A Multiple Regression Technique of Estimating Mean Monthly Temperature Using Sea-Level Pressure.

Abstract

A simple point to point stepwise linear regression model which predicts mean monthly temperature using mean monthly sea-level pressure data is shown to be comparable in skill to a model which uses the coefficients of the principal components of the sea-level pressure as predictors. Regression equations are formed using as dependent data the pressure records from individual grid points in an area centered over North America for the period 1899 to 1960. Forecasts are then made from the equations for an independent record from 1961 to 1977. These predictions are shown to be less accurate than the forecasts made using the coefficients of the principal components. However, they display identical skill in forecasting above or below the long term monthly mean. Limited skill is demonstrated in predicting mean monthly temperature for January based on an actual long range prediction. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1979
Accession Number
ADA105402

Entities

People

  • Bryan Elam Lilius

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Air Force
  • Atmospheres
  • Atmospheric Sciences
  • Data Science
  • Data Sets
  • Hemispheres
  • Magnetic Tape
  • Meteorology
  • North America
  • Northern Hemisphere
  • Precipitation
  • Regression Analysis
  • Sea Level
  • Statistics
  • United States
  • Universities
  • Wisconsin

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Life Cycle Cost Analysis
  • Mechanical Engineering/Mechanics of Materials.