, K. C. et al. GOWARD, S. N., 492, 502, 510 GOWARD, S. N., MARKHAM, B., DYE, D. G., DULANEY, W. and YANG, J., 269, 276 GRAEBER, E. J., s e e GERLACH, T. M. and GRAEBER, E.J. GRAEDEL,T. E. and CRUTZEN,P. J., 447, 470 GRAEME, E., s e e RoY, C. T. et al. GRAETZ, D., FISHER, R. and WILSON, M. F., 440, 470 GRAHAM, N., 168, 184 GRAHAM, N. E. and BARNETT,T. P., 209, 237 GRAHAM, N. E., MICHAELSEN, J. and BARNETT, T. P., 214, 237 GRAHAME, N. S., s e e MITCHELL,J. F. B. et al. GRAM, M. B., s e e B ARATH, F. T. et al. GRANIER, C. and BRASSEUR, G. P., 415, 431 GRANIER, C., s e e BRASSEUR, G. P. and GRANIER, C. GRANIER, C., s e e HAUGLUSTAINE,D. A. et al. GRANIER, C., s e e MADRONICH,S. and GRANIER,C. GRANT, K., s e e MILLER, A. J. et al., GRANT, W. B., 425, 431 GRANT, W. B. et al., 413, 431 GRAS, J. L., 372, 393 GRASSL, H., 360, 367, 368, 393 GRASSL, H. and LEVKOV, L., 368,393 GRATZ, A. J., NELLIS, W. J. and HINSEY, N. A., 134, 140 GRAUSTEIN, W. C., s e e SAVOIE, D. L. et al. GRAY, M., s e e DANARD, M. et al. GRAY, W. M., 310, 311 GRAY, W. M., s e e LANDSEA, C. W. and GRAY, W. M. GRAY, W. M., s e e LIGHTHILL,J. et al. GRAY, W. M., SHEAFFER, J. D. and KNAFF, J. A., 213,237 GRAYBILL, D. A. and SHIYATOV, S. G., 194, 237 GRECO, A. M., s e e BETZER, P. R. et al. GRECO, A. M., s e e SWAp, R. et al. GRECO, S., s e e SWAP, R. et al.
570
GREENBERG,J. P., s e e ZIMMERMAN,P. R. et al. GREENLAND ICE-CORE PROJECT MEMBERS (GRIP), 25, 62, 226, 237, 389, 393,534 GREENWALD, T. J., s e e STEPHENS, G. L. and GREENWALD, T. J. GREENWOOD, D. R., s e e WING, S. L. and GREENWOOD, D. R. GREGOIRE, D. C., s e e GOODFELLOW,W. D. et al. GREGORY R. T., s e e RICH, T. H. et al. GREGORY, G. L., s e e ANDREAE, M. O. et al. GREGORY, J. M., 327, 333,334, 345 GREGORY, J. M. and MITCHELL, J. F. B., 179, 180, 184 GRIEVE, R. A. F., 118, 140 GRIFFIN, J. J., s e e FERGUSON,W. S. et al. GRIFFIS, K. and CHAPMAN, D. J., 98, 140 GRIFFITHS, D. C., s e e TEGART, W. J. McG. et al. GRIMM, E. C., JACOBSON, G. L., WATTS, W. A., HANSEN, B. C. and MAASCH, K. A., 25, 62 GRIMMOND, C. S. B., 491,493, 511 GRIMMOND, C. S. B. and OKE, T. R., 493, 494, 498, 511 GRIMMOND, C. S. B., OKE, T. R. and CLEUGH, H. A., 48 I, 493,494, 500, 511 GRIMMOND, C. S. B., s e e SCHMID, H. P. et al. GRINSPOON, D., s e e ZAHNLE, K. and GRINSPOON, D. GROISMAN, P. Y., KARL, T. R. and KNIGHT, R. W., 58, 62 GROISMAN, P. YA., KOKNAEVA, V. V., BELOKRYLOVA,T. A. and KARL, T. R., 164, 184 GROISMAN, P. YA., s e e JONES, P. D. et al. GROISMAN, P. YA., s e e VINNIKOV,K. YA. et al. GROOTES, P. M., s e e ALLEY, R. B. et al. GROOTES, P. M., STUIVER, M., WHITE, J. W. C., JOHNSEN, S. and JOUZEL,J., 25, 62 GROSSMAN, A., s e e SHINE, K. P. et al. GROTCH, S. L., s e e ELSAESSER, H. W. et al. GROVE, A. T., s e e STREET, F. A. and GROVE, A. T. GROVE, J. M., 169, 184, 196, 237 GRUBER, A., s e e OHRING, G. et al. GRUSZCZYNSKI, M., HALAS, S., HOFFMAN, A. and MALKOWSKI, K., 120, 140 GRUSZCZYNSKI, M., HALAS, S., HOFFMAN, A., MALKOWSI~, K. and VEIZER,J., 120, 140 GUARD, C. P., s e e LIGHTHILL,J. et al. GUEDALIA, D., s e e ESTOURNEL,C. et al. GUENTHER, A. B., s e e FEHSENFELD,F. et al. GUENTHER, P. R., s e e KEELING,C. D. et al. GUETTER, P. J., s e e KUTZBACH,J. E. and GUETTER, P.J. GUILDERSON, TH. P., FAIRBANKS, R. G. and RUBENSTONE, J. L., 24, 36, 62 GUIOT, J., PONS, A., DE BEAULIEU, J. L. and REmLE, M., 22, 62 GUIOT, J., s e e BERGER, A. et al. GUMERMAN, G. J., 194, 237
References
Index
GUNDESTRUP,N. S., s e e DANSGAARD,W. et al. GUNDESTRUP, N. S., s e e JOHNSEN, S. J. et al. GUNDESTRUP, N. S., s e e TAYLOR, K. C. et al. GUNST, R. F., BASU, S. and BRUNELL, R., 159, 184 GUNTER, R. L., s e e BOATMAN,J. F. et al. GUPTA, S. K., DARNELL, W. L. and WILBER, A. C., 265, 276 GUPTA, S. K., s e e DARNELL, W. L. et al. GUTZLER, D. F., 228, 237 GUTZLER, D. F. and HARRISON, D. E., 218, 237 GUTZLER, D. S., s e e WALLACE,J. M. and GUTZLER, D.S. HACK, J. J., s e e HURRELL, J. et al. HACK, J. J., s e e SCHUBERT,W. H. et al. HACKMAN, C. H., s e e KAYE, J. A. and HACKMAN, C.H. HADLEY CENTER, 33, 63 HAGE, K. D., 503, 511 HAGGERTY, B. M., s e e RAMPINO, M. R. and HAGGERTY,B. M. HAHN, C. J., s e e WARREN, S. G. et al. HAHN, D. G., s e e MANAGE, S. and HAHN, D. G. HAKKARINEN, I. M., s e e ADLER, R. F. et al. HALAS, S., s e e GRUSZCZYNSKI,M. et al. HALES, J. M., s e e CHARLSON,R, J. et al. HALL, D. K., s e e CHANG, A. T. C. et al. HALL, D., s e e RUNNING, S. W. et al. HALL, F. G., HUEMMRICH, K. F., GOETZ, S. J., SELLERS, P. J. and NICKESON,J. E., 270, 276 HALL, F. G., s e e SELLERS, P. J. et al. HALL, M. A., 553 HALL, M. A., s e e SHACKLETON,N. J. et al. HALL, M., s e e BOERSMA,A. et al. HALL, M., s e e SANCETTA,C. et al. HALL, N. M. J., HOSKINS, B. J., VALDES, P. J. and SENIOR, C. A., 304, 311 HALL, W. D., s e e WISCOMBE,W. J. et al. HALLAM, A., 114, 119, 140 HALLETT, J., HUDSON, J. G. and ROGERS, C. F., 376, 393 HALLETT, J., s e e HUDSON, J. G. et al. HALLETT, J., s e e ROGERS, C. F. et al. HALPERT, M. S., s e e ROPELEWSKI, C. F. and HALPERT,M. S. HALTINER, G. J. and WILLIAMS,R. T., 282, 311 HAMELIN, B., s e e BARD, E. et al. HAMILL, P., s e e MCCORMICK,M. P. et al. HAMILTON, K., 205, 237 HAMILTON, K. and GARCIA, R. R., 222, 237 HAMMER, C. U., CLAUSEN, H. B. and DANSGAARD, W., 177, 184 HAMMER, C. U., CLAUSEN, H. B., DANSGAARD,W., NEFTEL, A., KRISTINSDOTTIR, P. and JOHNSON, E., 523,530, 534 HAMMER, C. U., s e e DANSGAARD,W. et al. HAMMER, C. U., s e e JOHNSEN, S. J. et al.
571
HAMMER, C. U., s e e TAYLOR, K. C. et al. HAMMOND, A. L., 477, 511 HAMPSON, R. F., s e e DEMORE, W. B. et al. HANES, J., s e e SEBAI, A. et al. HANSEN, A. D. A., ARTZ, R. S., PSZENNY, A. A. P. and LARSON, R. E., 393 HANSEN, A. D. A., s e e WHELPDALE, D. M. et al. HANSEN, A. R., s e e SALTZMAN,B. et al. HANSEN, B. C., s e e GRIMM, E. C. et al. HANSEN, J., 35, 318 HANSEN, J. and LAClS, A., 80, 92, 326, 345, 352, 359, 362, 382, 393 HANSEN, J. and LEBEDEFF, S., 158 HANSEN, J. E., JOHNSON, D., LACIS, A., LEBEDEFF, S., LEE, P., RIND, D. and RUSSELL, G., 437, 470 HANSEN, J. E., LACIS, A., RIND, D., RUSSELL, G., STONE, P., FUNG, I., RUEDY, R. and LERNER, J., 35, 63,466,470 HANSEN, J. E., s e e WANG, W.-C. et al. HANSEN, J., FUNG, I., LACIS, A., RIND, D., LEBEDEFF, S., RUEDY, R., RUSSELL, G. and STONE, P., 175, 184 HANSEN, J., LACIS, A., RUEDY, R. and SATO, M., 176, 184, 205,207, 237, 352, 393 HANSEN, J., LACIS, A., RUEDY, R., SATO, M. and WILSON, H., 17, 80, 92, 336, 345, 352, 384, 393 HANSEN, J., RIND, D., DELGENIO, A., LACIS, A., LEBEDEFF, S., PRATHER, M., RUEDY, R. and KARL, T., 334, 345 HANSEN, J., Rossow, W. and FUNG, I., 336, 345 HANSEN, J., SATO, M., LACIS, A. and RUEDY, R., 336, 345 HANSEN, J., s e e CHARLSON,R, J. et al. HANSEN, J., s e e LACIS, A. et al. HANSEN, J., s e e LORIUS, C. et al. HANSEN, J.E and LEBEDEFF, S., 184 HANSEN, K., s e e FLYGER, H. et al. HANSEN, L., s e e DUCE, R. A. et al. HAO, W. M., LIu, M.-H. and CRUTZEN,P. J., 451, 471 HAO, W. M., s e e SANHUEZA,E. et al. HAO, W. M., s e e SCHARFFE, D. et al. HARDY, C. C., s e e EINFELD, W. et al. HARDY, C. C., s e e WARD, D. E. and HARDY, C. C. HARMS, D. E., RAMAN, S. and MADALA, R. V., 263,276 HARNACK, R. P. and LANDSBERG, H. E., 504, 511 HARRELL, J., s e e BRISKIN,M. and HARRELL,J. HARRINGTON, C. R., 176, 184 HARRIS, W. M., s e e B ARATH, F. T. et al. HARRISON, D. E. and SCHOPF, P. S., 211,237 HARRISON, D. E., s e e GUTZLER, D. F. and HARRISON, D. E. HARRISON, E. F., 211 HARRISON, E. F., MINNIS, P., BARKSTROM, B. R. and GIBSON, G. G., 254, 276
References
Index
HARRISON, E. F., MINNIS, P., BARKSTROM, B. R., RAMANATHAN V., CESS, R. D. and GIBSON, G. G., 256, 276 HARRISON, E. F., s e e CESS, R. D. et al. HARRISON, E. F., s e e MINNIS, P. et al. HARRISON, E. F., s e e RAMANATHAN,V. et al. HARRISON, S. P., s e e STREET-PERROTT, F. A. and HARRISON, S. P. HARRISS, R. C., s e e ANDREAE,M. O. et al. HARRISS, R. C., s e e TALBOT, R. W. et al. HART, T. L., 456, 471 HARTLEY, W. N., 408, 431 HARTMANN, D. L., RAMANATHAN,V., BERRIOR, A. and Hum', G. E., 254, 276 HARTMANN, D. L., s e e KLEIN, S. A. and HARTMANN, D. L. HARTMANN, D., s e e RAMANATHAN,V. et al. HARTZELL, F. Z., 154, 184 HARVEY, L. D. D., 52, 54, 63,448, 471 HARVEY, L. D. D. and SCHNEIDER,S. H., 32, 63 HARWOOD, D. M., 82, 92 HARWOOD, R. S., s e e WATERS, J. W. et al. HASSAN, F. A., 194, 237 HASSELMANN, K., 43, 63, 175, 184 HASSELMANN, K., s e e FRANKIGNOUL, C. and HASSELMANN, K. HASSELMANN, K., s e e HERTERICH, K. and HASSELMANN, K. HASSELMANN, K., s e e SAUSEN, R. et al. HASTENRATH, S., 229, 237 HASTENRATH, S. and HELLER, L., 218, 237 HAUGLUSTAINE, D. A., GRANIER, C., BRASSEUR, G. P. and MAGIE, G., 319, 336, 339, 345, 418, 419,431 HAUGLUSTAINE, D. A., s e e SHINE, K. P. et al. HAUSCHILD, H., s e e RUDOLF,B. et al. HAY, J. E., 486, 511 HAY, J. E., s e e SALINGER,M. J. et al. HAY, W., s e e BRASS, G. et al. HAYDER, M. E., s e e WATTS, R. G. and HAYDER, M.E. HAYES JR., D. R., s e e CORRELL, D. L. et al. HAYES, D. E. and FRAKES, L. A., 82, 92 HAYES, J. M., s e e FREEMAN, K. H. and HAYES, J. M. HAYS, J. D., IMBRIE,J. and SHACKLETON,N. J., 31, 40, 63 HAYS, J. D., s e e IMBRIE,J. et al. HAYS, J. D., s e e MARTINSON,D. G. et al. HAYS, P. B., s e e WALKER, J. C. G. et al. HAYWARD, T. L., s e e VENRICK, E. L. et al. HE, Q. X., s e e Hsu, K. J. et al. HEAMAN, L. M., s e e LECHEMINANT, A. N. and HEAMAN, L. M. HEATH, D. F., KRUEGER, A. J. and PARK, n., 409, 431 HEATHCOTE, R. L., 468, 471
572
HECHT, A., 21, 63 HECKLEY, W. A., KELLY, G. and TIEDTKE, M., 264, 276 HEGG, D. A., RADKE, L. F. and HOBBS, P. V., 372, 393 HEGG, D. A., s e e RADKE, L. F. et al. HEIDAM, N. Z., s e e FLYGER, H. et al. HEIM JR., R. R., 278 HEIM JR., R. R., s e e KARL, T. R. et al. HEIMAN, A., 127 HEIMAN, A., FLEMING, T. H., ELLIOT, D. H. and FOLAND, K. A., 140 HEIMANN, M., 533 HEIMANN, M., s e e KEELING,C. D. et al. HEINRICH, H., s e e BOND, G. et al. HEINTZENBERG,J., 382, 393 HEINTZENBERG,J. and LARSSEN, S., 380, 393 HEISER, M. D., s e e SELLERS, P. J. et al. HELAS, G., s e e BINGEMER,H. G. et al. HELD, I. M., 192, 226, 237, 307, 308, 311 HELD, I. M., s e e STEPHENSON,D. and HELD, I. M. HELD, I. M., s e e SUAREZ,M. J. and HELD, I. M. HELLDEN, U., 436, 441,452, 471 HEELER, L., s e e HASTENRATH, S. and HEELER, L. HENDERSON-SELLERS, A., 5, 17, 18, 157, 164, 184, 231,237,435,453,459,465,466, 467,471 HENDERSON-SELLERS, A. and GORNITZ, V., 438, 440, 441,452, 455,459, 461,471 HENDERSON-SELLERS, A. and MCGUFFIE, K., 8, 10, 12, 17, 232, 237, 379, 393,467,471,545,552 HENDERSON-SELLERS, A. and PITMAN, A. J., 440, 471 HENDERSON-SELLERS, A. and WILSON, M. F., 452, 471 HENDERSON-SELLERS, A., DICKINSON, R. E., DURBIDGE, T. B., KENNEDY, P. J., McGUFFm, K. and PITMAN,A. J., 435,457,459,461,471 HENDERSON-SELLERS, A., DURBIDGE, T. B., PITMAN, A. J., DICKINSON, R. E., KENNEDY, P. J. and MCGUFFIE, K., 23 l, 237 HENDERSON-SELLERS, A., s e e DICKINSON, R. E. and HENDERSON-SELLERS,A. HENDERSON-SELLERS, A., s e e DICKINSON, R. E. et al. HENDERSON-SELLERS, A., s e e HENDERSONSELLERS, B. et al. HENDERSON-SELLERS, A., s e e JONES, P. A. and HENDERSON-SELLERS, A. HENDERSON-SELLERS, A., s e e MCGUFFIE, K. et al. HENDERSON-SELLERS, A., s e e SHINE, K. P. et al. HENDERSON-SELLERS, B., HENDERSON-SELLERS, A., BENBOW, S. M. P. and MCGUFFIE, K., 6, 17 HENG-YI, W., s e e SMITH, E. A. et al. HENSE, A., KRAHE, P. and FLOHN, n., 228, 237 HEREFORD, V., s e e DESHLER,T. et al. HERMAN, B. M., BROWNING, S. R. and RABINOFF, R., 389,393
References
Index
HERMAN,J. R.,
s e e STOLARSKI,R. S. et al. HERTERICH, H., s e e LAUTENSCHLAGER, M. and HERTERICH, H. HERTERIEH, K. and HASSELMANN, K., 43, 63 HERTOGEN, J., s e e SMrr, J. and HERTOGEN, J. HESS, M. et al., 486, 511 HEUER, K., 95, 140 HEUSSER, L., s e e SANCETTA,C. et al. HEWITT, C. N., s e e FEHSENFELD, F. et al. HICKEY, L. J., 111,140 HICKEY, L. J., s e e JOHNSON, K. R. and HICKEY, L.
J.
HICKS, B. B., s e e DUCE, R. A. et al. HIDE, R., DICKEY, J. O., MARCUS, S. L., ROSEN, R. D. and SALSTEIN, D. A., 292, 311 HILDEBRAND, A. R. et al., 96, 140 HILDEBRAND, P. H. and ACKERMAN, B., 496, 503, 511 HILL, G. F., s e e ANDREAE, M. O. et al. HILL, R. I., s e e CAMPBELL, I. H. et al. HILL, W. J., s e e BOJKOV, R. D. et al. HINSEY, N. A., s e e GRATZ, A. J. et al. HIPPEL, D. V., s e e SUBAK, S. et al. HIRSCHLER, M. M., s e e CULLIS, C. F. and HIRSCHLER, M. M. HIRST, A. C., 211,237 HIRST, A. C., s e e BATTISTI, D. S. and HIRST, A. C. HITCHMAN, M. H. and BRASSEUR, G. P., 413, 431 HITEHMAN, M. H., s e e BRASSEUR, G. P. and HITEHMAN,M. H. HITEHMAN, M. H., s e e BRASSEUR, G. P. et al. HJELMFELT, M. R., 479, 511 HOBBS, P. V., 372, 394 HOBBS, P. V. and RADKE, L. F., 376, 394 HOBBS, P. V., RADKE, L. F. and SHUMWAY, S. E., 372, 380, 394 HOBBS, P. V., s e e HEGG, D. A. et al. HOBBS, P. V., s e e KING, M. D. et al. HOBBS, P. V., s e e RADKE, L. F. et al. HODYEH, J. P., s e e DUNNING, G. R. and HODYEH, J.P. HOEEKER, W. H., s e e ANGELL, J. K. et al. HOFER, H., s e e STAUFFER, B. et al. HOFF, R. M., s e e BARRIE, L. A. and HOFF, R. M. HOFFERT, M. I. and COVEY, C., 52, 63, 80, 92, 549, 552 HOFFMAN, m., s e e GRUSZCZYNSKI,M. et al. HOFFMAN, D. J., s e e CHARLSON, R, J. et al. HOFFMAN, M. E., s e e SWAID, H. and HOFFMAN, M. E. HOFMANN, D. J., 389,394 HOFMANN, D. J., s e e CHARLSON, R. J. et al. HOFMANN, D. J., s e e DESHLER, T. et al. HOGAN, A. W., s e e FLYGER, H. et al. HOGSTROM, U., BERGSTROM, H. and ALEXANDERSSON, H., 496, 511
573
HOLBEN, B. N., s e e KAUFMAN, Y. J. et al. HOLDEN, J. R., s e e BARATH, F. T. et al. HOLDRIDGE,L. R., 466, 471 HOLLAND, G. J., 289, 290, 304, 305,309, 311 HOLLAND, G. J. and DIETACHMAYER, G. S., 305, 311 HOLLAND, G. J. and LANDER, M., 311 HOLLAND, G. J., MCBRIDE, J. L. and NICHOLLS, N. N., 310, 311 HOLLAND, G. J., s e e FAIRALL, C. W. et al. HOLLAND, G. J., s e e LANDER, M. and HOLLAND, G. J.
HOLLAND, G. J., s e e LIGHTHILL,J. et al. HOLLAND, G. J., s e e RITCHIE, E. A. and HOLLAND, G.J. HOLLAND, G. J., s e e RrrCnlE, E. A. et al. HOLLAND, G. J., s e e SIMPSON, J. S. et al. HOLLAND, G. J., s e e WANG, Y. and HOLLAND, G. J. HOLLAND, H. D., s e e KASTING, J. F. et al. HOLLINGSWORTH, A., HORN, J. and UPPALA, S., 264, 276 HOLLOWAY JR., J. L., s e e MANABE, S. and HOLLOWAY JR., J. L. HOLLOWAY, J. M., s e e HUSAR, R. B. et al. HOLOPAINEN, E., s e e FORTELIUS, C. and HOLOPAINEN, E. HOLSER, W. T. and MAGARITZ,M., 120, 140 HOLSER, W. T. and SCHONLAUB, H. P., 122 HOLSER, W. T., SCHONLAUB, H. P., BOECKELMANN, K. and MAGARITZ, M., 120, 140 HOLSER, W. T., s e e MAGARITZ, M. et al. HOLTON, J. R., 202, 237, 282, 286, 288, 289, 290, 311 HOLTON, J. R., s e e WEBSTER, P. J. and HOLTON, J. R.
HOLZER, W., s e e BRASS, G. et al. HONG, Y., s e e APSIMON, H. et al. HONRATH, R. E., s e e MAYEWSKI, P. A. et al. HOOD, J. J., s e e GALLO, K. P. et al. HOOD, L. L., s e e MCCORMICK, M. P. and HOOD, L. L. HOPPEL, W. A., 372, 380, 394 HOREL, J. D. and WALLACE, J. M., 204, 220, 237, 297, 304, 311 HORN, J., s e e HOLLINGSWORTH,A. et al. HOSKINS, B. J., 289, 298, 311 HOSrdNS, B. J. and KAROLY, D., 297, 305, 311 HOSrdNS, B. J. and VALDES, P. J., 304, 312 HOSKINS, B. J., HSU, H. H., JAMES, I. N., MASUTANI, P. D, SARDESHMUKH, P. D. and WHrrE, G. H., 283,312 HOSIONS, B. J., MCINTYRE, M. E. and ROBERTSON, A. W., 289, 311 HOSKINS, B. J., s e e HALL, N. M. J. et al. HOSKINS, B. J., s e e SARDESHMUKH, P. D. and HOSKINS, B. J. Hou, H., s e e WANG,K. et al.
References
Index
HOUGHTON, J. J., JENKINS, G. J. and EPHRAUMS, J. J., 317, 319, 320, 321,323,324, 325, 329, 330, 33 l, 345 HOUGHTON, J. T., 17 HOUGHTON, J. T., CALLANDER,B. A. and VARNEY, S. K., 2, 18, 33, 57, 63, 177, 180, 184, 307, 312, 317, 319, 320, 321, 323, 324, 325, 326, 327, 333, 334, 335, 344, 345, 358, 359, 362, 384, 394, 437,444, 446, 465,467,471 HOUGHTON, J. T., JENKINS, G. J. and EPHRAUMS,J. J., 2, 6, 15, 18, 33, 57, 63, 177, 180, 184, 348, 359, 362, 384, 394, 437, 446, 447, 449, 450, 465,467,471 HOUGHTON, R. A., 447,448,464, 465, 471 HOUGHTON, R. A. and SKOLE, D. L., 447,448, 471 HOUGHTON, R. A., SCHLESINGER,W. H., BROWN, S. and RICHARDS,J. F., 448, 471 HOUSE, M. R., s e e BECKER, R. T. et al. HOUSLEY, R. A., s e e CORFIELD,R. M. et al. HOVINE, S., 43, 63 HOWARD, C. J., s e e DEMORE, W. B. et al. HOWARD, K. W., s e e NEGRI, A. J. et al. HOWARD, L., 478, 511 HOWARD, W. R., s e e IMBRIE, J. et al. HOVT, D. V., 236 HSIUNG, J. and NEWELL, R. E., 229, 237 HSIUNG, J., s e e BOTTOMLEY,M. et al. Hsu, H. H., s e e HOSKINS, B. J. et al. Hsu, K. J., 102, 140 Hsu, K. J. and MCKENZIE J. A., 103, 104, 114, 107, 140 Hsu, K. J., MCKENZlEJ. A., WEISSERT, H. et al., 140 Hsu, K. J., MCKENZIE, J. A. and HE, Q. X., 102, 103, 109, 112, 140 Hsu, K. J., MCKENZIE, J. A., WEISSERT, H. et al., 102, 103, 109, 112 Hsu, K. J., OBERHANSLI,H. et al., 126, 140 HUANG, Z., s e e FAN, D. et al. HUBER, B. T., s e e BARRERA,E. et al. HUDSON, H. S., 244 HUDSON, H. S., s e e WILLSON, R. C. and HUDSON, H.S. HUDSON, J. G., 372, 388, 394 HUDSON, J. G. and FRISBIE, P. R., 372, 394 HUDSON, J. G., HALLETT, J. and RODGERS, C. F., 376, 394 HUDSON, J. G., s e e HALLETT,J. et al. HUDSON, J. G., s e e LEAITCH,W. R. et al. HUDSON, J. G., s e e ROGERS, C. F. et al. HUDSON, J. G., s e e SAX, R. I. and HUDSON,J. G. HUEBERT, B. J. and LAZRUS,A. L., 381,394 HUEMMRICH, K. F., s e e HALL, F. G. et al. HUENNEKE, L. F., s e e SCHLESINGER,W. H. et al. HUETE, A. R., s e e RUNNING, S. W. et al. HUFF, F. A. and CHANGNONJR., S. A, 504, 511 HUFF, F. A., s e e CHANGNONJR., S. A. and HUFF, F. A.
574
HUFF, F. A., s e e CHANGNONJR., S. A. et al. HUGHES, M. K. and DIAZ, H. F., 5, 18, 194, 237 HUGHES, T. J., 40, 63 HUGHES, T. J., DENTON, G. H., ANDERSON, O. M., ANDERSON, B. G., SCHILLING, D. n., FASTHOOK, J. L. and LINGLE, C. S., 47, 63 HUGHES, T. J., s e e DENTON, G. H. and HUGHES, T. J.
