Article Dans Une Revue Tellus A: Dynamic meteorology and oceanography Année : 2013

Weighted Ensemble Transform Kalman Filter for Image Assimilation

Résumé

This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF) proposed by Papadakis et al. (2010) for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF), incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST) satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.

Fichier principal
Vignette du fichier
TellusA-18803-final.pdf (3.21 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence
Loading...

Dates et versions

hal-00793804 , version 1 (25-02-2013)

Licence

Identifiants

Citer

Sébastien Beyou, Anne Cuzol, Sai Subrahmanyam Gorthi, Etienne Mémin. Weighted Ensemble Transform Kalman Filter for Image Assimilation. Tellus A: Dynamic meteorology and oceanography, 2013, 65, pp.1-33. ⟨10.3402/tellusa.v65i0.18803⟩. ⟨hal-00793804⟩
666 Consultations
731 Téléchargements

Altmetric

Partager

  • More