Van Allen radiation belt electron dynamics are governed by a wide range of physical processes that can simultaneously drive acceleration, transport and loss. However, each individual process can be linked to a specific energy-dependent pitch angle distribution (PAD). We employ a new, unsupervised machine learning technique on 7-years of Van Allen Probe Relativistic Electron-Proton Telescope data and discover that six PADs, two each of: pancake, butterfly, and flattop, successfully describe >70% of classified relativistic PADs. We investigate the occurrence and storm-time evolution of each PAD through 45 geomagnetic storms. We find new populations of PADs, including: “shadowing-like” and wave-particle interaction signatures at low-L, and radial diffusion and substorm injections at higher-L, as well as determining that wave-particle interaction dominated PADs are swamped by radial diffusion processes through geomagnetic storms. Our results clearly demonstrate that PAD characterisation is a key component of understanding Van Allen radiation belt electron dynamics

Atmospheric neutral density is a crucial component to accurately predicting and tracking the motion of satellites. During periods of elevated solar and geomagnetic activity atmospheric neutral density becomes highly variable and dynamic. This variability and enhanced dynamics make it difficult to accurately model neutral density leading to increased errors which propagate from neutral density models through to orbit propagation models. In this paper we investigate the dynamics of neutral density during geomagnetic storms. We use a combination of solar and geomagnetic variables to develop three Random Forest machine learning models of neutral density. These models are based on (1) slow solar indices, (2) high cadence solar irradiance, and (3) combined high-cadence solar irradiance and geomagnetic indices. During quiet-times all three models perform well; however, during geomagnetic storms the combined high cadence solar iradiance/geomagnetic model performs significantly better than the models based solely on solar activity. Overall, this work demonstrates the importance of including geomagnetic activity in the modeling of atmospheric density and serves as a proof of concept for using machine learning algorithms to model, and in the future forecast atmospheric density for operational use.

Waves which couple to energetic electrons are particularly important in space weather, as they drive rapid changes in the topology and intensity of Earth’s outer radiation belt during geomagnetic storms. This includes Ultra Low Frequency (ULF) waves that interact with electrons via radial diffusion which can lead to electron dropouts and rapid acceleration and inward transport of electrons during. In radiation belt simulations, the strength of this interaction is specified by ULF wave radial diffusion coefficients. In this paper we detail the development of new models of electric and magnetic radial diffusion coefficients derived from in-situ observations of the azimuthal electric field and compressional magnetic field. The new models use L* as it accounts for adiabatic changes due to the dynamic magnetic field coupled with an optimized set of four components of solar wind and geomagnetic activity, Bz, V, Pdyn and Sym-H, as independent variables (inputs). These independent variables are known drivers of ULF waves and offer the ability to calculate diffusion coefficients at a higher cadence then existing models based on Kp. We investigate the performance of the new models by characterizing the model residuals as a function of each independent variable and by comparing to existing radial diffusion models during a quiet geomagnetic period and through a geomagnetic storm. We find that the models developed here perform well under varying levels of activity and have a larger slope or steeper gradient as a function of L* as compared to existing models (higher radial diffusion at higher L* values).

We investigate the effects of intense chorus waves (wave power > 10-4 nT2) on relativistic electrons (E > 0.5 MeV) in the heart of the outer radiation belt (L* = 4 - 6) using superposed epoch approach. Combining electron flux and electromagnetic wave measurements from 70 geomagnetic storms during the Van Allen Probes mission, we show the relationship between integrated chorus wave power (0.1 - 0.8 equatorial electron gyrofrequency) and changes in relativistic electron flux on two hour timescales. During the loss-dominated storm main phase (Superposed Epoch -0.5 to 0 days), intense chorus waves mitigate the net loss of relativistic electrons. Conversely, in the early recovery phase (Superposed epoch 0 to 0.5 days), flux increases across a range of relativistic energies regardless of chorus wave power. The amount of electron flux at keV energies appears to have an influence on the consequences of chorus wave activity during geomagnetic storms.

The generation and propagation of Ultra Low Frequency (ULF) waves are intrinsically coupled to the cold plasma population in the terrestrial magnetosphere. During geomagnetic storms, extreme reconfigurations of the cold plasma creates a complex and dynamic system that drastically modifies this coupling. The extent and manner in which this coupling is affected remains an open question. In this report, we assess the coupling between ULF waves and cold plasmaspheric plumes during geomagnetic storms, and investigate the implications for ULF wave-driven radial transport of the outer radiation belt population. We present a series of event studies of Van Allen Probes observations. For each event, we use inferred measurements of the cold plasma density during plume crossings, in combination with magnetic and electric field observations of ULF waves. The event studies show very different, and at times contrasting, wave behaviour. This includes events where ULF waves appear to be spatially confined within plume structures. Initial estimates show that the localised patches of ULF wave power have significant implications for radial diffusion processes, and highlights the need for caution in estimating radial diffusion coefficients. We suggest that the cold plasma dynamics is an important source of uncertainty in radial diffusion models, and understanding cold plasma-ULF wave coupling is a critical area of future investigations.

We analyzed the contribution of electromagnetic ion cyclotron (EMIC) wave driven electron loss to a flux dropout event in September 2017. The evolution of electron phase space density (PSD) through the dropout showed the formation of a radially peaked PSD profile as electrons were lost at high L*, resembling distributions created by magnetopause shadowing. By comparing 2D Fokker Planck simulations of pitch angle diffusion to the observed change in PSD, we found that the μ and K of electron loss aligned with maximum scattering rates at dropout onset. We conclude that, during this dropout event, EMIC waves produced substantial electron loss. Because pitch angle diffusion occurred on closed drift paths near the last closed drift shell, no radial PSD minimum was observed. Therefore, the radial PSD gradients resembled solely magnetopause shadowing loss, even though the local pitch angle scattering produced electron losses of several orders of magnitude of the PSD.

Loss mechanisms act independently or in unison to drive rapid loss of electrons in the radiation belts. Electrons may be lost by precipitation into the Earth’s atmosphere, or through the magnetopause into interplanetary space; a process known as magnetopause shadowing. Whilst magnetopause shadowing is known to produce dropouts in electron flux, it is unclear if shadowing continues to remove particles in tandem with electron acceleration processes, limiting the overall flux increase. We investigated the contribution of shadowing to overall radiation belt fluxes throughout a geomagnetic storm starting on the 7 September 2017. We use new, multi-spacecraft phase space density calculations to decipher electron dynamics during each storm phase and identify features of magnetopause shadowing during both the net-loss and the net-acceleration storm phases. We also highlight two distinct types of shadowing; ‘direct’, where electrons are lost as their orbit intersects the magnetopause, and ‘indirect’, where electrons are lost through ULF wave driven radial transport towards the magnetopause boundary.