The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index; 17 of the 37 sources its claims cite were checked for support.
Increased ENSO sea surface temperature variability under four IPCC emission scenarios
Open accessAbstract
Sea surface temperature (SST) variability of El Niño–Southern Oscillation (ENSO) underpins its global impact, and its future change is a long-standing science issue. In its sixth assessment, the IPCC reports no systematic change in ENSO SST variability under any emission scenarios considered. However, comparison between the 20th and 21st century shows a robust increase in century-long ENSO SST variability under four IPCC plausible emission scenarios.
Overview
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Written from the paper’s full text.
TL;DR
Using CMIP6 models, the paper finds a robust inter-model consensus that ENSO SST variability increases in the 21st century relative to the 20th century under all four IPCC SSP scenarios, contrary to the IPCC AR6 assessment of no systematic change. The increase is statistically significant in multi-model means and is linked to stronger nonlinear Bjerknes feedback and air–sea coupling.
Key findings
- Under SSP585, 38 out of 43 (88.4%) CMIP6 models show greater Niño3.4 SST variability in 2000–2099 than in 1900–1999; the multi-model ensemble mean increase is 16.1%, statistically significant by a bootstrap test, and 15.7% when inter-model differences in ENSO amplitude are removed.
- Under SSP126, 34 out of 39 (87.2%) models show an increase in Niño3.4 SST variability, with a statistically significant multi-model mean increase of 11.7%.
- Across the four SSP scenarios, inter-model consensus ranges are 78.6–88.4% for Niño3.4, 76.2–81.6% for Niño3, and 73.8–81.4% for Niño4.
- With 50-year periods, 34 out of 43 (79.1%) models under SSP585 and 27 out of 39 (69.2%) under SSP126 produce increased ENSO SST variability; the relationship between stronger nonlinear Bjerknes feedback and greater future ENSO variability is statistically significant above the 99% confidence level.
Methods
- Analyzed all available CMIP6 SST outputs under SSP126 (39 models), SSP245 (42), SSP370 (38), and SSP585 (43), each covering 1900–2099, using one experiment per model; historical forcing was applied to 2014 and scenario forcing thereafter.
- Constructed monthly climatology over 1900–1999, computed SST anomalies, quadratically detrended them over the full 200 years, and calculated standard deviations over Niño3, Niño4, and Niño3.4 regions; compared 2000–2099 versus 1900–1999 and 2050–2099 versus 1965–2014.
- Used a bootstrap method with 10,000 resamples to test whether multi-model mean increases exceed internal variability at the 95% confidence level; an alternative normalization by each model’s full 200-year standard deviation was also applied.
Limitations
- Stated: the results are based on IPCC 21st-century transient warming scenarios, whereas studies showing decreased ENSO variability after instantaneous CO2 doubling/quadrupling concern equilibrium states; ocean mesoscale eddy-induced vertical heat transport is not resolved in CMIP6, so its effect is unknown.
- Stated: the conclusion is based solely on CMIP6 models, while a study using 36 CMIP5 and 20 CMIP6 models finds a large spread with no inter-model consensus, suggesting sensitivity to model generation; the result is also opposite to an observed ENSO variability decline since 1999/2000, which might be masked by decadal variability and not yet detectable.
- Evident from the text: short 30-year sampling periods, such as those used in the AR6 assessment, are strongly influenced by decadal climate fluctuations, stochastic noise, and the butterfly effect, which can obscure greenhouse-forced changes; the paper addresses this by using 100-year and 50-year periods.
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Claims the paper makes
26 Own result · 9 No full text of the sources · 5 Supported so far · 5 Partly supported · 4 Own interpretation · 3 Supported · 3 Own method · 1 No basis given · accuracy not yet measured
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“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.”
