Welcome to the PRESAGE project!
PRESAGE stands for PREdicting Solar Activity using machine learning on heteroGEneous data.

We are a team of data scientists and solar physicists that work together at developing new machine learning methods that support a deeper understanding of the mechanisms of solar activity in order to predict its events. The solar physics community is currently facing a deluge of data, which is too widely varied and complex to allow an overall analysis leading to a global understanding of solar activity. We propose to solve this problem by developing new machine learning algorithms that exploit these heterogeneous data, to:

  1. study the properties in 3D of objects of the solar atmosphere (filaments, sunspots…),
  2. model their evolutions and behaviors,
  3. study the correlations between many indicators of solar activity (inc. solar objects and their behaviors), solar activity events (flares, CMEs…), and their resulting terrestrial impacts (geomagnetic indices…), and
  4. use these new insights to predict the events of solar activity and their effects on Earth.

We are based at LIS in the DYNI team (Université de Toulon) and LESIA (Paris Observatory).

The project is funded by an ANR JCJC grant ANR-20-CE23-0014 for 4 years from September 2021.