Environmental Modelling and Prediction

486 Pages·2002·13.77 MB·English

by  Gongbing Peng, Yaping Shao, Lance M. Leslie (auth.), Professor Gongbing Peng, Professor Lance M. Leslie, Dr. Yaping Shao (eds.)

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Springer-Verlag Berlin Heidelberg GmbH
Gongbing Peng Lance M. Leslie
Yaping Shao (Eds.)
Environmental
Modelling
and Prediction
With 168 Figures
Springer
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ISBN 978-3-642-08685-4 ISBN 978-3-662-04868-9 (eBook)
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Preface
The environment is the aggregate of the physical, geographical and biochem
ical conditions under which we live. It significantly influences all aspects of
human society, including agriculture, industry, human health, resources, etc.
In recent history, we have been challenged not only by the impact of natural
environmental variability, but also by human induced environmental changes,
such as deforestation. destruction of the ozone layer, increased emission of
greenhouse gases and pollution of air, water and soil. It is now increasingly
understood that to better protect the environment is an essential task of hu
man society. Environmental modelling and prediction, i.e., the modelling of
environmental processes and the prediction of environmental changes, form
a critical component of this task.
The environment is a complex interactive system comprising five major
components and numerous sub-components. The major components are the
atmosphere, the hydrosphere, the cryosphere, the lithosphere and the bio
sphere. Environmental modelling and prediction is concerned with both the
behaviour of the individual components and their interactions, through the
mathematical and numerical representation of the the physical, chemical and
biological processes taking place within the environmental system. It is also
concerned with the variability, stability and predictability of the environment
as a dynamic system on a wide range of temporal and spatial scales.
There is an increasing requirement throughout the world for a better
understanding of environmental processes and an enhanced capability for
predicting environmental changes resulting from natural variations or human
interferences. Numerous studies dealing with the modelling and prediction of
individual components have been carried out in the past with considerable
success. In recent years. environmental research is more focused on integrated
approaches in which the environment is treated as a cohesive dynamic system.
However, so far there have been very few books dealing exclusively with the
lat.ter subject. Our aim in this book is to bring together the collective efforts
of scientists from several disciplines, to summarize recent developments in
theories, methodologies and applications of integrated environmental mod
elling and prediction. Our effort in achieving this aim is reflected in Chaps. 1,
2 and 11. In Chap. 1, the subject area is explored and the scope of the book is
defined. In Chap. 2, we have attempted to establish a theoretical framework
VI Preface
for modelling and predicting the environment as a dynamic system, while in
Chap. 11, examples of integrated environmental modelling and prediction are
presented.
For environmental modelling and prediction, the modelling and prediction
of the weather and climate components are of great importance for two main
reasons. First, the atmosphere is the most active part of the environmental
system on short time scales (up to a year). Second, the methods used in
atmospheric modelling and prediction are arguably the most highly developed
and also have the most complete data sets for verification. Chap. 3 of this
book is devoted to the modelling and prediction of the atmosphere on a wide
range of time and space scales. The next most important component of the
environment is the ocean which dominates the behaviour of the environment
on time scales from annual to decadal and beyond. Recent developments in
ocean modelling and prediction are presented in Chap. 4.
A detailed treatment of the other environmental components is also pre
sented because, although they interact with the atmosphere and the ocean,
they have their own distinct dynamic features. It is important for success
in environmental modelling and prediction that these individual components
and their interactions are also well understood. We summarize the theo
ries, methodologies and achievements in the modelling and prediction of the
land-surface, the continental hydrosphere, the cryosphere and the continen
tal biosphere (Chaps. 5, 6, 7 and 8, respectively). The interactions between
the atmosphere, the ocean and these environmental components are also dis
cussed. Some aspects of biological modelling and air quality modelling are
discussed in Chaps. 9 and 10.
The book also explores recent developments in the theory and applications
of environmental prediction, including systems analysis, information theory
and natural cybernetics. The further development and application of these
theories are very important for environmental modelling and prediction.
This book is a collective effort of many people. In particular, we wish to
thank Drs. R. Morison, M. England, P. Oke, P. Irannejad, S. Liu, C. Ciret,
Y. Tan, H. Duc, S. Zhao, M. Speer and L. Qi for their contributions to
the various chapters. The assistance of Dr. S. Xia in the preparation of the
manuscript and graphs is gratefully acknowledged.
Sydney, May 2001
Gongbing Peng
Lance M. Leslie
Yaping Shao
Contents
1. Environmental Science. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Gongbing Peng, Yaping Shao and Lance M. Leslie
1.1 The Environment and Environmental Challenges . . . . . . . . . . . 1
1.2 Environmental Modelling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 Environmental Prediction ............................... 10
1.4 Recent Developments in Environmental Sciences. . . . . . . . . . .. 12
1.4.1 Earth Systematics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 12
1.4.2 Natural Cybernetics. . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 14
1.4.3 Geographic Information System. . . . . . . . . . . . . . . . . . .. 16
1.4.4 Non-Linear Dynamical System Analysis and Predictabil-
ity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 17
1.4.5 Links of Environmental Science to Related Subjects .. 19
2. The Environmental Dynamic System .. . . . . . . . . . . . . . . . . . .. 21
Yaping Shao, Gongbing Peng and Lance M. Leslie
2.1 The Environment as a Dynamic System. . . . . . . . . . . . . . . . . .. 21
2.2 Mathematical Representations and Simplifications. . . . . . . . .. 30
2.2.1 Governing Equations for Atmosphere. . . . . . . . . . . . . .. 31
2.2.2 Governing Equations for the Oceans. . . . . . . . . . . . . . .. 33
2.2.3 Basic Equations for Land Surface. . . . . . . . . . . . . . . . . .. 34
2.2.4 Basic Equations for Ground Water ................. 35
2.2.5 Basic Equations for Ice. . . . . . . . . . . . . . . . . . . . . . . . . . .. 36
2.3 Predictability of the Environmental System. . . . . . . . . . . . . . .. 37
2.4 Methods for Environmental Prediction . . . . . . . . . . . . . . . . . . .. 45
2.5 Integrated Environmental Modelling Systems .............. 46
2.5.1 Atmosphere-Land Surface Interaction Scheme ........ 48
2.5.2 Atmosphere-Ocean Interaction Scheme. . . . . . . . . . . . .. 50
2.6 Ensemble Predictions .... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 52
2.6.1 Choosing the Initial Perturbations. . . . . . . . . . . . . . . . .. 53
2.6.2 Cell Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 54
2.7 Dynamic-Stochastic Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 56
2.7.1 Dissipative Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . .. 56
2.7.2 Synergetics...................................... 58
2.7.3 Deterministic Chaos Theory. . . . . . . . . . . . . . . . . . . . . .. 59
VIn Contents
2.7.4 Interactive Chaos ................................. 62
2.8 Natural Cybernetics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 66
3. Atmospheric Modelling and Prediction ...... . . . . . . . . . . . .. 75
Lance M. Leslie, Russel P. Morison, Milton S. Speer and Lixin Qi
3.1 Introduction........................................... 75
3.1.1 Impact on Society of Severe Weather and Climate Events 76
3.1.2 Historical Background. . . . . . . . . . . . . . . . . . . . . . . . . . .. 78
3.1.3 The Role of the Atmosphere in the Environmental Sys-
tern ............................................. 79
3.1.4 Numerical Weather Prediction and Modelling. . . . . . .. 80
3.2 Equations Governing Atmospheric Motion . . . . . . . . . . . . . . . .. 82
3.2.1 Some Commonly Used NWP Models. . . . . . . . . . . . . . .. 83
3.2.2 The UNSW HIRES Model. . . . . . . . . . . . . . . . . . . . . . . .. 84
3.3 Solving the Governing Equations. . . . . . . . . . . . . . . . . . . . . . . .. 85
3.3.1 The Shallow Water Equations. . . . . . . . . . . . . . . . . . . . .. 86
3.3.2 The Finite-difference Techniques ................... 87
3.3.3 Stability Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 88
3.3.4 Defining the Initial State for the Model Integration. .. 91
3.4 Applications........................................... 93
3.4.1 Very Short Range Forecasting (VSRF) . . . . . . . . . . . . .. 93
3.4.2 Short Range Forecasting (SRF) .................... 96
3.4.3 Medium Range Forecasting (MRF) ................. 99
3.4.4 Modelling the General Circulation of the Atmosphere. 101
3.5 Climate Modelling ...................................... 104
3.5.1 The GCM Model Numerics ........................ 105
3.5.2 The Model Physics ............................... 106
3.5.3 Ocean Model Coupling ............................ 107
3.6 Applications and Results ................................ 107
3.6.1 Medium range forecasting experiments .............. 107
3.6.2 Brief climatology of the model ..................... 108
3.6.3 Regional simulations .............................. 109
3.7 Statistical Models ...................................... 112
3.7.1 Deterministic and Statistical Models ................ 113
3.7.2 Analogue Retrieval Techniques ..................... 113
3.7.3 Combining Deterministic and Statistical Models ...... 114
3.7.4 Multiple Regression Markov Model ................. 115
3.8 Future Directions ....................................... 116
3.8.1 Impact of Cloud Microphysics ...................... 117
3.8.2 Ensemble Forecasting ............................. 117
3.8.3 Variational Data Assimilation ...................... 121
Contents IX