What the sources say
- Not checked — no full text of the sourcecites [9] Cai, W. et al. ENSO and greenhouse warming. Nat. Clim. Change 5, 849–859 (2015). source
- Supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). source
The main text reports that this CMIP5-only study selected models able to simulate the two distinct ENSO regimes and found a robust future increase in eastern-Pacific ENSO SST variance. The CMIP5–CMIP6 combination in the citing sentence is not attributed specifically to this paper. (LLM, conf=0.90)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Under greenhouse warming, an increased air-sea coupling arising from an enhanced upper equatorial ocean stratification underpins the increase in ENSO variability 10 .”
What the sources say
- Partly supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). sourceExperimental — accuracy not yet measured
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)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The IPCC AR6 statement on ENSO SST variability is contrary to studies 5-7 based on climate models participating in the sixth phase of the Coupled Model Intercomparison Project 8 (CMIP6).”
What the sources say
- Partly supportedcites [5] Fredriksen, H.-B., Berner, J., Subramanian, A. C. & Capotondi, A. How does El Niño-Southern Oscillation change under global warming – a first look at CMIP6. Geophys. Res. Lett. 47, e2020GL090640 (2020). sourceExperimental — accuracy not yet measured
The Results (§3.2) and Summary and Conclusion (§4) report increased ENSO-related SST variance in most of the 11 CMIP6 models, supporting the description of this paper as a CMIP6 study of ENSO SST variability. The paper does not discuss the IPCC AR6 statement or establish that its findings are contrary to it; that comparison is the citing authors’ framing. (LLM, conf=0.84)
- Supportedcites [6] Yang, Y. et al. Greenhouse warming intensifies north tropical Atlantic climate variability. Sci. Adv. 7, eabg9690 (2021). source
In Results, under “Increased ENSO variability” (page unavailable), the paper reports increased Niño3.4 variability under warming in 12 of 16 selected CMIP6 models and 16 of all 23 models. Materials and Methods, “Observed and CMIP6 data” (page unavailable), confirms that the study uses CMIP6 models. The comparison with the IPCC AR6 statement is the citing authors’ framing, not a statement attributed to this source. (LLM, conf=0.90)
- Not checked — no full text of the sourcecites [7] Cai, W. et al. Changing El Niño–Southern Oscillation in a warming climate. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-021-00199-z (2021). source
- Supportedcites [8] Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016). source
Citation 8 is attached to the identification of CMIP6, not to the claim that the IPCC AR6 statement conflicts with studies 5–7. The paper’s title identifies it as an overview of the Coupled Model Intercomparison Project Phase 6, and Section 2 describes modelling centres contributing to CMIP6. No page number is available in our copy. (LLM, conf=0.93)
plain- Asserted: passes — The authors put it forward as true.
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- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“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 .”
What the sources say
- Not checked — no full text of the sourcecites [9] Cai, W. et al. ENSO and greenhouse warming. Nat. Clim. Change 5, 849–859 (2015). source
- Partly supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). sourceExperimental — accuracy not yet measured
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)
plain- Asserted: passes — The authors put it forward as true.
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Every source the paper cites for this claim was checked and supports it.
In the paper
“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 .”
What the sources say
- Supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). source
The main text reports that 17 models with a reasonable nonlinear relationship were selected to assess eastern Pacific (EP) ENSO change, and that 15 of those 17 project increased E-index variance. The Diagnosis of nonlinear Bjerknes feedback section says their nonlinear response is close to the observed value. The consensus reported here concerns EP ENSO SST variability. (LLM, conf=0.92)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Models generally underestimate this feedback 10 .”
What the sources say
- Supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). source
The main text says that most of the 34 models have a lower-than-observed measure of ENSO nonlinearity, and that the 17 non-selected models show a weaker nonlinear Bjerknes feedback. The Methods section reports that the selected models' response is close to the observed value, so the claim is supported as a generalization, not as a statement about every model. (LLM, conf=0.90)
plain- Asserted: passes — The authors put it forward as true.
