Henri Lamarre

l’Université de Montréal

Solar flares are events triggered by magnetic reconnection in the magnetic field, which encompasses the solar corona and extends into its photosphere. The Earth’s magnetic field stops the majority of particles emitted by solar flares which reach the Earth. Thus, these eruptions do generally not directly affect humans. However, in the case of significant solar eruptions, the ejected particles can penetrate the terrestrial magnetic field and affect humans and our terrestrial infrastructure. In effect, these events pose a severe danger to the safety of our astronauts, cause lasting damage to our electrical grid on Earth, and scramble satellite communications.

Therefore, correctly predicting significant solar eruptions remains an active research field for several decades. However, the current models are not yet trustworthy. Most models do not predict the flares better than the static mean of the frequency of the flares. The solar flares have much in common with avalanches since they are both characterized by the accumulation of energy over a considerable period followed by a rapid outburst of this energy covering a vast range of characteristic scales. Moreover, other systems, such as seismic events or forest fires, share similar characteristics. Thus, network models have shown great promise in modeling types of phenomena and predicting their occurrence. The network models calculate the twisting of the magnetic field in the coronal loops to produce magnetic reconnections, thus modeling solar flares.

My project is to predict solar flare events using data assimilation techniques coupled with avalanche models. This methodology was established by Strugarek et al. 2014 and has undergone several tests (Thibeault et al. 2022). The idea, thus, is to build upon this existing protocol an operation system of prediction for intense solar flares.

Co-direction: Paul Charbonneau (Université de Montréal) et Antoine Strugarek (CEA Paris-Saclay)