摘要
利用ECMWF历史预报资料,从动力、热力、水汽、不稳定条件四个方面选取影响雷暴大风发生的因子,构建多因变量数组,并利用主成分分析确定配料系数及其阈值,在此基础上进行配料,研发了四川省雷暴大风概率预报产品投入应用。2018年汛期应用表明:雷暴大风产品对预报概率超过65%的区域有指示意义,且优于ECMWF数值预报的100 m高度风,在检验的个例中,有效命中率达25%以上。
By using ECMWF high-resolution forecast data,the factors that affect the occurrence of thunderstorm wind are selected from the aspects of dynamics,thermodynamics,water vapor,and unstable energy,the array of multi-dependent variable was constructed,and the ingredient coefficient and its threshold value of the forecasting factor were determined by principal component analysis(PCA).On the basis,the probability forecast product of thunderstorm wind in Sichuan was developed.In 2018,forecasting products of thunderstorm wind were indicative of areas where the probability of occurrence exceeds 65%,and were superior to wind of the ECMWF numerical forecast at the 100 m height.In the cases of test,the effective hit rate of forecast was more than 25%.
作者
陈永仁
康岚
曹萍萍
胡迪
罗辉
CHEN Yongren;KANG Lan;CAO Pinpin;HU Di;LUO Hui(Institute of Plateau Meteorology,CMA,Chengdu 610072,China;Sichuan Provincial Meteorological observatory,Chengdu 610072,China;Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province,Chengdu 610072,China)
出处
《高原山地气象研究》
2018年第4期45-52,共8页
Plateau and Mountain Meteorology Research
基金
高原与盆地暴雨旱涝灾害四川省重点实验室课题(2017-青年-03
2017-重点-01)
2017-2019四川强对流预报创新团队的资助
关键词
雷暴大风
主成分分析
概率预报
thunderstorm wind
principal component analysis
the ingredient method
