Combining analog method and ensemble data assimilation: application to the Lorenz-63 chaotic system

Abstract

Nowadays, ocean and atmosphere sciences face a deluge of data from space, in situ monitoring as well as numerical simulations. The availability of these different data sources offer new opportunities, still largely underexploited, to improve the understanding,modeling and reconstruction of geophysical dynamics. The classical way to reconstruct the space-time variations of a geophysical system from observations relies on data assimilation methods using multiple runs of the known dynamical model. This classical framework may have severe limitations including its computational cost, the lack of adequacy of the model with observed data, modeling uncertainties. In this paper, we explore an alternative approach and develop a fully data-driven framework, which combines machine learning and statistical sampling to simulate the dynamics of complex system. As a proof concept, we address Pierre Tandeo Télécom Bretagne, e-mail: pierre.tandeo@telecom-bretagne.eu Pierre Ailliot Université de Bretagne Occidentale, e-mail: pierre.ailliot@univ-brest.fr Juan Ruiz National Scientific and Technical Research Council, e-mail: jruiz@cima.fcen.uba.ar Alexis Hannart National Scientific and Technical Research Council, e-mail: alexis.hannart@cima.fcen.uba.ar Bertrand Chapron Ifremer, e-mail: bertrand.chapron@ifremer.fr Anne Cuzol Université de Bretagne Sud, e-mail: anne.cuzol@univ-ubs.fr Valérie Monbet Université de Rennes I, e-mail: valerie.monbet@univ-rennes1.fr Robert Easton University of Colorado, e-mail: robert.easton@colorado.edu Ronan Fablet Télécom Bretagne, e-mail: ronan.fablet@telecom-bretagne.eu

Cite this paper

@inproceedings{Tandeo2017CombiningAM, title={Combining analog method and ensemble data assimilation: application to the Lorenz-63 chaotic system}, author={Pierre Tandeo and Pierre Ailliot and Juan Ruiz and Alexis Hannart and Bertrand Chapron and Anne Cuzol and Val{\'e}rie Monbet and Robert Easton and Ronan Fablet}, year={2017} }