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Uncertainties in Numerical Weather Prediction

Specificaties
Paperback, blz. | Engels
Elsevier Science | e druk, 2020
ISBN13: 9780128154915
Rubricering
Elsevier Science e druk, 2020 9780128154915
€ 143,80
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Samenvatting

Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides general knowledge on all aspects of uncertainties in the weather prediction models in a single, easy to use reference. The book illustrates particular uncertainties in observations and data assimilation, as well as the errors associated with numerical integration methods. Stochastic methods in parameterization of subgrid processes are also assessed, as are uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer.

Through a better understanding of the uncertainties to watch for, readers will be able to produce more precise and accurate forecasts. This is an essential work for anyone who wants to improve the accuracy of weather and climate forecasting and interested parties developing tools to enhance the quality of such forecasts.

Specificaties

ISBN13:9780128154915
Taal:Engels
Bindwijze:Paperback

Inhoudsopgave

<p>1. DYNAMICAL CORES FOR NWP: AN UNCERTAIN LANDSCAPE</p> <p>2. DYNAMICAL MODEL DISCRETIZETION </p> <p>3. PROBABILISTIC VIEW OF NUMERICAL WEATHER PREDICTION AND ENSEMBLE PREDICTION </p> <p>4. PREDICTABILITY </p> <p>5. MODELING MOIST DYNAMICS ON SUBGRID SCALES</p> <p>6. ENSEMBLE DATA ASSIMILATION</p> <p>7. SUBGRID TURBULENCE MIXING</p> <p>8. UNCERTAINTIES IN THE SURFACE LAYER PHYSICS PARAMETERIZATIONS </p> <p>9. INTERACTION OF CLOUDS AND RADIATION</p> <p>10. UNCERTAINTIES IN THE PARAMETERIZATION OF CLOUD MICROPHYSICS: AN ILLUSTRATION OF THE PROBLEM</p> <p>11. MEOSCALE OROGRAPHIC FLOWS </p> <p>12. TRACERS AND ATMOSPHERIC RIVERS </p> <p>13. DYNAMIC IDENTIFICATION AND TRACING OF ERRORS IN NUMERICAL SIMULATIONS OF THE ATMOSPHERE</p>
€ 143,80
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        Uncertainties in Numerical Weather Prediction