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

  1. 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;
  2. Use observations and model predictions of critical pre-flare conditions to provide understanding of the physics and origin of solar flares;
  3. Develop machine learning methods to eliminate artifacts in solar data to increase the return of investment from NASA missions;
  4. Incorporate model-predicted solar drivers into heliophysics simulations to increase the space weather forecast lead time from tens of minutes to several days; and
  5. 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