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NPG | Articles | Volume 27, issue 1
Nonlin. Processes Geophys., 27, 51–74, 2020
https://doi.org/10.5194/npg-27-51-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Nonlin. Processes Geophys., 27, 51–74, 2020
https://doi.org/10.5194/npg-27-51-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 19 Feb 2020

Research article | 19 Feb 2020

Application of a local attractor dimension to reduced space strongly coupled data assimilation for chaotic multiscale systems

Courtney Quinn et al.

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Cited articles

Abarbanel, H. D., Brown, R., and Kennel, M. B.: Variation of Lyapunov exponents on a strange attractor, J. Nonlinear Sci., 1, 175–199, 1991. a
Anderson, J. L. and Anderson, S. L.: A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts, Mon. Weather Rev., 127, 2741–2758, 1999. a, b
Benettin, G., Galgani, L., and Strelcyn, J.-M.: Kolmogorov entropy and numerical experiments, Phys. Rev. A, 14, 2338, https://doi.org/10.1103/PhysRevA.14.2338, 1976. a
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects, Mon. Weather Rev., 129, 420–436, 2001. a, b, c
Bocquet, M. and Carrassi, A.: Four-dimensional ensemble variational data assimilation and the unstable subspace, Tellus A, 69, 1304504, https://doi.org/10.1080/16000870.2017.1304504, 2017. a
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This study presents a novel method for reduced-rank data assimilation of multiscale highly nonlinear systems. Time-varying dynamical properties are used to determine the rank and projection of the system onto a reduced subspace. The variable reduced-rank method is shown to succeed over other fixed-rank methods. This work provides implications for performing strongly coupled data assimilation with a limited number of ensemble members on high-dimensional coupled climate models.
This study presents a novel method for reduced-rank data assimilation of multiscale highly...
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