Olivier PANNEKOUCKE, INPT-ENM, CNRM, Météo-France/CERFACS
Parametric Kalman filter for chemical transport models
CoauthorsSophie RICCI, Sebastien BARTHELEMY, Richard MENARD, Olivier THUAL
Abstract: A computational simplification of the Kalman filter is introduced – the Parametric Kalman Filter (PKF). Instead of using ensembles, the dynamics of the error variance and the diffusion tensor, which is related to the correlation length-scales, are approximated and propagated all along the analysis and forecast cycles resulting in a Kalman filter like algorithm that is easy to compute and considerably more efficient than an ensemble Kalman filter. The Parametric Kalman Filter developed here has been applied to a simplified framework of the advection diffusion of a passive tracer. We discuss both the Lagrangian and Eulerian form of the algorithm.