Articles | Volume 13, issue 6
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


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Mirena Feist-Polner on behalf of the Authors (28 Sep 2017)  Author's response
ED: Publish subject to technical corrections (09 Oct 2017) by Giovanni Quattrocchi
AR by Reiner Onken on behalf of the Authors (11 Oct 2017)  Author's response    Manuscript
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.