A generic approach to explicit simulation of uncertainty in the NEMO ocean model

Brankart, J.-M.; Candille, G.; Garnier, F.; Calone, C.; Melet, A.; Bouttier, P.-A.; Brasseur, P.; Verron, J.

doi:https://doi.org/10.5194/gmd-8-1285-2015

Articles | Volume 8, issue 5

https://doi.org/10.5194/gmd-8-1285-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Nucleus for European Modelling of the Ocean - NEMO

https://doi.org/10.5194/gmd-8-1285-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 8, issue 5

Model description paper

|

04 May 2015

Model description paper |

| 04 May 2015

A generic approach to explicit simulation of uncertainty in the NEMO ocean model

J.-M. Brankart, G. Candille, F. Garnier, C. Calone, A. Melet, P.-A. Bouttier, P. Brasseur, and J. Verron

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Final revised paper (published on 04 May 2015)
Preprint (discussion started on 27 Jan 2015)

Interactive discussion

Status: closed

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

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RC C27: 'Review', Anonymous Referee #1, 09 Feb 2015
- AC C239: 'Answers to reviewer \#1', Jean-Michel BRANKART, 26 Mar 2015
RC C82: 'Review of Brankart et al.', Anonymous Referee #2, 27 Feb 2015
- AC C245: 'Answers to reviewer \#2', Jean-Michel BRANKART, 26 Mar 2015

Peer-review completion

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

AR by Jean-Michel Brankart on behalf of the Authors (27 Mar 2015) Author's response

ED: Publish subject to minor revisions (Editor review) (09 Apr 2015) by Sophie Valcke

AR by Jean-Michel Brankart on behalf of the Authors (13 Apr 2015) Manuscript

ED: Publish as is (16 Apr 2015) by Sophie Valcke

AR by Jean-Michel Brankart on behalf of the Authors (16 Apr 2015)

Short summary

In this paper, a simple and generic implementation approach is presented, with the aim of transforming a deterministic ocean model (like NEMO) into a probabilistic model. With this approach, several kinds of stochastic parameterizations are implemented to simulate the non-deterministic effect of unresolved processes, unresolved scales, and unresolved diversity. The method is illustrated with three applications, showing that uncertainties can produce a major effect in the model simulations.