Assimilation of satellite data in beta-plane ocean circulation models

The paper discusses a scheme based on Kalman-Bucy filters for the assimilation of satellite data in equatorial beta plane ocean circulation models. The state equation of the Kalman-Bucy filter is obtained by decoupling the nonlinearities from the Navier-Stokes equations by assuming an inviscid isentropic shallow water motion. Direct application of the Kalman-Bucy filter leads to a computationally intensive algorithm which precludes its application to meaningful sized domains. By imposing a Gauss Markov random field (GMRF) structure on the error covariance matrix, the authors obtain an efficient recursive algorithm, capable of estimating the velocity fields and the sea surface height.