Assimilation de température de surface par filtre de Kalman de transformation d'ensemble pondéré
Abstract
This paper presents a novel, efficient scheme for the analysis of Sea Surface Temperature (SST) ocean images. We consider the estimation of the velocity fields and vorticity values from a sequence of oceanic images. The contribution of this paper lies in proposing a novel, robust and simple approach based onWeighted Ensemble Transform Kalman filter (WETKF) data assimilation technique for the analysis of real SST images, that may contain coast regions or large areas of missing data due to the cloud cover.
Colloque sur le Traitement du Signal et des Images