A cloud feedback emulator (CFE, version 1.0) for an intermediate complexity model

Ullman, David J.; Schmittner, Andreas

doi:https://doi.org/10.5194/gmd-10-945-2017

Articles | Volume 10, issue 2

https://doi.org/10.5194/gmd-10-945-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-10-945-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 2

Development and technical paper

|

23 Feb 2017

Development and technical paper |

| 23 Feb 2017

A cloud feedback emulator (CFE, version 1.0) for an intermediate complexity model

David J. Ullman and Andreas Schmittner

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Final revised paper (published on 23 Feb 2017)
Supplement to the final revised paper
Preprint (discussion started on 26 Sep 2016)
Supplement to the preprint

Interactive discussion

Status: closed

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

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- Supplement

SC1: 'Executive Editor Comment on "The University of Victoria Cloud Feedback Emulator (UVic-CFE): cloud radiative feedbacks in an intermediate complexity model"', Astrid Kerkweg, 26 Sep 2016
- AC1: 'Updated Title', David Ullman, 17 Jan 2017
RC1: 'Review of “The University of Victoria Cloud Feedback Emulator (UVic-CFE): cloud radiative feedbacks in an intermediate complexity model”', Anonymous Referee #1, 11 Oct 2016
- AC2: 'Response to RC1', David Ullman, 18 Jan 2017
RC2: 'Options applied to UVic runs', Anonymous Referee #2, 14 Oct 2016
- AC3: 'Response to RC2', David Ullman, 18 Jan 2017
EC1: 'Editor comment', Klaus Gierens, 07 Nov 2016
- AC4: 'Response to EC1', David Ullman, 18 Jan 2017

Peer-review completion

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

AR by David Ullman on behalf of the Authors (18 Jan 2017)

ED: Publish subject to technical corrections (27 Jan 2017) by Klaus Gierens

AR by David Ullman on behalf of the Authors (02 Feb 2017) Manuscript

Short summary

One major source of uncertainty in the prediction of climate relates to how models simulate clouds and their impact on surface temperatures. We have developed a new method for incorporating the cloud results as derived from complex climate models and applying these results to a more simplified model. The benefit with this approach is that a more simplified model is able to be run more efficiently, while still maintaining complicated cloud effects and their effect on surface temperatures.