摘要
FY-4上的闪电成像仪(Lightning Mapping Imager,LMI)从静止轨道平台对视场覆盖范围内的闪电进行连续不间断的观测,闪电资料为监测预警强对流天气提供了重要信息。为研究FY-4闪电资料监测预警强对流的能力,以2018年5月7日厦门暴雨为研究个例,利用FY-4闪电资料、FY-4亮温资料、厦门市自动气象站降水资料以及地面闪电定位网监测数据,研究闪电数据在强降水监测预警中的应用。结果表明:FY-4闪电资料与地基闪电进行数据融合,有效减少了天基与地基闪电产品各自数据的不完整性、不确定性和误差;闪电的移动轨迹与对流云团的移动轨迹相符,且在云团移动轨迹的前方;温度梯度较大的区域和深对流内,闪电强度较强;闪电强度与雨强成正比,且闪电频数峰值多出现在降水峰值前45 min左右。
Research shows that lightning activity is generally ahead of the strong convection center,and strong lightning activity has a good correspondence with heavy precipitation. It is of great significance to apply lightning data in severe weather monitoring on a large scale. A dense network of lightning monitoring stations has been established in China at present,it provides accurate location and frequency of lightning that occurs nearby. But it’s difficult to give a comprehensive lightning distribution image,due to the limit of ground environment. In the field of view from the static orbit platform,the Lightning Mapping Imager(LMI)on FY4 makes up for the lack of ground monitoring and provides important information for severe convective weather monitoring while making continuous and uninterrupted observation of lightning. Taking the rainstorm in Xiamen on May 7,2018 as a case study,FY-4 bright temperature data,automatic weather station precipitation data and the fusion data of FY-4 lightning data and ground lightning location network data are used to analyze the application of lightning data in monitoring and warning heavy precipitation. The study shows that data fusion of FY-4 lightning data and ground lightning can effectively reduce the incompleteness,uncertainty and error of the respective data of the both. The moving track of lightning is consistent with that of convective cloud,and the former always lies ahead of the latter. The intensity of lightning is stronger in deep convection and areas with large temperature gradient,and it is positively proportional to the intensity of rain. The peak frequency of lightning mostly occurs about 45 minutes before the peak of precipitation.
作者
张晓芸
魏鸣
潘佳文
Zhang Xiaoyun;Wei Ming;Pan Jiawen(Collaborative Innovation Center for Weather Disaster Prediction and Assessment,Nanjing University of Information Science and Technology,Nanjing 210044,China;Xiamen Meteorological Service Center,Xiamen 361012,China)
出处
《遥感技术与应用》
CSCD
北大核心
2019年第5期1082-1090,共9页
Remote Sensing Technology and Application
基金
国家自然科学基金项目(41675029)
国家重点基础研究发展计划973项目(2013CB430102)
关键词
FY-4静止卫星
闪电成像仪
闪电强度
强降水
数据融合
FY-4 stationary satellite
Lightning mapping imager
Lightning intensity
Heavy precipitation
Data fusion