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    A Stochastic Model of n-Day Precipitation

    Source: Journal of Applied Meteorology:;1975:;volume( 014 ):;issue: 001::page 17
    Author:
    Todorovic, P.
    ,
    Woolhiser, David A.
    DOI: 10.1175/1520-0450(1975)014<0017:ASMODP>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: General expressions are derived for the distribution functions of the total amount of precipitation and the largest daily precipitation occurring in an n-day period. Two special cases are considered: (i) the probability of occurrence of precipitation on any day in an n-day period is a constant (binomial counting process) and (ii) the probability of occurrence of precipitation on any day depends on whether the previous day was wet or dry (Markov chain counting process). The distribution function for daily precipitation was assumed to be exponential. Analytic expressions are derived for the distribution functions for total precipitation or precipitation greater than a threshold. For the numerical example chosen, the Markov chain-exponential model is slightly superior to the binomial-exponential model. This stochastic model seems to have several advantages over present approaches.
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      A Stochastic Model of n-Day Precipitation

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    contributor authorTodorovic, P.
    contributor authorWoolhiser, David A.
    date accessioned2017-06-09T17:37:20Z
    date available2017-06-09T17:37:20Z
    date copyright1975/02/01
    date issued1975
    identifier issn0021-8952
    identifier otherams-8822.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231978
    description abstractGeneral expressions are derived for the distribution functions of the total amount of precipitation and the largest daily precipitation occurring in an n-day period. Two special cases are considered: (i) the probability of occurrence of precipitation on any day in an n-day period is a constant (binomial counting process) and (ii) the probability of occurrence of precipitation on any day depends on whether the previous day was wet or dry (Markov chain counting process). The distribution function for daily precipitation was assumed to be exponential. Analytic expressions are derived for the distribution functions for total precipitation or precipitation greater than a threshold. For the numerical example chosen, the Markov chain-exponential model is slightly superior to the binomial-exponential model. This stochastic model seems to have several advantages over present approaches.
    publisherAmerican Meteorological Society
    titleA Stochastic Model of n-Day Precipitation
    typeJournal Paper
    journal volume14
    journal issue1
    journal titleJournal of Applied Meteorology
    identifier doi10.1175/1520-0450(1975)014<0017:ASMODP>2.0.CO;2
    journal fristpage17
    journal lastpage24
    treeJournal of Applied Meteorology:;1975:;volume( 014 ):;issue: 001
    contenttypeFulltext
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