A new statistical approach to improve the satellite-based estimation of the radiative forcing by aerosol–cloud interactions

Patel, Piyushkumar N.; Quaas, Johannes; Kumar, Raj

doi:https://doi.org/10.5194/acp-17-3687-2017

Articles | Volume 17, issue 5

https://doi.org/10.5194/acp-17-3687-2017

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

https://doi.org/10.5194/acp-17-3687-2017

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

Articles | Volume 17, issue 5

Research article

|

16 Mar 2017

Research article |

| 16 Mar 2017

A new statistical approach to improve the satellite-based estimation of the radiative forcing by aerosol–cloud interactions

Piyushkumar N. Patel, Johannes Quaas, and Raj Kumar

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Final revised paper (published on 16 Mar 2017)
Supplement to the final revised paper
Preprint (discussion started on 07 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

RC1: 'Reviewer comments:acp-2016-680', Anonymous Referee #1, 22 Sep 2016
- AC1: 'Response to the Anonymous Referee 1's Comments', Piyush Patel, 02 Feb 2017
RC2: 'Review of ``A new statistical approach to improve the satellite based estimation of the radiative forcing by aerosol-cloud interactions''', Anonymous Referee #3, 29 Nov 2016
- AC2: 'Response to the Anonymous Referee 3's Comments', Piyush Patel, 02 Feb 2017

Peer-review completion

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

AR by Piyush Patel on behalf of the Authors (13 Feb 2017) Author's response Manuscript

ED: Publish as is (13 Feb 2017) by Armin Sorooshian

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Short summary

Radiative forcing by aerosol–cloud interactions (RF_aci) remains highly uncertain and difficult to quantify on the basis of current knowledge. The present study reassesses the estimated RF_aci by using a new statistical fitting approach, which improves the quantification of RF_aci with less uncertainty. The present work helps to improve the parameterisation of RF_aci in the present climate model.