HULME, M., 155, 166, 185 HUMERNIK, F. M., s e e LEZBERG,E. A. et al. HUNTJR., E. R., s e e RUNNING, S. W. et al. HUNT, G. E., s e e HARTMANN,D. L. et al. HUNTLEY, M. E., MARIN, V. and ESCRITOR, F., 541,552 HUON, S., s e e BOND, G. et al. HURRELL, J. W. and TRENBERTH,K. E., 263, 276 HURRELL, J. W., s e e TRENBERTH,K. E. et al. HURRELL, J., HACK, J. J. and BAUMHEFNER, D. P., 321,345 HUSAR, R. B. and STOWE, L. L., 349, 376, 379, 394 HUSAR, R. B. and WILSON JR., W. E., 379, 384, 394 HUSAR, R. B., HOLLOWAY,J. M. and PATTERSON, D. E., 379, 394 HUT, P., ALVAREZ,W. et al., 124, 140 HUTCHISON,J. H., s e e ESTES, R. and HUTCHISON,J. H. HUYBRECHTS,PH., 47, 63 HUYBRECHTS, PH., LETREGUILLY,A. and REEH, N., 58, 63 HVIDGERG, C. S. s e e DANSGAARD,W. et al. HVLDBORG, C. S., s e e DANSGAARD,W. et al. HYDE, W. T. and PELTIER, W. R., 40, 41, 63 HYDE, W. T., s e e SHORT, D. A. et al. ILYAS, M., s e e MADRONICH,S. et al. IMBRIE, J. and IMBRIE, J. Z., 31, 42, 49, 63, 231, 237 IMBRIE, J. and IMBRIE, K. P., 30, 63 IMBRIE, J. Z., s e e IMBRIE, J. and IMBRIE, J. Z. IMBRIE, J., BERGER, A., BOYLE, E. A., CLEMENS, S. C., DUFFY, A., HOWARD, W. R., KUKLA, G., KUTZBACH, J., MARTINSON, D. G., MCINTYRE, A., MIX, A. C., MOLFINO, B., MORLEY, J. J., PETERSON, L. C., PISIAS, N. G., PRELL, W. L., RAYMO, M. E., SHACKLETON, N. J. and TOGGWEILER,J. R., 64 IMBRIE, J., BOYLE, E. A., CLEMENS, S. C., DUFFY, A., HOWARD,W. R., KUKLA, G., KUTZBACH, J. E., MARTINSON, D. G., MClNTYRE, A., MIX, A. C., MOLFINO, B., MORLEY, J. J., PETERSON, L. C., PISIAS, N. G., PRELL, W. L., RAYMO, M. E., SHACKLETON, N. J. and TOGGWEILER,J. R., 22, 31, 37, 63 IMBRIE, J., BOYLE, E. A., CLEMENS, S. C., DUFFY, A., HOWARD,W. R., KUKLA, G., KUTZBACH,J.,
References
Index
MARTINSON, D. G., MCINTYRE, A., MIX, A. C., MOLFINO, B., MORLEY, J. J., PETERSON, L. C., PISIAS, N. G., PRELL, W. L., RAYMO, M. E., SHACKLETON, N. J., BERGER, A. and TOGGWEILER, J. R., 31 IMBRIE, J., HAYS, J. D., MARTINSON, D. G., MCINTYRE, A., MIX, A. C., MORLEY, J. J., PISIAS, N. G., PRELL, W. L. and SHACKLETON, N. J., 31, 40, 47, 49, 63 IMBRIE, J., MCINTYRE, A. and MIX, A. C., 31, 63 IMBRIE, J., s e e HAYS, J. D. IMBRIE, J., s e e MARTINSON, D. G. et al. IMBRIE, J., s e e SANCETTA, C. et al. IMBRIE, J., s e e SANTER, B. et al. IMBRIE, J., s e e SHACKLETON, N. J. and IMBRIE, J. IMBRIE, J., s e e SHACKLETON, N. J. et al. IMBRIE, K. P., s e e IMBRIE, J. and IMBRIE, K. P. INGRAM, W. J., s e e MITCHELL, J. F. B. et al. INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC), 2, 18, 72, 80, 92, 227, 230, 231, 232, 238,549, 552 IRVING, W. M., s e e BRYSON, R. A. et al. ISAAC, G. A., s e e LEAITCH, W. R. et al. ISAACS, R. G., s e e WANG, W.-C. et al. ISAKA, H., s e e FOUQUART, Y. and ISAKA, H. ISAKSEN, I. S. A., 319, 338, 345 ISAKSEN, I. S. A., RAMASWAMY, V., RODHE, H. and WIGLEY, T. M. L., 451,472 ISAKSEN, I. S. A., s e e WANG, W.-C. and ISAKSEN, I. S. A. ISRIC, 440, 472 IVERSEN, P., s e e JOHNSEN, S. J. et al. IVERSEN, T., s e e TARRASON, L. and IVERSEN, T. IVERSON, R. L., s e e BERRESHEIM, H. et al. IVEY, J. P., s e e AYERS, G. P. et al. IvY, S., s e e BOND, G. et al. JABLONSKI, D., 113, 141 JACKSON, D. L., s e e TJEMKES, S. A. et al. JACOB, D. J., s e e ANDREAE, M. O. et al. JACOB, D. J., s e e BINGEMER, H. G. et al. JACOB, D. J., s e e SPIRO, P. A. et al. JAr G. L., s e e GRIMM, E. C. et al. JAEGER, J.-J., s e e COURTILLOT, V. et al. JAEGER, J.-J., s e e ROCCHIA, R. et al. JAENICI~, R., 358, 364, 394, 397 JAENICKE, R., s e e PROSPERO, J. M. et al. JAESCHKE, W. A., s e e ANDREAE, M. O. and J AESCHKE, W. A. JAIPRAKASH, B. C., SINGH, J. and RAJU, D. S. N., 127, 141 JAMES, I. N., s e e HOSKINS, B. J. et al. JAMES, R. W. and Fox, P. T., 153, 185 JAMES, T. C., s e e ROCHE, A. E. et al. JANACEK, T. R., 84, 86, 92 JANACEK, T. R. and REA, D. K., 83, 84, 86, 92 JANACEK, T. R., s e e MILLER, K. G. et al.
575
JANACEK, T. R., s e e REA, D. K. et al. JANETOS, A., s e e WATSON, R. T. et al. JANETOS, m., s e e WATSON, R. W. et al. JANICOT, S., s e e DZIETARA, S. and JANICOT, S. JANOWIAK, J. E., 156, 185, 218, 238 JANOWIAK, J. E., s e e ARKIN, P. A. and JANOWlAK, J.E. JANTSCHIK, R., s e e BOND, G. et al. JARNOT, R. F., s e e BARATH, F. T. et al. JARNOT, R. F., s e e WATERS, J. W. et al. JARRELL, W. M., s e e SCHLESINGER,W. H. et al. JARZEN, D. M., s e e NICHOLS, D. J. et al. JASTROW, R., s e e BALIUNAS, S. and JASTROW, R. JAUREGUI, E., 477,480, 481,499, 501,508, 511 JAUREGUI, E., GODINEZ, L. and CRUZ, F., 500, 511 JAUREGUI, E., s e e OKE, T. R. et al. JEHANNO, C., s e e ROCCHIA, R. et al. JENKINS, G. J., s e e HOUGHTON, J. J. et al. JENKINS, W. J., s e e BREWER, P. G. et al. JENNE, R. J., s e e WOODRUFF, S. D. et al. JENNE, R. L. and MCKEE, T. B., 197, 238 JENNE, R. L., s e e WARREN, S. G. et al. JENNINGS, S. G., s e e O ' D o w D , C. D. et al. JI, M . , s e e LEETMAA, A. and JI, M. JIANG, H., s e e RAYMOND, D. J. and JIANG, H. JIANG, X., s e e BARNETT, T. V. et al. JIAQING, Z., s e e DAOHAN, C. et al. JICKELLS, T. D., s e e DUCE, R. A. et al. JIN-WEN, H., s e e DAo-YI, X. et al. JIRIKOVIC, J. and DAMON, P. E., 200, 238 JOHNSEN, S. J., CLAUSEN, H. B., DANSGAARD, W., FUHRER, K., GUNDESTRUP, N., HAMMER, C. U., IVERSEN, P., JOUSEL, J., STAUFFER, B. and STEFFENSEN, J. P., 25, 64, 517, 534 JOHNSEN, S. J., s e e DANSGAARD, W. et al. JOHNSEN, S. J., s e e GROOTES, P. M. et al. JOHNSON, A. I., s e e LAMB, H. H. and JOHNSON, m. I. et al. JOHNSON, A. L. A. and SIMMS, M. J., 111, 119, 141 JOHNSON, D. R., 285,286, 295,296, 312 JOHNSON, D. R. and DOWNEY, W. K., 285, 312 JOHNSON, D. R., s e e TOWNSEND, R. D. and JOHNSON, D. R. JOHNSON, D., s e e HANSEN, J. E. et al. JOHNSON, E., s e e HAMMER, C. U. et al. JOHNSON, G. D., s e e CROCKET, J. H. et al. JOHNSON, G. T., OKE, T. R., LYONS, T. J., STEYN, D. G., WATSON, I. D. and VOOGT, J. A., 499, 511 JOHNSON, G. T., s e e OKE, T. R. et al. JOHNSON, J. E., s e e QUINN, P. K. et al. JOHNSON, K. R., 96, 112, 141 JOHNSON, K. R. and HICKEY, L. J., 111, 141 JOHNSON, K. R., NICHOLS, D. J., ATTREP JR, M. and ORTH, C. J., 141 JOHNSON, S. J., s e e DANSGAARD, W. et al. JOHNSTON, D. S., s e e BORNSTEIN, R. D. and JOHNSTON, D. S.
References
Index
JONES, A. S., s e e BOULTON,G. S. et al. JONES, D. S., 117 JONES, D. S. et al., 141 JONES, D. S., MUELLER, P. A. et al., 108, 110, 141 JONES, P. A., 189 JONES, P. A. and HENDERSON-SELLERS, A., 164, 185 JONES, P. D., 18, 156, 157, 174, 185, 382, 394 JONES, P. D. and BRADLEY,R. S., 168, 185 JONES, P. D. and BRIFFA, K. R., 160, 185 JONES, P. D. and KELLY, P. M., 160, 185 JONES, P. D. and WIGLEY, Z. M. L., 151, 158, 185 JONES, P. D., GROISMAN, P. YA., COUGHLAN, M., PLUMMER, N., WANG, W.-C. and KARL, T. R., 155, 185, 197, 198,238 JONES, P. D., KELLY, P. M., GOODESS, C. M. and KARL, T. R., 479, 506, 511 JONES, P. D., RAPER, S. C. B. and WIGLEY, T. M. L., 158, 171,185 JONES, P. D., RAPER, S. C. B., BRADLEY, R. S., DIAZ, H. F., KELLY, P. M. and WIGLEY, T. M. L., 156, 158, 171, 185,207, 238 JONES, P. D., RAPER, S. C. B., CHERRY, B. S. G., GOODESS, C. M. and WIGLEY, Z. M. L., 185 JONES, P. D., RAPER, S. C. B., CHERRY, B. S. G., GOODESS, C. M., WIGLEY, T. M. L., BRADLEY, R. S. and DIAZ, H. F., 158 JONES, P. D., RAPER, S. C. B., SANTER, B. D., CHERRY, B. S. G., GOODESS, C. M.,KELLY, P. M., WIGLEY, Z. M. L., BRADLEY, R. S. and DIAZ, H. F., 185 JONES, P. D., s e e ALLAN, R. J. et al. JONES, P. D., s e e BRADLEY, R. S. and JONES, P. D. JONES, P. D., s e e BRADLEY,R. S. et al. JONES, P. D., s e e BRIFFA, K. R. and JONES, P. D. JONES, P. D., s e e BRIFFA, K. R. et al. JONES, P. D., s e e KARL, T. R. and JONES, P. D. JONES, P. D., s e e KARL, T. R. et al. JONES, P. D., s e e PARKER, D. E. et al. JONES, P. D., s e e ROPELEWSKI, C. F. and JONES, P. D. JONES, P. D., s e e SANTER,B. D. et al. JONES, P. D., s e e SEAR, C. B. et al. JONES, P. D., s e e WIGLEY, T. M. L. and JONES, P. D. JONES, P. D., s e e WIGLEY, T. M. L. et al. JONES, P. D., WIGLEY, T. M. L. and FARMER, G., 158, 171,185 JONES, P. D., WIGLEY, T. M. W. and WRIGHT, P. B., 382, 394 JONES, R. s e e MCEVEDY, C. and JONES, R. JORDAN, R. S., 207, 238 JOUSEL, J., s e e DANSGAARD,W. et al. JOUSEL, J., s e e JOHNSEN, S. J. JOUSSAUME, S., 24, 36, 64 JOUSSAUME, S. and JOUZEL, J., 36, 64 JOUZEL, J. et al., 226, 238
576
JOUZEL, J., BARKOV, N. I., BARNOLA, J. M., BENDER, M., CHAPPELLAZ, J., GENTHON, C., KOTLYAKOV, V. M., LIPENKOV, V., LORIUS, C., PETIT, J. R., RAYNAUD,D., RAISBECK, G., RITz, C., SOWERS, T., STIEVENARD,M., YIOU, F. and YIOU, P., 24, 38, 47, 50, 64, 520, 521,534 JOUZEL, J., LORIUS, C., PETIT, J. R., GENTHON, C., BARKOV, N. I., KOTLYAKOV, V. M. and PETROV, V. M., 520, 534 JOUZEL, J., s e e DANSGAARD,W. et al. JOUZEL, J., s e e GENTHON,C. et al. JOUZEL, J., s e e GROOTES,P. M. et al. JOUZEL, J., s e e JOHNSEN, S. J. et al. JOUZEL, J., s e e JOUSSAUME,S. and JOUZEL, J. JOUZEL, J., s e e LE TREUT, H. et al. JOUZEL, J., s e e LORIUS, C. et al. JOUZEL, J., s e e RAYNAUD,D. et al. JULIAN, P. R., s e e MADDEN, R. A. and JULIAN, P. R. JUSTICE, C. O., s e e RUNNING, S. W. et al. KADLECEK,J. A., s e e PUESCHEL,R. F. et al. KAHL, J. D. W., SEREEZE, M. C., STONE, R. S., SHIOTANI, S., KISLEY, M. and SCHNELL, R. C., 169, 185 KAIHO, K., 108, 141 KAIHO, K., s e e KAJ1WARA,Y. and KAIHO, K. KAIHO, K., s e e SAITO, T. et al. KAJIWARA, Y. and KAIHO, K., 109, 141 KALANDA, B. D., 494 KALANDA, B. D., OKE, T. R. and SP1TTLEHOUSE,O. L., 511 KALLBERG, P., s e e SWAP, R. et al. KALLEL, N., s e e DUPLESSY,J. C. et al. KALMA, J. D., 491, 511 KALMA, J. O., s e e STANHILL,G. and KALMA, J. D. KANAMITSU, M. and KRISHNAMURTI, T. N., 457, 472 KAPALA, A., s e e FLOHN, H. and KAPALA, A. KAPALA, A., s e e FLOHN, n. et al. KAPLAN, J., s e e DEMARIA, M. and KAPLAN, J. KARENTZ, D., s e e SMITH, R. C. et al. KARL, T. R., 200, 231,238 KARL, Z. R. and JONES, P. D., 479, 506, 508, 511 KARL,T. R. and STEURER,P. M., 157, 185,232, 238 KARL, T. R. and WILLIAMSJR., C. N., 185 KARL, Z. R. and WILLIAMS, J., 156 KARL, T. R., DIAZ, H. F. and KUKLA, G., 155, 185, 197, 238,478,479,497,498, 508, 511 KARL, T. R., HElM JR., R. R. and QUAYLE, R. G., 231,238 KARL, T. R., JONES, P. D., KNIGHT, R. W., KUKLA, G., PLUMMER, N., RAZUVAYEV,V., GALLO, K. P., LINDESAY, J., CHARLSON, R. J. and PETERSON, T. C., 163, 164, 185 KARL, T. R., KUKLA, G., RAZUVAYEV, V. N., CHANGERY, M. G., QUAYLE,R. G., HElM JR., R.
References
Index
R., EASTERLING, D. R. and Fu, C. B., 232, 238, 384, 394 KARL, T. R., s e e FOLLAND, C. K. et al. KARL, T. R., s e e GALLO, K. P. et al. KARL, T. R., s e e GROISMAN, P. Y. et al. KARL, T. R., s e e JONES, P. D. et al. KARL, T. R., s e e KUKLA, G. et al. KARL, T. R., s e e PLANTICO, M. S. et al. KARL, T. R., WILLIAMS JR., C. N. and YOUNG, P. J., 154, 185 KARL, T., s e e FOLLAND, C. K. et al. KARL, T., s e e GAVIN, J. et al. KARL, T., s e e HANSEN, J. et al. KARLI~N, W., s e e BRIFFA, K. R. et al. KAROLY, D. J., 156, 167, 186 KAROLY, D. J., COHEN, J. A., MEEHL, G. A., MEEHL, G. A., OORT, A. H., STOUFFER, R. J. and WETHERALD, R. T., 181, 186 KAROLY, D., s e e HOSKINS, B. J. and KAROLY, D. KASAHARA, A., BALGOVIND, R. C. and KATZ, B. B., 264, 276 KASTING, J. F., 6, 18 KASTING, J. F., HOLLAND, H. D. and KUMP, L. R., 542, 552 KASTING, J. F., RICHARDSON, S. M., POLLACK, J. B. and TOON, O. B., 103, 141 KASTING, J. F., s e e CALDEIRA, K. and KASTING, J. F. KASTING, J. F., s e e WALKER, J. C. G. and KASTING, J.F. KASTING, J. F., s e e WALKER, J. C. G. et al. KASTING, J. F., ZAHNLE, K. J. and WALKER, J. C. G., 543,552 KASTING, J. K. and RICHARDSON, S. M., 84, 92 KATES, R. W., s e e TURNER II, B. L. et al. KATZ, B. B., s e e KASAHARA, A. et al. KATZ, M. E., s e e MILLER, K. G. et al. KATZ, R. W., s e e GLANTZ, M. H. et al. KATZ, R. W., s e e NICHOLLS, N. and KATZ, R. W. KAUFFMAN, E. G., 114, 141 KAUFMAN, Y. J. and CHOU, M.-D., 379, 383, 385, 386, 394 KAUFMAN, Y. J. and NAKAJIMA, T., 377, 394 KAUFMAN, Y. J., FRASER, R. S. and FERRARE, R. A., 367, 394 KAUFMAN, Y. J., FRASER, R. S. and MAHONEY, R. L., 376, 394 KAUFMAN, Y. J., s e e FERRARE, R. A. et al. KAUFMAN, Y. J., s e e FRASER, R. S. et al. KAUFMAN, Y. J., s e e KING, M. D. et al. KAUFMAN, Y. J., SETZER, A., WARD, D., TANRE, D., HOLBEN, B. N., MENZEL, P., PEREIRA, M. C. and RASMUSSEN, R., 367, 394 KAUFMAN, Y. J., TUCKER, C. J. and FUNG, I., 367, 394 KAUFMANN, Y. J., s e e RUNNING, S. W. et al. KAYE, J. A. and HACKMAN, C. H., 418, 431
577
KEEHN, P. R., s e e NEGRI, A. J. et al. KEELING, C. D., BACASTON, R. B. and WHORF, T. P., 539, 552 KEELING, C. D., BACASTOW, R. B., BAINBRIDGE,A. E., EKDAHL, C. A., GUENTHER, P. R., WATERMAN, L. S. and CHIN, J. F. S., 230, 238 KEELING, C. D., B ACASTOW, R. B., CARTER, A. F., PIPER, S. C., WHORF, T. P., HEIMANN, M., MOOK, W. G. and ROELOFFZEN, H., 517, 534 KEENAN, T. D., s e e SIMPSON, J. S. et al. KEENE, W. C., s e e CHURCH, T. M. et al. KEENE, W. C., s e e GALLOWAY, J. N. et al. KEENE, W. C., s e e WHELPDALE, D. M. et al. KEIGWlN JR., L. D., s e e CORLISS, B. H. et al. KEIGWlN, L., 82 KEIGWIN, L. and CORLISS, B. H., 81, 92 KEIGWlN, L. D., 92 KEIGWlN, L. D., s e e LEHMAN, S. J. and KEIGWlN, L.D. KEIGWIN, L., s e e BOYLE, E. A. and KEIGWIN, L. KErn, D. J., s e e MILLER, K. G. et al. KEIMIG, F. T., s e e BRADLEY, R. S. et al. KELFKENS, H., s e e DE GRUIJL, F. R. et al. KELLER, G., 103, 104, 109, 118, 141 KELLER, G. and BARRERA, E., 134, 141 KELLER, G., s e e B ARRERA, E. and KELLER, G. KELLER, G., s e e CORLISS, B. H. et al. KELLER, G., s e e D' HONDT, S. et al. KELLER, G., s e e MACLEOD, N. and KELLER, G. KELLER, M., 448,472 KELLER, M., MITRE, M. E. and STALLARD, R. F., 448,449,472 KELLER, R., s e e FEES, E. and KELLER, R. KELLOGG, W. W., 347, 366, 394 KELLY, G. A., s e e LYRE, J. R. et al. KELLY, G. A., s e e HECKLEY, W. A. et al. KELLY, P. M. and SEAR, C. B., 176, 186 KELLY, P. M. and WIGLEY, T. M. L., 175, 186, 200, 238 KELLY, P. M., GOODESS, C. M. and CHERRY, B. S. G., 193,238 KELLY, P. M., s e e BRADLEY, R. S. et al. KELLY, P. M., s e e JONES, P. D. and KELLY, P. M. KELLY, P. M., s e e JONES, P. D. et al. KELLY, P. M., s e e SEAR, C. B. et al. KELLY, P. M., s e e WIGLEY, T. M. L. et al. KELLY-HANSEN, S.R., s e e BATES, T. S. et al. KENNEDY, P. J., s e e DICKINSON, R. E. and KENNEDY, P. J. KENNEDY, P. J., s e e DICKINSON,R. E. et al. KENNEDY, P. J., s e e HENDERSON-SELLERS,A. et al. KENNETT, J. P., 84, 93 KENNETT, J. P. J., s e e SHACKLETON, N. J. and KENNETT, J. P. KENNETT, J. P., s e e BROEcKER, W. S. et al. KENNETT, J. P., s e e STOTT, L. D. and KENNETT, J. P.
References
Index
KEPERT, J. D., s e e FAIRALL, C. W. et al. KERR, J. B. and MCELROY, C. T., 427, 431 KERSHAW, A. P., s e e MCGLONE, M. S. et al. KESSLER, A., 4, 18 KESSLER, R. W., BOSART, L. F. and GAZA, R. S., 153, 186 KEY, J. R., s e e SCHWEIGER,A. J. and KEY, J. R. KIDD, R. B., s e e RUDDIMAN,W. F. et al. KIDSON, J. W., 457, 472 KIDSON, J. W., s e e NEWELL, R. E. and KIDSON, J. W. KIEHL, J. T., 8, 18 KIEHL, J. T. and BRIEGLEB, B. P., 231, 238, 343, 345,362, 365,368, 378, 395,452, 472 KIEHL, J. T. and RAMANATHANV., 254, 255, 276 KIEHL, J. T., s e e CESS, R. D. et al. KIEHL, J. T., s e e WANG, W.-C. et al. KILADIS, G. N. and DIAZ, H. F., 214, 217, 220, 221,222, 238 KILADIS, G. N. and FELDSTEIN, S. B., 299, 300, 312 KILADIS, G. N. and SINHA, S. K., 216, 238 KILADIS, G. N. and VAN LOON, H., 214, 218, 221, 238 KILADIS, G. N. and WEICKMAN,K. M., 298, 312 KILADIS, G. N., s e e BRADLEY, R. S. et al. KILADIS, G. N., s e e DIAZ, H. F. and KILADIS,G. N. KIN, K. Y., s e e CROWLEY,T. J. et al. KIN, Y., s e e BOATMAN,J. F. et al. KIN, Y., s e e FALKOWSKI,P. G. et al. KING, M. D., KAUFMAN, Y. J., MENZEL, W. P. and TANRE, D., 259, 276 KING, M. D., RADKE, L. F. and HOBBS, P. V., 377, 395 KING, M. D., s e e NAKAJIMA,T. and KING, M. D. KING, M. D., s e e RADKE, L. F. et al. KINGTON, J., 151, 152, 186 KIPP, N. G., s e e SANCETTA,C. et al. KIPSTUHL, J., s e e TAYLOR, K. C. et al. KIRCHGASSER, W. T., s e e BECKER, R. T. et al. KIRK, E., s e e BARNETT, T. P. et al. KIRSCHVINK, J. L., s e e MAGARITZ,M. et al. KISLEY, M., s e e KAHL, J. D. W. et al. KLAPPER, G., s e e GOODFELLOW,W. D. et al. KLAS, M., s e e BOND, G. et al. KLAS, M., s e e BROECKER,W. S. et al. KLEIN, C., s e e WALKER, J. C. G. et al. KLEIN, S. A. and HARTMANN,D. L., 255, 277 KLEIN, W. H., s e e CORRELL, D. L. et al. KLEMCKE, C. H., s e e ROOSEN, G. R. et al. KLETT, J. D., s e e PRUPPAcHER, H. R. and KLETT, J. D. KLOEzEMAN, W. G., s e e BARATH, F. T. et al. KLOSE, G. J., s e e B ARATH, F. T. et al. KNAFF, J. A., s e e GRAY, W. M. et al. KNAP, A. H., s e e CHURCH, T. M. et al. KNAP, A. H., s e e DUCE, R. A. et al.
