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Abstract A radial diffusion model directly driven by the solar wind is developed to reproduce MeV electron variations between L=2-12 (L is L* in this study) from October 2012 to April 2015. The radial diffusion coefficient, internal source rate, quick loss due to EMIC waves, and slow loss due to hiss waves are all expressed in terms of the solar wind speed, dynamic pressure, and interplanetary magnetic field (IMF). The model achieves a prediction efficiency (PE) of 0.45 at L=5 and 0.51 at L=4 after converting the electron phase space densities to differential fluxes and comparing with Van Allen Probes measurements of 2 MeV and 3 MeV electrons at L=5 and L=4, respectively. Machine learning techniques are used to tune parameters to get higher PE. By tuning parameters for every 60-day period, the model obtains PE values of 0.58 and 0.82 at L=5 and L=4, respectively. Inspired by these results, we divide the solar wind activity into three categories based on the condition of solar wind speed, IMF Bz, and dynamic pressure, and then tune these three sets of parameters to obtain the highest PE. This experiment confirms that the solar wind speed has the greatest influence on the electron flux variations, particularly at higher L, while the dynamic pressure has more influence at lower L. Also, the PE at L=4 is mostly higher than those at L=5, suggesting that the electron loss due to the magnetopause shadowing combined with the outward radial diffusion is not well captured in the model. This article is protected by copyright. All rights reserved.
Published by: Journal of Geophysical Research: Space Physics Published on: 05/2021
YEAR: 2021   DOI: https://doi.org/10.1029/2020JA028988