[1] Thirty years ago Paulikas and Blake (1979) showed a remarkable correlation between geosynchronous relativistic electron fluxes and solar wind speed (Vsw). This seminal result has been a foundation of radiation belt studies, space weather forecasting, and current understanding of solar wind radiation belt coupling. We have repeated their analysis with a considerably longer-running data set from the Los Alamos National Laboratory energetic particle instruments with several surprising results. Rather than the roughly linear correlation between Vsw and log (flux), our results show a triangle-shaped distribution in which fluxes have a distinct velocity-dependent lower limit but a velocity-independent upper limit. The highest-electron fluxes can occur for any value of Vsw with no indication of a Vsw threshold. We also find a distinct solar cycle dependence with the triangle-shaped distribution evident in 2 declining phase years dominated by high-speed streams but essentially no correlation in 2 solar maximum years. For time periods that do show a triangle-shaped distribution we consider whether it can be explained by scatter due to other parameters. We examine the role of time dependence and time lag in producing the observed distribution. We also look at the same statistical relationship but at energies 1 MeV. We conclude that the relationship between radiation belt electron fluxes and solar wind velocity is substantially more complex than suggested by previous statistical studies. We find that there are important ways in which the "conventional wisdom" stating that high-velocity wind drives high-MeV electron fluxes is, in general, either misleading or unsupported.

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.

The DREAM3D diffusion model is applied to Van Allen Probes observations of the fast dropout and strong enhancement of MeV electrons during the October 2012 "double-dip" storm. We show that in order to explain the very different behavior in the two "dips," diffusion in all three dimensions (energy, pitch angle, and L * ) coupled with data-driven, event-specific inputs, and boundary conditions is required.Specifically, we find that outward radial diffusion to the solar wind-driven magnetopause, an event-specific chorus wave model, and a dynamic lower-energy seed population are critical for modeling the dynamics.In contrast, models that include only a subset of processes, use statistical wave amplitudes, or rely on inward radial diffusion of a seed population, perform poorly. The results illustrate the utility of the high resolution, comprehensive set of Van Allen Probes' measurements in studying the balance between source and loss in the radiation belt, a principal goal of the mission.

We present dynamic simulations of energy‐dependent losses in the radiation belt “slot region” and the formation of the two‐belt structure for the quiet days after the 1 March storm. The simulations combine radial diffusion with a realistic scattering model, based data‐driven spatially and temporally resolved whistler‐mode hiss wave observations from the Van Allen Probes satellites. The simulations reproduce Van Allen Probes observations for all energies and L shells (2–6) including (a) the strong energy dependence to the radiation belt dynamics (b) an energy‐dependent outer boundary to the inner zone that extends to higher L shells at lower energies and (c) an “S‐shaped” energy‐dependent inner boundary to the outer zone that results from the competition between diffusive radial transport and losses. We find that the characteristic energy‐dependent structure of the radiation belts and slot region is dynamic and can be formed gradually in ~15 days, although the “S shape” can also be reproduced by assuming equilibrium conditions. The highest‐energy electrons (E > 300 keV) of the inner region of the outer belt (L ~ 4–5) also constantly decay, demonstrating that hiss wave scattering affects the outer belt during times of extended plasmasphere. Through these simulations, we explain the full structure in energy and L shell of the belts and the slot formation by hiss scattering during storm recovery. We show the power and complexity of looking dynamically at the effects over all energies and L shells and the need for using data‐driven and event‐specific conditions.