578
KNIGHT, R. J., s e e TAYLOR, F. W. et al. KNIGHT, R. W., s e e GROISMAN,P. Y. et al. KNIGHT, R. W., s e e KARL, T. R. et al. KNOCHE, H. R., s e e FLOHN, H. et al. KNOX, F., 527 KNOX, F. and MCELROY, M., 534 KOBLINSKY, C. J., 272, 277 KOCI, B., s e e MAYEWSKI,P. A. et al. KOKNAEVA, V. V., s e e GROISMAN,P. YA. et al. KOLBER, Z., s e e FALKOWSKI,P. G. et al. KOMINZ, M. A. and PISlAS, N. G., 43, 64 KONIG, W., SAUSEN, R. and SIELMANN, F., 302, 312 KORNFIELD, J., s e e CHARNEY,J. G. et al. KOROTKEVICH, Y. S., BARNOLA, J. M. et al., 551 KOROTKEVITCH, Y. S., s e e BARNOLA,J. M. et al. KOROTKEVITCH, Y. S., s e e CHAPPELLAZ,J. et al. KOROTKEVITCH, Y. S., s e e GENTHON,C. et al. KORSHOVER, J~, s e e ANGELL, J. K. and KORSHOVER, J. KORSOG, P. E., s e e WOLFF, G. R. et al. KOTLYAKOV, V. M., s e e GENTHON,C. et al. KOTLYAKOV, V. M., s e e JOUZEL, J. et al. KRAHE, P., s e e HENSE, A. et al. KRASSILOV, V. A., 112, 141 KRAUS, E. B., s e e EMILIANI,C. et al. KREBS, C. J., 550, 552 KRISHNAMURTI, T. N., s e e KANAMITSU, M. and KRISHNAMURTI,T. N. KRISTINSDOTTIR,P., s e e HAMMER,C. U. KRrrz, M. A., s e e ANDREAE,M. O. et al. KRUEGER, A. J., s e e BLUTH, G. J. S. et al. KRUEGER, A. J., s e e HEATH, D. F. et al. KUKLA, G., BERGER, A., LOTTI, R. and BROWN, J., 42, 64 KUKLA, G., GAVIN, J. and KARL, T. R., 506, 511 KUKLA, G., s e e BERGER, A. et al. KUKLA, G., s e e GAVIN, J. et al. KUKLA, G., s e e IMBRIE,J. et al. KUKLA, G., s e e KARL, T. R. et al. KUKLA, G., s e e PLANTICO,M. S. et al. KUKLA, G., s e e RIND, D. et al. KUKLA, G., s e e ROBINSON,D. A. et al. KUMANAN, I., s e e SANDERSON,M. et al. KUMER, J. B., s e e ROCHE, A. E. et al. KUMP, L., 106, 141,543,552 KUMP, L. R. and LOVELOCK,J. E., 18 KUMP, L. R. and VOLK, T., 547, 552 KUMP, L. R.,, s e e KASTING,J. F. et al. KUMP, L. R., s e e LOVELOCK,J. E. and KUMP, L. R. Kuo YANG, R. T. W., s e e QUINN, W. H. et al. KURIHARA, Y., s e e LIGHTHILL,J. et al. KURYLO, M. J., s e e DEMURE, W. B. et al. KUSHNIR, V., s e e ESBENSEN, S. K. and KUSHNIR, V. KUSHNIR, Y., 226, 227, 239 KUTZBACH, J. E., 32, 34, 38, 64, 90, 93
References
Index
KUTZBACH, J. E. and BRYSON, R. A., 191,239 KUTZBACH, J. E. and GALLIMORE, R. G., 40, 64, 90, 93 KUTZBACH, J. E. and GUETTER, P. J., 35, 37, 38, 64, 90, 93 KUTZBACH, J. E. and OTTO-BLIESNER, B. L., 38, 64 KUTZBACH, J. E. and STREET-PERROrr, F. A., 37, 64 KUTZBACH, J. E. and WRIGHTJR., H. E., 64 KUTZBACH, J. E. and WRIGHT, D. G., 35 KUTZBACH, J. E. and ZIEGLER,A. M., 90, 93 KUTZBACH, J. E., s e e IMBRIE,J. et al. KUTZBACH, J. E., s e e PRELL, W. L. and KUTZBACH, J.E. KUTZBACH, J. E., s e e RUDDIMAN, W. F. and KUTZBACH, J. E. KUTZBACH, J. E., s e e WEBB, T. et al. KWON, T. Y., s e e CESS, R. D. et al. KYTE, F. T., 115, 141 KYTE, F. T. and WASSON,J. Z., 115, 141 KYTE, F. T., s e e MARGOLIS, S. V. et al. KYTE, F. T., s e e ZHOU, L. and KYTE, F. T. KYTE, F. T., ZHOU, Z. and WASSON, J. T., 97, 100, 115, 117, 141
LAASEN, K.,
see FRIIS-CHRISTENSEN, E. and LAASEN, K. LABEYRm, L. D., 527 LABEYRIE, L. D. and DUPLESSY, J. C., 534, 547, 552 LABEYRIE, L. D., DUPLESSY, J. C. and BLANC, P. L., 24, 47, 48, 64, 526, 534 LABEYRIE, L. D., s e e BOND, G. et al. LABEYRIE, L. D., s e e DUPLESSY,J. C. et al. LABITZKE, K. and VAN LOON, H., 199, 202, 203, 239 LABITZKE, K., s e e VAN LOON, H. and LABITZKE,K. LACAUX, J.-P., s e e PHAM-VAN-DINHet al. LACIS, A. A., s e e CESS, R. D. et al. LACIS, A. A., s e e HANSEN, J. and LACIS, A. A. LACIS, A. A., s e e HANSEN, J. et al. LACIS, A. A., s e e WANG, W.-C. et al. LACIS, A. A., WUEBBLES, D. J. and LOGAN, J. A., 319, 336, 339, 345 LACIS, A., HANSEN, J. and SATO, M., 205,239 LAI, C., s e e BERGER, W. H. et al. LAMB, B., s e e FEHSENFELD,F. et al. LAMB, H. H., 167, 177, 186, 193, 194, 195, 196, 205,239 LAMB, H. H. and JOHNSON, A. I., 152, 186 LAMB, P. J., 166, 186 LAMB, P. J. and PEPPLER, R. A., 218, 239 LAMPREY, H. F., 441,472 LANDER, M. and HOLLAND, G. J., 305, 312 LANDER, M., s e e HOLLAND,G. J. and LANDER, M. LANDER, M., s e e RITCHIE,E. A. et al. LANDsBERG, H. E., 498, 511
579
LANDSBERG, H. E.,
see HARNACK, R. P. and LANDSBERG, H. E. LANDSEA, C. W. and GRAY, W. M., 310, 312 LANDSEA, C. W., s e e LIGHTHILL,J. et al. LANG, P. M., s e e DLUGOKENCKY,E. J. et al. LANGNER, J. and RODHE, H., 357, 363, 368, 380, 381,395 LANGNER, J., RODHE, H., CRUTZEN, P. J. and ZIMMERMANN,P., 358, 379, 395 LANGNER, J., s e e CHARLSON,R. J. et al. LANGWAYJR., C. C., s e e DANSGAARD,W. et al. LANLY, J. P., 444, 472 LARSEN, R. J., s e e SAVOIE, D. L. et al. LARSON, J. A., s e e BRYSON, R. A. et al. LARSON, R. E., s e e HANSEN, A. D. A. et al. LARSON, T. V., s e e CHARLSON,R. J. et al. LARSSEN, S., s e e HEINTZENBERG, J. and LARSSEN, S. LASAGA, A. C., 547, 552 LASAGA, A. C., s e e BERNER, R. A. et al. LASSEN, K., 236 LASSEN, K., s e e FRIIS-CHRISTENSEN, E. and LASSEN, K. LASZLO, I. and PINKER, R. T., 258,268,277 LASZLO, I., s e e PINKER, R. T. and LASZLO, I. LASZLO, I., s e e WHITLOCK,C. H. et al. LATHAM, D., s e e MELOSH, H. J. et al. LATHAM, J. and SMITH, M. H., 351,395 LATIF, M., s e e BARNETT,T. P. et al. LATTER, J. H., s e e SIMKIN,T. et al. LAU, G. K., s e e BARATH, F. T. et al. LAU, K.-M. and BUSALACCm, A. J., 262, 277 LAU, K.-M. and SHEU, P. J., 214, 239 LAURSEN, K. K., s e e RADKE, L. F. et al. LAUTENSCHLAGER, M. and HERTERICH,n., 64 LAUTENSCHLAGER, M. and HERTERICH, K., 35 LAVAL, K., 437,456, 457, 458,472 LAVAL, K. and PICON, L., 455,457, 461,472 LAVAL, K., s e e POLCHER, J. and LAVAL, K. LAVERY, J. R., s e e CAO, H. X. et al. LAWSON, D. R. and WINCHESTER,J. W., 380, 395 LAZRUS, A. L., s e e HUEBERT, B. J. and LAZRUS, A. L. LE HOUI~ROU,H. N., 436, 441,456, 472 LE TREUT, H., PORTES, J., JOUZEL, J. and GHIL, M., 41, 65 LE TREUT, H., s e e BONY, S. and LE TREUT, H. LE TREUT, H., s e e CESS, R. D. et al. LE TREUT, H., s e e GHIL, M. and LE TREUT, H. LE TREUT, H., s e e LORIUS, C. et al. LE, J., s e e SHACKLETON,N. J. et al. LEAHY, G. D., s e e RETALLACK,G. J. et al. LEAITCH, W. R., ISAAC, G. A., STRAPP, J. W., BANIC, C. M. and WIEBE, n. A., 372, 395 LEAITCH, W. R., STRAPP, J. W., ISAAC, G. A. and HUDSON, J. G., 372, 395 LEAN, D. R. S., s e e MAZUMBER,A. et al.
References
Index
LEAN, J., 25, 64 LEAN, J. and RIND, D., 200, 239 LEAN, J. and ROWNTREE, P. R., 472 LEAN, J. and WARRILOW, D. A., 459, 461, 465, 472 LEAN, J., s e e FOUKAL, P. and LEAN, J. LEAN, J., SKUMANICH, A. and WHITE, O., 25, 64, 200, 239, 253,277 LEARY, P. N. and RAMPINO, M. R., 102, 141 LEBEDEFF, S., s e e nANSEN, J. et al. LEBEDEFF, S., s e e HANSEN, J.E and LEBEDEFF, S. LECHEMINANT, A. N. and HEAMAN, L. M., 129, 142 LEE, A. J., s e e DICKSON, R. R. et al. LEE, P., s e e HANSEN, J. E. et al. LEETMAA, A. and JI, M., 232, 239 LEGATES, D. R. and WILLMOTT, C. J., 155, 186, 260, 277 LEGG, E., s e e RUTLEDGE, G. et al. LEGG, T. P., s e e PARKER, D. E. et al. LEGGETT, J., s e e APSIMON, H. et al. LEGRAND, M. R., DELMAS, R. J. and CHARLSON, R. J., 545,552 LEGRAND, M. R., FENIET-SAIGNE, C., SALTZMAN, E. S., GERMAIN, C., BARKOV, N. I. and PETROV, V. N., 54, 65 LEGRAND, M. R., LORIUS, C., BARKOV, N. I. and PETROV, V. N., 54, 64 LEGRAND, M., s e e DELMAS, R. J. et al. LEHMAN, S. J., 524 LEHMAN, S. J. and KEIGWIN, L. D., 534 LEHMAN, T. M., 100, 142 LEIGHTON, H. G., s e e LI, Z.-X. and LEIGHTON, H. G. LEINEN, M., s e e REA, D. K. et al. LEMKE, P., 43, 65 LENZ, A. C., s e e GOODFELLOW, W. D. et al. LEOVY, C. B., s e e CHARLSON,R. J. et al. LERMAN, J. C., s e e DAMON, P. E. et al. LERNER, J., s e e HANSEN, J. et al. LERNER, J., s e e MATTHEWS, E. et al. LETREGUILLY, A., s e e HUYBRECHTS, PH. et al. LEUENBERGER, M. and SIEGENTHALER,U., 52, 65 LEVKOV, L., s e e GRASSL, H. and LEVKOV, L. LEVY III, H., s e e SAVOIE, D. L. et al. LEWIS, B. L., s e e ANDREAE, M. O. et al. LEWIS, J. S. et al., 100, 142 LEWIS, R. S., s e e ANDERS, E. et al. LEWIS, R. S., s e e WOLBACH, W. S. et al. LEZBERG, E. A., HUMENIK, F. M. and OTTERSON, D. A., 382, 395 LI, J-J., s e e WANG,K. et al. LI, S. M., s e e BERRESHEIM, H. et al. LI, S. M., s e e TALBOT, R. W. et al. LI, S., s e e ANDREAE,M. O. et al. LI, Z. X., s e e CESS, R. D. et al. LI, Z., ZHAN, L., YAO, J. and ZHOU, Y., 120, 142
580
LI, Z.-X. and LEIGHTON, H. G., 265, 277 LI, Z.-X., s e e CESS, R. D. et al. LIANG, X.-Z., s e e CESS, R. D. et al. LIANG, X.-Z., s e e DUDEK, M. P. et al. LIANG, X.-Z., s e e WANG, W.-C. et al. LmERTI, G. L., s e e PRABHAKARA,C. et al. LIGHTHILL, J., HOLLAND, G. J., GRAY, W. M., LANDSEA, C., CRAIG, G., EVANS, J. L., KURIHARA, Y. and GUARD, C. P., 310, 312 LIM, G.-H., s e e WALLACE,J. M. et al. LIN, C. A., s e e MYSAK, L. A. and LIN, C. A. LINDESAY, J., s e e KARL, T. R. et al. LINDZEN, R. S., s e e SUN, D. Z. and LINDZEN, R. S. LINDZEN, R.S. and NIGAM, S., 209, 239 LINGLE, C. S., s e e HUGHES, T. J. et al. LINZHONG, L., s e e DAOHAN, C. et al. LIPENKOV, V., s e e JOUZEL, J. et al. LIPPS, J. H., s e e SIGNORIII, P. W. and LIPPS, J. H. LISS, P. S., s e e DUCE, R. A. et al. Lrrr, T., s e e SANTER,B. et al. LIU, H., s e e OORT,A. H. and LIU, H. LIU, J., 486 LIU, J., s e e WANG, C. and LIU, J. LIU, M.-H., s e e HAO, W. M. et al. LIU, S. C., s e e FEHSENFELD, F. and LIU, S. C. LIU, S., s e e FEHSENFELD,F. et al. LIU, W. T., 272, 277 LIU, W. T., TANG, W. and WENTZ, F. J., 272, 277 LIVESEY, R. E., s e e B ARNSTON, A. G. and LIVESEY, R.E. LIVEZEY, R. E., s e e Mo, K. C. and LIVEZEY, R. E. LLOYD, C. R., 22, 65 LLOYD, J. C. R., s e e SHUTTLEWORTH,W. J. et al. LOCKWOOD, G. W., s e e RADICK, R. R. et al. LOGAN, J. A., 338, 345,356, 395 LOGAN, J. A., s e e LACIS, A. A. et al. LOGAN, J. A., s e e SPIRO, P. A. et al. LOGAN, J. A., s e e SPIVAKOVSKY,C. M. et al. LOHMANN, K. C., s e e ZACHOS, J. C. et al. LONDER,R., s e e SCHNEIDER,S. H. and LONDER,R. LONDON, J., s e e WARREN, S. G. et al. LONG, A., s e e DAMON, P. E. et al. LONG, A., s e e MICHAELSEN, J. and LONG, A. LOO, M. S., s e e BARATH, F. T. et al. LOOSE, T. and BORNSTEIN, R. D., 505, 511 LORENZ, E. N., 232, 239 LORIUS, C., B ARNOLA, J. M. et al., 551 LORIUS, C., JOUZEL, J., RAYNAUD, D., HANSEN, J. and LE TREUT, H., 80, 93 LORIUS, C., s e e B ARNOLA, J. M. et al. LORIUS, C., s e e JOUZEL, J. LORIUS, CL., JOUZEL, J., RAYNAUD, D., HANSEN, J. and LE TREUT, H., 31, 52, 55, 65 LORIUS, CL., JOUZEL, J., RAYNAUD, D., HANSEN, J. and LE, J., 22 LORIUS, CL., s e e CHAPPELLAZ,J. et al. LORIUS, CL., s e e GENTHON, C. et al.
References
Index
LORIUS, CL., s e e LEGRAND,M. R. et al. LORIUS, CL., s e e RAYNAUD,D. et al. LOTTI, R., s e e KUKLA, G. et al. LOUBERE, P., s e e DOWSETr, H. J. and LOUBERE, P. LOUGH, J. M., 166, 186 LOUGH, J.M., 222, 239 LOUTRE, M. F., 57, 65 LOUTRE, M. F., BERGER, A., BRETAGNON, P. and BLANC, P.-L., 200, 239 LOUTRE, M. F., s e e BERGER, A. and LOUTRE, M. F. LOUTRE, M. F., s e e BERGER, A. et al. LOVELAND, T. R., s e e RUNNING, S. W. et al. LOVELOCK, J. E., 4, 18, 537, 539, 540, 541, 542, 543,550, 551,552 LOVELOCK, J. E. and KUMP, L. R., 544, 545, 552 LOVELOCK, J. E. and WHITFIELD,M., 537, 550, 552 LOVELOCK, J. E., s e e CHARLSON,R. J. et al. LOVELOCK, J. E., s e e WATSON, A. J. and LOVELOCK, J. E. LOWRIE, W., ALVAREZ, W. and ASARO, F., 101, 142 LOWRY, W. P., 481,500, 512 LUBIN, D., MITCHELL, B. G., FREDERICK, J. E., ROBERTS, A. D., BOOTH, C. R., LUCAS, T. and NEUSCHULER, D., 425, 431 LUCAS, T., s e e LUBIN, D. et al. LUCAS, T., s e e STAMNES, K. et al. LUCKMAN, B. H., 196, 239 LUCKMAN, B. H., s e e OSBORN, G. and LUCKMAN, B.H.
LUDWIG, F. L., s e e SEAMAN, N. L. et al. LUDWIG, J. H., s e e MCCORMICK, R. A. and LUDWIG, J. H. LUGINA, K. M., s e e VINNIKOV,K. YA. et al. LUNDE, A. T., s e e BIRCHFmLD,G. E. et al. LURIA, M., s e e BOATMAN,J. F. et al. LUTHER, M. E., O'BRIEN, J. J. and PRELL, W. L., 38, 65 LUYENDYK, B., FORSYTH D. and PHILLIPS, J., 75, 84, 93 LYELL, C., 95, 142 LYJAK, L. V., s e e GILLE, J. C. and LYJAK, L. V. LYONS, J. B. and OFFICER, C. B., 134, 142 LYONS, J. D., s e e RADKE, L. F. et al. LYONS, J. H., s e e RADKE, L. F. et al. LYONS, T. J. and FORGAN, B. W., 486, 512 LYONS, T. J., s e e JOHNSON, G. T. et al. LYONS, W. B., s e e MAYEWSKI,P. A. et al. LYv, G., s e e DANARD, M. et al. MA, S., s e e Xu, D. et al. MAALOE, S., s e e STORETvEDT, K. M. et al. MAASCH, K. A. and SALTzMAN, B., 42, 43, 65 MAASCH, K. A., s e e GRIMM, E. C. et al. MAASCH, K. A., s e e SALTzMAN, B. and MAASCH, K.A. MAASCH, K. A., s e e SALTzMAN, B. et al.
581
MABBUTT, J. A., 441,465,472 MACCRACKEN, M. C. and MOSES, H., 181, 186 MACCRACKEN, M. C., s e e ELSAESSER, H. W. et al. MACDOUGAL, J. D., 101, 142 MACHEL, H., s e e FLOHN, H. et al. MACHTA, L., s e e MUNN, R. E. and MACHTA, L. MACINTYRE, A., s e e RIND, D. et al. MAClNTYRE, S., s e e SMITH, R. C. et al. MACKENSEN, A., 119 MACKENSEN, A. and EHRMANN,W. U., 142 MACKENSEN, A., s e e EHRMANN, W. U. and MACKENSEN, A. MACLEOD, N. and KELLER, G., 109, 110, 142 MADALA, R. V., s e e HARMS, D. E. et al. MADDEN, R. A. and JULIAN, P. R., 297, 305, 312 MADDEN, R. A. and RAMANATHAN,V., 181, 186 MADDEN, R. A., SHEA, D. J., BRANSTATOR, G. W., TRIBBIA, J. J. and WEBER, R., 159, 186 MADDISON, B. J., s e e BARATH, F. T. et al. MADDOX, R. A., s e e NEGRI, A. J. et al. MADRONICH, S., 421,422, 423,426, 431 MADRONICH, S. and DE GRUIJL, F. R., 431 MADRONICH, S. and GRANIER, C., 399, 424, 425, 431 MADRONICH, S., BJORN, L. O., ILYAS, M. and CALDWELL, M. M., 420, 424, 431 MAENHAUT, W., s e e ARTAXO, e. et al. MAENO, N., s e e MOORE, J. C. et al. MAGARITZ, M., 114, 142 MAGARITZ, M., BAR, R., BAUD, A. and HOLSER, W. T., 120, 142 MAGARITZ, M., HOLSER, W. T. and KIRSCHVINK,J. L., 142 MAGARITZ, M., MOUNT, J. F., DOEHNE, E., SHOWERS, W. and WARD, P., 127 MAGAR1TZ, M., s e e HOLSER, W. T. and MAGARITZ, M. MAGARITZ, M., s e e HOLSER, W. T. et al. MAGIE, G., s e e HAUGLUSTAINE,D. A. et al. MAHAJAN, I. K., s e e FRAMJI, K. K. and MAHAJAN, I.K. MAHLMAN, J. D., PINTO, J. P. and UMSCHEID, L. J., 336, 345 MAHONEY, J. J., 131, 142 MAHONEY, L., s e e FRASER, R. S. et al. MAHONEY, R. L., s e e KAUFMAN,Y. J. et al. MAIER-REIMER, E. and MIKOLAJEWICZ,U., 16, 18, 530, 534 MAIER-REIMER, E., MIKOLAJEWICZ, U. and CROWLEY, T., 84, 93 MALINGREAU, J. P., STEPHENS, G. and FELLOWS, L., 465,472 MALKOWSKI, K., s e e GRUSZCZYNSKI,M. et al. MALMBERG, S.-A., s e e DICKSON,R. R. et al. MALMGREN, B., s e e WIDMARK, J. G. V. and MALMGREN, B. MANABE, S., 318,530
References
Index
MANABE, S. and BROCCOLI,A. J., 35, 40, 65 MANABE, S. and HAHN, D. G., 35, 36, 65 MANABE, S. and HOLLOWAYJR., J. L., 466, 472 MANABE, S. and STOUFFER, R. J., 33, 34, 37, 40, 58, 65, 88, 93,226, 232, 239, 534 MANABE, S. and STRICKLER,R. F., 345 MANABE, S., BRYAN, K. and SPELMAN, M. J., 84, 93 MANABE, S., s e e BROCCOLI,A. J. and MANABE, S. MANABE, S., s e e DELWORTH,T. et al. MANABE, S., s e e MITCHELL,J. F. B. et al. MANABE, S., s e e SPELMAN,M. J. and MANABE, S. MANABE, S., s e e STOUFFER,R. J. et al. MANABE, S., SPELMAN, M. J. and STOUFFER, R., 327, 331,345 MANABE, S., STOUFFER, R. J., SPELMAN, M. J. and BRYAN, K., 327, 331,332, 345 MANGERUD, J., 47, 65 MANKIN, W. G., COFFEY, M. T. and GOLDMAN, A., 413,431 MANLEY, G., 151, 186 MANNEY, G. L., s e e WATERS, J. W. et al. MANSELL, J. W., s e e ACKERMAN,B. and MANSELL, J.W. MANTON, M. J., s e e AYERS, G. P. et al. MAO, H., s e e SHINE, K. P. et al. MAO, X., s e e Xu, D. et al. MAPES, B. E., 305, 312 MARCHAND, D. S., s e e STREET-PERROTT, F. A. et al. MARCUS, S. L., s e e HIDE, R. et al. MARGOLIS, S. V., CLAEYS, P. and KYTE, F. T., 117, 142 MARGOLIS, S. V., MOUNT, J. F., DOEHNE, E., SHOWERS, W. and WARD, P., 112, 142 MARGOLIS, S. V., s e e CLAEYS, P. et al. MARIN, V., s e e HUNTLEY,M. E. et al. MARKGRAF, V., s e e DIAZ, H. F. and MARKGRAF, V. MARKGRAF, V., s e e MCGLONE, M. S. et al. MARKHAM, B., s e e GOWARD, S. N. et al. MARQUES FILHO, A. DE O., s e e SHUTTLEWORTH, W.J. etal. MARSlAT, I. and BERGER, A., 47, 48, 65 MARSIAT, I., s e e BERGER, A. et al. MARSIAT,I., s e e GALLI~E,H. et al. MARSICO, D. C., s e e REYNOLDS, R. W. and MARSICO, D. C. MARTINSON, D. G., PISIAS, N. G., HAYS, J. D., IMBRIE, J., MOORE, T. C. and SHACKLETON, N. J., 39, 65 MARTINSON, D. G., s e e IMBRIE,J. et al. MARVIN, U. B., 95, 142 MASAIRE, K. A., s e e DLUGoKENCKY,E. J. et al. MASKELL, K, s e e ROWELL, D. P. et al.. MASLANIK, J. A., s e e BARRY, R. G. et al. MASS, C. F. and PORTMAN, D. A., 205,239
582
MASUTANI, P. D., s e e HOSKINS,B. J. et al. MATEER, C. L., 410, 431 MATHEWS, J. T., s e e TURNERII, B. L. et al. MATLICK, H. A., s e e SMITH, R. C. et al. MATSON, M., 273,277 MATTAUCH, R. J., s e e BARATH, F. T. et al. MATTHAI, S. K., s e e ENGELHARDT,W. v. et al. MATTHEWS, E., FUNG, I. and LERNER, J., 449, 472 MATTHEWS, R. K. and POORE, R. Z., 81, 93 MATZARAKIS, A. and MAYER, H., 507 MATZARKIS, A. and MAYER, H., 512 MAXWELL, W. D., 120, 123, 142 MAYER, H., s e e MATZARKIS,A. and MAYER, H. MAYEWSKI, P. A., LYONS, W. B., SPENCER, M. J., TWICKLER, M. S., BUCK, C. F. and WHITLOW, S., 382, 383,395 MAYEWSKI, P. A., LYONS, W. B., SPENCER, M. J., TWlCKLER, M., DANSGAARD, W., KOCI, B., DAVIDSON, C. I. and HONRATH, R. E., 382, 395 MAYEWSKI, P. A., s e e ALLEY, R. B. et al. MAZUMBER, A., TAYLOR, W. D., MCQUEEN, D. J. and LEAN, D. R. S., 541,553 MCAVANEY, B. J. and COLMAN,R. A., 292, 312 MCAVANEY, B. J., DAHNI, R. R., COLMAN, R. A., FRASER, J. R. and POWER, S. B., 307, 312 MCAVANEY, B. J., s e e CESS, R. D. et al. MCAVANEY, B. J., s e e POWER, S. B. et al. MCBRIDE, J. L., s e e HOLLAND,G. J. et al. MCCARTNEY, M. S., s e e TALLEY, L. D. and MCCARTNEY, M. S. MCCAUGHEY, J. H., s e e OKE, T. R. and MCCAUGHEY, J. H. MCCAULEY, S., s e e BICE, D. M. et al. MCCLELLAND, L., s e e SIMKIN,T. et al. MCCORMICK, M. P. and HOOD, L. L., 319, 345 MCCORMICK, M. P., HAMILL, P., PEPIN, T. J., CHU, W. P., SWISSLER, T. J. and MCMASTER, L. R., 411,432 MCCORMICK, M. P., VEIGA, R. E. and CHU, W. P., 319, 335,337, 346 MCCORMICK, R. A. and LUDWIG,J. H., 347, 395 MCCRACKEN, A. D., s e e GOODFELLOW,W. D. et al. MCCUTCHEON, J., s e e ROUSE, W. R. et al. MCELROY, C. T., s e e KERR, J. B. and MCELROY, C.T. MCELROY, M. B., s e e SPIVAKOVSKY,C. M. et al. MCELROY, M. B., s e e WOFSY, S. C. et al. MCELROY, M., s e e KNOX, F. and MCELROY, M. MCEVEDY, C. and JONES, R, 472 MCEWAN-MASON, J., s e e RICH, T. H. et al. MCGANN, R., s e e SALINGER,M. J. et al. MCGHEE JR, G. R., 124, 142 MCGHEE JR, G. R. et al., 115, 124, 142 MCGLADE, J. M., s e e ADAMS, J. M. et al. MCGLONE, M. S., KERSHAW, A. P. and MARKGRAF, V., 224, 239 McGOVERN, T. H., 169, 186
References
Index
McGOWAN, J. A., s e e VENRICK, E. L. et al. MCGREGOR, J. L. and WALSH, K., 321,346 MCGUFFIE, K., HENDERSON-SELLERS, A., ZHANG, H., DURBIDGE, T. B. and PITMAN, A. J., 434, 461,472 MCGUFFIE, K., s e e HENDERSON-SELLERS, m. and MCGUFFIE, K. MEGUFFIE, K., s e e HENDERSON-SELLERS,A. et al. MCGUFFIE, K., s e e HENDERSON-SELLERS,B. et al. MCINTYRE, A., s e e IMBRIE, J. et al. MCINTYRE, A., s e e RIND, D. et al. MClNTYRE, A., s e e RUDDIMAN, W. F. and MCINTYRE, A. MEINTYRE, M. E., s e e HOSrdNS, B. J. et al. McKAY, C. P. and THOMAS, G. E., 100, 142 MCKAY, C. P., s e e MILNE, D. H. and McKAY, C. P. MCKEE, T. B., s e e JENNE, R. L. and MCKEE, T. B. MCKENNA, M. C., 82, 93 MEKENZIE, J. A., s e e Hsu, K. J. and MCKENZIE, J. A. MCKENZIE, J. A., s e e Hsu, K. J. et al. MCKENZIE, D. and BICKLE, M. J., 128, 142 MCKENZIE, D., s e e WHITE, R. and MCKENZIE, D. MCKENZIE, R. L., s e e SECKMEYER, G. and MCKENZIE, R. L. MCKINLAY, A. F. and DIFFEY, B. L., 420, 432 MCKINNEY, M. L., 113, 142 MCKINNEY, R. P., s e e BARATH, F. T. et al. MCLAIN, D. R., s e e EBBESMEYER,C. C. et al. MCLAREN, D. J., 124, 125, 142 MCLAREN, D. J. and GOODFELLOW, W. D., 98, 114, 115, 119, 120, 126, 134, 143 MELAREN, D. J., s e e GELDSETZER,H. H. J. et al. MELAREN, D. J., s e e GOODFELLOW,W. D. et al. MCLEAN, D. M., 97, 129, 143 MCMAHON, C. K., s e e PATTERSON, E. M. and MCMAHON, C. K. MCMANUS, J., s e e BOND, G. et al. MEMASTER, L. R., s e e MCCORMICK, M. P. et al. MENAB, A. L., s e e GALLO, K. P. et al. MCNALLY, A. P., s e e EYRE, J. R. et al. MEPETERS, R. D., s e e STOLARSKI, R. S. MEQUEEN, D. J., s e e MAZUMBER, A. et al. MCROBERTS, C. A., s e e BICE, D. M. et al. MEADEN, G. T., s e e ELSOM, D. M. and MEADEN, G.T. MEADOWS, A., s e e SELLERS, A. and MEADOWS, A. MEARNS, L. O., s e e GIORGI, F. and MEARNS, L. O. MEEHL, G. A., 213, 218,224, 240 MEEHL, G. A. and BRANsTATOR, G. W., 225, 229, 240 MEEHL, G. A., s e e GATES, W. L. et al. MEEHL, G. A., s e e KAROLY, D. J. et al. MEEHL, G. A., s e e WASHINGTON, W. M. and MEEHL, G. A. MEESE, D. A., s e e ALLEY, R. B. et al.
