Articles | Volume 25, issue 3
https://doi.org/10.5194/npg-25-633-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-25-633-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Sep 2018
Research article |
| 04 Sep 2018
| 04 Sep 2018
Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Alberto Carrassi
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Marc Bocquet
CEREA, joint laboratory École des Ponts ParisTech and EDF R&D, Université Paris-Est,
Champs-sur-Marne, France
Viewed
Total article views: 3,767 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Feb 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,461 | 1,133 | 173 | 3,767 | 148 | 153 |
- HTML: 2,461
- PDF: 1,133
- XML: 173
- Total: 3,767
- BibTeX: 148
- EndNote: 153
Total article views: 2,902 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 04 Sep 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,984 | 763 | 155 | 2,902 | 135 | 135 |
- HTML: 1,984
- PDF: 763
- XML: 155
- Total: 2,902
- BibTeX: 135
- EndNote: 135
Total article views: 865 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Feb 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 477 | 370 | 18 | 865 | 13 | 18 |
- HTML: 477
- PDF: 370
- XML: 18
- Total: 865
- BibTeX: 13
- EndNote: 18
Viewed (geographical distribution)
Total article views: 3,767 (including HTML, PDF, and XML)
Thereof 3,469 with geography defined
and 298 with unknown origin.
Total article views: 2,902 (including HTML, PDF, and XML)
Thereof 2,643 with geography defined
and 259 with unknown origin.
Total article views: 865 (including HTML, PDF, and XML)
Thereof 826 with geography defined
and 39 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
17 citations as recorded by crossref.
- A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations S. Pawar et al. 10.1007/s13137-021-00185-z
- Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models M. Bocquet et al. 10.5194/npg-26-143-2019
- A new mathematical framework for atmospheric blocking events V. Lucarini & A. Gritsun 10.1007/s00382-019-05018-2
- On the numerical integration of the Lorenz-96 model, with scalar additive noise, for benchmark twin experiments C. Grudzien et al. 10.5194/gmd-13-1903-2020
- Joint identification of contaminant source characteristics and hydraulic conductivity in a tide-influenced coastal aquifer A. Dodangeh et al. 10.1016/j.jconhyd.2022.103980
- A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China G. Jia et al. 10.1016/j.jes.2021.08.048
- Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology Y. Chen et al. 10.5194/tc-18-2381-2024
- Strongly Coupled Data Assimilation in Multiscale Media: Experiments Using a Quasi‐Geostrophic Coupled Model S. Penny et al. 10.1029/2019MS001652
- Inferring the instability of a dynamical system from the skill of data assimilation exercises Y. Chen et al. 10.5194/npg-28-633-2021
- Application of a local attractor dimension to reduced space strongly coupled data assimilation for chaotic multiscale systems C. Quinn et al. 10.5194/npg-27-51-2020
- Online learning of both state and dynamics using ensemble Kalman filters M. Bocquet et al. 10.3934/fods.2020015
- Combining harmonic pumping with a tracer test for fractured aquifer characterization A. Dodangeh et al. 10.1007/s10040-023-02595-9
- Particle filters for data assimilation based on reduced‐order data models J. Maclean & E. Van Vleck 10.1002/qj.4001
- Dynamical effects of inflation in ensemble‐based data assimilation under the presence of model error G. Scheffler et al. 10.1002/qj.4307
- Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error C. Grudzien et al. 10.1137/17M114073X
- Inference of stochastic parametrizations for model error treatment using nested ensemble Kalman filters G. Scheffler et al. 10.1002/qj.3542
- On Temporal Scale Separation in Coupled Data Assimilation with the Ensemble Kalman Filter M. Tondeur et al. 10.1007/s10955-020-02525-z
16 citations as recorded by crossref.
- A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations S. Pawar et al. 10.1007/s13137-021-00185-z
- Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models M. Bocquet et al. 10.5194/npg-26-143-2019
- A new mathematical framework for atmospheric blocking events V. Lucarini & A. Gritsun 10.1007/s00382-019-05018-2
- On the numerical integration of the Lorenz-96 model, with scalar additive noise, for benchmark twin experiments C. Grudzien et al. 10.5194/gmd-13-1903-2020
- Joint identification of contaminant source characteristics and hydraulic conductivity in a tide-influenced coastal aquifer A. Dodangeh et al. 10.1016/j.jconhyd.2022.103980
- A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China G. Jia et al. 10.1016/j.jes.2021.08.048
- Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology Y. Chen et al. 10.5194/tc-18-2381-2024
- Strongly Coupled Data Assimilation in Multiscale Media: Experiments Using a Quasi‐Geostrophic Coupled Model S. Penny et al. 10.1029/2019MS001652
- Inferring the instability of a dynamical system from the skill of data assimilation exercises Y. Chen et al. 10.5194/npg-28-633-2021
- Application of a local attractor dimension to reduced space strongly coupled data assimilation for chaotic multiscale systems C. Quinn et al. 10.5194/npg-27-51-2020
- Online learning of both state and dynamics using ensemble Kalman filters M. Bocquet et al. 10.3934/fods.2020015
- Combining harmonic pumping with a tracer test for fractured aquifer characterization A. Dodangeh et al. 10.1007/s10040-023-02595-9
- Particle filters for data assimilation based on reduced‐order data models J. Maclean & E. Van Vleck 10.1002/qj.4001
- Dynamical effects of inflation in ensemble‐based data assimilation under the presence of model error G. Scheffler et al. 10.1002/qj.4307
- Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error C. Grudzien et al. 10.1137/17M114073X
- Inference of stochastic parametrizations for model error treatment using nested ensemble Kalman filters G. Scheffler et al. 10.1002/qj.3542
1 citations as recorded by crossref.
Latest update: 24 Dec 2024
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.
Using the framework Lyapunov vectors, we analyze the asymptotic properties of ensemble based...
