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
AI snapshot
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.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- 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.
- 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- 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. 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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- 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.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- 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.
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.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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.
- 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.
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.
- 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.
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
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
Items 101–200 of 263
Shuping, Z., Ying, J., & Collins, M. D. (2023) · Journal of Climate · doi:10.1175/jcli-d-22-0554.1 · Cited by 8
Strain variation and anomalous climate synergistically influence cholera pandemics
Rodó, X., Bouma, M. J., Rodríguez-Arias, M. À., Roy, M., Yebra, P. D., Petrova, D., García‐Díez, M., & Pascual, M. (2024) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0012275 · Cited by 7
ENSO amplifies global vegetation resilience variability in a changing climate
Zhou, W. H., Li, C., Zhang, H., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-66987-z · Cited by 7
Tsuchida, K., Mochizuki, T., Kawamura, R., & Kawano, T. (2023) · Geophysical Research Letters · doi:10.1029/2023gl106127 · Cited by 6
“In addition, Cai et al. (2022) suggested that SST variability associated with ENSO increases in the second half of the 21st century compared to the 20th century, which implies that the internally generated radiative feedbacks (negative feedbacks) will be strengthened under a warming climate.”
BackgroundTriple dip La-Nina, unorthodox circulation and unusual spin in air quality of India
Beig, G., Anand, V., Korhale, N., Sobhana, S. B., Harshitha, K. M., & Kripalani, R. H. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.170963 · Cited by 7
Vaideanu, P. C., Ionita-Scholz, M., Voiculescu, M., et al. (2023) · Atmosphere · doi:10.3390/atmos14030456 · Cited by 7
Individual variability in diving behavior of the Black-vented Shearwater in an ever-changing habitat
Soldatini, C., Rosas‐Hernández, M. P., Albores-Barajas, Y. V., Catoni, C., Ramos, A., Dell’Omo, G., Rattenborg, N. C., & Chimienti, M. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.163286 · Cited by 8
Xiao, L., Yang, P., Wang, Y., et al. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3471826 · Cited by 6
“For instance, anomalies in sea surface temperature (SST) are closely linked to El Niño and La Niña phenomena, which are associated with increased frequency and intensity of extreme weather events worldwide [1], [2], [3].”
BackgroundUnderstanding ENSO Weakening in Warmer Climates
Tuckman, P. (2025) · Geophysical Research Letters · doi:10.1029/2024gl113124 · Cited by 8
Gao, Y., Han, Z., Li, Z., & Deng, X. (2025) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2025.108543 · Cited by 7
Enduring impacts of El Niño on life expectancy in past and future climates
Xu, Y., Zhu, W., Samanta, D., & Horton, B. P. (2026) · Nature Climate Change · doi:10.1038/s41558-025-02534-4 · Cited by 7
“To address this, previous studies have proposed a method to filter the physically realistic models by calcu lating the quadratic coefficient ( α parameter) in the relationship between PC1 and PC2 from the EOF analysis used to calculate the E - and C -indices 42,65 .”
InfluentialIrfan, M., Safrina, S., Koriyanti, E., et al. (2023) · Journal of Groundwater Science and Engineering · doi:10.26599/jgse.2023.9280008 · Cited by 6
Mondal, S., Ray, A., Boas, M., Navus, S. G., Lee, M.-A., Dey, S., & Barman, K. K. (2024) · PLoS ONE · doi:10.1371/journal.pone.0307644 · Cited by 6
Mahendra, N., Chilukoti, N., Chowdary, J. S., et al. (2024) · Global and Planetary Change · doi:10.1016/j.gloplacha.2024.104601 · Cited by 6
Sunil, A., Deepthi, B., Rashid, M., Sreedhar, R., Ganjir, G., & Adarsh, S. (2025) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-025-03049-2 · Cited by 8
“Sea surface temperature is an important climatic indicator that governs many natural processes, having practical significance in almost all climate related fields ( Deser et al. 2010; Hartmann 2015; Chin et al. 2017; Xiao et al. 2019; Cai et al. 2022).”
Rashid, H. (2022) · Frontiers in Climate · doi:10.3389/fclim.2022.954449 · Cited by 6
“However, the latest, CMIP6 models show a somewhat stronger ensemblemean increase in ENSO variability than the CMIP5 models do (Fredriksen et al., 2020; Grose et al., 2020; Cai et al., 2022).”