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- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Because ENSO SST variability underpins consequential ENSO-related climate variability and climate extremes within and outside the Pacific 6,11,12 , how ENSO SST variability might respond to greenhouse warming is a fundamental issue in climate change science 7,9,13 , with critical societal ramifications.”
What the sources say
- Supportedcites [6] Yang, Y. et al. Greenhouse warming intensifies north tropical Atlantic climate variability. Sci. Adv. 7, eabg9690 (2021). source
The Results section describes ENSO-related precipitation changes within the Pacific and shows that ENSO variability influences climate variability in the north tropical Atlantic. The Discussion links that remote variability to droughts, floods, and extreme Atlantic hurricanes. Together, these passages support the broad claim about climate variability and extremes within and outside the Pacific; page numbers are unavailable in our copy. (LLM, conf=0.87)
- Not checked — no full text of the sourcecites [11] Ashok, K., Behera, S. K., Rao, S. A., Weng, H. Y. & Yamagata, T. El Niño Modoki and its possible teleconnection. J. Geophys. Res. 112, C11007 (2007). source
- Supportedcites [12] Cai, W. et al. Climate impacts of the El Niño–Southern Oscillation on South America. Nat. Rev. Earth Environ. 1, 215–231 (2020). source
The Introduction says that the location of ENSO sea-surface temperature anomalies has major consequences for impacts in South America and other regions of the globe. Section 3, “Mechanism for ENSO impact” (page unavailable), describes ENSO effects on rainfall and temperature through local forcing and remote teleconnections, and notes that extreme-event frequency is generally more affected in ENSO years. (LLM, conf=0.88)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“However, sampling ENSO SST variability over relatively short 30-year running periods would be subject to a strong influence from decadal climate fluctuations such that stochastic noise and butterfly effect can obscure the impact of greenhouse forcing [14][15][16] .”
What the sources say
- Supportedcites [14] Maher, N., Matei, D., Milinski, S. & Marotzke, J. ENSO change in climate projections: forced response or internal variability? Geophys. Res. Lett. 45, 11–390 (2018). source
The Introduction (page unavailable) describes strong decadal and interdecadal ENSO variability and says internal variability arises from the climate system’s chaotic nature. Section 4 (page unavailable) finds that internal variability on 30-year timescales exceeds observed changes, which therefore cannot be attributed to forcing. This supports the claim that variability can obscure a greenhouse-forced signal in short analysis periods. (LLM, conf=0.91)
- Not checked — no full text of the sourcecites [15] Zheng, X.-T., Hui, C. & Yeh, S. W. Response of ENSO amplitude to global warming in CESM large ensemble: uncertainty due to internal variability. Clim. Dyn. 50, 4019–4035 (2018). source
- Partly supportedcites [16] Cai, W. et al. Butterfly effect and a self-modulating El Niño response to global warming. Nature 585, 68–73 (2020). sourceExperimental — accuracy not yet measured
The Conclusion and implications says decadal variability, stochastic forcing and butterfly perturbations can shape ENSO variability and its response to greenhouse warming. That supports the general concern about obscuring a forced signal, but our copy does not establish it specifically for 30-year running periods; its main comparisons use 50-year periods. (LLM, conf=0.83)
hedgeddirect- Asserted: passes — The authors put it forward as true.
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- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the SSP126 scenario (Fig. 1b), which represents a strong mitigation path under the Paris Agreement to limit warming to 1.5-2.0°C relative to the pre-industrial level, a total of 34 out of 39 models (87.2%) generate an increase in Niño3.4SST variability.”
plaindirect- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A similar increase (15.7%) is obtained when inter-model differences in representing ENSO amplitude are removed (Extended Data Fig. 2).”
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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- Probably not a substantial claim. 8
- It may state two separate claims as one. 8
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Besides some improvements in the representation of the tropical Pacific climate 20 , more CMIP6 models simulate realistic ENSO nonlinear feedbacks 7 .”
