• Adler, R. F., and Coauthors, 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • An, S.-I., and B. Wang, 2000: Interdecadal change of the structure of the ENSO mode and its impact on the ENSO frequency. J. Climate, 13, 20442055, https://doi.org/10.1175/1520-0442(2000)013<2044:ICOTSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • An, S.-I., and F.-F. Jin, 2001: Collective role of thermocline and zonal advective feedbacks in the ENSO mode. J. Climate, 14, 34213432, https://doi.org/10.1175/1520-0442(2001)014<3421:CROTAZ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • An, S.-I., Y.-G. Ham, J.-S. Kug, F.-F. Jin, and I.-S. Kang, 2005: El Niño–La Niña asymmetry in the Coupled Model Intercomparison Project simulations. J. Climate, 18, 26172627, https://doi.org/10.1175/JCLI3433.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Battisti, D. S., and A. C. Hirst, 1989: Interannual variability in a tropical atmosphere–ocean model: Influence of the basic state, ocean geometry and nonlinearity. J. Atmos. Sci., 46, 16871712, https://doi.org/10.1175/1520-0469(1989)046<1687:IVIATA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bayr, T., M. Latif, D. Dommenget, C. Wengel, J. Harlaß, and W. Park, 2018: 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
  • Behringer, D. W., and Y. Xue, 2004: Evaluation of the global ocean data assimilation system at NCEP: The Pacific Ocean. Eighth Symp. on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, Seattle, WA, Amer. Meteor. Soc., 2.3, https://ams.confex.com/ams/pdfpapers/70720.pdf.

  • 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
  • Caldwell, P. M., and Coauthors, 2019: The DOE E3SM coupled model version 1: Description and results at high resolution. J. Adv. Model. Earth Syst., 11, 40954146, https://doi.org/10.1029/2019MS001870.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cane, M. A., and S. E. Zebiak, 1985: A theory for El Niño and the Southern Oscillation. Science, 228, 10851087, https://doi.org/10.1126/science.228.4703.1085.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Capotondi, A., A. Wittenberg, and S. Masina, 2006: Spatial and temporal structure of tropical Pacific interannual variability in 20th century coupled simulations. Ocean Modell., 15, 274298, https://doi.org/10.1016/j.ocemod.2006.02.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Capotondi, A., Y.-G. Ham, A. Wittenberg, and J.-S. Kug, 2015: Climate model biases and El Niño Southern Oscillation (ENSO) simulation. U.S. CLIVAR Variations, No. 13, U.S. International CLIVAR Project Office, Southampton, United Kingdom, 21–25.

  • Capotondi, A., A. T. Wittenberg, J.-S. Kug, K. Takahashi, and M. McPhaden, 2020a: ENSO diversity. El Niño Southern Oscillation in a Changing Climate, Amer. Geophys. Union, 65–86, https://doi.org/10.1002/9781119548164.ch4.

    • Crossref
    • Export Citation
  • Capotondi, A., C. Deser, A.S. Phillips, Y. Okumura, and S. M. Larson, 2020b: ENSO and Pacific decadal variability in the Community Earth System Model version 2. J. Adv. Model. Earth Syst., 12, e2019MS002022, https://doi.org/10.1029/2019MS002022.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carton, J. A., G. A. Chepurin, and L. Chen, 2018: SODA3: A new ocean climate reanalysis. J. Climate, 31, 69676983, https://doi.org/10.1175/JCLI-D-18-0149.1.

    • 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, H.-C., and F.-F. Jin, 2021: Simulations of ENSO phase-locking in CMIP5 and CMIP6. J. Climate, 34, 51355149, https://doi.org/10.1175/JCLI-D-20-0874.1.

