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    Monte Carlo Simulation of Solar Reflectances for Cloudy Atmospheres

    Source: Journal of the Atmospheric Sciences:;2003:;Volume( 060 ):;issue: 016::page 1881
    Author:
    Barker, H. W.
    ,
    Goldstein, R. K.
    ,
    Stevens, D. E.
    DOI: 10.1175/1520-0469(2003)060<1881:MCSOSR>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Monte Carlo simulations of solar radiative transfer were performed for a well-resolved, large, three-dimensional (3D) domain of boundary layer cloud simulated by a cloud-resolving model. In order to represent 3D distributions of optical properties for ?2 ? 106 cloudy cells, attenuation by droplets was handled by assigning each cell a cumulative distribution of extinction derived from either a model or an assumed discrete droplet size spectrum. This minimizes the required number of detailed phase functions. Likewise, to simulate statistically significant, high-resolution imagery, it was necessary to apply variance reduction techniques. Three techniques were developed for use with the local estimation method of computing reflectance ?. First, small fractions of ? come from numerous, small contributions of ? computed at each scattering event. Terminating calculation of ? when it falls below ?min ≈ 10?3 was found to impact estimates of ? minimally but reduced computation time by ?10%. Second, large fractions of ? come from infrequent realizations of large ?. When sampled poorly, they boost Monte Carlo noise significantly. Removing ? ? ?max, storing them in a domainwide reservoir, adding ?max to local estimates of ?, and, at simulation's end, distributing the reservoir across the domain in proportion to local ?, tends to reduce variance much. This regionalization technique works well when the number of photons per unit area is small (nominally ? 50 000). A value of ?max ≈ 100 reduces variance of ? greatly with little impact on estimates of ?. Third, if ? are computed using exact (e.g., Mie) phase functions for the first N scattering events, and thereafter a blunt-nosed corresponding phase function (e.g., Henyey?Greenstein) is used, production of large ? is thwarted resulting in reduced variance and time required to achieve accurate estimates of ?.
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      Monte Carlo Simulation of Solar Reflectances for Cloudy Atmospheres

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4159844
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    • Journal of the Atmospheric Sciences

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    contributor authorBarker, H. W.
    contributor authorGoldstein, R. K.
    contributor authorStevens, D. E.
    date accessioned2017-06-09T14:38:14Z
    date available2017-06-09T14:38:14Z
    date copyright2003/08/01
    date issued2003
    identifier issn0022-4928
    identifier otherams-23299.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4159844
    description abstractMonte Carlo simulations of solar radiative transfer were performed for a well-resolved, large, three-dimensional (3D) domain of boundary layer cloud simulated by a cloud-resolving model. In order to represent 3D distributions of optical properties for ?2 ? 106 cloudy cells, attenuation by droplets was handled by assigning each cell a cumulative distribution of extinction derived from either a model or an assumed discrete droplet size spectrum. This minimizes the required number of detailed phase functions. Likewise, to simulate statistically significant, high-resolution imagery, it was necessary to apply variance reduction techniques. Three techniques were developed for use with the local estimation method of computing reflectance ?. First, small fractions of ? come from numerous, small contributions of ? computed at each scattering event. Terminating calculation of ? when it falls below ?min ≈ 10?3 was found to impact estimates of ? minimally but reduced computation time by ?10%. Second, large fractions of ? come from infrequent realizations of large ?. When sampled poorly, they boost Monte Carlo noise significantly. Removing ? ? ?max, storing them in a domainwide reservoir, adding ?max to local estimates of ?, and, at simulation's end, distributing the reservoir across the domain in proportion to local ?, tends to reduce variance much. This regionalization technique works well when the number of photons per unit area is small (nominally ? 50 000). A value of ?max ≈ 100 reduces variance of ? greatly with little impact on estimates of ?. Third, if ? are computed using exact (e.g., Mie) phase functions for the first N scattering events, and thereafter a blunt-nosed corresponding phase function (e.g., Henyey?Greenstein) is used, production of large ? is thwarted resulting in reduced variance and time required to achieve accurate estimates of ?.
    publisherAmerican Meteorological Society
    titleMonte Carlo Simulation of Solar Reflectances for Cloudy Atmospheres
    typeJournal Paper
    journal volume60
    journal issue16
    journal titleJournal of the Atmospheric Sciences
    identifier doi10.1175/1520-0469(2003)060<1881:MCSOSR>2.0.CO;2
    journal fristpage1881
    journal lastpage1894
    treeJournal of the Atmospheric Sciences:;2003:;Volume( 060 ):;issue: 016
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian