Very Short Range Statistical Forecasting of Automated Weather Observations.

Abstract

A procedure is developed for providing weather forecasting guidance over the short period between 1 to 60 minutes. It uses automated surface observation elements as predictors and predictands. The same equations project probabilistic predictions iteratively minute-by-minute. The model is founded on a Markov assumption and utilizes multivariate linear regression as the statistical operator. Details are given on how the model is constructed and how it compares with other objective methods such as climatology and persistence. Tests are performed on a new nonlinear approach.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1984
Accession Number
ADA149539

Entities

People

  • R. G. Miller

Organizations

  • National Weather Service

Tags

Communities of Interest

  • Air Platforms
  • Sensors

DTIC Thesaurus Topics

  • Atmospheric Sciences
  • Climatology
  • Computer Languages
  • Computers
  • Dew Point
  • Markov Chains
  • Markov Processes
  • Mathematical Models
  • Models
  • Probability
  • Probability Distributions
  • Rotary Wing Aircraft
  • Statistical Analysis
  • Stochastic Processes
  • United States
  • Weather
  • Weather Forecasting

Fields of Study

  • Mathematics

Readers

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