Pressure image assimilation for atmospheric motion estimation

Abstract : The complexity of the laws of dynamics governing 3-D atmospheric flows associated with incomplete and noisy observations make the recovery of atmospheric dynamics from satellite image sequences very difficult. In this paper, we address the challenging problem of estimating physical sound and time-consistent horizontal motion fields at various atmospheric depths for a whole image sequence. Based on a vertical decomposition of the atmosphere, we propose a dynamically consistent atmospheric motion estimator relying on a multilayer dynamic model. This estimator is based on a weak constraint variational data assimilation scheme and is applied on noisy and incomplete pressure difference observations derived from satellite images. The dynamic model is a simplified vorticity-divergence form of a multilayer shallow-water model. Average horizontal motion fields are estimated for each layer. The performance of the proposed technique is assessed using synthetic examples and using real world meteorological satellite image sequences. In particular, it is shown that the estimator enables exploiting fine spatio-temporal image structures and succeeds in characterizing motion at small spatial scales.
Type de document :
Article dans une revue
Tellus A, Co-Action Publishing, 2009, 61 (1), pp.160-178. <10.1111/j.1600-0870.2008.00370.x>
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Contributeur : Nicolas Papadakis <>
Soumis le : jeudi 26 mai 2011 - 17:23:26
Dernière modification le : samedi 14 janvier 2017 - 01:08:17



Thomas Corpetti, Patrick Héas, Etienne Memin, Nicolas Papadakis. Pressure image assimilation for atmospheric motion estimation. Tellus A, Co-Action Publishing, 2009, 61 (1), pp.160-178. <10.1111/j.1600-0870.2008.00370.x>. <hal-00596223>



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