Articles | Volume 23, issue 2
Research article
11 Mar 2016
Research article |  | 11 Mar 2016

Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method

J. Mandel, E. Bergou, S. Gürol, S. Gratton, and I. Kasanický


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 Jan Mandel on behalf of the Authors (30 Nov 2015)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (03 Dec 2015) by Olivier Talagrand
RR by Anonymous Referee #2 (04 Jan 2016)
RR by Emmanuel Cosme (21 Jan 2016)
ED: Publish subject to minor revisions (further review by Editor) (22 Jan 2016) by Olivier Talagrand
AR by Jan Mandel on behalf of the Authors (01 Feb 2016)  Author's response    Manuscript
ED: Publish subject to technical corrections (04 Feb 2016) by Olivier Talagrand
Short summary
A stochastic method, the ensemble Kalman smoother (EnKS), is proposed as a linear solver in four-dimensional variational data assimilation (4DVAR). The method approaches 4DVAR for large ensembles. Regularization provides global convergence, and it is implemented as an additional artificial observation. Since the EnKS is uncoupled from the insides of the 4DVAR, any version of EnKS can be used.