    • Search Google Scholar
    • Export Citation
  • Choi, K.-Y., G. A. Vecchi, and A. T. Wittenberg, 2013: ENSO transition, duration, and amplitude asymmetries: Role of the nonlinear wind stress coupling in a conceptual model. J. Climate, 26, 94629476, https://doi.org/10.1175/JCLI-D-13-00045.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Choi, K.-Y., G. A. Vecchi, and A. T. Wittenberg, 2015: Nonlinear zonal wind response to ENSO in the CMIP5 models: Roles of the zonal and meridional shift of the ITCZ/SPCZ and the simulated climatological precipitation. J. Climate, 28, 85568573, https://doi.org/10.1175/JCLI-D-15-0211.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cox, M. D., 1980: Generation and propagation of 30-day waves in a numerical model of the Pacific. J. Phys. Oceanogr., 10, 11681186, https://doi.org/10.1175/1520-0485(1980)010<1168:GAPODW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cravatte, S., W. S. Kessler, N. Smith, and S. E. Wijffels, 2016: First report of TPOS 2020. GOOS-215, 200 pp., http://tpos2020.org/first-report/.

    • Search Google Scholar
    • Export Citation
  • Danabasoglu, G., and Coauthors, 2020: The Community Earth System Model Version 2 (CESM2). J. Adv. Model. Earth Syst., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916.

    • Crossref
    • Export Citation
  • DiNezio, P. N., B. P. Kirtman, A. C. Clement, S. Lee, G. A. Vecchi, and A. Wittenberg, 2012: Mean climate controls on the simulated response of ENSO to increasing greenhouse gases. J. Climate, 25, 73997420, https://doi.org/10.1175/JCLI-D-11-00494.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, H., M. Newman, M. A. Alexander, and A. T. Wittenberg, 2020: Relating CMIP5 model biases to seasonal forecast skill in the tropical Pacific. Geophys. Res. Lett., 47, e2019GL086765, https://doi.org/10.1029/2019GL086765.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eisenman, I., L. Yu, and E. Tziperman, 2005: Westerly wind bursts: ENSO’s tail rather than the dog? J. Climate, 18, 52245238, https://doi.org/10.1175/JCLI3588.1.

    • 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
  • Gebbie, G., I. Eisenman, A. Wittenberg, and E. Tziperman, 2007: Modulation of westerly wind bursts by sea surface temperature: A semistochastic feedback for ENSO. J. Atmos. Sci., 64, 32813295, https://doi.org/10.1175/JAS4029.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giese, B. S., and S. Ray, 2011: El Niño variability in Simple Ocean Data Assimilation (SODA), 1871–2008. J. Geophys. Res., 116, C02024, https://doi.org/10.1029/2010JC006695.

    • Search Google Scholar
    • Export Citation
  • Golaz, J. C., and Coauthors, 2019: The DOE E3SM Coupled Model version 1: Overview and evaluation at standard resolution. J. Adv. Model. Earth Syst., 11, 20892129, https://doi.org/10.1029/2018MS001603.

    • 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
  • Griffies, S. M., and Coatuhors, 2015: Impacts on ocean heat from transient mesoscale eddies in a hierarchy of climate models. J. Climate, 28, 952977, https://doi.org/10.1175/JCLI-D-14-00353.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guilyardi, E., A. Wittenberg, A. Fedorov, M. Collins, C. Wang, A. Capotondi, G. J. van Oldenborgh, and T. Stockdale, 2009: Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bull. Amer. Meteor. Soc., 90, 325340, https://doi.org/10.1175/2008BAMS2387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guilyardi, E., H. Bellenger, M. Collins, S. Ferrett, W. Cai, and A. Wittenberg, 2012: A first look at ENSO in CMIP5. CLIVAR Exchanges, No. 58, International CLIVAR Project Office, Southampton, United Kingdom, 29–32.

  • Guilyardi, E., A. Capotondi, M. Lengaigne, S. Thual, and A. T. Wittenberg, 2020: ENSO modeling: History, progress, and challenges. El Niño Southern Oscillation in a Changing Climate, Amer. Geophys. Union, 201–226, https://doi.org/10.1002/9781119548164.ch9.

