Preface |
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xi | |
Acronyms and abbreviations |
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xiii | |
Principal symbols |
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xviii | |
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1 | (5) |
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2 The governing systems of equations |
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6 | (11) |
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6 | (1) |
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2.2 Reynolds' equations: separating unresolved turbulence effects |
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7 | (3) |
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2.3 Approximations to the equations |
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10 | (7) |
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3 Numerical solutions to the equations |
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17 | (102) |
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3.1 Overview of basic concepts |
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17 | (6) |
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23 | (28) |
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3.3 Finite-difference methods |
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51 | (7) |
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3.4 Effects of the numerical approximations |
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58 | (38) |
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3.5 Lateral-boundary conditions |
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96 | (18) |
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3.6 Upper-boundary conditions |
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114 | (2) |
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116 | (1) |
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3.8 Practical summary of the process for setting up a model |
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116 | (3) |
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4 Physical-process parameterizations |
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119 | (52) |
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119 | (2) |
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4.2 Cloud microphysics parameterizations |
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121 | (8) |
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4.3 Convective parameterizations |
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129 | (11) |
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4.4 Turbulence, or boundary-layer, parameterizations |
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140 | (15) |
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4.5 Radiation parameterizations |
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155 | (11) |
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4.6 Stochastic parameterizations |
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166 | (1) |
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4.7 Cloud-cover, or cloudiness, parameterizations |
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166 | (5) |
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5 Modeling surface processes |
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171 | (27) |
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171 | (1) |
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5.2 Land-surface processes that must be modeled |
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172 | (13) |
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5.3 Ocean or lake processes that must be modeled |
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185 | (2) |
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5.4 Modeling surface and subsurface processes over land |
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187 | (5) |
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5.5 Modeling surface and subsurface processes over water |
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192 | (1) |
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192 | (2) |
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5.7 Urban-canopy modeling |
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194 | (2) |
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5.8 Data sets for the specification of surface properties |
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196 | (2) |
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198 | (54) |
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198 | (1) |
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6.2 Observations used for model initialization |
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199 | (11) |
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6.3 Continuous versus intermittent data-assimilation methods |
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210 | (5) |
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215 | (1) |
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6.5 The statistical framework for data assimilation |
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216 | (11) |
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6.6 Successive-correction methods |
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227 | (3) |
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6.7 Statistical interpolation (optimal interpolation) |
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230 | (1) |
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6.8 Three-dimensional variational analysis |
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231 | (2) |
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6.9 Diabatic-initialization methods |
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233 | (3) |
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6.10 Dynamical balance in the initial conditions |
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236 | (6) |
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6.11 Advanced data-assimilation methods |
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242 | (6) |
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6.12 Hybrid data-assimilation methods |
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248 | (1) |
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6.13 Initialization with idealized conditions |
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249 | (3) |
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252 | (32) |
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252 | (2) |
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7.2 The ensemble mean and ensemble dispersion |
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254 | (3) |
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7.3 Sources of uncertainty, and the definition of ensemble members |
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257 | (4) |
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7.4 Interpretation and verification of ensemble forecasts |
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261 | (8) |
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7.5 Calibration of ensembles |
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269 | (2) |
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7.6 Time-lagged ensembles |
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271 | (1) |
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7.7 Limited-area, short-range ensemble forecasting |
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272 | (1) |
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7.8 Graphically displaying ensemble-model products |
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273 | (7) |
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7.9 Economic benefits of ensemble predictions |
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280 | (4) |
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284 | (10) |
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284 | (1) |
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8.2 Model error and initial-condition error |
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284 | (3) |
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8.3 Land-surface forcing's impact on predictability |
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287 | (1) |
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8.4 Causes of predictability variations |
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288 | (2) |
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8.5 Special predictability considerations for limited-area and mesoscale models |
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290 | (2) |
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8.6 Predictability and model improvements |
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292 | (1) |
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8.7 The impact of post processing on predictability |
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293 | (1) |
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294 | (27) |
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294 | (1) |
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9.2 Some standard metrics used for model verification |
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295 | (4) |
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9.3 More about reference forecasts and their use |
