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The application of time series models to cloud field morphology analysisA modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.
Document ID
19870057577
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Chin, Roland T.
(Wisconsin Univ. Madison, WI, United States)
Jau, Jack Y. C.
(Wisconsin Univ. Madison, WI, United States)
Weinman, James A.
(Wisconsin, University Madison, United States)
Date Acquired
August 13, 2013
Publication Date
March 1, 1987
Publication Information
Publication: Journal of Climate and Applied Meteorology
Volume: 26
ISSN: 0733-3021
Subject Category
Meteorology And Climatology
Accession Number
87A44851
Funding Number(s)
CONTRACT_GRANT: NSF ATM-84-14467
CONTRACT_GRANT: NAG5-580
Distribution Limits
Public
Copyright
Other

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