Very Short Range Statistical Forecasting of Automated Weather Observations.

Abstract

A procedure is developed for providing weather forecasting guidance over the short range period of 10, 20, 30, ..., 120 minutes. It uses the Automated Weather Observing System (AWOS) elements as predictors and predictands. The model is founded on Markov assumptions and uses multivariate regression as the statistical operator. Details are given on how the Generalized Exponential Markov (GEM) model compares with persistance. Tests are performed on a test sample of almost 400,000 cases. Overall, GEM succeeds in bettering current short range weather forecasting techniques (i.e. persistence) over the twelve projection periods of 10, 20, 30..., 120 minutes. The ability of GEM to successfully predict VFR to IFR, and IFR to LOW IFR changes in both visibility and ceiling is also demonstrated.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
ADA190803

Entities

People

  • Robert G. Miller

Organizations

  • National Weather Service

Tags

Communities of Interest

  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Atmospheric Sciences
  • Cloud Cover
  • Computers
  • Data Analysis
  • Detectors
  • Dew Point
  • Equations
  • False Alarms
  • Plastic Explosives
  • Probability
  • Regression Analysis
  • Statistics
  • Tensile Strength
  • Test And Evaluation
  • Weather Forecasting
  • Wind Direction

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Mathematics or Statistics
  • Statistical inference.