Ocean Science
Ocean Science
OS
Articles | Volume 13, issue 6
Articles | Volume 13, issue 6
https://doi.org/10.5194/os-13-925-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/os-13-925-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
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

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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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
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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.
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