4.7 Article

ENSO-Like and ENSO-Induced Tropical Pacific Decadal Variability in CGCMs

期刊

JOURNAL OF CLIMATE
卷 26, 期 5, 页码 1485-1501

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-12-00118.1

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资金

  1. Korea Meteorological Administration Research and Development Program [CATER 2012-3043]
  2. Korea Meteorological Administration [CATER-2012-3043] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Outputs from coupled general circulation models (CGCMs) are used in examining tropical Pacific decadal variability (TPDV) and their relationships with El Nino-Southern Oscillation (ENSO). Herein TPDV is classified as either ENSO-induced TPDV (EIT) or ENSO-like TPDV (ELT), based on their correlations with a decadal modulation index of ENSO amplitude and spatial pattern. EIT is identified by the leading EOF mode of the low-pass filtered equatorial subsurface temperature anomalies and is highly correlated with the decadal ENSO modulation index. This mode is characterized by an east-west dipole structure along the equator. ELT is usually defined by the first EOF mode of subsurface temperature, of which the spatial structure is similar to ENSO. Generally, this mode is insignificantly correlated with the decadal modulation of ENSO. EIT closely interacts with the residuals induced by ENSO asymmetries, both of which show similar spatial structures. On the other hand, ELT is controlled by slowly varying ocean adjustments analogous to a recharge oscillator of ENSO. Both types of TPDV have similar spectral peaks on a decadal-to-interdecadal time scale. Interestingly, the variances of both types of TPDV depend on the strength of connection between El Nino-La Nina residuals and EIT, such that the strong two-way feedback between them enhances EIT and reduces ELT. The strength of the two-way feedback is also related to ENSO variability. The flavors of El Nino-La Nina with respect to changes in the tropical Pacific mean state tend to be well simulated when ENSO variability is larger in CGCMs. As a result, stronger ENSO variability leads to intensified interactive feedback between ENSO residuals and enhanced EIT in CGCMs.

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