Articles | Volume 17, issue 2
https://doi.org/10.5194/gmd-17-759-2024
https://doi.org/10.5194/gmd-17-759-2024
Model evaluation paper
 | 
30 Jan 2024
Model evaluation paper |  | 30 Jan 2024

Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1

Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Piotr Zmijewski on behalf of the Authors (04 Sep 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Sep 2023) by Simon Unterstrasser
RR by Anonymous Referee #1 (22 Sep 2023)
RR by Anonymous Referee #2 (26 Sep 2023)
ED: Reconsider after major revisions (26 Sep 2023) by Simon Unterstrasser
AR by Piotr Zmijewski on behalf of the Authors (08 Nov 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Nov 2023) by Simon Unterstrasser
RR by Anonymous Referee #2 (24 Nov 2023)
ED: Publish subject to technical corrections (03 Dec 2023) by Simon Unterstrasser
AR by Piotr Zmijewski on behalf of the Authors (08 Dec 2023)  Author's response   Manuscript 
Download
Short summary
In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.