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Reconstruction de la circulation océanique à partir d'observations satellitaires à très haute résolution

Abstract : During the last decade, high resolution observations have significantly increased mainly due to the strong innovations of satellite technology. The amount of observed information from satellites is large, and it is necessary to identify effective techniques to treat and to generate surface maps of the ocean dynamics. The future SWOT mission will collect sea surface height (SSH) measurements with a high spatial resolution : some dynamics at small wavelengths, which is known as submeso-scale, will be present in these new observations. Satellite observations could be used to carry out a vertical projection into the deeper ocean and to other variables. The question that rises is which methods can be used to carry out a 3D multivariate analysis with a significant precision, especially at meso and submeso-scale.We work here in a data/image assimilation framework : our objective if to reconstruction with good precision the dynamics in the upper oceanic layer (~500 m) using satellite observations. To do so, we implement a two-step method that uses different observations of the sea surface. The first step consist on the SEEK filter which is a data assimilation technique to carry out a first linear correction of the flow. The second step uses an image assimilation method (Gaultier et al , 2012) to correct the location of the main dynamical structure. This main dynamical structure is obtained by the computation of the Lyapunov exponents. A probability approach is applied to provide uncertainties on the estimates at each step. A first probability distribution of a background state is supposed to be known : the two-step method corrects this probability distribution at each step in order to converge towards the real ocean state. The SEEK filter corrects the background probability distribution using a SSH observation. The second step continues this correction towards smaller scales by using an image structure observation. To carry out the vertical projection, an ensemble of 3D multivariate EOFs (Empirical Orthogonal Functions) is used (Duran-Moro et al, 2017).The method is tested using synthetic data generated by a numerical model in the Solomon Sea region (SOSMOD36). The spatial resolution of these simulations is of ~3 km. We evaluate the response of our method in an idealized case study by using pseudo-observations generated from the simulations. The method provides good results and the estimates are corrected also in the vertical and in terms of other variables. A more detailed exploration of the altimetric observation is realized, especially related to future SWOT observations. Errors of SWOT observations have strong spatial correlations and another technique needs to be used in our method : this modification is carried out following work done in Ruggiero et al, 2016. Simulations from another NEMO configuration in the North Atlantic region (NATL60) are also used to evaluate the method. This second test allows us to explore the method in a different latitude of the globe.
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Submitted on : Wednesday, September 5, 2018 - 10:59:10 AM
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Marina Duran Moro. Reconstruction de la circulation océanique à partir d'observations satellitaires à très haute résolution. Sciences de la Terre. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAU037⟩. ⟨tel-01868174⟩



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