基于FY-4A卫星和随机森林算法的西藏山南市雷电短临预报方法  

Lightning Nowcasting Method for Tibet Shannan City Based on FY-4A Satellite Data and Random Forest Algorithm

作　　者：张蕾 姚叶青 苗开超 陈定梅 王传辉 ZHANG Lei;YAO Yeqing;MIAO Kaichao;CHEN Dingmei;WANG Chuanhui(Anhui Public Weather Service Center,Hefei 23003l;Shannan Meteorological Bureau,Xizang,Shannan 856000)

机构地区：[1]安徽省公共气象服务中心,合肥230031 [2]西藏山南市气象局,山南856000

出　　处：《气象科技》2023年第6期867-878,共12页Meteorological Science and Technology

基　　金：安徽省气象局创新发展专项(CXM202111)资助。

摘　　要：针对青藏高原地区雷电短临预报缺乏雷达资料的问题,采用FY-4A卫星多通道数据、欧洲中心第5代再分析资料(ERA5)中的对流指数、闪电定位仪资料等多源监测数据,根据雷电的发生、发展机理,提出了18个关键预报因子,利用随机森林算法建立了适用于西藏山南地区的雷电短临预报模型。统计分析各预报因子在有无雷电天气样本中的概率密度分布与随机森林模型得到的特征重要度指标,结果表明提出的预报因子物理意义明确,建立的模型可信度较高。利用随机森林算法分别对未来10 min、20 min、30 min建立雷电预报模型,并与光流外推预报方法进行对比检验,结果表明:随机森林模型预报效果命中率(POD)、临界成功指数(CSI)均高于光流法,空报率(FAR)也相对较低;未来20 min的随机森林预报模型CSI评分最高,整体预报效果最佳。Due to the lack of radar data in the Tibet Plateau region,lightning nowcasting has met certain difficulties.In order to solve this problem,the FY-4A satellite,the convection index of ERA5 reanalysis data and lightning location information are being used to propose 18 prediction factors in accordance with the mechanism of formation and development of lightning.A lightning nowcasting model is being established based on the random forest algorithm for Tibet's Shannan region.By statistically analysing the probability density distribution of each prediction factor in the lightning and non-lightning samples,and comparing with the feature importance from the random forest model,it is demonstrated that the statistical analysis results fit well with the conclusion from the important feature.Therefore the proposed prediction factors have a relatively clear physical meaning and the established model is of high reliability.The results also reveal that the difference between the infrared brightness temperature and land surface temperature,the lightning location data of the past 10 minutes,the K-index and the infrared brightness temperature of channels ll and 12 have significant contributions to the lightning nowcasting model.Analysing the prediction ability of the random forest model at different development stages of lightning,through two cases,the results show that the model can effectively predict the lightning location for the next 30 minutes.The lightning forecasting location is in good consistency with the observation data,especially at the stage of strong convective development.However,at the early stages of the convective development and dissipation,due to the model limitations in predicting the evolution of convection,the model has a relatively high false alarm ratio(FAR)and miss alarm ratio(MAR),so the prediction effect is relatively poor.To find the best predictable time scale,the lightning nowcasting models have been trained separately for the next 10,20 and 30 minutes by using the random forest algorithm.The vali

关 键 词：雷电短临预报 随机森林 FY-4A卫星 对流指数 

分 类 号：P405[天文地球—大气科学及气象学]