Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 23
Articles | Volume 16, issue 23
https://doi.org/10.5194/gmd-16-7143-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-7143-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 23
Model evaluation paper
 | 
08 Dec 2023
Model evaluation paper |  | 08 Dec 2023

An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields

Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm

Viewed

Total article views: 1,546 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,049 445 52 1,546 37 33
  • HTML: 1,049
  • PDF: 445
  • XML: 52
  • Total: 1,546
  • BibTeX: 37
  • EndNote: 33
Views and downloads (calculated since 15 Mar 2023)
Cumulative views and downloads (calculated since 15 Mar 2023)

Viewed (geographical distribution)

Total article views: 1,546 (including HTML, PDF, and XML) Thereof 1,493 with geography defined and 53 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 09 May 2024
Download
Short summary
This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.
Read more