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An ENSO stability analysis. Part I: results from a hybrid coupled model

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Abstract

In this study, we use the Bjerknes stability (BJ) index as a tool to investigate overall El Niño-Southern Oscillation (ENSO) stability in a hybrid-coupled model (HCM) with various atmosphere and ocean background states. This HCM shows that ENSO growth rates as measured by the BJ index and linear growth rates estimated directly with a time series of the Niño 3.4 indices from the coupled model simulations exhibit similar dependence on background states, coupling strength, and thermodynamic damping intensity. That is, the BJ index and linear growth rates increase with a decrease in the intensity of the background wind, an increase in coupling strength, or a decrease in the intensity of thermodynamic damping, although the BJ index tends to overestimate the growth rate. A detailed analysis of the components of the BJ index formula suggests the importance of model climatological background states and oceanic dynamic parameters in determining ENSO stability. We conclude that the BJ index may serve as a useful tool for qualitatively evaluating the overall ENSO stability in coupled models or in observations without a detailed eigen-analysis that is difficult to perform in models more complex than relatively simple models.

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Acknowledgments

This research is supported by NSF grants ATM 0652145 and ATM 0650552 and NOAA grants GC01-229. The authors thank Drs. Eric Guilyardi, Axel Timmermann and Shang-Ping Xie and anonymous reviewers for their valuable comments and May Izumi for her careful editing of the manuscript.

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  1. Seon Tae Kim

    Present address: Department of Earth System Science, University of California, Irvine, CA, 92697, USA

Authors and Affiliations

  1. Department of Meteorology, University of Hawai’i at Manoa, 2525 Correa Road, HIG350, Honolulu, HI, 96822, USA

    Seon Tae Kim & Fei-Fei Jin

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  1. Seon Tae Kim
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  2. Fei-Fei Jin
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Correspondence to Seon Tae Kim.

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Kim, S.T., Jin, FF. An ENSO stability analysis. Part I: results from a hybrid coupled model. Clim Dyn 36, 1593–1607 (2011). https://doi.org/10.1007/s00382-010-0796-0

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