冬小麦保险理赔的高精度气象数据查询研究——以河南省一次大风气象灾害为例

Research on High-precision Meteorological Data Query for Winter Wheat Insurance Claims-A Case Study of a Gale Meteorological Disaster in Henan Province

为解决河南省冬小麦保险理赔中气象凭证获取渠道不统一、查询效率低、理赔控制难、理赔不规范等问题,本文首先对2018—2021年河南冬小麦保险案例进行分析,发现暴雨、风灾、冻灾和旱灾是河南省主要的农业气象灾害保险理赔类型。基于风灾持续时间短、成灾范围小、保险理赔获取气象凭证查询难度大,本研究以河南省冬小麦风灾为例,对气象站点数据、智能网格实况数据和基于站点数据克里金插值法三种方法进行对比,研究河南冬小麦风灾保险理赔优化查询方法。结果表明:基于站点数据,克里金插值法优于站点数据和智能网格实况数据;当极大风速大于10 m/s时,克里金插值法可以作为未覆盖站点数据的有效补充,在保险理赔查询气象凭证中具有较好的适用性,可提高保险理赔中获取气象凭证的有效性和准确性,为冬小麦农业保险风灾理赔的气象查询提供参考依据。

In order to solve the problems such as inconsistent access to meteorological vouchers,low query efficiency,difficult claims control,and non-standard claims in winter wheat insurance claims in Henan Province,this paper first analyzes the case of winter wheat disaster insurance in Henan Province from 2018 to 2021,and finds that rainstorm,wind,frost and drought are the main types of agricultural meteorological disaster claims in Henan Province.Because of the short duration and small scope of wind disasters,it is difficult to obtain meteorological vouchers for insurance claims.This study takes the winter wheat wind disaster in Henan Province as an example,comparing meteorological station data,intelligent grid live data,and Kriging interpolation method based on station data,and studies the optimization query method for insurance claims for winter wheat disasters in Henan Province.The results show that the Kriging interpolation method based on site data is superior to site data and intelligent grid live data,and when the maximum wind speed is greater than 10 m/s,the Kriging interpolation method can serve as an effective supplement to uncovered station data,which has good applicability in insurance claim query meteorological vouchers,improving the effectiveness and accuracy of obtaining meteorological vouchers in insurance claims.It can provide a reference basis for winter wheat agricultural insurance claim wind disaster query.