DEVELOPMENT OF STATISTICAL OPERATORS FOR PREDICTION OF LOW CLOUDS

Abstract

A study was made of the statistical prediction of low-cloud amounts and cloudbase heights. Cloud data and other atmospheric parameters over the central and eastern United States were analyzed on a grid mesh of approximately 52 mi (1/4-NWP grid). Predictability of low-cloud amount was evaluated by using the screening regression method and testing the significance of the selected predictors. Predictors considered were low-cloud amount, empirically normalized cloud height, pressure, 850-mb height, surface and 850-mb temperature and dew- point spread, 850-mb geostrophic wind, and derived terms such as vorticity, divergence, and advection. The regression equations were tested on independent data. The equations may be useful for short-period prediction because they provide a better cloud forecast than persistence. They would probably be improved by including other predictors and by extending the area from which the predictors are chosen.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1963
Accession Number
AD0414449

Entities

People

  • Abraham M. Pavlowitz
  • Duane S. Cooley

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aircrafts
  • Cloud Cover
  • Data Analysis
  • Data Science
  • Developmental Tests
  • Dew Point
  • Equations
  • Geostrophic Wind
  • Grids
  • Information Science
  • Magnetic Tape
  • Sea Level
  • Standards
  • Stations
  • Surface Temperature
  • United States
  • Verification

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Psychometric Testing or Psychological Assessment.