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:
- study the properties in 3D of objects of the solar atmosphere (filaments, sunspots…),
- model their evolutions and behaviors,
- 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
- use these new insights to predict the events of solar activity and their effects on Earth.
![](https://presage.lis-lab.fr/wp-content/uploads/2022/12/image-1.png)
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.