    • Crossref
    • Export Citation
  • Ham, Y.-G., and J.-S. Kug, 2012: 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., and J.-S. Kug, 2015: Improvement of ENSO simulation based on intermodel diversity. J. Climate, 28, 9981015, https://doi.org/10.1175/JCLI-D-14-00376.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hansen, D., and C. A. Paul, 1984: Genesis and effects of long waves in the equatorial Pacific. J. Geophys. Res., 89, 10431, https://doi.org/10.1029/JC089iC06p10431.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hayashi, M., and F.-F. Jin, 2017: Subsurface nonlinear dynamical heating and ENSO asymmetry. Geophys. Res. Lett., 44, 12 42712 435, https://doi.org/10.1002/2017GL075771.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hayashi, M., F.-F. Jin, and M. F. Stuecker, 2020: Dynamics for El Niño–La Niña asymmetry constrain equatorial-Pacific warming pattern. Nat. Commun., 11, 4230, https://doi.org/10.1038/s41467-020-17983-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • He, J., N. C. Johnson, G. A. Vecchi, B. Kirtman, A. T. Wittenberg, and S. Sturm, 2018: Precipitation sensitivity to local variations in tropical sea surface temperature. J. Climate, 31, 92259238, https://doi.org/10.1175/JCLI-D-18-0262.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Held, I. M., and Coauthors, 2019: Structure and performance of GFDL’s CM4.0 climate model. J. Adv. Model. Earth Syst., 11, 36913727, https://doi.org/10.1029/2019MS001829.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hendon, H. H., M. C. Wheeler, and C. Zhang, 2007: Seasonal dependence of the MJO–ENSO relationship. J. Climate, 20, 531543, https://doi.org/10.1175/JCLI4003.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

  • Izumo, T., J. Vialard, M. Lengaigne, and I. Suresh, 2020: Relevance of relative sea surface temperature for tropical rainfall interannual variability. Geophys. Res. Lett., 47, e2019GL086182, https://doi.org/10.1029/2019GL086182.

    • Crossref
    • Export Citation
  • Jiang, W., P. Huang, G. Huang, and J. Ying, 2021: Origins of the excessive westward extension of ENSO SST simulated in CMIP5 and CMIP6 models. J. Climate, 34, 28392851, https://doi.org/10.1175/JCLI-D-20-0551.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., 1997a: An equatorial ocean recharge paradigm for ENSO. Part I: Conceptual model. J. Atmos. Sci., 54, 811829, https://doi.org/10.1175/1520-0469(1997)054<0811:AEORPF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., 1997b: An equatorial ocean recharge paradigm for ENSO. Part II: A stripped-down coupled model. J. Atmos. Sci., 54, 830847, https://doi.org/10.1175/1520-0469(1997)054<0830:AEORPF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., and J. D. Neelin, 1993: Modes of interannual tropical ocean–atmosphere interaction—A unified view. Part I: Numerical results. J. Atmos. Sci., 50, 34773503, https://doi.org/10.1175/1520-0469(1993)050<3477:MOITOI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., S. T. Kim, and L. Bejarano, 2006: A coupled-stability index for ENSO. Geophys. Res. Lett., 33, L23708, https://doi.org/10.1029/2006GL027221.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, F.-F., H.-C. Chen, S. Zhao, M. Hayashi, C. Karamperidou, M. F. Stuecker, R. Xie, and L. Geng, 2020: Simple ENSO models. El Niño Southern Oscillation in a Changing Climate, Amer. Geophys. Union, 119–151, https://doi.org/10.1002/9781119548164.ch6.

    • Crossref
    • Export Citation
  • Johnson, N., and S.-P. Xie, 2010: Changes in the sea surface temperature threshold for tropical convection. Nat. Geosci., 3, 842845, https://doi.org/10.1038/ngeo1008.

    • 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
  • Kessler, W. S., 2001: EOF representations of the Madden–Julian oscillation and its connection with ENSO. J. Climate, 14, 30553061, https://doi.org/10.1175/1520-0442(2001)014<3055:EROTMJ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kessler, W. S., M. J. McPhaden, and K. M. Weickmann, 1995: Forcing of intraseasonal Kelvin waves in the equatorial Pacific. J. Geophys. Res., 100, 10613, https://doi.org/10.1029/95JC00382.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kessler, W. S., and Coauthors, 2019: Second Report of TPOS 2020. GOOS-234, 265 pp., http://tpos2020.org/second-report/.

