An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

Rothenberg, Daniel; Wang, Chien

doi:https://doi.org/10.5194/gmd-10-1817-2017

Articles | Volume 10, issue 4

https://doi.org/10.5194/gmd-10-1817-2017

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

https://doi.org/10.5194/gmd-10-1817-2017

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

Articles | Volume 10, issue 4

Development and technical paper

|

27 Apr 2017

Development and technical paper |

| 27 Apr 2017

An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

Daniel Rothenberg and Chien Wang

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Final revised paper (published on 27 Apr 2017)
Supplement to the final revised paper
Preprint (discussion started on 28 Oct 2016)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of manuscript “An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: Development and offline assessment for use in an aerosol-climate model” by Daniel Rothenberg and Chien Wang', Anonymous Referee #1, 29 Nov 2016
RC2: 'Review', Anonymous Referee #2, 20 Dec 2016
RC3: 'Review of manuscript by Rothenberg and Wang', Anonymous Referee #3, 21 Dec 2016
AC1: 'Response to Reviews and Comments', Daniel Rothenberg, 03 Feb 2017

Peer-review completion

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

AR by Daniel Rothenberg on behalf of the Authors (15 Feb 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (02 Mar 2017) by Graham Mann

RR by Anonymous Referee #2 (08 Mar 2017)

RR by Anonymous Referee #3 (25 Mar 2017)

ED: Publish subject to technical corrections (26 Mar 2017) by Graham Mann

Short summary

Climate models include descriptions of how cloud droplets form from particles in the atmosphere. We have developed an efficient parameterization of this process by building an emulator of a detailed model, which can accurately predict cloud droplet number concentrations and potentially include additional physics and chemistry. We further show that using different parameterizations could influence droplet number estimates in global models and their aerosol indirect effect on climate.