globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2017MS001096
Scopus记录号: 2-s2.0-85029445530
论文题名:
Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green's function approach
作者: Zhou C; , Zelinka M; D; , Klein S; A
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2017
卷: 9, 期:5
起始页码: 2174
结束页码: 2189
语种: 英语
英文关键词: Atmospheric temperature ; Oceanography ; Submarine geophysics ; Surface properties ; Surface waters ; Tropics ; Cloud feedbacks ; Green's function approaches ; Interannual variation ; Sea surface temperature (SST) ; Sea-surface temperature change ; Spatial patterns ; Temperature changes ; Tropospheric temperature ; Green computing ; annual variation ; atmospheric general circulation model ; climate feedback ; cloud cover ; extratropical environment ; global change ; global warming ; Green function ; sea surface temperature ; spatial analysis ; temperature anomaly ; tropical environment ; troposphere
英文摘要: The spatial pattern of sea surface temperature (SST) changes has a large impact on the magnitude of cloud feedback. In this study, we seek a basic understanding of the dependence of cloud feedback on the spatial pattern of warming. Idealized experiments are carried out with an AGCM to calculate the change in global mean cloud-induced radiation anomalies (ΔRcloud) in response to imposed surface warming/cooling in 74 individual localized oceanic “patches”. Then the cloud feedback in response to a specific warming pattern can be approximated as the superposition of global cloud feedback in response to a temperature change in each region, weighted by the magnitude of the local temperature changes. When there is a warming in the tropical subsidence or extratropical regions, the local decrease of LCC results in a positive change in Rcloud. Conversely, warming in tropical ascent regions increases the free-tropospheric temperature throughout the tropics, thereby enhancing the inversion strength over remote regions and inducing positive global low-cloud cover (LCC) anomalies and negative Rcloud anomalies. The Green's function approach performs reasonably well in predicting the response of global mean ΔLCC and net ΔRcloud, but poorly for shortwave and longwave components of ΔRcloud due to its ineffectiveness in predicting middle and high cloud cover changes. The approach successfully captures the change of cloud feedback in response to time-evolving CO2-induced warming and captures the interannual variations in ΔRcloud observed by CERES. The results highlight important nonlocal influences of SST changes on cloud feedback. © 2017. The Authors.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75730
Appears in Collections:影响、适应和脆弱性
气候变化与战略

Files in This Item:

There are no files associated with this item.


作者单位: Lawrence Livermore National Laboratory, Livermore, CA, United States

Recommended Citation:
Zhou C,, Zelinka M,D,et al. Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green's function approach[J]. Journal of Advances in Modeling Earth Systems,2017-01-01,9(5)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Zhou C]'s Articles
[, Zelinka M]'s Articles
[D]'s Articles
百度学术
Similar articles in Baidu Scholar
[Zhou C]'s Articles
[, Zelinka M]'s Articles
[D]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Zhou C]‘s Articles
[, Zelinka M]‘s Articles
[D]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.