  • Kim, D., J.-S. Kug, I.-S. Kang, F.-F. Jin, and A. T. Wittenberg, 2008: Tropical Pacific impacts of convective momentum transport in the SNU coupled GCM. Climate Dyn., 31, 213226, https://doi.org/10.1007/s00382-007-0348-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, S. T., and F.-F. Jin, 2011: An ENSO stability analysis. Part II: Results from the twentieth and twenty-first century simulations of the CMIP3 models. Climate Dyn., 36, 16091627, https://doi.org/10.1007/s00382-010-0872-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, S. T., W. Cai, F.-F. Jin, and J.-Y. Yu, 2014: ENSO stability in coupled climate models and its association with mean state. Climate Dyn., 42, 33133321, https://doi.org/10.1007/s00382-013-1833-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirtman, B. P., 1997: Oceanic Rossby wave dynamics and the ENSO period in a coupled model. J. Climate, 10, 16901704, https://doi.org/10.1175/1520-0442(1997)010<1690:ORWDAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kleeman, R., and A. M. Moore, 1997: A theory for the limitation of ENSO predictability due to stochastic atmospheric transients. J. Atmos. Sci., 54, 753767, https://doi.org/10.1175/1520-0469(1997)054<0753:ATFTLO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kug, J.-S., K. P. Sooraj, D. Kim, I.-S. Kang, F.-F. Jin, Y. N. Takayabu, and M. Kimoto, 2009: Simulation of state-dependent high-frequency atmospheric variability associated with ENSO. Climate Dyn., 32, 635648, https://doi.org/10.1007/s00382-008-0434-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kug, J.-S., Y.-G. Ham, J.-Y. Lee, and F.-F. Jin, 2012: Improved simulation of two types of El Niño in CMIP5 models. Environ. Res. Lett., 7, 034002, https://doi.org/10.1088/1748-9326/7/3/034002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leloup, J., M. Lengaigne, and J. P. Boulanger, 2008: Twentieth century ENSO characteristics in the IPCC database. Climate Dyn., 30, 277291, https://doi.org/10.1007/s00382-007-0284-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lengaigne, M., E. Guilyardi, J. P. Boulanger, C. Menkes, P. Delecluse, P. Inness, J. Cole, and J. Slingo, 2004: Triggering of El Niño by westerly wind events in a coupled general circulation model. Climate Dyn., 23, 601620, https://doi.org/10.1007/s00382-004-0457-2.

    • 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
  • Lloyd, J., E. Guilyardi, H. Weller, and J. Slingo, 2012: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: The shortwave flux feedback. J. Climate, 25, 42754293, https://doi.org/10.1175/JCLI-D-11-00178.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lu, B., F. F. Jin, and H. L. Ren, 2018: A coupled dynamic index for ENSO periodicity. J. Climate, 31, 23612376, https://doi.org/10.1175/JCLI-D-17-0466.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McPhaden, M. J., 2004: Evolution of the 2002/03 El Niño. Bull. Amer. Meteor. Soc., 85, 677696, https://doi.org/10.1175/BAMS-85-5-677.

  • Moore, A. M., and R. Kleeman, 1999: Stochastic forcing of ENSO by the intraseasonal oscillation. J. Climate, 12, 11991220, https://doi.org/10.1175/1520-0442(1999)012<1199:SFOEBT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neelin, J. D., M. Latif, and F.-F. Jin, 1994: Dynamics of coupled ocean–atmosphere models: The tropical problem. Annu. Rev. Fluid Mech., 26, 617659, https://doi.org/10.1146/annurev.fl.26.010194.003153.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neelin, J. D., D. S. Battisti, A. C. Hirst, F.-F. Jin, Y. Wakata, T. Yamagata, and S. E. Zebiak, 1998: ENSO theory. J. Geophys. Res. Oceans, 103, 14 26114 290, https://doi.org/10.1029/97JC03424.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Perigaud, C. M., and C. Cassou, 2000: Importance of oceanic decadal trends and westerly wind bursts for forecasting El Niño. Geophys. Res. Lett., 27, 389392, https://doi.org/10.1029/1999GL010781.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Philander, S. G. H., 1978: Instabilities of zonal equatorial currents, 2. J. Geophys. Res., 83, 3679, https://doi.org/10.1029/JC083iC07p03679.

