Quantification of the precipitation loss of radiation belt electrons observed by SAMPEX
Journal Article
Overview
abstract
Based on SAMPEX/PET observations, the rates and the spatial and temporal variations of electron loss to the atmosphere in the Earth's radiation belt were quantified using a drift diffusion model that includes the effects of azimuthal drift and pitch angle diffusion. The measured electrons by SAMPEX can be distinguished as trapped, quasi‐trapped (in the drift loss cone), and precipitating (in the bounce loss cone). The drift diffusion model simulates the low‐altitude electron distribution from SAMPEX. After fitting the model results to the data, the magnitudes and variations of the electron lifetime can be quantitatively determined based on the optimum model parameter values. Three magnetic storms of different magnitudes were selected to estimate the various loss rates of ∼0.5–3 MeV electrons during different phases of the storms and at L shells ranging from L = 3.5 to L = 6.5 (L represents the radial distance in the equatorial plane under a dipole field approximation). The storms represent a small storm, a moderate storm from the current solar minimum, and an intense storm right after the previous solar maximum. Model results for the three individual events showed that fast precipitation losses of relativistic electrons, as short as hours, persistently occurred in the storm main phases and with more efficient loss at higher energies over wide range of L regions and over all the SAMPEX‐covered local times. In addition to this newly discovered common feature of the main phase electron loss for all the storm events and at all L locations, some other properties of the electron loss rates, such as the local time and energy dependence that vary with time or locations, were also estimated and discussed. This method combining model with the low‐altitude observations provides direct quantification of the electron loss rate, a prerequisite for any comprehensive modeling of the radiation belt electron dynamics.
