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	Extreme hot summers in China in the CMIP5 climate models
	Leng G. Y.; Tang, Q. H.; Huang, S. Z.; Zhang, X. J.
	2016
关键词	2 degrees-c precipitation extremes temperature extremes human health heat impact risk simulations variability projections
英文摘要	Given the severe impacts of hot summers on human and natural systems, we attempt to quantify future changes in extreme hot summer frequency in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) projections. Unlike previous studies focusing on fixed future time slices, we investigate the changes as a function of global mean temperature (GMT) rise. Analyses show that extreme hot summers (June-July-August mean temperature higher than 90% quantile of 1971-2000 climatology) are projected to occur at least 80% of the time across China with a GMT rise of 2 degrees C. The fraction of land area with extreme hot summers becoming the norm (median of future summer temperatures exceed the extreme) will increase from similar to 15 % with 0.5 degrees C of GMT rise to similar to 97 % with 2.5 degrees C GMT rise, which is much greater than for the global land surface as a whole. A distinct spatial pattern of the GMT rise threshold over which the local extreme hot summer first becomes the norm is revealed. When averaged over the country, the GMT rise threshold is 0.96 degrees C. Earth system models exhibit comparable results to climate system models, but with a relatively larger spread. Further analysis shows that the concurrence of hot and dry summers will increase significantly with the spatial structure of responses depending on the definition of drying. The increase of concurrent hot and dry conditions will induce potential droughts which would be more severe than those induced by only precipitation deficits.
出处	Climatic Change
卷	135
期	3-4
页	669-681
语种	英语
ISSN号	0165-0009
DOI标识	10.1007/s10584-015-1576-y
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/43024]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Leng G. Y.,Tang, Q. H.,Huang, S. Z.,et al. Extreme hot summers in China in the CMIP5 climate models. 2016.

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