583
MEGAW, W. J., s e e FLYGER, H. et al. MI~GIE, G., s e e HAUGLUSTAINE,D. A. et al. MEINCKE, J., s e e DICKSON, R. R. et al. MEIRA FILHO, L. G., s e e WATSON, R. T. et al. MEIRA FILHO, L. G., s e e WATSON, R. W. et al. MEKO, D. M., s e e MITCHELLJR., J. M. et al. MEKO, D. M., s e e STOCKTON, C. W. and MEKO, D. M. MEKO, D. M., s e e STOCKTON, C. W. et al. MELESHKO, V. P., s e e CESS, R. D. et al. MELESHKO, V. P., s e e GATES, W. L. et al. MELESHKO, V., s e e MITCHELL, J. F. B. et al. M~LICE, J. L., s e e BERGEN, A. et al. MELOSH, H. J., 100, 129, 143 MELOSH, H. J., SCHNEIDER, N. M., ZAHNLE, K. J. and LATHAM, D., 101, 143 MELOSH, H. J., s e e VICKERY, A. M. and MELOSH,
H.J. MENGEL, J. G., s e e CROWLEY, T. J. et al. MENGEL, J. G., s e e NORTH, G. R. et al. MENGEL, J. G., s e e SHORT, D. A. et al. MENZEL, P., s e e KAUFMAN, Y. J. et al. MENZEL, P., s e e RUTLEDGE, G. et al. MENZEL, W. P., s e e KING, M. D. et al. MENZIES, D., s e e SMITH, R. C. et al. MERCER, J. H., 196, 240 MERGENTHALER,J. L., s e e ROCHE, A. E. et al. MERONEY, R. N., 494, 512 MERRILL, J. Z., s e e ANDREAE, M. O. et al. MERRILL, J. T., s e e BERRESHEIM,H. et al. MERRILL, J. T., s e e BETZER, P. R. et al. MERRILL, J. T., s e e DUCE, R. A. et al. MERRILL, J. T., s e e GALLOWAY, J. N. et al. MERRILL, J. T., s e e PROSPERO, J. M. et al. MERRILL, J. T., s e e SAVOIE, D. L. et al. METHOD, T. and CARLSON, T. N., 486, 512 MEYER, W. B., s e e TURNER II, B. L. et al. MICHAELSEN, J. and LONG, A., 240 MICHAELSEN, J. and THOMPSON, L. G., 222, 240 MICHAELSEN, J., s e e GRAHAM, N. E. et al. MICHAUD, R. and DEROME, J., 27 l, 277 MICHEL, H. V., s e e ALVAREZ, L. W. et al. MICHEL, n. V., s e e ALVAREZ, W. et al. MICHEL, H. V., s e e ASARO, F. et al. MIDDLETON, N. and THOMAS, D. S. G., 436, 472 MIDDLETON, W. E. K., 152, 186 MIHALOPOULOS, N., s e e BINGEMER, H. G. et al. MIKOLAJEWICZ, U., s e e MAIER-REIMER, E. and MIKOLAJEWICZ, U. MIKOLAJEWICZ, U., s e e MAIER-REIMER, E. et al. MILANKOVITCH, M. M., 30, 65 MILLER, A. J., NAGATANI, R. M., TIAO, G. C., NIU, X. F., REINSEL, G. C., WUEBBLES, D. and GRANT, K., 319, 346 MILLER, J. M., s e e DUCE, R. A. et al. MILLER, K. G., FAIRBANKS, R. G. and MOUNTAIN, G. S., 118, 119, 143
References
Index
MILLER, K. G., JANACEK, T. R., KATZ, M. E. and KEIL, D. J., 86, 93 MILLER, M. J., s e e BETTS, A. K. et al. MILLS, G. M. and ARNFIELD,A. J., 490, 512 MILNE, D. H. and MACKAY, C. P., 98, 143 MINNIS, P., 352 MINNIS, P., HARRISON, E. F., STOWE, L. L., GIBSON, G. G., DENN, F. M., DOELLING, D. R. and SMITH, W. L., 395 MINNIS, P., s e e CESS, R. D. et al. MINNIS, P., s e e HARRISON,E. F. et al. MINNIS, P., s e e RAMANATHAN,V. et al. MINTZ, Y., s e e SHUKLA,J. and MINTZ, Y. MINrZ, Y., s e e SUD, Y. C. et al. MITCHELL, B. G., s e e LUBIN, D. et al. MITCHELL, J. F. B., 33, 34, 37, 38, 65, 347, 366, 367 MITCHELL, J. F. B., GRAHAME, N. S. and NEEDHAM, K. J., 38, 66 MITCHELL, J. F. B., MANABE, S., MELESHKO, V. and TOKIOKA, T., 166, 186 MITCHELL, J. F. B., s e e CAO, H. X. et al. MITCHELL, J. F. B., s e e CESS, R. D. et al. MITCHELL, J. F. B., s e e GATES, W. L. et al. MITCHELL, J. F. B., s e e GREGORY, J. M. and MITCHELL, J. F. B. MITCHELL, J. F. B., s e e SCHLESINGER, M. E. and MITCHELL, J. F. B. MITCHELL, J. F. B., s e e SENIOR, C. A. and MITCHELL, J. F. B. MITCHELL, J. F. B., s e e STREET-PERROTT, F. A. et al. MITCHELL, J. F. B., SENIOR, C. A. and INGRAM,W. J., 260, 277 MITCHELL, J. G., s e e STORETVEDT,K. M. et al. MITCHELL, JR., J. M., 156, 186, 240, 395 MITCHELL, JR., J. M., s e e GILMAN, D. L. et al. MITCHELL, JR., J. M., s e e STOCKTON,C. W. et al. MITCHELL, JR., J. M., STOCKTON,C. W. and MEKO, D. M., 199, 200, 202, 240 MITCHELL, T. P., 191, 192, 231 MITCHELL, T. P., s e e WRIGHT, P. B. et al. MITRE, M. E., s e e KELLER, M. et al. Mix, A. C., 520, 547, 553 Mix, A. C. and FAIRBANKS,R. G., 534 MIX, A. C., s e e IMBRIE,J. et al. MIX, A. C., s e e SHACKLETON,N. J. et al. Mo, K. and RASMUSSON,E. M., 300, 312 MO, K. C. and LIVEZEY,R. E., 204, 240 MO, T., s e e WANG, W.-C. et al. MOHNEN, V. A., GOLDSTEIN, W. and WANG, W.C., 319, 346 MOHNEN, V., s e e PROSPERO, J. M. et al. MOLFINO, B., s e e IMBRIE,J. et al. MOLINA, L. T. and MOLINA, M. J., 420, 432 MOLINA, M. J., s e e DEMORE, W. B. et al.
584
MOLINA, M. J.,
see
MOLINA, L. T. and MOLINA, M.
J.
MOLION, L. C. B., s e e SHUTTLEWORTH,W. J. et al. MOLLER, D., 357, 395 MOLNAR, G., s e e WANG, W.-C. et al. MONAHAN, E. C., s e e CIPRIANO,R. J. et al. MONTANARI, A., 115, 118, 143 MONTANARI, A., s e e ALVAREZ,W. et al. MONTANARI, A., s e e SMIT, J. et al. MONTIGNY, R., s e e COURTILLOT,V. et al. MONTIGNY, R., s e e VANDAMME,D. et al. MOOK, W. G., s e e KEELING,C. D. MOOLEY, n. A., s e e BHALME, H. N. and MOOLEY, D.A. MOOR, E., s e e NEFTEL, A. et al. MOORE, A. M., s e e POWER, S. B. et al. MOORE, C. J., s e e SHUTTLEWORTH,W. J. et al. MOORE, J. C., NARITA, H. and MAENO, N., 177, 186 MOORE, M., s e e COLE, J. E. et al. MOORE, T. C., PISIAS, N. G. and DUNN, D.A., 31, 66 MOORE, T. C., s e e MARTINSON,D. G. et al. MOORE, T. C., s e e TAYLOR, K. C. et al. MORCRETTE, J. J., s e e CESS, R. D. et al. MORCRETTE, J. J., s e e FOUQUART,Y. et al. MORESHET, S., s e e STANHILL, G. and MORESHET, S. MORIYAMA, S., 347, 362, 395 MORLEY, J. J., s e e IMBRIE,J. et al. MORRIS, P., s e e TAYLOR, F. W. et al. MORRISON, D., s e e CHAPMAN, C. R. and MORRISON, n. MOSES, H., s e e MACCRACKEN, M. C. and MOSES, H. MOSLEY-THOMPSON, E., s e e THOMPSON, L. G. et al. MOUNT, J. F., s e e MARGOLIS, S. V. et al. MOUNTAIN, G. S., s e e MILLER, K. G. et al. MOYERS, J., s e e PROSPERO, J. M. et al. MUELLER, P. A., s e e JONES, D. S. et al. MULLEN, G., s e e SAGAN, C. and MULLEN, G. MOLLER, H., 49, 66 MULLER, J.-P., s e e RUNNING, S. W. et al. MUNN, R. E. and MACHTA, L., 437,472 MUNN, R. E., s e e CLARK, W. C. and MUNN, R. E. MURPHY, J. M., 33, 40, 66 MURPHY, R. E., s e e SELLERS, P. J. et al. MURRAY, R. J. and SIMMONDS,I., 302, 312 MYERS, N., 435,436, 438, 444, 445,464, 472, 473 MYLNE, M. F. and ROWNTREE, P. R., 453, 454, 459,473 MYSAK, L. A. and LIN, C. A., 226, 240 MYSAK, L. A., s e e STOCKER, T. F. and MYSAK, L. A. MYSAK, L. A., s e e STOCKER,T. W. et al.
References
Index
NAGATANI, R. M., s e e MILLER, A. J. NAKAJIMA, T. and KING, M. D., 258, 277 NAKAJIMA, T., s e e KAUFMAN, Y. J. and NAKAJIMA, T. NAMIAS, J., 226, 240 NAMIAS, J. and CAYAN, D. R., 226, 240 NAMIAS, J., s e e DOUGLAS,A. V. et al. NANCE, J. D., s e e RADKE, L. F. et al. NAPIER, W. M., 95 NAPIER, W. M. and CLUBE, S. V. M., 97, 143 NARITA, H., s e e MOORE, J. C. et al. NASRALLAH, H. A., BRAZEL, A. J. and BALLING JR., R. C., 501,512 NATIONAL RESEARCH COUNCIL (NRC), 230, 240, 259, 277 NAUJOKAT, B., 202, 240 NEAL, V. T., s e e QUINN, W. H. et al. NEEDHAM, K. J., s e e MITCHELL,J. F. B. et al. NEES, R. T., s e e PROSPERO, J. M. and NEES, R. T. NEES, R. T., s e e PROSPERO, J. M. et al. NEFTEL, A., MOOR, E., OESCHGER, H. and STAUFFER, B., 524, 534 NEFTEL, A., OESCHGER, H., SCHWANDER, J., STAUFFER, B. and ZUMBRUNN,R., 524, 534 NEFTEL, A., OESCHGER, H., STAFFELBACH, T. and STAUFFER, l . , 525, 526, 534 NEFTEL, A., s e e B ARNOLA, J. M. et al. NEFTEL, A., s e e HAMMER, C. U. NEGRI, A. J., ADLER, R. F., MADDOX, R. A., HOWARD, K. W. and KEEHN, P. R., 261,277 NEGRI, A. J., s e e ADLER, R. F. et al. NEINCKE, J., s e e DICKSON,R. R. et al. NELLIS, W. J., s e e GRATZ, A. J. et al. NEUMANN, G. and PIERSON, JR, W. J., 545, 546, 553 NEUSCHULER, D., s e e LUBIN, D. et al. NEWCOMB, W. W., s e e TUCKER, C. J. et al. NEWELL, R. E. and KIDSON, J. W., 457,473 NEWELL, R. E. and WEARE, B. C., 220, 229, 240 NEWELL, R. E., s e e BOTTOMLEY,M. et al. NEWELL, R. E., s e e HSIUNG, J. and NEWELL, R. E. NEWHALL, C. G. and SELF, S., 205,240 NEWHALL, C., s e e SIMKIN,T. et al. NEWIGER, M., 368, 395 NEWMAN, M. J. and ROOD, R. T., 537, 553 NEWSOME, J., s e e BOULTON,G. S. et al. NEWTON, C. R., s e e BICE, D. M. et al. NEZVAL, YE. I., s e e GARADZHA,M. P. and NEZVAL, YE. I. NGUYEN, B. C., BONSANG, B. and GAUDRY, A., 348, 395 NGUYEN, B. C., s e e BINGEMER,H. G. et al. NICHOLLS, N., 216, 223,224, 238, 240, 309, 312 NICHOLLS, N. and KATZ, R. W., 174, 186 NICHOLLS, N. N., s e e HOLLAND,G. J. et al. NICHOLLS, N., s e e ALLAN, R. J. et al. NICHOLLS, N., s e e FOLLAND, C. K. et al.
585
NICHOLLS, N., s e e GLANTZ, M. H. et al. NICHOLLS, S., 373,395 NICHOLS, D. J., JARZEN, D. M., ORTH, C. J. and OLIVER, P. Q., 112, 117, 143 NICHOLS, D. J., s e e JOHNSON, K. R. et al. NICHOLS, F. H., s e e EBBESMEYER,C. C. et al. NICHOLSON, S. E., 166, 187 NICHOLSON, S. E. and ENTEKHABI, D., 218, 229, 240 NICKESON, J. E., s e e HALL, F. G. et al. NICOLET, M., s e e BATES, D. R. and NICOLET, M. NICOLIS, C., 43, 66 NIGAM, S., s e e LINDZEN,R.S. and NIGAM, S. NIGHTINGALE,T., s e e TAYLOR, F. W. et al. NISBET, E. G., s e e DLUGOKENCKY,E. J. et al. NITTA, T. and YAMADA, S., 168, 187 NIU, X. F., s e e MILLER, A. J. NOAD, D., s e e ROUSE, W. R. et al. NOBRE, C. A., SELLERS, P. J. and SHUKLA, J., 435, 455,465,473 NOBRE, C., s e e SHUKLA,J. et al. NOBRE, J. C. A., s e e SHUTTLEWORTH,W. J. et al. NORMAN, J. M., s e e STARKS, P. J. et al. NORTH, G. R., 66, 94 NORTH, G. R. and CROWLEY,T. J., 43, 66 NORTH, G. R., MENGEL, J. G. and SHORT, O. A., 32, 66 NORTH, G. R., s e e CROWLEY, T. J. and NORTH, G. R.
NORTH, G. R., s e e CROWLEY,T. J. et al. NORTH, G. R., s e e SHORT, D. A. et al. NORTH, G. R., s e e SIMPSON,J. et al. NOVAES, F. C., s e e SALATI, E. et al. NOWLAN, G. S., s e e GOODFELLOW,W. D. et al. NRIAGU, J. O., s e e APSIMON, H. et al. NUCCIARONE, J. J., s e e PRABHAKARA,C. et al. NUNEZ, M. and OKE, T. R., 490, 492, 512 NYENZI, B. S., s e e FOLLAND,C. K. et al. O'BRIEN, D. P., s e e CURRIE, R. G. and O'BRIEN, D.P. O'BRIEN, J. J., s e e LUTHER, M. E. et al. O'DOwD, C. D. and SMITH, M. H., 351,382, 395 O'DOWD, C. D., SMITH, M. H. and JENNINGS, S. G., 395 O'KEEFE, J. D. and AHRENS, T. J., 98, 100, 102, 143 O'NEILL, C. A., s e e PENNER, J. E. et al. O'NIELL, C. E., s e e PENNER, J. E. et al. OBERHANSLI, H., s e e Hsu, K. J. et al. OECD, 381,395 OERLEMANS, J., 40, 66 OERLEMANS, J. and VERNEKAR,A. D., 32, 66 OERLEMANS, J., s e e WARRICK, R. A. and OERLEMANS, J. OESCHGER, H., 67, 534 OESCHGER, n., s e e BARNOLA,J. M. et al.
References
Index
OESCHGER, H., s e e BERNER,W. et al. OESCHGER, H., s e e BROECKER,W. S. et al. OESCHGER, H., s e e NEFTEL, A. et al. OESCHGER, H., s e e STAUFFER,B. et al. OESCHGER, H., s e e WATSON, R. W. et al. OFFICER, C. B., s e e CROCKET,J. H. et al. OFFICER, C. B., s e e LYONS, J. B. and OFFICER, C. B. OGILVIE, A. E. J., 193, 241 OGLESBY, R., 39, 66 OGREN, J. A. and CHARLSON,R. J., 382, 395 OHRING, G., GALLO, K., GRUBER, A., PLANET, W., STOWE, L. and TARPLEY, J. D., 246, 277 OKE, T. R., 155, 187, 437, 473, 478, 479, 482, 483, 484, 485, 486, 487, 488, 490, 491, 492, 493, 495, 498, 499, 500, 501, 503, 505, 507, 512 OKE, T. R. and CLEUGH, n. A., 488, 512 OKE, T. R. and EAST, C., 497, 512 OKE, T. R. and FUGGLE, R. F., 512 OKE, T. R. and MCCAUGHEY, J. H., 488, 493,494, 512 OKE, T. R., JOHNSON, G. T., STEYN, O. G. and WATSON, I. D., 488, 499 OKE, T. R., s e e CLEUGH,n. A. and OKE, T. R. OKE, T. R., s e e GRIMMOND, C. S. B. and OKE, T. R. OKE, T. R., s e e GRIMMOND,C. S. B. et al. OKE, T. R., s e e JOHNSON, G. T. et al. OKE, T. R., s e e KALANDA,B. D. et al. OKE, T. R., s e e NUNEZ, M. and OKE, T. R. OKE, T. R., s e e Ross, S. L. and OKE, T. R. OKE, T. R., s e e ROTH, M. and OKE, T. R. OKE, T. R., s e e ROTH, M. et al. OKE, T. R., s e e SCHMID,n. P. and OKE, T. R. OKE, T. R., s e e SCHMID,n. P. et al. OKE, T. R., s e e STEYN, D. G. and OKE, T. R. OKE, T. R., s e e VOOGT, J. A. and OKE, T. R. OKE, T. R., TAESLER, R. and OLSSON, L. E., 480, 512 OKE, T. R., ZEUNER, G. and JAUREGUI, E., 493, 509, 512 OKE, T. R.JOHNSON, G. T., STEYN, D. G. and WATSON, I. D., 489, 512 OKOTH--OGENDO, n. W. O., s e e BILSBORROW,R. E.and OKOTH--OGENDO,n. W. O. OLIVER, P. Q., s e e NICHOLS,D. J. et al. OLSEN, P. E., 24, 66 OLSEN, P. E., FOWELL, S. J. and CORNET, B., 115, 117, 119, 143 OLSON, J. G., s e e TRENBERTH, K. E. and OLSON, J. G. OLSSON, L. E., s e e OKE, T. R. et al. OLTMANS, S. J., s e e SAVOIE, D. L. et al. ONDRUSEK, M., s e e SMITH,R. C. et al. OORT, A. H., 283, 312 OORT, A. H. and LIU, H., 170, 171, 187
586
OORT, A. H. and PEIXOTO, J. P., 283, 291, 312 OORT, A. H., s e e CARISSIMO,B. C. et al. OORT, A. H., s e e KAROLY, D. J. et al. OORT, A. H., s e e PEIXOTO,J. P. and OORT, A. H. OPDYKE, B. N. and WILKINSON,B. H., 104, 143 OPDYKE, N. D., s e e SHACKLETON, N. J. and OPDYKE, N. D. OPPO, D., s e e DUPLESSY,J. C. et al. ORCHARD,M . J . , s e e GELDSETZER,H. H. J. et al. ORCHARD,M. J., s e e GOODFELLOW,W. D. et al. ORTH, C. J., 115, 116, 143 ORTH, C. J., ATTREPJR., M. and QUINTANA, L. R., 115, 116, 117, 124, 143 ORTH, C. J., GILMORE, J. S., QUINTANA, L. R. and SHEEHAN, P. M., 125, 143 ORTH, C. J., s e e JOHNSON,K. R. et al. ORTH, C. J., s e e NICHOLS,D. J. et al. ORTH, C. J., s e e WANG, K. et al. ORTH, C. J., s e e WOLBACH,W. S. et al. ORUE-ETXEBARRIA, s e e ROCCHIA,R. et al. OSBORN, G. and LUCKMAN,B. H., 196, 241 OSTLUND, H. G., DORSEY, H. G. and BRESCHER, R., 88, 93 OTTAWA, 440, 473 OTTERMAN, J., 435, 441,456, 473 OTTERSON, D. A., s e e LEZBERG, E. A. et al. OTTO-BLIESNER, B. L., s e e KUTZBACH, J. E. and OTTO-BLIESNER, B. L. OVERPECK,J., s e e RIND, D. and OVERPECK,J. OWEN, J. A., s e e ROWELL,D. P. et al. OWEN, R. M. and REA, D. K., 84, 93 OWEN, T., CESS, R. D. and RAMANATHAN,V., 537, 553 PACK, D. H., s e e ANGELL, J. K. et al. PACYNA, J. M., s e e APSIMON,H. et al. PAGE, A. L., s e e APSIMON,H. et al. PALMER, C. W. P., s e e TAYLOR, F. W. et al. PALMER, T. N., 238 PALMER, T. N., s e e FOLLAND, C. K. et al. PALUTIKOF, J. P., s e e GODDESS, C. M. et al. PANDEY, J., s e e BHANDARI,N. et al. PANDIS, S. N., PAULSON,S. E., SEINFELD,J. H. and FLAGAN, R. C., 356, 395 PANT, G. B., s e e PARTHASARATHY, B. and PANT, G.B. PANT, G. B., s e e SUKUMAR,R. et al. PAOLINO, D. A., s e e TRENBERTH, K. E. and PAOLINO, D. A. PARK, H., s e e HEATH, D. F. et al. PARKER, D. E. and Cox, D. I., 169, 187 PARKER, D. E. and FOLLAND, C. K., 229, 241 PARKER, D. E., JONES, P. D., BEVAN, A. and FOLLAND, C. K., 160, 187 PARKER, D. E., LEGG, T. P. and FOLLAND, C. K., 151,187 PARKER, D. E., s e e BOTToMLEY, M. et al.
References
Index
PARKER, D. E., s e e FOLLAND, C. K. and PARKER, D.E. PARKER, D. E., s e e FOLLAND, C. K. et al. PARKINSON, C. L. and GLOERSEN, P., 273,277 PARKINSON, C. L., s e e WASHINGTON, W. M. and PARKINSON, C. L. PARRISH, J. T., s e e SPICER, R. A. and PARRISH, J. T. PARTHASARATHY, B. and PANT, G. B., 216, 241 PARTHASARATHY, B., DIAZ, H. F. and EISCHEID, J. K., 217, 241 PASZYNSrd, J., 486, 512 PATEL, S. R., s e e SHUTTLEWORTH,W. J. et al. PATERNE, M., s e e DUPLESSY, J. CL. et al. PATTERSON, D. E., s e e HUSAR, R. B. et al. PATTERSON, E. M. and MCMAHON, C. K., 353,395 PATTERSON, G. R., s e e ETHRIDGE, D. et al. PAULSON, S. E., s e e PANDIS, S. N. et al. PEARMAN, ETHERIDGE, D., DE SILVA, F. and FRASER, P. J., 447 PEARMAN, G. I. and FRASER, P. J., 447,473 PEARMAN, G. I., ETHERIDGE, D., DE SILVA, F. and FRASER, P. J., 473,525,534 PEARMAN, G. I., s e e ETHERIDGE, D. M. et al. PECKHAM, G. E., s e e B ARATH, F. T. et al. PEIXOTO, J. P. and OORT, A. H., 268, 271, 277, 283, 291,293,296, 297, 312 PEIXOTO, J. P., s e e OORT, A. H. and PEIXtDTO,J. P. PELTIER, W. R., 41, 66 PELTIER, W. R., s e e DEBLONDE, G. and PELTIER, W.R. PELTIER, W. R., s e e HYDE, W. T. and PELTIER, W. R.
PELTIER, W. R., s e e SHACKLETON,N. J. et al. PELTIER, W. R., s e e TUSHINGHAM, A. M. and PELTIER, W. R. PENG, T.-H., s e e BROECKER, W. S. and PENG, T.H. PENNER, J. E., DICKINSON, R. E. and O'NEILL, C. A., 231, 241, 348, 362, 363, 364, 367, 369, 376, 378,395,434, 437, 451,452, 473 PENNER, J. E., s e e GHAN, S. J. et al. PEPIN, T. J., s e e MCCORMICK, M. P. et al. PEPPLER, R. A., s e e LAMB, P. J. and PEPPLER, R. A. PEREIRA, M. C., s e e ANDREAE, M. O. et al. PEREIRA, M. C., s e e KAUFMAN, Y. J. et al. PERRITT, R. W., s e e S ALATI, E. et al. PERSSON, A., s e e LYRE, J. R. et al. PESKETT, G. D., s e e TAYLOR, F. W. et al. PESTIAUX, P., DUPLESSY, J. C., VAN DER MERSCH, I. and BERGER, A., 41, 66 PESTIAUX, P., s e e ADEN, J. et al. PESTIAUX, P., s e e ROYER, J. F. et al. PETEET, D. M., s e e BROEcKER, W. S. et al. PETEET, D. M., s e e RIND, D. and PETEET, D. M. PETEET, D. M., s e e RIND, D. et al. PETERSEN, K. L., 194, 241
587
PETERSON, D. H., s e e EBBESMEYER, C. C. et al. PETERSON, J. T. and STOFFEL, T. L., 486, 512 PETERSON, J. Z., FLOWERS, E. C. and RUDISILL, J. H., 486, 512 PETERSON, L. C., s e e IMBRIE, J. et al. PETERSON, M., s e e COOK, E. R. et al. PETERSON, T. C., s e e KARL, T. R. et al. PETERSON, W., s e e BARRON, E. J. and PETERSON, W. PETERSON, W., s e e B ARRON, E. J. et al. PETERSON, W., s e e BRASS, G. et al. PETIT, J. R., s e e JOUZEL, J. et al. PETIT, J.-R., BRIAT, M. and ROYER, A., 350, 396 PETIT-MAIRE, J. R., 38, 66 PETIT-MAIRE, J. R., RISER, J., FABRE, J. and COMMELIN, D., 66 PETIT-MAIRE, N., RISER, J., FABRE, J. and COMMELIN, D., 38 PETRENCHUK, O. P., 350, 351,396 PETROV, V. M., s e e JOUZEL, J. et al. PETROV, V. N., s e e DE ANGELIS, M. et al. PETROV, V. N., s e e LEGRAND, M. R. et al. PETZOLD, D. E., s e e FENG, J. Z. and PETZOLD, D. E. PFAENDTNER, J., s e e SCHUBERT, S. D. et al. PFEIL, F., s e e DURKEE, P. A. et al. PHAM-VAN-DINH, LACAUX, J.-P. and SERPOLAY, R., 376, 396 PHILANDER, S. G. H., 168, 173, 187, 209, 210, 211,213,241,297, 312 PHILANDER, S. G. H., s e e CHAD, Y. and PHILANDER, S. G. H. PHILLIPS, J., s e e LUYENDYK, B. et al. PIASECrd, S., 117, 120, 143 PICKARD, G. L. and EMERY, W. J., 208, 210, 241 PICKETT, H. M., s e e BARATH, F. T. et al. PICON, L., s e e LAVAL, K. and PICON, L. PIEPGRASS, M., s e e TWOMEY, S. A. et al. PIERCE, L.L., s e e RUNNING, S. W. et al. PIERSON, JR, W. J., s e e NEUMANN, G. and PIERSON, JR, W. J. PILAT, M. J., s e e CHARLSON, R. J. and PILAT, M. J. PILAT, M. J., s e e ENSOR, D. S. et al. PINKER, R. T. and LASZLO, I., 265, 266, 277 PINKER, R. T., s e e LASZLO, I. and PINKER, R. T. PINKER, R. T., s e e WHITLOCK, C. H. et al. PINTO, J. P . , s e e MAHLMAN, J. D. et al. PINTO, J. P., s e e WANG, W.-C. et al. PINTY, B., s e e DICKINSON,R. E. et al. PIPER, S. C., s e e KEELING, C. D. et al. PIRRE, M., s e e BRASSEUR, G. P. et al. PISIAS, N. G. and SHACKLETON,N. J., 42 PISIAS, N. G., s e e IMBRIE, J. et al. PISIAS, N. G., s e e KOMINZ, M. A. and PISIAS, N. G. PISIAS, N. G., s e e MARTINSON, D. G. et al. PISIAS, N. G., s e e MOORE, T. C. et al. PISIAS, N. G., s e e SHACKLETON, N. J. et al.
