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    Application of Unsupervised Learning Techniques to Identify Atlantic Tropical Cyclone Rapid Intensification Environments

    Source: Journal of Applied Meteorology and Climatology:;2021:;volume( 060 ):;issue: 001::page 119
    Author:
    Mercer, Andrew E.;Grimes, Alexandria D.;Wood, Kimberly M.
    DOI: 10.1175/JAMC-D-20-0105.1
    Publisher: American Meteorological Society
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      Application of Unsupervised Learning Techniques to Identify Atlantic Tropical Cyclone Rapid Intensification Environments

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4281380
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    contributor authorMercer, Andrew E.;Grimes, Alexandria D.;Wood, Kimberly M.
    date accessioned2022-03-26T20:24:42Z
    date available2022-03-26T20:24:42Z
    date copyright01 Jan. 2021
    date issued2021
    identifier otherjamc-d-20-0105.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4281380
    publisherAmerican Meteorological Society
    titleApplication of Unsupervised Learning Techniques to Identify Atlantic Tropical Cyclone Rapid Intensification Environments
    typeJournal Paper
    journal volume60
    journal issue1
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/JAMC-D-20-0105.1
    journal fristpage119
    journal lastpage138
    treeJournal of Applied Meteorology and Climatology:;2021:;volume( 060 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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