IVT postprocessing model V 1.0. In Integrated Vapor Transport Forecast Models, Reanalysis, and Postprocessing Machine Learning Models for the North American West Coast [2008-2017]

William E. Chapman & Brian Kawzenuk
This study tests the utility of convolutional neural networks (CNN) as a postprocessing framework for improving the National Center for Environmental Prediction’s Global Forecast System’s (GFS) integrated vapor transport (IVT) forecast field in the Eastern Pacific and Western United States. IVT is the characteristic field of atmospheric river (AR) events, which provide over 65% of yearly precipitation at some U.S. west-coast locations. When compared to GFS, the method reduces full field root mean squared error...
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