Uncertainties in Numerical Weather Prediction

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.

• Provides a comprehensive overview of the state of numerical weather prediction at spatial scales, from hundreds of meters, to thousands of kilometers
• Focuses on short-term 1-15 day atmospheric predictions, with some coverage appropriate for longer-term forecasts
• Includes references to climate prediction models to allow applications of these techniques for climate simulations

Students and researchers in atmospheric sciences, including not only weather forecasting, but also climate sciences; developers of tools for numerical weather prediction in research centres and universities

1. Data assimilation
2. Convection and precipitation
3. Cloud microphysics and aerosols
4. Radiation
5. Turbulent mixing
6. Surface processes
7. Orographic processes
8. Scale interaction and conceptual tools
9. Mathematical tools and methods
10. Solutions of dynamical models
11. Ensemble prediction
12. Post-processing methods