Chinese Journal of Agrometeorology ›› 2019, Vol. 40 ›› Issue (06): 402-410.doi: 10.3969/j.issn.1000-6362.2019.06.007

Previous Articles    

A Weather-index-based Insurance-oriented Method for Hail Disaster Assessment on Fruits Loss

LUAN Qing-zu, DONG Peng-jie, YE Cai-hua   

  1. 1. Institute of Urban Meteorology, CMA, Beijing 100089, China; 2.Beijing Municipal Climate Center, Beijing 100089; 3.Beijing Tongzhouqu Meteorological Bureau, Beijing 101100
  • Online:2019-06-20 Published:2019-06-11

Abstract: Hail disaster is one of meteorological disasters threatening agricultural producing in China. Solving the problem of loss assessment methods that has been restraining index-based insurance production design for hail is of scientific value for developing stable and sustainable weather-index-based insurance(WII) productions, and also is of guiding significance for promoting WII productions in wide rang. Considering objective demanding of claiming index design for WII productions, a loss assessment method for fruits suffering from hail disaster was proposed based on momentum equation in this paper. The method satisfied claiming index design requirements for WII productions by introducing hail recognition technology relying on meteorological radar observation.And also, it revealed the disaster-causing mechanism of hail damage to fruits by attaining fruits’ sensitive parameters to hail crash, through analyzing the stress relation of fruits in the process of hail damage and quantifying fruits’ physical characteristics representation after crash by hail. Feasibility in application of loss assessment for hail was analyzed in the case of peaches growing in Pinggu district of Beijing. Results showed that the method was so simple, rapid and efficient that was able to assess peaches’ damage level caused by hail, based on which designing fruits WII productions for hail was practically viable.

Key words: Fruit firmness, Critical damage-incurred diameter, Momentum equation, Weather-index-based insurance, Hail size distribution