近地面大气电场数据EMD方法分析  

EMD Based Analysis of Atmospheric Electric Field Data

作　　者：徐栋璞[1,2,3] 王振会[1,2] 曾庆锋[1,2] 敖雪[1,2] 

机构地区：[1]南京信息工程大学气象灾害省部共建教育部重点实验室,南京210044 [2]南京信息工程大学大气物理学院,南京210044 [3]江苏省无锡市江阴气象局,江阴214432

出　　处：《气象科技》2013年第1期170-176,共7页Meteorological Science and Technology

基　　金：公益性行业科研专项(GYHY200806014);江苏省研究生培养创新工程(CXLX11_0624)共同资助

摘　　要：将经验模态分解(EMD)方法应用于2009年夏季近地面大气电场资料的分析,分解出雷暴和晴天天气大气电场的不同时间尺度变化分量,并提取两类天气状态下的大气电场振荡特征进行对比。结果表明:EMD方法适合应用于近地面大气电场资料的分析,雷暴天气大气电场以晴天天气大气电场作为背景场,包含了周期振荡平稳的晴天天气成分;晴天天气大气电场能量集中于长周期振荡分量,而雷暴电场能量主要是集中于短周期振荡分量。发生雷暴前,IMF(本征模态函数)1分量的中心频率会出现明显跳跃或其对应幅度明显增大的现象。利用这些特征对随机选出的38次过程进行预报效果检验,得到预警的探测概率为84.2%。An analysis of the near-surface atmospheric electric field data in the summer of 2009 is presented based on the empirical mode decomposition （EMD） method. The vari-scaled components of the atmospheric electric field in thunderstorm and fair weather are decomposed and the atmospheric electric field oscillation characteristics of two types of weather conditions are extracted and compared. The results show that the EMD method is suitable for the analysis of atmospheric electric field data. The atmospheric electric field in thunderstorm weather is under the background of atmospheric electric field in fair weather, and so contains the steady periodic oscillation compositions of fair weather. The atmospheric electric field energy in fair weather is concentrated in the long-period oscillation component, while that in thunderstorm weather is mainly concentrated in the short-period oscillation component. Before cloud-to-ground lightning occurring, the central frequency of IMF1 （IMF： Intrinsic Mode Function） will jump or the corresponding amplitude of IMF1 will increased significantly. According to these characteristics, 38 thunderstorms selected randomly are tested with lightning location data and the results show that the detection probability of warning is 84.2%.

关 键 词：EMD 大气电场 雷暴天气 雷电预警 

分 类 号：P315.7[天文地球—地震学]