Ocean Data Assimilation using Sequential Methods based on the Kalman Filter

Pierre Brasseur (1)

1 LEGI - Laboratoire des Écoulements Géophysiques et Industriels [Grenoble]

The main purpose of this chapter is to review the fundamentals of the Kalman Filter for ocean data assimilation and to expose the basic ingredients of practical assimilation algorithms developed for applied ocean research and operational forecasting, focusing mainly on high-resolution applications. Important implementation issues such as the reduction in dimensionality of the estimation problem, the simplification of the schemes based on static error covariances, the formulation of low-rank filters, the problem of consistency verification, and the concepts of adaptivity and incremental analysis updating will be addressed using scientific and operational examples. Finally, the discussion will conclude with a number of key questions related to the assimilation challenges of the next decade.

Mots clés: data assimilation; mesoscale ocean circulation; reduced-order Kalman filters; statistical estimation; ocean forecasting

Domaines: Mécanique des fluides [physics.class-ph]; Mécanique des fluides [physics.class-ph]

Pierre Brasseur. Ocean Data Assimilation using Sequential Methods based on the Kalman Filter: From theory to practical implementations. E. Chassignet; J. Verron. Ocean Weather Forecasting, pp.271-316, 2006, ⟨10.1007/1-4020-4028-8_10⟩. ⟨hal-00232778⟩