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Statistical Methods for Persistent Precipitation Patterns

A. M. FeyerhermKansas State University, Manhattan, Kans.

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L. Dean BarkKansas State University, Manhattan, Kans.

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Abstract

Procedures are developed to estimate the probability of occurrence for a given consecutive sequence of wet and dry days which begins with a specified day of the year. A good first approximation for such a probability can be obtained by assuming that the sequence can be described as a first order Markov chain. Initial and transition probabilities in the Markov chain model are estimated so as to reflect seasonal variation.

Abstract

Procedures are developed to estimate the probability of occurrence for a given consecutive sequence of wet and dry days which begins with a specified day of the year. A good first approximation for such a probability can be obtained by assuming that the sequence can be described as a first order Markov chain. Initial and transition probabilities in the Markov chain model are estimated so as to reflect seasonal variation.

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