loading page

Radiation belt model including semi-annual variation and Solar driving (Sentinel)
  • +3
  • Christos Katsavrias,
  • Sigiava Aminalragia-Giamini,
  • Constantinos Papadimitriou,
  • Ioannis A. Daglis,
  • Ingmar Sandberg,
  • Piers Jiggens
Christos Katsavrias
University of Athens

Corresponding Author:[email protected]

Author Profile
Sigiava Aminalragia-Giamini
Space Applications and Research Consultancy
Author Profile
Constantinos Papadimitriou
National Observatory of Athens
Author Profile
Ioannis A. Daglis
National and Kapodistrian University of Athens
Author Profile
Ingmar Sandberg
Space Applications and Research Consultancy
Author Profile
Piers Jiggens
European Space Agency
Author Profile


The Earth’s outer radiation belt response to geospace disturbances is extremely variable spanning from a few hours to several months. In addition, the numerous physical mechanisms, which control this response, depend on the electron energy, the time-scale and the various types of geospace disturbances. As a consequence, the various models that currently exist are either specialized, orbit-specific data-driven models, or sophisticated physics-based ones. In this paper we present a new approach for radiation belt modelling using Machine Learning methods driven solely by solar wind speed and pressure, Solar flux at 10.7 cm and the $\theta$ angle controlling the Russell-McPherron effect. We show that the model can successfully reproduce and predict the electron fluxes of the outer radiation belt in a broad energy (0.033–4.062 MeV) and L-shell (2.5–5.9) range and, moreover, it can capture the long-term modulation of the semi-annual variation. We also show that the model can generalize well and provide successful predictions, even outside of the spatio-temporal range it has been trained with, using >0.8 MeV electron flux measurements from GOES-15/EPEAD at geostationary orbit.
Jan 2022Published in Space Weather volume 20 issue 1. 10.1029/2021SW002936