Phd in ASTRONOMY ASTROPHYSICS AND SPACE SCIENCE

Thesis title: A Multi-Scale Investigation of Solar-Magnetosphere-Ionosphere Coupling: From Solar Flare Statistics to Ionospheric Modeling and Forecasting

This thesis presents a multi-scale investigation of the solar-magnetosphere-ionosphere coupling, a critical area of research for understanding and forecasting space weather phenomena. The motivations for this work are twofold, encompassing both the scientific quest to understand the complex plasma dynamics that characterize the near-Earth space and to decode the Sun-Earth system connection, as well as a pressing operational need to protect our technologically reliant society from the effects of solar activity. The research follows a comprehensive approach, tracing the chain of events from the drivers of space weather to the response of the ionosphere and its modeling. We first focus on the properties of solar flares by developing a new catalogue that is then used to investigate their waiting time distribution and multifractal nature, providing a deeper understanding of their underlying physics. The focus then shifts to the analysis of the high-latitude ionosphere, a region where a complex current system dissipates energy from the Sun. By analyzing in-situ satellite measurements, the scaling properties of magnetic field and electron density fluctuations are explored. This analysis reveals the turbulent and intermittent nature of the ionospheric plasma, providing insights into energy dissipation, and highlighting hemispheric asymmetries and the influence of geomagnetic conditions on the fractal topology of the ionosphere. Finally, the thesis addresses the challenge of modeling and forecasting the ionosphere’s behavior. A climatological model for high-latitude ionospheric irregularities is presented, based on a spherical harmonic decomposition of key parameters. Furthermore, state-of-the-art machine learning techniques, including Denoising Diffusion Probabilistic Models and a Graph Neural Network framework, are applied to forecast ionospheric convection patterns and dynamics. These models demonstrate significant potential for improving short-term space weather predictions and can be used as a baseline for future long-term applications. Overall, this thesis contributes to a deeper understanding of the coupled Sun-Earth system by bridging the gap between the large-scale phenomena driving space weather and the small-scale processes that characterize the ionospheric response. The results and models presented are of significant importance for both the scientific community and the operational efforts to mitigate the adverse effects of space weather on our technological infrastructure.