N. J. Hardman-mountford, A. J. Richardson, D. C. Boyer, A. Kreiner, and H. J. Boyer, Relating sardine recruitment in the Northern Benguela to satellite-derived sea surface height using a neural network pattern recognition approach, Progress in Oceanography, vol.59, issue.2, pp.241-255, 2003.

P. Traon, Satellites and operational oceanography, pp.29-54, 2011.

K. Von-schuckmann, P. Le-traon, E. Alvarez-fanjul, L. Axell, M. Balmaseda et al., The copernicus marine environment monitoring service ocean state report, Journal of Operational Oceanography, vol.9, issue.sup2, pp.235-320, 2016.

A. C. Lorenc, S. P. Ballard, R. S. Bell, N. B. Ingleby, P. L. Andrews et al., The Met. Office global three-dimensional variational data assimilation scheme, Quarterly Journal of the Royal Meteorological Society, vol.126, issue.570, pp.2991-3012, 2000.

G. Evensen, Data Assimilation, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00229825

S. Hong and J. Dudhia, Next-generation numerical weather prediction : Bridging parameterization, explicit clouds, and large eddies, Bulletin of the American Meteorological Society, vol.93, issue.1, pp.6-9, 2012.

J. Jose, R. Manuel, P. , and T. Miyoshi, Estimating model parameters with ensemble-based data assimilation : A review, Journal of the Meteorological Society of Japan. Ser. II, vol.91, issue.2, pp.79-99, 2013.

P. Tandeo, P. Ailliot, B. Chapron, R. Lguensat, and R. Fablet, The analog data assimilation : application to 20 years of altimetric data, International Workshop on Climate Informatics, pp.1-2, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01356222

L. Steven, J. L. Brunton, J. Proctor, and . Nathan-kutz, Discovering governing equations from data by sparse identification of nonlinear dynamical systems, Proceedings of the National Academy of Sciences, vol.113, issue.15, pp.3932-3937, 2016.

S. Ouala, C. Herzet, and R. Fablet, Sea surface temperature prediction and reconstruction using patch-level neural network representations, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01883209

K. He, X. Zhang, S. Ren, and J. Sun, Deep Residual Learning for Image Recognition, 2015.

M. Fraccaro, . Søren-kaae, U. Sønderby, O. Paquet, and . Winther, Sequential Neural Models with Stochastic Layers, 2016.

C. J. Donlon, M. Martin, J. Stark, J. Roberts-jones, E. Fiedler et al., The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system, Remote Sensing of Environment, vol.116, pp.140-158, 2012.

B. Ping, F. Su, and Y. Meng, An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data, PLOS ONE, vol.11, issue.5, p.155928, 2016.

R. Fablet, P. H. Viet, and R. Lguensat, DataDriven Models for the Spatio-Temporal Interpolation of Satellite-Derived SST Fields, IEEE Transactions on Computational Imaging, vol.3, issue.4, pp.647-657, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01656178

O. Pannekoucke, E. Emili, and O. Thual, Modelling of local length-scale dynamics and isotropizing deformations, Quarterly Journal of the Royal Meteorological Society, vol.140, issue.681, pp.1387-1398, 2013.
URL : https://hal.archives-ouvertes.fr/hal-02101388

O. Pannekoucke, S. Ricci, S. Barthelemy, R. Ménard, and O. Thual, Parametric Kalman filter for chemical transport models, Tellus A : Dynamic Meteorology and Oceanography, vol.68, p.31547, 2016.

R. Lguensat, P. H. Viet, M. Sun, G. Chen, T. Fenglin et al., Data-driven Interpolation of Sea Level Anomalies using Analog Data Assimilation, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01609851

R. Fablet, S. Ouala, and C. Herzet, Bilinear residual Neural Network for the identification and forecasting of dynamical systems, SciRate, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01686766

Y. Lecun, P. Haffner, L. Bottou, and Y. Bengio, Object Recognition with Gradient-Based Learning, Shape, Contour and Grouping in Computer Vision, pp.319-345, 1999.

R. Lguensat, P. Tandeo, P. Ailliot, M. Pulido, and R. Fablet, The Analog Data Assimilation, Monthly Weather Review, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01609141