• AchutaRao, K., and K. R. Sperber, 2006: ENSO simulation in coupled ocean-atmosphere models: Are the current models better? Climate Dyn., 27, 115, https://doi.org/10.1007/s00382-006-0119-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • An, S.-I., J.-W. Kim, S.-H. Im, B.-M. Kim, and J.-H. Park, 2011: Recent and future sea surface temperature trends in tropical Pacific warm pool and cold tongue regions. Climate Dyn., 39, 13731383, https://doi.org/10.1007/s00382-011-1129-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson, W. B., R. Seager, W. Baethgen, M. Cane, and L. You, 2019: Synchronous crop failures and climate-forced production variability. Sci. Adv., 5, eaaw1976, https://doi.org/10.1126/sciadv.aaw1976.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anyamba, A., and et al. , 2019: Global disease outbreaks associated with the 2015–2016 El Niño event. Sci. Rep., 9, 1930, https://doi.org/10.1038/s41598-018-38034-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arora, V. K., and et al. , 2011: Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys. Res. Lett., 38, L05805, https://doi.org/10.1029/2010gl046270.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ashok, K., S. K. Behera, S. A. Rao, H. Weng, and T. Yamagata, 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res., 112, C11007, https://doi.org/10.1029/2006jc003798.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bao, Q., and et al. , 2013: The Flexible Global Ocean-Atmosphere-Land System Model, Spectral version 2: FGOALS-s2. Adv. Atmos. Sci., 30, 561576, https://doi.org/10.1007/s00376-012-2113-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bayr, T., D. Dommenget, T. Martin, and S. B. Power, 2014: The eastward shift of the Walker circulation in response to global warming and its relationship to ENSO variability. Climate Dyn., 43, 27472763, https://doi.org/10.1007/s00382-014-2091-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bayr, T., M. Latif, D. Dommenget, C. Wengel, J. Harlaß, and W. Park, 2017: Mean-state dependence of ENSO atmospheric feedbacks in climate models. Climate Dyn., 50, 31713194, https://doi.org/10.1007/s00382-017-3799-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bayr, T., C. Wengel, M. Latif, D. Dommenget, J. Lübbecke, and W. Park, 2019: Error compensation of ENSO atmospheric feedbacks in climate models and its influence on simulated ENSO dynamics. Climate Dyn., 53, 155172, https://doi.org/10.1007/s00382-018-4575-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bellenger, H., E. Guilyardi, J. Leloup, M. Lengaigne, and J. Vialard, 2014: ENSO representation in climate models: From CMIP3 to CMIP5. Climate Dyn., 42, 19992018, https://doi.org/10.1007/s00382-013-1783-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bentsen, M., and et al. , 2013: The Norwegian Earth System Model, NorESM1-M—Part I: Description and basic evaluation of the physical climate. Geosci. Model Dev., 6, 687720, https://doi.org/10.5194/gmd-6-687-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bi, D., and et al. , 2013: The ACCESS coupled model: Description, control climate and evaluation. Aust. Meteor. Oceanogr. J., 63, 4164, https://doi.org/10.22499/2.6301.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, J. N., C. Langlais, and C. Maes, 2013: Zonal structure and variability of the western Pacific dynamic warm pool edge in CMIP5. Climate Dyn., 42, 30613076, https://doi.org/10.1007/s00382-013-1931-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, J. N., C. Langlais, and A. Sen Gupta, 2015: Projected sea surface temperature changes in the equatorial Pacific relative to the warm pool edge. Deep-Sea Res. II, 113, 4758, https://doi.org/10.1016/j.dsr2.2014.10.022.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cai, W., and et al. , 2018: Increased variability of eastern Pacific El Niño under greenhouse warming. Nature, 564, 201206, https://doi.org/10.1038/s41586-018-0776-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cane, M., A. Clement, A. Kaplan, Y. Kushnir, D. Pozdnyakov, R. Seager, S. Zebiak, and R. Murtugudde, 1997: Twentieth-century sea surface temperature trends. Science, 275, 957960, https://doi.org/10.1126/science.275.5302.957.