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ARS Home » Pacific West Area » Tucson, Arizona » SWRC » Research » Publications at this Location » Publication #138794

Title: PRECIPITATION SIMULATION MODELS 1425

Author
item KEEFER, TIMOTHY

Submitted to: Encyclopedia of Water Science
Publication Type: Review Article
Publication Acceptance Date: 11/20/2002
Publication Date: 7/13/2003
Citation: Keefer, T.O. 2003. Precipitation simulation models. In: Stewart, B.A., Howell, T.A. Encyclopedia of Water Science. New York: Marcell Dekker, Inc. pp. 729-733.

Interpretive Summary: Computer models which generate synthesized sequences of precipitation at a range of spatial and temporal scales are called precipitation simulation models. There are three categories of these types of models: 1) general circulation models operate at large spatial scales, 2) stochastic rainstorm models generate individual storm events, and 3) daily precipitation models generate precipitation at daily time steps for a single location. The selection and use of these models should be justified by the time and space resolution of the desired results. It is expected that some future developments to precipitation simulation models will be techniques which link the output of general circulation models at large scales down to the scales of farms or watersheds; that the physical dynamics of precipitation storm events will be more faithfully represented; and the inclusion of large atmospheric phenomena like El Nino will be incorporated into daily precipitation models.

Technical Abstract: Precipitation simulation models generate synthesized sequences of precipitation at a range of spatial and temporal scales. Three broad categories are general circulation models, stochastic spatial-temporal rainstorm models and daily precipitation models. Model selection and use should be justified by the desired resolution of results and ability to fully estimate the required parameters. Future developments to precipitation simulation models will be downscaling techniques which link regional and local scales, improved algorithms to more faithfully represent the stochastic and physical dynamics of precipitation, and the inclusion of low-frequency oscillations and spatial distribution of parameters in daily precipitation models.