Assimilation of SST Satellite Images for Estimation of Ocean Circulation Velocity

Étienne Huot (1, 2, 3) , Isabelle Herlin (1, 2) , Gennady K. Korotaev (4)

1 Clime - Coupling environmental data and simulation models for software integration
2 CEREA - Centre d'Enseignement et de Recherche en Environnement Atmosphérique
3 UVSQ - Université de Versailles Saint-Quentin-en-Yvelines
4 MHI - Marine Hydrophysical Institute

The objective of this study is to compute the surface circulation velocity from oceanographic image sequences. Data assimilation provides a mathematical solution to combine optimally observations and models. We define a dedicated Image Model consistent with the physical knowledge of ocean dynamic. Satellite images are then assimilated into this model using a variational data assimilation scheme. This technique relies on the adjoint model definition to compute the minimum of a cost function measuring the discrepancy between model's outputs and observations. The method takes into account the physical knowledge of the ocean circulation, which is relevant for explaining images evolution and, in case of missing data due to clouds occlusion or lack of acquisitions, the estimation is still consistent with the physical evolution laws.

Mots clés: Image sequence analysis; partial differential equations; optimal control; sea surface

Domaines: Modélisation et simulation

Étienne Huot, Isabelle Herlin, Gennady K. Korotaev. Assimilation of SST Satellite Images for Estimation of Ocean Circulation Velocity. IGARSS - Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Jul 2008, Boston, United States. pp.847-850, ⟨10.1109/IGARSS.2008.4779127⟩. ⟨inria-00583029⟩