Modeling radiation belt electron dynamics during GEM challenge intervals with the DREAM3D diffusion model

Abstract

As a response to the Geospace Environment Modeling (GEM) “Global Radiation Belt Modeling Challenge,” a 3D diffusion model is used to simulate the radiation belt electron dynamics during two intervals of the Combined Release and Radiation Effects Satellite (CRRES) mission, 15 August to 15 October 1990 and 1 February to 31 July 1991. The 3D diffusion model, developed as part of the Dynamic Radiation Environment Assimilation Model (DREAM) project, includes radial, pitch angle, and momentum diffusion and mixed pitch angle‐momentum diffusion, which are driven by dynamic wave databases from the statistical CRRES wave data, including plasmaspheric hiss, lower‐band, and upper‐band chorus. By comparing the DREAM3D model outputs to the CRRES electron phase space density (PSD) data, we find that, with a data‐driven boundary condition at Lmax = 5.5, the electron enhancements can generally be explained by radial diffusion, though additional local heating from chorus waves is required. Because the PSD reductions are included in the boundary condition at Lmax = 5.5, our model captures the fast electron dropouts over a large L range, producing better model performance compared to previous published results. Plasmaspheric hiss produces electron losses inside the plasmasphere, but the model still sometimes overestimates the PSD there. Test simulations using reduced radial diffusion coefficients or increased pitch angle diffusion coefficients inside the plasmasphere suggest that better wave models and more realistic radial diffusion coefficients, both inside and outside the plasmasphere, are needed to improve the model performance. Statistically, the results show that, with the data‐driven outer boundary condition, including radial diffusion and plasmaspheric hiss is sufficient to model the electrons during geomagnetically quiet times, but to best capture the radiation belt variations during active times, pitch angle and momentum diffusion from chorus waves are required.

Quantifying the effect of magnetopause shadowing on electron radiation belt dropouts

“…Results indicate that during the small but representative storm events, the drift loss to the magnetopause (i.e, magnetopause shadowing) together with outward radial diffusion is mainly responsible for the electron loss, contributing approximately 93-99 % of the total loss near the geosynchronous orbit (L * > 5.0), but with the inner region (L * ≤ 5.0) requiring some additional loss mechanisms (only 60 % can be explained by the above coupled mechanism). Future studies will be directed to quantify relative contributions of other individual or mixed loss mechanisms, such as pitch angle and energy diffusions, which can be included within multidimensional models to represent wave-particle interactions (e.g., Beutier and Boscher, 1995;Albert et al, 2009;Su et al, 2010;Subbotin et al, 2010;Tu et al, 2013).…”

The distribution of plasmaspheric hiss wave power with respect to plasmapause location

“…Pitch angle scattering due to particle interactions with hiss waves leads to precipitation to the atmosphere (loss) of electrons over a wide range of energies, from tens of keV to over 1 MeV (see Millan and Thorne [2007] for a review). The role of hiss in radiation belt evolution is significant enough that predictive simulations of the inner magnetosphere and terrestrial radiation belts use statistical hiss wave power distributions as input [Shprits et al, 2008;Subbotin and Shprits, 2009;Fok et al, 2011;Tu et al, 2013;Horne et al, 2013]. The role of hiss in radiation belt evolution is significant enough that predictive simulations of the inner magnetosphere and terrestrial radiation belts use statistical hiss wave power distributions as input [Shprits et al, 2008;Subbotin and Shprits, 2009;Fok et al, 2011;Tu et al, 2013;Horne et al, 2013].…”

Three‐dimensional stochastic modeling of radiation belts in adiabatic invariant coordinates

“…Quasi-linear diffusion theory has been formulated to quantify the nonadiabatic changes of energetic electron fluxes, and diffusion models that are based on solving an electron Fokker-Planck equation have been developed [e.g., Albert et al, 2009;Subbotin et al, 2010;Subbotin and Shprits, 2012;Fok et al, 2008;Varotsou et al, 2008;Tao et al, 2008Tao et al, , 2009Tu et al, 2009Tu et al, , 2013Camporeale et al, 2013a;Glauert et al, 2014]. Typically, solving the Fokker-Planck equation involves using a numerical grid and finite-difference methods.…”