Ocean Science
Ocean Science
OS
Articles | Volume 20, issue 6
Articles | Volume 20, issue 6
https://doi.org/10.5194/os-20-1513-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-20-1513-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 6
Research article
 | 
25 Nov 2024
Research article |  | 25 Nov 2024

Assessing storm surge model performance: what error indicators can measure the model's skill?

Rodrigo Campos-Caba, Jacopo Alessandri, Paula Camus, Andrea Mazzino, Francesco Ferrari, Ivan Federico, Michalis Vousdoukas, Massimo Tondello, and Lorenzo Mentaschi

Viewed

Total article views: 1,384 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
952 260 172 1,384 36 63 89
  • HTML: 952
  • PDF: 260
  • XML: 172
  • Total: 1,384
  • Supplement: 36
  • BibTeX: 63
  • EndNote: 89
Views and downloads (calculated since 22 May 2024)
Cumulative views and downloads (calculated since 22 May 2024)

Viewed (geographical distribution)

Total article views: 1,384 (including HTML, PDF, and XML) Thereof 1,384 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 08 Oct 2025
Download
Short summary
Here we show the development of high-resolution simulations of storm surge in the northern Adriatic Sea employing different atmospheric forcing data and physical configurations. Traditional metrics favor a simulation forced by a coarser database and employing a less sophisticated setup. Closer examination allows us to identify a baroclinic model forced by a high-resolution dataset as being better able to capture the variability and peak values of the storm surge.
Read more
Share
Special issue
Extremes in the marine environment: analysis of multi-temporal...