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    GEPS-Based Monthly Prediction at the Canadian Meteorological Centre

    Source: Monthly Weather Review:;2016:;volume( 144 ):;issue: 012::page 4867
    Author:
    Lin, Hai
    ,
    Gagnon, Normand
    ,
    Beauregard, Stephane
    ,
    Muncaster, Ryan
    ,
    Markovic, Marko
    ,
    Denis, Bertrand
    ,
    Charron, Martin
    DOI: 10.1175/MWR-D-16-0138.1
    Publisher: American Meteorological Society
    Abstract: ynamical monthly prediction at the Canadian Meteorological Centre (CMC) was produced as part of the seasonal forecasting system over the past two decades. A new monthly forecasting system, which has been in operation since July 2015, is set up based on the operational Global Ensemble Prediction System (GEPS). This monthly forecasting system is composed of two components: 1) the real-time forecast, where the GEPS is extended to 32 days every Thursday; and 2) a 4-member hindcast over the past 20 years, which is used to obtain the model climatology to calibrate the monthly forecast. Compared to the seasonal prediction system, the GEPS-based monthly forecasting system takes advantage of the increased model resolution and improved initialization.Forecasts of the past 2-yr period (2014 and 2015) are verified. Analysis is performed separately for the winter half-year (November?April), and the summer half-year (May?October). Weekly averages of 2-m air temperature (T2m) and 500-hPa geopotential height (Z500) are assessed. For Z500 in the Northern Hemisphere, limited skill can be found beyond week 2 (days 12?18) in summer, while in winter some skill exists over the Pacific and North American region beyond week 2. For T2m in North America, significant skill is found over a large part of the continent all the way to week 4 (days 26?32). The distribution of the wintertime T2m skill in North America is consistent with the influence of the Madden?Julian oscillation, indicating that a significant part of predictability likely comes from the tropics.
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      GEPS-Based Monthly Prediction at the Canadian Meteorological Centre

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    contributor authorLin, Hai
    contributor authorGagnon, Normand
    contributor authorBeauregard, Stephane
    contributor authorMuncaster, Ryan
    contributor authorMarkovic, Marko
    contributor authorDenis, Bertrand
    contributor authorCharron, Martin
    date accessioned2017-06-09T17:34:08Z
    date available2017-06-09T17:34:08Z
    date copyright2016/12/01
    date issued2016
    identifier issn0027-0644
    identifier otherams-87327.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230984
    description abstractynamical monthly prediction at the Canadian Meteorological Centre (CMC) was produced as part of the seasonal forecasting system over the past two decades. A new monthly forecasting system, which has been in operation since July 2015, is set up based on the operational Global Ensemble Prediction System (GEPS). This monthly forecasting system is composed of two components: 1) the real-time forecast, where the GEPS is extended to 32 days every Thursday; and 2) a 4-member hindcast over the past 20 years, which is used to obtain the model climatology to calibrate the monthly forecast. Compared to the seasonal prediction system, the GEPS-based monthly forecasting system takes advantage of the increased model resolution and improved initialization.Forecasts of the past 2-yr period (2014 and 2015) are verified. Analysis is performed separately for the winter half-year (November?April), and the summer half-year (May?October). Weekly averages of 2-m air temperature (T2m) and 500-hPa geopotential height (Z500) are assessed. For Z500 in the Northern Hemisphere, limited skill can be found beyond week 2 (days 12?18) in summer, while in winter some skill exists over the Pacific and North American region beyond week 2. For T2m in North America, significant skill is found over a large part of the continent all the way to week 4 (days 26?32). The distribution of the wintertime T2m skill in North America is consistent with the influence of the Madden?Julian oscillation, indicating that a significant part of predictability likely comes from the tropics.
    publisherAmerican Meteorological Society
    titleGEPS-Based Monthly Prediction at the Canadian Meteorological Centre
    typeJournal Paper
    journal volume144
    journal issue12
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-16-0138.1
    journal fristpage4867
    journal lastpage4883
    treeMonthly Weather Review:;2016:;volume( 144 ):;issue: 012
    contenttypeFulltext
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