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    Simulated polarimetric fields of ice vapor growth using the Adaptive Habit Model. Part I: Large-Eddy Simulations

    Source: Monthly Weather Review:;2017:;volume( 145 ):;issue: 006::page 2281
    Author:
    Sulia, Kara J.
    ,
    Kumjian, Matthew R.
    DOI: 10.1175/MWR-D-16-0061.1
    Publisher: American Meteorological Society
    Abstract: he bulk adaptive habit model (AHM) explicitly predicts ice particle aspect ratio, improving the representation of microphysical processes and properties, including ice/liquid phase partitioning. With the unique ability to predict ice particle shape and density, the AHM is combined with an offline forward operator to produce fields of simulated polarimetric variables. An evaluation of AHM-forward-simulated dual-polarization radar signatures in an idealized Arctic mixed-phase cloud is presented. Interpretations of those signatures are provided through microphysical model output using Weather Research and Forecasting Large-Eddy Simulations.Vapor-grown ice properties are associated with distinct observable signatures in polarimetric radar variables, with clear sensitivities to the simulated ice particle properties, including ice number, size, and distribution shape. In contrast, liquid droplet number has little influence on both polarimetric and microphysical variables in the case presented herein. Polarimetric quantities are sensitive to the dominating crystal habit type in a volume, with enhancements for aspect ratios much lower or higher than unity. This synthesis of a microphysical model and a polarimetric forward simulator is a first step in the evaluation of detailed AHM microphysics.
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      Simulated polarimetric fields of ice vapor growth using the Adaptive Habit Model. Part I: Large-Eddy Simulations

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4230935
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    • Monthly Weather Review

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    contributor authorSulia, Kara J.
    contributor authorKumjian, Matthew R.
    date accessioned2017-06-09T17:33:54Z
    date available2017-06-09T17:33:54Z
    date issued2017
    identifier issn0027-0644
    identifier otherams-87283.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230935
    description abstracthe bulk adaptive habit model (AHM) explicitly predicts ice particle aspect ratio, improving the representation of microphysical processes and properties, including ice/liquid phase partitioning. With the unique ability to predict ice particle shape and density, the AHM is combined with an offline forward operator to produce fields of simulated polarimetric variables. An evaluation of AHM-forward-simulated dual-polarization radar signatures in an idealized Arctic mixed-phase cloud is presented. Interpretations of those signatures are provided through microphysical model output using Weather Research and Forecasting Large-Eddy Simulations.Vapor-grown ice properties are associated with distinct observable signatures in polarimetric radar variables, with clear sensitivities to the simulated ice particle properties, including ice number, size, and distribution shape. In contrast, liquid droplet number has little influence on both polarimetric and microphysical variables in the case presented herein. Polarimetric quantities are sensitive to the dominating crystal habit type in a volume, with enhancements for aspect ratios much lower or higher than unity. This synthesis of a microphysical model and a polarimetric forward simulator is a first step in the evaluation of detailed AHM microphysics.
    publisherAmerican Meteorological Society
    titleSimulated polarimetric fields of ice vapor growth using the Adaptive Habit Model. Part I: Large-Eddy Simulations
    typeJournal Paper
    journal volume145
    journal issue006
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-16-0061.1
    journal fristpage2281
    journal lastpage2302
    treeMonthly Weather Review:;2017:;volume( 145 ):;issue: 006
    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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