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RECORD NUMBER: 16 OF 54

OLS Field Name OLS Field Data
Main Title Hierarchical Stochastic Model of Large-Scale Atmospheric Circulation Patterns and Multiple Station Daily Precipitation.
Author Wilson, L. L. ; Lettenmaier, D. P. ; Skyllingstad, E. ;
CORP Author Washington Univ., Seattle. Dept. of Civil Engineering. ;Battelle Pacific Northwest Labs., Richland, WA.;Corvallis Environmental Research Lab., OR.
Publisher c1992
Year Published 1992
Report Number DE-AC06-76RLO-1830; EPA/600/J-92/287;
Stock Number PB92-217421
Additional Subjects Atmospheric models ; Atmospheric circulation ; Precipitation(Meteorology) ; Markov processes ; Stochastic processes ; Weather forecasting ; Prediction equations ; North Pacific Ocean ; Cascade Mountains ; Pacific Northwest Region(United States)
Holdings
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Status
NTIS  PB92-217421 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. 06/01/1993
Collation 22p
Abstract
A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. Four algorithms are investigated for classification of daily weather states; k means, fuzzy clustering, principal components, and principal components coupled with k-means clustering. A semi-Markov model with a geometric distribution for within-class lengths of stay is used to describe the evolution of weather classes. A hierarchical modified Polya urn model is used to simulate precipitation conditioned on the regional weather type. An information measure that considers both the probability of climate class occurrence and conditional precipitation probabilities is developed to quantify the extent to which each of the climate classification schemes discriminates the precipitation states at the precipitation stations. The model is implemented using National Meteorological Center historical atmospheric observations for the period 1965-88 mapped to 5 degree by 5 degree grid cells over the eastern North Pacific, and three precipitation stations west of the Cascade mountain range in the State of Washington. Comparison of simulated weather class-station precipitation time series with observational data shows that the model preserved weather class statistics and mean daily precipitation quite well, especially for stations highest in the hierarchy.