Modeling for Atmospheric Background Radiance Structures

Abstract

Atmospheric infrared radiance fluctuations result from fluctuations in the density of atmospheric species, individual molecular state populations, and kinetic temperatures and pressures along the sensor line of sight (LOS). The SHARC-4 program models the atmospheric background radiance fluctuations. It predicts a two dimensional radiance spatial covariance function from the underlying 3D atmospheric structures. The radiance statistics are non-stationary and are dependent on bandpass, sensor location and field of view (FOV). In the upper atmosphere non-equilibrium effects are important Fluctuations in kinetic temperature can result in correlated or anti-correlated fluctuations in vibrational state temperatures. The model accounts for these effects and predicts spatial covariance functions for molecular state number densities and vibrational temperatures. SHARC predicts the non-equilibrium dependence of molecular state number density fluctuations on kinetic temperature and density fluctuations, and calculates mean LOS radiances and radiance derivatives. The modeling capabilities are illustrated with sample predictions of MSX like experiments with MSX sensor bandpasses, sensor locations and FOV. The model can be applied for all altitudes and arbitrary sensor FOV including nadir and limb viewing.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1995
Accession Number
ADA638003

Entities

People

  • James Brown
  • James W. Duff
  • John Gruninger
  • Ramesh Sharma
  • Robert D. Sears
  • Robert L. Sundberg

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Adaptive Systems
  • Altitude
  • Atmospheres
  • Atmospheric Sciences
  • Chemical Kinetics
  • Covariance
  • Energy Transfer
  • Engineering
  • Information Operations
  • Line Of Sight
  • Radiance
  • Stationary
  • Statistics
  • Steady State
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Sensor Fusion and Tracking Systems.
  • Spectroscopy.