台风海燕的气候变化归因与帝国学院风暴模式

IF 2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Nathan Sparks, Ralf Toumi
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引用次数: 0

摘要

迄今为止,很难模拟气候变化下热带气旋发生可能性的变化。我们首次应用帝国理工学院风暴模型生成的随机热带气旋事件集,将气候变化的贡献归因于2013年的台风海燕。与工业化前的基线相比,我们估计像海燕这样登陆最大风速的台风要大+3.5米/秒。这与以前的全物理数值模型估计很一致。海燕类型事件的当前重现期为850年,气候变化的部分归因风险为98%。如果没有气候变化,这一事件不太可能发生。从IRIS模型中获得的信息类型可以在损失和损害基金的背景下为巨灾债券收益率的补贴提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Climate change attribution of Typhoon Haiyan with the Imperial College Storm Model

Climate change attribution of Typhoon Haiyan with the Imperial College Storm Model

It is difficult to model changes in the likelihood of tropical cyclones under climate change to date. We do this, for the first time, by a applying a stochastic tropical cyclone event set generated by the Imperial College Storm Model to attribute the contribution of climate change to the case of Typhoon Haiyan in 2013. Compared to a pre-industrial baseline, we estimate that a typhoon with a landfall maximum wind speed like Haiyan was larger by +3.5 m/s. This is in good agreement with previous full physics numerical model estimates. A Haiyan type of event has a current return period of 850 years, and the fractional attributable risk due to climate change is 98%. Without climate change, this event was very unlikely. The type of information available from the IRIS model could inform subsidizing of catastrophe bond yield in the context of the loss and damage fund.

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来源期刊
Atmospheric Science Letters
Atmospheric Science Letters METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
4.90
自引率
3.30%
发文量
73
审稿时长
>12 weeks
期刊介绍: Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques. We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.
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