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    Multiseason Lead Forecast of the North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE)

    Source: Journal of Climate:;2012:;volume( 026 ):;issue: 011::page 3631
    Author:
    Villarini, Gabriele
    ,
    Vecchi, Gabriel A.
    DOI: 10.1175/JCLI-D-12-00448.1
    Publisher: American Meteorological Society
    Abstract: y considering the intensity, duration, and frequency of tropical cyclones, the power dissipation index (PDI) and accumulated cyclone energy (ACE) are concise metrics routinely used to assess tropical storm activity. This study focuses on the development of a hybrid statistical?dynamical seasonal forecasting system for the North Atlantic Ocean?s PDI and ACE over the period 1982?2011. The statistical model uses only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational record, reflecting the role of both local and nonlocal effects on the genesis and development of tropical cyclones in the North Atlantic basin. SSTs are predicted using a 10-member ensemble of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1), an experimental dynamical seasonal-to-interannual prediction system. To assess prediction skill, a set of retrospective predictions is initialized for each month from November to April, over the years 1981?2011. The skill assessment indicates that it is possible to make skillful predictions of ACE and PDI starting from November of the previous year: skillful predictions of the seasonally integrated North Atlantic tropical cyclone activity for the coming season could be made even while the current one is still under way. Probabilistic predictions for the 2012 North Atlantic tropical cyclone season are presented.
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      Multiseason Lead Forecast of the North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE)

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    contributor authorVillarini, Gabriele
    contributor authorVecchi, Gabriel A.
    date accessioned2017-06-09T17:07:01Z
    date available2017-06-09T17:07:01Z
    date copyright2013/06/01
    date issued2012
    identifier issn0894-8755
    identifier otherams-79631.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4222432
    description abstracty considering the intensity, duration, and frequency of tropical cyclones, the power dissipation index (PDI) and accumulated cyclone energy (ACE) are concise metrics routinely used to assess tropical storm activity. This study focuses on the development of a hybrid statistical?dynamical seasonal forecasting system for the North Atlantic Ocean?s PDI and ACE over the period 1982?2011. The statistical model uses only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational record, reflecting the role of both local and nonlocal effects on the genesis and development of tropical cyclones in the North Atlantic basin. SSTs are predicted using a 10-member ensemble of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1), an experimental dynamical seasonal-to-interannual prediction system. To assess prediction skill, a set of retrospective predictions is initialized for each month from November to April, over the years 1981?2011. The skill assessment indicates that it is possible to make skillful predictions of ACE and PDI starting from November of the previous year: skillful predictions of the seasonally integrated North Atlantic tropical cyclone activity for the coming season could be made even while the current one is still under way. Probabilistic predictions for the 2012 North Atlantic tropical cyclone season are presented.
    publisherAmerican Meteorological Society
    titleMultiseason Lead Forecast of the North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE)
    typeJournal Paper
    journal volume26
    journal issue11
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-12-00448.1
    journal fristpage3631
    journal lastpage3643
    treeJournal of Climate:;2012:;volume( 026 ):;issue: 011
    contenttypeFulltext
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