Retrieval of Ballistic Densities and Layer Thicknesses from Satellite Radiance Observations.

Abstract

The general objective of this work is to develop and evaluate techniques for determining atmospheric parameters in meteorologically 'silent' areas from satellite radiance observations. A non-statistical method for obtaining ballistic densities directly from satellite radiance observations is derived. The method takes advantage of the fact that both the ballistic density and the satellite radiances depend upon weighted vertical integrals of the atmospheric temperature. Tests of this method on realistically simulated radiances indicate root-mean-square retrieval errors of 1/4 to 1/3 of the standard deviation of ballistic density for individual months. The method thus appears to be suitable for application to areas of the globe with a paucity of conventional radiosonde observations. Fleming's direct inversion method for retrieving layer thicknesses is evaluated on a set of realistically simulated satellite radiances. Results indicate that there is no significant advantage to be gained by using the previous day's temperature profile rather than a monthly mean temperature profile for the geographical area as the standard profile required by the method. This result, together with the relatively low retrieval errors obtained with the method, suggest that it would be appropriate for use in meteorologically silent areas.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1977
Accession Number
ADA047098

Entities

People

  • Dina Goldberg
  • Eliram Broida
  • George Ohring

Organizations

  • Tel Aviv University

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Satellites
  • Atmospheric Sciences
  • Atmospheric Temperature
  • Boundaries
  • Integrals
  • Inversion
  • Measurement
  • Observation
  • Planetary Sciences
  • Radiosondes
  • Simulations
  • Spacecraft
  • Standards
  • Statistics
  • Surface Temperature
  • United States

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Regression Analysis.

Technology Areas

  • Space