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 dynamics. 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.
['Etienne Huot', 'Isabelle Herlin', 'Gennady K. Korotaev']
Assimilation of SST Satellite Images for Estimation of Ocean Circulation Velocity