Data assimilation using the global ionosphere-thermosphere model

Abstract

We consider a data assimilation technique for coupled ionospheric and thermospheric dynamics. The Global Ionosphere-Thermosphere Model (GITM) is used to simulate the ionospheric and thermospheric dynamics, and evaluate the performance of the data assimilation scheme that estimates the ion densities and flow speeds. This estimation technique is based on the state dependent Riccati equation (SDRE), which uses a frozen linear dynamics matrix for the time update of the error covariance and the evaluation of the Kalman filter gain. We demonstrate the performance of the data assimilation technique on a section of the ionosphere. © Springer-Verlag Berlin Heidelberg 2006.