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基于inpolygon的区域外闪电剔除方法研究

杨仲江 江珂 曹洪亮 楼嘉懿

灾害学Issue(3):72-76,5.
灾害学Issue(3):72-76,5.DOI:10.3969/j.issn.1000-811X.2014.03.014

基于inpolygon的区域外闪电剔除方法研究

Inpolygon-based Elimination Method of Regional Lightning

杨仲江 1江珂 2曹洪亮 1楼嘉懿2

作者信息

  • 1. 南京信息工程大学 中国气象局气溶胶与云降水重点开放实验室,江苏 南京210044
  • 2. 南京信息工程大学 大气物理学院,江苏 南京210044
  • 折叠

摘要

Abstract

The integrity and accuracy of lightning data is the basis of lightning disaster risk assessment,which influence the accuracy of the results,and series of scientific research depended on the lightning data.The data which is outside of the area will not affect the accuracy of inquiry when exploring regional distribution of lightning, but when time distribution of lightning is explored,only the data inside of the area is valid.There are serious errors using the traditional method of lightning frequency statistics in an area,on behalf of a rectangular area bounded by latitude and longitude.Inpolygon function method is firstly applied to distinguish between interior and exterior light-ning data of statistical area simply and quickly,using the geographical map of provinces,cities and counties as boundary,thus the accuracy of lightning raw data will be greatly increased.Taking Jiangsu province as an exam-ple,lightning frequency counted by the traditional method are compared with the new inpolygon function method. The results show that in 2012,the lightning data of Jiangsu province counted by the new method account for 50.46% of the traditional method,which means the error of the traditional method,is as high as 98.18%.We can get real and effective lightning frequency data in the province by eliminating those outside the province,and greatly improve the accuracy and reliability of the lightning disaster risk assessment and thunderstorm distribution analysis.

关键词

闪电资料/shaperead函数/inpolygon函数/地理底图/误差

Key words

lightning data/shaperead function/inpolygon function/geographical map/error

分类

资源环境

引用本文复制引用

杨仲江,江珂,曹洪亮,楼嘉懿..基于inpolygon的区域外闪电剔除方法研究[J].灾害学,2014,(3):72-76,5.

基金项目

国家自然科学基金项目(41175003);江苏高校优势学科建设工程资助项目 ()

灾害学

OACSCDCSTPCD

1000-811X

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