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    Comments on “Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence”

    Source: Weather and Forecasting:;2016:;volume( 031 ):;issue: 004::page 1393
    Author:
    Schultz, David M.
    ,
    Spengler, Thomas
    DOI: 10.1175/WAF-D-16-0067.1
    Publisher: American Meteorological Society
    Abstract: n a recent article, Qian et al. introduced the quantities moist vorticity and moist divergence to diagnose locations of heavy rain. These quantities are constructed by multiplying the relative vorticity and divergence by relative humidity to the power k, where k = 10 in their article. Their approach is similar to that for the previously constructed quantity generalized moist potential vorticity. This comment critiques the approach of Qian et al., demonstrating that the moist vorticity, moist divergence, and by extension generalized moist potential vorticity are flawed mathematically and meteorologically. Raising relative humidity to the 10th power is poorly justified and is based on a single case study at a single time. No meteorological evidence is presented for why areas of moist vorticity and moist divergence should overlap with regions of 24-h accumulated rainfall. All three quantities have not been verified against the output of precipitation directly from the model nor is the approach of combining meteorological quantities into a single parameter appropriate in an ingredients-based forecasting approach. Researchers and forecasters are advised to plot the model precipitation directly and employ an ingredients-based approach, rather than rely on these flawed quantities.
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      Comments on “Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence”

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4232006
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    contributor authorSchultz, David M.
    contributor authorSpengler, Thomas
    date accessioned2017-06-09T17:37:25Z
    date available2017-06-09T17:37:25Z
    date copyright2016/08/01
    date issued2016
    identifier issn0882-8156
    identifier otherams-88247.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4232006
    description abstractn a recent article, Qian et al. introduced the quantities moist vorticity and moist divergence to diagnose locations of heavy rain. These quantities are constructed by multiplying the relative vorticity and divergence by relative humidity to the power k, where k = 10 in their article. Their approach is similar to that for the previously constructed quantity generalized moist potential vorticity. This comment critiques the approach of Qian et al., demonstrating that the moist vorticity, moist divergence, and by extension generalized moist potential vorticity are flawed mathematically and meteorologically. Raising relative humidity to the 10th power is poorly justified and is based on a single case study at a single time. No meteorological evidence is presented for why areas of moist vorticity and moist divergence should overlap with regions of 24-h accumulated rainfall. All three quantities have not been verified against the output of precipitation directly from the model nor is the approach of combining meteorological quantities into a single parameter appropriate in an ingredients-based forecasting approach. Researchers and forecasters are advised to plot the model precipitation directly and employ an ingredients-based approach, rather than rely on these flawed quantities.
    publisherAmerican Meteorological Society
    titleComments on “Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence”
    typeJournal Paper
    journal volume31
    journal issue4
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-16-0067.1
    journal fristpage1393
    journal lastpage1396
    treeWeather and Forecasting:;2016:;volume( 031 ):;issue: 004
    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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