MULTIMODEL CONSENSUS FORECASTING OF LOW TEMPERATURE AND ICY WEATHER OVER CENTRAL AND SOUTHERN CHINA IN EARLY 2008

Based on the daily mean temperature and 24-h accumulated total precipitation over central and southern China, the features and the possible causes of the extreme weather events with low temperature and icing conditions,which occurred in the southern part of China during early 2008, are investigated in this study. In addition, multimodel consensus forecasting experiments are conducted by using the ensemble forecasts of ECMWF, JMA, NCEP and CMA taken from the TIGGE archives. Results show that more than a third of the stations in the southern part of China were covered by the extremely abundant precipitation with a 50-a return period, and extremely low temperature with a 50-a return period occurred in the Guizhou and western Hunan province as well. For the 24- to 216-h surface temperature forecasts, the bias-removed multimodel ensemble mean with running training period(R-BREM) has the highest forecast skill of all individual models and multimodel consensus techniques. Taking the RMSEs of the ECMWF 96-h forecasts as the criterion, the forecast time of the surface temperature may be prolonged to 192 h over the southeastern coast of China by using the R-BREM technique. For the sprinkle forecasts over central and southern China, the R-BREM technique has the best performance in terms of threat scores(TS) for the 24- to 192-h forecasts except for the 72-h forecasts among all individual models and multimodel consensus techniques. For the moderate rain, the forecast skill of the R-BREM technique is superior to those of individual models and multimodel ensemble mean.

MULTIMODEL CONSENSUS FORECASTING OF LOW TEMPERATURE AND ICY WEATHER OVER CENTRAL AND SOUTHERN CHINA IN EARLY 2008

Based on the daily mean temperature and 24-h accumulated total precipitation over central and southern China, the features and the possible causes of the extreme weather events with low temperature and icing conditions, which occurred in the southern part of China during early 2008, are investigated in this study. In addition, multimodel consensus forecasting experiments are conducted by using the ensemble forecasts of ECMWF, JMA, NCEP and CMA taken from the TIGGE archives. Results show that more than a third of the stations in the southern part of China were covered by the extremely abundant precipitation with a 50-a return period, and extremely low temperature with a 50-a return period occurred in the Guizhou and western Hunan province as well. For the 24- to 216-h surface temperature forecasts, the bias-removed multimodel ensemble mean with running training period (R-BREM) has the highest forecast skill of all individual models and multimodel consensus techniques. Taking the RMSEs of the ECMWF 96-h forecasts as the criterion, the forecast time of the surface temperature may be prolonged to 192 h over the southeastern coast of China by using the R-BREM technique. For the sprinkle forecasts over central and southern China, the R-BREM technique has the best performance in terms of threat scores (TS) for the 24- to 192-h forecasts except for the 72-h forecasts among all individual models and multimodel consensus techniques. For the moderate rain, the forecast skill of the R-BREM technique is superior to those of individual models and multimodel ensemble mean.