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    Predictability of Frontal Waves and Cyclones

    Source: Weather and Forecasting:;2015:;volume( 030 ):;issue: 005::page 1291
    Author:
    Frame, Thomas H. A.
    ,
    Methven, John
    ,
    Roberts, Nigel M.
    ,
    Titley, Helen A.
    DOI: 10.1175/WAF-D-15-0039.1
    Publisher: American Meteorological Society
    Abstract: he statistical properties and skill in predictions of objectively identified and tracked cyclonic features (frontal waves and cyclones) are examined in the 15-day version of the Met Office Global and Regional Ensemble Prediction System (MOGREPS-15). The number density of cyclonic features is found to decline with increasing lead time, with analysis fields containing weak features that are not sustained past the first day of the forecast. This loss of cyclonic features is associated with a decline in area-averaged enstrophy with increasing lead time. Both feature number density and area-averaged enstrophy saturate by around 7 days into the forecast. It is found that the feature number density and area-averaged enstrophy of forecasts produced using model versions that include stochastic energy backscatter saturate at higher values than forecasts produced without stochastic physics. The ability of MOGREPS-15 to predict the locations of cyclonic features of different strengths is evaluated at different spatial scales by examining the Brier skill (relative to the analysis climatology) of strike probability forecasts: the probability that a cyclonic feature center is located within a specified radius. The radius at which skill is maximized increases with lead time from 650 km at 12 h to 950 km at 7 days. The skill is greatest for the most intense features. Forecast skill remains above zero at these scales out to 14 days for the most intense cyclonic features, but only out to 8 days when all features are included irrespective of intensity.
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      Predictability of Frontal Waves and Cyclones

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    contributor authorFrame, Thomas H. A.
    contributor authorMethven, John
    contributor authorRoberts, Nigel M.
    contributor authorTitley, Helen A.
    date accessioned2017-06-09T17:37:00Z
    date available2017-06-09T17:37:00Z
    date copyright2015/10/01
    date issued2015
    identifier issn0882-8156
    identifier otherams-88128.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231874
    description abstracthe statistical properties and skill in predictions of objectively identified and tracked cyclonic features (frontal waves and cyclones) are examined in the 15-day version of the Met Office Global and Regional Ensemble Prediction System (MOGREPS-15). The number density of cyclonic features is found to decline with increasing lead time, with analysis fields containing weak features that are not sustained past the first day of the forecast. This loss of cyclonic features is associated with a decline in area-averaged enstrophy with increasing lead time. Both feature number density and area-averaged enstrophy saturate by around 7 days into the forecast. It is found that the feature number density and area-averaged enstrophy of forecasts produced using model versions that include stochastic energy backscatter saturate at higher values than forecasts produced without stochastic physics. The ability of MOGREPS-15 to predict the locations of cyclonic features of different strengths is evaluated at different spatial scales by examining the Brier skill (relative to the analysis climatology) of strike probability forecasts: the probability that a cyclonic feature center is located within a specified radius. The radius at which skill is maximized increases with lead time from 650 km at 12 h to 950 km at 7 days. The skill is greatest for the most intense features. Forecast skill remains above zero at these scales out to 14 days for the most intense cyclonic features, but only out to 8 days when all features are included irrespective of intensity.
    publisherAmerican Meteorological Society
    titlePredictability of Frontal Waves and Cyclones
    typeJournal Paper
    journal volume30
    journal issue5
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-15-0039.1
    journal fristpage1291
    journal lastpage1302
    treeWeather and Forecasting:;2015:;volume( 030 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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