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DOI	10.1175/JCLI-D-19-1017.1
	Attribution of extreme precipitation with updated observations and CMIP6 simulations
	Dong S.; Sun Y.; Li C.; Zhang X.; Min S.-K.; Kim Y.-H.
发表日期	2021
ISSN	0894-8755
起始页码	871
结束页码	881
卷号	34 期号:3
英文摘要	While the IPCC Fifth Assessment Working Group I report assessed observed changes in extreme precipitation on the basis of both absolute and percentile-based extreme indices, human influence on extreme precipitation has rarely been evaluated on the basis of percentile-based extreme indices. Here we conduct a formal detection and attribution analysis on changes in four percentile-based precipitation extreme indices. The indices include annual precipitation totals from days with precipitation exceeding the 99th and 95th percentiles of wet-day precipitation in 1961-90 (R99p and R95p) and their contributions to annual total precipitation (R99pTOT and R95pTOT). We compare these indices from a set of newly compiled observations during 1951-2014 with simulations from models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). We show that most land areas with observations experienced increases in these extreme indices with global warming during the historical period 1951-2014. The new CMIP6 models are able to reproduce these overall increases, although with considerable over- or underestimations in some regions. An optimal fingerprinting analysis reveals detectable anthropogenic signals in the observations of these indices averaged over the globe and over most continents. Furthermore, signals of greenhouse gases can be separately detected, taking other forcing into account, over the globe and over Asia in these indices except for R95p. In contrast, signals of anthropogenic aerosols and natural forcings cannot be detected in any of these indices at either global or continental scales. © 2020 American Meteorological Society
英文关键词	Global warming; Greenhouse gases; Annual precipitation; Anthropogenic aerosols; Anthropogenic signals; Coupled Model Intercomparison Project; Detection and attributions; Extreme precipitation; Optimal fingerprinting; Precipitation extremes; Precipitation (meteorology)
语种	英语
来源期刊	Journal of Climate
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/170935
作者单位	National Climate Center, Laboratory for Climate Studies, China Meteorological Administration, Beijing, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory of Geographic Information Science, Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, China; Climate Research Division, Environment and Climate Change Canada, Toronto, ON, Canada; Division of Environmental Science and Engineering, Pohang University of Science and Technology, Pohang, South Korea
推荐引用方式 GB/T 7714	Dong S.,Sun Y.,Li C.,et al. Attribution of extreme precipitation with updated observations and CMIP6 simulations[J],2021,34(3).
APA	Dong S.,Sun Y.,Li C.,Zhang X.,Min S.-K.,&Kim Y.-H..(2021).Attribution of extreme precipitation with updated observations and CMIP6 simulations.Journal of Climate,34(3).
MLA	Dong S.,et al."Attribution of extreme precipitation with updated observations and CMIP6 simulations".Journal of Climate 34.3(2021).