Articles | Volume 21, issue 5
https://doi.org/10.5194/os-21-2579-2025
https://doi.org/10.5194/os-21-2579-2025
Research article
 | 
24 Oct 2025
Research article |  | 24 Oct 2025

On the global reconstruction of ocean interior variables: a feasibility data-driven study with simulated surface and water column observations

Aina Garcia-Espriu, Cristina González-Haro, and Fernando Aguilar-Gómez

Viewed

Total article views: 3,435 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,223 1,091 121 3,435 179 123
  • HTML: 2,223
  • PDF: 1,091
  • XML: 121
  • Total: 3,435
  • BibTeX: 179
  • EndNote: 123
Views and downloads (calculated since 24 Feb 2025)
Cumulative views and downloads (calculated since 24 Feb 2025)

Viewed (geographical distribution)

Total article views: 3,435 (including HTML, PDF, and XML) Thereof 3,338 with geography defined and 97 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 02 May 2026
Download
Short summary
Ocean measurements currently rely on buoys for depth data and satellites for surface observations. We investigated combining these using data-driven approaches to reconstruct full 4D ocean profiles. Using an ocean model as ground truth, we simulated satellite surface data and ARGO profiles and then applied machine learning to predict complete temperature and salinity profiles. Results showed accurate predictions that matched simulation data and captured seasonal patterns.
Share