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- W2113485151 abstract "A probabilistic model for the temporal description of daily rainfall occurrences at a single location is presented. By defining an event as a day with measurable precipitation the model is cast into the discrete-time point process framework. In the proposed model the sequence of times between events is formed by sampling from two geometric distributions, according to transition probabilities specified by a Markov chain. The model belongs to the class of Markov renewal processes and exhibits clustering relative to the independent Bernoulli process. As a special case, it reduces to a renewal model with a mixture distribution for the interarrival times. The rainfall occurrence model coupled with a mixed exponential distribution for the nonzero daily rainfall amounts was applied to the daily rainfall series for Snoqualmie Falls, Washington, and was successful in preserving the short-term structure of the occurrence process, as well as the distributional properties of the seasonal rainfall amounts." @default.
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- W2113485151 date "1987-05-01" @default.
- W2113485151 modified "2023-10-16" @default.
- W2113485151 title "A Markov Renewal Model for rainfall occurrences" @default.
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- W2113485151 doi "https://doi.org/10.1029/wr023i005p00875" @default.
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