1Ionospheric Data Assimilation by Use of the Kalman Filter

Abstract. A fully 3-dimensional Global Assimilative Ionospheric Model (GAIM) is currently being developed by a joint University of Southern California and JPL team. To estimate the electron density on a global grid, GAIM uses a first-principles ionospheric physics model (“forward ” model) and one of two estimation techniques: the Kalman filter and 4DVAR (4-Dimensional VARiational). Because of the large dimension of the state (i.e., electron density on a global 3-D grid), implementation of a full Kalman filter is not computationally feasible. Therefore, we have implemented a band-limited Kalman in which a full time propagation of the covariance is performed but only a portion of the covariance matrix is retained. The retained elements are determined based on assumed physical correlation lengths in the ionosphere. The effectiveness of ground GPS data for specifying the ionosphere is assessed by assimilating slant TEC data from 98 sites into the GAIM Kalman filter and validating the retrieved electron density field against independent measurements. A series of GAIM retrievals are presented and validated by comparisons to: JPL’s GIM map of vertical TEC, vertical TEC measurements from the TOPEX altimeter, and slant TEC data from GPS sites that were not included in the assimilation runs. 1