What the sources say
- Partly supportedcites [20] Planton, Y. et al. Evaluating climate models with the CLIVAR 2020 ENSO metrics package. Bull. Am. Meteorol. Soc. 102, E193–E217 (2021). sourceExperimental — accuracy not yet measured
The Summary reports improved ENSO patterns and other metrics in CMIP6, but it does not establish that more models simulate realistic nonlinear feedbacks. The Evaluation of ENSO processes says none of its five feedback-process metrics improved significantly from CMIP5 to CMIP6, and one degraded; it also notes that numerous nonlinear processes were not included in that short metric list. (LLM, conf=0.83)
- Not checked — no full text of the sourcecites [7] Cai, W. et al. Changing El Niño–Southern Oscillation in a warming climate. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-021-00199-z (2021). source
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“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 .”
What the sources say
- Not checked — no full text of the sourcecites [19] Dommenget, D., Bayr, T. & Frauen, C. Analysis of the non-linearity in the pattern and time evolution of El Niño–Southern Oscillation. Clim. Dyn. 40, 2825–2847 (2013). source
- Supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
Every source the paper cites for this claim was checked and supports it.
In the paper
“In addition, our conclusion is based solely on CMIP6 models, but a recent study based on 36 CMIP5 models and 20 CMIP6 models 23 finds a large spread in the projected ENSO change with no inter-model consensus; the discrepancy suggests a sensitivity of our result to model generations.”
What the sources say
- Supportedcites [23] Beobide-Arsuaga, G. et al. Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models. Clim. Dyn. 56, 3875–3888 (2021). source
Section 2.1 (Data) states that the study analyzed 36 CMIP5 and 20 CMIP6 models. Section 6 (Summary and discussion) reports that the models highly disagree on future ENSO amplitude change, with projections ranging from decreases to increases. (LLM, conf=0.94)
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“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 .”
What the sources say
- Not checked — no full text of the sourcecites [7] Cai, W. et al. Changing El Niño–Southern Oscillation in a warming climate. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-021-00199-z (2021). source
- Supportedcites [10] Cai, W. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018). source
In the main text (page not supplied), the paper says that parameter α connects the E-index and C-index skewness values and measures ENSO diversity, encapsulating nonlinear feedback. Figure 1’s caption likewise describes α as a measure of the contrast between eastern- and central-Pacific ENSO regimes and their skewness. (LLM, conf=0.92)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“consistent with findings by previous studies of a stronger rainfall response to ENSO SST variability even if ENSO SST variability itself does not change 2-4 .”
What the sources say
- Not checked — no full text of the sourcecites [2] Power, S. B., Delage, F., Chung, C., Kociuba, G. & Keay, K. Robust twenty-first century projections of El Niño and related precipitation variability. Nature 502, 541–545 (2013). source
- Not checked — no full text of the sourcecites [3] Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014). source
- Supportedcites [4] Wang, G. et al. Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization. Nat. Clim. Change 7, 568–572 (2017). source
The “Robust underpinning process” section says warming reduces the meridional surface-temperature gradient, making extreme El Niño easier to induce even if temperature variability does not change. The “Additional information” section links that reduced gradient to convection and extraordinary eastern equatorial Pacific rainfall, supporting the paraphrase’s rainfall-response point. Our copy provides no page numbers for these passages. (LLM, conf=0.85)
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The multi-model ensemble mean increase (16.1%) is statistically significant according to a Bootstrap method 18 (see 'Bootstrap test' in Methods and Extended Data Fig. 1).”
