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    An Analysis of the Temporal Evolution of ENSO Prediction Skill in the Context of the Equatorial Pacific Ocean Observing System

    Source: Monthly Weather Review:;2015:;volume( 143 ):;issue: 008::page 3204
    Author:
    Kumar, Arun
    ,
    Chen, Mingyue
    ,
    Xue, Yan
    ,
    Behringer, David
    DOI: 10.1175/MWR-D-15-0035.1
    Publisher: American Meteorological Society
    Abstract: ubsurface ocean observations in the equatorial tropical Pacific Ocean dramatically increased after the 1990s because of the completion of the TAO moored array and a steady increase in Argo floats. In this analysis the question explored is whether a steady increase in ocean observations can be discerned in improvements in skill of predicting sea surface temperature (SST) variability associated with El Niño?Southern Oscillation (ENSO)? The analysis is based on the time evolution of skill of sea surface temperatures in the equatorial tropical Pacific since 1982 based on a seasonal prediction system. It is found that for forecasts up to a 6-month lead time, a clear fingerprint of increases in subsurface ocean observations is not readily apparent in the time evolution of prediction skill that is dominated much more by the signal-to-noise consideration of SSTs to be predicted. Finding no clear relationship between an increase in ocean observations and prediction skill of SSTs, various possibilities for why it may be so are discussed. This discussion is to motivate further exploration on the question of the tropical Pacific observing system, its influence on the skill of ENSO prediction, and the capabilities of the current generation of coupled models and ocean data assimilation systems to take advantage of ocean observations.
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      An Analysis of the Temporal Evolution of ENSO Prediction Skill in the Context of the Equatorial Pacific Ocean Observing System

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4230714
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    contributor authorKumar, Arun
    contributor authorChen, Mingyue
    contributor authorXue, Yan
    contributor authorBehringer, David
    date accessioned2017-06-09T17:32:59Z
    date available2017-06-09T17:32:59Z
    date copyright2015/08/01
    date issued2015
    identifier issn0027-0644
    identifier otherams-87084.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230714
    description abstractubsurface ocean observations in the equatorial tropical Pacific Ocean dramatically increased after the 1990s because of the completion of the TAO moored array and a steady increase in Argo floats. In this analysis the question explored is whether a steady increase in ocean observations can be discerned in improvements in skill of predicting sea surface temperature (SST) variability associated with El Niño?Southern Oscillation (ENSO)? The analysis is based on the time evolution of skill of sea surface temperatures in the equatorial tropical Pacific since 1982 based on a seasonal prediction system. It is found that for forecasts up to a 6-month lead time, a clear fingerprint of increases in subsurface ocean observations is not readily apparent in the time evolution of prediction skill that is dominated much more by the signal-to-noise consideration of SSTs to be predicted. Finding no clear relationship between an increase in ocean observations and prediction skill of SSTs, various possibilities for why it may be so are discussed. This discussion is to motivate further exploration on the question of the tropical Pacific observing system, its influence on the skill of ENSO prediction, and the capabilities of the current generation of coupled models and ocean data assimilation systems to take advantage of ocean observations.
    publisherAmerican Meteorological Society
    titleAn Analysis of the Temporal Evolution of ENSO Prediction Skill in the Context of the Equatorial Pacific Ocean Observing System
    typeJournal Paper
    journal volume143
    journal issue8
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-15-0035.1
    journal fristpage3204
    journal lastpage3213
    treeMonthly Weather Review:;2015:;volume( 143 ):;issue: 008
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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