Climate Dynamics

, Volume 50, Issue 11–12, pp 4019–4035 | Cite as

Response of ENSO amplitude to global warming in CESM large ensemble: uncertainty due to internal variability

  • Xiao-Tong Zheng
  • Chang Hui
  • Sang-Wook Yeh


El Niño–Southern Oscillation (ENSO) is the dominant mode of variability in the coupled ocean-atmospheric system. Future projections of ENSO change under global warming are highly uncertain among models. In this study, the effect of internal variability on ENSO amplitude change in future climate projections is investigated based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. A large uncertainty is identified among ensemble members due to internal variability. The inter-member diversity is associated with a zonal dipole pattern of sea surface temperature (SST) change in the mean along the equator, which is similar to the second empirical orthogonal function (EOF) mode of tropical Pacific decadal variability (TPDV) in the unforced control simulation. The uncertainty in CESM-LE is comparable in magnitude to that among models of the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting the contribution of internal variability to the intermodel uncertainty in ENSO amplitude change. However, the causations between changes in ENSO amplitude and the mean state are distinct between CESM-LE and CMIP5 ensemble. The CESM-LE results indicate that a large ensemble of ~15 members is needed to separate the relative contributions to ENSO amplitude change over the twenty-first century between forced response and internal variability.



We acknowledge the CESM-LE project for providing model outputs, which may be obtained from We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. We thank Shang-Ping Xie and Qinyu Liu for helpful discussions. This work was supported by the National Basic Research Program of China (2012CB955600 and 2015CB954300), the National Natural Science Foundation of China (41476003), NSFC-Shandong Joint Fund for Marine Science Research Centers (U1406401), and the China Meteorological Public Welfare Scientific Research Project (GYHY201306027).


