Ensemble Data Assimilation for the RAM-SCB Model

Over the course of the last two decades, 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 present the implementation of the ensemble Kalman filter (EnKF) to the Ring Current-Atmosphere Interactions Model with Self-Consistent Magnetic field (RAM-SCB) using particle flux data from the Van Allen Probes. The ring current environment is estimated using EnKF to capture the enhancement storm event that took place on 7--10 September of 2017, where a large double-dip geomagnetic storm was observed. The assimilated results show a significant improvement in the estimation of the ring current particle distributions in the RAM-SCB model, leading to better agreement with observations. A number of features are captured and will be discussed in the presentation.