BackgroundAccounting for risk-catch-cost trade-offs in a harvest strategy for a small, highly variable fishery
Plagányi, É. E., Blamey, L. K., Deng, R. A., et al. (2022) · Fisheries Research · doi:10.1016/j.fishres.2022.106518 · Cited by 6
Jupin, J. L. J., García‐López, A. A., Briceño‐Zuluaga, F. J., et al. (2023) · International Journal of Climatology · doi:10.1002/joc.8318 · Cited by 6
“The possible further increases in the frequency and intensity of extreme El Niño events related to climate change (Cai et al., 2022; Wang et al., 2019) may lead to future drought conditions in the URB and associated socioeconomic consequences, although further research and consideration of various…”
BackgroundEarly emergence and determinants of human-induced Walker circulation weakening
Wu, M., Li, C., Collins, M. D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53509-6 · Cited by 5
“For example, the amplitude of ENSO is proposed to increase by the end of the century 57,58 , potentially exacerbating the weakening of the Walker circulation and hastening the emergence time of the weakening signal.”
Large Ensemble Simulations of Climate Models for Climate Change Research: A Review
Lin, P., Yang, L., Zhao, B., et al. (2025) · Advances in Atmospheric Sciences · doi:10.1007/s00376-024-4012-2 · Cited by 5
“…can have a substantial effect on the modes of internal variability via local processes (Yeh et al., 2009; Booth et al., 2012; Fang et al., 2014; Cai et al., 2018, 2022; Freund et al., 2019; Li et al., 2020a; Qin et al., 2020a; Murphy et al., 2021; Crespo et al., 2022; He et al., 2023) or…”
Laira, M. D., Graciano, D. S., de Andrade, S. A. L., Zambrosi, F. C. B., & Ribeiro, R. V. (2025) · Plant Science · doi:10.1016/j.plantsci.2025.112611 · Cited by 5
Quantifying salinity and drought drive forces on paddy field loss in the Mekong Delta, Vietnam
Wang, Q., Yang, K., Zhu, Y., et al. (2025) · Communications Earth & Environment · doi:10.1038/s43247-025-02490-z · Cited by 5
“Additionally, global climate change is moving towards drier dry seasons and wetter rainy seasons 11 .”
Self-citationAdvanced Peak Phase of ENSO under Global Warming
Zheng, X., Hui, C., Han, Z., & Wu, Y. (2024) · Journal of Climate · doi:10.1175/jcli-d-24-0002.1 · Cited by 7
Hong, J., Kim, D., Lopez, H., Lee, S., Mercer, A. E., & Johnson, N. C. (2025) · npj Climate and Atmospheric Science · doi:10.1038/s41612-025-00972-7 · Cited by 5
“According to SPEAR-LENS, ENSO variance is projected to continue increasing until the mid-21st century, consistent with previous studies 12,27,28,58 – 60 .”
Future climate response to observed strong El Niño analogues
Castro, P. T., Ruprich‐Robert, Y., & Maycock, A. C. (2025) · npj Climate and Atmospheric Science · doi:10.1038/s41612-025-01003-1 · Cited by 7
“While several modelling studies have examined ENSO tele-connections in a future climate, they have generally used freely-evolving coupled climate models and therefore do not permit a separation of mechanisms 1 and 2 29,36 – 39 .”
İklim değişikliğinin ormanlar üzerindeki etkisi: İklim akılcı ormancılık bakış açısı
Sargıncı, M., & BEYAZYÜZ, F. (2022) · Anadolu Orman Araştırmaları Dergisi · doi:10.53516/ajfr.1139640 · Cited by 6
Júnior, J. P. V. A., Mota, É. M. T., Campos, C. C., et al. (2023) · Marine Pollution Bulletin · doi:10.1016/j.marpolbul.2022.114503 · Cited by 5
Tropical Pacific Warming Patterns Influence Future Hydroclimate Shifts and Extremes in the Americas
Heede, U. K., Lenssen, N., Karnauskas, K. B., & Deser, C. (2025) · Earth s Future · doi:10.1029/2025ef006014 · Cited by 4
Kong, J., Wu, L., Cao, J., et al. (2024) · Agriculture · doi:10.3390/agriculture14040619 · Cited by 4
Self-citationAsymmetric ENSO teleconnections in a symmetric CO 2 concentration pathway
An, S., Shin, S.-H., Liu, C., et al. (2024) · Environmental Research Letters · doi:10.1088/1748-9326/ad7b5c · Cited by 4
“Due to the critical need to understand the impacts of climate change and explore adaptation strategies, numerous studies have been conducted on the future ENSO projections (Collins et al 2010, Kim et al 2014, Cai et al 2022, Olson et al 2022).”
