YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Monthly Weather Review
    • View Item
    •   YE&T Library
    • AMS
    • Monthly Weather Review
    • 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

    Ensemble Probabilistic Forecasts of a Tornadic Mesoscale Convective System from Ensemble Kalman Filter Analyses Using WSR-88D and CASA Radar Data

    Source: Monthly Weather Review:;2012:;volume( 140 ):;issue: 007::page 2126
    Author:
    Snook, Nathan
    ,
    Xue, Ming
    ,
    Jung, Youngsun
    DOI: 10.1175/MWR-D-11-00117.1
    Publisher: American Meteorological Society
    Abstract: his study examines the ability of a storm-scale numerical weather prediction (NWP) model to predict precipitation and mesovortices within a tornadic mesoscale convective system that occurred over Oklahoma on 8?9 May 2007, when the model is initialized from ensemble Kalman filter (EnKF) analyses including data from four Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) X-band and five Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars. Ensemble forecasts are performed and probabilistic forecast products generated, focusing on prediction of radar reflectivity (a proxy of quantitative precipitation) and mesovortices (an indication of tornado potential).Assimilating data from both the CASA and WSR-88D radars for the ensemble and using a mixed-microphysics ensemble during data assimilation produces the best probabilistic mesovortex forecast. The use of multiple microphysics schemes within the ensemble aims to address at least partially the model physics uncertainty and effectively plays a role of flow-dependent inflation (in precipitation regions) during EnKF data assimilation. The ensemble predicts with high probability (approximately 0.65) the near-surface mesovortex associated with the first of three reported tornadoes. Though a bias toward stronger precipitation is noted in the ensemble forecasts, all experiments produce skillful probabilistic forecasts of radar reflectivity on a 0?3-h time scale as evaluated by multiple probabilistic verification metrics. These results suggest that both the inclusion of CASA radar data and use of a mixed-microphysics ensemble during EnKF data assimilation positively impact the skill of 2?3-h ensemble forecasts of mesovortices, despite having little impact on the quality of precipitation forecasts (analyzed in terms of predicted radar reflectivity), and are important steps toward an operational EnKF-based ensemble analysis and probabilistic forecast system to support convective-scale warn-on-forecast operations.
    • Download: (5.603Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Ensemble Probabilistic Forecasts of a Tornadic Mesoscale Convective System from Ensemble Kalman Filter Analyses Using WSR-88D and CASA Radar Data

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4229698
    Collections
    • Monthly Weather Review

    Show full item record

    contributor authorSnook, Nathan
    contributor authorXue, Ming
    contributor authorJung, Youngsun
    date accessioned2017-06-09T17:29:24Z
    date available2017-06-09T17:29:24Z
    date copyright2012/07/01
    date issued2012
    identifier issn0027-0644
    identifier otherams-86170.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4229698
    description abstracthis study examines the ability of a storm-scale numerical weather prediction (NWP) model to predict precipitation and mesovortices within a tornadic mesoscale convective system that occurred over Oklahoma on 8?9 May 2007, when the model is initialized from ensemble Kalman filter (EnKF) analyses including data from four Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) X-band and five Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars. Ensemble forecasts are performed and probabilistic forecast products generated, focusing on prediction of radar reflectivity (a proxy of quantitative precipitation) and mesovortices (an indication of tornado potential).Assimilating data from both the CASA and WSR-88D radars for the ensemble and using a mixed-microphysics ensemble during data assimilation produces the best probabilistic mesovortex forecast. The use of multiple microphysics schemes within the ensemble aims to address at least partially the model physics uncertainty and effectively plays a role of flow-dependent inflation (in precipitation regions) during EnKF data assimilation. The ensemble predicts with high probability (approximately 0.65) the near-surface mesovortex associated with the first of three reported tornadoes. Though a bias toward stronger precipitation is noted in the ensemble forecasts, all experiments produce skillful probabilistic forecasts of radar reflectivity on a 0?3-h time scale as evaluated by multiple probabilistic verification metrics. These results suggest that both the inclusion of CASA radar data and use of a mixed-microphysics ensemble during EnKF data assimilation positively impact the skill of 2?3-h ensemble forecasts of mesovortices, despite having little impact on the quality of precipitation forecasts (analyzed in terms of predicted radar reflectivity), and are important steps toward an operational EnKF-based ensemble analysis and probabilistic forecast system to support convective-scale warn-on-forecast operations.
    publisherAmerican Meteorological Society
    titleEnsemble Probabilistic Forecasts of a Tornadic Mesoscale Convective System from Ensemble Kalman Filter Analyses Using WSR-88D and CASA Radar Data
    typeJournal Paper
    journal volume140
    journal issue7
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-11-00117.1
    journal fristpage2126
    journal lastpage2146
    treeMonthly Weather Review:;2012:;volume( 140 ):;issue: 007
    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