Statistical investigation on equatorial pitch angle distribution of energetic electrons in Earth’s outer radiation belt during CME- and CIR-driven storms

Abstract

We present a statistical investigation (September 2012 - September 2017) of pitch angle distribution (PAD) of energetic electrons (∼30 keV - 1 MeV) in the outer radiation belt (L ≥ 3) during CME- and CIR-driven geomagnetic storms using Van Allen Probe measurements. We selected geomagnetic storms based on minimum of SYM-H being less than -50 nT and classified the storms according to their drivers. Thus, we obtained 23 CME- and 24 CIR-driven storms. During the storm intervals, pitch angle resolved electron flux measurements are obtained from the MagEIS instrument on-board Van Allen Probe-A spacecraft. We assume symmetric pitch angle distributions around 90° pitch angle and fit the observed PADs with Legendre polynomials after propagating them to the magnetic equator. Legendre coefficients c2 and c4, and the ratio R = |c2/c4| are used to categorize the different PAD types. To resolve the spatio-temporal distribution of PADs, these coefficients are binned in 5 L-shell bins, 12 MLT bins for seven energy channels and four storm phases. We found that several hundreds of keV electrons exhibit clear dependence on local time, storm phases and storm drivers, with increased anisotropy for CME-driven storms during main and early recovery phases. On the contrary, we found that tens of keV electrons do not exhibit significant dependence on these parameters. We have discussed the different physical mechanisms responsible for the observed MLT dependent PADs and found drift-shell splitting to be the major contributor.

Using Machine Learning to Diagnose Relativistic Electron Distributions in the Van Allen Radiation Belts

“…Figure 5a shows the mean flux as a function of PA and E for the first cluster (Cluster 0), which shows evidence of a peaked distribution around 90 degrees, described as a "pancake distribution" (e.g. Chakraborty et al (2022); West et al (1973); Gannon et al (2007); Horne et al (2003)). Figure 5b has a low flux flattop distribution for Cluster 1.…”

“…Figure 5c shows a butterfly-like distribution for Cluster 2 at lower energies (< 2.5 MeV), where there is a reduction of flux at 90 degrees (e.g. Zhao et al (2018); Selesnick & Blake (2002); Chakraborty et al (2022); Gannon et al (2007); West et al (1973)). Cluster 3 (Figure 5d) displays a flattop distribution at lower energies (< 2.5 MeV) where flux plateaus at a constant at pitch angles of approximately 60 to 130 degrees (e.g.…”

“…The behaviour of energetic particles in the Van Allen radiation belts is difficult to diagnose due to their complicated dynamics. At times, radiation belt dynamics can be dominated by a multitude of loss, transport and acceleration processes (Chakraborty et al 2022;Chu et al 2021;Baker et al 2018;Reeves et al 2003;Li & Hudson 2019) including magnetospheric shadowing (e.g., Staples et al (2020); Herrera et al (2016)), and wave-particle interactions (e.g., Artemyev et al (2016); Ripoll et al (2020)) involving pitch angle scattering (e.g., Summers & Thorne (2003); Chaston et al (2018)) and atmospheric precipitation (e.g., Rae et al (2018); Rodger et al (2007)). These different physical processes drive relativistic electron behaviour at different energies and pitch angles, leading to differently shaped energy-dependent pitch angle distributions (PADs).…”

“…These different physical processes drive relativistic electron behaviour at different energies and pitch angles, leading to differently shaped energy-dependent pitch angle distributions (PADs). Hence, PADs are essential in understanding the state of plasma regions (Bakrania et al 2020a) that can have a pancake (peak at 90°), butterfly (electron flux minima at 90°), or flattop (flux plateau over a range of pitch angles centred on 90°) shape (Chakraborty et al 2022;Zhao et al 2018;Souza et al 2016;Gannon et al 2007;Horne et al 2003).…”

“…However, with 20 million observations, it is impossible to reliably identify PADs of similar shape by eye, which likely introduces significant bias to the results. Traditional PAD studies typically pre-define the shape of the distributions a priori (e.g., Liu et al (2020); Ozeke et al (2022); Chakraborty et al (2022)) at given energies. In this work, we adopt a different approach and consider PADs at all energies and without the assumptions of specific PAD shapes.…”