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