An offline framework for high-dimensional ensemble Kalman filters to reduce the time to solution

Zheng, Yongjun; Albergel, Clément; Munier, Simon; Bonan, Bertrand; Calvet, Jean-Christophe

doi:https://doi.org/10.5194/gmd-13-3607-2020

Articles | Volume 13, issue 8

https://doi.org/10.5194/gmd-13-3607-2020

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

https://doi.org/10.5194/gmd-13-3607-2020

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

Articles | Volume 13, issue 8

Development and technical paper

|

19 Aug 2020

Development and technical paper |

| 19 Aug 2020

An offline framework for high-dimensional ensemble Kalman filters to reduce the time to solution

Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet

Download

Final revised paper (published on 19 Aug 2020)
Preprint (discussion started on 18 Jun 2019)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review of 'An offline framework...'', Anonymous Referee #1, 30 Jul 2019
- AC1: 'Reply to Reviewer#1', Clément Albergel, 05 Dec 2019
RC2: 'Reviewer Comments', Anonymous Referee #2, 10 Feb 2020
- AC2: 'Response to Reviewer#2', Clément Albergel, 20 Feb 2020
EC1: 'Reviews', Adrian Sandu, 10 Feb 2020
- AC3: 'Response to editor', Clément Albergel, 20 Feb 2020

Peer-review completion

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

AR by Clément Albergel on behalf of the Authors (25 Feb 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (02 Mar 2020) by Adrian Sandu

RR by Elias D. Nino-Ruiz (26 Apr 2020)

ED: Publish subject to minor revisions (review by editor) (10 Jun 2020) by Adrian Sandu

AR by Clément Albergel on behalf of the Authors (19 Jun 2020) Author's response Manuscript

ED: Publish as is (07 Jul 2020) by Adrian Sandu

AR by Clément Albergel on behalf of the Authors (09 Jul 2020) Manuscript

Short summary

This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.