Using precipitation forecast data from European Centre for Medium-Range Weather Forecasts,National Centers for Environmental Prediction,German meteorological service,China Meteorological Administration,Japan Meteorological Agency,and the daily observed precipitation in Meishan from January 1,2020 to January 2,2023,the model precipitation is first revised using the optimal TS score method,and then the multi-model ensemble forecasts are carried out using probability-matching mean,bias-removed ensemble mean and weighted ensemble mean schemes,whose effects are experimented and compared.The results show that the probability-matching mean scheme improves the accuracy of clear-rainy forecast,but poorly forecasts heavy rain and rainstorm.The bias-removed ensemble mean scheme has a smaller improvement for rain prediction.Both the weighted ensemble mean and classified station-ensemble schemes improve the accuracy of clear-rainy forecast greatly,and reduce the omission rate of rainstorm,resulting in a larger improvement in the TS score of rainstorm.
关键词
最优TS评分/多模式集成/概率匹配平均/加权集成平均/分类站点集成
Key words
optimal threat score/multi-model ensemble/probability matching mean/weighted ensemble mean/classified station ensemble
维普
万方数据