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    Variability and Predictability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Atmospheric Simulations

    Source: Journal of Climate:;2019:;volume 032:;issue 011::page 3153
    Author:
    Mei, Wei
    ,
    Kamae, Youichi
    ,
    Xie, Shang-Ping
    ,
    Yoshida, Kohei
    DOI: 10.1175/JCLI-D-18-0554.1
    Publisher: American Meteorological Society
    Abstract: AbstractVariability of North Atlantic annual hurricane frequency during 1951?2010 is studied using a 100-member ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The ensemble mean results well capture the interannual-to-decadal variability of hurricane frequency in best track data since 1970, and suggest that the current best track data might underestimate hurricane frequency prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the main development region (MDR) accounts for more than 80% of the SST-forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a useful predictor; a 1°C increase in this SST difference produces 7.05 ± 1.39 more hurricanes. The hurricane frequency also exhibits strong internal variability that is systematically larger in the model than observations. The seasonal-mean environment is highly correlated among ensemble members and contributes to less than 10% of the ensemble spread in hurricane frequency. The strong internal variability is suggested to originate from weather to intraseasonal variability and nonlinearity. In practice, a 20-member ensemble is sufficient to capture the SST-forced variability.
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      Variability and Predictability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Atmospheric Simulations

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4263128
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    contributor authorMei, Wei
    contributor authorKamae, Youichi
    contributor authorXie, Shang-Ping
    contributor authorYoshida, Kohei
    date accessioned2019-10-05T06:41:49Z
    date available2019-10-05T06:41:49Z
    date copyright3/14/2019 12:00:00 AM
    date issued2019
    identifier otherJCLI-D-18-0554.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263128
    description abstractAbstractVariability of North Atlantic annual hurricane frequency during 1951?2010 is studied using a 100-member ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The ensemble mean results well capture the interannual-to-decadal variability of hurricane frequency in best track data since 1970, and suggest that the current best track data might underestimate hurricane frequency prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the main development region (MDR) accounts for more than 80% of the SST-forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a useful predictor; a 1°C increase in this SST difference produces 7.05 ± 1.39 more hurricanes. The hurricane frequency also exhibits strong internal variability that is systematically larger in the model than observations. The seasonal-mean environment is highly correlated among ensemble members and contributes to less than 10% of the ensemble spread in hurricane frequency. The strong internal variability is suggested to originate from weather to intraseasonal variability and nonlinearity. In practice, a 20-member ensemble is sufficient to capture the SST-forced variability.
    publisherAmerican Meteorological Society
    titleVariability and Predictability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Atmospheric Simulations
    typeJournal Paper
    journal volume32
    journal issue11
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-18-0554.1
    journal fristpage3153
    journal lastpage3167
    treeJournal of Climate:;2019:;volume 032:;issue 011
    contenttypeFulltext
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