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# Intensification of El Niño-induced atmospheric anomalies under greenhouse warming

## Abstract

The El Niño/Southern Oscillation (ENSO) has a profound influence on global climate and ecosystems. Determining how the ENSO responds to greenhouse warming is a crucial issue in climate science. Despite recent progress in understanding, the responses of important ENSO characteristics, such as air temperature and atmospheric circulation, are still unknown. Here, we use a suite of global climate model projections to show that greenhouse warming drives a robust intensification of ENSO-driven variability in boreal winter tropical upper tropospheric temperature and geopotential height, tropical humidity, subtropical jets and tropical Pacific rainfall. These robust changes are primarily due to the Clausius–Clapeyron relationship, whereby saturation vapour pressure increases nearly exponentially with increasing temperature. Therefore, the vapour response to temperature variability is larger under a warmer climate. As a result, under global warming, even if the ENSO’s sea surface temperature remains unchanged, the response of tropical lower tropospheric humidity to the ENSO amplifies, which in turn results in major reorganization of atmospheric temperature, circulation and rainfall. These findings provide a novel theoretical constraint for ENSO changes and reduce uncertainty in the ENSO response to greenhouse warming.

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## Data availability

The CMIP6 data are available at https://pcmdi.llnl.gov/CMIP6/. The CMIP5 data are available at https://esgf-node.llnl.gov/search/cmip5/. The version 2 National Centers for Environmental Prediction/Department of Energy reanalysis and Global Precipitation Climatology Project precipitation data are from http://www.esrl.noaa.gov/psd/data/gridded/. Hadley Center SST data were provided by the Met Office Hadley Center (https://www.metoffice.gov.uk/hadobs/hadisst/).

## Code availability

The code associated with this paper is available on request from K.H.

## References

1. 1.

Jin, F.-F. Tropical ocean–atmosphere interaction, the Pacific Cold Tongue, and the El Niño–Southern Oscillation. Science 274, 76–78 (1996).

2. 2.

Wallace, J. M. et al. The structure and evolution of ENSO-related climate variability in the tropical Pacific: lessons from TOGA. J. Geophys. Res. 103, 14241–14259 (1998).

3. 3.

Neelin, J. D. et al. ENSO theory. J. Geophys. Res. 103, 14261–14290 (1998).

4. 4.

McPhaden, M. J., Zebiak, S. E. & Glantz, M. H. ENSO as an integrating concept in Earth science. Science 314, 1740–1745 (2006).

5. 5.

Deser, C., Alexander, M. A., Xie, S. P. & Phillips, A. S. Sea surface temperature variability: patterns and mechanisms. Ann. Rev. Mar. Sci. 2, 115–143 (2010).

6. 6.

Horel, J. D. & Wallace, J. M. Planetary-scale atmospheric phenomena associated with the Southern Oscillation. Mon. Weather Rev. 109, 813–829 (1981).

7. 7.

Trenberth, K. E. et al. Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res. 103, 14291–14324 (1998).

8. 8.

Gill, A. E. Some simple solutions for heat-induced tropical circulation. Q. J. R. Meteorol. Soc. 106, 447–462 (1980).

9. 9.

Wang, B., Wu, R. G. & Fu, X. H. Pacific–East Asian teleconnection: how does ENSO affect East Asian climate? J. Clim. 13, 1517–1536 (2000).

10. 10.

Chiang, J. C. H. & Sobel, A. H. Tropical tropospheric temperature variations caused by ENSO and their influence on the remote tropical climate. J. Clim. 15, 2616–2631 (2002).

11. 11.

Su, H., Neelin, J. D. & Meyerson, J. E. Sensitivity of tropical tropospheric temperature to sea surface temperature forcing. J. Clim. 16, 1283–1301 (2003).

12. 12.

Seager, R., Harnik, N. I., Kushnir, Y., Robinson, W. A. & Miller, J. Mechanisms of hemispherically symmetric climate variability. J. Clim. 16, 2960–2978 (2003).

13. 13.

Neelin, J. D. & Su, H. Moist teleconnection mechanisms for the tropical South American and Atlantic sector. J. Clim. 18, 3928–3950 (2005).

14. 14.

Xie, S.-P. et al. Indian ocean capacitor effect on Indo-Western Pacific climate during the summer following El Niño. J. Clim. 22, 730–747 (2009).

15. 15.

Adames, Á. F. & Wallace, J. M. On the tropical atmospheric signature of El Niño. J. Atmos. Sci. 74, 1923–1939 (2017).

16. 16.