References
Index
PITMAN, A. J., s e e HENDERSON-SELLERS, A. and PITMAN, A. J. PITMAN, A. J., s e e HENDERSON-SELLERS,A. et al. PITMAN, A. J., s e e MCGUFFIE, K. et al. Prr'rocK, A. B., 175, 179, 187, 199, 202, 241 PIVOVAROVA, Z. I., 177, 187 PLANET, W., s e e OHRING,G. et al. PLANTICO, M. S., KARL, T. R., KUKLA, G. and GAVIN, J., 232, 241 PLATT, C. M. R., s e e ETHRIDGE,D. et al. PLATT, T., s e e SATHYENDRANATH,S. et al. PLAYFORD, P. E., s e e BECKER, R. T. et al. PLUMMER, N., s e e JONES, P. D. et al. PLUMMER, N., s e e KARL, T. R. et al. POLCHER, J. and LAVAL, K., 463,473 POLLACK, J. B. et al., 98, 99, 143 POLLACK, J. B., s e e KASTING,J. F. et al. POLLACK, J. B., s e e SAGAN,C. et al. POLLACK, J. B., s e e TURCO, R. P. et al. POLLACK, J. B., TOON, O. W., SAGAN, C., SUMMERS, A., BALDWIN, B. and CAMP, W. V., 205,241 POLLAK, L. D., s e e CONRAD, V. and POLLAK, L. D. POLLARD, D., 40, 66 POLLARD, D. and THOMPSON, S. L., 76, 93 POLLARD, D., s e e BARRON, E. J. et al. POLLARD, D., s e e BONAN, G. B. et al. PONS, A., s e e GUIOT, J. et al. POORE, R. Z., s e e MATTHEWS,R. K. and POORE, R. Z. PORCH, W. M., s e e ENSOR, D. S. et al. PORTER, S. C. and DENTON, G. H., 196, 241 PORTES, J., s e e LE TREUT, H. et al. PORTMAN, D. A., s e e MASS, C. F. and PORTMAN, D.A. POTTER, G. L., s e e CESS, R. D. et al. POTTER, J. F., s e e ROCHE, A. E. et al. POTTER, K. W., 156, 187 POWER, S. B., COLMAN, R. A., MCAVANEY, B. J., DAHNI, R. R., MOORE, A. M. and SMITH, N. R., 308, 312 POWER, S. B., s e e MCAVANEY, B. J. et al. PRABHAKARA, C., DALU, G., LIBERTI, G. L., NUCCIARONE, J. J. and SUHASINI,R., 261,277 PRATHER, M., s e e HANSEN,J. et al. PREINING, O., 358, 396 PREISENDORFER, R. W. and BARNETT, T. P., 450, 473 PRELL, W. L., 31, 66 PRELL, W. L. and KUTZBACH,J. E., 38, 66 PRELL, W. L., s e e IMBRIE,J. et al. PRELL, W. L., s e e LUTHER, M. E. et al. PRELLER, R. H., s e e BARRY, R. G. et al. PREMOLI-SILVA, I., s e e CORFIELD,R. M. et al. PRENTICE, K. C., 467, 473 PRENTICE, K. C. and FUNG, I. Y., 466, 473 PREZELIN, B. B., s e e SMITH, R. C. et al.
588
PRICE, J. C., 502, 513 PRICE, R., s e e APSIMON,H. et al. PRINN, R. G. and FEGLEY, B., 100, 143 PROB,~LD, F., 486, 513 PROFITT, M. H., s e e ANDERSON,J. G. et al. PROSPERO, J. M., 350, 396 PROSPERO, J. M. and NEES, R. T., 350, 388, 396 PROSPERO, J. M., CHARLSON, R. J., MOHNEN, V., JAENICKE, R., DELANY, A. C., MOYERS, J., ZOLLER, W. and RAHN, K., 364, 396 PROSPERO, J. M., SAVOIE, D. L., NEES, R. T., DUCE, R. A. and MERRILL, J., 380, 396 PROSPERO, J. M., s e e DUCE, R. A. et al. PROSPERO, J. M., s e e SAVOIE, D. L. and PROSPERO, J.M.
PROSPERO, J. M., s e e SAVOm, D. L. et al. PROSPERO, J. M., s e e UEMATSU, M. et al. PROTHERO, D. R., s e e SWISHER III, C. C. and PROTHERO, D. R. PRUPPACHER, H. R. and KLETr, J. D., 372, 396 PSZENNY, A. A. P., s e e GALLOWAY,J. N. et al. PSZENNY, A. A. P., s e e HANSEN, A. D. A. et al. PUESCHEL, R. F., s e e ELLIS, H. T. and PUESCHEL, R.F. PUESCHEL, R. F., VAN VALIN, C. C., CASTILLO, R. C., KADLECEK, J. A. and GANOR, E. J., 372, 388, 396 PULWARTY, R. S., s e e DIAZ, H. F. and PULWARTY, R.S.
QIN-WEN, Z., s e e DAo-YI, X. et al. QUADRENNIALOZONESYMPOSIUM,339, 340, 346 QUAITE, F. E., 432 QUAITE, F. E., SUTHERLAND, I . M. and SUTHERLAND, J. C., 424 QUAY, P. D., s e e STUIVER,M. and QUAY, P. D. QUAYLE, R. G., s e e KARL, T. R. et al. QUINBY-HUNT, M. S., s e e WILDE, P. et al. QUINN, P. K., BATES, T. S., JOHNSON, J. E., COVERT, D. S. and CHARLSON,R. J., 381,396 QUINN, P. K., s e e BATES, T. S. et al. QUINN, W. H., 194, 218, 222, 223, 241 QUINN, W. H., NEAL, V. T. and ANTUNEZ DE MAYOLO, S. E., 222, 241 QUINN, W. H., ZOPF, D. O., SHORT, K. S. and Kuo YANG, R. T. W., 222, 241 QUINTANA, L. R., s e e ORTH, C. J. et al. QUIRK, W. J., s e e CHARNEY,J. G. et al. RABINOFF, R., s e e HERMAN,B. M. et al. RADICK, R. R., LOCKWOOD, G. W. and BALIUNAS, S.L., 199, 241 RADKE, L. F., 372, 376, 396 RADKE, L. F., COAKLEYJR., J. A. and KING, M. D., 373,396 RADKE, L. F., HEGG, D. A., HOBBS, P. V., NANCE, J. D., LYONS, J. H., LAURSEN, K. K., WEISS, R.
References
Index
E., RIGGAN, P. J. and WARD, D. E., 366, 376, 396 RADKE, L. F., HEGG, D. A., LYONS, J. D., BROCK, C. A., HOBBS, P. V., WEISS, R. and RASMUSSEN, R., 363,396 RADKE, L. F., s e e HEGG, D. A. et al. RADKE, L. F., s e e HOBBS, P. V. and RADKE, L. F. RADKE, L. F., s e e HOBBS, P. V. et al. RADKE, L. F., s e e KING, M. D. et al. RADKE, L. F., s e e TWOHY, C. H. et al. RAEMDONCK, H., s e e ANDREAE, M. O. et al. RAHN, K., s e e PROSPERO,J. M. et al. RAISBECK, G., s e e JOUZEL, J. et al. RAJAGOPALAN, G., s e e SUKUMAR,R. et al. RAJU, D. S. N., s e e JAIPRAKASH,B. C. et al. RALSTON, C. W., s e e ARMENTANO, T. V. and RALSTON, C. W. RAM, M., s e e ALLEY, R. B. et al. RAMAGE, C. S., 202, 241 RAMAKRISHNAN, P. S., 459, 473 RAMAN, S., s e e HARMS, D. E. et al. RAMANATHAN, V., 53, 66, 318, 346 RAMANATHAN, V. and COLLINS, W., 228, 241 RAMANATHAN, V., CESS, R. D., HARRISON, E. F., MINNIS, P., BARKSTROM, B. R., AHMAD, E. and HARTMANN, D., 228,241, 319, 346 RAMANATHAN, V., s e e CESS, R. D. et al. RAMANATHAN, V., s e e HARRISON,E. F. et al. RAMANATHAN, V., s e e HARTMANN,D. L. et al. RAMANATHAN, V., s e e KIEHL, J. T. and RAMANATHAN, V. RAMANATHAN, V., s e e MADDEN, R. A. and RAMANATHAN, V. RAMANATHAN, V., s e e OWEN, T. et al. RAMANKUTTY, N., s e e SCHLESINGER, M. E. and RAMANKUTTY, N. RAMASWAMY, V., SCHWARZKOPF, M. D. and SHINE, K. P., 319, 320, 336, 346, 419, 432 RAMASWAMY, V., s e e ISAKSEN,I. S. m. et al. RAMASWAMY, W., s e e SCHWARZKOPF, M. D. and RAMASWAMY, V. RAMASWAMY, V., s e e SHINE, K. P. et al. RAMESH, R., s e e SUKUMAR,R. et al. RAMPINO, M. R., 122, 123, 128, 143 RAMPINO, M. R. and CALDEIRA,K., 97, 128, 143 RAMPINO, M. R. and HAGGERTY, B. M., 114, 116, 143 RAMPINO, M. R. and SELF, S., 98, 130, 144 RAMPINO, M. R. and STOTHERS, R. B., 97, 102, 124, 127, 128, 132, 144 RAMPINO, M. R. and VOLK, T., 106, 144 RAMPINO, M. R., s e e CALDEIRA, K. and RAMPINO, M.R. RAMPINO, M. R., s e e CALDEIRA,K. et al. RAMPINO, M. R., s e e LEARY, P. N. and RAMPINO, M.R. RAMPINO, M. R., s e e SELF, S. et al.
589
RAMPINO, M. R., s e e STOTHERS,R. B. et al. RAMPINO, M. R., SELF, S. and STOTHERS, R. B., 129, 131,132, 144 RANDALL, n. A. and TJEMKES, S. A., 254, 277 RANDALL, D. A., s e e CESS, R. D. et al. RAPER, S. C. B., s e e JONES, P. D. et al. RAPER, S. C. B., s e e WIGLEY, T. M. L. and RAPER, S. C. B. RAPER, S. C. B., CHERRY, B. S. G., GODDESS, C. M. and WIGLEY, T. M. L., 156 RASKIN, P., s e e SUBAK, S. et al. RASMUSSEN, E. M. and CARPENTER, T. H., 173, 187 RASMUSSEN, R., s e e KAUFMAN,Y. J. et al. RASMUSSEN, R., s e e RADKE, L. F. et al. RASMUSSON, E. M., 267, 277 RASMUSSON, E. M. and CARPENTER, T. H., 207, 211,213,214,216 RASMUSSON, E. M. and No, K., 301 RASMUSSON, E. M., s e e No, K. and RASMUSSON, E.M. RASMUSSON, E. M., WONG, X. and ROPELEWSKI, C. E., 213,241 RASMUSSON, R. M. and CARPENTER,T. H., 241 RASOOL, S. I. and SCHNEIDER,S. H., 347, 396 RAUP, D. M., 96, 114, 118, 120, 144 RAVINDRAN, P., s e e SATHYENDRANATH,S. et al. RAVISHANKARA,A. R., s e e DEMORE, W. B. et al. RAY, J. D., s e e BOATMAN,J. F. et al. RAYMO, M. E. et al., 117, 144 RAYMO, M. E., s e e IMBRIE,J. et al. RAYMOND, D. J. and JIANG, H., 305, 313 RAYNAUD, D., 524 RAYNAUD, D. and BARNOLA, J. M., 534 RAYNAUD, D., JOUZEL, J., BARNOLA, J. M., CHAPPELLAZ, J., DELMAS, R. J. and LORIUS, CL., 47, 66 RAYNAUD, D., s e e BARNOLA, J. M. et al. RAYNAUD, D., s e e CHAPPELLAZ,J. et al. RAYNAUD, D., s e e GENTHON,C. et al. RAYNAUD, D., s e e JOUZEL, J. et al. RAYNAUD, D., s e e LORIUS, C. et al. RAYNAUD, Y., s e e BARNOLA,J. M. et al. RAZUVAYEV, V. N., s e e KARL, T. R. et al. REA, D. K., LEINEN, M. and JANACEK, T. R., 84, 86, 93 REA, D. K., s e e JANACEK,T. R. and REA, D. K. REA, D. K., s e e OWEN, R. M. and REA, D. K. READ, P. L., s e e ALLEN, M. R. et al. READ, W. G., s e e WATERS, J. W. et al. RECKER, E. E., s e e REED, R. J. and RECKER, E. E. REDMOND, K. T., s e e EBBESMEYER,C. C. et al. REED, R. J., 202, 241 REED, R. J. and RECKER, E. E., 305, 313 REEH, N., s e e HUYBRECHTS,PH. et al. REHKOPF, J., 368, 396 REID, G. C., 195, 199, 200, 242
References
Index
REID, G. C., s e e GAGE, K. S. and REID, G. C. REILLE,M., s e e GUIOT,J. et al. REINERS, P. W., s e e BICE, D. M. et al. REINHARDT, K. H., s e e DUCE, R. A. et al. REINSEL, G. C., s e e BOJKOV, R. D. et al. REINSEL, G. C., s e e MILLER, A. J. REISS, M., s e e RUDOLF, B. et al. REMER, L. A., s e e SOMERVILLE, R. C. J. and REMER, L. A. RENNE, P. R. and BASU, A. R., 127, 144 RENNE, P. R. et al., 127, 144 RETALLACK, G. J., LEAHY, G. D. and SPOON, M. D., l l l , 144 REUTER, D., s e e SUSSKIND,J. et al. REYNOLDS, J. F., s e e SCHLESINGER,W. H. et al. REYNOLDS, R. W., 272, 277 REYNOLDS, R. W. and MARSICO, O. C., 154, 187 RHEIN, M., s e e SCHLOSSER,P. et al. RHINES, P. B., s e e BREWER, P. G. et al. RIBEIRO, M. N. G., s e e SHUTTLEWORTH,W. J. et al. RICH, P. V., s e e RICH, T. H. et al. RICH, Z. n., RICH, P. V., WAGSTAFF, B., MCEWAN-MASON, J., DOUTHITT, C. B., GREGORY, R. T. and FELTON, E. A., 73, 93 RIEHARDS, F. and ARrdN, P. A., 261,278 RICHARDS, G. R., 231,242 RICHARDS, J. F., 434, 439, 473 RIEHARDS, J. F., s e e HOUGHTON,R. A. et al. RIEHARDS, J. F., s e e TURNERII, B. L. et al. RICHARDSONIII, J. B., s e e ROLLINS, H. B. et al. RICHARDSON, S. M., s e e KASTING,J. F. et al. RICHARDSON, S. M., s e e KASTING, J. K. and RICHARDSON, S. M. RICHES, M. R., s e e CESS, R. D. et al. RICKARDS, R. B., s e e COCKS, L. R. M. and RICKARDS, R. B. RIEBSAME, W. E., 438,473 RIGGAN, P. J., s e e RADKE, L. F. et al. RIKUS, L., s e e CESS, R. D. et al. RILEY, J. P. and CHESTER, R., 545,553 RIND, D., 35, 66, 84, 93,530 RIND, D. and CHANDLER, M., 84, 85, 86, 93 RIND, D. and OVERPECK,J., 200, 242 RIND, D. and PETEET, D., 36, 66, 84, 93 RIND, D., GOLDBERG,R. and RUEDY, R., 164, 187 RIND, D., PETEET, D. and KUIO~A,G., 39, 67 RIND, D., PETEET, D. M., BROECKER, W. S., MACINTYRE, A. and RUDDIMAN, W. F., 37, 66, 84, 93,535 RIND, D., s e e BROEcKER, W. S. et al. RIND, D., s e e CHANDLER, M. et al. RIND, D., s e e HANSEN, J. et al. RIND, D., s e e LEAN, J. and RIND, D. RIND, D., s e e TSELIOUDIS,G. et al. RISER, J., s e e PETIT-MAIRE,J. R. et al. RITCHEY, N. A., s e e DARNELL,W. L. et al. RITEHEY, N. m., s e e WHITLOEK,C. n. et al.
590
RITCHIE, E. A. and HOLLAND,G. J., 305, 313 RITCHIE, E. A., HOLLAND, G. J. and LANDER, M., 305,313 Rrrz, C., s e e JOUZEL,J. et al. ROBERT, C. and CHAMLEY, H., 112, 144 ROBERTS, A. D., s e e LUBIN, D. et al. ROBERTS, J., s e e SHUTTLEWORTH,W. J. et al. ROBERTSON, A. W., s e e HOSKINS,B. J. et al. ROBINSON, D. A., 278 ROBINSON, D. A., DEWEY, K. F. and HElM JR., R. R., 273 ROBINSON, D. A., SERREZE, M. C., BARRY, R. G., SCHARFEN,G. and KUKLA, G., 272, 273,278 ROBOCK, A., 173, 177, 187 ROBUIN, G., s e e STORETVEDT,K. M. et al. ROCCHIA, R., BOCLET, D., BONTE, P., BUFFETAUT, E., ORUE-ETXEBARRIA, JAEGER, J.-J. and JEHANNO, C., 144 ROCCHIA, R., BOCLET, O., COURTILLOT, V. and JAEGER, J.-J., 134, 144 ROCHE, A. E., KUMER, J. B., MERGENTHALER, J. L., ELY, G. A., UPLINGER,W. G., POTTER, J. F., JAMES, Z. C. and STERRIT,L. W., 41 l, 432 RODDA, J. C., 155, 187 RODDY, D. J., s e e TINUS, R. W. and RODDY, D. J. RODGERS, C. D., s e e TAYLOR, F. W. et al. RODGERS, C. F., s e e HUDSON,J. G. et al. RODHE, H., s e e CHARLSON,R. J. et al. RODHE, H., s e e ENGARDT,M. and RODHE, H. RODHE, H., s e e ISAKSEN,I. S. A. et al. RODHE, H., s e e LANGNER,J. and RODHE, H. RODHE, H., s e e LANGNER,J. et al. RODHE, H., s e e WATSON, R. W. et al. ROEEKNER, E., s e e BARNETT,T. P. et al. ROECKNER, E., s e e CESS, R. D. et al. ROELOFFZEN, H., s e e KEELING,C. D. ROGERS J., s e e VANLOON, H. and ROGERS, J. ROGERS, C. F., HUDSON, J. G., ZIELINSKA, B., TANNER, R. L., HALLErr, J. and WATSON, J. G., 376, 396 ROGERS, C. F., s e e HALLETT, J. et al. ROGERS, J. C., 218, 242 ROLLINS, H. B., RICHARDSON III, J. B. and SANDWEISS, D. H., 224, 242 RONOV, A., s e e BUDYKO, M. and RONOV, A. ROOD, R. B., s e e SCHUBERT, S. D. et al. ROOD, R. T., s e e NEWMAN,M. J. and ROOD, R. T. ROOSEN, G. R., ANGIONNE,R. J. and KLEMCKE, C. H., 379, 396 ROOTH, C., 43, 67 ROOTH, C. G., s e e BREWER, P. G. et al. ROPELEWSKI, C. E., s e e RASMUSSON,E. M. et al. ROPELEWSrd, C. F. and HALPERT, M. S., 214, 220, 221,242 ROPELEWSrd, C. F. and JONES, P. D., 174, 187 ROSEN, R. D., SALSTEIN, D. A. and WOOD, T. M., 291,292, 313
References
Index
ROSEN, R. D., s e e HIDE, R. et al. ROSENFIELD, J., s e e SUSSKIND,J. et al. Ross, S. L. and OKE, T. R., 479, 513 ROSSOW, W. B., 255, 278 Rossow, W. B. and SCHIFFER,R. A., 255, 278 ROSSOW, W. B., s e e Fu, R. et al. Rossow, W. B., s e e TSELIOUDIS,G. et al. Rossow, W., s e e HANSEN,J. et al. ROTH, M., 496, 513 ROTH, M. and OKE, T. R., 496, 513 ROTH, M., OKE, T. R. and EMERY, W. J., 502, 513 ROTH, M., OKE, T. R. and STEYN, D. G., 496, 513 ROTHLISBERGER,F. and GEYH, M. A., 196, 242 ROUSE, W. R., NOAD, D. and MCCUTCHEON, J., 486, 487, 513 ROWELL, D. P., FOLLAND, C. K., MASKELL, K, OWEN, J. A. and WARD, M. N., 166, 187 ROWNTREE, P. R., 455,473 ROWNTREE,P. R., s e e LEAN,J. and ROWNTREE,P. R. ROWNTREE, P. R., s e e MYLNE, M. F. and ROWNTREE, P. R. ROWNTREE, P. R., s e e WALKER, J. and ROWNTREE, P.R. ROY, C. T., GIES, H. P. and GRAEME, E., 425,432 ROYER, A., s e e PETIT, J.-R. et al. ROYER, J. F., 38 ROYER, J. F., DEQUE, M. and PESTIAUX, P., 39, 67 ROYER, J. F., s e e CESS, R. D. et al. RUBENSTONE,J. L., s e e GUILDERSON,TH. P. et al. RUDDIMAN, W. F. and KUTZBACH,J. E., 34, 67 RUDDIMAN, W. F. and MCINTYRE, A., 24, 40, 67 RUDDIMAN, W. F., KIDD, R. B., THOMAS, E. et al., 31, 67 RUDDIMAN, W. F., s e e RIND, D. et al. RUDISILL, J. H., s e e PETERSON,J. T. et al. RUDOLF, B., HAUSCHILD, H., REISS, M. and SCHNEIDER, U., 156, 187 RUDOLPH, J., s e e EHHALT, D. H. et al. RUEDI, R., s e e HANSEN, J. et al. RUEDY, R., s e e HANSEN, J. et al. RUEDY, R., s e e RIND, D. et al. RUFFELL, A., s e e SIMMS, M. J. and RUFFELL, A. RUMBAUGH, W. F., 154, 187 RUNNING, S. W., JUSTICE, C. O., SALOMONSON,V., HALL, D., BARKER, J., KAUFMANN, Y. J., STRAHLER, A. H., HUETE, A. R., MULLER, J.-P., VANDERBILT, V., WAN, Z. M., TEILLET, P. and CARNEGGIE, O., 267, 278 RUNNING, S. W., LOVELAND, Z. R., PIERCE, L.L. and HUNTJR., E. R., 269, 278 RUSSEL, G., s e e HANSEN, J. et al. RUSSELL III, J. M., s e e GILLE, J. C. and RUSSELL III, J. M. RUTHKOSKY, M. S., s e e WOLFF, G. R. et al. RUTLEDGE, G., LEGG, E. and MENZEL, P., 262, 278 RYAN, B. F., WATTERSON, I. G. and EVANS, J. L., 310,313
591
SACHSE, G. W., s e e ANDREAE,M. O. et al. SADLER, J. C., 305, 313 SAGAN, C. and MULLEN, G., 537, 553 SAGAN, C., s e e POLLACK,J. I . et al. SAGAN, C., s e e TURCO, R. P. et al. SAGAN, C., TOON, O. B. and POLLACK, J. B., 231, 242, 435,440, 452, 474 SAITO, Z., YAMANOI,Z. and KAIHO, K., 117, 144 SALATI, E., DOUROJEANNI, M. J., NOVAES, F. C., DE OLIVEIRA, A. E., PERRITT, R. W., SCHUBART, H. O. R. and UMANA, J. C., 437, 474 SALINGER, M. J., HAY, J. E., MCGANN, R. and FITZHARRIS, B. B., 164, 187 SALOMONSON,V., s e e RUNNING, S. W. et al. SALSTEIN, D. A., s e e HIDE, R. et al. SALSTEIN, O. A., s e e ROSEN, R. D. et al. SALTZMAN, B., 40, 43, 67 S ALTZMAN,B. and MAASCH, K. A., 42, 67 SALTZMAN, B. and SUTERA,A., 43, 67 SALTZMAN,B., HANSEN,A. R. and MAASCH, K. A., 42, 67 SALTZMAN, B., s e e MAASCH, K. A. and SALTZMAN, B. SALTZMAN, E., s e e BRASS, G. et al. SALTZMAN,E. S., s e e LEGRAND,M. R. et al. SALTZMAN, E. S., s e e SAVOIE, D. L. et al. SANCETTA, C., HEUSSER, L. and HALL, M. A., 117, 144 SANCETTA, C., IMBRIE, J. and KIPP, N. G., 23, 67 SANDBERG, C. A., ZIEGLER, W., DREESEN, R. and BUTLER, J. L., 124, 125, 144 SANDERSON, M., KUMANAN, I., TANGUAY, T. and SCHERTZER,W., 486, 513 SANDWEISS, D. H., 224, 242 SANDWEISS, D. H., s e e ROLLINS, n. B. et al. SANHUEZA, E., HAO, W. M., SCHARFFE, O., DONESO, L. and CRUTZEN,P. J., 448, 474 SANHUEZA, E., s e e SCHARFFE,O. et al. SANHUEZA, E., s e e WATSON, R. T. et al. SANHUEZA, E., s e e WATSON, R. W. et al. SANTER, B. D., WIGLEY, Z. M. L. and JONES, P. D., 181,188 SANTER, B., BERGER, A., EDDY, J. A., FLOHN, H., IMBRIE, J., LITT, Z., SCHNEIDER, S. H., SCHWEINGRUBER, F. H. and STUIVER, M., 39, 67 SANTER, R., s e e FOUQUART,Y. et al. SARDESHMUKH,P. D. and HOSKINS, B. J., 289, 290, 298,299, 304, 313 SARDESHMUKH,P. D., s e e HOSKINS, B. J. et al. SARGENT, N. E., s e e BOER, G. J. and SARGENT, N. E. SARMIENTO, J. L., 527 SARMIENTO,J. L. and TOGGWEILER,R., 535 SATA, M., s e e HANSEN,J. et al. SATHYENDRANATH,S., GOUVEIA,A. D., SHETYE, S. R., RAVINDRAN,P. and PLATT, T., 541,553
References
Index
S ATO, M., s e e HANSEN,J. et al. SATO, M., s e e LACIS, A. et al. SAUSEN, R., BARTHEL, K. and HASSELMANN, K., 33, 67 SAUSEN, R., s e e KONIG, W. et al. SAVIN, S., 73, 93 SAVIN, S., DOUGLAS, R. G. and STEHLI, F. G., 74, 93 SAVlN, S., s e e BARRERA,E. et al. SAVOIE, D. L. and PROSPERO,J. M., 380, 396 SAVOIE, D. L., PROSPERO, J. M. and SALTZMAN,E. S., 380, 396 SAVOIE, D. L., PROSPERO, J. M., LARSEN, R. J. and SALTZMANN, E. S., 380, 396 SAVOIE, D. L., PROSPERO, J. M., OLTMANS, S. J., GRAUSTEIN, W. C., TUREKIAN, K. K., MERRILL, J. T. and LEVY III, H., 380, 396 SAVOIE, D. L., s e e PROSPERO,J. M. et al. SAX, R. I. and HUDSON,J. G., 372, 397 SCHAAKE, P., 151, 188 SCHARFEN, G., s e e ROBINSON,D. A. et al. SCHARFFE, D., HAD, W. M., DONOSO, L., CRUTZEN, P. J. and SANHUEZA,E., 449,474 SCHARFFE, D., s e e SANHUEZA,E. et al. SCHEBESKE, G., s e e ANDREAE,T. W. et al. SCHECHER, W. D., s e e CORRELL, D. L. et al. SCHERTZER, W., s e e SANDERSON,M. et al. SCHIDLOWSKI,M., s e e AHARON, P. et al. SCHIDLOWSKI, M., s e e WALKER,J. C. G. et al. SCHIFFER, R. A., s e e Rossow, W. B. and SCHIFFER, R.A. SCHILLING, D. H., s e e HUGHES,T. J. et al. SCHLESE, U., s e e BARNETT,T. P. et al. SCHLESE, U., s e e CESS, R. D. et al. SCHLESlNGER, M. E., 10, 18, 33, 67, 230, 242 SCHLESINGER, M. E. and MITCHELL, J. F. B., 33, 67, 384, 397 SCHLESINGER, M. E. and RAMANKUTTY, N., 175, 178, 188, 200, 226, 242 SCHLESIMGER, M. E., s e e BARNETT, T. P. and SCHLESINGER,M. E. SCHLESINGER, M. E., s e e BARNETT,T. P. et al. SCHLESINGER, W. H., REYNOLDS, J. F., CUNNINGHAM, G. L., HUENNEKE,L. F., JARRELL,W. M., VIRGINIA, R. A. and WHITFORD, W. G., 448,474 SCHLESINGER,W. H., s e e HOUGHTON,R. A. et al. SCHLOSSER, P., BONISCH, G., RHEIM, M. and BAYER, R., 532, 535 SCHMID, H. P., 484, 513 SCHMID, H. P. and OKE, T. R., 484, 513 SCHMID, H. P., CLEUGH, H. A., GRIMMOND, C. S. B. and OKE, T. R., 488, 513 SCHMIDT, M., 200, 242, 372, 380, 397 SCHMIDT, U., s e e EHHALT, D. H. et al. SCHNEIDER, N. M., s e e MELOSH, H. J. et al. SCHNEIDER, S. H., 7, 8, 18, 552
