Data Assimilation for the Space Weather Environment: Ring Current Estimation with Ensemble Kalman Filter

Over the recent years there has been significant progress to develop data assimilation techniques to improve the predictive capabilities of space weather models. As a consequence, data assimilation methods have been widely adopted into several fields of space weather, including specification and forecasting of the ionosphere-thermosphere, ring currents, radiation belts, and solar photosphere to name a few. We will present a new assimilation method based on the ensemble Kalman filter that projects into the space of dominant model dynamics and perform the assimilation in this new space. The new assimilation method is applied to a ring current model to incorporate data from several satellites, including the Van Allen Probes. The results provide a dramatic improvement over other versions of the Kalman filter techniques, and provides a solution with a reduced forecast error.