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Capotondi, A., and et al. , 2015: Understanding ENSO diversity. Bull. Amer. Meteor. Soc., 96, 921938, https://doi.org/10.1175/BAMS-D-13-00117.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cashin, P., K. Mohaddes, and M. Raissi, 2017: Fair weather or foul? The macroeconomic effects of El Niño. J. Int. Econ., 106, 3754, https://doi.org/10.1016/j.jinteco.2017.01.010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chang, P., B. Wang, T. Li, and L. Ji, 1994: Interactions between the seasonal cycle and the Southern Oscillation—Frequency entrainment and chaos in a coupled ocean-atmosphere model. Geophys. Res. Lett., 21, 28172820, https://doi.org/10.1029/94GL02759.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, C., M. A. Cane, A. T. Wittenberg, and D. Chen, 2017: ENSO in the CMIP5 simulations: Life cycles, diversity, and responses to climate change. J. Climate, 30, 775801, https://doi.org/10.1175/JCLI-D-15-0901.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, D., and et al. , 2015: Strong influence of westerly wind bursts on El Niño diversity. Nat. Geosci., 8, 339345, https://doi.org/10.1038/ngeo2399.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Choi, J., S.-I. An, and S.-W. Yeh, 2011: Decadal amplitude modulation of two types of ENSO and its relationship with the mean state. Climate Dyn., 38, 26312644, https://doi.org/10.1007/s00382-011-1186-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chung, P.-H., and T. Li, 2013: Interdecadal relationship between the mean state and El Niño types. J. Climate, 26, 361379, https://doi.org/10.1175/JCLI-D-12-00106.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coats, S., and K. B. Karnauskas, 2017: Are simulated and observed twentieth century tropical Pacific sea surface temperature trends significant relative to internal variability? Geophys. Res. Lett., 44, 99289937, https://doi.org/10.1002/2017GL074622.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, M., and T. C. M. Groups, 2004: El Niño- or La Niña-like climate change? Climate Dyn., 24, 89104, https://doi.org/10.1007/s00382-004-0478-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, M., and et al. , 2010: The impact of global warming on the tropical Pacific Ocean and El Niño. Nat. Geosci., 3, 391397, https://doi.org/10.1038/ngeo868.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, W. J., and et al. , 2011: Development and evaluation of an Earth-system model—HadGEM2. Geosci. Model Dev., 4, 10511075, https://doi.org/10.5194/gmd-4-1051-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dewitte, B., S.-W. Yeh, B.-K. Moon, C. Cibot, and L. Terray, 2007: Rectification of ENSO variability by interdecadal changes in the equatorial background mean state in a CGCM simulation. J. Climate, 20, 20022021, https://doi.org/10.1175/JCLI4110.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Di Lorenzo, E., K. M. Cobb, J. C. Furtado, N. Schneider, B. T. Anderson, A. Bracco, M. A. Alexander, and D. J. Vimont, 2010: Central Pacific El Niño and decadal climate change in the North Pacific Ocean. Nat. Geosci., 3, 762765, https://doi.org/10.1038/ngeo984.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donner, L. J., and et al. , 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 34843519, https://doi.org/10.1175/2011JCLI3955.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dufresne, J. L., and et al. , 2013: Climate change projections using the IPSL-CM5 Earth system model: From CMIP3 to CMIP5. Climate Dyn., 40, 21232165, https://doi.org/10.1007/s00382-012-1636-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., and et al. , 2012: GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: Physical formulation and baseline simulation characteristics. J. Climate, 25, 66466665, https://doi.org/10.1175/JCLI-D-11-00560.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 19371958, https://doi.org/10.5194/gmd-9-1937-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fogli, P. G., and et al. , 2009: INGV-CMCC carbon (ICC): A carbon cycle earth system model. CMCC Research Paper 61, 31 pp., http://www.cmcc.it/publications-meetings/publications/research-papers/rp0061-ingv-cmcc-carbon-icc-a-carbon-cycle-earth-system-model.

