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全国雷电灾害分析及雷灾经济损失预测
引用本文:刘 佼,肖稳安,陈红兵.全国雷电灾害分析及雷灾经济损失预测[J].气象与环境科学,2010,33(4):21-26.
作者姓名:刘 佼  肖稳安  陈红兵
作者单位: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.江苏省气象局,南京 210008
摘    要:利用中国气象局雷电防护管理办公室编写的《1998-2008年全国雷电灾害汇编》资料,对1998-2008年全国雷电灾害进行了时间、空间、行业分布,经济损失,人员伤亡等方面的统计分析。结果表明:我国近11 a雷电灾害总体上呈增长趋势,每年的6-8月为雷灾的高发期。我国雷灾在地域上的分布主要集中在华南沿海和华东沿海地区。全国雷灾涉及行业最为严重的是电力业。近年来因雷电导致的建筑物损害、供电故障、火灾爆炸事故次数之间的整体比例为9∶5∶3,建筑物损害的事故发生最多,但火灾爆炸事故的经济损失最大。我国近年来所发生雷灾中因雷电致死致伤的人员比例为1∶1。利用上述统计分析结果,运用灰色关联法,预测2009-2012年间我国雷灾直接经济损失年均40591.53万元。

关 键 词:雷灾  雷灾经济损失  分析  预测

National Lightning Disaster Analysis and Economic Loss Forecast
Liu Jiao,Xiao Wenan,Chen Hongbing.National Lightning Disaster Analysis and Economic Loss Forecast[J].Meteorological and Environmental Sciences,2010,33(4):21-26.
Authors:Liu Jiao  Xiao Wenan  Chen Hongbing
Abstract:This paper statistically analyzed national lightning disasters from time, space, industry distribution, economic loss and casualties on the basis of "1998-2008 National Lightning Compiled " which published by Office of Lightning Protection and Disasters Alleviation of China Meteorological Administration. The results indicated that national lightning disasters showed increasing trend in recent 11years, the lightning peak period was from June to August of each year. Geographical distribution of lightning disasters in China mostly concentrated in Southern and Eastern coastal regions. The most severe lightning accidents in China appeared in electrical power industry. The ratio of building damage, power failure, fire and explosion due to lightning occurred in China was about 9:5:3 in recent years. The ratio of building damage is the highest, but the fire and explosion accidents are in the largest economic loss. The ratio of deaths and injuries due to lightning is 1:1. Based on the analysis results, using the gray relational method, the paper forecasted the lightning disasters economic losses during 2009-2012 of China is 405.9153 million Yuan.
Keywords:lightning disaster  lightning disasters economic loss  analysis  forecast
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