592
SCHNEIDER, S. H. and BOSTON, P. J., 2, 18 SCHNEIDER, S. H. and LONDER, R., 542, 553 SCHNEIDER, S. H. and THOMPSON, S. L., 32, 67, 93, 135, 144 SCHNEIDER, S. H., s e e BARROM,E. J. et al. SCHNEIDER, S. H., s e e COVEY, C. et al. SCHNEIDER, S. H., s e e HARVEY, L. D. D. and SCHNEIDER, S. H. SCHNEIDER, S. H., s e e RASOOL, S. I. and SCHNEIDER, S. n. SCHNEIDER, S. H., s e e SANTER, B. et al. SCHNEIDER, S. n., s e e TAYLOR, B. L. et al. SCHNEIDER, S. H., THOMPSON, S. L. and B ARRON, E. J., 84 SCHNEIDER, S. S., 231,242 SCHNEIDER,O., s e e RUDOLF, B. et al. SCHNELL, R. C., s e e KAHL, J. D. W. et al. SCHNETZLER,C. C., s e e BLUTH, G. J. S. et al. SCHONLAUB,H. P., s e e HOLSER,W. T. et al. SCHOPF, J. W., 4, 18 SCHOPF, P. S., s e e HARRISON,D. E. and SCHOPF, P. S. SCHOPF, T. J. M., s e e WISE, K. P. and SCHOPF, T. J. M. SCHOTLAND,R., s e e GALL, R. et al. SCHUBART, H. O. R., s e e SALATI, E. et al. SCHUBERT,J. K. and BOTTJER, D. J., 117, 144 SCHUBERT, S. D., ROOD, R. B. and PFAENDTMER, J., 263,278 SCHUBERT, W. H., HACK, J. J., SILVA DIAS, P. L. and FULTON, S. R., 290, 313 SCHUBERT,W. H., s e e SILVADIAS, P. L. et al. SCHULTZ, P. H. and GAULT, D. E., 101,144 SCHOTZ, L., 350, 397 SCHWANDER,J., s e e NEFTEL, A. et al. SCHWANDER,J., s e e STAUFFER,B. et al. SCHWARTZ, S. A., s e e VERSTRAETE, M. M. and SCHWARTZ, S. A. SCHWARTZ, S. E., 348, 376, 397, 545,553 SCHWARTZ, S. E., s e e CHARLSON,R. J. et al. SCHWARTZ, S. E., s e e TEN BRINK, H. M. et al. SCHWARTZMAN, D. W. and VOLK, T., 539, 547, 548, 553 SCHWARZKOPF, M. D. and RAMASWAMY, V., 336, 346, 419, 432 SCHWARZKOPF,M. D., s e e RAMASWAMY,V. et al. SCHWARZKOPF,M. D., s e e StoNE, K. P. et al. SCHWEIGER,A. J. and KEY, J. R., 257, 278 SCHWEINGRUBER,F. H., s e e BRIFFA, K. R. et al. SCHWEINGRuBER,F. H., s e e SANTER,B. et al. SCOTTO, J.., COTrOM, G., URBACH, F., BERGER, D. and FEARS, T., 425,435 SEAMAN, N. L, LUDWIG, F. L., DONALL, E. G., WARNER, T. T. and BHRUMRALKAR,C. M., 479, 507, 509, 513 SEAR, C. B., KELLY, P. M., JONES, P. D. and GODDESS, C. M., 176, 188
References
Index
SEAR, C. B., s e e KELLY, P. M. and SEAR, C. B. SEARS, J. W. and ALT, D., 129, 144 SEBAI, A., FERAUD, G. and HANES, J., 144 SEBAI, A., FERAUD, G., BERTRAND, H. and HANES, J., 127 SECKMEYER, G. and MCKENZIE, R. L., 425, 432 SELLER, W. and CRUTZEN, P. J., 444, 474 SEINFELD, J. H., s e e PANDIS, S. N. et al. SEINFELD, J. H., s e e ZHANG, S.-H. et al. SEKERA, Z. and DAVE, J. V., 409,432 SEKIHARA, K., 486, 513 SEKINE, K., s e e YAMASHITA, S. and SEKINE, K. SELF, S., RAMPINO, M. R. and BERBERA, J. J., 205, 242 SELF, S., s e e NEWHALL,C. G. and SELF, S. SELF, S., s e e RAMPINO, M. R. and SELF, S. SELF, S., s e e RAMPINO,M. R. et al. SELF, S., s e e STOTHERS, R. B. et al. SELF, S., s e e THORDARSON,TH. and SELF, S. SELLERS, A. and MEADOWS, A., 75, 94 SELLERS, P. J., HALL, F. G., ASRAR, G., STREBEL, D. E. and MURPHY, R. E., 270, 278 SELLERS, P. J., HEISER, M. D. and HALL, F. G., 270, 278 SELLERS, P. J., s e e HALL, F. G. et al. SELLERS, P. J., s e e NOBRE, C. A. et al. SELLERS, P. J., s e e SHUKLA,J. et al. SELLERS, W. D., 32, 67,230, 242 SELTZER, G. O., 196, 242 SENIOR, C. A. and MITCHELL, J. F. B., 33, 67 SENIOR, C. A., s e e HALL, N. M. J. et al. SENIOR, C. A., s e e MITCHELL,J. F. B. et al. SEPKOSKI JR., J. J., 117, 145 SEREEZE, M. C., s e e KAHL, J. D. W. et al. SERPOLAY, R., s e e PHAM-VAN-DINHet al. SERREZE, M. C., s e e BARRY, R. G. et al. SERREZE, M. C., s e e ROBINSON,D. A. et al. SETLOW, R. B., 420, 432 SETON, J., s e e TWOMEY, S. et al. SETZER, A. W., s e e ANDREAE,M. O. et al. SETZER, A., s e e KAUFMAN,Y. J. et al. SEVRUK, B., 155, 188 SHACKLETON, N. J., 66, 526, 535 SHACKLETON, N. J. and BOERSMA, A., 81,82, 88, 94 SHACKLETON, N. J. and IMBRIE, J., 21, 67 SHACKLETON, N. J. and KENNETT, J. P., 82, 94 SHACKLETON, N. J. and OPDYKE, N. D., 22, 23, 67 SHACKLETON, N. J., BACKMAN, J. et al., 108, 117, 145 SHACKLETON, N. J., BERGER, A. and PELTIER, W. R., 22, 68 SHACKLETON, N. J., IMBRIE, J. and HALL, M. A., 518,535,547,553 SHACKLETON, N. J., IMBRIE, J. and PISIAS, N. G., 31, 68 SHACKLETON, N. J., LE, J., MIX, A. and HALL, M. A., 47, 49, 50, 68
593
SHACKLETON, N. J., s e e BOERSMA, A. and SHACKLETON, N. J. SHACKLETON, N. J., s e e BOERSMA,A. et al. SHACKLETON, N. J., s e e CHAPPELL, J. and SHACKLETON, N. J. SHACKLETON, N. J., s e e DUPLESSY,J. C. et al. SHACKLETON, N. J., s e e GALL~E, H. et al. SHACKLETON, N. J., s e e HAYS, J. D. SHACKLETON, N. J., s e e IMBRIE,J. et al. SHACKLETON, N. J., s e e MARTINSON, D. G. et al. SHACKLETON, N. J., s e e SHACKLETON,N. J. SHANKLIN, J. D., s e e FARMAN,J. C. et al. SHARPTON, V. L., DALRYMPLE, G. B. et al., 96, 145 SHARPTON, V. L., s e e DE SILVA, S. L. et al. SHAW, D., s e e DONN, W. and SHAW, D. SHAW, G. E., 348,360, 397 SHAW, M., s e e ZHANG, S.-H. et al. SHEA, D. J., s e e MADDEN, R. m. et a l . SHEA, D. J., s e e TRENBERTH, K. and SHEA, D. J. \ SHEA, D. J., s e e VAN LOON, H. and SHEA, n. J. SHEA, n. M. and AUER, A. H., 496, 503, 513 SHEAFFER, J. D., s e e GRAY, W. M. et al. SHEEHAN, P. M. et al., 96, 145 SHEEHAN, P. M., s e e ORTH, C. J. et al. SHEININ, D. A., s e e CESS, R. D. et al. SHELDON, G. W., s e e TEGART, W. J. McG. et al. SHEMA, R., s e e DURKEE, P. A. et al. SHEN, G. T., s e e COLE, J. E. et al. SHETYE, S. R., s e e SATHYENDRANATH,S. et al. SHEU, P. J., s e e LAU, K.-M. and SHEU, P. J. SHICKEDANZ, P. T., s e e CHANGNONJR., S. A. et al. SHINE, K. P., BRIEGLEB, B. P., GROSSMAN, A., HAUGLUSTAINE, D., MAD, H., RAMASWAMY,V., SCHWARZKOPF, M. D., VAN DORLAND, R. and WANG, W.-C., 336, 346 SHINE, K. P., HENDERSON-SELLERS, A. and SLINGO, A., 375,397 SHINE, K. P., s e e RAMASWAMY,V. et al. SHINE, K. P., s e e AUSTIN, J. et al. SHINE, K. P., s e e RAMASWAMY,V. et al. SHIOTANI, S., s e e KAHL, J. D. W. et al. SHIYATOV, S. G., s e e GRAYBILL, D. A. and SHIYATOV, S. G. SHMITZ, J., s e e GALL, R. et al. SHOEMAKER, C. S., s e e SHOEMAKER, E. M. et al. SHOEMAKER, E. M., s e e EMILIANI, C. et al. SHOEMAKER, E. M., WOLFE, R. F. and SHOEMAKER, C. S., 95, 97, 135, 145 SHORT, D. A., MENGEL, J. G., CROWLEY, T. J., HYDE, W. T. and NORTH, G. R., 32, 68 SHORT, D. A., s e e CROWLEY,T. J. et al. SHORT, D. A., s e e NORTH, G. R. et al. SHORT, K. S., s e e QUINN, W. H. et al. SHOWERS, W., s e e MARGOLIS, S. V. et al. SHREFFLER, J. H., 495, 513 SHUGART, H. H., s e e EMANUEL,W. R. et al.
References
Index
SHUGART, H. H., s e e SMITH, T. M. and SHUGART, H.H. SHUKLA, J., 474 SHUKLA, J. and MINTZ, Y., 260, 278, 435,474 SHUKLA, J., NOBRE, C. and SELLERS, P. J., 437, 455,459 SHUKLA, J., s e e NOBRE,C. A. et al. SHUKLA, J., s e e Sun, Y. C. et al. SHUKLA, P. N., s e e BHANOARI,N. et al. SHULKA, J., s e e BENGTSSON,L. and SHULKA,J. SHUMAN, C. A., s e e ALLEY, R. B. et al. SHUMWAY, S. E., s e e HOBBS, P. V. et al. SHUTTLEWORTH, W. J., GASH, J. H. C., LLOYD, J. C. R., MOORE, C. J., ROBERTS, J., MARQUES FILHO, A. DE O., FISCH, G., DE PAULA SILVA FILHO, V., RIBEIRO, M. N. G., MOLION, L. C. B., DE ABREU SA, L. D., NOBRE, J. C. A., CABRAL, G. M. R., PATEL, S. R. and DE MORALS, J. C., 453, 474 SIEBERT, L., s e e SIMKIN, T. et al. SIEBES, G., s e e B ARATH, F. T. et al. SIEGENTHALER,U., 527 SIEGENTHALER, U. and WENK, T., 535 SIEGENTHALER, U., s e e LEUENBERGER, M. and SIEGENTHALER,U. SIEGENTHALER,U., s e e STAUFFER,B. et al. SIEGENTHALER,U., s e e WATSON,R. W. et al. SIEGMUND,P. C., 313 SIELMANN, F., s e e KONIG, W. et al. SILVERING, n., s e e BOATMAN,J. F. et al. SILVERING, H., s e e GALLOWAY,J. N. et al. SIGNOR III, P. W. and LIees, J. H., 114, 145 SIGURDSSON, H., 96, 129, 130, 145,205,242 SIGURDSSON, H., D'HONDT, S. and CAREY, S., 102, 145 SIGURDSSON, H., D'HONDT, S., ARTHUR, M. A. et al., 134, 145 SILVA DIAS, P. L., SCHUBERT, W. H. and DEMARIA, M., 290, 313 SILVA DIAS, P. L., s e e ANDREAE,M. O. et al. SILVADIAS, P. L., s e e SCHUBERT,W. H. et al. SIMET, C., s e e BOND, G. et al. SIMKIN, T., SIEBERT, L., MCCLELLAND, L., BRIDGE, D., NEWHALL, C. and LATTER, J. H., 177, 188 SIMMONDS, I., s e e MURRAY, R. J. and SIMMONDS, I. SIMMS, M. J., 119, 145 SIMMS, M. J. and RUFFELL, A., 119, 145 SIMMS, M. J., s e e JOHNSON, A. L. A. and SIMMS, M.J. SIMPSON, J. and WIGGERT,V., 373,397 SIMPSON, J. S., KEENAN, T. D., FERRIER, B., SIMPSON, R. H. and HOLLAND,G. J., 305, 313 SIMPSON, J., ADLER, R. F. and NORTH, G. R., 261, 278 SIMPSON, R. H., s e e SIMPSON,J. S. et al.
594
SINGH, I. B., s e e AHARON, P. et al. SINGH, J., s e e JAIPRAKASH, B. C. et al. SINHA, S. K., s e e KILADIS,G. N. and SINHA, S. K. SKINNER, B., s e e APSIMON,H. et al. SKULL, D. and TUCKER,C., 246, 278 SKULL, D. L. and TUCKER, C. J., 444, 474 SKULL, D. L., s e e HOUGHTON,R. A. and SKULL, D. L. SKUMANICH,m., s e e LEAN, J. et al. SKUMANICH,L., s e e LEAN, J. et al. SLAPER, H., s e e DE GRUIJL, F. R. et al. SLINGO, A., 378, 397 SLINGO, A. and SLINGO, J. M., 278 SLINGO, A., s e e CESS, R. D. et al. SLINGO, A., s e e SHINE, K. P. et al. SLINGO, J. M. and SLINGO, A., 254 SLINGO, J. M., s e e SLINGO, A. and SLINGO, J. M. SLINGO, J., s e e TANRE, D. et al. SLINN, W. G. N., 384, 397 SLOAN, J., s e e BRASS, G. et al. SLOAN, L. C. and BARRON, E. J., 83, 84, 86, 87, 88, 94 SLUSSER, J., s e e STAMNES, K. et al. SLUTZ, R. J., s e e WOODRUFF, S. D. et al. SMIC, 350, 351,397 SMILEY, C. J., 73, 94 SMIT, J., 96, 103, 107, 110, 111, 112, 113, 145 SMIT, J. and HERTOGEN, J., 95, 145 SMIT, J., MONTANARI,A. et al., 96, 145 SMITH, E. A., COOPER, H. J., CROSSON, W. L. and HENG-YI, W., 270, 278 SMITH, E. A., s e e WILBER, A. C. et al. SMITH, G. D., s e e BOULTON, G. S. et al. SMITH, G. L., s e e B ARKSTROM, B. R. and SMITH, G.L. SMITH, L. A., s e e ALLEN, M. R. et al. SMITH, L. D. and VONDERHAAR, T. H., 257, 278 SMITH, L., s e e FOUQUART,Y. et al. SMITH, M. H., s e e LATHAM,J. and SMITH, i . H. SMITH, M. H., s e e O'nown, C. D. and SMITH, i . H. SMITH, M. H., s e e O ' Down, C. D. et al. SMITH, N. R., s e e POWER, S. B. et al. SMITH, R. C., PREZELIN, B. B., BAKER, K. S., BIDIGARE, R. R., BOUCHER, N. P., COLEY, T., KARENTZ, D., MAClNTYRE, S., MATLICK, H. A., MENZlES, D., ONDRUSEK, M., WAN, Z. and WATERS, K. J., 425,432 SMITH, T. M. and SHUGART, H. H., 465,474 SMITH, W. E., s e e Sun, Y. C. and SMITH, W. E. SMITH, W. L., s e e MINNIS, P. et al. SODEN, B. J. and BRETHERTON, F. P., 263,278 SOKOLOV, A. P., s e e CESS, R. D. et al. SOLOMON, m., s e e TRENBERTH, K. E. and SOLOMON,A. SOLOMON, S., s e e BRASSEUR,G. P. and SOLOMON, S.
References
Index
SOLOW,A., s e e GORNITZ, V. and SOLOW,A. SOLTIS, F. S., s e e BARATH,F. T. et al. SOMERVILLE,R. C. J. and REMER,L. A., 260, 278 SOUTHAM,J., s e e BRASS, G. et al. SOWERS, T., s e e JOUZEL, J. et al. SPELMAN, M. J. and MANABE, S., 85, 94 SPELMAN,M. J., s e e MANABE, S. et al. SPENCER, M. J., s e e MAYEWSrd, P. A. et al. SPENCER,R. W., 156, 188 SPENCER,R. W. and CHRISTY,J. R., 169, 170, 171, 172, 173, 188, 205,220, 232, 242, 262, 278 SPICER, R. A. and CORFIELD,R. M., 72, 73, 94 SPICER, R. A. and PARRISH, J. T., 73, 94 SPIRO, P. A., JACOB, D. J. and LOGAN, J. A., 357, 397 SPITTLEHOUSE, D. L., s e e KALANDA, B. D. et al. SPIVAKOVSKY, C. M., YEVICH, R., LOGAN, J. A., WOFSY, S. C. and MCELROY, M. B., 338, 346 SPOON, M. D., s e e RETALLACK, G. J. et al. SPYERS-DURAN, P. A., s e e FITZGERALD, J. W. and SPYERS-DURAN,P. A. SQUIRES, P., s e e TWOMEY, S. and SQUIRES, P. STAEHELIN, J., s e e STOLARSKI, R. S. et al. STAFFELBACH, T., s e e NEFTEL, A. et al. STALLARD,R. F., s e e D'HONDT, S. et al. STALLARD,R. F., s e e KELLER, M. et al. STAMNES, K., SLUSSER, J., BOWEN, M., BOOTH, C. and LUCAS, T., 425,432 STANHILL,G. and KALMA,J. D., 486, 508, 513 STANHILL, G. and MORESHET, S., 486, 513 STANLEY, S. M., 97, 122, 123, 145 STANLEY, S. M. and CAMPBELL, L. D., 117, 145 STARKS, P. J., NORMAN, J. M., BLAD, B. L., WALTER-SHEA, E. A. and WALTHALL, C. L., 265,278 STAUFFER, B., HOFER, H., OESCHGER, H., SCHWANDER, J. and SIEGENTHALER, U., 230, 242, 523,535 STAUFFER, B., s e e BERNER, W. et al. STAUFFER, B., s e e JOHNSEN, S. J. et al. STAUFFER,B., s e e NEFrEL, m. et al. STAUFFER, R. J., s e e JOHNSEN, S. J. STAUFFER, R. J., s e e MANABE, S. and STAUFFER, R. J.
STAYLOR, W. F., s e e DARNELL, W. L. et al. STAYLOR, W. F., s e e WHITLOCK, C. H. et al. STEDMAN,D. H., s e e WOLFF, G. R. et al. STEELE, L. P., s e e DLUGOKENCKY,E. J. et al. STEFFENSEN, J. P., s e e DANSGAARD, W. et al. STEFFENSEN, J. P., s e e JOHNSEN, S. J. et al. STEHLI, F. G., s e e SAVIN, S. et al. STEINNES, E., s e e APSIMON, H. et al. STEPANOV, V., s e e CAMPBELL, I. H. et al. STEPHENS, G. L., 370, 397 STEPHENS, G. L. and GREENwALD, T. J., 256, 257, 278 STEPHENS, G. L., s e e TJEMKES, S. A. et al.
595
STEPHENS,G., s e e MALINGREAU,J. P. et al. STEPHENSON, D. and HELD, I. M., 313 STERENBORG, H. J. C. M., s e e DE GRUIJL, F. R. et al. STERRIT,L. W., s e e ROCHE, A. E. et al. STEURER, P. M., s e e KARL, T. R. and STEURER,P. M. STEURER, P. M., s e e WOODRUFF, S. D. et al. STEVENS, C. M., s e e CRAIG, H. et al. STEVENSON,D. J., s e e WALKER,J. C. G. et al. STEVENSON, M. P., s e e EMANUEL, W. R. et al. STEYN, D. G., 496, 513 STEYN, D. G. and OKE, T. R., 488, 513 STEYN, D. G., s e e JOHNSON, G. T. et al. STEYN, D. G., s e e OKE, T. R. et al. STEYN, D. G., s e e ROTH, M. et al. STIEVENARD, M., s e e JOUZEL, J. STIEVENARD, M., s e e JOUZEL, J. et al. STOCKER,T. F. and MYSAK, L. A., 192, 195, 226, 242 STOCKER,T. W. and WRIGHT,D. G., 37, 43, 68 STOCKER, T. W., WRIGHT, D. G. and MYSAK, L. A., 43, 68 STOCKTON, C. W. and MEKO, D. M., 199, 242 STOCKTON, C. W., MITCHELLJR., J. M. and MEKO, D. M., 201,242 STOCKTON, C. W., s e e MITCHELLJR., J. M. et al. STOFFEL, T. L., s e e PETERSON, J. T. and STOFFEL, T.L. STOLARSKI, R. S. and CICERONE, R. J., 401,432 STOLARSKI, R. S., BLOOMFIELD, P., MCPETERS, R. D. and HERMAN, J. R., 335,337, 346 STOLARSKI, R. S., BOJKOV, R., BISHOP, L., ZEREFOS, C., STAEHELIN, J. and ZAWODNY, J., 421,425,432 STONE, P. H., 84, 94 STONE, P., s e e HANSEN, J. et al. STONE, R. S., s e e KAHL, J. D. W. et al. STORETVEDT,K. M., MITCHELL,J. G., ABRANCHES, M. C., MAALOE, S. and ROBUIN, G., 127, 145 STORMS, n., s e e ARTAXO, P. et al. STOTHERS, R. B., 128, 145 STOTHERS, R. B., s e e RAMPINO, M. R. and STOTHERS,R. B. STOTHERS, R. B., s e e RAMPINO, M. R. et al. STOTHERS, R. B., WOLFE, J. A., SELF, S. and RAMPINO, M. R., 130, 131 STOTT, L. D. and KENNETT, J. P., 104, 108, 110, 134, 145 STOTT, L. D., s e e ZACHOS, J. C. et al. STOUFFER, R., 345 STOUFFER, R. J., MANABE, S. and BRYAN, K., 40, 68, 175, 188 STOUFFER,R. J., MANABE,S. and VINNIKOV,K. Y., 34, 68 STOUFFER, R. J., s e e DELWoRTH, T. et al. STOUFFER, R. J., s e e GATES, W. L. et al.
References
Index
STOUFFER, R. J., s e e KAROLY,D. J. et al. STOUFFER, R. J., s e e MANABE, S. and STOUFFER,R. J.
STOUFFER, R. J., s e e MANABE,S. et al. STOWE, L. L., s e e HUSAR, R. B. and STOWE,L. L. STOWE, L. L., s e e MINNIS, P. et al. STOWE, L., s e e OHRING,G. et al. STRAHLER, A. n., s e e RUNNING, S. W. et al. STRAMSKI, O., s e e BRICAUD, A. and STRAMSKI,O. STRAPP, J. W., s e e LEAITCH,W. R. et al. STREBEL, D. E., s e e SELLERS, P. J. et al. STREET, F. A. and GROVE, A. T., 24, 68 STREET-PERROTT, F. A., 34, 68 STREET-PERROTT, F. A. and HARRISON, S. P., 35, 68 STREET-PERROTT, F. A., MITCHELL, J. F. B., MARCHAND, D. S. and BRUNNER,J. S., 38, 68 STREET-PERROTT, F. A., s e e KUTZBACH, J. E. and STREET-PERROTT, F. A. STREET-PERROTT,F. A., s e e WEBB, Z. et al. STRETEN, N. A., 208, 243 STRETEN, N. A. and ZILLMAN,J. W., 208, 243 STRICKLER, R. F., s e e MANABE, S. and STRICKLER, R.F. STROUP, D. P., s e e WOLFF,G. R. et al. STUIVER, M. and BRAZIUNAS,T. F., 175, 188 STUIVER, M. and QUAY, P. D., 200, 243 STUIVER, M., s e e GROOTES,P. M. et al. STUIVER, M., s e e SANTER,B. et al. SUAREZ, M. J. and HELD, I. M., 32, 68 SUBAK, S., RASKIN, P. and HIPPEL, D. V., 322, 323, 346 SUCKLING,P. W., 487, 513 SUD, Y. C. and FENNESSY, M., 456, 458,474 SUD, Y. C. and SMITH, W. E., 437, 474 SUD, Y. C., CHAO, W. C. and WALKER,G. K., 269, 279 SUD, Y. C., SHUKLA, J. and MINTZ, Y., 455,474 SUHASINI, R., s e e PRABHAKARA,C. et al. SUKUMAR, R., RAMESH, R., PANT, G. B. and RAJAGOPALAN,G., 194, 243 SUMAN, D. O., 355,397 SUMMERS, A., s e e POLLACK,J. B. et al. SUN, D. Z., 38 SUN, D. Z. and LINDZEN,R. S., 36, 68 SUN, Y., s e e Xu, D. et al. SUSSKIND, J., 262, 271,279 SUSSKIND, J., ROSENFIELD,J. and REUTER, D., 263, 279 SUSSKIND, J., s e e CHAHINE,M. T. and SUSSKIND,J. SUTERA, A., s e e SALTzMAN, B. and SUTERA,A. SUTHERLAND, B. M., s e e QUAITE, F. E. et al. SUTHERLAND, J. C., s e e QUAITE, F. E. et al. SUTTER, C. B., s e e DESHLER,T. et al. SUTTIE, R. A., s e e B ARATH, F. T. et al. SVEINBJORNSDOTTIR,A. E., s e e DANSGAARD,W. et al.
