Journal cover Journal topic
Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
Nonlin. Processes Geophys., 22, 645-662, 2015
http://www.nonlin-processes-geophys.net/22/645/2015/
doi:10.5194/npg-22-645-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
03 Nov 2015
Expanding the validity of the ensemble Kalman filter without the intrinsic need for inflation
M. Bocquet et al.
Download
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC C312: 'Reviewer Comments for npg-2015-47', Anonymous Referee #1, 13 Aug 2015 Printer-friendly Version 
RC C373: 'Comments on “Expanding the validity of the ensemble Kalman filter without the intrinsic need for inflation” by Bocquet, Raanes and Hannart.', Anonymous Referee #2, 03 Sep 2015 Printer-friendly Version 
AC C455: 'Response to Referee 2', Marc Bocquet, 28 Sep 2015 Printer-friendly Version 
AC C452: 'Response to Referee 1', Marc Bocquet, 28 Sep 2015 Printer-friendly Version 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Dr 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 Dr. Zoltan Toth  
AR by Dr Marc Bocquet on behalf of the Authors (07 Oct 2015)  Author's response  Manuscript
ED: Publish subject to technical corrections (08 Oct 2015) by Dr. Zoltan Toth  
Publications Copernicus
Download
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.
The popular data assimilation technique known as the ensemble Kalman filter (EnKF) suffers from...
Share