A protocol for probabilistic extreme event attribution analyses

Q1 Mathematics
S. Philip, S. Kew, G. J. van Oldenborgh, F. Otto, R. Vautard, Karin van der Wiel, A. King, F. Lott, J. Arrighi, Roop K. Singh, M. V. van Aalst
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引用次数: 109

Abstract

Abstract. Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service.
概率极端事件归因分析协议
摘要在过去的几年里,人们开发了一些方法来回答有关全球变暖对最近极端事件影响的问题。现在已经进行了许多“事件归因”研究,其中相当一部分甚至在事件发生后的几周内进行,以提高结果的有用性。在进行这些分析时,很明显,归因本身只是从观察极端事件到成功传达归因声明的扩展过程的一步。在这篇论文中,我们详细介绍了世界天气归因小组在过去4年中制定的协议,以及涵盖温暖、寒冷、潮湿、干燥和暴风雨极端情况的大约20多项快速和慢速归因研究。它从选择分析哪些事件开始,然后进行事件定义、观测分析、模型评估、多模型多方法归因、危害综合、脆弱性和暴露分析,最后进行沟通程序。本文记录了该协议。希望我们的协议将有助于设计未来的事件归因研究,并作为操作归因服务协议的起点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography Earth and Planetary Sciences-Atmospheric Science
CiteScore
4.80
自引率
0.00%
发文量
9
审稿时长
26 weeks
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