The Solar Storms and Terrestrial Impacts Center (SOLSTICE) is a NASA-funded center under the DRIVE (Diversify, Realize, Integrate, Venture, Educate) initiative. The SOLSTICE PI is Prof. Tamas Gombosi (UM/CLaSP).
The SOLSTICE aim is to introduce a novel approach to integrated heliophysics data analysis and modeling by interlinking deterministic simulations with data-driven machine learning approaches to make significant progress in physical understanding and space weather predictions of solar eruptions and their terrestrial impacts.
The main objectives are to
- Use deep learning models and solar observations to predict solar flares and coronal mass ejections (CMEs), and thereby increase the forecast lead time and reliability;
- Use observations and model predictions of critical pre-flare conditions to provide understanding of the physics and origin of solar flares;
- Develop machine learning methods to eliminate artifacts in solar data to increase the return of investment from NASA missions;
- Incorporate model-predicted solar drivers into heliophysics simulations to increase the space weather forecast lead time from tens of minutes to several days; and
- Combine machine learning and physics-based modeling to improve our capability to model and predict geospace dynamics and the impact of magnetic storms on the magnetosphere-ionosphere system.
Our group is focused on tasks 4 and 5:
- Simulations: We develop a statistical database of space weather simulations;
- Methods: We develop quantitative analysis tools to study the flow of energy, mass and momentum through the Sun-Earth system;
- Auroras: We carry out case studies to increase understanding of the physical processes behind the space weather phenomena.
For more information see the SOLSTICE website