气候变化领域集成服务门户(CCPortal): Advanced risk-based event attribution for heavy regional rainfall events

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DOI	10.1038/s41612-020-00141-y
	Advanced risk-based event attribution for heavy regional rainfall events
	Imada Y.; Kawase H.; Watanabe M.; Arai M.; Shiogama H.; Takayabu I.
发表日期	2020
ISSN	23973722
卷号	3 期号:1
英文摘要	Risk-based event attribution (EA) science involves probabilistically estimating alterations of the likelihoods of particular weather events, such as heat waves and heavy rainfall, owing to global warming, and has been considered as an effective approach with regard to climate change adaptation. However, risk-based EA for heavy rain events remains challenging because, unlike extreme temperature events, which often have a scale of thousands of kilometres, heavy rainfall occurrences depend on mesoscale rainfall systems and regional geographies that cannot be resolved using general circulation models (GCMs) that are currently employed for risk-based EA. Herein, we use GCM large-ensemble simulations and high-resolution downscaled products with a 20-km non-hydrostatic regional climate model (RCM), whose boundary conditions are obtained from all available GCM ensemble simulations, to show that anthropogenic warming increased the risk of two record-breaking regional heavy rainfall events in 2017 and 2018 over western Japan. The events are examined from the perspective of rainfall statistics simulated by the RCM and from the perspective of background large-scale circulation fields simulated by the GCM. In the 2017 case, precipitous terrain and a static pressure pattern in the synoptic field helped reduce uncertainty in the dynamical components, whereas in the 2018 case, a static pressure pattern in the synoptic field provided favourable conditions for event occurrence through a moisture increase under warmer climate. These findings show that successful risk-based EA for regional extreme rainfall relies on the degree to which uncertainty induced by the dynamic components is reduced by background conditioning. © 2020, The Author(s).
语种	英语
scopus关键词	climate modeling; estimation method; extreme event; global warming; heat wave; precipitation intensity; regional climate; Japan
来源期刊	npj Climate and Atmospheric Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178028
作者单位	Meteorological Research Institute, Japan Meteorological Agency, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan; Atmosphere and Ocean Research Institute, the University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan; Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan; National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
推荐引用方式 GB/T 7714	Imada Y.,Kawase H.,Watanabe M.,et al. Advanced risk-based event attribution for heavy regional rainfall events[J],2020,3(1).
APA	Imada Y.,Kawase H.,Watanabe M.,Arai M.,Shiogama H.,&Takayabu I..(2020).Advanced risk-based event attribution for heavy regional rainfall events.npj Climate and Atmospheric Science,3(1).
MLA	Imada Y.,et al."Advanced risk-based event attribution for heavy regional rainfall events".npj Climate and Atmospheric Science 3.1(2020).