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NPG | Articles | Volume 26, issue 3
Nonlin. Processes Geophys., 26, 143–162, 2019
https://doi.org/10.5194/npg-26-143-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Nonlin. Processes Geophys., 26, 143–162, 2019
https://doi.org/10.5194/npg-26-143-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 10 Jul 2019

Research article | 10 Jul 2019

Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models

Marc Bocquet et al.

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Abarbanel, H. D. I., Rozdeba, P. J., and Shirman, S.: Machine Learning: Deepest Learning as Statistical Data Assimilation Problems, Neural Comput., 30, 2025–2055, https://doi.org/10.1162/neco_a_01094, 2018. a, b
Amezcua, J., Goodliff, M., and van Leeuwen, P.-J.: A weak-constraint 4DEnsembleVar. Part I: formulation and simple model experiments, Tellus A, 69, 1271564, https://doi.org/10.1080/16000870.2016.1271564, 2017. a
Asch, M., Bocquet, M., and Nodet, M.: Data Assimilation: Methods, Algorithms, and Applications, Fundamentals of Algorithms, SIAM, Philadelphia, 2016. a, b
Aster, R. C., Borchers, B., and Thuber, C. H.: Parameter Estimation and Inverse Problems, Elsevier Academic Press, 2nd Edn., 2013. a
Bocquet, M.: Parameter field estimation for atmospheric dispersion: Application to the Chernobyl accident using 4D-Var, Q. J. Roy. Meteor. Soc., 138, 664–681, https://doi.org/10.1002/qj.961, 2012. a, b
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This paper describes an innovative way to use data assimilation to infer the dynamics of a physical system from its observation only. The method can operate with noisy and partial observation of the physical system. It acts as a deep learning technique specialised to dynamical models without the need for machine learning tools. The method is successfully tested on chaotic dynamical systems: the Lorenz-63, Lorenz-96, and Kuramoto–Sivashinski models and a two-scale Lorenz model.
This paper describes an innovative way to use data assimilation to infer the dynamics of a...
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