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    The Different Relationships between the ENSO Spring Persistence Barrier and Predictability Barrier

    Source: Journal of Climate:;2022:;volume( 035 ):;issue: 018::page 6207
    Author:
    Yishuai Jin
    ,
    Zhengyu Liu
    ,
    Wansuo Duan
    DOI: 10.1175/JCLI-D-22-0013.1
    Publisher: American Meteorological Society
    Abstract: In this paper, we investigate the relationship between the El Niño–Southern Oscillation (ENSO) spring persistence barrier (PB) and predictability barrier (PD) and apply it to explain the interdecadal modulation of ENSO prediction skill using the anomaly correlation coefficient (ACC). Previous studies showed that a longer persistence (i.e., autocorrelation) tends to produce a higher prediction skill. Using the recharge oscillator model of ENSO, both analytical and numerical solutions suggest that the predictability (i.e., ACC) is related to the persistence of sea surface temperature (SST) and cross correlation between SST and subsurface ocean heat content in the tropical Pacific. In particular, a larger damping rate in SST anomalies will lead to a lower persistence and ACC and a stronger PD. However, a shortened ENSO period, which controls the cross correlation, will lead to a lower persistence but a higher ACC associated with a weaker PD. Finally, we apply our solutions to observations and suggest that a higher ACC associated with a weaker PD after 1960 is caused by the shortened ENSO period.
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      The Different Relationships between the ENSO Spring Persistence Barrier and Predictability Barrier

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4290229
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    contributor authorYishuai Jin
    contributor authorZhengyu Liu
    contributor authorWansuo Duan
    date accessioned2023-04-12T18:46:33Z
    date available2023-04-12T18:46:33Z
    date copyright2022/09/15
    date issued2022
    identifier otherJCLI-D-22-0013.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290229
    description abstractIn this paper, we investigate the relationship between the El Niño–Southern Oscillation (ENSO) spring persistence barrier (PB) and predictability barrier (PD) and apply it to explain the interdecadal modulation of ENSO prediction skill using the anomaly correlation coefficient (ACC). Previous studies showed that a longer persistence (i.e., autocorrelation) tends to produce a higher prediction skill. Using the recharge oscillator model of ENSO, both analytical and numerical solutions suggest that the predictability (i.e., ACC) is related to the persistence of sea surface temperature (SST) and cross correlation between SST and subsurface ocean heat content in the tropical Pacific. In particular, a larger damping rate in SST anomalies will lead to a lower persistence and ACC and a stronger PD. However, a shortened ENSO period, which controls the cross correlation, will lead to a lower persistence but a higher ACC associated with a weaker PD. Finally, we apply our solutions to observations and suggest that a higher ACC associated with a weaker PD after 1960 is caused by the shortened ENSO period.
    publisherAmerican Meteorological Society
    titleThe Different Relationships between the ENSO Spring Persistence Barrier and Predictability Barrier
    typeJournal Paper
    journal volume35
    journal issue18
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-22-0013.1
    journal fristpage6207
    journal lastpage6218
    page6207–6218
    treeJournal of Climate:;2022:;volume( 035 ):;issue: 018
    contenttypeFulltext
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