Articles | Volume 22, issue 6
Nonlin. Processes Geophys., 22, 645–662, 2015
https://doi.org/10.5194/npg-22-645-2015
Nonlin. Processes Geophys., 22, 645–662, 2015
https://doi.org/10.5194/npg-22-645-2015

Research article 03 Nov 2015

Research article | 03 Nov 2015

Expanding the validity of the ensemble Kalman filter without the intrinsic need for inflation

M. Bocquet et al.

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Marc Bocquet on behalf of the Authors (28 Sep 2015)  Author's response    Manuscript
ED: Publish subject to minor revisions (further review by Editor) (05 Oct 2015) by Zoltan Toth
AR by Marc Bocquet on behalf of the Authors (07 Oct 2015)  Author's response    Manuscript
ED: Publish subject to technical corrections (08 Oct 2015) by Zoltan Toth
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Short summary
The popular data assimilation technique known as the ensemble Kalman filter (EnKF) suffers from sampling errors due to the limited size of the ensemble. This deficiency is usually cured by inflating the sampled error covariances and by using localization. This paper further develops and discusses the finite-size EnKF, or EnKF-N, a variant of the EnKF that does not require inflation. It expands the use of the EnKF-N to a wider range of dynamical regimes.