Increased variability of eastern Pacific El Niño under greenhouse warming
Open accessAbstract
The El Niño-Southern Oscillation (ENSO) is the dominant and most consequential climate variation on Earth, and is characterized by warming of equatorial Pacific sea surface temperatures (SSTs) during the El Niño phase and cooling during the La Niña phase. ENSO events tend to have a centre-corresponding to the location of the maximum SST anomaly-in either the central equatorial Pacific (5° S-5° N, 160° E-150° W) or the eastern equatorial Pacific (5° S-5° N, 150°-90° W); these two distinct types of ENSO event are referred to as the CP-ENSO and EP-ENSO regimes, respectively. How the ENSO may change under future greenhouse warming is unknown, owing to a lack of inter-model agreement over the response of SSTs in the eastern equatorial Pacific to such warming. Here we find a robust increase in future EP-ENSO SST variability among CMIP5 climate models that simulate the two distinct ENSO regimes. We show that the EP-ENSO SST anomaly pattern and its centre differ greatly from one model to another, and therefore cannot be well represented by a single SST 'index' at the observed centre. However, although the locations of the anomaly centres differ in each model, we find a robust increase in SST variability at each anomaly centre across the majority of models considered. This increase in variability is largely due to greenhouse-warming-induced intensification of upper-ocean stratification in the equatorial Pacific, which enhances ocean-atmosphere coupling. An increase in SST variance implies an increase in the number of 'strong' EP-El Niño events (corresponding to large SST anomalies) and associated extreme weather events.
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There was a lack of inter-model consensus among CMIP5 models unless model selection was applied on the basis of the realism of the simulated ENSO.
“There was a lack of inter-model consensus among available models that participated in the previous instalments of CMIP5, unless model selection was applied on the basis of the realism of the simulated ENSO 9,10 .”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
The main text says earlier assessments lacked inter-model consensus on the response of Niño3 SST variability, and the model-selection analysis says selecting models that better simulate ENSO enhanced consensus. But the same analysis reports reasonable consensus for increased E-index variance even without selection: 24 of 34 CMIP5 models (71%). The claim therefore overstates selection as necessary for consensus in general. (LLM, conf=0.88)
Experimental — accuracy not yet measuredUnder greenhouse warming, an increased air-sea coupling arising from an enhanced upper equatorial ocean stratification underpins the increase in ENSO variability.
“Under greenhouse warming, an increased air-sea coupling arising from an enhanced upper equatorial ocean stratification underpins the increase in ENSO variability 10 .”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
The paper’s summary states that enhanced upper-equatorial-Pacific stratification under greenhouse warming strengthens wind–ocean coupling and increases eastern Pacific El Niño SST variance. The citing sentence broadens this specific finding to ENSO variability generally; the passage does not establish that all ENSO variability increases. (LLM, conf=0.85)
Experimental — accuracy not yet measuredStudies based on CMIP5 models alone, or on a combination of CMIP5 and a smaller set of earlier available CMIP6 models, have found that models better simulating ENSO dynamics tend to generate increased ENSO SST variability.
“Studies based on CMIP5 models alone, or on a combination of CMIP5 and a smaller set of earlier available CMIP6 models 9,10 , have found that models better simulating ENSO dynamics tend to generate increased ENSO SST variability.”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
Models generally underestimate the nonlinear Bjerknes feedback.
“Models generally underestimate this feedback 10 .”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
Nonlinear Bjerknes feedback is particularly important: once warm SST anomalies establish deep atmospheric convection in the equatorial eastern Pacific, the response of equatorial zonal wind anomalies increases nonlinearly to further sea surface warming, amplifying El Niño growth.
“Nonlinear Bjerknes feedback is particularly important, in which once warm SST anomalies establish deep atmospheric convection in the equatorial eastern Pacific, the response of equatorial zonal wind anomalies increases nonlinearly to further sea surface warming 19 , amplifying El Niño growth 10 .”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
An inter-model consensus of increased ENSO SST variability emerges in a subset of models that simulate a reasonably realistic nonlinear positive feedback.
“As a result, an inter-model consensus of increased ENSO SST variability emerges in a subset of models that simulate a reasonably realistic nonlinear positive feedback 10 .”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
SST skewness in the eastern equatorial Pacific is an integral component of a parameter that also encapsulates skewness in the central Pacific to depict ENSO nonlinearity as a whole.