What the sources say
- Not checked — no full text of the sourcecites [18] Austin, P. C. & Tu, J. V. Bootstrap methods for developing predictive models. Am. Stat. 58, 131–137 (2004). source
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The multi-model ensemble mean increase (11.7%) is statistically significant.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using statistics over another longer period, for example, 50 years of the current climate of 1965-2015 and the future climate of 2050-2099, an inter-model consensus emerges, with a total of 34 out of 43 (79.1%)models under SSP585, and 27 out of 39 (69.2%) models under SSP126, generating an increase in Niño3.4SST variability (Fig. 2a,b).”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“As such, the skewness in three model outliers that project a decrease in ENSO variability in Figs. 1 and 2 is either small (UKESM1-0-LL) or negative (BCC-CSM2-MR, CESM2).”
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Inter-model consensus is seen in all four SSP emission scenarios (Extended Data Figs.3, 4 and 5), ranging between 78.6-88.4% for Niño3.4,76.2-81.6% for Niño3, and 73.8-81.4% for Niño4 across emission scenarios.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Even on centennial timescales, ENSO variability is influenced by internal climate fluctuations 17 .”
What the sources say
- Not checked — no full text of the sourcecites [17] Li, J. et al. Interdecadal modulation of El Niño amplitude during the past millennium. Nat. Clim. Change 1, 114–118 (2011). source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, as the period for calculating ENSO statistics lengthens, the influence of internal variability tapers off, whereas the effect of greenhouse warming is better diagnosed.”
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We also note that our result is opposite to an observed decline in ENSO variability since 1999/2000 (ref.24 ); however, any greenhouse warming-induced ENSO variability change in the two decades since 1999/2000 might be masked by decadal variability and not yet detectable.”
hedged- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Further, ocean mesoscale eddy-induced vertical heat transport is part of ENSO dynamics 22 , but is not resolved in CMIP6 models; as such, whether or how incorporation of ocean mesoscale eddies alters our conclusion is not known.”
What the sources say
- Not checked — no full text of the sourcecites [22] Wengel, C. et al. Future high-resolution El Niño/Southern Oscillation dynamics. Nat. Clim. Change 11, 758–765 (2021). source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“we note findings of decreased ENSO variability 21,22 in equilibrium state after an instantaneous doubling/quadrupling of CO 2 , which seemingly contradict our conclusion”
What the sources say
- Not checked — no full text of the sourcecites [21] Callahan, C. W. et al. Robust decrease in El Niño/Southern Oscillation amplitude under long-term warming. Nat. Clim. Change 11, 752–757 (2021). source
- Not checked — no full text of the sourcecites [22] Wengel, C. et al. Future high-resolution El Niño/Southern Oscillation dynamics. Nat. Clim. Change 11, 758–765 (2021). source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
A long analysis period reduces the effect of internal variability, allowing a better detection of the greenhouse-forced effect.
“A long analysis period reduces the effect of internal variability, allowing a better detection of the greenhouse-forced effect.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Increased ENSO sea surface temperature variability under four IPCC emission scenarios
“50 years of the current climate of 1965-2015 and the future climate of 2050-2099”
§ CMIP6 models.
“between the 50-year future climate of 2050-2099 and current climate of 1965-2014 (Fig. 2).”
Citations
Cites
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-1937-2016 · Cited by 11,981
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., & Kaplan, A. (2003) · Journal of Geophysical Research Atmospheres · doi:10.1029/2002jd002670 · Cited by 11,133
El Niño Modoki and its possible teleconnection
Ashok, K., Behera, S. K., Rao, S. A., Weng, H., & Yamagata, T. (2007) · Journal of Geophysical Research: Oceans · doi:10.1029/2006jc003798 · Cited by 2,721
Increasing frequency of extreme El Niño events due to greenhouse warming.
