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    Drop Size Distribution Broadening Mechanisms in a Bin Microphysics Eulerian Model

    Source: Journal of the Atmospheric Sciences:;2020:;volume( 77 ):;issue: 009::page 3249
    Author:
    Pardo, Lianet Hernández;Morrison, Hugh;Machado, Luiz A. T.;Harrington, Jerry Y.;Lebo, Zachary J.
    DOI: 10.1175/JAS-D-20-0099.1
    Publisher: American Meteorological Society
    Abstract: In this study, processes that broaden drop size distributions (DSDs) in Eulerian models with two-moment bin microphysics are analyzed. Numerous tests are performed to isolate the effects of different physical mechanisms that broaden DSDs in two- and three-dimensional Weather Research and Forecasting Model simulations of an idealized ice-free cumulus cloud. Sensitivity of these effects to modifying horizontal and vertical model grid spacings is also examined. As expected, collision–coalescence is a key process broadening the modeled DSDs. In-cloud droplet activation also contributes substantially to DSD broadening, whereas evaporation has only a minor effect and sedimentation has little effect. Cloud dilution (mixing of cloud-free and cloudy air) also broadens the DSDs considerably, whether or not it is accompanied by evaporation. This mechanism involves the reduction of droplet concentration from dilution along the cloud’s lateral edges, leading to locally high supersaturation and enhanced drop growth when this air is subsequently lifted in the updraft. DSD broadening ensues when the DSDs are mixed with those from the cloud core. Decreasing the horizontal and vertical model grid spacings from 100 to 30 m has limited impact on the DSDs. However, when these physical broadening mechanisms (in-cloud activation, collision–coalescence, dilution, etc.) are turned off, there is a reduction of DSD width by up to ~20%–50% when the vertical grid spacing is decreased from 100 to 30 m, consistent with effects of artificial broadening from vertical numerical diffusion. Nonetheless, this artificial numerical broadening appears to be relatively unimportant overall for DSD broadening when physically based broadening mechanisms in the model are included for this cumulus case.
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      Drop Size Distribution Broadening Mechanisms in a Bin Microphysics Eulerian Model

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    contributor authorPardo, Lianet Hernández;Morrison, Hugh;Machado, Luiz A. T.;Harrington, Jerry Y.;Lebo, Zachary J.
    date accessioned2022-01-30T17:52:27Z
    date available2022-01-30T17:52:27Z
    date copyright9/17/2020 12:00:00 AM
    date issued2020
    identifier issn0022-4928
    identifier otherjasd200099.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4264098
    description abstractIn this study, processes that broaden drop size distributions (DSDs) in Eulerian models with two-moment bin microphysics are analyzed. Numerous tests are performed to isolate the effects of different physical mechanisms that broaden DSDs in two- and three-dimensional Weather Research and Forecasting Model simulations of an idealized ice-free cumulus cloud. Sensitivity of these effects to modifying horizontal and vertical model grid spacings is also examined. As expected, collision–coalescence is a key process broadening the modeled DSDs. In-cloud droplet activation also contributes substantially to DSD broadening, whereas evaporation has only a minor effect and sedimentation has little effect. Cloud dilution (mixing of cloud-free and cloudy air) also broadens the DSDs considerably, whether or not it is accompanied by evaporation. This mechanism involves the reduction of droplet concentration from dilution along the cloud’s lateral edges, leading to locally high supersaturation and enhanced drop growth when this air is subsequently lifted in the updraft. DSD broadening ensues when the DSDs are mixed with those from the cloud core. Decreasing the horizontal and vertical model grid spacings from 100 to 30 m has limited impact on the DSDs. However, when these physical broadening mechanisms (in-cloud activation, collision–coalescence, dilution, etc.) are turned off, there is a reduction of DSD width by up to ~20%–50% when the vertical grid spacing is decreased from 100 to 30 m, consistent with effects of artificial broadening from vertical numerical diffusion. Nonetheless, this artificial numerical broadening appears to be relatively unimportant overall for DSD broadening when physically based broadening mechanisms in the model are included for this cumulus case.
    publisherAmerican Meteorological Society
    titleDrop Size Distribution Broadening Mechanisms in a Bin Microphysics Eulerian Model
    typeJournal Paper
    journal volume77
    journal issue9
    journal titleJournal of the Atmospheric Sciences
    identifier doi10.1175/JAS-D-20-0099.1
    journal fristpage3249
    journal lastpage3273
    treeJournal of the Atmospheric Sciences:;2020:;volume( 77 ):;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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