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    A Climatology of Operational Storm-Based Warnings: A Geospatial Analysis 

    Source: Weather and Forecasting:;2016:;volume( 032 ):;issue: 001:;page 47
    Author(s): Harrison, David R.; Karstens, Christopher D.
    Publisher: American Meteorological Society
    Abstract: his study provides a quantitative climatological analysis of the fundamental geospatial components of storm-based warnings and offers insight into how the National Weather Service (NWS) uses the current storm-based warning ...
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    A Machine Learning Tutorial for Operational Meteorology. Part II: Neural Networks and Deep Learning 

    Source: Weather and Forecasting:;2023:;volume( 038 ):;issue: 008:;page 1271
    Author(s): Chase, Randy J.; Harrison, David R.; Lackmann, Gary M.; McGovern, Amy
    Publisher: American Meteorological Society
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    Development of a Human–Machine Mix for Forecasting Severe Convective Events 

    Source: Weather and Forecasting:;2018:;volume 033:;issue 003:;page 715
    Author(s): Karstens, Christopher D.; Correia, James; LaDue, Daphne S.; Wolfe, Jonathan; Meyer, Tiffany C.; Harrison, David R.; Cintineo, John L.; Calhoun, Kristin M.; Smith, Travis M.; Gerard, Alan E.; Rothfusz, Lans P.
    Publisher: American Meteorological Society
    Abstract: AbstractProviding advance warning for impending severe convective weather events (i.e., tornadoes, hail, wind) fundamentally requires an ability to predict and/or detect these hazards and subsequently communicate their ...
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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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