Articles | Volume 24, issue 1
https://doi.org/10.5194/acp-24-109-2024
https://doi.org/10.5194/acp-24-109-2024
Research article
 | Highlight paper
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05 Jan 2024
Research article | Highlight paper |  | 05 Jan 2024

Climatologically invariant scale invariance seen in distributions of cloud horizontal sizes

Thomas D. DeWitt, Timothy J. Garrett, Karlie N. Rees, Corey Bois, Steven K. Krueger, and Nicolas Ferlay

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-943', Simon R. Proud, 14 Jun 2023
    • AC2: 'Reply on CC1', Thomas DeWitt, 22 Sep 2023
  • RC1: 'Comment on egusphere-2023-943', Anonymous Referee #1, 07 Jul 2023
  • RC2: 'Comment on egusphere-2023-943', Anonymous Referee #2, 12 Aug 2023
  • AC1: 'Responses and changes to reviewer comments', Thomas DeWitt, 22 Sep 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Thomas DeWitt on behalf of the Authors (22 Sep 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (29 Sep 2023) by Corinna Hoose
RR by Anonymous Referee #1 (13 Oct 2023)
ED: Publish as is (19 Oct 2023) by Corinna Hoose
AR by Thomas DeWitt on behalf of the Authors (31 Oct 2023)  Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Thomas DeWitt on behalf of the Authors (19 Dec 2023)   Author's adjustment   Manuscript
EA: Adjustments approved (20 Dec 2023) by Corinna Hoose
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Executive editor
The field of climate prediction has been bedeviled by the problem of how to represent the enormous complexity of clouds. The usual strategy is to peform deterministic simulations with advanced cloud models. The study outlined here concentrates on a statistical approach that is arguably better suited to determining the mean climatological state. The presented observations from a wide range of satellite platforms show that a power-law well describes frequencies of occurence of cloud sizes across a very wide range of scales, and that the exponent is robust to local climatological characteristics as surface temperature, aerosol loading, Coriolis forces, or dominant cloud type. Instead, the distribution of cloud sizes emerge simply from a competition for energy and air that occurs due to small-scale cloud mixing processes at cloud edge.
Short summary
Viewed from space, a defining feature of Earth's atmosphere is the wide spectrum of cloud sizes. A recent study predicted the distribution of cloud sizes, and this paper compares the prediction to observations. Although there is nuance in viewing perspective, we find robust agreement with theory across different climatological conditions, including land–ocean contrasts, time of year, or latitude, suggesting a minor role for Coriolis forces, aerosol loading, or surface temperature.
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