Evaluating models' response of tropical low clouds to SST forcings using CALIPSO observations

Cesana, Grégory; Del Genio, Anthony D.; Ackerman, Andrew S.; Kelley, Maxwell; Elsaesser, Gregory; Fridlind, Ann M.; Cheng, Ye; Yao, Mao-Sung

doi:https://doi.org/10.5194/acp-19-2813-2019

Articles | Volume 19, issue 5

https://doi.org/10.5194/acp-19-2813-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-19-2813-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 5

Research article

|

04 Mar 2019

Research article |

| 04 Mar 2019

Evaluating models' response of tropical low clouds to SST forcings using CALIPSO observations

Grégory Cesana, Anthony D. Del Genio, Andrew S. Ackerman, Maxwell Kelley, Gregory Elsaesser, Ann M. Fridlind, Ye Cheng, and Mao-Sung Yao

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Final revised paper (published on 04 Mar 2019)
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Preprint (discussion started on 15 Nov 2018)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'review comments', Anonymous Referee #1, 13 Dec 2018
- AC1: 'Response to reviewer 1 comments', Gregory Cesana, 08 Jan 2019
RC2: 'Review of Cesana et. al.', Anonymous Referee #2, 27 Dec 2018
- AC2: 'Response to reviewer 2 comments', Gregory Cesana, 08 Jan 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Gregory Cesana on behalf of the Authors (14 Jan 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (15 Jan 2019) by Johannes Quaas

RR by Anonymous Referee #1 (16 Jan 2019)

ED: Publish as is (17 Jan 2019) by Johannes Quaas

AR by Gregory Cesana on behalf of the Authors (18 Jan 2019)

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Short summary

The response of low clouds to climate change (i.e., cloud feedbacks) is still pointed out as being the largest source of uncertainty in climate models. Here we use CALIPSO observations to discriminate climate models that reproduce observed interannual change of cloud fraction with SST forcings, referred to as a present-day cloud feedback. Modeling moist processes in the planetary boundary layer is crucial to produce large stratocumulus decks and realistic present-day cloud feedbacks.