Abrupt shift of El Niño periodicity under CO 2 mitigation
Iwakiri, T., Kug, J., Jin, F., Zhao, S., An, S., Kim, G.-I., & Park, D. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2426048122 · Cited by 4
“In terms of amplitude, ENSO is projected to intensify under global warming across state - of - the - art climate models ( 27 , 28 ).”
Biomass Burning Emissions of Black Carbon over the Maritime Continent and ENSO Variability
Xie, B., Yang, Y., Wang, H., et al. (2023) · Journal of Climate · doi:10.1175/jcli-d-22-0553.1 · Cited by 4
Processes that Contribute to Future South Asian Monsoon Differences in E3SMv2 and CESM2
Meehl, G. A., Shields, C. A., Arblaster, J. M., et al. (2024) · Geophysical Research Letters · doi:10.1029/2024gl109056 · Cited by 4
Liang, Y., & Fedorov, A. V. (2024) · Journal of Climate · doi:10.1175/jcli-d-23-0681.1 · Cited by 4
Hemisphere-Dependent Impacts of ENSO and Atmospheric Eddies on Hadley Circulation
Hasan, M., Larson, S. M., McMonigal, K., et al. (2024) · Journal of Climate · doi:10.1175/jcli-d-24-0112.1 · Cited by 4
Climate, crops, and postharvest conflict
Ubilava, D. (2023) · American Journal of Agricultural Economics · doi:10.1111/ajae.12504 · Cited by 3
Carvalho, B. C., Corrêa, A. L. T., da Silva, A. B., & Ciotti, Á. M. (2024) · Regional Studies in Marine Science · doi:10.1016/j.rsma.2024.103991 · Cited by 4
Ren, X., & Liu, W. (2025) · Communications Earth & Environment · doi:10.1038/s43247-025-01996-w · Cited by 5
“This uncertainty stems not only from a balance of amplifying and damping feedbacks that govern ENSO and are in fl uenced by climate change 10 , but also from the uncertainty of future anthropogenicaerosolandgreenhousegas(GHG)emissions 13 .”
Lluch-Cota, S. E., Sicard, M. T., Calderón-Liévanos, S., & Echavarria, H. V. (2023) · Estuarine Coastal and Shelf Science · doi:10.1016/j.ecss.2023.108252 · Cited by 4
Coquereau, A., Sévellec, F., Huck, T., Hirschi, J., & Hochet, A. (2024) · Journal of Climate · doi:10.1175/jcli-d-23-0606.1 · Cited by 3
Auckland, C., Abrahamsen, E. P., Meredith, M. P., et al. (2024) · Journal of Geophysical Research Oceans · doi:10.1029/2024jc021089 · Cited by 3
A half-century drying in Gobi Oasis, possible role of ENSO and warming/moistening of Northwest China
Li, Q., Wu, Y., Duan, X., et al. (2025) · Global and Planetary Change · doi:10.1016/j.gloplacha.2025.104769 · Cited by 3
Yang, Y., Wu, L. X., Cai, W., Cheng, X., Mei, X., Jia, F., Li, S., Geng, T., Chen, Y., & Wang, H. (2025) · Geophysical Research Letters · doi:10.1029/2025gl114761 · Cited by 4
Self-citationFuels Mediate the Influence of Climate Teleconnections on Wildfires in Dryland Ecosystems
Qu, Y., Veraverbeke, S., Miralles, D. G., Fan, J., Vereecken, H., & Montzka, C. (2025) · Global Change Biology · doi:10.1111/gcb.70406 · Cited by 3
Robust circulation changes in the tropics under a warming climate: a topical review
Thomas, T. M., & Bala, G. (2025) · Frontiers in Climate · doi:10.3389/fclim.2025.1713513 · Cited by 4
Influence of the boreal spring arctic oscillation on the midsummer maritime continent precipitation
Tao, Y., Zeng, G., Chen, C., et al. (2025) · Atmospheric Research · doi:10.1016/j.atmosres.2025.108730 · Cited by 3
Increased interannual variability of Sahel rainfall under greenhouse warming
Yang, K., Wang, G., Cai, W., Mohíno, E., Rodríguez‐Fonseca, B., Ng, B., & Yeh, S. (2025) · Nature Communications · doi:10.1038/s41467-025-67885-0 · Cited by 7
“However, the increase is much larger and with stronger inter-model consensus in CMIP6 models than in the CMIP5 models 51 (Supplemen-taryFig.12),whichmightbeattributedtoastrongerprojectedincrease in ENSO variability 52 and a more substantial wetting of the Sahel mean state in CMIP6 models 53 .”
