Articles | Volume 13, issue 6
https://doi.org/10.5194/os-13-925-2017
https://doi.org/10.5194/os-13-925-2017
Research article
 | 
20 Nov 2017
Research article |  | 20 Nov 2017

Forecast skill score assessment of a relocatable ocean prediction system, using a simplified objective analysis method

Reiner Onken

Viewed

Total article views: 3,378 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,858 1,337 183 3,378 200 249
  • HTML: 1,858
  • PDF: 1,337
  • XML: 183
  • Total: 3,378
  • BibTeX: 200
  • EndNote: 249
Views and downloads (calculated since 23 May 2017)
Cumulative views and downloads (calculated since 23 May 2017)

Viewed (geographical distribution)

Total article views: 3,378 (including HTML, PDF, and XML) Thereof 3,175 with geography defined and 203 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 17 Jun 2026
Download
Short summary
An ocean prediction model was driven by observations via assimilation. The best forecast was obtained using a smoothing scale of 12.5 km and a time window of 24 h for data selection. Mostly, the forecasts were better than that of a run without assimilation, the skill score increased with increasing forecast range, and the score for temperature was higher than the score for salinity. It is shown that a vast number of data can be managed by the applied method without data reduction.
Share