Abstract: The ionosphere is a charged region of the upper atmosphere. Ionospheric storms can have important effects on radio communications and navigation systems. Nowcasts and forecasts of the ionosphere could help mitigate these damaging effects. Recent advances in the field of ionospheric imaging and new forecasting developments are presented here. The term data assimilation refers to a group of techniques designed to estimate atmospheric or oceanic states. In practice, data assimilation techniques seek to improve a modelled estimate of the state by incorporating observations. A review of ionospheric physics and several data assimilation approaches will be presented. Results of ionospheric specification techniques such as GPS ionospheric tomography and the Ensemble Kalman Filter are presented. The relationship between data assimilation and forecasting is explored with reference to the physics of the thermosphere-ionosphere system. An important conclusion of this work is that accurate initial specification of neutral parameters, in particular the thermospheric composition, results in far more accurate electron density forecasts than accurate initial specification of ionospheric electron density. Ensemble-modeled time-evolving covariance estimates are used to estimate thermospheric winds and composition from ionospheric observations.