596
SWAID, H. and HOFFMAN,M. E., 492, 513 SWAIN, A. M., s e e BRYSON,R. A. and SWAIN,A. M. SWAP, R., GARSTANG,M., GRECO, S., TALBOT, R. and KALLBERG,P., 350, 397 SWIFT, J. H., s e e BREWER, P. G. et al. SWISHERIII, C. C. and PROTHERO,D. R., 118, 145 SWISSLER,T. J., s e e MCCORMICK,M. P. et al. SYTKUS, J. I., s e e FRAKES, L. A. et al. TAESLER, R., s e e OKE, T. R. et al. TAKAHASHI, T., s e e BREWER, P. G. et al. TAKAMURA, T., 488, 513 TALBOT, R. W., ANDREAE, M. O., ANDREAE,T. W. and HARRISS, R. C., 353,356, 376, 397 TALBOT, R. W., ANDREAE,M. O., BERRESHEIM,n., ARTAXO, P., GARSTANG, M., HARRISS, R. C., BELCHER, K. M. and LI, S. M., 350, 356, 397 TALBOT, R. W., s e e ANDREAE,M. O. et al. TALBOT, R. W., s e e SWAP, R. et al. TALLEY, L. D. and MCCARTNEY, M. S., 88, 94 TANAKA, M., 304, 313 TANAKA, M., s e e YAMAMOTO,G. M. et al. TANG, I. N., 363, 397 TANG, W., s e e LIU, W. T. et al. TANGUAY,T., s e e SANDERSON,M. et al. TANIMOTO, T., s e e ANDERSON, D. L. et al. TANNER, R. L., s e e ROGERS, C. F. et al. TANRE, D., GELEYN, J. F. and SLINGO,J., 368, 397 TANRE, D., s e e KAUFMAN,Y. J. et al. TANRE, D., s e e KING, M. D. et al. TANS, P. P., s e e DLUGOKENCKY,E. J. et al. TAPPER, N. J., 503, 513 TARPLEY, J. D., s e e GALLO, K. P. et al. TARPLEY, J. D., s e e OHRING,G. et al. TARRASON, L. and IVERSEN,T., 379, 397 TARSALA,J. A., s e e BARATH,F. T. et al. TAYLOR, B. L., GAL-CHEN, T. and SCHNEIDER, S. H., 205,243 TAYLOR, F. W., RODGERS,C. O., WHITNEY, J. G., WERRETT, S. T., BARNETT, J. J., PESKETT, G. D., VENTERS, P., BALLARD, J., PALMER, C. W. P., KNIGHT, R. J., MORRIS, P., NIGHTINGALE,T. and DUDHA, A., 411,432 TAYLOR, K. C., HAMMER, C. U., ALLEY, R. B., CLAUSEN, H. B., DAHL-JENSEN, D., GOW, A. J., GUNDESTRUP, N. S., KIPSTUHL,J., MOORE, J. C. and WADDINGTON,E. D., 25, 68 TAYLOR, K. C., s e e ALLEY, R. B. et al. TAYLOR, K. C., s e e CESS, R. D. et al. TAYLOR, K. E., s e e CESS, R. D. et al. TAYLOR, K. E., s e e GHAN, S. J. et al. TAYLOR, K. E., s e e MAZUMBER,A. et al. TAYLOR, W. D., s e e GHAN, S. J. et al. TAYLOR, W. D., s e e MAZUMBER,A. et al. TEDESCO, K., s e e BOND, G. et al. TEGART, W. J. McG., SHELDON, G. W. and GRIFFITHS, D. C., 2, 18
References Index TEILLET, P., s e e RUNNING, S. W. et al. TELLER, J. T., s e e BROECKER,W. S. et al. TEN BRINK, H. M., SCHWARTZ, S. E. and DAUM, P. H., 363,397 THIERSTEIN, n. R., 103, 109, 145, 146 THOMAS, D. S. G., s e e MIDDLETON, N. and THOMAS, D. S. G. THOMAS, E., 86, 94 THOMAS, E., s e e RUDDIMAN,W. F. et al. THOMAS, G. E., s e e McKAY, C. P. and THOMAS, G. E. THOMAS, R. H., 273,279 THOMPSON, A. M., 319, 342, 346 THOMPSON, L. G., 243 THOMPSON, L. G., MOSLEY-THOMPSON, E. and ARNAO, B. M., 222, 243 THOMPSON, L. G., MOSLEY-THOMPSON, E. and THOMPSON, P. A., 223,227,243 THOMPSON, L. G., s e e MICHAELSEN, J. and THOMPSON, L. G. THOMPSON, P. A., 223 THOMPSON, P. A., s e e THOMPSON,L. G. et al. THOMPSON, S. L., s e e BARRON, E. J. et al. THOMPSON, S. L., s e e BONAN, G. B. et al. THOMPSON, S. L., s e e COVEY, C. and THOMPSON, S.L. THOMPSON, S. L., s e e COVEY, C. et al. THOMPSON, S. L., s e e POLLARD,D. and THOMPSON, S.L. THOMPSON, S. L., s e e SCHNEIDER, S. H. and THOMPSON, S. L. THOMPSON, S. L., s e e TRIPOLI, G. J. and THOMPSON, S. L. THORDARSON, TH. and SELF, S., 129, 130, 146 THORNTON, I., s e e APSIMON, H. et al. THUNELL, R. C., 119, 146 THUNELL, R. C., s e e GERSTEL, J. et al. TIAO, G. C., s e e BOJKOV, R. D. et al. TIAO, G. C., s e e MILLER, A. J. TIEDTKE, M., s e e HECKLEY,W. A. et al. TINDALE, N. W., s e e BETZER, P. R. et al. TINUS, R. W. and RODDY, D. J., 99, 101,146 TIWARI, R. S. and VIJAYA, 120, 146 TJEMKES, S. A., s e e RANDALL, D. A. and TJEMKES, S.A. TJEMKES, S. A., STEPHENS, G. L. and JACKSON, D. L., 263,279 TOGGWEILER, J. R., s e e IMBRIE,J. et al. TOGGWEILER, R., s e e SARMIENTO, J. L. and TOGGWEILER, R. TOKIOKA, T., s e e MITCHELL,J. F. B. et al. TOKOS, J., s e e CHURCH, Z. M. et al. TOMINAGA, K., s e e YOSHIDA,A. et al. TOON, O. B. et al., 98, 99, 100, 146 TOON, O. B., s e e KASTING,J. F. et al. TOON, O. B., s e e SAGAN, C. et al. TOON, O. B., s e e TURCO, R. P. et al.
597
TOON, O. W., s e e POLLACK,J. B. et al. TORRES, A. L., s e e ANDREAE,M. O. et al. TOWNSEND, R. D. and JOHNSON, D. R., 285, 313 TRAINER, M., s e e FEHSENFELD, F. et al. TRAMONTANO, J. M., s e e CHURCH, T. M. et al. TRENBERTH, K. E., 33, 68, 156, 167, 168, 169, 188, 208, 209, 211, 213, 227, 228, 243, 268, 279, 283,284, 286, 302, 303, 313 TRENBERTH, K. E. and OLSON, J. G., 170, 188, 283, 313 TRENBERTH, K. E. and PAOLINO, D. A., 156, 188 TRENBERTH, K. E. and SHEA, D. J., 213,243 TRENBERTH, K. E. and SOLOMON, A., 286, 293, 294, 295, 313 TRENBERTH, K. E., BERRY, J. C. and BUJA, L. E., 286, 313 TRENBERTH, K. E., BRANSTATOR, G. W. and ARKIN, P. A., 262, 279 TRENBERTH, K. E., CHRISTY, J. R. and HURRELL, J. W., 159, 170, 188 TRENBERTH, K. E., s e e HURRELL, J. W. and TRENBERTH, K. E. TRIBBIA, J. J., s e e MADDEN, R. A. et al. TRICOT, C., 52, 53, 68 TRICOT, C. and BERGER, A., 30, 68 TRICOT, C., s e e BERGER, A. et al. TRICOT, C., s e e GALLI~E,H. et al. TRIPOLI, G. J. and THOMPSON, S. L., 130, 146 TROTTER, D. E., s e e EDDY, J. A. et al. TRUMBORE, S., s e e BROECKER,W. S. et al. TSELIOUDIS, G., Rossow, W. B. and RIND, D., 256, 259,260, 279 TSONIS, A. A., s e e ELSNER, J. B. and TSONIS, A. A. TUCKER, C. J., DREGNE, H. E. and NEWCOMB, W. W., 436, 441,443,452, 474 TUCKER, C. J., s e e KAUFMAN,Y. J. et al. TUCKER, C. J., s e e SKOLE, D. L. and TUCKER, C. J. TUEDY, R., s e e CHANDLER,M. et al. TUNCEL, G., ARAS, N. K. and ZOLLER, W. H., 380, 397 TURCO, R. P., TOON, O. B., ACKERMAN, T. P., POLLACK, J. B. and SAGAN, C., 100, 101, 135, 146 TUREKIAN, K. K., s e e SAVOIE, D. L. et al. TURNER II, B. L., CLARK, W. C., KATES, R. W., RICHARDS, J. F., MATHEWS, J. T. and MEYER, W. B., 437, 474 TURVEY, D. E., s e e AVERS, G. P. et al. TUSHINGHAM, A. M. and PELTIER, W. R., 24, 68 TWICKLER, M. S., s e e MAYEWSKI,P. A. et al. TWIST, D., s e e ELSTON, W. E. and TWIST, D. TWOHY, C. H., CLARKE, A. D., WARREN, S. G., RADKE, L. F. and CHARLSON, R. J., 377, 397 TWOMEY, S., 348, 373,377, 378,387, 397, 398 TWOMEY, S. A., PIEPGRASS, M. and WOLFE, Z. L., 377, 382, 398 TWOMEY, S. and SQUIRES, P., 372, 398
References
Index
TWOMEY, S. and WARNER, J., 372, 398 TWOMEY, S., DAVIDSON, K. A. and SETON, J., 372, 380, 398 TWOMEY, S., s e e WARNER, J. and TWOMEY, S. UDO, R. K., AREOLA, O. O., AYOADE, J. O. and AFOLAYAN, A. A., 438,474 UEMATSU, M., DUCE, R. A. and PROSPERO, J. M., 350, 398 UEMATSU, M., s e e BETZER, P. R. et al. UHL, C. and BUSCHBACHER,R., 465,474 UMANA, J. C., s e e S ALATI, E. et al. UMSCHEID, L. J., s e e MAHLMAN, J. D. et al. UNCOD, 439, 44 1,474 UNITED NATIONS, 435,441,474, 475,480, 513 UNITED NATIONS ENVIRONMENT PROGRAM, 420, 432, 433, 434, 436, 441, 442, 474, 475, 480, 481,513 UPCHURCH JR., G. R., 111, 112, 146 UPCHURCH JR., G. R., s e e WOLFE, J. A. and UPCHURCHJR., G. R. UPLINGER, W. G., s e e ROCHE, A. E. et al. UPPALA, S., s e e HOLLINGSWORTH,A. et al. URBACH, F., BERGER, D. and DAVIES, R. E., 420, 432 URBACH, F., s e e SCOTTO,J. et al. UREY, H. C., 95, 97, 146 US NATIONALACADEMY of SCIENCES, 5, 18 V ALDES, P., 90, 94 V ALDES, P. J., s e e HALL, N. M. J. et al. VALDES, P. J., s e e HOSKINS,B. J. and VALDES, P. J. VALENTINE, J. W., 120, 122, 146 VAN DER LEUN, J. C., s e e DE GRUIJL, F. R. et al. VANDER MERSCH, I., s e e PESTIAUX,P. et al. VAN DORLAND, R., s e e SHINE, K. P. et al. VAN GRIEKEN, R., s e e ARTAXO, P. et al. VAN LOON, H., 156, 188 VAN LOON, H. and LABITZKE, K., 175, 179, 188, 202, 203,204, 243 VAN LOON, H. and ROGERS, J., 167, 188, 204, 243 VAN LOON, H. and SHEA, D. J., 174, 188, 213,243 VAN LOON, H., s e e CHEN, W. Y. et al. VAN LOON, H., s e e KILADIS, G. N. and VAN LOON, H. VAN LOON, H., s e e LABITZKE, K. and VAN LOON, H. VAN LOON, H., s e e WILLIAMS,J. and VAN LOON, H. VAN VALIN, C. C., s e e BOATMAN, J. F. et al. VAN VALIN, C. C., s e e PUEScHEL, R. F. et al. VAN WEELDEN, H., s e e DE GRUIJL, F. R. et al. VAN WEERING, T. C. E., s e e DUPLESSY, J. CL. et al. VAN YPERsELE, J. P., s e e ADEM, J. et al. VAN YPERsELE, J. P., s e e BERGER, m. et al. VAN YPERsELE, J. P., s e e GALLEE, H. et al. VANDAMME, D., COURTILLOT, V., BESSE, J. and MONTIGNY, R., 127, 146
598
VANDAMME, D., s e e COURTILLOT,V. et al. VANDERBILT, V., s e e RUNNING, S. W. et al. VARNEY, S. K., s e e HOUGHTON, J. T. et al. VAUTARD, R. and GHIL, M., 201,243 VAUTARD, R., s e e GHIL, M. and VAUTARD, R. VEHIL, R., s e e ESTOURNEL, C. et al. VEIGA, R. E., s e e MCCORMICK, M. P. et al. VEIZER, J., s e e GRUSZCZYNSKI,M. et al. VENKATESAN, M. I. and DAHL, J., 102, 146 VENRICK, E. L., McGOWAN, J. A., CAYAN, D. R. and HAYWARD, T. L., 227, 243 VENTERS, P., s e e TAYLOR, F. W. et al. VERNEKAR, A. D., s e e OERLEMANS, J. and VERNEKAR, A. D. VERSTRAETE, M. M., 446, 465,475 VERSTRAETE,M. M. and SCHWARTZ,S. A., 441,475 VERSTRAETE, M. M., s e e DICKINSON, R. E. et al. VICKERY, A. M. and MELOSH, n. J., 115, 146 VIJAYA, s e e TIWARI, R. S. and VUAYA VILLALBA, R., 194, 243 VINCENT, D. G., 208, 243 VINNIKOV, K. YA., GROISMAN, P. YA. and LUGINA, K. M., 158, 188 VINNIKOV, K. YA., s e e FOLLAND, C. K. et al. VINNIKOV, K. YA., s e e STOUFFER, R. J. et al. VIRGINIA, R. A., s e e SCHLESINGER,W. n. et al. VISSCHER, H. and BRUGMAN, W. A., 117, 120, 146 VITERBO, P., s e e BETTS, A. K. et al. VOGEL, J. L., s e e CHANGNONJR., S. A. et al. VOLK, T., s e e CALDEIRA,K. et al. VOLK, T., s e e KUMP, L. R. and VOLK, T. VOLK, T., s e e RAMPINO,M. R. and VOLK, T. VOLK, T., s e e SCHWARTZMAN,D. W. and VOLK, T. VON RUDLOFF, H., 152, 188 VONDER HAAR, T. H., s e e CARISSIMO, B. C. et al. WONDER HAAR, T. H., s e e SMITH, L. D. and VONDERHAAR, T. H. VOOGT, J. A. and OKE, T. R., 499, 514 VOOGT, J. A., s e e JOHNSON,G. T. et al. VUKOVICH, F. M., 502, 514 VULIS, I. L., s e e CESS, R. D. and VULIS, I. L. WADDINGTON, E. D., s e e ALLEY, R. B. et al. WADDINGTON, E. D., s e e TAYLOR, K. C. et al. WAGGONER, A. P., s e e COVERT, D. S. et al. WAGGONER, A. P., WEISS, A. P., AHLQUIST, N. C., COVERT, D. S. and CHARLSON, R. J., 363, 398 WAGSTAFF, B., s e e RICH, T. H. et al. WALKER, G. K., s e e SOD, Y. C. et al. WALKER, G. T., 214, 243 WALKER, J. and ROWNTREE, P. R., 456, 475 WALKER, J. C. G., 84, 94, 539, 553 WALKER, J. C. G. and KASTING, J. F., 549, 553 WALKER, J. C. G., HAYS, P. B. and KASTING, J. F., 537,538, 547,553 WALKER, J. C. G., KLEIN, C., SCHIDLOWSKI, M., STEVENSON, D. J. and WALTER, M. R., 543, 553
References
Index
WALKER, J. C. G., s e e KASTING, J. F. et al. WALLACE, J. M., 228, 243 WALLACE, J. M. and GUTZLER, D. S., 204, 243, 297, 313 WALLACE, J. M., LIM, G.-H. and BLACKMON, M. L., 302, 313 WALLACE, J. M., s e e DESER, C. and WALLACE, J. M. WALLACE, J. M., s e e HOREL, J. D. and WALLACE, J.M.
WALLACE, J. M., s e e WRIGHT, P. B. et al. WALSH, J. E., s e e CHAPMAN, W. L. and WALSH, J. E. WALSH, K., s e e MCGREGOR, J. L. and WALSH, K. WALTER, L. S., s e e BLUTH, G. J. S. et al. WALTER, M. R., s e e WALKER, J. C. G. et al. WALTER, R. C., s e e EBINGER, C. J. et al. WALTERS, S., s e e BRASSEUR, G. P. et al. WALTER-SHEA, E. A., s e e STARKS, P. J. et al. WALTHALL, C. L., s e e STARKS, P. J. et al. WALTHER, E. G., s e e FLYGER, H. et al. WALTON, J. J., s e e COVEY, C. et al. WALTON, J. J., s e e ELSAESSER,H. W. et al. WALZEBUCK, J., s e e ENGELHARDT,W. v. et al. WAN, Z. M., s e e RUNNING, S. W. et al. WAN, Z., s e e SMITH, R. C. et al. WANDIGA, S. O., s e e ZIMMERMAN,P. R. et al. WANG, C. and LIU, J., 486, 514 WANG, J-X., CHAI, Z-F. et al., 115, 116, 146 WANG, K., 115, 146 WANG, K., ORTH, C. J., ATTREP JR, M., CHATTERTON, B. D. E., Hou, H. and GELDSETZER, H. H. J., 115, 124, 125, 146 WANG, K., ORTH, C. J., ATTREP JR, M., CHATTERTON, B. D. E., WANG, X. and LI, J-J., 146 WANG, W.-C. and ISAKSEN, I. S. A., 344, 346 WANG, W.-C., DUDEK, M. P. and LIANG, X., 327, 328, 331,346 WANG, W.-C., DUDEK, M. P., LIANG, X.-Z. and KIEHL, J. T., 328, 346 WANG, W.-C., PINTO, J. P. and YUNG, Y. L., 319, 336, 339, 346 WANG, W.-C., s e e DUDEK, M. P. et al. WANG, W.-C., s e e JONES, P. D. et al. WANG, W.-C., s e e MOHNEN, V. A. et al. WANG, W.-C., s e e SHINE, K. P. et al. WANG, W.-C., WUEBBLES, D. J., WASHINGTON,W. M., ISAACS, R. G. and MOLNAR, G., 318, 346 WANG, W.-C., YUNG, Y. L., LACIS, A. A., MO, T. and HANSEN, J. E., 318, 346 WANG, W.-C., ZHUANG, Y.-Z. and BOJKOV, R. D., 319, 320, 336, 340, 343,346 WANG, X., s e e WANG, K. et al. WANG, Y. and HOLLAND,G. J., 305, 313 WARD, D. E., 353, 398 WARD, D. E. and HARDY, C. C., 353, 398
599
WARD, D. E., s e e EINFELD, W. et al. WARD, D. E., s e e KAUFMAN, Y. J. et al. WARD, D. E., s e e RADKE, L. F. et al. WARD, M. N., s e e ROWELL, D. P. et al. WARD, P., 114 WARD, P., s e e MARGOLIS, S. V. et al. WARNECK, P., 352, 353, 356, 358, 363, 364, 380, 398 WARNER, C. W., s e e CALDWELL,M. M. et al. WARNER, J. and TWOMEY, S., 372, 376, 380, 398 WARNER, J., s e e TWOMEY, S. and WARNER, J. WARNER, T. T., s e e SEAMAN, N. L. et al. WARREN, S. G. and CLARKE, A. D., 382, 398 WARREN, S. G., HAHN, C. J., LONDON, J., CHERVIN, R. M. and JENNE, R. L., 362, 398 WARREN, S. G., s e e ANDERSON,T. L. et al. WARREN, S. G., s e e CHARLSON,R. J. et al. WARREN, S. G., s e e Zwonv, C. n. et al. WARRICK, R. A. and OERLEMANS,J., 23 l, 243 WARRICK, R. A., BARROW, E. M. and WIGLEY, T. M. L., 57, 68 WARRILOW, D. A., s e e LEAN, J. and WARRILOW, D. A. WASHINGTON,W. M., 345,552 WASHINGTON, W. M. and MEEHL, G. A., 40, 68, 224, 243 WASHINGTON,W. M. and PARKINSON,C. L., 33, 68 WASHINGTON, W. M., s e e BARRON, E. J. and WASHINGTON, W. M. WASHINGTON,W. M., s e e CESS, R. D. et al. WASHINGTON,W. M., s e e WANG, W.-C. et al. WASHINGTON,W. M., s e e WILLIAMS, J. et al. WASSON, J. T., s e e KYTE, F. T. and WASSON, J. T. WASSON, J. T., s e e KYTE, F. T. et al. WATATANI, S., s e e YOSHIDA, A. et al. WATERHOUSE, J. B., 146 WATERMAN, L. S., s e e KEELING,C. D. et al. WATERS, J. W., FROIDEVAUX, L., READ, W. G., MANNEY, G. L., ELSON, L. S., FLOWER, D. A., JARNOT, R. F. and HARWOOD, R. S., 407, 432 WATERS, J. W., s e e BARATH, F. T. et al. WATERS, K. J., s e e SMITH, R. C. et al. WATSON, A. J. and LOVELOCK, J. E., 539, 540, 553 WATSON, I. D., s e e JOHNSON, G. T. et al. WATSON, I. D., s e e OKE, T. R. et al. WATSON, J. G., s e e ROGERS, C. F. et al. WATSON, R. T., MEIRA FILHO, L. G., SANHUEZA, E. and JANETOS, A., 177, 189, 446, 448, 449, 450, 451,475 WATSON, R. W., RODHE, H., OESCHGER, H. and SIEGENTHALER,U., 177, 188 WATTERSON, I. G., s e e FARRELL, B. and WATTERSON, I. G. WATTERSON, I. G., s e e RYAN, B. F. et al. WATTS, M., 441,475 WATTS, R. G., 62 WATTS, R. G. and HAYDER, M. E., 41, 69
References
Index
WATTS,W. A., s e e GRIMM,E. C. et al. WEARE, B. C., 210, 244 WEARE, I . C., s e e NEWELL, R. E. and WEARE, B. C. WEBB, P. N., s e e BARRERA,E. et al. WEBB, R. S. s e e ANDERSON, D. M. and WEBB, R. S. WEBB, T., STREET-PERROTT, F. A. and KUTZBACH, J. E., 37, 69 WEBER, R., s e e MADDEN, R. A. et al. WEBSTER,P. J., 209, 210, 226, 244, 289, 290, 313 WEBSTER,P. J. and CHANG,H.-R., 298, 305, 314 WEBSTER, P. J. and HOLTON, J. R., 298, 314 WEBSTER, P. J. and YANG, S., 214 WEBSTER, P. J., s e e CHANG, H.-R. and WEBSTER, P.J. WEBSTER, P. J., s e e ZHANG, C. and WEBSTER, P. J. WEEMS, R. E., 119, 146 WEERTMAN, J., s e e BIRCHFIELD, G. E. and WEERTMAN, J. WEERTMAN, J., s e e BIRCHFIELD,G. E. et al. WEFERS, M., 350, 398 WEICKMANN, K. M., s e e KILADIS, G. N. and WEICKMANN,K. M. WEISS, A. P., s e e WAGGONER,A. P. et al. WEISS, R. E., s e e COVERT, D. S. et al. WEISS, R. E., s e e RADKE, L. F. et al. WEISSERT, H., s e e Hsu, K. J. et al. WEISSMAN, P. R., s e e COVEY, C. et al. WELCH, R. M., s e e WISCOMBE,W. J. et al. WELHAN, J. A., s e e CRAIG, H. et al. WELLMAN, D. L., s e e BOATMAN,J. F. et al. WELLS, L. E., 224, 244 WENDEL, G. J., s e e WOLFF, G. R. et al. WENDLAND, W. M., 244 WENDLAND, W. M. and BRYSON, R. A., 194 WENK, T., s e e SIEGENTHALER,U. and WENK, T. WENTZ, F. J., 272, 279 WEtCrz, F. J., s e e LIU, W. T. et al. WERRETT, S. T., s e e TAYLOR, F. W. et al. WESTBERG, H., s e e FEHSENFELD,F. et al. WETHERALD,R. T., s e e CESS, R. D. et al. WETHERALD, R. T., s e e KAROLY, D. J. et al. WEZEL, F. C., s e e CROCKET,J. H. et al. WHELPDALE, D. M., KEENE, W. C., HANSEN, A. D. A. and BOATMAN, J., 381,398 WHELPDALE, D. M., s e e CHURCH, Z. M. et al. WHELPDALE, D. M., s e e GALLOWAY,J. N. et al. WHISTON, W., 95, 147 WHITE, G. H., s e e HOSrdNS, B. J. et al. WHITE, J. M., EATON, F. D. and AUER JR., A. H., 487,488, 514 WHITE, J. W. C., s e e ALLEY, R. B. et al. WHITE, J. W. C., s e e GROOTES, P. M. et al. WHITE, O., s e e LEAN, J. et al. WHITE, R. and MCKENZIE, D., 128, 147 WHITE, W. n., 363,398
600
WHITEAND, J. W. C., s e e DANSGAARD,W. et al. WHITFIELD, M., s e e LOVELOCK, J. E. and WHITFIELD, M. WHITFORD, W. G., s e e SCHLESINGER,W. n. et al. WHITLOCK, C. n., CHARLOCK,Z. P., STAYLOR, W. F., PINKER, R. Z., LASZLO, I., DIPASQUALE, R. C. and RITCHEY, N. A., 265,279 WHITLOW, S., s e e MAYEWSKI,P. A. et al. WHITMORE, Z. C., 547, 553 WHITNEY, J. G., s e e TAYLOR, F. W. et al. WHORE, Z. P., s e e KEELING,C. O. WHORE, Z. P., s e e KEELING,C. O. et al. WIDMARK, J. G. V. and MALMGREN,B., 108, 147 WIEBE, n. A., s e e LEAITCH,W. R. et al. WIGGERT, V., s e e SIMPSON,J. and WIGGERT, V. WIGLEY, T. M. L., 17, 18, 40, 69, 158, 326, 348, 383,385,387, 398, 545,553 WIGLEY, Z. M. L. and BARNETr, T. P., 178, 189 WIGLEY, T. M. L. and JONES, P. D., 166, 189 WIGLEY, Z. M. L. and RAPER, S. C. l . , 175, 178, 189, 346 WIGLEY, T. M. L., ANGELL, J. K. and JONES, P. D., 170, 189 WIGLEY, T. M. L., JONES, P. D. and KELLY, P. M., 170, 189 WIGLEY, T. M. L., s e e ISAKSEN,I. S. A. et al. WIGLEY, T. M. L., s e e JONES, P. D. and WIGLEY, T. M. L. WIGLEY, T. M. L., s e e JONES, P. D. et al. WIGLEY, T. M. L., s e e KELLY,P. M. and WIGLEY, T. M. L. WIGLEY, Z. M. L., s e e SANTER, B. D. et al. WIGLEY,T. M. L., s e e WARRICK,R. A. et al. WIGLEY, T. M. L., s e e WILLIAMS,J. and WIGLEY, T. M. L. WIGLEY, T. M. W., s e e JONES, P. O. et al. WILBER, A. C., s e e DARNELL,W. L. et al. WILBER, A. C., s e e GUPTA, S. K. et al. WILBER, A. C., SMITH, E. A. and COOPER, H. J., 276 WILDE, P., BERRY, W. B. N. and QUINBY-HUNT, M.S., 147 WILDE, P., BERRY, W. B. N., QUINBY-HUtCr, M. S. et al., 125 WILHEIT, T. J., CHANG, A. T. C. and CHIU, L. C., 261,279 WILHEIT,T. T., s e e CHANG,A. T. C. and WILHEIT, T.T. WILKINSON, B. n., s e e OPDYKE, B. N. and WILKINSON, B. H. WILKINSON, S. K., s e e BOATMAN, J. F. et al. WILLIAMS JR., C. N., s e e KARL, T. R. and WILLIAMSJR., C. N. WILLIAMSJR., C. N., s e e KARL, Z. R. et al. WILLIAMS R. T., s e e BROEcKER, W. S. et al. WILLIAMS, J. and VAN LOON, n., 156, 189 WILLIAMS, J. and WIGLEY, T. M. L., 168, 189
References
Index
WILLIAMS, J., BARRY, R. G. and WASHINGTON,W. M., 35, 69 WILLIAMS, M., 443,444, 475 WILLIAMS, R. T., s e e BREWER, P. G. et al. WILLIAMS, R. T., s e e HALTINER, G. J. and WILLIAMS, R. T. WILLMOTT, C. J., s e e LEGATES, D. R. and WILLMOTT, C. J. WILLSON, R. C., 244, 245,253,279 WILLSON, R. C. and HUDSON, H. S., 175, 189, 199, 253,279 WILSON, C., s e e FALKOWSKI,P. G. et al. WILSON, H., s e e nANSEN, J. et al. WILSON, M. F., s e e DICKINSON,R. E. et al. WILSON, M. F., s e e GRAETZ, D. et al. WILSON, M. F., s e e HENDERSON-SELLERS,A. and WILSON, M. F. WILSON, W. E., s e e FALKOWSKI,P. G. et al. WILSON, W. E., s e e HUSAR, R. B. and WILSONJR., W.E. WILSON, W. E., s e e HUSAR, R. B. and WILSON, W. E. WILSON, W. J., s e e BARATH, F. Z. et al. WINCHESTER, J. W., s e e LAWSON, D. R. and WINCHESTER, J. W. WING, S. L. and GREENWOOD, D. R., 83, 94 WIRICK, C., s e e FALKOWSKI,P. G. et al. WISCOMBE, W. J., WELCH, R. M. and HALL, W. D., 375, 398 WISE, K. P. and SCHOPF, Z. J. M., 114, 147 WISE, S. W., s e e ZACHOS, J. C. et al. WOFSY, S. C., MCELROY, M. B. and YUNG, Y. L., 401,432 WOFSY, S. C., s e e ANDREAE,M. O. et al. WOFSY, S. C., s e e SPIVAKOVSKY,C. M. et al. WOLBACH, W. S., GILMOUR, I., ANDERS, E., ORTH, C. J. and BROOKS, R. R., 101, 110, 147 WOLBACH, W. S., LEWIS, R. S. and ANDERS, E., 101,147 WOLBACH, W. S., s e e ANDERS, E. et al. WOLBACH, W. S., s e e GILMOUR,I. et al. WOLDEGABRIEL,G., s e e EBINGER,C. J. et al. WOLFE, G. V., s e e ANDERSON,Z. L. et al. WOLFE, J. A., 82, 94, 111, 147 WOLFE, J. A. and UPCHURCH JR., G. R., 74, 94, 111,147 WOLFE, J. A., s e e STOTHERS,R. B. et al. WOLFE, R. F., s e e SHOEMAKER,E. M. et al. WOLFE, T. L., s e e TWOMEY, S. A. et al. WOLFF, G. R., RUTHKOSKY,M. S., STROUP, D. P., KORSOG, P. E., FERMAN, M. A., WENDEL, G. J. and STEDMAN,D. H., 380, 398 WOLFF, J. A., s e e DE SILVA, S. L. et al. WOLFI, W., s e e BROEcKER, W. S. et al. WOLTER, K., 229, 244 WONG, X., s e e RASMUSSON,E. M. et al.
