Articles | Volume 25, issue 1
https://doi.org/10.5194/npg-25-129-2018
https://doi.org/10.5194/npg-25-129-2018
Research article
 | 
01 Mar 2018
Research article |  | 01 Mar 2018

Accelerating assimilation development for new observing systems using EFSO

Guo-Yuan Lien, Daisuke Hotta, Eugenia Kalnay, Takemasa Miyoshi, and Tse-Chun Chen

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Interactive discussion

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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 Guo-Yuan Lien on behalf of the Authors (22 Nov 2017)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (05 Dec 2017) by Zoltan Toth
AR by Guo-Yuan Lien on behalf of the Authors (13 Dec 2017)  Author's response    Manuscript
ED: Publish subject to technical corrections (10 Jan 2018) by Zoltan Toth
AR by Guo-Yuan Lien on behalf of the Authors (18 Jan 2018)  Author's response    Manuscript
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Short summary
The ensemble forecast sensitivity to observation (EFSO) method can efficiently clarify under what conditions observations are beneficial or detrimental for assimilation. Based on EFSO, an offline assimilation method is proposed to accelerate the development of data selection strategies for new observing systems. The usefulness of this method is demonstrated with the assimilation of global satellite precipitation data.