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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 24, issue 3
Nonlin. Processes Geophys., 24, 329–341, 2017
https://doi.org/10.5194/npg-24-329-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nonlin. Processes Geophys., 24, 329–341, 2017
https://doi.org/10.5194/npg-24-329-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 03 Jul 2017

Research article | 03 Jul 2017

An estimate of the inflation factor and analysis sensitivity in the ensemble Kalman filter

Guocan Wu and Xiaogu Zheng

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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 Guocan Wu on behalf of the Authors (19 Dec 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Dec 2016) by Amit Apte
RR by Anonymous Referee #2 (06 Jan 2017)
RR by Anonymous Referee #1 (06 Jan 2017)
ED: Reconsider after major revisions (further review by Editor and Referees) (09 Mar 2017) by Amit Apte
AR by Guocan Wu on behalf of the Authors (22 Mar 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (11 Apr 2017) by Amit Apte
RR by Anonymous Referee #2 (24 Apr 2017)
ED: Publish subject to minor revisions (further review by Editor) (13 May 2017) by Amit Apte
AR by Guocan Wu on behalf of the Authors (17 May 2017)  Author's response    Manuscript
ED: Publish as is (26 May 2017) by Amit Apte
Publications Copernicus
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Short summary
The accuracy of the assimilation results crucially relies on the estimate accuracy of forecast error covariance matrix in data assimilation. Ensemble Kalman filter estimates the forecast error covariance matrix as the sampling covariance matrix of the ensemble forecast states, which need to be further inflated. The experiment results on the Lorenz-96 model show that the analysis error is reduced and the analysis sensitivity to observations is improved using the proposed inflation technique.
The accuracy of the assimilation results crucially relies on the estimate accuracy of forecast...
Citation