Articles | Volume 25, issue 3
Nonlin. Processes Geophys., 25, 633–648, 2018
https://doi.org/10.5194/npg-25-633-2018

Special issue: Numerical modeling, predictability and data assimilation in...

Nonlin. Processes Geophys., 25, 633–648, 2018
https://doi.org/10.5194/npg-25-633-2018

Research article 04 Sep 2018

Research article | 04 Sep 2018

Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error

Colin Grudzien et al.

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Status: closed
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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 Colin Grudzien on behalf of the Authors (08 Jun 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (11 Jun 2018) by Juan Manuel Lopez
RR by Anonymous Referee #2 (14 Jun 2018)
RR by Anonymous Referee #3 (05 Jul 2018)
RR by S.G. Penny (27 Jul 2018)
ED: Publish subject to minor revisions (review by editor) (03 Aug 2018) by Juan Manuel Lopez
AR by Colin Grudzien on behalf of the Authors (13 Aug 2018)  Author's response    Manuscript
ED: Publish as is (20 Aug 2018) by Juan Manuel Lopez
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Short summary
Using the framework Lyapunov vectors, we analyze the asymptotic properties of ensemble based Kalman filters and how these are influenced by dynamical chaos, especially in the context of random model errors and small ensemble sizes. Particularly, we show a novel derivation of the evolution of forecast uncertainty for ensemble-based Kalman filters with weakly-nonlinear error growth, and discuss its impact for filter design in geophysical models.