Collins, M. et al. The impact of global warming on the tropical Pacific Ocean and El Niño. Nat. Geosci. 3, 391–397 (2010).

17. 17.

Cai, W. J. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).

18. 18.

Cai, W. J. et al. ENSO and greenhouse warming. Nat. Clim. Change 5, 849–859 (2015).

19. 19.

Cai, W. J. et al. Increased variability of eastern Pacific El Niño under greenhouse warming. Nature 564, 201–206 (2018).

20. 20.

Yeh, S. W. et al. El Niño in a changing climate. Nature 461, 511–514 (2009).

21. 21.

Yeh, S. W. et al. ENSO atmospheric teleconnections and their response to greenhouse gas forcing. Rev. Geophys. 56, 185–206 (2018).

22. 22.

Fasullo, J. T., Otto-Bliesner, B. L. & Stevenson, S. ENSO’s changing influence on temperature, precipitation, and wildfire in a warming climate. Geophys. Res. Lett. 45, 9216–9225 (2018).

23. 23.

Perry, S. J., McGregor, S., Sen Gupta, A., England, M. H. & Maher, N. Projected late 21st century changes to the regional impacts of the El Niño–Southern Oscillation. Clim. Dynam. 54, 395–412 (2020).

24. 24.

Wang, B. et al. Historical change of El Niño properties sheds light on future changes of extreme El Niño. Proc. Natl Acad. Sci. USA 116, 22512–22517 (2019).

25. 25.

Watanabe, M. et al. Uncertainty in the ENSO amplitude change from the past to the future. Geophys. Res. Lett. 39, L20703 (2012).

26. 26.

Kim, S. T. et al. Response of El Niño sea surface temperature variability to greenhouse warming. Nat. Clim. Change 4, 786–790 (2014).

27. 27.

Power, S., 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).

28. 28.

Chung, C. T. Y., Power, S. B., Arblaster, J. M., Rashid, H. A. & Roff, G. L. Nonlinear precipitation response to El Niño and global warming in the Indo-Pacific. Clim. Dynam. 42, 1837–1856 (2014).

29. 29.

Huang, P. & Xie, S. P. Mechanisms of change in ENSO-induced tropical Pacific rainfall variability in a warming climate. Nat. Geosci. 8, 922–927 (2015).

30. 30.

Meehl, G. A. & Teng, H. Multi-model changes in El Niño teleconnections over North America in a future warmer climate. Clim. Dynam. 29, 779–790 (2007).

31. 31.

Kug, J.-S., An, S.-I., Ham, Y.-G. & Kang, I.-S. Changes in El Niño and La Niña teleconnections over North Pacific–America in the global warming simulations. Theor. Appl. Climatol. 100, 275–282 (2010).

32. 32.

Zhou, Z., Xie, S., Zheng, X., Liu, Q. & Wang, H. Global warming-induced changes in El Niño teleconnections over the North Pacific and North America. J. Clim. 27, 9050–9064 (2014).

33. 33.

Power, S. B. & Delage, F. P. D. El Niño–Southern Oscillation and associated climatic conditions around the world during the latter half of the twenty-first century. J. Clim. 31, 6189–6207 (2018).

34. 34.

McPhaden, M. J., Lee, T. & McClurg, D. El Niño and its relationship to changing background conditions in the tropical Pacific Ocean. Geophys. Res. Lett. 38, L15709 (2011).

35. 35.

Ying, J., Huang, P., Lian, T. & Chen, D. K. Intermodel uncertainty in the change of ENSO’s amplitude under global warming: role of the response of atmospheric circulation to SST anomalies. J. Clim. 32, 369–383 (2019).

36. 36.

Frankcombe, L. M., England, M. H., Mann, M. E. & Steinman, B. A. Separating internal variability from the externally forced climate response. J. Clim. 28, 8184–8202 (2015).

37. 37.

Xie, S. P. et al. Global warming pattern formation: sea surface temperature and rainfall. J. Clim. 23, 966–986 (2010).

38. 38.

Hu, K. et al. Interdecadal variations in ENSO influences on Northwest Pacific–East Asian early summertime climate simulated in CMIP5 models. J. Clim. 27, 5982–5998 (2014).

39. 39.

Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 5686–5699 (2006).

40. 40.

Neelin, J. D. & Held, I. M. Modeling tropical convergence based on the moist static energy budget. Mon. Weather Rev. 115, 3–12 (1987).

41. 41.

Yan, Z. et al. Eastward shift and extension of ENSO-induced tropical precipitation anomalies under global warming. Sci. Adv. 6, eaax4177 (2020).

42. 42.

