Variational fronts tracking in sea surface temperature images

Abstract

Nowadays, high resolution sea surface temperature (SST) observations recorded from orbital satellites are available. Because SST fronts appearing at the ocean surface convey information about the dynamics of deeper ocean layers, their study is of high interest in oceanography. In this paper we present a variational method for fronts tracking in SST images. The proposed method integrates into the variational data assimilation framework a variational method for fronts detection using the level set formulation. This allows our method to extract temporally consistent fronts in SST images sequences. The proposed method is validated on two sequences of SST images of two regions, the region of Malvinas and the region of Aghulas-Benguela, which host very active oceanic fronts.