    • Crossref
    • Export Citation
  • Frauen, C., D. Dommenget, N. Tyrrell, M. Rezny, and S. Wales, 2014: Analysis of the nonlinearity of El Niño–Southern Oscillation teleconnections. J. Climate, 27, 62256244, https://doi.org/10.1175/JCLI-D-13-00757.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Freund, M. B., B. J. Henley, D. J. Karoly, H. V. McGregor, N. J. Abram, and D. Dommenget, 2019: Higher frequency of central Pacific El Niño events in recent decades relative to past centuries. Nat. Geosci., 12, 450455, https://doi.org/10.1038/s41561-019-0353-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and et al. , 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, https://doi.org/10.1175/2011JCLI4083.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gettelman, A., and et al. , 2019: High climate sensitivity in the Community Earth System Model version 2 (CESM2). Geophys. Res. Lett., 46, 83298337, https://doi.org/10.1029/2019GL083978.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giorgetta, M. A., and et al. , 2013: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Model. Earth Syst., 5, 572597, https://doi.org/10.1002/jame.20038.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graham, F. S., A. T. Wittenberg, J. N. Brown, S. J. Marsland, and N. J. Holbrook, 2017: Understanding the double peaked El Niño in coupled GCMs. Climate Dyn., 48, 20452063, https://doi.org/10.1007/s00382-016-3189-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graham, N. E., 1994: Decadal-scale climate variability in the tropical and north Pacific during the 1970s and 1980s—Observations and model results. Climate Dyn., 10, 135162, https://doi.org/10.1007/BF00210626.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, C., and M. J. McPhaden, 2016: Ocean processes affecting the twenty-first-century shift in ENSO SST variability. J. Climate, 29, 68616879, https://doi.org/10.1175/JCLI-D-15-0870.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guilyardi, E., 2005: El Niño–mean state–seasonal cycle interactions in a multi-model ensemble. Climate Dyn., 26, 329348, https://doi.org/10.1007/s00382-005-0084-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ham, Y.-G., and J.-S. Kug, 2011: How well do current climate models simulate two types of El Niño? Climate Dyn., 39, 383398, https://doi.org/10.1007/s00382-011-1157-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ham, Y.-G., J.-S. Kug, J.-Y. Park, and F.-F. Jin, 2013: Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern Oscillation events. Nat. Geosci., 6, 112116, https://doi.org/10.1038/ngeo1686.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hare, S. R., and N. J. Mantua, 2000: Empirical evidence for North Pacific regime shifts in 1977 and 1989. Prog. Oceanogr., 47, 103145, https://doi.org/10.1016/S0079-6611(00)00033-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global warming. J. Climate, 19, 56865699, https://doi.org/10.1175/JCLI3990.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henley, B. J., J. Gergis, D. J. Karoly, S. Power, J. Kennedy, and C. K. Folland, 2015: A tripole index for the interdecadal Pacific oscillation. Climate Dyn., 45, 30773090, https://doi.org/10.1007/s00382-015-2525-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henley, B. J., and et al. , 2017: Spatial and temporal agreement in climate model simulations of the interdecadal Pacific oscillation. Environ. Res. Lett., 12, 044011, https://doi.org/10.1088/1748-9326/aa5cc8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, S., and A. V. Fedorov, 2018: Cross-equatorial winds control El Niño diversity and change. Nat. Climate Change, 8, 798802, https://doi.org/10.1038/s41558-018-0248-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., A. Kumar, H.-L. Ren, H. Wang, M. L’Heureux, and F.-F. Jin, 2013: Weakened interannual variability in the tropical Pacific Ocean since 2000. J. Climate, 26, 26012613, https://doi.org/10.1175/JCLI-D-12-00265.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iizumi, T., J.-J. Luo, A. J. Challinor, G. Sakurai, M. Yokozawa, H. Sakuma, M. E. Brown, and T. Yamagata, 2014: Impacts of El Niño Southern Oscillation on the global yields of major crops. Nat. Commun., 5, 3712, https://doi.org/10.1038/ncomms4712.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ji, D., and et al. , 2014: Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1. Geosci. Model Dev., 7, 20392064, https://doi.org/10.5194/gmd-7-2039-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kao, H.-Y., and J.-Y. Yu, 2009: Contrasting eastern-Pacific and central-Pacific types of ENSO. J. Climate, 22, 615632, https://doi.org/10.1175/2008JCLI2309.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Karnauskas, K. B., R. Seager, A. Kaplan, Y. Kushnir, and M. A. Cane, 2009: Observed strengthening of the zonal sea surface temperature gradient across the equatorial Pacific Ocean. J. Climate, 22, 43164321, https://doi.org/10.1175/2009JCLI2936.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, S. T., and J.-Y. Yu, 2012: The two types of ENSO in CMIP5 models. Geophys. Res. Lett., 39, L11704, https://doi.org/10.1029/2012gl052006.

