Preprints
https://doi.org/10.5194/esd-2022-26
https://doi.org/10.5194/esd-2022-26
 
11 Aug 2022
11 Aug 2022
Status: this preprint is currently under review for the journal ESD.

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

Nicola Maher1,2, Robert C. Jnglin Wills3, Pedro DiNezio2, Jeremy Klavans2, Sebastian Milinski4,5, Sara C. Sanchez2, Samantha Stevenson6, Malte F. Stuecker7, and Xian Wu8 Nicola Maher et al.
  • 1Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, CO 80309, USA
  • 2Department of Atmospheric and Oceanic Sciences (ATOC), University of Colorado at Boulder, Boulder, CO 80309, USA
  • 3Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA
  • 4Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80307, USA
  • 5Cooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, CO 80307, USA
  • 6Bren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
  • 7Department of Oceanography International Pacific Research Center (IPRC), School of Ocean and Earth Science and Technology (SOEST), University of Hawai‘i at Manoa, Honolulu, HI, USA
  • 8Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80305, USA

Abstract. Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find non-linear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The non-linear changes in ENSO SST variability found in many models demonstrate the importance of characterising this time-dependent behaviour, as it implies that ENSO impacts may vary dramatically throughout the 21st century.

Nicola Maher et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esd-2022-26', Anonymous Referee #1, 29 Aug 2022
  • RC2: 'Comment on esd-2022-26', Anonymous Referee #2, 31 Aug 2022

Nicola Maher et al.

Nicola Maher et al.

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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 non-linear fashion in many models and that there are large differences between models. These non-linear changes imply that ENSO impacts may vary dramatically throughout the 21st century.
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