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Response of El Niño sea surface temperature variability to greenhouse warming

Nature Climate Change volume 4, pages 786–790 (2014)Cite this article

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Abstract

The destructive environmental and socio-economic impacts of the El Niño/Southern Oscillation1,2 (ENSO) demand an improved understanding of how ENSO will change under future greenhouse warming. Robust projected changes in certain aspects of ENSO have been recently established3,4,5. However, there is as yet no consensus on the change in the magnitude of the associated sea surface temperature (SST) variability6,7,8, commonly used to represent ENSO amplitude1,6, despite its strong effects on marine ecosystems and rainfall worldwide1,2,3,4,9. Here we show that the response of ENSO SST amplitude is time-varying, with an increasing trend in ENSO amplitude before 2040, followed by a decreasing trend thereafter. We attribute the previous lack of consensus to an expectation that the trend in ENSO amplitude over the entire twenty-first century is unidirectional, and to unrealistic model dynamics of tropical Pacific SST variability. We examine these complex processes across 22 models in the Coupled Model Intercomparison Project phase 5 (CMIP5) database10, forced under historical and greenhouse warming conditions. The nine most realistic models identified show a strong consensus on the time-varying response and reveal that the non-unidirectional behaviour is linked to a longitudinal difference in the surface warming rate across the Indo-Pacific basin. Our results carry important implications for climate projections and climate adaptation pathways.

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Figure 1: Observed ENSO amplitude and topical Pacific zonal winds.
Figure 2: Time variation of simulated ENSO amplitude and ENSO stability.
Figure 3: Factors driving a coupling intensity between anomalous thermocline slope and surface wind in the equatorial Pacific.
Figure 4: Time-varying MME linear trends.

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Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. S.T.K. is supported by CSIRO Office of Chief Executive and Wealth from Oceans Flagship, and W.C. is supported by the Australian Climate Change Science Program, and a CSIRO Office of Chief Executive Science Leader award. A.S. is supported by the Australian Research Council. S-I.A. is supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2009-C1AAA001-2009-0093042).

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Authors and Affiliations

  1. CSIRO Marine and Atmospheric Research, Aspendale, Victoria 3195, Australia

    Seon Tae Kim & Wenju Cai

  2. Physical Oceanography Laboratory, Qingdao Collaborative Innovation Center of Marine Science and Technology, Ocean University of China, Qingdao 266003, China

    Wenju Cai & Lixin Wu

  3. Department of Meteorology, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA

    Fei-Fei Jin

  4. ARC Centre of Excellence for Climate System Science and Climate Change Research Centre, University of New South Wales, Sydney 2052, Australia

    Agus Santoso

  5. LOCEAN, IPSL, 75252 Paris Cedex 05, France

    Eric Guilyardi

  6. NCAS-Climate, University of Reading, Reading RG6 6BB, UK

    Eric Guilyardi

  7. Department of Atmospheric Sciences, Yonsei University, Seoul 120-749, Korea

    Soon-Il An

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  1. Seon Tae Kim
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Contributions

S.T.K. and W.C. designed the study. S.T.K. performed the data analysis. S.T.K. and W.C. wrote the initial manuscript. All authors discussed the results and contributed to improvement of the manuscript.

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Correspondence to Seon Tae Kim or Wenju Cai.

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Kim, S., Cai, W., Jin, FF. et al. Response of El Niño sea surface temperature variability to greenhouse warming. Nature Clim Change 4, 786–790 (2014). https://doi.org/10.1038/nclimate2326

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