Intense Auroral Activity (HILDCAAs) Observation as a Predictor of Radiation Belt Relativistic Electrons

Abstract:

Relativistic (E > 0.6, > 2.0, and > 4.0 MeV) electrons at geosynchronous orbit during solar cycle 23 are well-correlated with the intervals of high-intensity, long-duration, continuous AE activity (HILDCAA) events. Cluster-4 passes were examined for electromagnetic chorus waves in the 5 < L < 10 and 0 < MLT < 12 region. All the HILDCAA events under study were found to be characterized by enhanced whistler-mode chorus waves and flux enhancements of magnetospheric relativistic electrons of all three energies compared to the pre-event flux levels. CIR magnetic storms followed by HILDCAA events show almost the same relativistic electron signatures. It is concluded that the CIR storms have little to do with the acceleration of relativistic electrons. The response of the energetic electrons to HILDCAAs was found to vary with solar cycle phase. The initial electron fluxes were lower for events occurring during the ascending and solar maximum (AMAX) phases than for events occurring during the descending and solar minimum (DMIN) phases. The flux increases for the DMIN-phase events were > 50% larger than for the AMAX-phase events. It is concluded that electrons are accelerated to relativistic energies most often and most efficiently during the DMIN-phases of the solar cycle. Enhanced E > 0.6 MeV electron fluxes at geosynchronous orbit were first detected ~1 day after the statistical onset of HILDCAAs, E > 2.0 MeV electrons after ~1.5 days, and E > 4.0 MeV electrons after ~2.5 days. It is proposed that relativistic electrons are bootstrapped from high energy electrons: the E > 0.6 MeV electrons are accelerated from HILDCAA-injected E ~100 keV electrons, the E > 2.0 MeV electrons from the E > 0.6 MeV electron population, and consequently the E > 4.0 MeV electrons are accelerated from the E > 2.0 MeV population, etc. Relativistic electron acceleration and decay timescales will be provided for wave-particle investigators to attempt to match their models to empirically derived values.