Ocean Science
Ocean Science
OS
Articles | Volume 20, issue 4
Articles | Volume 20, issue 4
https://doi.org/10.5194/os-20-1035-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-20-1035-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 4
Research article
 | 
28 Aug 2024
Research article |  | 28 Aug 2024

Deep learning for the super resolution of Mediterranean sea surface temperature fields

Claudia Fanelli, Daniele Ciani, Andrea Pisano, and Bruno Buongiorno Nardelli

Viewed

Total article views: 1,045 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
746 244 55 1,045 23 22
  • HTML: 746
  • PDF: 244
  • XML: 55
  • Total: 1,045
  • BibTeX: 23
  • EndNote: 22
Views and downloads (calculated since 20 Feb 2024)
Cumulative views and downloads (calculated since 20 Feb 2024)

Viewed (geographical distribution)

Total article views: 1,045 (including HTML, PDF, and XML) Thereof 1,052 with geography defined and -7 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 15 Nov 2024
Download
Short summary
Sea surface temperature (SST) is an essential variable to understanding the Earth's climate system, and its accurate monitoring from space is essential. Since satellite measurements are hindered by cloudy/rainy conditions, data gaps are present even in merged multi-sensor products. Since optimal interpolation techniques tend to smooth out small-scale features, we developed a deep learning model to enhance the effective resolution of gap-free SST images over the Mediterranean Sea to address this.
Read more
Special issue
Special Issue for the 54th International Liège Colloquium...