Quantifying the evolution of interplanetary coronal mass ejections by coupling physics-based and data-driven modeling

Coronal mass ejections (CMEs) are considered to be one of the main drivers of space weather. They consist of large-scale eruptions of magnetised plasma, originating predominantly from active regions in the low solar corona and are extremely common events. During solar maxima, they occur on a daily basis, at times exceeding 10 events per day. CMEs can affect space missions and when they propagate towards Earth and interact with the magnetosphere, they can adversely impact a variety of assets, such as satellites, aviation, electricity networks and gas or oil pipelines. In addition, they can impact our daily life for example due to navigation system disturbances and failures. Such impacts occur during geomagnetic storms and the prediction of such events and the level of impact on Earth that they incur is extremely important for our society. The understanding of the physical processes that lay at origin of CMEs, their eruptions but as importantly their propagation through the heliosphere and their impact on Earth and other planets or spacecraft of interest is a crucial step towards the improvement of our current space weather forecasting capabilities. Whether a CME strongly impacts our Earth's environment or not, is generally dependent on the dynamic pressure, speed, magnetic field structure and strength of the CME in question.

In this thesis we have focused on both the mapping our current capabilities with respect to the prediction of CMEs as well as the improvement of the European Heliospheric FOREcasting Information Asset (EUHFORIA), a recently developed magnetohydrodynamic model that can model both the ambient solar wind as well as CMEs propagation through it. We focus on improving the EUHFORIA model to include a magnetised CME. The new CME model will be validated by comparing the simulation results with real observations. Furthermore, we explore how grid stretching and adaptive mesh refinement can influence the computional time as well as the accuracy of the results.

The results of this thesis directly contribute to the improvement of simulating the propagation of CMEs throughout the inner heliosphere, with the inclusion of a magnetic field within the CME model. Furthermore, it provides scientists the support and tools to benchmark future work by providing more insight into the errors related to CME model input parameters, as well as providing guidelines towards community-developed benchmarking of CME arrival time and impact.