Preliminary Study of Precipitation Ensemble Prediction Based on Multimodel in Chaohu Lake

Based on the data from INCA, WRF(mesoscale model), ECMWF, JMA (Global model) and observed data around Chaohu Lake, multimodel test equations are established to access the following two methods: the Adaptive least square statistical ensemble, method and the weighted average method. Results show: 1) The error of forecasts from the 2 integrated forecasts is significantly small than that from the single model. 2) The error resulted by the Adaptive least square method is larger than that by the weighted average method in 6-24 h term, but is small in 48-72 h term. 3) For the light rain grade the, TS score of the Adaptive least square method was the highest. For above moderate rain grads, the TS score of the weighted average method is higher than other one. In addition, the correct rate of the weighted average method is always higher than that of the Adaptive least square method.