A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain

A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain AbstractThe demand for climatological precipitation fields on a regular grid is growing dramatically as ecological and hydrological models become increasingly linked to geographic information systems that spatially represent and manipulate model output. This paper presents an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions. PRISM (Precipitation-elevation Regressions on Independent Slopes Model) brings a combination of climatological and statistical concepts to the analysis of orographic precipitation. Specifically, PRISM 1) uses a digital elevation model (DEM) to estimate the orographic elevations of precipitation stations; 2) uses the DEM and a windowing technique to group stations onto individual topographic facets; 3) estimates precipitation at a DEM grid cell through a regression of precipitation versus DEM elevation developed from stations on the cell's topographic facet; and 4) when possible, calculates a prediction interval for the estimate, which is an approximation of the uncertainty involved. PRISM exhibited the lowest cross-validation bias and absolute error when compared to kriging, detrended kriging, and cokriging in the Willamette River basin, Oregon. PRISM was also applied to northern Oregon and to the entire western United States; detrended kriging and cokriging could not be used, because there was no overall relationship between elevation and precipitation. Cross-validation errors in these applications were confined to relatively low levels because PRISM continually adjusts its frame of reference by using localized precipitation-DEM elevation relationships. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain

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Copyright
Copyright © American Meteorological Society
ISSN
0894-8763
D.O.I.
10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2
Publisher site
See Article on Publisher Site

Abstract

AbstractThe demand for climatological precipitation fields on a regular grid is growing dramatically as ecological and hydrological models become increasingly linked to geographic information systems that spatially represent and manipulate model output. This paper presents an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions. PRISM (Precipitation-elevation Regressions on Independent Slopes Model) brings a combination of climatological and statistical concepts to the analysis of orographic precipitation. Specifically, PRISM 1) uses a digital elevation model (DEM) to estimate the orographic elevations of precipitation stations; 2) uses the DEM and a windowing technique to group stations onto individual topographic facets; 3) estimates precipitation at a DEM grid cell through a regression of precipitation versus DEM elevation developed from stations on the cell's topographic facet; and 4) when possible, calculates a prediction interval for the estimate, which is an approximation of the uncertainty involved. PRISM exhibited the lowest cross-validation bias and absolute error when compared to kriging, detrended kriging, and cokriging in the Willamette River basin, Oregon. PRISM was also applied to northern Oregon and to the entire western United States; detrended kriging and cokriging could not be used, because there was no overall relationship between elevation and precipitation. Cross-validation errors in these applications were confined to relatively low levels because PRISM continually adjusts its frame of reference by using localized precipitation-DEM elevation relationships.

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