Probabilistic Weather Forecast Calibration: New Results from the ECMWF Reforecasts
Tom Hamill, NOAA ESRL, Physical Sciences Laboratory
We review the impact of probabilistic forecast calibration using reforecast data sets from a 1998 version of the NCEP GFS and a 2005 version of the ECMWF forecast models. With both models, there is a substantial impact on temperature and precipitation forecast skill from the application of calibration techniques using reforecasts. The large training sample sizes were especially important for the correction of longer-lead temperature forecasts and precipitation forecasts at high thresholds. It is argued that the computation of reforecast data sets should become an integral part of operational ensemble prediction systems.
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