Self-citationCompound climate events threaten tropical semi-enclosed marine ecosystems
Plagányi, É. E., Blamey, L. K., Kenyon, R., Brodie, S. J., Deng, R. A., Parker, D. S., Pillans, R. D., Murphy, N., Miller, M., Desbiens, A. A., et al. (2026) · Science · doi:10.1126/science.adv0367 · Cited by 4
袁, 星., 王, 钰., 周, 诗., 李, 华., & 李, 晨. (2024) · SCIENTIA SINICA Terrae · doi:10.1360/sste-2024-0007 · Cited by 3
Nipah Virus: Through a Pandemic Lens
Salvi, P., Martins, S., Das, S., Bhat, M., & Pathare, A. (2024) · Springer eBooks · doi:10.1007/978-981-97-4480-0_1 · Cited by 2
Xu, H., & Bocchiola, D. (2025) · Theoretical and Applied Climatology · doi:10.1007/s00704-024-05331-9 · Cited by 3
“Recent intensification of climate change has significant implications for sustainability, and disaster risk reduction, at the global, national, and regional levels (Bao et al. 2017; Cai et al. 2022; Padrón et al. 2020; Vicedo-Cabrera et al. 2021; Zhao et al. 2020).”
O’Grady, J., Stephenson, A. G., & McInnes, K. L. (2025) · Coastal Engineering · doi:10.1016/j.coastaleng.2025.104725 · Cited by 3
Asymmetrical Ocean Carbon Responses in the Tropical Pacific Ocean to La Niña and El Niño
Sun, C.-F., Liao, E.-H., & Zhu, X.-M. (2025) · Geophysical Research Letters · doi:10.1029/2024gl112039 · Cited by 1
Mastropierro, M., Peano, D., & Zanchettin, D. (2025) · Biogeosciences · doi:10.5194/bg-22-5231-2025 · Cited by 4
Olson, R., Kim, S., Fan, Y., & An, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-26513-3 · Cited by 3
Shackleton, D., Memon, F. A., Chen, A., Dutta, S., Kanungo, S., & Deb, A. (2023) · Gut Pathogens · doi:10.1186/s13099-023-00565-w · Cited by 3
“Further, our results do not suggest that the projected intensification of ENSO [55] and changes to IOD [56] resulting from climate change will significantly influence cholera burden in Kolkata.”
ResultElsbury, D., Butler, A. H., Albers, J. R., Breeden, M. L., & Langford, A. O. (2023) · Atmospheric chemistry and physics · doi:10.5194/acp-23-5101-2023 · Cited by 4
Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble
Milovac, J., Iturbide, M., Fernández, J., Gutiérrez, J. M., Díez-Sierra, J., & Jones, R. (2024) · Climate Dynamics · doi:10.1007/s00382-024-07218-x · Cited by 4
“…phenomenon, play a significant role in the SST variability, leading to substantial increases during specific years and seasons (Bulgin et al. 2020; Cai et al. 2022), global SST changes as compared to pre-industrial (PI) times is primarily driven by climate change (Froelicher et al. 2018;…”
Zhang, J., Li, J., Zhang, K., et al. (2024) · Fishes · doi:10.3390/fishes9120488 · Cited by 3
Reversed tropical-Arctic teleconnection under climate change
Tang, W., Sun, B., Keenlyside, N. S., Li, F., He, S., Li, H., Zhou, B., & Wang, H. (2025) · npj Climate and Atmospheric Science · doi:10.1038/s41612-025-01243-1 · Cited by 2
“With ongoing global warming, the frequency of extremeElNiñoeventsmayincrease 5 ,andtheinterannualvariabilityinSST related to ENSO could be signi fi cantly ampli fi ed 4,7,8 , thereby substantially impacting the global climate system.”
Wong, M. L., & Wang, X. (2026) · Climate of the past · doi:10.5194/cp-22-1-2026 · Cited by 2
“Current projections of future changes in ENSO variability and the east–west SST gradient over the tropical Pacific remain uncertain due to conflicting projections from different climate models (Cai et al., 2022; Kohyama et al., 2017; Poli et al., 2016).”
Wu, S., Lorenzo, E. D., Zhao, Y., et al. (2026) · npj Climate and Atmospheric Science · doi:10.1038/s41612-025-01315-2 · Cited by 2
Multi-year La Niña–El Niño transition influenced Earth’s extreme energy uptake in 2022–2023
Tsuchida, K., Kosaka, Y., & Minobe, S. (2026) · Nature Geoscience · doi:10.1038/s41561-026-01921-6 · Cited by 2
ENSO shapes salinity regimes and fish migration in the China Seas
Wang, Z., Huang, H., Wang, G., et al. (2026) · Nature Climate Change · doi:10.1038/s41558-026-02559-3 · Cited by 2
Self-citationNandini‐Weiss, S. D., Ojha, S., Köhl, A., et al. (2023) · Climate Dynamics · doi:10.1007/s00382-023-06982-6 · Cited by 2
Laurie, N. D., Henderson, A. C. G., Rodríguez, R., et al. (2024) · Annals of the American Association of Geographers · doi:10.1080/24694452.2024.2377222 · Cited by 2
“The ENSO dominates modern climate variability, and to understand its response to elevated greenhouse gases considerable research has gone into understanding its modern dynamics and history (e.g., Moy et al. 2002; Cobb et al. 2013; Cai et al. 2022).”
Larson, S. M., & McMonigal, K. (2025) · Geophysical Research Letters · doi:10.1029/2024gl111878 · Cited by 2
Possible coherency of synchronous warming of tropical oceans and the QBO amplitude variation
Zhu, X., & Rao, J. (2025) · Atmospheric Research · doi:10.1016/j.atmosres.2025.108241 · Cited by 2
King’uza, P. H., Zhou, B., & Limbu, P. T. S. (2025) · International Journal of Climatology · doi:10.1002/joc.70038 · Cited by 3
Drivers of past and future changes in weather, climate and ocean extremes
Hay, J. E., & Williams, P. D. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-85541-9.00012-2 · Cited by 2
Dunkl, I., Bastos, A., & Ilyina, T. (2025) · Earth System Dynamics · doi:10.5194/esd-16-151-2025 · Cited by 2
Solaimani, K., Ahmadi, S. B., & Shokrian, F. (2023) · Research Square · doi:10.21203/rs.3.rs-2419746/v1 · Cited by 2
Tailored forecasts can predict extreme climate informing proactive interventions in East AfricaPreprint
Funk, C. C., Harrison, L., Segele, Z., Rosenstock, T. S., Steward, P., anderson, L., de Perez, E. C., Maxwell, D., Endris, H. S., Koech, E., et al. (2023) · doi:10.22541/essoar.167591094.46381358/v1 · Cited by 2
Wan, Y., Xu, F., Chang, S., et al. (2024) · Applied Sciences · doi:10.3390/app14031090 · Cited by 1
Wang, Q., Zhang, Z., & Crabbe, M. J. C. (2024) · Journal of Marine Science and Engineering · doi:10.3390/jmse12081439 · Cited by 1
Gallerani, E. M., Williams, P., Cavanaugh, K. C., & Gillespie, T. W. (2025) · Journal of Biogeography · doi:10.1111/jbi.15121 · Cited by 1
Ramesh, K., Mitchell, N. J., Hindley, N. P., & Moffat‐Griffin, T. (2025) · Journal of Geophysical Research Atmospheres · doi:10.1029/2024jd043134 · Cited by 1
“The global warming due to rising levels of CO 2 could lead to more frequent and intense El Niño events (e.g., Cai et al., 2022), and thus influence the tropical deep convective systems and tidal forcings, subsequently the semidiurnal tidal amplitudes in the MLT region.”
