O3: Innovative Solutions 

under development

Moderator:

Irina Kitiashvili, (NASA/ARC, USA), irina.n.kitiashvili@nasa.gov

Co-Moderator: 

Sophie Murray (Trinity College Dublin, Ireland), Sophie.Murray@tcd.ie

This overarching activity utilizes new technologies and approaches aiming to advance space weather understanding, modeling and forecasting capabilities. Current revolutionary technological developments allow us to observe the solar dynamics with high spatial and temporal resolutions in a wide range of wavelength, and get access to computational resources, which enable high-fidelity modeling and data analysis. Simultaneously, increasing data flows challenge us to search for new approaches for comprehensive multi-dimensional data analyses. The Innovative Solutions cluster is aiming to crystalize interlinks between mathematical modeling, observational data analysis, and computational and observing technologies.

This overarching activity includes:

  • Utilization of existing and emerging data science approaches (e.g., artificial intelligence (AI), machine learning (ML)  methods, data mining, and big data solutions);
  • Development of next generation simulation codes;
  • Exploring innovative approaches for performing multiscale modeling and observational data synthesis;
  • Stimulating solutions for cross-analysis observational data from various sources;
  • Facilitating innovations for synergetic analysis and modeling approaches, such as data assimilation and ensemble and data-driven modeling;
  • Designing, development and deployment of new instrumentation (e.g., small satellites, ground-based networks, new instrumentation concepts).

Action topics:

  • Improve space weather modeling and prediction capabilities through the implementation of data assimilation approach, ensemble-type modeling, machine learning methods, and others.
  • Develop technology for efficient integration of different observational data in a comprehensive description of solar activity processes.
  • Understand how advanced data and scientific methods (e.g., deep learning, clustering analysis, etc.) can improve our forecasting capabilities and expand our comprehension of space weather processes
  • Stimulate the development of technologies for physics-based ML and AI methods and algorithms
  • Improve the performance of space weather models by the implementation of new digital technologies and utilization of high performance computing (HPC) capabilities. Investigate the possibility of utilizing quantum computing capabilities.
  • Facilitate the development of new instrumentation concepts.
  • Stimulate new approaches for collaborative developments and enhance accessibility to models and observational data.

This cluster will work in close partnership with upcoming COSPAR Panel on Innovative Solutions.