Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 11
Articles | Volume 18, issue 11
https://doi.org/10.5194/gmd-18-3211-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3211-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 11
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

Viewed

Total article views: 970 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
502 259 209 970 51 41
  • HTML: 502
  • PDF: 259
  • XML: 209
  • Total: 970
  • BibTeX: 51
  • EndNote: 41
Views and downloads (calculated since 22 Apr 2024)
Cumulative views and downloads (calculated since 22 Apr 2024)

Viewed (geographical distribution)

Total article views: 970 (including HTML, PDF, and XML) Thereof 951 with geography defined and 19 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 06 Jun 2025
Download
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.
Read more
Share