Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO

Daewel, Ute; Schrum, Corinna

doi:https://doi.org/10.5194/esd-8-801-2017

Articles | Volume 8, issue 3

https://doi.org/10.5194/esd-8-801-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Multiple drivers for Earth system changes in the Baltic Sea...

https://doi.org/10.5194/esd-8-801-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 8, issue 3

Research article

|

07 Sep 2017

Research article |

| 07 Sep 2017

Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO

Ute Daewel and Corinna Schrum

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Final revised paper (published on 07 Sep 2017)
Preprint (discussion started on 13 Apr 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review', Anonymous Referee #1, 08 May 2017
- AC1: 'Reply to Review #1', Ute Daewel, 09 Jun 2017
RC2: 'Review: Daewel and Schrum, Low frequency variability in North Sea and Baltic Sea identified through simulations with the 3-d coupled physical-biogeochemical model ECOSMO', Anonymous Referee #2, 09 May 2017
- AC2: 'Reply to Review #2', Ute Daewel, 09 Jun 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (review by Editor) (24 Jun 2017) by Markus Meier

AR by Ute Daewel on behalf of the Authors (03 Jul 2017) Author's response Manuscript

ED: Publish as is (20 Jul 2017) by Markus Meier

Short summary

Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.