Recorded presentation2.3
Calibration of Probabilistic ECMWF and GFS Temperature and Precipitation Forecasts Using Reforecasts
Tom Hamill, NOAA/ESRL, Boulder, CO; and R. Hagedorn and J. Whitaker
We review results of calibrating daily probabilistic precipitation and temperature forecasts based on ensemble reforecast data sets for a newer (2005) ECMWF and older (1998) NCEP GFS models. We show that large training data sets are not necessary for the calibration of short-term temperature forecasts, but longer-lead temperature forecasts and precipitation forecasts benefit from large sample size. We also show that the decade-old GFS, after calibration, has more skill than the raw ECMWF forecasts. However, after calibration, the ECMWF forecasts are much more skillful than GFS calibrated forecasts, and a multi-model combination of the two is more skillful than either individually. We discuss the implications for operational usage of reforecasts. Recorded presentation
Session 2, Ensemble Forecasting Including Post Processing II
Monday, 21 January 2008, 10:45 AM-11:45 AM, 219
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