Articles | Volume 13, issue 9
Geosci. Model Dev., 13, 4107–4157, 2020
https://doi.org/10.5194/gmd-13-4107-2020

Special issue: Particle-based methods for simulating atmospheric aerosol...

Geosci. Model Dev., 13, 4107–4157, 2020
https://doi.org/10.5194/gmd-13-4107-2020

Development and technical paper 08 Sep 2020

Development and technical paper | 08 Sep 2020

Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2

Shin-ichiro Shima et al.

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Interactive discussion

Status: closed
Status: closed
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 Shin-ichiro Shima on behalf of the Authors (24 May 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (08 Jun 2020) by Simon Unterstrasser
RR by Anonymous Referee #1 (19 Jun 2020)
ED: Publish subject to minor revisions (review by editor) (04 Jul 2020) by Simon Unterstrasser
AR by Shin-ichiro Shima on behalf of the Authors (13 Jul 2020)  Author's response    Manuscript
ED: Publish as is (22 Jul 2020) by Simon Unterstrasser
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Short summary
Using the super-droplet method, we constructed a detailed numerical model of mixed-phase clouds based on kinetic description and subsequently demonstrated that a large-eddy simulation of a cumulonimbus which predicts ice particle morphology without assuming ice categories or mass–dimension relationships is possible. Our results strongly support the particle-based modeling methodology’s efficacy for simulating mixed-phase clouds.