Abstract
Abstract The applicability of meteorological general circulation models (GCMs) is limited by their spatial resolution. In this paper, a method is developed for improving the resolution of GCM-generated rainfall fields, using ideas from Bayesian image analysis to improve the resolution of the binary wet–dry image. This approach incorporates both the spatial and temporal memory of the rainfall field and can be adapted to utilize any available physical information. The method is illustrated using data from a network of weather radar stations in Arkansas, and some informal diagnostic procedures are developed for assessing the adequacy of the underlying model.
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