GSTDTAP  > 气候变化
DOI10.1007/s00382-017-3768-9
On the nonlinearity of spatial scales in extreme weather attribution statements
Angelil, Oliver1,2; Stone, Daithi3; Perkins-Kirkpatrick, Sarah1,2; Alexander, Lisa V.1,2; Wehner, Michael3; Shiogama, Hideo4; Wolski, Piotr5; Ciavarella, Andrew6; Christidis, Nikolaos6
2018-04-01
发表期刊CLIMATE DYNAMICS
ISSN0930-7575
EISSN1432-0894
出版年2018
卷号50页码:2739-2752
文章类型Article
语种英语
国家Australia; USA; Japan; South Africa; England
英文摘要

In the context of ongoing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event-some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.


英文关键词Attribution Extremes C20C+ AGCMs
领域气候变化
收录类别SCI-E
WOS记录号WOS:000428600200024
WOS关键词FUTURE CHANGES ; CLIMATE ; PRECIPITATION ; TEMPERATURE
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/35242
专题气候变化
作者单位1.UNSW Australia, Climate Change Res Ctr, Sydney, NSW 2052, Australia;
2.UNSW Australia, ARC Ctr Excellence Climate Syst Sci, Sydney, NSW 2052, Australia;
3.Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA;
4.Natl Inst Environm Studies, Tsukuba, Ibaraki 3058506, Japan;
5.Univ Cape Town, Climate Syst Anal Grp, Environm & Geog Sci, Rondebosch, South Africa;
6.Met Off Hadley Ctr, Exeter EX1 3PB, Devon, England
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Angelil, Oliver,Stone, Daithi,Perkins-Kirkpatrick, Sarah,et al. On the nonlinearity of spatial scales in extreme weather attribution statements[J]. CLIMATE DYNAMICS,2018,50:2739-2752.
APA Angelil, Oliver.,Stone, Daithi.,Perkins-Kirkpatrick, Sarah.,Alexander, Lisa V..,Wehner, Michael.,...&Christidis, Nikolaos.(2018).On the nonlinearity of spatial scales in extreme weather attribution statements.CLIMATE DYNAMICS,50,2739-2752.
MLA Angelil, Oliver,et al."On the nonlinearity of spatial scales in extreme weather attribution statements".CLIMATE DYNAMICS 50(2018):2739-2752.
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