The ionosphere is a critical region of Earth’s upper atmosphere, playing a significant role in technologies such as radio communication, GPS, and satellite systems. However, its variability, influenced by solar and geomagnetic activity as well as interactions with the thermosphere and lower atmosphere, makes predicting its true state challenging. Reliable operational ionospheric forecast models are crucial for mitigating risks to terrestrial technologies. Despite advancements, current modelling capabilities often provide low-skill forecasts and struggle to capture the ionosphere's non-linear and variable nature. My PhD research focuses on incorporating advanced data assimilation techniques into existing ionospheric models. This work aims to improve the reliability of ionospheric forecasts, enabling better operational responses to space weather events, while advancing our scientific understanding of ionospheric dynamics.