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 Canadian Regional Data Assimilation and Forecasting System

    Source: Weather and Forecasting:;2010:;volume( 025 ):;issue: 006::page 1645
    Author:
    Fillion, Luc
    ,
    Tanguay, Monique
    ,
    Lapalme, Ervig
    ,
    Denis, Bertrand
    ,
    Desgagne, Michel
    ,
    Lee, Vivian
    ,
    Ek, Nils
    ,
    Liu, Zhuo
    ,
    Lajoie, Manon
    ,
    Caron, Jean-François
    ,
    Pagé, Christian
    DOI: 10.1175/2010WAF2222401.1
    Publisher: American Meteorological Society
    Abstract: This paper describes the recent changes to the regional data assimilation and forecasting system at the Canadian Meteorological Center. A major aspect is the replacement of the currently operational global variable resolution forecasting approach by a limited-area nested approach. In addition, the variational analysis code has been upgraded to allow limited-area three- and four-dimensional variational data assimilation (3D- and 4DVAR) analysis approaches. As a first implementation step, the constraints were to impose similar background error correlation modeling assumptions, equal computer resources, and the use of the same assimilated data. Both bi-Fourier and spherical-harmonics spectral representations of background error correlations were extensively tested for the large horizontal domain considered for the Canadian regional system. Under such conditions, it is shown that the new regional data assimilation and forecasting system performs as well as the current operational system and it produces slightly better 24-h accumulated precipitation scores as judged from an ensemble of winter and summer cases. Because of the large horizontal extent of the regional domain considered, a spherical-harmonics spectral representation of background error correlations was shown to perform better than the bi-Fourier representation, considering all evaluation scores examined in this study. The latter is more suitable for smaller domains and will be kept for the upcoming use in the kilometric-scale local analysis domains in order to support the Canadian Meteorological Center?s (CMC?s) operations using multiple domains over Canada. The CMC?s new regional system [i.e., a regional limited-area 3DVAR data assimilation system coupled to a limited-area model (REG-LAM3D)] is now undergoing its final evaluations before operational transfer. Important model and data assimilation upgrades are currently under development to fully exploit this new system and are briefly presented.
    • Download: (4.854Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      The Canadian Regional Data Assimilation and Forecasting System

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4213393
    Collections
    • Weather and Forecasting

    Show full item record

    contributor authorFillion, Luc
    contributor authorTanguay, Monique
    contributor authorLapalme, Ervig
    contributor authorDenis, Bertrand
    contributor authorDesgagne, Michel
    contributor authorLee, Vivian
    contributor authorEk, Nils
    contributor authorLiu, Zhuo
    contributor authorLajoie, Manon
    contributor authorCaron, Jean-François
    contributor authorPagé, Christian
    date accessioned2017-06-09T16:38:46Z
    date available2017-06-09T16:38:46Z
    date copyright2010/12/01
    date issued2010
    identifier issn0882-8156
    identifier otherams-71495.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213393
    description abstractThis paper describes the recent changes to the regional data assimilation and forecasting system at the Canadian Meteorological Center. A major aspect is the replacement of the currently operational global variable resolution forecasting approach by a limited-area nested approach. In addition, the variational analysis code has been upgraded to allow limited-area three- and four-dimensional variational data assimilation (3D- and 4DVAR) analysis approaches. As a first implementation step, the constraints were to impose similar background error correlation modeling assumptions, equal computer resources, and the use of the same assimilated data. Both bi-Fourier and spherical-harmonics spectral representations of background error correlations were extensively tested for the large horizontal domain considered for the Canadian regional system. Under such conditions, it is shown that the new regional data assimilation and forecasting system performs as well as the current operational system and it produces slightly better 24-h accumulated precipitation scores as judged from an ensemble of winter and summer cases. Because of the large horizontal extent of the regional domain considered, a spherical-harmonics spectral representation of background error correlations was shown to perform better than the bi-Fourier representation, considering all evaluation scores examined in this study. The latter is more suitable for smaller domains and will be kept for the upcoming use in the kilometric-scale local analysis domains in order to support the Canadian Meteorological Center?s (CMC?s) operations using multiple domains over Canada. The CMC?s new regional system [i.e., a regional limited-area 3DVAR data assimilation system coupled to a limited-area model (REG-LAM3D)] is now undergoing its final evaluations before operational transfer. Important model and data assimilation upgrades are currently under development to fully exploit this new system and are briefly presented.
    publisherAmerican Meteorological Society
    titleThe Canadian Regional Data Assimilation and Forecasting System
    typeJournal Paper
    journal volume25
    journal issue6
    journal titleWeather and Forecasting
    identifier doi10.1175/2010WAF2222401.1
    journal fristpage1645
    journal lastpage1669
    treeWeather and Forecasting:;2010:;volume( 025 ):;issue: 006
    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