  • Knutti, R., D. Masson, and A. Gettelman, 2013: Climate model genealogy: Generation CMIP5 and how we got there. Geophys. Res. Lett., 40, 11941199, https://doi.org/10.1002/grl.50256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kohyama, T., and D. L. Hartmann, 2017: Nonlinear ENSO Warming Suppression (NEWS). J. Climate, 30, 42274251, https://doi.org/10.1175/JCLI-D-16-0541.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kohyama, T., D. L. Hartmann, and D. S. Battisti, 2017: La Niña–like mean-state response to global warming and potential oceanic roles. J. Climate, 30, 42074225, https://doi.org/10.1175/JCLI-D-16-0441.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kosaka, Y., and S.-P. Xie, 2013: Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature, 501, 403407, https://doi.org/10.1038/nature12534.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kug, J.-S., F.-F. Jin, and S.-I. An, 2009: Two types of El Niño events: Cold tongue El Niño and warm pool El Niño. J. Climate, 22, 14991515, https://doi.org/10.1175/2008JCLI2624.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Larkin, N. K., and D. E. Harrison, 2005: Global seasonal temperature and precipitation anomalies during El Niño autumn and winter. Geophys. Res. Lett., 32, L16705, https://doi.org/10.1029/2005GL022860.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, T., and M. J. McPhaden, 2010: Increasing intensity of El Niño in the central-equatorial Pacific. Geophys. Res. Lett., 37, L14603, https://doi.org/10.1029/2010GL044007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • L’Heureux, M. L., D. C. Collins, and Z.-Z. Hu, 2012: Linear trends in sea surface temperature of the tropical Pacific Ocean and implications for the El Niño–Southern Oscillation. Climate Dyn., 40, 12231236, https://doi.org/10.1007/s00382-012-1331-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, G., and S.-P. Xie, 2014: Tropical biases in CMIP5 multimodel ensemble: The excessive equatorial Pacific cold tongue and double ITCZ problems. J. Climate, 27, 17651780, https://doi.org/10.1175/JCLI-D-13-00337.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lian, T., D. Chen, J. Ying, P. Huang, and Y. Tang, 2018: Tropical Pacific trends under global warming: El Niño-like or La Niña-like? Natl. Sci. Rev., 5, 810812, https://doi.org/10.1093/nsr/nwy134.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Y., and et al. , 2017: Recent enhancement of central Pacific El Niño variability relative to last eight centuries. Nat. Commun., 8, 15386, https://doi.org/10.1038/ncomms15386.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Z., and E. Lorenzo, 2018: Mechanisms and predictability of pacific decadal variability. Curr. Climate Change Rep., 4, 128144, https://doi.org/10.1007/s40641-018-0090-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lloyd, J., E. Guilyardi, H. Weller, and J. Slingo, 2009: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Atmos. Sci. Lett., 10, 170176, https://doi.org/10.1002/asl.227.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Long, M. C., K. Lindsay, S. Peacock, J. K. Moore, and S. C. Doney, 2013: Twentieth-century oceanic carbon uptake and storage in CESM1(BGC). J. Climate, 26, 67756800, https://doi.org/10.1175/JCLI-D-12-00184.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lübbecke, J. F., and M. J. McPhaden, 2014: Assessing the twenty-first-century shift in ENSO variability in terms of the Bjerknes stability index. J. Climate, 27, 25772587, https://doi.org/10.1175/JCLI-D-13-00438.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., W. Sasaki, and Y. Masumoto, 2012: Indian Ocean warming modulates Pacific climate change. Proc. Natl. Acad. Sci. USA, 109, 18 70118 706, https://doi.org/10.1073/pnas.1210239109.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mann, M. E., M. Cane, S. E. Zebiak, and A. Clement, 2005: Volcanic and solar forcing of the tropical Pacific over the past 1000 years. J. Climate, 18, 447456, https://doi.org/10.1175/JCLI-3276.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis, 1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Amer. Meteor. Soc., 78, 10691079, https://doi.org/10.1175/1520-0477(1997)078<1069:apicow>2.0.co;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McPhaden, M. J., T. Lee, and D. McClurg, 2011: El Niño and its relationship to changing background conditions in the tropical Pacific Ocean. Geophys. Res. Lett., 38, L15709, https://doi.org/10.1029/2011gl048275.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., and et al. , 2013: Climate change projections in CESM1(CAM5) compared to CCSM4. J. Climate, 26, 62876308, https://doi.org/10.1175/JCLI-D-12-00572.