Cai, W., Borlace, S., Lengaigne, M., van Rensch, P., Collins, M., Vecchi, G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., et al. (2014) · Nature Climate Change · doi:10.1038/nclimate2100 · Cited by 2,198
Self-citationThe impact of global warming on the tropical Pacific Ocean and El Niño
Collins, M., An, S.-I., Cai, W., Ganachaud, A., Guilyardi, E., Jin, F.-F., Jochum, M., Lengaigne, M., Power, S., Timmermann, A., et al. (2010) · Nature Geoscience · doi:10.1038/ngeo868 · Cited by 1,230
Self-citationCai, W., Santoso, A., Wang, G., Yeh, S.-W., An, S.-I., Cobb, K. M., Collins, M., Guilyardi, E., Jin, F.-F., Kug, J.-S., et al. (2015) · Nature Climate Change · doi:10.1038/nclimate2743 · Cited by 891
Self-citationClimate impacts of the El Niño–Southern Oscillation on South America
Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., et al. (2020) · Nature Reviews Earth & Environment · doi:10.1038/s43017-020-0040-3 · Cited by 782
Self-citationChanging El Niño–Southern Oscillation in a warming climate
Cai, W., Santoso, A., Collins, M., Dewitte, B., Karamperidou, C., Kug, J.-S., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Taschetto, A. S., et al. (2021) · Nature Reviews Earth & Environment · doi:10.1038/s43017-021-00199-z · Cited by 702
Self-citationIncreased variability of eastern Pacific El Niño under greenhouse warming
Cai, W., Wang, G., Dewitte, B., Wu, L., Santoso, A., Takahashi, K., Yang, Y., Carréric, A., & McPhaden, M. J. (2018) · Nature · doi:10.1038/s41586-018-0776-9 · Cited by 642
Self-citationBootstrap Methods for Developing Predictive Models
Austin, P. C., & Tu, J. V. (2004) · The American Statistician · doi:10.1198/0003130043277 · Cited by 622
Robust twenty-first-century projections of El Niño and related precipitation variability
Power, S., Delage, F., Chung, C., Kociuba, G., & Keay, K. (2013) · Nature · doi:10.1038/nature12580 · Cited by 448
Interdecadal modulation of El Niño amplitude during the past millennium
Li, J., Xie, S.-P., Cook, E. R., Huang, G., D'Arrigo, R., Liu, F., Ma, J., & Zheng, X.-T. (2011) · Nature Climate Change · doi:10.1038/nclimate1086 · Cited by 349
Analysis of the non-linearity in the pattern and time evolution of El Niño southern oscillation
Dommenget, D., Bayr, T., & Frauen, C. (2013) · Climate Dynamics · doi:10.1007/s00382-012-1475-0 · Cited by 252
Evaluating Climate Models with the CLIVAR 2020 ENSO Metrics Package
Planton, Y. Y., Guilyardi, E., Wittenberg, A. T., Lee, J., Gleckler, P. J., Bayr, T., McGregor, S., McPhaden, M. J., Power, S., Roehrig, R., et al. (2021) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-19-0337.1 · Cited by 246
Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization
Wang, G., Cai, W., Gan, B., Wu, L., Santoso, A., Lin, X., Chen, Z., & McPhaden, M. J. (2017) · Nature Climate Change · doi:10.1038/nclimate3351 · Cited by 227
Self-citationEyring, V., Bony, S., Meehl, G. A., et al. (2015) · doi:10.5194/gmdd-8-10539-2015 · Cited by 195
ENSO Change in Climate Projections: Forced Response or Internal Variability?