Liu, Z. Y. et al. Evolution and forcing mechanisms of El Niño over the past 21,000 years. Nature 515, 550–553 (2014).

43. 43.

Stevenson, S., Capotondi, A., Fasullo, J. & Otto-Bliesner, B. Forced changes to twentieth century ENSO diversity in a last Millennium context. Clim. Dynam. 52, 7359–7374 (2019).

44. 44.

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. Dynam. 50, 4019–4035 (2018).

45. 45.

Wang, L., Chen, W. & Huang, R. Interdecadal modulation of PDO on the impact of ENSO on the East Asian winter monsoon. Geophys. Res. Lett. 35, L20702 (2008).

46. 46.

Maher, N., Matei, D., Milinski, S. & Marotzke, J. ENSO change in climate projections: forced response or internal variability? Geophys. Res. Lett. 45, 11390–11398 (2018).

47. 47.

Seager, R., Kushnir, Y., Nakamura, J., Ting, M. & Naik, N. Northern Hemisphere winter snow anomalies: ENSO, NAO and the winter of 2009/10. Geophys. Res. Lett. 37, L14703 (2010).

48. 48.

Hu, K., Xie, S.-P. & Huang, G. Orographically anchored El Niño effect on summer rainfall in central China. J. Clim. 30, 10037–10045 (2017).

49. 49.

Chen, W., Feng, J. & Wu, R. Roles of ENSO and PDO in the link of the East Asian winter monsoon to the following summer monsoon. J. Clim. 26, 622–635 (2013).

50. 50.

Seager, R., Naik, N. & Vogel, L. Does global warming cause intensified interannual hydroclimate variability? J. Clim. 25, 3355–3372 (2012).

51. 51.

Kanamitsu, M. et al. NCEP-DOE AMIP-II reanalysis (R-2). Bull. Am. Meteorol. Soc. 83, 1631–1643 (2002).

52. 52.

Adler, R. F. et al. The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–present). J. Hydrometeorol. 4, 1147–1167 (2003).

53. 53.

Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Gerophys. Res. 108, 4407 (2003).

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## Acknowledgements

The work was supported by the National Key Research and Development Program of China (fund number 2019YFA0606703), National Natural Science Foundation of China (41831175), Second Tibetan Plateau Scientific Expedition and Research (STEP) programme (grant number 2019QZKK0102), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20060500), National Natural Science Foundation of China (41775086, 41722504 and 91937302), Key Deployment Project of the Centre for Ocean Mega-Research of Science, Chinese Academy of Sciences (COMS2019Q03) and Youth Innovation Promotion Association of CAS. Y.K. was supported by the Japan Ministry of Education, Culture, Sports, Science and Technology (JPMXD0717935457) and Japan Society for the Promotion of Science (18H01278, 18H01281 and 19H05703). S.-P.X. was supported by the National Science Foundation (AGS 1934392).

## Author information

Authors

### Contributions

K.H. and G.H. conceived the study, performed the analyses, built the mechanism and wrote the paper. P.H., Y.K. and S.-P.X. contributed to improving the paper and assisted in interpretation of the results.

### Corresponding authors

Correspondence to Kaiming Hu or Gang Huang.

## Ethics declarations

### Competing interests

The authors declare no competing interests.

## Additional information

Peer review information Primary Handling Editor: Tom Richardson. Nature Geoscience thanks Tobias Bayr, Andrea Taschetto and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

## Extended data

### Extended Data Fig. 1 Projected change in ENSO-driven variability in boreal winter tropical SST, humidity and air temperature.

The analysis is the same as that in Fig. 1 except for applying a “scaling” method (see Method) for detrending data prior to regressions. The result is almost the same as that in Fig. 1, indicating the result is not sensitive to the selection of method for detrending.

### Extended Data Fig. 2 Projected change in ENSO SST, humidity and air temperature in 18 CMIP5 models (see Methods) from 1950-1999 in historical experiments to 2050-2099 in RCP8.5 experiments.

a, Changes in DJF climatological SST in the MME. b, Comparison of the standard deviation of DJF Niño 3.4 SST index over the two periods in each model and the MME. c, d, Comparison of DJF tropical mean (10°S-10°N) ENSO-driven surface specific humidity ($$q_{sfc}^\prime$$; c) and 200-hPa air temperature ($$T_{200}^\prime$$; d) between the two periods. Error bars in the MME mean correspond to the 95% confidence interval (see Methods). The MME $$q_{sfc}^\prime$$ and $$T_{200}^\prime$$ increases by 9.6±6.1% and 11.5±8.4% respectively for per 1 K background warming in the tropics.

