This project demonstrates how the current limit of thermospheric mass density predictability can be extended by systematically integrating observations into a coupled thermosphere-ionosphere first-principles model. An ensemble data assimilation procedure, constructed with the NCAR Data Assimilation Research Testbed (DART) and the NCAR Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIEGCM),can take advantage of the tight coupling between the ionosphere and thermosphere, enabling the inference of thermospheric temperature and compositions from abundant GPS-based ionospheric observations. Observing system simulation experiments suggest that thermospheric states, particularly temperature, can be well inferred by assimilating electron density profiles obtained from the COSMIC/FORMOSAT-3 mission into the TIEGCM. This in turn leads to a significant improvement of the neutral mass density forecasting longer than 3 days. Furthermore, validation of assimilation analyses with independent CHAMP mass density observations confirms that the approach indeed improves the thermospheric mass density specification. Predictability of the ionosphere can also be extended considerably by the approach developed in this project.