Maher, N., Matei, D., Milinski, S., & Marotzke, J. (2018) · Geophysical Research Letters · doi:10.1029/2018gl079764 · Cited by 170
How 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
Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models
Beobide-Arsuaga, G., Bayr, T., Reintges, A., & Latif, M. (2021) · Climate Dynamics · doi:10.1007/s00382-021-05673-4 · Cited by 149
The Interdecadal Shift of ENSO Properties in 1999/2000: A Review
Hu, Z.-Z., Kumar, A., Huang, B., Zhu, J., L’Heureux, M., McPhaden, M. J., & Yu, J.-Y. (2020) · Journal of Climate · doi:10.1175/jcli-d-19-0316.1 · Cited by 139
Future high-resolution El Niño/Southern Oscillation dynamics
Wengel, C., Lee, S.-S., Stuecker, M. F., Timmermann, A., Chu, J.-E., & Schloesser, F. (2021) · Nature Climate Change · doi:10.1038/s41558-021-01132-4 · Cited by 117
Butterfly effect and a self-modulating El Niño response to global warming
Cai, W., Ng, B., Geng, T., Wu, L., Santoso, A., & McPhaden, M. J. (2020) · Nature · doi:10.1038/s41586-020-2641-x · Cited by 111
Self-citationZheng, X.-T., Hui, C., & Yeh, S.-W. (2018) · Climate Dynamics · doi:10.1007/s00382-017-3859-7 · Cited by 102
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
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
Self-citationGreenhouse 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
Self-citationAddendum: Butterfly effect and a self-modulating El Niño response to global warming
Cai, W., Ng, B., Geng, T., et al. (2021) · Nature · doi:10.1038/s41586-021-03261-4 · Cited by 2
Self-citationA New Way of Evaluating ENSO in Climate Models: The CLIVAR ENSO Metrics Package
Planton, Y. Y., Guilyardi, É., Wittenberg, A. T., et al. (2021) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-19-0337.a · Cited by 2
Research works printed but not linked: 1
- IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, in the press).
Cited by
Sorted by citations
Increased occurrences of consecutive La Niña events under global warming
Geng, T., Jia, F., Cai, W., Wu, L., Gan, B., Jing, Z., Li, S., & McPhaden, M. J. (2023) · Nature · doi:10.1038/s41586-023-06236-9 · Cited by 289
Self-citationAnthropogenic impacts on twentieth-century ENSO variability changes
Cai, W., Ng, B., Geng, T., Jia, F., Wu, L., Wang, G., Liu, Y., Gan, B., Yang, K., Santoso, A., et al. (2023) · Nature Reviews Earth & Environment · doi:10.1038/s43017-023-00427-8 · Cited by 176
Self-citationPersistent effect of El Niño on global economic growth
Callahan, C. W., & Mankin, J. (2023) · Science · doi:10.1126/science.adf2983 · Cited by 125
Southern Ocean warming and its climatic impacts
Cai, W., Gao, L., Luo, Y., Li, X., Zheng, X., Zhang, X., Cheng, X., Jia, F., Purich, A., Santoso, A., et al. (2023) · 中国科学通报：英文版 · doi:10.1016/j.scib.2023.03.049 · Cited by 90
Self-citationProjected ENSO Teleconnection Changes in CMIP6
McGregor, S., Cassou, C., Kosaka, Y., & Phillips, A. S. (2022) · Geophysical Research Letters · doi:10.1029/2021gl097511 · Cited by 99
“, 2021), but significant when the entire 21st century is contrasted against the 20th century (Cai et al., 2022).”
Background
Metadata
- Authors
- Cai, W., Ng, B., Wang, G., Santoso, A., Wu, L., & Yang, K.
- Venue
- Nature Climate Change
- Published
- 2022-01-31
- Volume
- 12
- Issue
- 3
- Pages
- 228-231
- ISSN
- 1758-678X (ISSN-L)
- 1758-6798
- OpenAlex
- W4210819470
- Cited by
- 263
- References
- 24
- Citations by year
- 2026: 40 · 2025: 61 · 2024: 77 · 2023: 60 · 2022: 25
- FWCI
- 21.85
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Climate Change (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Australian Government
- Commonwealth Scientific and Industrial Research Organisation
- Chinese Academy of Sciences (XDB40030000, 2019YFC1509100)
- Centre for Southern Hemisphere Oceans Research
- Joint Research Centre
- National Key Research and Development Program of China (2019YFC1509100)
- 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 › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
- Keywords
- ENSO, sea surface temperature variability, IPCC climate scenarios, climate change projections
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-16, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-16 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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