GAIM driven by different empirical models: a comparison with Data Assimilation

The Mid-low latitude Ionospheres variability is a consequence of external and internal forcings such as solar EUV, thermosphere winds, and chemical processes. However, the extent to which specific drivers influence both short and long term variability is not well understood. Data assimilation (DA) techniques for the Ionosphere-Thermosphere (IT) system provide a way of combining theoretical physics-based models with observational data for studies of specific events/days. In this study the Global Assimilation of Ionosphere Measurements (GAIM) model is used to compared physics-based climatology outputs driven by different empirical models for solar EUV flux, electron/ion temperature, and thermospheric horizontal winds. The physics-based model runs are then compared to DA runs to assess the performance of the physics-based model. Additionally, differences in the empirical drivers and their impact on the resulting comparisons are discussed.