Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean

Santana-Falcón, Yeray; Brasseur, Pierre; Brankart, Jean Michel; Garnier, Florent

doi:https://doi.org/10.5194/os-16-1297-2020

Articles | Volume 16, issue 5

https://doi.org/10.5194/os-16-1297-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/os-16-1297-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 5

Research article

|

29 Oct 2020

Research article |

| 29 Oct 2020

Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean

Yeray Santana-Falcón, Pierre Brasseur, Jean Michel Brankart, and Florent Garnier

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Final revised paper (published on 29 Oct 2020)
Preprint (discussion started on 24 Feb 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of Santana-Falcón et al.', Anonymous Referee #1, 25 Mar 2020
- AC1: 'Response to Reviewer 1', Yeray Santana-Falcón, 28 May 2020
RC2: 'Review of "Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic Ocean"', Anonymous Referee #2, 23 Apr 2020
- AC2: 'Response to Reviewer 2', Yeray Santana-Falcón, 28 May 2020

Peer-review completion

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

AR by Anna Wenzel on behalf of the Authors (17 Jun 2020) Author's response

ED: Referee Nomination & Report Request started (07 Jul 2020) by Bernadette Sloyan

RR by Anonymous Referee #1 (21 Jul 2020)

ED: Publish subject to technical corrections (01 Sep 2020) by Bernadette Sloyan

AR by Yeray Santana-Falcón on behalf of the Authors (03 Sep 2020) Author's response Manuscript

Short summary

Data assimilation is the most comprehensive strategy to estimate the biogeochemical state of the ocean. Here, surface Chl a data are daily assimilated into a 24-member NEMO–PISCES ensemble configuration to implement a complete 4D assimilation system. Results show the assimilation increases the skills of the ensemble, though a regional diagnosis suggests that the description of model and observation uncertainties needs to be refined according to the biogeochemical characteristics of each region.