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Jason E. Nachamkin


The composite method is applied to verify a series of idealized and real precipitation forecasts as part of the Spatial Forecast Verification Methods Intercomparison Project. The test cases range from simple geometric shapes to high-resolution (∼4 km) numerical model precipitation output. The performance of the composite method is described as it is applied to each set of forecasts. In general, the method performed well because it was able to relay information concerning spatial displacement and areal coverage errors. Summary scores derived from the composite means and the individual events displayed relevant information in a condensed form. The composite method also showed an ability to discern performance attributes from high-resolution precipitation forecasts from several competing model configurations, though the results were somewhat limited by the lack of data. Overall, the composite method proved to be most sensitive in revealing systematic displacement errors, while it was less sensitive to systematic model biases.

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