Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green's function approach

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

doi:10.1002/2017MS001096

Title: Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green's function approach

Journal Article · Thu Sep 14 00:00:00 EDT 2017 · Journal of Advances in Modeling Earth Systems

DOI:https://doi.org/10.1002/2017MS001096· OSTI ID:1390341

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Lawrence Livermore National Laboratory, Livermore California USA

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 (ΔR_cloud) 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 R_cloud. 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 ΔR_cloud, but poorly for shortwave and longwave components of ΔR_cloud due to its ineffectiveness in predicting middle and high cloud cover changes. Finally, the approach successfully captures the change of cloud feedback in response to time-evolving CO₂-induced warming and captures the interannual variations in ΔR_cloud observed by CERES. The results highlight important nonlocal influences of SST changes on cloud feedback.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1390341

Alternate ID(s):: OSTI ID: 1390342; OSTI ID: 1463011

Report Number(s):: LLNL-JRNL-733335

Journal Information:: Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Vol. 9 Journal Issue: 5; ISSN 1942-2466

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 84 works

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Title: Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green's function approach

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