Ocean Science
Ocean Science
OS
Articles | Volume 21, issue 4
Articles | Volume 21, issue 4
https://doi.org/10.5194/os-21-1315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-21-1315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 4
Research article
 | 
14 Jul 2025
Research article |  | 14 Jul 2025

Application of the HIDRA2 deep-learning model for sea level forecasting along the Estonian coast of the Baltic Sea

Amirhossein Barzandeh, Matjaž Ličer, Marko Rus, Matej Kristan, Ilja Maljutenko, Jüri Elken, Priidik Lagemaa, and Rivo Uiboupin

Viewed

Total article views: 1,079 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
915 114 50 1,079 14 67 92
  • HTML: 915
  • PDF: 114
  • XML: 50
  • Total: 1,079
  • Supplement: 14
  • BibTeX: 67
  • EndNote: 92
Views and downloads (calculated since 29 Nov 2024)
Cumulative views and downloads (calculated since 29 Nov 2024)

Viewed (geographical distribution)

Total article views: 1,079 (including HTML, PDF, and XML) Thereof 1,073 with geography defined and 6 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 03 Oct 2025
Download
Short summary
We evaluated a deep-learning model, HIDRA2, for predicting sea levels along the Estonian coast and compared it to traditional numerical models. HIDRA2 performed better overall, offering faster forecasts and valuable uncertainty estimates using ensemble predictions.
Read more
Share
Special issue
Special issue on ocean extremes (55th International Liége...