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    Estimating Cloud Field Albedo Using One-Dimensional Series Of Optical Depth

    Source: Journal of the Atmospheric Sciences:;1996:;Volume( 053 ):;issue: 019::page 2826
    Author:
    Barker, Howard W.
    DOI: 10.1175/1520-0469(1996)053<2826:ECFAUO>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: This study examines the ability to estimate regional cloud albedo using 1D series of cloud optical depth τ similar to those inferred from ground-based microwave radiometers. The investigation has two facets: use of appropriate radiative transfer algorithms and adequate portrayal of cloud structure. Using 1024 ? 1024 pixel arrays of τ inferred from 28.5-m resolution Landsat data, regional albedos and albedos along individual scanlines are computed by a 3D Monte Carlo (MC) photon transport algorithm. Assuming the scanlines to be proxies for 1D series of τ a 2D MC algorithm and the Independent Pixel Approximation (IPA) are used to compute albedos for scanlines of various lengths and resolutions. Regarding the appropriateness of doing radiative transfer calculations on a 1D series of τ, it is shown that for 1D series of τ containing 1024 pixels (?30 km), lack of information about cloud structure adjacent to the series yields root-mean-square errors for 2D MC albedos of about 2% for a stratocumulus and 20% for two cumulus cloud fields. For the cumulus cases there is a marked tendency to over (under) estimate albedos for relatively bright (dark) scanlines. For the same series, the IPA performs very well relative to the, 2D MC for stratocumulus conditions. For broken cumulus clouds, however, notable biases between the 2D MC and IPA results stem mostly from the neglect of cloud sides by the IPA. In all cases, random errors are small. The IPA is then used to investigate the accuracy of estimating regional cloud albedo with 1D datasets containing various amounts of information. It is demonstrated that for series with less than 100 pixels (?3 km) at full resolution, the probability of attaining good estimates of regional cloud albedo is very low regardless of cloud type. Ideally, series with more than 1024 pixels should be used. Regarding sensitivity to data resolution, estimated regional albedos are almost resolution independent for pixel sizes up to about 2 km (?70 pixels). At coarser resolutions. loss of cloud structure information important for radiative transfer is great and the quality of regional albedo estimates degraded, particularly for oblique sun.
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      Estimating Cloud Field Albedo Using One-Dimensional Series Of Optical Depth

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    contributor authorBarker, Howard W.
    date accessioned2017-06-09T14:34:06Z
    date available2017-06-09T14:34:06Z
    date copyright1996/10/01
    date issued1996
    identifier issn0022-4928
    identifier otherams-21846.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4158230
    description abstractThis study examines the ability to estimate regional cloud albedo using 1D series of cloud optical depth τ similar to those inferred from ground-based microwave radiometers. The investigation has two facets: use of appropriate radiative transfer algorithms and adequate portrayal of cloud structure. Using 1024 ? 1024 pixel arrays of τ inferred from 28.5-m resolution Landsat data, regional albedos and albedos along individual scanlines are computed by a 3D Monte Carlo (MC) photon transport algorithm. Assuming the scanlines to be proxies for 1D series of τ a 2D MC algorithm and the Independent Pixel Approximation (IPA) are used to compute albedos for scanlines of various lengths and resolutions. Regarding the appropriateness of doing radiative transfer calculations on a 1D series of τ, it is shown that for 1D series of τ containing 1024 pixels (?30 km), lack of information about cloud structure adjacent to the series yields root-mean-square errors for 2D MC albedos of about 2% for a stratocumulus and 20% for two cumulus cloud fields. For the cumulus cases there is a marked tendency to over (under) estimate albedos for relatively bright (dark) scanlines. For the same series, the IPA performs very well relative to the, 2D MC for stratocumulus conditions. For broken cumulus clouds, however, notable biases between the 2D MC and IPA results stem mostly from the neglect of cloud sides by the IPA. In all cases, random errors are small. The IPA is then used to investigate the accuracy of estimating regional cloud albedo with 1D datasets containing various amounts of information. It is demonstrated that for series with less than 100 pixels (?3 km) at full resolution, the probability of attaining good estimates of regional cloud albedo is very low regardless of cloud type. Ideally, series with more than 1024 pixels should be used. Regarding sensitivity to data resolution, estimated regional albedos are almost resolution independent for pixel sizes up to about 2 km (?70 pixels). At coarser resolutions. loss of cloud structure information important for radiative transfer is great and the quality of regional albedo estimates degraded, particularly for oblique sun.
    publisherAmerican Meteorological Society
    titleEstimating Cloud Field Albedo Using One-Dimensional Series Of Optical Depth
    typeJournal Paper
    journal volume53
    journal issue19
    journal titleJournal of the Atmospheric Sciences
    identifier doi10.1175/1520-0469(1996)053<2826:ECFAUO>2.0.CO;2
    journal fristpage2826
    journal lastpage2837
    treeJournal of the Atmospheric Sciences:;1996:;Volume( 053 ):;issue: 019
    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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