4. Ocean Modelling and Prediction .......................... 125
Matthew H. England and Peter R. Oke
4.1 Introduction ........................................... 125
4.1.1 What Is an Ocean Model? ......................... 125
4.1.2 Mean Large-scale Ocean Circulation ................ 126
4.1.3 Oceanic Variability ............................... 126
4.1.4 The Oceans, Climate, and Forcing .................. 129
4.2 A Brief History of Ocean Modelling ....................... 131
4.3 Anatomy of Ocean Models ............................... 132
4.3.1 Governing Physics and Equations .................. 132
4.3.2 Model Choice of Vertical Coordinate ................ 135
4.3.3 Subgrid-scale Processes and Dissipation ............. 136
4.3.4 Boundary Conditions and Surface Forcing ........... 141
4.4 Some Commonly Used Ocean Models ..................... 145
4.4.1 The GFDL Modular Ocean Model .................. 145
4.4.2 The Princeton Ocean Model ....................... 147
4.4.3 The Miami Isopycnic Coordinate Model (MICOM) ... 149
4.4.4 The DieCast Model ............................... 149
4.5 Ocean Model Applications ............................... 150
4.5.1 A Global Coarse Resolution Model ................. 150
4.5.2 Global Eddy-permitting Simulations ................ 153
4.5.3 Regional Simulations in the North Atlantic Ocean .... 154
4.5.4 ENSO Modelling ................................. 156
4.5.5 A Regional Model of the Southern Ocean ............ 157
4.5.6 A Coastal Ocean Model off Eastern Australia ........ 158
4.5.7 A Coastal Model of a River Plume ................. 159
4.6 Exploiting Ocean Observations ........................... 160
4.6.1 Model Assessment ................................ 160
4.6.2 Inverse Methods and Data Assimilation ............. 165
4.6.3 Applications of Data Assimilation to Coastal Ocean
Models .......................................... 168
4.6.4 Application of Data Assimilation to Large-scale Models 169
4.6.5 Variational Data Assimilation, Example ............. 169
4.7 Concluding Remarks .................................... 171
5. Land Surface Processes ................................... 173
Parviz lrannejad and Yaping Shao
5.1 The Importance of Land-surface Processes ................. 173
5.2 Land-surface Parameterization Schemes ................... 176
5.3 Modelling Soil Hydrology in Land-surface Schemes .......... 179
5.3.1 Bucket Model .................................... 179
5.3.2 Force-restore Model ............................... 180
5.3.3 Multi-layer Soil Model ............................ 181
5.4 Soil Temperature ....................................... 185
5.5 Surface Energy Balance ................................. 187
X Contents
5.5.1 Surface Fluxes ................................... 188
5.5.2 Evaporation from Unsaturated Soil ................. 190
5.5.3 Transpiration .................................... 191
5.5.4 Bulk Transfer Coefficients ......................... 192
5.5.5 Canopy (Vegetation) Resistance .................... 194
5.5.6 Canopy Water Storage ............................ 195
5.5.7 Surface Albedo ................................... 196
5.6 Carbon-dioxide Budget .................................. 198
5.7 Verification of Land-surface Schemes ...................... 198
5.8 Land Surface Modelling over Heterogeneous Surfaces ........ 202
5.8.1 Models of Dynamic Effects ........................ 204
5.8.2 Models of Aggregation Effects ...................... 206
5.9 Land-surface Parameters ................................ 209
5.10 The Impact of Land Surface on Climate and Weather: Some
Case Studies ........................................... 210
6. Hydrological Modelling and Forecasting .................. 215
Suxia Liu
6.1 The Hydrosphere ....................................... 215
6.2 Mathematical Representation and Simplification ............ 219
6.2.1 Water Vapour ................................... 219
6.2.2 Precipitation ..................................... 222
6.2.3 Soil Water ....................................... 224
6.2.4 Infiltration ...................................... 226
6.2.5 Depression Storage ............................... 229
6.2.6 Vegetation Water ................................. 230
6.2.7 Interception ..................................... 232
6.2.8 Evapotranspiration ............................... 233
6.2.9 Channel Flow .................................... 235
6.2.10 Overland Flow ................................... 236
6.2.11 Groundwater .................................... 237
6.2.12 Water Quality ................................... 239
6.3 Hydrological Modelling .................................. 244
6.3.1 Xinanjiang Model ................................ 245
6.3.2 TOPOMODEL .................................. 248
6.3.3 Integrated Hydrological Modelling System ........... 250
6.4 Hydrological Forecasting ................................ 254
6.4.1 Short-term Hydrological Forecasting ................ 255
6.4.2 Mid- and Long-term Hydrological Forecasting ........ 262
6.4.3 Water Quality Forecasting ......................... 264
6.4.4 Water Supply and Water Demand Forecasting ....... 267