YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Weather and Forecasting
    • View Item
    •   YE&T Library
    • AMS
    • Weather and Forecasting
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    The NOAA/CIMSS ProbSevere Model: Incorporation of Total Lightning and Validation

    Source: Weather and Forecasting:;2018:;volume 033:;issue 001::page 331
    Author:
    Cintineo, John L.
    ,
    Pavolonis, Michael J.
    ,
    Sieglaff, Justin M.
    ,
    Lindsey, Daniel T.
    ,
    Cronce, Lee
    ,
    Gerth, Jordan
    ,
    Rodenkirch, Benjamin
    ,
    Brunner, Jason
    ,
    Gravelle, Chad
    DOI: 10.1175/WAF-D-17-0099.1
    Publisher: American Meteorological Society
    Abstract: AbstractThe empirical Probability of Severe (ProbSevere) model, developed by the National Oceanic and Atmospheric Administration (NOAA) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS), automatically extracts information related to thunderstorm development from several data sources to produce timely, short-term, statistical forecasts of thunderstorm intensity. More specifically, ProbSevere utilizes short-term numerical weather prediction guidance (NWP), geostationary satellite, ground-based radar, and ground-based lightning data to determine the probability that convective storm cells will produce severe weather up to 90 min in the future. ProbSevere guidance, which updates approximately every 2 min, is available to National Weather Service (NWS) Weather Forecast Offices with very short latency. This paper focuses on the integration of ground-based lightning detection data into ProbSevere. In addition, a thorough validation analysis is presented. The validation analysis demonstrates that ProbSevere has slightly less skill compared to NWS severe weather warnings, but can offer greater lead time to initial hazards. Feedback from NWS users has been highly favorable, with most forecasters responding that ProbSevere increases confidence and lead time in numerous warning situations.
    • Download: (1.774Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      The NOAA/CIMSS ProbSevere Model: Incorporation of Total Lightning and Validation

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4261369
    Collections
    • Weather and Forecasting

    Show full item record

    contributor authorCintineo, John L.
    contributor authorPavolonis, Michael J.
    contributor authorSieglaff, Justin M.
    contributor authorLindsey, Daniel T.
    contributor authorCronce, Lee
    contributor authorGerth, Jordan
    contributor authorRodenkirch, Benjamin
    contributor authorBrunner, Jason
    contributor authorGravelle, Chad
    date accessioned2019-09-19T10:05:15Z
    date available2019-09-19T10:05:15Z
    date copyright2/1/2018 12:00:00 AM
    date issued2018
    identifier otherwaf-d-17-0099.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261369
    description abstractAbstractThe empirical Probability of Severe (ProbSevere) model, developed by the National Oceanic and Atmospheric Administration (NOAA) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS), automatically extracts information related to thunderstorm development from several data sources to produce timely, short-term, statistical forecasts of thunderstorm intensity. More specifically, ProbSevere utilizes short-term numerical weather prediction guidance (NWP), geostationary satellite, ground-based radar, and ground-based lightning data to determine the probability that convective storm cells will produce severe weather up to 90 min in the future. ProbSevere guidance, which updates approximately every 2 min, is available to National Weather Service (NWS) Weather Forecast Offices with very short latency. This paper focuses on the integration of ground-based lightning detection data into ProbSevere. In addition, a thorough validation analysis is presented. The validation analysis demonstrates that ProbSevere has slightly less skill compared to NWS severe weather warnings, but can offer greater lead time to initial hazards. Feedback from NWS users has been highly favorable, with most forecasters responding that ProbSevere increases confidence and lead time in numerous warning situations.
    publisherAmerican Meteorological Society
    titleThe NOAA/CIMSS ProbSevere Model: Incorporation of Total Lightning and Validation
    typeJournal Paper
    journal volume33
    journal issue1
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-17-0099.1
    journal fristpage331
    journal lastpage345
    treeWeather and Forecasting:;2018:;volume 033:;issue 001
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian