A Hybrid Particle-Ensemble Kalman Filter for High Dimensional Lagrangian Data Assimilation

摘要

We apply the recently proposed hybrid particle-ensemble Kalman filter to assimilate Lagrangian data into a non-linear, high-dimensional quasi-geostrophic ocean model. Effectively the hybrid filter applies a particle filter to the highly nonlinear, low-dimensional Lagrangian instrument variables while applying an ensemble Kalman type update to the high-dimensional Eulerian flow field. We present some initial results from this hybrid filter and compare those to results from a standard ensemble Kalman filter and an ensemble run without assimilation.