DocumentCode
1314004
Title
The Hirlam project [meteorology]
Author
Cats, Gerard ; Wolters, Lex
Author_Institution
R. Netherlands Meteorol. Inst., De Bilt, Netherlands
Volume
3
Issue
4
fYear
1996
Firstpage
4
Lastpage
7
Abstract
In 1985 the national meteorological institutes of Denmark, Finland, Iceland, The Netherlands, Norway, and Sweden joined forces to develop and maintain a numerical short range weather forecasting system. Later Ireland and Spain joined the project, and the Hirlam (high resolution limited area modeling) project is now in its third phase. Version 2 of the Hirlam system, built during the second phase of the project, is now used in routine weather forecasting at almost all participating institutes. Modern numerical weather forecasting systems have three basic components: an analysis unit, a forecast model, and a postprocessor. Analysis provides the initial conditions for the model, based on recent observations and other sources of information. The forecast model spatially and temporally discretizes and then integrates the classical equations-Newton´s second law, mass conservation, and thermodynamics. In the postprocessing step, the relevant weather phenomena (for example, wind speed at 10 m height) are calculated from the model variables. The article outlines the analysis unit, forecast model, and postprocessor of the Hirlam system, as well as its implementation on massively parallel processing systems
Keywords
geophysical techniques; geophysics computing; parallel machines; parallel programming; weather forecasting; Hirlam project; analysis unit; classical equations; forecast model; high resolution limited area modeling; initial conditions; mass conservation; massively parallel processing systems; meteorology; model variables; national meteorological institutes; numerical short range weather forecasting system; postprocessor; routine weather forecasting; thermodynamics; weather phenomena; Cats; Humidity; Information analysis; Information resources; Land surface temperature; Meteorology; Ocean temperature; Parallel processing; Predictive models; Sea surface; Thermodynamics; Weather forecasting; Wind forecasting; Wind speed;
fLanguage
English
Journal_Title
Computational Science & Engineering, IEEE
Publisher
ieee
ISSN
1070-9924
Type
jour
DOI
10.1109/99.556505
Filename
556505
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