摘要
利用安溪县国家气象站2004—2015年的雷暴观测资料,分析安溪县雷暴的气候特征及环境背景分类。并根据雷暴活动特征及雷暴天气产生的环境场条件,诊断和分析T639数值模式输出产品与雷暴观测资料的相关性,对41个相关因子做显著性检验,挑选相关性较好的9个因子做分析。对9个预报因子进行0、1化处理并进行逐步回归,选取850 hPa垂直速度、850 hPa假相当位温、700 hPa温度、K指数、850 hPa比湿等5个因子,建立雷暴潜势预报方程。利用2015—2017年T639模式资料进行回代分析评估,发现当雷暴概率预报Y值>0.6时,雷暴预报准确率最高,达85.60%,且漏报率、空报率很低。再以2018年T639数值模式资料对雷暴潜势概率进行计算评估,准确率为83.84%,漏报率为5.75%,空报率为10.41%。由此可见,基于T639数值产品的雷暴潜势方程可以为安溪县雷暴天气的预警预报和防雷减灾服务提供客观的参考和依据。
The climatic characteristics and circulation background classification of the thunderstorms in Anxi county have been analyzed by virtue of utilizing thunderstorm observation data from 2004 to2015 of Anxi’s national meteorological station.The correlation between the output products of T639 numerical schema and thunderstorm observation data were diagnosed,it was analyzed according to the characteristics of thunderstorm activity and the environmental conditions of thunderstorm weather.41 related factors are tested in terms of statistical significance,and 9 factors with better correlation are selected for analysis.9 forecasting factors are treated with 0,1 and stepwise regression.Finally,five factors were selected to establish the thunderstorm potential prediction equation,such as 850 hPa vertical velocity,850 hPa potential pseudo-equivalent temperature,700 hPa temperature,K index and850 hPa specific humidity.Back substitution is analyzed and evaluated on the basis of the T639 model data from 2015 to 2017.It is demonstrated that when the accuracy of thunderstorm forecast Y choose>0.6,the hit rate is the highest,85.60%,as well as the missing report rate and the empty report rate are lowest.Furthermore,the probability of thunderstorm potential is calculated and evaluated through referenced to T639 numerical schema data of 2018.The accuracy of TSK is 83.84%,the missing report rate is 5.75%,and the empty report rate is 10.41%.The thunderstorm potential equation based on T639 numerical products can provide objective reference and basis for thunderstorm weather prediction as well as anti-thunder and reducing disaster loss in Anxi county.
作者
韦英英
程思
韩庚
仇耀
冯晋勤
WEI Yingying;CHENG Si;HAN Geng;QIU Yao;FENG Jinqin(Fujian Key Laboratory of Severe Weather,Fuzhou 350000,China;Quanzhou Meteorological Bureau,Quanzhou 362000,China)
出处
《沙漠与绿洲气象》
2020年第6期46-53,共8页
Desert and Oasis Meteorology
基金
福建省气象局基层科技项目(2018J59)
福建省气象局基层科技项目(2019J04)
泉州市科技局项目(2019N117S)。
关键词
雷暴
气候统计
T639数值产品
潜势预报方程
thunderstorm
climatological statistics
T639 numerical model products
equation of thunderstorm potential prediction