### Extended Data Fig. 3 Projected change in ENSO SST, humidity and air temperature in 30 CMIP6 models (see Methods) from 1950-1999 in historical experiments to 2050-2099 in SSP585 experiments.

a, Changes in DJF climatological SST in the MME. b, Comparison of the standard deviation of DJF Niño 3.4 SST index over the two periods in each model and the MME. c, d, Comparison of DJF tropical mean (10°S-10°N) ENSO-driven surface specific humidity ($$q_{sfc}^\prime$$; c) and 200-hPa air temperature ($$T_{200}^\prime$$; d) between the two periods. Error bars in the MME mean correspond to the 95% confidence interval (see Methods). The MME $$q_{sfc}^\prime$$ and $$T_{200}^\prime$$ increases by 10.2±6.0% and 12.2±8.5% respectively for per 1 K background warming in the tropics.

### Extended Data Fig. 4 Vertical structure of ENSO-driven anomalies of boreal winter air humidity, temperature and circulation.

a, DJF zonally mean ENSO-driven specific humidity anomalies (q′; contours; at interval of 0.05 g kg–1 K–1) and air temperature anomalies (T′; colors) during 1979-2018 in the observations. b, DJF zonally mean ENSO-driven zonal wind anomalies (U′; black contours; at interval of 0.2 m s–1 K–1) and geopotential height anomalies (Z′; colors) during 1979-2018 in the observations. c-d, similar to a and b but for the MME during 400-449 model years in the PI control runs. Stippling in a and b denotes passing 95% confidence level based on a two-tailed Student’s t test, and in c and d indicates that more than 85% of models agree on the sign of the MME.

### Extended Data Fig. 5 ENSO-driven anomalies of boreal winter tropospheric air temperature, 200hPa geopotential height and circulation.

a and c, Vertically averaged (850-200 hPa) ENSO-driven DJF air temperature anomalies (T′). b and d, 200-hPa ENSO-driven DJF geopotential height (Z200′; colors) and wind (UV200′; vectors) anomalies. Anomalies in a and b are derived from the observations during 1979-2018, while in c and d are from the MME during 400-449 model years in the PI control runs. Stippling in a and b denotes passing 95% confidence level based on a two-tailed Student’s t test, and in c and d indicates that more than 85% of models agree on the sign of the MME.

### Extended Data Fig. 6 ENSO-driven DJF anomalies in boreal winter specific humidity and rainfall.

a and c, ENSO-driven DJF low-level 1000-500hPa vertically averaged specific humidity anomalies (q′). b and d, ENSO-driven DJF rainfall anomalies (Pr′). Anomalies in a and b are derived from the observations during 1979-2018, while in c and d are from the MME during 400-449 model years in the PI control runs. Stippling in a and b denotes passing 95% confidence level based on a two-tailed Student’s t test, and in c and d indicates that more than 85% of models agree on the sign of the MME.

### Extended Data Fig. 7 Changes in the response of specific humidity to tropical Indian Ocean SST variability under global warming.

a and b, The regression of June-to-August (JJA) mean SST (a) and 1000-500hPa vertically averaged specific humidity (b) onto a tropical Indian Ocean SST index in the period of P_ctrl. The tropical Indian Ocean SST index is defined as averaging JJA SST anomalies in the domain of 10°S-10°N, 40°E-100°E. c and d, Similar to a and b but for the period of P_warm. e and f, Differences between the two periods (P_warm- P_ctrl). Stippling indicates that more than 85% of models agree on the sign of the MME. The result shows that the response of specific humidity to tropical Indian Ocean SST variability strengthens under global warming.

### Extended Data Fig. 8 Changes in the response of specific humidity to tropical Atlantic SST variability under global warming.

a and b, The regression of JJA SST (a) and 1000-500hPa vertically averaged specific humidity (b) onto a tropical Atlantic SST index in the period of P_ctrl. The tropical Atlantic SST index is defined as averaging JJA SST anomalies in the domain of 10°S-10°N, 60°W-0°. c and d, Similar to a and b but for the period of P_warm. c and d, Differences between the two periods (P_warm- P_ctrl). Stippling indicates that more than 85% of models agree on the sign of the MME. The result shows that the response of specific humidity to tropical Atlantic SST variability strengthens under global warming.

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### Cite this article

Hu, K., Huang, G., Huang, P. et al. Intensification of El Niño-induced atmospheric anomalies under greenhouse warming. Nat. Geosci. 14, 377–382 (2021). https://doi.org/10.1038/s41561-021-00730-3

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