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299 | (1) |
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9.4 Truth data sets: observations versus analyses of observations |
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300 | (1) |
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9.5 Special considerations |
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301 | (5) |
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9.6 Verification in terms of probability distribution functions |
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306 | (1) |
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9.7 Verification stratified by weather regime, time of day, and season |
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307 | (2) |
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9.8 Feature-based, event-based, or object-based verification |
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309 | (3) |
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9.9 Verification in terms of the scales of atmospheric features |
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312 | (5) |
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9.10 The use of reforecasts for model verification |
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317 | (1) |
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9.11 Forecast-value-based verification |
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317 | (1) |
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9.12 Choosing appropriate verification metrics |
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317 | (1) |
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9.13 Model-verification toolkits |
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318 | (1) |
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9.14 Observations for model verification |
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318 | (3) |
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10 Experimental design in model-based research |
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321 | (22) |
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10.1 Case studies for physical-process analysis |
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321 | (2) |
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10.2 Observing-system simulation experiments |
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323 | (5) |
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10.3 Observing-system experiments |
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328 | (1) |
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10.4 Big-Brother-Little-Brother experiments |
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329 | (1) |
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330 | (1) |
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331 | (7) |
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10.7 Predictive-skill studies |
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338 | (1) |
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10.8 Simulations with synthetic initial conditions |
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339 | (1) |
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10.9 The use of reduced-dimension and reduced-physics models |
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339 | (1) |
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10.10 Sources of meteorological observational data |
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340 | (3) |
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11 Techniques for analyzing model output |
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343 | (15) |
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343 | (1) |
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11.2 Graphical methods for displaying and interpreting model output and observations |
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343 | (9) |
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11.3 Mathematical methods for analysis of the structure of model variable fields |
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352 | (4) |
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11.4 Calculation of derived variables |
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356 | (1) |
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11.5 Analysis of energetics |
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356 | (2) |
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12 Operational numerical weather prediction |
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358 | (8) |
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358 | (2) |
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360 | (1) |
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12.3 Considerations for operational limited-area models |
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361 | (1) |
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361 | (1) |
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362 | (1) |
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12.6 Real-time verification |
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363 | (1) |
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12.7 Managing model upgrades and developments |
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363 | (1) |
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12.8 The relative role of models and forecasters in the forecasting process |
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364 | (2) |
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13 Statistical post processing of model output |
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366 | (12) |
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366 | (1) |
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13.2 Systematic-error removal |
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367 | (8) |
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375 | (1) |
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376 | (2) |
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14 Coupled special-applications models |
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378 | (23) |
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378 | (3) |
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381 | (1) |
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382 | (4) |
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14.4 River discharge, and floods |
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386 | (3) |
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14.5 Transport, diffusion, and chemical transformations of gases and particles |
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389 | (4) |
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14.6 Transportation safety and efficiency |
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393 | (1) |
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14.7 Electromagnetic-wave and sound-wave propagation |
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394 | (2) |
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14.8 Wildland-fire probability and behavior |
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396 | (1) |
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396 | (3) |
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399 | (1) |
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14.11 Military applications |
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399 | (2) |
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15 Computational fluid-dynamics models |
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401 | (6) |
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401 | (1) |
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401 | (1) |
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15.3 Scale distinctions between mesoscale models and LES models |
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402 | (1) |
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15.4 Coupling CFD models and mesoscale models |
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403 | (2) |
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15.5 Examples of CFD-model applications |
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405 | (1) |
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15.6 Algorithmic approximations to CFD models |
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405 | (2) |
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16 Climate modeling and downscaling |
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407 | (49) |
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16.1 Global climate prediction |
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408 | (23) |
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16.2 Reanalyses of the current global climate |
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431 | (1) |
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432 | (19) |
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16.4 Modeling the climate impacts of anthropogenic landscape changes |
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451 | (5) |
Appendix Suggested code structure and experiments for a simple shallow-fluid model |
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456 | (5) |
References |
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461 | (62) |
Index |
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523 | |