“SST skewness in the eastern equatorial Pacific is an integral component of a parameter that also encapsulates skewness in the central Pacific to depict ENSO nonlinearity as a whole 7,10 .”
From Increased ENSO sea surface temperature variability under four IPCC emission scenarios (2022) · cites this paper as [10]
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Cites
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Flagged first, then by citations
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Cited by
Sorted by citations
Increased ENSO sea surface temperature variability under four IPCC emission scenarios
Cai, W., Ng, B., Wang, G., Santoso, A., Wu, L., & Yang, K. (2022) · Nature Climate Change · doi:10.1038/s41558-022-01282-z · Cited by 263 · see citing works
Self-citationHow Does El Niño–Southern Oscillation Change Under Global Warming—A First Look at CMIP6
Fredriksen, H., Berner, J., Subramanian, A. C., & Capotondi, A. (2020) · Geophysical Research Letters · doi:10.1029/2020gl090640 · Cited by 153 · see citing works
Robust decrease in El Niño/Southern Oscillation amplitude under long-term warming
Callahan, C. W., Chen, C., Rugenstein, M., Bloch-Johnson, J., Yang, S., & Moyer, E. J. (2021) · Nature Climate Change · doi:10.1038/s41558-021-01099-2 · Cited by 87 · see citing works
Enhanced North Pacific impact on El Niño/Southern Oscillation under greenhouse warming
Jia, F., Cai, W., Gan, B., Wu, L., & Di Lorenzo, E. (2021) · Nature Climate Change · doi:10.1038/s41558-021-01139-x · Cited by 78 · see citing works
Self-citationENSO Impact on Marine Fisheries and Ecosystems
Lehodey, P., Bertrand, A., Hobday, A. J., Kiyofuji, H., McClatchie, S., Menkès, C. E., Pilling, G., Polovina, J., & Tommasi, D. (2020) · Geophysical Monograph Series · doi:10.1002/9781119548164.ch19 · Cited by 73 · see citing works
Greenhouse warming intensifies north tropical Atlantic climate variability
Yang, Y., Wu, L., Guo, Y., Gan, B., Cai, W., Huang, G., Li, X., Geng, T., Jing, Z., Li, S., et al. (2021) · Science Advances · doi:10.1126/sciadv.abg9690 · Cited by 66 · see citing works
Self-citation
- Authors
- Cai, W., Wang, G., Dewitte, B., Wu, L., Santoso, A., Takahashi, K., Yang, Y., Carréric, A., & McPhaden, M. J.
- Affiliations
- CSIRO Oceans and Atmosphere (AU)
- Universidad Católica del Norte (CL)
- Qingdao National Laboratory for Marine Science and Technology (CN)
- Servicio Nacional de Meteorología e Hidrología del Perú (PE)
- Beijing Normal University (CN)
- Laboratoire d’Études en Géophysique et Océanographie Spatiales (FR)
- NOAA Pacific Marine Environmental Laboratory (US)
- Corresponding author
- Cai, Wenju
- Wu, Lixin
- ORCID
- Venue
- Nature
- Published
- 2018-12
- Volume
- 564
- Issue
- 7735
- Pages
- 201-206
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2904020421
- Cited by
- 642
- References
- 2
- Citations by year
- 2026: 43 · 2025: 85 · 2024: 72 · 2023: 72 · 2022: 97 · 2021: 127 · 2020: 96 · 2019: 49 · 2018: 1
- FWCI
- 39.94
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Americanae (AECID Library) (publishedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- NOAA Institutional Repository (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
- Funders
- Australian Government
- Commonwealth Scientific and Industrial Research Organisation
- Joint Research Centre
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Geology and Paleoclimatology Research
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Keywords
- ENSO, eastern Pacific El Niño, global warming, sea surface temperature variability, upper ocean stratification, ocean-atmosphere interaction, CMIP5 climate models, extreme weather events, ENSO predictability
- MeSH terms
- Models, Theoretical, Pacific Ocean, Nonlinear Dynamics, Greenhouse Effect, Ecosystem, Global Warming, El Nino-Southern Oscillation
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