Study on the Spatiotemporal Distribution Characteristics of Lightning Activities in the Chengdu-Chongqing Region
Based on the lightning positioning monitoring data in the Chengdu-Chongqing region from 2016 to 2022,this study utilizes methods such as mathematical statistics and ArcGIS spatial analysis to investigate the spa-tiotemporal distribution characteristics of lightning activity in the region.The results indicate that negative flashes dominate lightning activity in the Chengdu-Chongqing region,accounting for an annual average proportion of 92.7％.The annual variation in the proportion of negative flashes shows a significant decreasing trend.Seasonal variations are evident,with the highest proportion occurring in summer,reaching 76.4％.The monthly variation curve exhibits a single-peak pattern,with July and August being the peak months for lightning activity.Daily var-iation shows a double-peak pattern,with lightning activity predominantly occurring from 23:00 to 04:00 the next day,accounting for 31.7％,while 10:00-12:00 represents the valley value of lightning activity.The most frequent range for lightning current amplitude is 7-17 kA,with 95％of lightning intensities being below 50 kA and 90％below 40 kA.High lightning incidence areas in the Chengdu-Chongqing region are mainly distributed in moun-tainous and hilly areas.The high-density zone is located in the southwest of Chongqing,including Yongchuan,Bishan,Jiangjin,Qijiang,and the main urban area,with a density generally exceeding 6 times/km2.The second-highest density area is distributed in parts of Yunyang in Chongqing,and some areas in Neijiang,Ziyang,Suining,Nanchong,and Guangyuan in Sichuan,with a density generally exceeding 3 times/km2.The research results pro-vide substantial data support for lightning monitoring,forecasting,and warning in the Chengdu-Chongqing region,especially during the summer flood season,to enhance the ability to respond to and prevent lightning disasters.
lightning activityspatiotemporal distributionArcGISChengdu-Chongqing region
NETL
NSTL
万方数据