601
WOOD, T. M., s e e ROSEN, R. D. et al. WOODRUFF, S. D., SLUTZ, R. J., JENNE, R. J. and STEURER, P. M., 152, 189 WOODS, P., 465,475 WOODWARD,F. I., s e e ADAMS, J. M. et al. WOOLF, D. K., s e e CIPRIANO, R. J. et al. WORLD CLIMATERESEARCHPROGRAMME(WCRP), 156, 189 WORLD METEOROLOGICALORGANIZATION(WMO), 156, 189, 317, 319, 320, 322, 323, 325, 335, 340, 346, 399, 406, 409, 410, 420, 425, 432, 448,449,475 WORLD METEOROLOGICALORGANIZATION (WMO) and UNITED NATIONS ENVIRONMENT PROGRAMME (UNEP), 160, 164, 189 WORLD RESOURCESINSTITUTE,435,440, 444, 475 WRIGHT JR., H. E., s e e KUTZBACH, J. E. and WRIGHTJR., n. E. WRIGHT, D. G., s e e STOCKER, T. W. and WRIGHT, D.G. WRIGHT, D. G., s e e STOCKER,Z. W. et al. WRIGHT, n. E., 196, 244 WRIGHT, P. B., s e e JONES, P. D. et al. WRIGHT, P. B., WALLACE, J. M., MITCHELL, T. P. and DESER, C., 221,244 WU, G., s e e BERGER, W. H. et al. Wu, K.-D., s e e CHEN, W. Y. et al. Wu, M. L. C. and CHANG, L. A., 265, 279 WUEBBLES, D. J., s e e LACIS, A. A. et al. WUEBBLES, D. J., s e e MILLER, A. J. WUEBBLES, D. J., s e e WANG, W.-C. et al. WYRTKI, K., 210, 212, 244 Xu, D., MA, S., ZHANG, Q. and Xu, D., MA, S., ZHANG, Q. and
CHAI, Z, YANG, Z., CHAI, Z., YANG, Z.,
MAO, X., SUN, Y., 120 MAO, X., SUN, Y., 147
YABUSHITA, S. and ALLEN, A. J., 102, 147 YAGAI, I., s e e CESS, R. D. et al. YAMADA, S., s e e NITTA, T. and YAMADA, S. YAMAMOTO, G. M., TANAKA, M. and ARAO, K., 379, 398 YAMANOI, T., s e e SAITO, T. et al. YAMASAKI, M., 305, 314 YAMASHITA, S., 486, 514 YAMASHITA, S. and SEKINE, K., 479, 514 YAN, Z., s e e DAo-YI, X. et al. YANG, J., s e e GOWARD, S. N. et al. YANG, R., s e e FAN, D. et al. YANG, S., 244 YANG, Z., s e e Xu, D. et al. YAO, J., s e e LI., Z. et al. YAOQI, Z., s e e CHIFANG,C. et al. YAP, D., 491,514 YASUNARI, T., 218, 244 YEMANE, T., s e e EBINGER,C. J. et al.
References
Index
YEN, M.-C., s e e CHEN, W. Y. et al. YERSEL, M. and GOBLE, R., 496, 514 YEVICH, R., s e e SPIVAKOVSKY,C. M. et al. YIM, W., s e e APSIMON, H. et al. YIOU, F., s e e JOUZEL, J. YIOU, F., s e e JOUZEL, J. et al. YIOU, P., s e e JOUZEL, J. et al. YI-YIN, S., s e e DAO-YI, X. et al. YOSHIDA, A., 487, 514 YOSHIDA, A., TOMINAGA, K. and WATATANI, S., 490, 514 YOSHIKADO, H., 505, 514 YOUNG, K. C., 156, 189 YOUNG, K., s e e GALL, R. et al. YOUNG, P. J., s e e KARL, T. R. et al. YOUNG, R. W., s e e BETZER, P. R. et al. YUNG, Y. L., s e e WANG, W.-C. et al. YUNG, Y. L., s e e WOFSY, S. C. et al. YUREVlCH, F. B., s e e COAKLEYJR., J. A. et al.
ZACHOS, J. C. and ARTHUR, M. A., 103, 104, 106, 108, 110, 147 ZACHOS, J. C., ARTHUR, M. A. and DEAN, W. E., 108, 111,147 ZACHOS, J. C., BREZA, J. R. and WISE, S. W., 118, 119, 147 ZACHOS, J. C., s e e CALDEIRA,K. et al. ZACHOS, J. C., s e e GERSTEL, J. et al. ZACHOS, J. C., STOTT, L. D. and LOHMANN, K. C., 82, 83, 94 ZAHNLE, K., 101 ZAHNLE, K. and GRINSPOON, D., 102, 147 ZAHNLE, K. J., 147 ZAHNLE, K. J., s e e KASTING,J. F. et al. ZAHNLE, K., s e e MELOSH, H. J. et al. ZARDECKI, A., s e e GERSTL, S. A. and ZARDECKI, A. ZAWODNY, J., s e e STOLARSKI,R. S. et al.
6O2
ZEBIAK, S. E., 211,244 ZEBIAK, S. E., s e e CANE, M. A. and ZEBIAK, S. E. ZEBIAK, S. E., s e e GORDON,A. L. et al. ZEIGLER, A. M. s e e KUTZBACH,J. E. and ZEIGLER, A.M. ZEREFOS, C., s e e STOLARSKI,R. S. et al. ZETTERBERG,P., s e e BRIFFA, K. R. et al. ZEUNER, G., s e e OKE, T. R. et al. ZHAN, L., s e e LI., Z. et al. ZHANG, C. and WEBSTER, P. J., 298, 314 ZHANG, H., s e e MCGUFFIE, K. et al. ZHANG, M. H., s e e CESS, R. D. et al. ZHANG, Q., s e e Xu, D. et al. ZHANG, S.-H., SHAW, M., SEINFELD, J. H. and FLAGAN, R. C., 356, 398 ZHANG, Y.-S., s e e ANDERSON,D. L. et al. ZHI-FANG, C., s e e DAO-YI, X. et al. ZHOU, L. and KYTE, F. T., 120, 147 ZHOU, Y., s e e LI., Z. et al. ZHOU, Z., s e e KYTE, F. T. et al. ZHUANG, Y.-Z., s e e WANG, W.-C. et al. ZIEGLER, W., s e e SANDBERG,C. A. et al. ZIELINSKA, B., s e e ROGERS, C. F. et al. ZIELINSrd, G. A., s e e ALLEY, R. B. et al. ZILLMAN, J. W., s e e STRETEN, N. A. and ZILLMAN, J.W. ZIMMERMAN, P. R., GREENBERG, J. P., WANDIGA, S. O. and CRUTZEN,P. J., 449, 475 ZIMMERMAN,P., s e e FEHSENFELD,F. et al. ZIMMERMANN,P., s e e LANGNER,J. et al. ZINDLER, A., s e e BARD, E. et al. ZOBRIST, J., s e e DREVER, J. I. and ZOBRIST, J. ZOLLER, W. H., s e e PROSPERO,J. M. et al. ZOLLER, W. H., s e e TUNCEL,G. et al. ZOPF, D. O., s e e QUINN, W. H. et al. ZUMBRUNN, R., s e e NEFFEL, A. ZUMBUHL, H. J., 169, 189
Geographical Index
Adelaide, 493 Africa, 295, 323,376, 388, 440, 457-458, 461-463, 480 Agulhas Plateau, 109 Alaska, 79, 161, 168,221,225 Alps, 120 Amazon, 209, 219, 246, 356, 377, 381, 438, 461462 Antarctic, 75, 78, 108, 119, 162, 291,302, 318, 408, 428,520, 524, 547 Arctic, 202 Atlantic, 107, 166, 193, 195, 461-462, 529-532, 545 Australia, 124-125,162,216-217,295,331,440,480 Austria, 119 Azores, 167 Berlin, 491 Bermuda, 380 Bolivia, 445 Brazil, 122, 445 Budapest, 486, 491 Burma, 445 Byrd Station, Antarctica, 524 Cairo, 194, 501 Cameroon, 445 Camp Century, Greenland, 522, 524 Canada, 116, 161,194, 221,225,425,440, 543 Cape Grim, Tasmania, 364, 373,380 Central America, 445 Chicago, 504 China, 124-125, 197,323,331,369, 388 Christmas Island, 214 Colombia, 445 Congo, 209,445 Copenhagen, 427 Coronation Gulf, 129 Darwin, 210 Detroit, 486 Ecuador, 445 E1Chic6n, 171,176, 207, 351 England, 119 Ethiopia, 218 Europe, 77, 117, 124, 191,323,480 Fairbanks, 491,497
603
Falkland Plateau, 122-123, 127 Fiji, 214 Former Soviet Union, 164, 323 France, 110 Gabon, 445 Galapagos Islands, 208 Germany, 110 Great Plains, 111,201 Greenland, 82, 162, 167-168, 193-194, 272, 382383,463,524, 531 Guadalajara, 500 Guam, 380 Guyanas, 445 Hamilton, 486 Hangchow, 486 Hong Kong, 491 Iceland, 176, 193 India, 445, 497 Indian Ocean, 119, 221,295 Indonesia, 445 Iowa, 194 Isua, 4 Ivory Coast, 445 Jakarta, 481 Japan, 323 Kalahari, 209 Kampuchea, 445 Karachi, 481,501 Kilauea volcano, 133 Korea 507 Krakatoa, 176, 205 Krakow, 486 Kuwait, 501 Laki, 129, 205, 351 Laos, 445 London, 504 Los Angeles, 486, 491 Madagascar, 445 Malaysia, 445 Manhattan, 491 Marshall Islands, 214 Maud Rise, 110, 119
Geographical Index Mauna Loa, 382, 539 Mexico, 219,445,480, 492, 497, 501 Mexico City, 481, 491-492, 493 Mississippi, 43,504 Montreal, 491 Moscow, 491 Mount Pinatubo, 171, 176, 207, 227, 352, 413 St Helens, 176, 351 Myanma, 445 -
Nairobi, 501 Nevada, 125 New York, 505 New Zealand, 110, 480 Nigeria, 438,441,445,497, 501 Nile River, 194, 218, 222-223 Nordeste, Brazil, 218 North Africa, 126 - America, 77, 83, 109 Atlantic, 37, 43 Norway, 193 Norwegian Sea, 523 -
Pacific, 110, 173,208, 210, 295,463, 529-531 Pangea, 122 Papua New Guinea, 445 Paran~i River, 219 Patagonia, 194 Peru, 207-209, 214, 224, 445 Philippines, 445 Phoenix, 501,504 Quebec, 125
S~o Paulo, 481 Scandinavia, 169, 194 Seychelles, 218 Shanghai, 486, 507 Shatsky Rise, 110 Shetland Islands, 82 Siberia, 79, 162, 461-462 Singapore, 481 South Africa, 129 - East Asia, 436, 461-463,497 Spain, 107, 109 Sri Lanka, 218 St Louis, 486, 491,493,504, 506 Sweden, 425 Switzerland, 169 Sydney, 491 Tahiti, 210 Thailand, 445,480, 507 Tibetan plateau, 218 Tokyo, 486, 504-505 Toulouse, 486 Tucson, 491-492, 493,498 Uruguay, 219 USA, 130, 154, 323,369, 384, 425, 438,440, 507 Vancouver, 486, 491,493 Venezuela, 445 Vietnam, 445 Vostok, 522 Walvis Ridge, 108 Weddell Sea, 110
Rocky Mountains, 111 Yukon, 116, 168 Sacramento, 493,500, 501 Sahara, 367,441,443 Sahel, 165-166, 218, 229, 331,441,443, 456-459, 465
604
Z~iire, 445 Zimbabwe, 218
Subject Index
Absorption bands, 317-318, 359 Acid rain, 100-101, 112, 135 Advanced Earth Observing System (ADEOS), 250 -, Very High Resolution Radiometer (AVHRR), 246, 248, 269-270 Aeolian dust, 83-85, 86, 349-351, 364, 367, 434, 532 Aerosol cooling, 347-365,382-384 -, trends, 379-382 -, warming, 365-368 Aerosols, 16-17, 50, 130, 131, 176-177, 207, 231, 253,258, 347-389,433,437,467,485-486 Africa, 295,323,376, 388, 440, 457-458, 461-463, 480 Agricultural trends, 438-439, 448 Airborne Antarctic Ozone Experiment, 416 Air pollution, 480 Alaska, 77, 161, 168, 221,225 Amazon, 209, 219, 246, 356, 377, 381, 438, 461462 Anasazi, 194 Anoxic ocean, 125 Antarctic, 75, 78, 108, 119, 162, 291,302, 318,408, 428,520, 524, 547 -, Bottom Water (AABW), 528 -, ice core, 350 Anticyclones, 301-304 Archaean, 4, 542-543 Arctic, 202 Areal runoff, 297 Asteroids, 95, 97-98, 128, 135, 136, 348 Atlantic, 107, 166, 193, 195, 461-462, 529-531, 532, 545 Atmospheric aerosols, 451-452 -, turbidity, 360 -, waves, 288-291 Atmospheric Model Intercomparison Project (AMIP), 272, 292-293,297,300-301 Attribution of climate change, 180 Benguela Current, 209 Biological pump (oceans), 523 Biomass burning, 349, 353-355, 364, 366, 376, 450-451 Biophysical feedback, 456 Biosphere-Atmosphere Transfer Scheme (BATS), 457,460 Bolide, 116 Bowen ratio, 492
605
Bureau of Meteorology Research Centre (BMRC), 292, 297, 299-301,307-308 C3/C4 pathways (in plants), 550 Cape Grim, Tasmania, 364, 373,380 Carbon budget, 324, 446-448, 526, 549 -, silicate weathering, 547-548 Charney mechanism, 456, 458 Chlorine, 402-403 Chlorofluorocarbons (CFCs), 177, 317-334, 338, 340, 400, 404, 416-4 18,425 CLAW hypothesis, 348, 375-376, 539, 544-546 CLIMAP, 24, 34, 36, 526, 545 Climate analysis, 283-288 -, models, 10, 21, 32, 282-283 -, regulation, 538-541 -, variability, 225-230 Climatic Research Unit (CRU), 157-158 -, effects of atmospheric aerosols, 358-379 Cloud condensation nuclei (CCN), 54, 106, 258260, 348, 351, 370-378, 387-388, 452, 504, 539, 541,549 -, feedbacks, 84, 326, 329, 389,453,461 -, forcing, 268 -, variations, 232, 379 CO2 concentration, 35, 37, 42, 50, 52, 75, 78, 81, 84, 89, 102-105, 126, 133-134, 136, 166, 177, 181, 224-225, 230, 259, 306-307, 317-334, 340, 343, 385-386, 400, 418, 446--451, 464467, 508, 517-518, 520-522, 524-529, 538539,542-543,549-551 -, fertilization, 465 COHMAP, 24, 36 Comets, 97, 102, 115-116, 128, 135, 136, 348 Comprehensive Ocean-Atmosphere Data Set (COADS), 152-153 Cool Sun paradox, 537 Cretaceous, 71-81, 85, 89, 104, 108-110, 133 -, -Tertiary boundary, 100-112, 114-115, 125128, 134-136 Cryosphere, 272-274 Cyclones, 301-304 Daisyworld, 537,539-541 Deep Sea Drilling Project (DSDP), 108-110, 112 Deforestation, 436, 441-446 Demographic change, 324 Desertification, 441-442, 445,454 Devonian, 115
Subject Index Dimethyl sulphide (DMS), 54, 106, 136, 348, 357358,374, 388,539, 541,544-546 Diurnal temperature, 163-164, 384, 502 DNA, 399, 421-422 Dust cloud, 97-98 -, veil index, 177 Earth Observing System (EOS), 250-251,267, 271, 412 Earthquakes, 128 Earth Radiation Budget (ERB), 254-255, 318 , Experiment (ERBE), 254-255,257, 258 East African jet, 457 Eccentricity (of Earth orbit), 26-29 Eemian interglacial, 22, 38 E1 Chic6n, 171, 176, 207, 351 Electromagnetic radiation, 245, 359,487, 492 E1 Nifio, 261, 310 E1 Nifio-Southern Oscillation (ENSO), 173-174, 191, 193, 199, 207-225,229, 262, 282, 297 -, variability, 222-223 Energy balance model (EBM), 10, 75-79 -, consumption, 509 -, use, 437, 501 Enteric fermentation, 450 Eocene, 5, 71-72, 81-88, 89, 115, 118-119 Equilibrium greenhouse warming, 327-331,466 Erosion, 434 European Centre for Medium-range Weather Forecasting (ECMWF), 156, 263,268, 303 Fingerprinting of climate change, 181,274 First GARP Global Experiment (FGGE), 268, 292, 295 First ISLSCP Field Experiment (FIFE), 270 Flood basalts, 123, 127-128, 130-133 Flux correction, 33,271 Foraminifera, 73, 81,107, 226, 518, 526-527 Fossil fuel use, 322-324, 386, 450, 549 Framework Convention on Climate Change, 2 Frasnian-Famennian extinctions, 124-125
Great Plains, 1 1 1 , 2 0 1 Greenhouse effect, 7, 177-178, 180, 230-232, 307309, 317-344, 352, 365, 385-387, 437, 509, 549 -, gas concentrations, 324-325,446-451,538-539 - - , emissions, 322-324 Greenland, 82, 162, 167-168, 193-194, 272, 382383,463,524, 531 -, ice core, 129, 517, 522-523 - - - , project (GRIP), 58, 226, 389, 520 Hadley cell, 8, 10, 45,300, 306, 455,457 Historical record, 157-158 History of meteorological observations, 151-152 Holocene, 25, 37, 56, 195,224, 519, 524 Homogeneity of meteorological record, 152-156 Homoeostatis, 537 Hurricanes- see Tropical cyclones Ice ages, 22 Ice-albedo feedback, 51,330, 467 Ice sheet simulation, 46-54, 56 Impact energy, 97 -, extinction, 114 -, volcanism, 127-129 Indian Ocean, 119, 221,295 Intergovernmental Panel on Climate Change (IPCC), 2-3, 10, 15, 72, 80, 89, 164, 179-180, 230, 321, 324-325,355,358,444, 446, 508 International Oceanographic Commission (IOC), 230 -, Council of Scientific Unions (ICSU), 230 -, Satellite Cloud Climatology Project (ISCCP), 255-256, 265-266, 269 - - , Landsurface Climatology Project (ISLSCP), 270 Interstellar cloud, 102 Intertropical Convergence Zone (ITCZ), 208, 213, 218,295, 299 Iridium, 115-117, 120, 123-124, 126, 136 Irrigation, 438 Isua, 4 Jurassic, 115-117
GARP Atlantic Tropical Experiment (GATE), 261 GENESIS 76-78, 80, 85 Geophysiology, 537-551 Glaciers, 5, 273 Global Atmospheric Research Programme (GARP), 261,268 -, climate model (GCM), 10, 12, 32, 35-36, 73, 75-79, 84-85, 89, 99, 155, 159, 163, 166, 178, 180-182, 224-225, 228, 231, 250-252, 255, 272, 282-283, 285, 292, 321, 323, 327, 334, 342, 369, 378, 453, 456-459, 465, 477, 479,482 -, Precipitation Climatology Project (GPCP), 155156, 261 Gravity wave drag, 288, 290
606
Kalahari, 209 Kellwasser event, 124 Kelvin waves, 210, 288-289 Kepler's second law, 29 Kilauea volcano, 133 Krakatoa, 176, 205 KT boundary - see Cretaceous-Tertiary boundary Lake desiccation, 24 Laki eruption, 129, 205, 351 Landsat, 246-247, 270 Landsurface, 8, 264, 269 Land use change, 246, 331,433-468 La Nifia, 174, 213,222
Subject Index Largescale circulation, 8 Last glacial maximum (LGM), 5, 16, 22-23, 34-36, 52, 54 Laurentide ice sheet, 25, 35, 37 Leaf area index, 269 Little ice age, 168, 175, 195-199, 222, 253 Los Angeles Basin, 356 Macrofossils, 82, 86 Marine mass extinctions, 113 -, stratocumulus, 258 Mass extinctions, 97, 114, 134 Matuyama-Brunhes boundary, 22 Maud Rise, 110, 119 Mauna Loa, 382, 539 Maunder minimum, 175,200 Maximum temperature, 154, 163,497-498 Mediaeval warm period, 168, 193-195, 224 Megacities, 480 Mesospheric ice clouds, 100 Meteorites, 95 Meteorological data assimilation, 263-264, 283 Methane concentration, 177, 230, 317-334, 340, 400, 404, 446-451,464, 520-522, 543 METROMEX, 504 Microtektites, 96, 114,-115, 123, 136 Microwave sounding unit (MSU), 169-173, 176, 205-206, 232, 248, 262-263 Milankovitch theory, 30-31, 40, 44, 231,547 Minimum temperature, 154, 163,497-498 Miocene, 5 Model hierarchy, 10, 21, 32 Monsoon, 38, 194, 209, 214, 216-217, 304-306 -, gyre, 305 Montreal protocol, 2, 324, 426-427 Mount Pinatubo, 171,176, 207, 227, 352, 413 -, St Helens, 176, 351 National Aeronautics and Space Administration (NASA), 246-247,412, 416 Nile River, 194, 218, 222-223 Nitrate aerosols, 356-357 Nitrogen fertilizer, 449 Non-methane hydrocarbons, 356 Nordeste, Brazil, 218 North Atlantic, 37, 43 - - , deep water, 178,226, 520, 524, 528-532, 547 -, Oscillation (NAO), 167 NO x, 100-101, 103, 135, 317-335, 340, 400-401, 404--407, 425,446-451,464 Nuclear winter, 135-136, 347 Numerical weather prediction, 263-264 -
Obliquity (of Earth orbit), 26-29, 51 Ocean alkalinity, 104-106, 527-528 Oceanic conveyor belt, 16, 529-531 -, heat transport, 84-85, 88,326, 331
607
Oligocene, 5, 115, 118 Orbital insolation, 29, 34 -, parameters (of the Earth), 25-29, 200 Ordovician, 125-126 Oxygen isotope, 22-23, 41-42, 47, 49, 73, 80--82, 108-112, 117, 122, 125, 127, 195, 226, 230, 517-525 Ozone concentration (stratosphere), 100, 334-338, 343,399-429 -, "hole", 406-408, 416, 428 -, photochemistry, 400-406 Pacific, 110, 173,208, 210, 295,463,529-531 -, North America pattern (PNA), 297, 304 Palaeoclimate, 22, 32 Palmer Drought Area Index (PDAI), 201-202 - - , Severity Index (PDSI), 200-201 Pangaea, 122 Paran~i River, 219 Permian, 124 , Triassic boundary, 120-124 Phanerozoic, 113 Phase locking (of climate), 41 Pleistocene, 43, 100, 114, 191,230 Pliocene, 89, 100, 116-117 Polar stratospheric clouds (PSCs), 406, 415 Policy development, 2, 22, 180, 425-428 Population, 435, 438,468,477-478, 507 Precambrian, 116, 124-125 Precession (of Earth orbit), 26-29, 51 -, of the perihelion of the axis, 28 Precipitation from satellites, 260-264 -, records, 164-167, 217 Quasi-biennial oscillation (QBO), 179, 199, 202205, 213,288 Quaternary, 5, 55, 59, 539, 544-548 Radiative convective model, 52-53, 98 -, forcing, 320 Reanalysis project, 302 Red noise, 192 Reforestation, 464 Regional climate change, 321 Reservoir construction, 438-440 Rice cultivation, 449-450 Rossby radius of deformation, 290 -, waves, 288-290, 299-301 Roughness length, 454--455,478-479,484, 494 Runaway greenhouse, 6, 59 Sahara, 367, 441,443 Sahel, 165-166, 218, 229, 331,441,443, 456-459, 465 Satellites, 245-274, 335-337, 411, 492, 502, see also EOS, Landsat, MSU, SPOT Sea breeze, 505 -, ice, 273
Subject Index -, salt, 351 Sea-level change, 526 Severe weather events, 309 Skin cancer, 420--423 Snow albedo, 46, 51 Soil erosion, 436, 440 Solar insolation, 101,175,206, 221,252-253,293 -, variability, 199-205 South Pacific Convergence Zone (SPCZ), 208, 218 Southern Oscillation Index (SO1), 174, 207, 210211,213 SPECMAP, 31, 42, 49 Spectral analysis, 47 SPOT, 247 Statistical-dynamical models, 10, 14, 44-54, 339 Storm tracks, 301-304 Stratospheric cooling, 328 -, ice clouds 406-408 -, ozone - see Ozone concentration (stratosphere) -, temperatures, 203 Stromatolites, 117 Sulphate aerosols, 130, 164, 173, 177, 231, 347389,412-415,452 Sunspots, 175, 179, 199, 201-202 Surface albedo, 437, 452, 453, 459, 461,488-489, 540 -, Heat Island Model (SHIM), 499 -, pressure records, 167-168, 203-204 -, Radiation Budget (SRB), 265 Surprises (climate catastrophes), 14, 117, 193, 226, 389, 517-533,550 Teleconnections, 214, 224, 281-282 Temperature records, 158-159, 172, 196-198, 382384 Termites, 450 Terpenes, 355-356 Tertiary Strangelove Ocean, 103, 106, 127 Thermohaline circulation, 85, 88, 226, 529-531 Thermometers, 153 Tibetan plateau, 218 Time series analysis, 192 Tissue damage due to UV increase, 424 TOPEX-POSEIDON, 272 Total Ozone Mapping Spectrometer (TOMS), 409410, 412, 421-422
608
Transient response to greenhouse warming, 331-334 Tree rings, 168, 196, 201-222 Triassic, 119 Tropical cyclones (typhoons, hurricanes), 209, 304305,309-310 -, deforestation, 322, 435,444-445,455,459-463 -, Rainfall Measuring Mission (TRMM), 250, 261262 Tropospheric ozone, 317-335, 338-344, 487 Tunguska, 101 Typhoons- see Tropical cyclones UK Meteorological Office GCM, 334 Ultraviolet radiation, 399, 405, 420, 425, 427, 429, 487, 506 Upper air data, 169-172 Urban boundary layer (UBL), 483, 486--487, 494496 -, canopy layer (UCL), 482-483, 486, 490-491, 494-496 -, heat island, 155, 197,478,498-500 -, humidity, 502-503 -, plume, 505 -, rain islands, 504 Vegetation change, 466 -, indices (VI), 269-270 Volcanic eruptions, 131, 171, 176, 205-207, 347, 349, 351-352, 537 -, explosivity index, 205 Vostok, 522 Walker circulation, 214, 306, 455,463 -, Gilbert, 214 Walvis Ridge, 108 Warm epochs, 71-88 Water vapour feedback, 52-54, 99-100, 228 Weddell Sea, 110 --, Bottom Water (WSBW), 520 Wildfires, 101 World Climate Research Programme (WCRP), 155156, 265,272 -, Meteorological Organization (WMO), 152, 154, 159, 164, 230, 324 Younger Dryas, 37, 43, 517, 523-524, 531