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meinshausen, M., and et al. , 2011: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109, 213241, https://doi.org/10.1007/s10584-011-0156-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meinshausen, M., and et al. , 2020: The SSP greenhouse gas concentrations and their extensions to 2500. Geosci. Model Dev., https://doi.org/10.5194/gmd-2019-222, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miller, R. L., and et al. , 2014: CMIP5 historical simulations (1850–2012) with GISS ModelE2. J. Adv. Model. Earth Syst., 6, 441478, https://doi.org/10.1002/2013MS000266.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neelin, J. D., F. F. Jin, and H. H. Syu, 2000: Variations in ENSO phase locking. J. Climate, 13, 25702590, https://doi.org/10.1175/1520-0442(2000)013<2570:VIEPL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, M., G. P. Compo, and M. A. Alexander, 2003: ENSO-forced variability of the Pacific decadal oscillation. J. Climate, 16, 38533857, https://doi.org/10.1175/1520-0442(2003)016<3853:EVOTPD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, M., S.-I. Shin, and M. A. Alexander, 2011: Natural variation in ENSO flavors. Geophys. Res. Lett., 38, L14705, https://doi.org/10.1029/2011GL047658.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Power, S., T. Casey, C. Folland, A. Colman, and V. Mehta, 1999: Inter-decadal modulation of the impact of ENSO on Australia. Climate Dyn., 15, 319324, https://doi.org/10.1007/s003820050284.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiao, F., Z. Song, Y. Bao, Y. Song, Q. Shu, C. Huang, and W. Zhao, 2013: Development and evaluation of an Earth System Model with surface gravity waves. J. Geophys. Res. Oceans, 118, 45144524, https://doi.org/10.1002/jgrc.20327.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rasmusson, E. M., and T. H. Carpenter, 1982: Variation in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110, 354384, https://doi.org/10.1175/1520-0493(1982)110<0354:VITSST>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rayner, N. A., D. E. Parker, and E. B. Horton, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ren, H.-L., and F.-F. Jin, 2011: Niño indices for two types of ENSO. Geophys. Res. Lett., 38, L04704, https://doi.org/10.1029/2010GL046031.

  • Roeckner, E., and et al. , 2003: The atmospheric general circulation model ECHAM 5. Part I: Model description. MPI Rep. 349, 140 pp., https://www.mpimet.mpg.de/fileadmin/models/echam/mpi_report_349.pdf.

  • Rotstayn, L. D., S. J. Jeffrey, M. A. Collier, S. M. Dravitzki, A. C. Hirst, J. I. Syktus, and K. K. Wong, 2012: Aerosol- and greenhouse gas-induced changes in summer rainfall and circulation in the Australasian region: A study using single-forcing climate simulations. Atmos. Chem. Phys., 12, 63776404, https://doi.org/10.5194/acp-12-6377-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sakamoto, T. T., and et al. , 2012: MIROC4h—A new high-resolution atmosphere–ocean coupled general circulation model. J. Meteor. Soc. Japan, 90, 325359, https://doi.org/10.2151/jmsj.2012-301.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., M. Cane, N. Henderson, D.-E. Lee, R. Abernathey, and H. Zhang, 2019: Strengthening tropical Pacific zonal sea surface temperature gradient consistent with rising greenhouse gases. Nat. Climate Change, 9, 517522, https://doi.org/10.1038/s41558-019-0505-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Solomon, A., and M. Newman, 2012: Reconciling disparate twentieth-century Indo-Pacific Ocean temperature trends in the instrumental record. Nat. Climate Change, 2, 691699, https://doi.org/10.1038/nclimate1591.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stuecker, M. F., A. Timmermann, F.-F. Jin, S. McGregor, and H.-L. Ren, 2013: A combination mode of the annual cycle and the El Niño/Southern Oscillation. Nat. Geosci., 6, 540544, https://doi.org/10.1038/ngeo1826.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sullivan, A., J.-J. Luo, A. C. Hirst, D. Bi, W. Cai, and J. He, 2016: Robust contribution of decadal anomalies to the frequency of central-Pacific El Niño. Sci. Rep., 6, 38540, https://doi.org/10.1038/srep38540.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, D. Z., and Z. Y. Liu, 1996: Dynamic ocean-atmosphere coupling: A thermostat for the tropics. Science, 272, 11481150, https://doi.org/10.1126/science.272.5265.1148.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taschetto, A. S., A. S. Gupta, N. C. Jourdain, A. Santoso, C. C. Ummenhofer, and M. H. England, 2014: Cold tongue and warm pool ENSO events in CMIP5: Mean state and future projections. J. Climate, 27, 28612885, https://doi.org/10.1175/JCLI-D-13-00437.