A three-dimensional regional assimilative model of the ionospheric electron density

Abstract

The focus of this thesis is on the development, implementation, and validation of a three-dimensional regional assimilative model of the ionospheric electron density. Empirical climatological models, like the International Reference Ionosphere (IRI) model (Bilitza et al. 2017), cannot predict the whole ionospheric variability, specifically under disturbed magnetic conditions. The model presented in this work has the purpose to improve the IRI description by implementing a data assimilation procedure, based on ionospheric measurements collected by several ground-based or satellite-based instruments. The first phase of the development of the model, called IRI UPdate (IRI UP), is devoted to update the IRI model by ingesting effective indices (IG12eff and R12eff) calculated after assimilating F2 layer characteristics values, measured by a network of ionosondes or derived by vertical total electron content values measured by a network of Global Navigational Satellite Systems receivers. The ingestion of effective indices in the IRI model allows to significantly improve the F2 layer peak density and height description. Being the F2 layer peak an anchor point for the whole IRI’s vertical electron density profile, such procedure allows to update the whole profile. The second phase of the development of the model is devoted to improve the modeling of the topside part of the ionospheric vertical electron density profile by making use of the IRI UP method and in-situ measurements collected by Swarm satellites. Finally, a procedure called IonoPy, embedding the two aforementioned steps, assimilates the whole bottomside electron density profile measured by an ionosonde, thus further improving the ionospheric plasma description in the bottomside ionosphere. All the procedures described in this thesis have been tested and validated by comparing them with other similar models or with independent datasets, for both quiet and disturbed conditions.