Articles | Volume 17, issue 15
Atmos. Chem. Phys., 17, 9535–9546, 2017
https://doi.org/10.5194/acp-17-9535-2017
Atmos. Chem. Phys., 17, 9535–9546, 2017
https://doi.org/10.5194/acp-17-9535-2017

Research article 08 Aug 2017

Research article | 08 Aug 2017

Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

Hendrik Andersen et al.

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Hendrik Andersen on behalf of the Authors (12 Jun 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (12 Jun 2017) by Barbara Ervens
RR by Anonymous Referee #1 (15 Jun 2017)
RR by Anonymous Referee #2 (19 Jun 2017)
ED: Reconsider after minor revisions (Editor review) (27 Jun 2017) by Barbara Ervens
AR by Hendrik Andersen on behalf of the Authors (06 Jul 2017)  Author's response    Manuscript
ED: Publish as is (10 Jul 2017) by Barbara Ervens
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Short summary
Aerosol-cloud interactions continue to contribute large uncertainties to our climate system understanding. In this study, we use near-global satellite and reanalysis data sets to predict marine liquid-water clouds by means of artificial neural networks. We show that on the system scale, lower-tropospheric stability and boundary layer height are the main determinants of liquid-water clouds. Aerosols show the expected impact on clouds but are less relevant than some meteorological factors.
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