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    Potential Predictability of the Silk Road Pattern and the Role of SST as Inferred from Seasonal Hindcast Experiments of a Coupled Climate Model

    Source: Journal of Climate:;2020:;volume( 33 ):;issue: 022::page 9567
    Author:
    Kwan-Kit Li, Ronald;Tam, Chi-Yung;Lau, Ngar-Cheung;Sohn, Soo-Jin;Ahn, Joong-Bae
    DOI: 10.1175/JCLI-D-20-0235.1
    Publisher: American Meteorological Society
    Abstract: The Silk Road pattern (SR) is a leading mode of atmospheric circulation over midlatitude Eurasia in boreal summer. Its temporal phase is known to be unpredictable in many models. Previous studies have not reached a clear consensus on the role of sea surface temperature (SST) associated with SR. By comparing seasonal hindcasts from the Pusan National University (PNU) coupled general circulation model with reanalysis, we investigate if there are any sources of predictability originating from the SST. It was found that the PNU model cannot predict SR temporally. In fact, SR is associated with El Niño–Southern Oscillation (ENSO) in the model hindcasts, in contrast to reanalysis results in which SR is more associated with North Atlantic SST anomalies. The PNU system, however, shows potential predictability in SR associated with tropical Pacific SST. Bias in stationary Rossby waveguides is proposed as an explanation for the SR–ENSO relationship in hindcast runs. Model upper-level wind bias in the North Atlantic results in a less continuous waveguide connecting the North Atlantic to Asia, and may hinder wave propagations induced by North Atlantic SST to trigger SR. On the other hand, model upper-level wind bias in the subtropical western Pacific may favor westward propagation of zonally elongated waves from the ENSO region to trigger SR. This study implies that the role of SST with regard to SR can be substantially changed depending on the fidelity of model upper-level background winds.
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      Potential Predictability of the Silk Road Pattern and the Role of SST as Inferred from Seasonal Hindcast Experiments of a Coupled Climate Model

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    contributor authorKwan-Kit Li, Ronald;Tam, Chi-Yung;Lau, Ngar-Cheung;Sohn, Soo-Jin;Ahn, Joong-Bae
    date accessioned2022-01-30T18:01:15Z
    date available2022-01-30T18:01:15Z
    date copyright10/6/2020 12:00:00 AM
    date issued2020
    identifier issn0894-8755
    identifier otherjclid200235.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4264361
    description abstractThe Silk Road pattern (SR) is a leading mode of atmospheric circulation over midlatitude Eurasia in boreal summer. Its temporal phase is known to be unpredictable in many models. Previous studies have not reached a clear consensus on the role of sea surface temperature (SST) associated with SR. By comparing seasonal hindcasts from the Pusan National University (PNU) coupled general circulation model with reanalysis, we investigate if there are any sources of predictability originating from the SST. It was found that the PNU model cannot predict SR temporally. In fact, SR is associated with El Niño–Southern Oscillation (ENSO) in the model hindcasts, in contrast to reanalysis results in which SR is more associated with North Atlantic SST anomalies. The PNU system, however, shows potential predictability in SR associated with tropical Pacific SST. Bias in stationary Rossby waveguides is proposed as an explanation for the SR–ENSO relationship in hindcast runs. Model upper-level wind bias in the North Atlantic results in a less continuous waveguide connecting the North Atlantic to Asia, and may hinder wave propagations induced by North Atlantic SST to trigger SR. On the other hand, model upper-level wind bias in the subtropical western Pacific may favor westward propagation of zonally elongated waves from the ENSO region to trigger SR. This study implies that the role of SST with regard to SR can be substantially changed depending on the fidelity of model upper-level background winds.
    publisherAmerican Meteorological Society
    titlePotential Predictability of the Silk Road Pattern and the Role of SST as Inferred from Seasonal Hindcast Experiments of a Coupled Climate Model
    typeJournal Paper
    journal volume33
    journal issue22
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-20-0235.1
    journal fristpage9567
    journal lastpage9580
    treeJournal of Climate:;2020:;volume( 33 ):;issue: 022
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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