Auroral Electron Energy and Flux from Molecular Nitrogen Ultraviolet Emissions Observed by the S3-4 Satellite

Abstract

The UV spectra over the southern hemisphere nightside auroral oval have been obtained from an AFGL spectral/photometric experiment on board the low-altitude polar-orbiting S3-4 satellite. A detailed analysis of nightside auroral spectra from seven orbits between mid-May and June 1978 was performed to estimate the average energy and total energy flux of incident electrons. This study was based on observations of the N2 LBH (3-10) (1928-A) band and the N2 VK (0-5) (2604 A) band emission intensities and the application of model calculations. Comparison of the estimated quantities with the statistical satellite measurement of incident particles indicates that the LBH (3-10) band emission intensity can be used to estimate the total energy flux of incident electrons, similar to the N2(+) 1N (0-0) (3914 A) band emission intensity in the visible region. In addition, the ratio of the LBH (3-10) to the VK (0-5) bande mission intensities indicates the average energy of incident auroral electrons in much the same way that the N2(+)1N (0-0) and O I (6300 A) emission ratio does in the visible region. This study shows the use of different constituent emissions, model calculations, and synthetic spectra to infer the inherent possibilities in these types of studies. Reprints. (jhd)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 29, 1989
Accession Number
ADA212017

Entities

People

  • C.-i. Meng
  • G. J. Romick
  • M. Ishimoto
  • R. E. Huffman

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Altitude
  • Artificial Satellites
  • Classification
  • Demography
  • Electron Energy
  • Emission
  • Energy Levels
  • Hemispheres
  • Intensity
  • K Band
  • Low Altitude
  • Measurement
  • Nitrogen
  • Particles
  • Southern Hemisphere
  • Spectra

Fields of Study

  • Physics

Readers

  • Molecular Photonics/Laser Physics
  • Space/Atmospheric Physics.

Technology Areas

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