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This paper describes a model-based approach to perform tracking of extratropical atmospheric disturbances from a sequence of satellite cloud-cover images. More precisely, it deals with the estimation of motion of these spiral-shaped cloud systems (both translational and rotational motion), and the measurement of the evolution of their shape. Tracking is achieved by recording from one image to the next the changes of the model parameter values. A maximum likelihood criterion is used in the process of fitting model to sensed data. The defined model takes into account geometric and intensity aspects. Such an approach readily yields global information on the disturbance cloud system of interest. As a requirement in such an application is robustness to noise, to this end two versions of the modeling have been considered.