  1. An S-I, Choi J (2015) Why the twenty-first century tropical Pacific trend pattern cannot significantly influence ENSO amplitude? Clim Dyn 44:133–146CrossRefGoogle Scholar
  2. Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97:163–172CrossRefGoogle Scholar
  3. Burgman RJ, Schopf PS, Kirtman BP (2008) Decadal modulation of ENSO in a hybrid coupled model. J Clim 21:5482–5500CrossRefGoogle Scholar
  4. Cai W, Borlace S, Lengaigne M, Rensch P, Collins M, Vecchi G, Timmermann A, Santoso A, McPhaden M, Wu L, England M, Wang G-J, Guilyardi E, Jin F-F (2014) Increasing frequency of extreme El Niño events due to greenhouse warming. Nat Clim Change 4:111–116CrossRefGoogle Scholar
  5. Cai W et al (2015a) ENSO and greenhouse warming. Nat Clim Change 5:849–859CrossRefGoogle Scholar
  6. Cai W, Wang G, Santoso A, McPhaden M, Wu L, Jin F-F, Timmermann A, Collins M, Vecchi G, Lengaigne M, England M, Dommenget D, Takahashi K, Guilyardi E (2015b) More frequent extreme La Niña events under greenhouse warming. Nat Clim Change 5:132–137CrossRefGoogle Scholar
  7. Choi J, An SI, Yeh SW, Yu J-Y (2013) ENSO-like and ENSO-induced tropical pacific decadal variability in CGCMs. J Clim 26:1485–1501CrossRefGoogle Scholar
  8. Chowdary JS, Xie S-P, Tokinaga H, Okumura YM, Kubota H, Johnson NC, Zheng XT (2012) Inter-decadal variations in ENSO teleconnection to the Indo-western Pacific for 1870–2007. J Clim 25:1722–1744CrossRefGoogle Scholar
  9. Collins M, An S-I, Cai W, Ganachaud A, Guilyardi E, Jin F-F, Jochum M, Lengaigne M, Power S, Timmermann A, Vecchi G, Wittenberg A (2010) The impact of global warming on the tropical Pacific Ocean and El Niño. Nat Geosci 3:391–397CrossRefGoogle Scholar
  10. Deser C, Phillips AS, Bourdette V, Teng H (2012a) Uncertainty in climate change projections: the role of internal variability. Clim Dyn 38:527–546CrossRefGoogle Scholar
  11. Deser C, Knutti R, Solomon S, Phillips AS (2012b) Communication of the role of natural variability in future North American climate. Nat Clim Change 2:775–779CrossRefGoogle Scholar
  12. DiNezio PN, Kirtman BP, Clement AS, Lee S-K, Vecchi GA, Wittenberg A (2012) Mean climate controls on the simulated response of ENSO to increasing greenhouse gases. J Clim 25:7399–7420CrossRefGoogle Scholar
  13. Fang Y, Chiang JCH, Chang P (2008) Variation of mean sea surface temperature and modulation of El Niño–Southern Oscillation variance during the past 150 years. Geophys Res Lett 35:L14709. doi: 10.1029/2008GL033761 CrossRefGoogle Scholar
  14. Guilyardi E, Wittenberg A, Fedorov A, Collins M, Wang C, Capotondi A, van Oldenborgh GJ, Stockdale T (2009) Understanding El Niño in ocean–atmosphere general circulation models: progress and challenges. Bull Am Meteor Soc 90:325–340CrossRefGoogle Scholar
  15. Ham YG, Kug J-S (2016) ENSO amplitude changes due to greenhouse warming in CMIP5: role of mean tropical precipitation in the twentieth century. Geophys Res Lett. doi: 10.1002/2015gl066864 Google Scholar
  16. Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteor Soc 90:1095–1107CrossRefGoogle Scholar
  17. Hawkins E, Sutton R (2012) Time of emergence of climate signals. Geophys Res Lett 39:L01702CrossRefGoogle Scholar
  18. Hurrell J et al (2013) The community earth system model: a framework for collaborative research. Bull Am Meteorol Soc 94:1339–1360CrossRefGoogle Scholar
  19. Johnson NC, Xie S-P (2010) Changes in the sea surface temperature threshold for tropical convection. Nat Geosci 3:842–845CrossRefGoogle Scholar
  20. Kay JE et al (2015) The community earth system model (CESM) large ensemble project: a community resource for studying climate change in the presence of internal climate variability. Bull Am Meteorol Soc 96:1333–1349CrossRefGoogle Scholar
  21. Kim S-T, Cai W, Jin F-F, Santoso A, Wu L, Guilyardi E, An S-I (2014) Response of El Niño sea surface temperature variability to greenhouse warming. Nat Clim Change 4:786–790CrossRefGoogle Scholar
  22. Li J, Xie S-P, Cook ER, Huang G, D’Arrigo R, Liu F, Ma J, Zheng X-T (2011) Interdecadal modulation of El Niño amplitude during the past millennium. Nat Clim Change 1:114–118CrossRefGoogle Scholar
  23. Li J, Xie S-P, Cook ER, Morales M, Christie D, Johnson NC, Chen F, D’Arrigo R, Fowler A, Gou X, Fang K (2013) El Niño modulations over the past seven centuries. Nat Clim Change 3:822–826CrossRefGoogle Scholar
  24. Liu Z, Vavrus S, He F, Wen N, Zhong Y (2005) Rethinking tropical ocean response to global warming: the enhanced equatorial warming. J Clim 18:4684–4700CrossRefGoogle Scholar
  25. Liu F, Luo Y, Lu Y, Wan X (2016) Response of the tropical Pacific Ocean to El Niño versus global warming. Clim Dyn 48:935–956CrossRefGoogle Scholar