Shekhar, M., Pandey, P., Singh, S., et al. (2025) · Dynamics of Atmospheres and Oceans · doi:10.1016/j.dynatmoce.2025.101558 · Cited by 1
A nonlinear perspective in understanding projected El Niño-Southern Oscillation in a warming climate
Cai, W., Geng, T., Wu, S., et al. (2025) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/csb-2025-0258 · Cited by 1
Self-citationInterannual and Intraseasonal Variability in the Southern Hemisphere
Chung, C. T. Y., Boschat, G., Cowan, T., et al. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009352680.013 · Cited by 1
Changing El Niño-Southern Oscillation (ENSO) and impacts under greenhouse warming
Cai, W., Geng, T., Jia, F., Wu, S., & Wang, H. (2025) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2024-1104 · Cited by 2
Self-citationUpper-ocean stratification changes control ENSO amplitude shift under sustained global warming
Zhang, R., Chen, M., Gao, C., Zhou, L., Zhi, H., Liu, S., Tao, L., Minmin, W. U., Gao, J., & Wang, H. (2026) · Nature Communications · doi:10.1038/s41467-026-69931-x · Cited by 1
Jiang, Y., Li, X., Zhou, X., Fowler, H. J., & Yang, S. (2026) · Global and Planetary Change · doi:10.1016/j.gloplacha.2026.105397 · Cited by 1
Xing, Q., Gao, Z., Ito, S.-I., Yu, H., Yu, W., & Chen, X. (2026) · Nature Communications · doi:10.1038/s41467-026-70986-z · Cited by 3
“…parallels the rising frequency, amplitude, and spatial extent of large-scale climate phenomena such asENSO and marine heatwaves under anthropogenic warming 6,9 , with cascading impacts on precipitation, heat distribution, atmospheric circulation, sea-ice extent, and extreme events 4,14,17,19 – 22 .”
Liu, X., Zhang, F., Jim, C. Y., Li, J., Ahmed, Z., He, X., Ma, X., & Tan, M. L. (2026) · Environmental Research · doi:10.1016/j.envres.2026.124641 · Cited by 1
Twentieth-century ENSO changes affected by anthropogenic warming
Geng, T., Jia, F., & Cai, W. (2023) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2023-0541 · Cited by 1
Self-citationNakaegawa, T., & Mizuta, R. (2023) · International Journal of Climatology · doi:10.1002/joc.8261 · Cited by 1
“However, Cai et al. (2022) showed that variability will increase.”
Chambon, J., Börger, L., Weimerskirch, H., & Hennicke, J. C. (2024) · Marine Ecology Progress Series · doi:10.3354/meps14660 · Cited by 1
Projected ENSO influences on global crop yields using a climate-crop model ensemble
Harrington-Tsunogai, J., Hayashi, M., Shiogama, H., Takimoto, T., Kim, W., & Iizumi, T. (2025) · Climate Research · doi:10.3354/cr01763 · Cited by 1
Shepherd, T. J., Coburn, J. J., Barthelmie, R. J., & Pryor, S. C. (2022) · Climate · doi:10.3390/cli10080117 · Cited by 1
Paleoclimate constrains future El Niño/Southern Oscillation increasePreprint
Pontes, G. M., Dias, P. L. D. S., & Menviel, L. (2022) · Research Square · doi:10.21203/rs.3.rs-2062789/v1 · Cited by 1
Maher, N., Wills, R. C. J., DiNezio, P., et al. (2022) · Earth System Dynamics · doi:10.5194/esd-2022-26-cc1 · Cited by 1
Kamaraj, M., & Rangarajan, S. (2023) · Research Square · doi:10.21203/rs.3.rs-3095621/v1 · Cited by 1
The influence of global warming on ENSO dynamicsPreprint
Zhang, M., Yan, L., Nayak, A., Xiong, L., & Lall, U. (2024) · Research Square · doi:10.21203/rs.3.rs-4438731/v1 · Cited by 1
New study helps solve a 30-year-old puzzle: how is climate change affecting El Niño and La Niña?
Cai, W., & Santoso, A. (2023) · doi:10.64628/aa.xnntst5h9 · Cited by 1
Self-citationEnhanced ENSO variability moderates future Southern Ocean warming
(2022) · Nature Climate Change · doi:10.1038/s41558-022-01406-5
Elsbury, D., Butler, A. H., Albers, J. R., et al. (2023) · Atmospheric chemistry and physics · doi:10.5194/acp-2022-700-rc2
Future Southern Ocean and Antarctic shelf ocean warming affected by projected ENSO variability
Jia, F., Cai, W., & Wang, G. (2023) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2023-0251
Self-citationSECAS EXTREMAS NO NORDESTE BRASIL: UMA REVISÃO SISTEMÁTICA DE LITERATURA
Silva, M. R. V. D., Parra, L. M. P., Aires, M., et al. (2023) · Revista Contemporânea · doi:10.56083/rcv3n4-018
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
