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    Detecting Shifts in Hurricane Rates Using a Markov Chain Monte Carlo Approach

    Source: Journal of Climate:;2004:;volume( 017 ):;issue: 013::page 2652
    Author:
    Elsner, James B.
    ,
    Niu, Xufeng
    ,
    Jagger, Thomas H.
    DOI: 10.1175/1520-0442(2004)017<2652:DSIHRU>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Time series of annual hurricane counts are examined using a changepoint analysis. The approach simulates posterior distributions of the Poisson-rate parameter using Gibbs sampling. A posterior distribution is a distribution of a parameter conditional on the data. The analysis is first performed on the annual series of major North Atlantic hurricane counts from the twentieth century. Results show significant shifts in hurricane rates during the middle 1940s, the middle 1960s, and at 1995, consistent with earlier published results. The analysis is then applied to U.S. hurricane activity. Results show no abrupt changes in overall coastal hurricane rates during the twentieth century. In contrast, the record of Florida hurricanes indicates downward shifts during the early 1950s and the late 1960s. The shifts result from fewer hurricanes passing through the Bahamas and the western Caribbean Sea. No significant rate shifts are noted along either the Gulf or East Coasts. Climate influences on coastal hurricane activity are then examined. Results show a significant reduction in U.S. hurricane activity during strong El Niño events and during the positive phase of the North Atlantic Oscillation (NAO). ENSO effects are prominent over Florida while NAO effects are concentrated along the Gulf Coast.
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      Detecting Shifts in Hurricane Rates Using a Markov Chain Monte Carlo Approach

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4207822
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    • Journal of Climate

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    contributor authorElsner, James B.
    contributor authorNiu, Xufeng
    contributor authorJagger, Thomas H.
    date accessioned2017-06-09T16:21:47Z
    date available2017-06-09T16:21:47Z
    date copyright2004/07/01
    date issued2004
    identifier issn0894-8755
    identifier otherams-6648.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4207822
    description abstractTime series of annual hurricane counts are examined using a changepoint analysis. The approach simulates posterior distributions of the Poisson-rate parameter using Gibbs sampling. A posterior distribution is a distribution of a parameter conditional on the data. The analysis is first performed on the annual series of major North Atlantic hurricane counts from the twentieth century. Results show significant shifts in hurricane rates during the middle 1940s, the middle 1960s, and at 1995, consistent with earlier published results. The analysis is then applied to U.S. hurricane activity. Results show no abrupt changes in overall coastal hurricane rates during the twentieth century. In contrast, the record of Florida hurricanes indicates downward shifts during the early 1950s and the late 1960s. The shifts result from fewer hurricanes passing through the Bahamas and the western Caribbean Sea. No significant rate shifts are noted along either the Gulf or East Coasts. Climate influences on coastal hurricane activity are then examined. Results show a significant reduction in U.S. hurricane activity during strong El Niño events and during the positive phase of the North Atlantic Oscillation (NAO). ENSO effects are prominent over Florida while NAO effects are concentrated along the Gulf Coast.
    publisherAmerican Meteorological Society
    titleDetecting Shifts in Hurricane Rates Using a Markov Chain Monte Carlo Approach
    typeJournal Paper
    journal volume17
    journal issue13
    journal titleJournal of Climate
    identifier doi10.1175/1520-0442(2004)017<2652:DSIHRU>2.0.CO;2
    journal fristpage2652
    journal lastpage2666
    treeJournal of Climate:;2004:;volume( 017 ):;issue: 013
    contenttypeFulltext
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