  26. Lu J, Zhao B (2012) The role of oceanic feedback in the climate response to doubling CO2. J Clim 25:7544–7563CrossRefGoogle Scholar
  27. Luo Y, Lu J, Liu F, Liu W (2015) Understanding the El Niño-like oceanic response in the tropical Pacific to global warming. Clim Dyn 45:1945–1964CrossRefGoogle Scholar
  28. Neale RB et al. (2012) Description of the NCAR community atmosphere model (CAM 5.0). NCAR tech note TN-486, pp 274Google Scholar
  29. Ogata T, Xie S-P, Wittenberg A, Sun D-Z (2013) Interdecadal amplitude modulation of El Niño/Southern Oscillation and its impacts on tropical Pacific decadal variability. J Clim 26:7280–7297CrossRefGoogle Scholar
  30. Philander SG (1990) El Niño, La Niña and the southern oscillation. Academic Press, San Diego, CA, 293 ppGoogle Scholar
  31. Power S, Delage F, Chung C, Kociuba G, Keay K (2013) Robust twenty-first-century projections of El Niño and related precipitation variability. Nature 502:541–545CrossRefGoogle Scholar
  32. Rashid HA, Hirst AC, Marsland SJ (2016) An atmospheric mechanism for ENSO amplitude changes under an abrupt quadrupling of CO2 concentration in CMIP5 models. Geophys Res Lett 43:1687–1694. doi: 10.1002/2015GL066768 CrossRefGoogle Scholar
  33. Rodgers KB, Friederichs P, Latif M (2004) Tropical Pacific decadal variability and its relation to decadal modulations of ENSO. J Clim 17:3761–3774CrossRefGoogle Scholar
  34. Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296CrossRefGoogle Scholar
  35. Smith RD et al (2010) The parallel ocean program (POP) reference manual: ocean component of the community climate system model (CCSM) and community earth system model (CESM). Los Alamos National Laboratory Tech Rep LAUR-10-01853, p 141Google Scholar
  36. Stevenson SL (2012) Significant changes to ENSO strength and impacts in the twenty-first century: results from CMIP5. Geophys Res Lett 39:L17703CrossRefGoogle Scholar
  37. Sun F, Yu J-Y (2009) A 10–15-yr modulation cycle of ENSO intensity. J Clim 22:1718–1735CrossRefGoogle Scholar
  38. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498CrossRefGoogle Scholar
  39. Vecchi GA, Soden BJ (2007) Global warming and the weakening of the tropical circulation. J Clim 20:4316–4340CrossRefGoogle Scholar
  40. Watanabe M, Wittenberg AT (2012) A method for disentangling El Niño–mean state interaction. Geophys Res Lett 39:L14702. doi: 10.1029/2012GL052013 CrossRefGoogle Scholar
  41. Watanabe M, Kug J-S, Jin F-F, Collins M, Ohba M, Wittenberg AT (2012) Uncertainty in the ENSO amplitude change from the past to the future. Geophys Res Lett 39:L20703CrossRefGoogle Scholar
  42. Wittenberg AT (2002) ENSO response to altered climates. Ph.D. thesis, Princeton UniversityGoogle Scholar
  43. Wittenberg AT (2009) Are historical records sufficient to constrain ENSO simulations? Geophys Res Lett 36:L12702CrossRefGoogle Scholar
  44. Wittenberg AT, Rosati A, Delworth TL, Vecchi GA, Zeng F (2014) ENSO modulation: is it decadally predictable? J Clim 27:2667–2681CrossRefGoogle Scholar
  45. Xie S-P, Deser C, Vecchi GA, Ma J, Teng H, Wittenberg AT (2010a) Global warming pattern formation: sea surface temperature and rainfall. J Clim 23:966–986CrossRefGoogle Scholar
  46. Xie S-P, Du Y, Huang G, Zheng X-T, Tokinaga H, Hu K, Liu Q (2010b) Decadal shift in El Niño influences on Indo-western Pacific and East Asian climate in the 1970s. J Clim 23:3352–3368CrossRefGoogle Scholar
  47. Yeh S-W, Kirtman B (2004) Tropical Pacific decadal variability and ENSO amplitude modulation in a CGCM. J Geophys Res 109:C11009. doi: 10.1029/2004JC002442 CrossRefGoogle Scholar
  48. Yeh S-W, Kirtman B (2007) ENSO amplitude changes due to climate change projections in different coupled models. J Clim 20:203–217CrossRefGoogle Scholar
  49. Zheng X-T, Xie S-P, Lv L-H, Zhou Z-Q (2016) Intermodel uncertainty in ENSO amplitude change tied to Pacific ocean warming pattern. J Clim 29:7265–7279CrossRefGoogle Scholar
  50. Zhou Z-Q, Xie S-P, Zheng X-T, Liu Q, Wang H (2014) Global warming-induced changes in El Niño teleconnections over the North Pacific and North America. J Clim 27:9050–9064CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Physical Oceanography Laboratory/CIMSTOcean University of China and Qingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  2. 2.Key Laboratory of Ocean–Atmosphere Interaction and Climate in Universities of ShandongOcean University of ChinaQingdaoChina
  3. 3.Department of Marine Sciences and Convergent TechnologyHanyang UniversityAnsanSouth Korea
  4. 4.College of Oceanic and Atmospheric SciencesOcean University of ChinaQingdaoChina

Personalised recommendations