气候变化领域集成服务门户(CCPortal): Spatial radiative feedbacks from internal variability using multiple regression

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DOI	10.1175/JCLI-D-19-0396.1
	Spatial radiative feedbacks from internal variability using multiple regression
	Bloch-Johnson J.; Rugenstein M.; Abbot D.S.
发表日期	2020
ISSN	0894-8755
起始页码	4121
结束页码	4140
卷号	33 期号:10
英文摘要	The sensitivity of the climate to CO2 forcing depends on spatially varying radiative feedbacks that act both locally and nonlocally. We assess whether a method employing multiple regression can be used to estimate local and nonlocal radiative feedbacks from internal variability. We test this method on millennial-length simulations performed with six coupled atmosphere-ocean general circulation models (AOGCMs). Given the spatial pattern of warming, the method does quite well at recreating the top-of-atmosphere flux response for most regions of Earth, except over the Southern Ocean where it consistently overestimates the change, leading to an overestimate of the sensitivity. For five of the six models, the method finds that local feedbacks are positive due to cloud processes, balanced by negative nonlocal shortwave cloud feedbacks associated with regions of tropical convection. For four of these models, the magnitudes of both are comparable to the Planck feedback, so that changes in the ratio between them could lead to large changes in climate sensitivity. The positive local feedback explains why observational studies that estimate spatial feedbacks using only local regressions predict an unstable climate. The method implies that sensitivity in these AOGCMs increases over time due to a reduction in the share of warming occurring in tropical convecting regions and the resulting weakening of associated shortwave cloud and longwave clear-sky feedbacks. Our results provide a step toward an observational estimate of time-varying climate sensitivity by demonstrating that many aspects of spatial feedbacks appear to be the same between internal variability and the forced response. © 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
英文关键词	Earth atmosphere; Tropics; Climate sensitivity; Coupled atmosphere ocean general circulation model; Internal variability; Local regression; Multiple regressions; Observational study; Top of atmospheres; Tropical convection; Climate models; atmospheric general circulation model; carbon dioxide; climate change; climate feedback; cloud radiative forcing; longwave radiation; multiple regression; oceanic general circulation model; shortwave radiation; warming; Southern Ocean
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/171326
作者单位	NCAS-Climate, University of Reading, Reading, United Kingdom; Max Planck Institute for Meteorology, Hamburg, Germany; Department of the Geophysical Sciences, University of Chicago, Chicago, IL, United States
推荐引用方式 GB/T 7714	Bloch-Johnson J.,Rugenstein M.,Abbot D.S.. Spatial radiative feedbacks from internal variability using multiple regression[J],2020,33(10).
APA	Bloch-Johnson J.,Rugenstein M.,&Abbot D.S..(2020).Spatial radiative feedbacks from internal variability using multiple regression.Journal of Climate,33(10).
MLA	Bloch-Johnson J.,et al."Spatial radiative feedbacks from internal variability using multiple regression".Journal of Climate 33.10(2020).