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Enhanced North Pacific impact on El Niño/Southern Oscillation under greenhouse warming

Nature Climate Change volume 11, pages 840–847 (2021)Cite this article

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Abstract

A majority of El Niño/Southern Oscillation (ENSO) events are preceded by the North Pacific Meridional Mode (NPMM), a dominant coupled ocean–atmospheric mode of variability. How the precursory NPMM forcing on ENSO responds to greenhouse warming remains unknown. Here, using climate model ensembles under high-emissions warming scenarios, we find an enhanced future impact on ENSO by the NPMM. This is manifested by increased sensitivity of boreal-winter equatorial Pacific winds and sea surface temperature (SST) anomalies to the NPMM three seasons before. The enhanced NPMM impact translates into an increased frequency of NPMM that leads to an extreme El Niño or La Niña. Under greenhouse warming, higher background SSTs cause a nonlinear evaporation–SST relationship to more effectively induce surface wind anomalies in the equatorial western Pacific, conducive to ENSO development. Thus, NPMM contributes to an increased frequency of future extreme ENSO events and becomes a more influential precursor for their predictability.

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Fig. 1: Observed and modelled forcing of the NPMM on ENSO.
Fig. 2: Enhanced impact of the NPMM forcing on ENSO under greenhouse warming.
Fig. 3: Stronger impact of the NPMM on ENSO in the future climate.
Fig. 4: Mechanism for the stronger NPMM forcing on ENSO.
Fig. 5: Enhanced impact of the NPMM forcing on ENSO in a single-model ensemble experiment.

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Data availability

Data related to the paper can be downloaded from the following websites: HadISST v1.1, https://www.metoffice.gov.uk/hadobs/hadisst/; NCEP/NCAR Reanalysis, https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.html; CMIP5 database, https://esgf-node.llnl.gov/projects/cmip5/; CMIP6 database, https://esgf-node.llnl.gov/projects/cmip6/. A detailed reference and DOI for each CMIP6 model are provided in the Supplementary Information. The CAM3.1-RGO model experiment data are available from the corresponding authors on request.

Code availability

Codes for calculating MCA and NPMM pattern are publicly available via Zenodo at https://doi.org/10.5281/zenodo.5147938 (ref. 57). All other codes are available from the corresponding author on request.

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Acknowledgements

This work is supported by the Strategic Priority Research Program of Chinese Academy of Sciences, grant number XDB40030000. F.J. is supported by the National Key Research and Development Program of China (2020YFA0608801), National Natural Science Foundation of China (NSFC) projects (41876008, 41730534) and Youth Innovation Promotion Association of Chinese Academy of Sciences (2021205). B.G. is supported by NSFC projects (41922039, 91858102) and National Key Research and Development Program of China (2019YFA0607001, 2016YFA0601804). W.C. is also supported by CSHOR. CSHOR is a joint research Centre for Southern Hemisphere Oceans Research between QNLM and CSIRO. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.

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Authors and Affiliations

  1. CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology/Center for Ocean Mega‐Science, Chinese Academy of Sciences and Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, China

    Fan Jia

  2. Centre for Southern Hemisphere Oceans Research (CSHOR), CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia

    Wenju Cai

  3. Key Laboratory of Physical Oceanography and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China and Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, China

    Wenju Cai, Bolan Gan & Lixin Wu

  4. International Laboratory for High-Resolution Earth System Prediction, Texas A&M University, College Station, TX, USA

    Bolan Gan

  5. School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA

    Emanuele Di Lorenzo

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Contributions

F.J., W.C. and L.W. designed the research; F.J. performed the experiment, analysed the data and wrote the initial manuscript with W.C.; B.G. contributed to the mechanism analysis; all authors contributed to interpreting results and improving this paper.

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Correspondence to Wenju Cai or Lixin Wu.

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Peer review information Nature Climate Change thanks Jing Ma and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Figs. 1–9, Table 1 and References.

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Jia, F., Cai, W., Gan, B. et al. Enhanced North Pacific impact on El Niño/Southern Oscillation under greenhouse warming. Nat. Clim. Chang. 11, 840–847 (2021). https://doi.org/10.1038/s41558-021-01139-x

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