气候变化研究进展 ›› 2022, Vol. 18 ›› Issue (2): 253-260.doi: 10.12006/j.issn.1673-1719.2021.067

• 简讯 • 上一篇    

三个全球气象灾害数据库对比及展望

王毅1(), 杨舒楠1(), 张立生1, 曹勇1, 尹宜舟2   

  1. 1 中国气象局国家气象中心,北京 100081
    2 中国气象局国家气候中心,北京 100081
  • 出版日期:2022-03-30 发布日期:2021-12-24
  • 通讯作者: 杨舒楠
  • 作者简介:王毅,男,高级工程师, yiwang@cma.gov.cn
  • 基金资助:
    国家重点研发计划(2020YFE0201900);国家自然科学基金项目(41975100);国家重点研发计划(2017YFC1502004)

Comparative analysis and outlook of three global databases for meteorological disasters

WANG Yi1(), YANG Shu-Nan1(), ZHANG Li-Sheng1, Cao Yong1, YIN Yi-Zhou2   

  1. 1 National Meteorological Center, China Meteorological Administration, Beijing 100081, China
    2 National Climate Center, China Meteorological Administration, Beijing 100081, China
  • Online:2022-03-30 Published:2021-12-24
  • Contact: YANG Shu-Nan

摘要:

针对气象相关灾害,对3个主要全球灾害数据库进行了概述,包括比利时鲁汶大学国家灾害流行病研究中心的紧急灾害数据库(EM-DAT)、德国慕尼黑再保险公司的自然灾害数据库(NatCat)和瑞士再保险公司的数据库(Sigma),比较了各灾害数据库在建设目的、收录标准及灾害种类划分上的差异。EM-DAT由于能够访问下载,在国际上应用最广泛。NatCat和Sigma在灾害经济损失评估方面更具优势。全球灾害数据库对早期历史灾害事件及欠发达地区的灾害事件收录存在一定的偏差,对一些小型灾害反映不足。未来需要进一步提升灾害数据的可靠性和精细度,完善灾害数据库的标准规范,加强多种灾害数据库的交叉校验,为研究气候变化及人类活动与气象灾害之间的联系奠定扎实的数据基础。

关键词: 气象灾害, 全球数据库, 灾害损失, 极端天气

Abstract:

This paper reviews three global disaster databases focused on meteorological disasters including Emergency Events Database (EM-DAT) of Belgium, NatCat of Munich Re (NatCat) and Sigma of Swiss Re (Sigma). The differences in purposes, criteria and classification of disaster types across global databases are compared. EM-DAT is mostly used globally due to its free accessibility while NatCat and Sigma are more advantageous on economic loss assessment. The global disaster databases have some bias in the collection of early historical disasters and disasters in undeveloped areas as well as ignoring some small-scale disasters. In the future, it is necessary to further improve the reliability and fineness of disaster data, the standards and specifications of databases, and strengthen the cross-checking of multiple disaster databases in order to lay a solid foundation of data for studying the links between climate change, human activities and meteorological disasters.

Key words: Meteorological disasters, Global database, Disaster loss, Extreme weather

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