Forecasting High-Energy Proton and Electron Fluxes at LEO Orbits

Satellites in LEO orbit are exposed to high energy radiation, more so on account of geomagnetic storms which exacerbate harmful space environmental effects. For example, high energy radiation belt photons cause ionization effects and displacement damage effects – harmful for opto-electronic technologies, while high energy electrons contribute to deep dielectric charging and discharging resulting in performance degradation of electronic equipment and computer bit flips. In this study we employ information theoretic measures in parallel with machine learning for time series data techniques to make a 2-4 day ahead forecast of the energy fluxes of high energy protons and electrons averaged over L-shells L2 – L4. First, we recast storm times in terms of the new composite magnetospheric activity index: the whole-Earth index E(1) proposed by Borovsky and Lao (2023) in place of the traditionally used solitary Dst or Kp indices. Secondly, we access mutual information between combinations of upstream solar wind variables and magnetospheric indices to arrive at a set of parameters that can separate storm times from quiet times. Finally, with these assessments, we compare with results output by several architectures of neural networks.