The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences

Maher, Nicola; Wills, Robert C. Jnglin; DiNezio, Pedro; Klavans, Jeremy; Milinski, Sebastian; Sanchez, Sara C.; Stevenson, Samantha; Stuecker, Malte F.; Wu, Xian

doi:https://doi.org/10.5194/esd-14-413-2023

Articles | Volume 14, issue 2

https://doi.org/10.5194/esd-14-413-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-14-413-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 2

Research article

|

14 Apr 2023

Research article |

| 14 Apr 2023

The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences

Nicola Maher, Robert C. Jnglin Wills, Pedro DiNezio, Jeremy Klavans, Sebastian Milinski, Sara C. Sanchez, Samantha Stevenson, Malte F. Stuecker, and Xian Wu

Supplement

https://doi.org/10.5194/esd-14-413-2023-supplement

Data sets

An open infrastructure for access to distributed geospatial data ESGF (The Earth System Grid Federation) https://doi.org/10.1016/j.future.2013.07.002

Multi-Model Large Ensemble Archive (MMLEA) Multi-Model Large Ensemble Archive (MMLEA) https://www.cesm.ucar.edu/community-projects/mmlea

CESM2 Large Ensemble Community Project (LENS2) CESM2 Large Ensemble Community Project (LENS2) https://www.cesm.ucar.edu/community-projects/lens2

GFDL SPEAR Large Ensembles GFDL SPEAR Large Ensembles https://www.gfdl.noaa.gov/spear_large_ensembles/

MPI Grand Ensemble Max-Planck-Institut für Meteorologie https://esgf-data.dkrz.de/projects/mpi-ge/

The ETH Zurich CMIP6 next generation archive: technical documentation L. Brunner, M. Hauser, R. Lorenz, and U. Beyerle https://doi.org/10.5281/zenodo.3734128

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Short summary

Understanding whether the El Niño–Southern Oscillation (ENSO) is likely to change in the future is important due to its widespread impacts. By using large ensembles, we can robustly isolate the time-evolving response of ENSO variability in 14 climate models. We find that ENSO variability evolves in a nonlinear fashion in many models and that there are large differences between models. These nonlinear changes imply that ENSO impacts may vary dramatically throughout the 21st century.