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tatebe, H., Y. Imada, M. Mori, M. Kimoto, and H. Hasumi, 2013: Control of decadal and bidecadal climate variability in the tropical Pacific by the off-equatorial South Pacific Ocean. J. Climate, 26, 65246534, https://doi.org/10.1175/JCLI-D-12-00137.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Timmermann, A., and et al. , 2018: El Niño–Southern Oscillation complexity. Nature, 559, 535545, https://doi.org/10.1038/s41586-018-0252-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., and D. P. Stepaniak, 2001: Indices of El Niño evolution. J. Climate, 14, 16971701, https://doi.org/10.1175/1520-0442(2001)014<1697:LIOENO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tziperman, E., L. Stone, M. Cane, and H. Jarosh, 1994: El Niño chaos: Overlapping of resonances between the seasonal cycle and the Pacific Ocean–atmosphere oscillator. Science, 264, 7274, https://doi.org/10.1126/science.264.5155.72.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., B. J. Soden, A. T. Wittenberg, I. M. Held, A. Leetmaa, and M. J. Harrison, 2006: Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing. Nature, 441, 7376, https://doi.org/10.1038/nature04744.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voldoire, A., and et al. , 2012: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 20912121, https://doi.org/10.1007/s00382-011-1259-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Volodin, E. M., N. A. Dianskii, and A. V. Gusev, 2010: Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations. Izv. Atmos. Oceanic Phys., 46, 414431, https://doi.org/10.1134/S000143381004002X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., X. Luo, Y.-M. Yang, W. Sun, M. A. Cane, W. Cai, S.-W. Yeh, and J. Liu, 2019: Historical change of El Niño properties sheds light on future changes of extreme El Niño. Proc. Natl. Acad. Sci. USA, 116, 22 51222 517, https://doi.org/10.1073/pnas.1911130116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ward, P. J., B. Jongman, M. Kummu, M. D. Dettinger, F. C. Sperna Weiland, and H. C. Winsemius, 2014: Strong influence of El Niño Southern Oscillation on flood risk around the world. Proc. Natl. Acad. Sci. USA, 111, 15 65915 664, https://doi.org/10.1073/pnas.1409822111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and et al. , 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 63126335, https://doi.org/10.1175/2010JCLI3679.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, S., and et al. , 2011: MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev., 4, 845872, https://doi.org/10.5194/gmd-4-845-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wengel, C., 2018: Seasonal ENSO phase locking in the Kiel Climate Model: The importance of the equatorial cold sea surface temperature bias. Climate Dyn., 50, 901919, https://doi.org/10.1007/s00382-017-3648-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wittenberg, A. T., 2009: Are historical records sufficient to constrain ENSO simulations? Geophys. Res. Lett., 36, L12702, https://doi.org/10.1029/2009GL038710.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wittenberg, A. T., A. Rosati, N.-C. Lau, and J. J. Ploshay, 2006: GFDL’s CM2 global coupled climate models. Part III: Tropical Pacific climate and ENSO. J. Climate, 19, 698722, https://doi.org/10.1175/JCLI3631.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, T., and et al. , 2008: The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate. Climate Dyn., 34, 123147, https://doi.org/10.1007/s00382-008-0487-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yeh, S.-W., J.-S. Kug, B. Dewitte, M.-H. Kwon, B. P. Kirtman, and F.-F. Jin, 2009: El Niño in a changing climate. Nature, 461, 511514, https://doi.org/10.1038/nature08316.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yeh, S.-W., B. P. Kirtman, J.-S. Kug, W. Park, and M. Latif, 2011: Natural variability of the central Pacific El Niño event on multi-centennial timescales. Geophys. Res. Lett., 38, L02704, https://doi.org/10.1029/2010gl045886.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yeh, S.-W., X. Wang, C. Wang, and B. Dewitte, 2015: On the relationship between the North Pacific climate variability and the central Pacific El Niño. J. Climate, 28, 663677, https://doi.org/10.1175/JCLI-D-14-00137.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yukimoto, S., and et al. , 2012: A new global climate model of the Meteorological Research Institute: MRI-CGCM3-model description and basic performance. J. Meteor. Soc. Japan, 90A, 2364, https://doi.org/10.2151/jmsj.2012-a02.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, H., A. Clement, and P. Di Nezio, 2014: The South Pacific meridional mode: A mechanism for ENSO-like variability. J. Climate, 27, 769783, https://doi.org/10.1175/JCLI-D-13-00082.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, M., H. H. Hendon, O. Alves, G. Liu, and G. Wang, 2016: Weakened eastern Pacific El Niño predictability in the early twenty-first century. J. Climate, 29, 68056822, https://doi.org/10.1175/JCLI-D-15-0876.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Warming Patterns Affect El Niño Diversity in CMIP5 and CMIP6 Models

