Local Forecasting through Extrapolation of GOES Imagery Patterns.

Abstract

An attractive approach to short-range forecasting is to determine cloud motion from a sequence of satellite images and extrapolate the patterns and associated weather into the future. Objective motion vector techniques are available and the forecast procedure can be accomplished by computer. This approach is being evaluated at AFGL and this report presents results of testing motion vector techniques. Tracking and covariance techniques were compared along with winds aloft and persistence (no motion) as controls. A covariance technique had top score, but only slightly better than persistence. Complicating factors and implications to forecasting are discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 23, 1980
Accession Number
ADA089701

Entities

People

  • H. Stuart Muench

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Satellites
  • Automatic
  • Computer Programs
  • Geophysics
  • Geosynchronous Satellites
  • Massachusetts
  • Navigation
  • New England
  • New Hampshire
  • Research Facilities
  • Satellite Imaging
  • Security
  • Stationary
  • Time Intervals
  • United States

Readers

  • Computer Vision.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Regression Analysis.

Technology Areas

  • Space