Warner T.T. Numerical weather and climate prediction (Cambridge, 2011). - ОГЛАВЛЕНИЕ / CONTENTS
Навигация

Архив выставки новых поступлений | Отечественные поступления | Иностранные поступления | Сиглы
ОбложкаWarner T.T. Numerical weather and climate prediction. - Cambridge: Cambridge University Press, 2011. - xxii, 526 p.: ill. - Ref.: p.461-522. - Ind.: p.523-526. - ISBN 978-0-521-51389-0
 

Оглавление / Contents
 
Preface ........................................................ xi
Acronyms and abbreviations ................................... xiii
Principal symbols ........................................... xviii

1  Introduction ................................................. 1

2  The governing systems of equations ........................... 6
   2.1  The basic equations ..................................... 6
   2.2  Reynolds' equations: separating unresolved turbulence
        effects ................................................. 7
   2.3  Approximations to the equations ........................ 10

3  Numerical solutions to the equations ........................ 17
   3.1  Overview of basic concepts ............................. 17
   3.2  Numerical frameworks ................................... 23
   3.3  Finite-difference methods .............................. 51
   3.4  Effects of the numerical approximations ................ 58
   3.5  Lateral-boundary conditions ............................ 96
   3.6  Upper-boundary conditions ............................. 114
   3.7  Conservation issues ................................... 116
   3.8  Practical summary of the process for setting up
        a model ............................................... 116

4  Physical-process parameterizations ......................... 119
   4.1  Background ............................................ 119
   4.2  Cloud microphysics parameterizations .................. 121
   4.3  Convective parameterizations .......................... 129
   4.4  Turbulence, or boundary-layer, parameterizations ...... 140
   4.5  Radiation parameterizations ........................... 155
   4.6  Stochastic parameterizations .......................... 166
   4.7  Cloud-cover, or cloudiness, parameterizations ......... 166

5  Modeling surface processes ................................. 171
   5.1  Background ............................................ 171
   5.2  Land-surface processes that must be modeled ........... 172
   5.3  Ocean or lake processes that must be modeled .......... 185
   5.4  Modeling surface and subsurface processes over land ... 187
   5.5  Modeling surface and subsurface processes over
        water ................................................. 192
   5.6  Orographic forcing .................................... 192
   5.7  Urban-canopy modeling ................................. 194
   5.8  Data sets for the specification of surface
        properties ............................................ 196

6  Model initialization ....................................... 198
   6.1  Background ............................................ 198
   6.2  Observations used for model initialization ............ 199
   6.3  Continuous versus intermittent data-assimilation
        methods ............................................... 210
   6.4  Model spinup .......................................... 215
   6.5  The statistical framework for data assimilation ....... 216
   6.6  Successive-correction methods ......................... 227
   6.7  Statistical interpolation (optimal interpolation) ..... 230
   6.8  Three-dimensional variational analysis ................ 231
   6.9  Diabatic-initialization methods ....................... 233
   6.10 Dynamical balance in the initial conditions ........... 236
   6.11 Advanced data-assimilation methods .................... 242
   6.12 Hybrid data-assimilation methods ...................... 248
   6.13 Initialization with idealized conditions .............. 249

7  Ensemble methods ........................................... 252
   7.1  Background ............................................ 252
   7.2  The ensemble mean and ensemble dispersion ............. 254
   7.3  Sources of uncertainty, and the definition of
        ensemble members ...................................... 257
   7.4  Interpretation and verification of ensemble
        forecasts ............................................. 261
   7.5  Calibration of ensembles .............................. 269
   7.6  Time-lagged ensembles ................................. 271
   7.7  Limited-area, short-range ensemble forecasting ........ 272
   7.8  Graphically displaying ensemble-model products ........ 273
   7.9  Economic benefits of ensemble predictions ............. 280

8  Predictability ............................................. 284
   8.1  Background ............................................ 284
   8.2  Model error and initial-condition error ............... 284
   8.3  Land-surface forcing's impact on predictability ....... 287
   8.4  Causes of predictability variations ................... 288
   8.5  Special predictability considerations for limited-
        area and mesoscale models ............................. 290
   8.6  Predictability and model improvements ................. 292
   8.7  The impact of post processing on predictability ....... 293

