Articles | Volume 30, issue 1
https://doi.org/10.5194/npg-30-85-2023
https://doi.org/10.5194/npg-30-85-2023
Research article
 | 
08 Mar 2023
Research article |  | 08 Mar 2023

Rain process models and convergence to point processes

Scott Hottovy and Samuel N. Stechmann

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-865', Anonymous Referee #1, 20 Oct 2022
  • RC2: 'Comment on egusphere-2022-865', Anonymous Referee #2, 21 Oct 2022
  • RC3: 'Comment on egusphere-2022-865', Anonymous Referee #3, 31 Oct 2022
  • AC1: 'Author Comments on egusphere-2022-865', Scott Hottovy, 30 Dec 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Scott Hottovy on behalf of the Authors (30 Dec 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Jan 2023) by Balasubramanya Nadiga
RR by Anonymous Referee #2 (06 Feb 2023)
ED: Publish as is (14 Feb 2023) by Balasubramanya Nadiga
AR by Scott Hottovy on behalf of the Authors (16 Feb 2023)
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Short summary
Rainfall is erratic and difficult to predict. Thus, random models are often used to describe rainfall events. Since many of these random models are based more on statistics than physical laws, it is desirable to develop connections between the random statistical models and the underlying physics of rain. Here, a physics-based model is shown to converge to a statistics-based model, which helps to provide a physical basis for the statistics-based model.