Mixture model of generalized chain-dependent processes and its application to simulation of interannual variability of daily rainfall

This study is devoted to simulation of the interannual variability of daily rainfall, such as the mean and variance of seasonal rainfall totals and the correlation between seasonal rainfall totals and a seasonal climate variable (e.g., an index of atmospheric or oceanic circulation). Prior work established that a mixture of chain-dependent processes, involving conditioning on an observed seasonal circulation index, results in improved representation of the interannual variance of seasonal rainfall totals, as well as of the correlation between rainfall and this index. The present study extends this work through consideration of a mixture model of generalized chain-dependent processes. Here "generalized" refers to the inclusion of a generalized linear model in accounting for the relationship between daily rainfall statistics and the circulation index. It is shown that this extension results in further improvements in the simulation of the interannual variability of seasonal rainfall and, especially, in its correlation with the circulation index.

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NOTICE: This is the author's version of a work accepted for publication by Elsevier. Changes resulting from the publishing process, including peer review, editing, corrections, structural formatting and other quality control mechanisms, may not be reflected in this document. Changes may have been made to this work since it was submitted for publication.


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Author Zheng, Xiaogu
Katz, Richard
Publisher UCAR/NCAR - Library
Publication Date 2008-01-30T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:25:42.528515
Metadata Record Identifier edu.ucar.opensky::articles:18046
Metadata Language eng; USA
Suggested Citation Zheng, Xiaogu, Katz, Richard. (2008). Mixture model of generalized chain-dependent processes and its application to simulation of interannual variability of daily rainfall. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7rf5wkq. Accessed 28 June 2025.

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