Uncertainties in Numerical Weather Prediction
- 1st Edition - November 25, 2020
- Editors: Haraldur Olafsson, Jian-Wen Bao
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 5 4 9 1 - 5
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 5 7 1 0 - 7
Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmos… Read more
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 climate sciences; developers of tools for numerical weather prediction in research centres and universities
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
- Edition: 1
- Published: November 25, 2020
- Language: English
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Haraldur Olafsson
Haraldur Ólafsson 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 Université 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.
Affiliations and expertise
Professor, Reykjavik School of Meteorology, University of IcelandJB
Jian-Wen Bao
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.
Affiliations and expertise
Research Meteorologist, Physical Sciences Laboratory, NOAARead Uncertainties in Numerical Weather Prediction on ScienceDirect