Extended Abstract

the s outhern part of Ch ina d uring the period fro m 1 J anuary until 3 1 J anuary 2 008, t hemultimodel con sensus f orecasts of th e 24h ac cumulated total pre cipitation have beenconducted fo r the fo recast pe riod fr om 16 t o 3 1 J anuary 2 008. S imilar to the procedurementioned in section 4, 6 days training period was chosen as the optimal training period andthe TRMM (Tropical Ra infall Me asuring Mission) prec ipitation da ta were c hosen as the“observed data”. Threat score (TS), also known as the critical success index (Schaefer, 1990),(a)(b)Fig.1. The extreme daily mean temperature (a) and 24h accumulated total precipitation (b)distribution for different return periods during the period from10 January to 2 February 2008.or equitable threat score (ETS) which is a modification of the threat score to explain the correctforecasts as a res ult of chance (Gilb ert, 18 84), is u sed at the Natio nal Centers f orEnvironmental P rediction (NCEP ) a lmost e xclusively as the mo st impo rtant v ariable forverification of t he skill in p recipitation forecasting (M esinger, 2008). In thi s s tudy, TS withdifferent rank s was utiliz ed to ev aluate the pr ecipitation for ecast skills of different indiv idualmodels and multimodel consensus forecasts. It is defined as follows,NATS NA NB NCwith NA denoting the total number of correct forecasting points, NB the total number of falsealarm points, and NC the total number of forecast miss points.Figure 2 shows the TS score of 24h accumulated total precipitation forecast for sprinkle andmoderate r ain ov er c entral a nd s outhern Chin a during the p eriod from 2 5 January un til 1February 2008 with the forecast time from 24-216h, including the CMA, JMA, NCEP, ECMWF,multimodel ensemble mean a nd bias-removed ensemble mean with running training period.Comparing forecasts of the sprinkle (0.1-10mm/24h) rain of the individual models, the forecastskills of the JMA model are the best among four models except for the 24h forecasts. Withincreasing precipitation ranks, the TS scores of the individual models decrease considerably.For the mo derate ra in (10-25mm/24h) f orecasts over c entral a nd s outhern Ch ina, the TSscores of the JMA model contain large fluctuations and the ECMWF forecasts are more stable,while the forecast skills of the CMA model are not satisfactory. In order to obtain better forecastskills, the ensemble forecasts of the JMA, ECMWF and NCEP models were selected to carryon the mu ltimodel c onsensus forecasts. The TS sco res have b een improved by using theR-BREM technique for most forecast time exc ept for 72h and 216h forecasts compared withthe ECMWF forecasts which have the best performance among four models. For the moderaterain forecasting, the 24h-192h TS scores of the R-BREM technique are higher than those of-372-