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干旱区地理 ›› 2019, Vol. 42 ›› Issue (3): 469-477.doi: 10.12118/j.issn.1000-6060.2019.03.02

• 气候与水文 • 上一篇    下一篇

内蒙古牧区暴风雪风险评估研究

德勒格日玛1,2,韩理2,孟雪峰2,月河2, 计艳霞2, 张莫日根2,   

  1. 1 南京信息工程大学,江苏 南京 2100442 内蒙古自治区气象台,内蒙古 呼和浩特 010051

  • 收稿日期:2017-10-09 修回日期:2018-09-21 出版日期:2019-05-25 发布日期:2019-05-18
  • 作者简介:德勒格日玛(1981-),女,内蒙古鄂尔多斯市人,高级工程师,从事短期天气气候预测、灾害风险评估及研究工作.Email:gerima_dele@aliyun.com
  • 基金资助:
    国家自然科学基金项目(41265004);内蒙古暴雪(暴风雪)专家型预报员创新团队资助

Risk assessment of snowstorm in pasturing areas of Inner Mongolia

Delegerima1,2, HAN Li2, MENG Xuefeng2, HANG Yuehe2, JI Yanxia2,ZHANG Morgen2   

  1. (1 Nanjing University of Information Science & Technology,Nanjing 210044,Jiangsu,China;
    2 Inner Mongolia Meteorological Observatory,Hohhot 010051,Inner Mongolia,China)
  • Received:2017-10-09 Revised:2018-09-21 Online:2019-05-25 Published:2019-05-18

摘要: 暴风雪天气是内蒙古草原牧区危害严重的气象灾害之一。为了更确切的了解暴风雪灾害天气的特征,分季节对暴风雪天气进行了类型,即秋末初春暴风雪天气、隆冬暴风雪天气、春末初夏湿雪冷雨型暴风雪天气;通过因子分析法、灰色关联分析对三种类型暴风雪天气进行分析,发现上述三种类型暴风雪天气都为风、雪、寒潮灾害群天气;每个季节最主要的影响因子不同,导致的灾害程度不同;因此掌握各个季节暴风雪天气的特征对预报员提高预报预警水平很有实际意义。尝试使用BP神经网络法、支持向量机对暴风雪灾害等级进行评估,通过与根据灾情评定的灾害等级对比分析,发现SVM方法的评估效果优于BP神经网络法,因此,基于数值预报产品通过SVM方法做暴风雪灾害预警产品成为可能,可为暴风雪灾害预报预警业务提供客观参考依据,能够提升预报服务效果,减少灾害损失。

关键词: 暴风雪, 风险评估, BP , SVM

Abstract: The snowstorm occurs every year in the middle and eastern part of Inner Mongolia,China and it often induces serious harm.Therefore,it is necessary to improve the forecasting,early warning and service level of such weather disasters and reduce disaster losses as much as possible.Because the hazard degree caused by snowstorm is different in various seasons,it is necessary to do the analysis by seasons,so the snowstorm is classified into three categories based on the seasons namely,the late autumn and early spring snowstorm,the midwinter snowstorm,and the cold rain or wet snow type of snowstorm occurred in the late spring and early summer,which have been analyzed in this paper.Based on the factor analysis method and grey correlation degree analysis it is found that the snowstorms,regardless of the types,happened in different seasons were basically all the hazardous weathers due to the gale,the snowfall and the cold wave or even a combination of the three.The leading factors were different in different seasons which led to different hazard degrees.The understanding of the characteristics of the snowstorms in various seasons will help the weather forecasters in snowstorms prediction and early warning.The BP neural network method and SVM method were further used to evaluate the snowstorm hazard level with the data about the snowstorm events that have occurred in the last several decades.Through comparing the effect of evaluated results,it showed that the computational efficiency of SVM method was better and it makes the earlywarning possible in the snowstorm forecasting based on the numerical forecast product.

Key words: snowstorm, risk assessment, BP, SVM