江苏暴雨概率预报及其业务应用  

Application of the heavy rainfall probability forecast in Jiangsu

作　　者：陈圣劼[1] 孙燕[1] 刘安宁[1] 罗兵[1] 

机构地区：[1]江苏省气象台,南京210008

出　　处：《气象科学》2016年第2期269-274,共6页Journal of the Meteorological Sciences

基　　金：国家科技支撑计划项目(2011BAK21B00);江苏省气象台自立科技研发项目(ST201401);江苏省科技厅科技支撑计划社会发展项目(BE2011818)

摘　　要：以未来12~36 h、36~60 h和60~84 h的暴雨预报为目标,利用2011年—2013年夏季6—8月欧洲细网格数值模式预报产品分析了江苏夏季暴雨的可能预报因子。通过对各因子进行相关性、敏感性和代表性分析后,优选了22个对不同强度降水具有较好区分能力的暴雨预报因子。以这些因子为基础建立了一种简单的江苏省暴雨概率预报方法。其预报产品已在江苏省气象业务一体化平台上投入业务使用。该方法在2011—2013年7月,针对提前12 h预报的历史回报试验中,TS技巧评分平均为13.6,明显高于EC细网格24 h降水预报产品（平均TS评分仅为4.5）。在2014年梅汛期的6月25—26日、7月1—2日和7月4—5日三次区域性暴雨个例的预报试验中,提前60、36、12 h的预报效果均较好,其平均TS评分（44.6）也明显高于欧洲细网格数值模式的降水预报（20.4）。Aiming at the heavy rainfall probability forecast in Jiangsu province in the coming 12-36, 36-60 and 60-84 hours, an investigation has been conducted on the possible predictors of summer rainfall in Jiangsu province by European Center of Medium range Weather forecasts （ECMWF） fine mesh numer- ical forecast model products in summer （June-August） for the period of 2011-2013. The optimized pre- dictors that can well distinguish rainfall with different grades amount to 22 have been selected to analyze their relativity, sensitivity and representativeness. On the basis of the 22 factors, a simple heavy rainfall probability forecast method in Jiangsu province was proposed, and the products of this method have been put into use on the Jiangsu Weather Service Integrated Platform. Great prediction effects of this method were achieved in the reforecast of heavy rain for the future 12 hours in all the examples for July of 2011- 2013 and in the three regional heavy rain examples during 2014 Meiyu season. The average Ts score for the reforecast of the heavy rainfall probability in Jiangsu province is 13.6 and obviously exceeds that of the rainfall prediction by ECMWF numerical forecast model （the average Ts score is only 4.5）. Besides, in the forecast test of the three examples, the average Ts scores for the prediction of heavy rain region of 60-hour, 36-hour and 12-hour in advance based on the new probability forecast method is 44.6, which is also much higher than that of ECMWF numerical forecast model （20.4）.

关 键 词：暴雨 EC细网格模式 预报因子选取 概率预报方法 检验评分 

分 类 号：P456.1[天文地球—大气科学及气象学]