A novel data assimilation model for the plasmasphere

Abstract:

We present a novel technique for imaging and data assimilation of the topside ionosphere and plasmasphere. The technique incorporates the SAMI2 model as a physics-based background model for assimilation. The Gauss-Markov Kalman filter technique is used to advance estimates of electron density and background error covariances forward in time. We incorporate regularization techniques in the assimilation algorithm to stabilize the solution in face of limited data perturbation to prevent non-physical altitudinal variation in density estimates due to limited availability of data. The above-the-horizon observations from the Global Positioning System (GPS) receiver onboard Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) satellites are utilized in the assimilation algorithm. The estimation results show reasonable agreement with in-situ density measurements of Defense Meteorological Satellite Program satellites and Van Allen Probes derived densities during geomagnetically quiet and severe storm-time conditions, respectively. The results demonstrate great potential for the use of assimilation of COSMIC above-the-horizon measurements in monitoring and studying the morphology and dynamics of large-scale structures of the electron density in the topside ionosphere and plasmasphere.