Articles | Volume 14, issue 5
Geosci. Model Dev., 14, 2635–2657, 2021
https://doi.org/10.5194/gmd-14-2635-2021

Special issue: Model infrastructure integration and interoperability (MI3)

Geosci. Model Dev., 14, 2635–2657, 2021
https://doi.org/10.5194/gmd-14-2635-2021

Development and technical paper 12 May 2021

Development and technical paper | 12 May 2021

Developing a common, flexible and efficient framework for weakly coupled ensemble data assimilation based on C-Coupler2.0

Chao Sun et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Chao Sun on behalf of the Authors (13 Oct 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (29 Oct 2020) by Wolfgang Kurtz
RR by Anonymous Referee #1 (12 Nov 2020)
RR by Anonymous Referee #2 (16 Nov 2020)
ED: Reconsider after major revisions (02 Dec 2020) by Wolfgang Kurtz
AR by Chao Sun on behalf of the Authors (15 Dec 2020)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (23 Dec 2020) by Wolfgang Kurtz
RR by Anonymous Referee #1 (29 Dec 2020)
ED: Reconsider after major revisions (19 Jan 2021) by Wolfgang Kurtz
AR by Chao Sun on behalf of the Authors (02 Feb 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (17 Feb 2021) by Wolfgang Kurtz
RR by Anonymous Referee #1 (16 Mar 2021)
ED: Publish as is (08 Apr 2021) by Wolfgang Kurtz
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Short summary
Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.