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    Simulation of Daily Weather Data Using Theoretical Probability Distributions

    Source: Journal of Applied Meteorology:;1979:;volume( 019 ):;issue: 009::page 1029
    Author:
    Bruhn, J. A.
    ,
    Fry, W. E.
    ,
    Fick, G. W.
    DOI: 10.1175/1520-0450(1980)019<1029:SODWDU>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A computer simulation model was constructed to supply daily weather data to a plant disease management model for potato late blight. In the weather model Monte Carlo techniques were employed to generate daily values of precipitation, maximum temperature, minimum temperature, minimum relative humidity and total solar radiation. Each weather variable is described by a known theoretical probability distribution but the values of the parameters describing each distribution are dependent on the occurrence of rainfall. Precipitation occurrence is described by a first-order Markov chain. The amount of rain, given that rain has occurred, is described by a gamma probability distribution. Maximum and minimum temperature are simulated with a trivariate normal probability distribution involving maximum temperature on the previous day, maximum temperature on the current day and minimum temperature on the current day. Parameter values for this distribution are dependent on the occurrence of rain on the previous day. Both minimum relative humidity and total solar radiation are assumed to be normally distributed. The values of the parameters describing the distribution of minimum relative humidity is dependent on rainfall occurrence on the previous day and current day. Parameter values for total solar radiation are dependent on the occurrence of rain on the current day. The assumptions made during model construction were found to be appropriate for actual weather data from Geneva, New York. The performance of the weather model was evaluated by comparing the cumulative frequency distributions of simulated weather data with the distributions of actual weather data from Geneva, New York and Fort Collins, Colorado. For each location, simulated weather data were similar to actual weather data in terms of mean response, variability and autocorrelation. The possible applications of this model when used with models of other components of the agro-ecosystem are discussed.
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      Simulation of Daily Weather Data Using Theoretical Probability Distributions

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4233507
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    contributor authorBruhn, J. A.
    contributor authorFry, W. E.
    contributor authorFick, G. W.
    date accessioned2017-06-09T17:40:37Z
    date available2017-06-09T17:40:37Z
    date copyright1980/09/01
    date issued1979
    identifier issn0021-8952
    identifier otherams-9961.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4233507
    description abstractA computer simulation model was constructed to supply daily weather data to a plant disease management model for potato late blight. In the weather model Monte Carlo techniques were employed to generate daily values of precipitation, maximum temperature, minimum temperature, minimum relative humidity and total solar radiation. Each weather variable is described by a known theoretical probability distribution but the values of the parameters describing each distribution are dependent on the occurrence of rainfall. Precipitation occurrence is described by a first-order Markov chain. The amount of rain, given that rain has occurred, is described by a gamma probability distribution. Maximum and minimum temperature are simulated with a trivariate normal probability distribution involving maximum temperature on the previous day, maximum temperature on the current day and minimum temperature on the current day. Parameter values for this distribution are dependent on the occurrence of rain on the previous day. Both minimum relative humidity and total solar radiation are assumed to be normally distributed. The values of the parameters describing the distribution of minimum relative humidity is dependent on rainfall occurrence on the previous day and current day. Parameter values for total solar radiation are dependent on the occurrence of rain on the current day. The assumptions made during model construction were found to be appropriate for actual weather data from Geneva, New York. The performance of the weather model was evaluated by comparing the cumulative frequency distributions of simulated weather data with the distributions of actual weather data from Geneva, New York and Fort Collins, Colorado. For each location, simulated weather data were similar to actual weather data in terms of mean response, variability and autocorrelation. The possible applications of this model when used with models of other components of the agro-ecosystem are discussed.
    publisherAmerican Meteorological Society
    titleSimulation of Daily Weather Data Using Theoretical Probability Distributions
    typeJournal Paper
    journal volume19
    journal issue9
    journal titleJournal of Applied Meteorology
    identifier doi10.1175/1520-0450(1980)019<1029:SODWDU>2.0.CO;2
    journal fristpage1029
    journal lastpage1036
    treeJournal of Applied Meteorology:;1979:;volume( 019 ):;issue: 009
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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