Understanding Extreme Radiation Belt Electron Dropout During the May 2024 Superstorm

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Abstract
The geomagnetic storm in May 2024 represents the most extreme space weather event over the past twenty years, providing a unique opportunity to investigate energetic particle dynamics under exceptionally strong solar wind driving conditions. Among the various particle populations affected by such extreme storms, outer radiation belt electrons are of particular interest because they respond rapidly to storm-time magnetospheric reconfigurations and pose significant hazards to satellites operating in near-Earth space.Observations from the Arase satellite reveal that MeV radiation belt electron fluxes dropped by several orders of magnitude during the main phase of the May 2024 superstorm. This extreme dropout coincided with intense magnetopause compression to a minimum standoff distance of L~3.7, estimated using the Space Weather Modeling Framework, and enhanced ultra-low-frequency (ULF) Pc5 wave activity derived from SuperMAG. To investigate the physical mechanisms controlling this extreme electron loss, we performed simulations using the Versatile near‐Earth environment of Radiations Belts and ring current (VERB) model, systematically examining the roles of magnetopause shadowing, radial diffusion, and local wave-driven scattering.We find that commonly used empirical radial diffusion models, parameterized by Kp, fail to reproduce the observed electron flux profiles during this event. Instead, accurately capturing the extreme electron dropout requires that enhanced radial diffusion be properly timed relative to magnetopause compression and storm-time wave activity. In addition, stronger plasmaspheric hiss scattering is necessary to reproduce losses at lower L*. These results demonstrate that extreme radiation belt electron dropout during superstorms is controlled by the coupled timing of magnetopause compression, radial diffusion, and local scattering processes, emphasizing the importance of physically timed transport and loss representations in extreme storm modeling.