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Time lapse simulation of interrelated weather conditions

Author: Irving I Gringorten; U.S. Air Force Geophysics Laboratory. Meteorology Division.
Publisher: Hanscom AFB, Massachusetts : Air Force Geophysics Laboratory, Air Force Systems Command, United States Air Force, 1983.
Series: AFGL-TR, 83-141.; Environmental research papers (Hanscom AFB, Mass.), no. 839.
Edition/Format:   Print book : National government publication : EnglishView all editions and formats
Summary:
This paper has been prompted by the need, in war games, for a stochastic model of the sequence of weather conditions as they might impinge on air/ground combat operations. Such a time sequence of weather, including ceiling, visibility, and cloud cover, for one or more stations, has been perceived as inadequately modeled, so far. The present work is based on previously developed sequences in the Ornstein-Uhlenbeck  Read more...
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Details

Material Type: Government publication, National government publication
Document Type: Book
All Authors / Contributors: Irving I Gringorten; U.S. Air Force Geophysics Laboratory. Meteorology Division.
OCLC Number: 10326721
Notes: Cover title.
Distributed to depository libraries in microfiche.
"20 May 1983."
Description: 47 pages : illustrations ; 28 cm.
Series Title: AFGL-TR, 83-141.; Environmental research papers (Hanscom AFB, Mass.), no. 839.
Other Titles: Technical Report Archive & Image Library (TRAIL)
Responsibility: Irving I. Gringorten.

Abstract:

This paper has been prompted by the need, in war games, for a stochastic model of the sequence of weather conditions as they might impinge on air/ground combat operations. Such a time sequence of weather, including ceiling, visibility, and cloud cover, for one or more stations, has been perceived as inadequately modeled, so far. The present work is based on previously developed sequences in the Ornstein-Uhlenbeck process. Joint sequences call for a modification, but still basically comprise a Markov process. Formulas or algorithms have been developed for the joint occurrence of two interrelated events changing simultaneously in a Markov time sequence. The model process is particularly applicable to a changing combination of ceiling and visibility at one station, or to the changing combination of cloud cover at two adjacent stations. A brief examination of the time sequence of three simultaneous events reveals a rapidly increasing complication of solution, making an alternative study of a real coverage of weather conditions more acceptable when more than two variables are involved.

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