9  Verification methods ....................................... 294
   9.1  Background ............................................ 294
   9.2  Some standard metrics used for model verification ..... 295
   9.3  More about reference forecasts and their use .......... 299
   9.4  Truth data sets: observations versus analyses of
        observations .......................................... 300
   9.5  Special considerations ................................ 301
   9.6  Verification in terms of probability distribution
        functions ............................................. 306
   9.7  Verification stratified by weather regime, time of
        day, and season ....................................... 307
   9.8  Feature-based, event-based, or object-based
        verification .......................................... 309
   9.9  Verification in terms of the scales of atmospheric
        features .............................................. 312
   9.10 The use of reforecasts for model verification ......... 317
   9.11 Forecast-value-based verification ..................... 317
   9.12 Choosing appropriate verification metrics ............. 317
   9.13 Model-verification toolkits ........................... 318
   9.14 Observations for model verification ................... 318

10 Experimental design in model-based research ................ 321
   10.1 Case studies for physical-process analysis ............ 321
   10.2 Observing-system simulation experiments ............... 323
   10.3 Observing-system experiments .......................... 328
   10.4 Big-Brother-Little-Brother experiments ................ 329
   10.5 Reforecasts ........................................... 330
   10.6 Sensitivity studies ................................... 331
   10.7 Predictive-skill studies .............................. 338
   10.8 Simulations with synthetic initial conditions ......... 339
   10.9 The use of reduced-dimension and reduced-physics
        models ................................................ 339
   10.10 Sources of meteorological observational data ......... 340

11 Techniques for analyzing model output ...................... 343
   11.1 Background ............................................ 343
   11.2 Graphical methods for displaying and interpreting
        model output and observations ......................... 343
   11.3 Mathematical methods for analysis of the structure
        of model variable fields .............................. 352
   11.4 Calculation of derived variables ...................... 356
   11.5 Analysis of energetics ................................ 356

12 Operational numerical weather prediction ................... 358
   12.1 Background ............................................ 358
   12.2 Model reliability ..................................... 360
   12.3 Considerations for operationallimited-area models ..... 361
   12.4 Computational speed ................................... 361
   12.5 Postprocessing ........................................ 362
   12.6 Real-time verification ................................ 363
   12.7 Managing model upgrades and developments .............. 363
   12.8 The relative role of models and forecasters in the
        forecasting process ................................... 364

13 Statistical post processing of model output ................ 366
   13.1 Background ............................................ 366
   13.2 Systematic-error removal .............................. 367
   13.3 Weather generators .................................... 375
   13.4 Downscaling methods ................................... 376

14 Coupled special-applications models ........................ 378
   14.1 Background ............................................ 378
   14.2 Wave height ........................................... 381
   14.3 Infectious diseases ................................... 382
   14.4 River discharge, and floods ........................... 386
   14.5 Transport, diffusion, and chemical transformations
        of gases and particles ................................ 389
   14.6 Transportation safety and efficiency .................. 393
   14.7 Electromagnetic-wave and sound-wave propagation ....... 394
   14.8 Wildland-fire probability and behavior ................ 396
   14.9 The energy industry ................................... 396
   14.10 Agriculture .......................................... 399
   14.11 Military applications ................................ 399

15 Computational fluid-dynamics models ........................ 401
   15.1 Background ............................................ 401
   15.2 Types of CFD models ................................... 401
   15.3 Scale distinctions between mesoscale models and LES
        models ................................................ 402
   15.4 Coupling CFD models and mesoscale models .............. 403
   15.5 Examples of CFD-model applications .................... 405
   15.6 Algorithmic approximations to CFD models .............. 405

16 Climate modeling and downscaling ........................... 407
   16.1 Global climate prediction ............................. 408
   16.2 Reanalyses of the current global climate .............. 431
   16.3 Climate downscaling ................................... 432
   16.4 Modeling the climate impacts of anthropogenic
        landscape changes ..................................... 451

Appendix Suggested code structure and experiments for
   a simple shallow-fluid model ............................... 456
References .................................................... 461
Index ......................................................... 523


Архив выставки новых поступлений | Отечественные поступления | Иностранные поступления | Сиглы
 

[О библиотеке | Академгородок | Новости | Выставки | Ресурсы | Библиография | Партнеры | ИнфоЛоция | Поиск | English]
  Пожелания и письма: branch@gpntbsib.ru
© 1997-2020 Отделение ГПНТБ СО РАН (Новосибирск)
Статистика доступов: архив | текущая статистика
 

Документ изменен: Wed Feb 27 14:23:38 2019 Размер: 14,445 bytes.
Посещение N 1016 c 10.07.2012