Numerical weather and climate prediction:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2011
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. 461-522 |
| Physical Description: | XXII, 526 S. Ill., graph. Darst., Kt. |
| ISBN: | 9780521513890 |
Staff View
MARC
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| 100 | 1 | |a Warner, Thomas T. |d 1943-2011 |e Verfasser |0 (DE-588)1011425203 |4 aut | |
| 245 | 1 | 0 | |a Numerical weather and climate prediction |c Thomas Tomkins Warner |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2011 | |
| 300 | |a XXII, 526 S. |b Ill., graph. Darst., Kt. | ||
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Record in the Search Index
| _version_ | 1804145706674421760 |
|---|---|
| adam_text | Contents
Preface
page
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
viii Contents
5.5
Modeling surface and subsurface processes over water
192
5.6
Orographie
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
Contents
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 operational limited-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
Contents
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
|
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| ctrlnum | (OCoLC)707170831 (DE-599)GBV624567907 |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 551 - Geology, hydrology, meteorology |
| dewey-raw | 551.634 |
| dewey-search | 551.634 |
| dewey-sort | 3551.634 |
| dewey-tens | 550 - Earth sciences |
| discipline | Geologie / Paläontologie Physik Geographie |
| edition | 1. publ. |
| format | Book |
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| indexdate | 2024-07-09T23:23:43Z |
| institution | BVB |
| isbn | 9780521513890 |
| language | English |
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| physical | XXII, 526 S. Ill., graph. Darst., Kt. |
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| publisher | Cambridge Univ. Press |
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| spelling | Warner, Thomas T. 1943-2011 Verfasser (DE-588)1011425203 aut Numerical weather and climate prediction Thomas Tomkins Warner 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2011 XXII, 526 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. 461-522 Klimatologie (DE-588)4031178-8 gnd rswk-swf Numerische Wettervorhersage (DE-588)4268740-8 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Numerische Wettervorhersage (DE-588)4268740-8 s Mathematisches Modell (DE-588)4114528-8 s DE-604 Klimatologie (DE-588)4031178-8 s Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022562367&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Warner, Thomas T. 1943-2011 Numerical weather and climate prediction Klimatologie (DE-588)4031178-8 gnd Numerische Wettervorhersage (DE-588)4268740-8 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| subject_GND | (DE-588)4031178-8 (DE-588)4268740-8 (DE-588)4114528-8 |
| title | Numerical weather and climate prediction |
| title_auth | Numerical weather and climate prediction |
| title_exact_search | Numerical weather and climate prediction |
| title_full | Numerical weather and climate prediction Thomas Tomkins Warner |
| title_fullStr | Numerical weather and climate prediction Thomas Tomkins Warner |
| title_full_unstemmed | Numerical weather and climate prediction Thomas Tomkins Warner |
| title_short | Numerical weather and climate prediction |
| title_sort | numerical weather and climate prediction |
| topic | Klimatologie (DE-588)4031178-8 gnd Numerische Wettervorhersage (DE-588)4268740-8 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| topic_facet | Klimatologie Numerische Wettervorhersage Mathematisches Modell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022562367&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT warnerthomast numericalweatherandclimateprediction |