A Pacific centennial oscillation predicted by coupled GCMs

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Internal climate variability at the centennial time scale is investigated using long control integrations from three state-of-the-art global coupled general circulation models. In the absence of external forcing, all three models produce centennial variability in the mean zonal sea surface temperature (SST) and sea level pressure (SLP) gradients in the equatorial Pacific with counterparts in the extratropics. The centennial pattern in the tropical Pacific is dissimilar to that of the interannual El Nino-Southern Oscillation (ENSO), in that the most prominent expression in temperature is found beneath the surface of the western Pacific warm pool. Some global repercussions nevertheless are analogous, such as a hemispherically symmetric atmospheric wave pattern of alternating highs and lows. Centennial variability in western equatorial Pacific SST is a result of the strong asymmetry of interannual ocean heat content anomalies, while the eastern equatorial Pacific exhibits a lagged, Bjerknes-like response to temperature and convection in the west. The extratropical counterpart is shown to be a flux-driven response to the hemispherically symmetric circulation anomalies emanating from the tropical Pacific. Significant centennial-length trends in the zonal SST and SLP gradients rivaling those estimated from observations and model simulations forced with increasing CO_2 appear to be inherent features of the internal climate dynamics simulated by all three models. Unforced variability and trends on the centennial time scale therefore need to be addressed in estimated uncertainties, beyond more traditional signal-to-noise estimates that do not account for natural variability on the centennial time scale.
© 2012 American Meteorological Society. The authors thank two anonymous reviewers for their insightful comments throughout the review process, and Delia Oppo for her constructive feedback on an early draft of this manuscript. KBK gratefully acknowledges support from the WHOI Ocean and Climate Change Institute (OCCI). JES and RS were supported by NOAA's Climate Variability and Predictability Program (Award NA10OAR431037). We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and the WCRP's Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multimodel dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. Thanks especially to NOAA GFDL for providing the millennial simulation output of the GFDL CM2.1.
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