Abstract
CARMEN 2&3 (CARactérisation et Modélisation de l’Environnement ) CNES (Centre National d’ Études Spatiales) missions aim to measure particle fluxes in the radiation belts via ICARE-NG (Influence sur les Composants Avancés des Radiations de l’Espace-Nouvelle Génération) monitor embedded on Low Earth Orbit (LEO) satellites. In this paper we find a projection model of these data onto the elliptical orbit satellite RBSP (Radiation Belt Storm Probes) flux particles levels measurements. The projection is done with a machine learning algorithm. Trained with data from CARMEN missions, the algorithm aims to predict particle flux measured by RBSP. We obtain satisfying results we find a good projection model on a large L* interval (L* = 3.4 - 5.5 for CARMEN 2). While the global trend of the temporal variation of electron flux values is well predicted, the algorithm is not able to predict the suddenness of solar events which produces abrupt slope changes and maxima in the temporal evolution of fluxes.
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