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  • 1 CSIRO Agriculture and Food, Melbourne, and School of Earth Sciences, University of Melbourne, and Climate and Energy College, University of Melbourne, Parkville, Victoria, Australia
  • | 2 School of Earth Sciences, University of Melbourne, and ARC Centre of Excellence for Climate Extremes, University of Melbourne, Parkville, Victoria, Australia
  • | 3 School of Earth, Atmosphere and Environment, Monash University, Clayton, and School of Earth Sciences, University of Melbourne, and ARC Centre of Excellence for Climate Extremes, University of Melbourne, Parkville, Victoria, Australia
  • | 4 National Environmental Science Programme, Earth Systems and Climate Change Hub, CSIRO, Aspendale, Victoria, Australia
  • | 5 CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
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Abstract

Given the consequences and global significance of El Niño–Southern Oscillation (ENSO) events it is essential to understand the representation of El Niño diversity in climate models for the present day and the future. In recent decades, El Niño events have occurred more frequently in the central Pacific (CP). Eastern Pacific (EP) El Niño events have increased in intensity. However, the processes and future implications of these observed changes in El Niño are not well understood. Here, the frequency and intensity of El Niño events are assessed in models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6), and results are compared to extended instrumental and multicentury paleoclimate records. Future changes of El Niño are stronger for CP events than for EP events and differ between models. Models with a projected La Niña–like mean-state warming pattern show a tendency toward more EP but fewer CP events compared to models with an El Niño–like warming pattern. Among the models with more El Niño–like warming, differences in future El Niño can be partially explained by Pacific decadal variability (PDV). During positive PDV phases, more El Niño events occur, so future frequency changes are mainly determined by projected changes during positive PDV phases. Similarly, the intensity of El Niño is strongest during positive PDV phases. Future changes to El Niño may thus depend on both mean-state warming and decadal-scale natural variability.

Corresponding author: Mandy B. Freund, mandy.freund@csiro.au

Abstract

Given the consequences and global significance of El Niño–Southern Oscillation (ENSO) events it is essential to understand the representation of El Niño diversity in climate models for the present day and the future. In recent decades, El Niño events have occurred more frequently in the central Pacific (CP). Eastern Pacific (EP) El Niño events have increased in intensity. However, the processes and future implications of these observed changes in El Niño are not well understood. Here, the frequency and intensity of El Niño events are assessed in models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6), and results are compared to extended instrumental and multicentury paleoclimate records. Future changes of El Niño are stronger for CP events than for EP events and differ between models. Models with a projected La Niña–like mean-state warming pattern show a tendency toward more EP but fewer CP events compared to models with an El Niño–like warming pattern. Among the models with more El Niño–like warming, differences in future El Niño can be partially explained by Pacific decadal variability (PDV). During positive PDV phases, more El Niño events occur, so future frequency changes are mainly determined by projected changes during positive PDV phases. Similarly, the intensity of El Niño is strongest during positive PDV phases. Future changes to El Niño may thus depend on both mean-state warming and decadal-scale natural variability.

Corresponding author: Mandy B. Freund, mandy.freund@csiro.au
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