Articles | Volume 18, issue 5
https://doi.org/10.5194/gmd-18-1851-2025
https://doi.org/10.5194/gmd-18-1851-2025
Methods for assessment of models
 | 
18 Mar 2025
Methods for assessment of models |  | 18 Mar 2025

Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall

Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini

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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 gmd-2024-99', Kun Zheng, 04 Oct 2024
  • RC2: 'Comment on gmd-2024-99', Anonymous Referee #2, 11 Oct 2024
  • AC1: 'Review reply on gmd-2024-99', Jenna Ritvanen, 27 Nov 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jenna Ritvanen on behalf of the Authors (27 Nov 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (29 Nov 2024) by Charles Onyutha
RR by Anonymous Referee #1 (15 Dec 2024)
ED: Publish subject to minor revisions (review by editor) (30 Dec 2024) by Charles Onyutha
AR by Jenna Ritvanen on behalf of the Authors (16 Jan 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (17 Jan 2025) by Charles Onyutha
AR by Jenna Ritvanen on behalf of the Authors (22 Jan 2025)  Manuscript 
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Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
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