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    Exploring the Usefulness of Machine Learning Severe Weather Guidance in the Warn-on-Forecast System: Results from the 2022 NOAA Hazardous Weather Testbed Spring Forecasting Experiment

    Source: Weather and Forecasting:;2024:;volume( 039 ):;issue: 007::page 1023
    Author:
    Flora, Montgomery L.
    ,
    Gallo, Burkely
    ,
    Potvin, Corey K.
    ,
    Clark, Adam J.
    ,
    Wilson, Katie
    DOI: 10.1175/WAF-D-24-0038.1
    Publisher: American Meteorological Society
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      Exploring the Usefulness of Machine Learning Severe Weather Guidance in the Warn-on-Forecast System: Results from the 2022 NOAA Hazardous Weather Testbed Spring Forecasting Experiment

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4299910
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    • Weather and Forecasting

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    contributor authorFlora, Montgomery L.
    contributor authorGallo, Burkely
    contributor authorPotvin, Corey K.
    contributor authorClark, Adam J.
    contributor authorWilson, Katie
    date accessioned2024-12-24T13:57:47Z
    date available2024-12-24T13:57:47Z
    date copyright01 Jul. 2024
    date issued2024
    identifier otherwefo-WAF-D-24-0038.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4299910
    languageEnglish
    publisherAmerican Meteorological Society
    titleExploring the Usefulness of Machine Learning Severe Weather Guidance in the Warn-on-Forecast System: Results from the 2022 NOAA Hazardous Weather Testbed Spring Forecasting Experiment
    typeJournal Paper
    journal volume39
    journal issue7
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-24-0038.1
    journal fristpage1023
    journal lastpage1044
    treeWeather and Forecasting:;2024:;volume( 039 ):;issue: 007
    contenttypeFulltext
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