Inner Belt Wisp Precipitation Measured by ELFIN: Regimes of Energetic Electron Scattering by VLF Transmitter Waves

Abstract

Man‐made very low frequency (VLF) transmitter waves play a critical role in energetic electron scattering and precipitation from the inner radiation belt, a type of which is called wisp precipitation. Wisps exhibit dispersive energy‐versus‐L spectra due to the evolution of electron cyclotron resonance conditions with near‐monochromatic VLF transmitter waves. Here, we report on such observations of inner belt wisp precipitation events with full pitch angle resolution in the energy range of 50 to ∼500 keV as measured by Electron Loss and Fields Investigation (ELFIN) at L −4 to 10−2 s−1. These are several orders of magnitude larger than the diffusion rates calculated from models using global statistical averages of VLF transmitter wave power. When using our estimated diffusion coefficients to deduce the associated local transmitter wave amplitudes near the equator, based on quasilinear calculations from a transmitter‐induced electron diffusion model, we find these wave amplitudes to be >1 mV/m. Although probable overestimates, such inferred wave amplitudes exceed the theoretical threshold amplitude for nonlinear interactions, strongly suggesting that it is necessary to include nonlinear effects for an accurate evaluation of energetic electron scattering by transmitter waves.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 01, 2022
Source ID
10.1029/2022ja030968

Entities

People

  • Anton V. Artemyev
  • Colin Wilkins
  • D. Mourenas
  • Ethan Tsai
  • J. Wu
  • Qianli Ma
  • Vassilis Angelopoulos
  • Xiao‐jia Zhang
  • Yangyang Shen

Organizations

  • Air Force Office of Scientific Research
  • Boston University
  • National Aeronautics and Space Administration
  • National Science Foundation
  • Paris-Saclay University
  • University of California, Los Angeles
  • University of Texas at Dallas

Tags

Fields of Study

  • Physics

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Plasma Physics / Magnetohydrodynamics
  • Space/Atmospheric Physics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Microelectronics