Articles | Volume 18, issue 11
https://doi.org/10.5194/gmd-18-3211-2025
https://doi.org/10.5194/gmd-18-3211-2025
Methods for assessment of models
 | 
02 Jun 2025
Methods for assessment of models |  | 02 Jun 2025

Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study

Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on egusphere-2024-568 - No Compliance with GMD's policy', Juan Antonio Añel, 12 May 2024
    • CC1: 'Reply on CEC1', Maurin Zouzoua, 21 May 2024
    • AC1: 'Reply on CEC1', Maurin Zouzoua, 24 May 2024
  • RC1: 'Comment on egusphere-2024-568', Anonymous Referee #1, 20 Jun 2024
    • AC2: 'Reply on RC1', Maurin Zouzoua, 30 Sep 2024
  • RC2: 'Comment on egusphere-2024-568', Anonymous Referee #2, 01 Aug 2024
    • AC3: 'Reply on RC2', Maurin Zouzoua, 30 Sep 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Maurin Zouzoua on behalf of the Authors (30 Sep 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (22 Oct 2024) by Nathaniel Chaney
RR by Anonymous Referee #2 (28 Oct 2024)
ED: Publish as is (30 Jan 2025) by Nathaniel Chaney
AR by Maurin Zouzoua on behalf of the Authors (11 Feb 2025)  Author's response   Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Maurin Zouzoua on behalf of the Authors (05 May 2025)   Author's adjustment   Manuscript
EA: Adjustments approved (22 May 2025) by Nathaniel Chaney
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Short summary
This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
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