Statistical Inference of Cloud Thickness from NOAA IV Scanning Radiometer Data.

Abstract

A statistical correlation between cloud thickness and brightness is shown by regression analyses using the least square method. Cloud thickness are obtained from two sources; pilot reports and the Three-Dimensional Nephanalysis (3DNEPH) program for cases of single stratus and strato-cumulus layers. Brightness values are obtained from the NOAA IV satellite scanning radiometer. Regression analyses are performed on both thickness data sources used in conjunction with the scanning radiometer data. The results are shown by the regression curve relating pilot report thicknesses and brightness accounting for 66% (R sq = 0.66) of the variance between the variables, and the regression curve relating 3DNEPH thicknesses and brightness accounting for 46% (R sq = 0.46) of the variance between the variables. Moreover, in view of the effect of cloud compositions on the cloud brightness, regression analyses are performed on both thickness data sources excluding those cases whose origin is an unstable maritime tropical air mass. Results of these regression analyses reveal increases in the correlation between cloud thickness and brightness with 88% and 55% of the variances accounted for pilot reports and 3DNEPH program data sources, respectively. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 05, 1976
Accession Number
ADA031160

Entities

People

  • Kuo-nan Liou
  • Robert Feddes
  • William J. Kaveney

Organizations

  • University of Utah

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  • Space

DTIC Thesaurus Topics

  • Air Force
  • Computational Science
  • Computer Programs
  • Data Science
  • Databases
  • Great Lakes
  • High Pressure
  • Information Science
  • Least Squares Method
  • Measurement
  • Meteorological Satellites
  • New England
  • Regression Analysis
  • Ridges
  • Statistical Analysis
  • Three Dimensional
  • United States

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  • Atmospheric Science/Meteorology
  • Regression Analysis.
  • Spectroscopy.

Technology Areas

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