Evaluation of the AFGL (Air Force Geophysics Laboratory) Cloud Simulation model

Abstract

This report documents progress in validating two empirical models of the distribution of total sky cover over lines and areas. The Burger Area Algorithm (BAA), as applied to sky cover, is a mathematical model of the probability that fraction C or less of area A is covered by clouds, given scale length r and mean clear pO (one minus the mean sky cover). The Burger Line Algorithm (BLA) is similar except it gives the probability of linear coverage rather than areal coverage. The validation procedure adopted relies on sky cover distributions over lines and areas of various sizes at three U.S. sites representative of several homogeneous climatic regions. The distributions will be obtained empirically from satellite imagery. The six tasks identified are: 1) Select test areas; 2) Determine sample sizes; 3) Acquire satellite imagery; 4) Develop cloud detection and analysis algorithms; 5) Create a sky cover database; and 6) Determine error bounds for the BAA and BLA models. This report discusses the output of Task 1 through 4 which are currently complete (April 1985). The methodology employed during Task 2 (Monte Carlo simulation of the validation process) is described in detail.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1987
Accession Number
ADA203542

Entities

People

  • Gary Rasmussen
  • Paul Janota
  • Ralph Ferraro

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computational Science
  • Data Science
  • Data Sets
  • Databases
  • Detection
  • Goodness Of Fit Tests
  • Information Processing
  • Information Science
  • Mathematical Models
  • Monte Carlo Method
  • Probability
  • Satellite Imaging
  • Simulations
  • Statistical Algorithms
  • Statistics

Readers

  • Atmospheric Science/Meteorology
  • Computer Vision.
  • Statistical inference.

Technology Areas

  • Space