Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation

Shutyaev, Victor; Le Dimet, Francois-Xavier; Parmuzin, Eugene

doi:https://doi.org/10.5194/npg-25-429-2018

Articles | Volume 25, issue 2

https://doi.org/10.5194/npg-25-429-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Numerical modeling, predictability and data assimilation in...

https://doi.org/10.5194/npg-25-429-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 2

Research article

|

21 Jun 2018

Research article |

| 21 Jun 2018

Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation

Victor Shutyaev, Francois-Xavier Le Dimet, and Eugene Parmuzin

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Final revised paper (published on 21 Jun 2018)
Preprint (discussion started on 07 Feb 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Referee report', Anonymous Referee #1, 08 Mar 2018
- AC1: 'Interactive comment', Victor Shutyaev, 11 Apr 2018
RC2: 'Comments to the authors', Anonymous Referee #2, 02 Apr 2018
- AC2: 'Interactive comment', Victor Shutyaev, 11 Apr 2018

Peer-review completion

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

AR by Victor Shutyaev on behalf of the Authors (18 Apr 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (20 Apr 2018) by Olivier Talagrand

RR by Anonymous Referee #2 (07 May 2018)

RR by Olivier Talagrand (14 May 2018)

ED: Publish subject to minor revisions (review by editor) (14 May 2018) by Olivier Talagrand

AR by Victor Shutyaev on behalf of the Authors (23 May 2018) Author's response Manuscript

ED: Publish as is (25 May 2018) by Olivier Talagrand

AR by Victor Shutyaev on behalf of the Authors (01 Jun 2018) Manuscript

Short summary

The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters of the model. The observation data, and hence the optimal solution, may contain uncertainties. A response function is considered as a functional of the optimal solution after assimilation. The sensitivity of the response function to the observation data is studied. The results are relevant for monitoring and prediction of sea and ocean states.