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

About the Authors

Haraldur �lafsson is a professor of atmospheric physics at the University of Iceland, leading the Reykjavik School of Meteorology. He is a former professor and the leader of the Bergen School of Meteorology at the University of Bergen in Norway. He has a doctorate from Universit� Paul Sabatier in France and a Cand. Scient. from the University of Oslo, Norway. Haraldur Olafsson is an expert in mesoscale meteorology and climatology and orographic processes.

Jian-Wen Bao is a research meteorologist at NOAA Physical Sciences Laboratory. He was responsible for developing and testing the physics component of a research global weather prediction model. He is currently participating in a project as a project co-lead to develop an advanced physics suite in NOAA’s Unified Forecast System.

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