  • Philander, S. G. H., 1990: El Niño, La Niña, and the Southern Oscillation. International Geophysics Series, Vol. 46, Academic Press, 293 pp.

  • Planton, Y. Y., and Coauthors, 2021: Evaluating climate models with the CLIVAR 2020 ENSO metrics package. Bull. Amer. Meteor. Soc., 102, E193E217, https://doi.org/10.1175/BAMS-D-19-0337.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rasch, P. J., and Coauthors, 2019: An overview of the atmospheric component of the Energy Exascale Earth System Model. J. Adv. Model. Earth Syst., 11, 23772411, https://doi.org/10.1029/2019MS001629.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ray, S., A. T. Wittenberg, S. M. Griffies, and F. Zeng, 2018: Understanding the equatorial Pacific cold tongue time-mean heat budget. Part II: Evaluation of the GFDL-FLOR coupled GCM. J. Climate, 31, 998710 011, https://doi.org/10.1175/JCLI-D-18-0153.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Siongco, A. C., H. Ma, S. A. Klein, S. Xie, A. R. Karspeck, K. Raeder, and J. L. Anderson, 2020: A hindcast approach to diagnosing the equatorial Pacific cold tongue SST bias in CESM1. J. Climate, 33, 14371453, https://doi.org/10.1175/JCLI-D-19-0513.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sooraj, K. P., D. Kim, J.-S. Kug, S.-W. Yeh, F.-F. Jin, and I.-S. Kang, 2009: Effects of the low-frequency zonal wind variation on the high frequency atmospheric variability over the tropics. Climate Dyn., 33, 495507, https://doi.org/10.1007/s00382-008-0483-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevenson, S., A. T. Wittenberg, J. Fasullo, S. Coats, and B. Otto-Bliesner, 2021: Understanding diverse model projections of future extreme El Niño. J. Climate, 34, 449464, https://doi.org/10.1175/JCLI-D-19-0969.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Suarez, M. J., and P. S. Schopf, 1988: A delayed action oscillator for ENSO. J. Atmos. Sci., 45, 32833287, https://doi.org/10.1175/1520-0469(1988)045<3283:ADAOFE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, Y., F. Wang, and D. Z. Sun, 2016: Weak ENSO asymmetry due to weak nonlinear air–sea interaction in CMIP5 climate models. Adv. Atmos. Sci., 33, 352364, https://doi.org/10.1007/s00376-015-5018-6.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vijayeta, A., and D. Dommenget, 2018: An evaluation of ENSO dynamics in CMIP simulations in the framework of the recharge oscillator model. Climate Dyn., 51, 17531771, https://doi.org/10.1007/s00382-017-3981-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., and J. Picaut, 2004: Understanding ENSO physics—A review. Earth’s Climate: The Ocean–Atmosphere Interaction, Geophys. Monogr., Vol. 147, Amer. Geophys. Union, 21–48.

    • Crossref
    • Export Citation
  • Wilson, D., and A. Leetmaa, 1988: Acoustic Doppler current profiling in the equatorial Pacific in 1984. J. Geophys. Res., 93, 13947, https://doi.org/10.1029/JC093iC11p13947.

    • 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
  • Wittenberg, A. T., and Coauthors, 2018: Improved simulations of tropical Pacific annual-mean climate in the GFDL FLOR and HiFLOR coupled GCMs. J. Adv. Model. Earth Syst., 10, 31763220, https://doi.org/10.1029/2018MS001372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, S., and Coauthors, 2018: Understanding cloud and convective characteristics in version 1 of the E3SM atmosphere model. J. Adv. Model. Earth Syst., 10, 26182644, https://doi.org/10.1029/2018MS001350.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, A., F.-F. Jin, W. Zhang, J. Boucharel, S. Zhao, and X. Yuan, 2020: Delineating the seasonally modulated nonlinear feedback onto ENSO from tropical instability waves. Geophys. Res. Lett., 47, e2019GL085863, https://doi.org/10.1029/2019GL085863.

    • Crossref
    • Export Citation
  • Yu, J.-Y., and S. T. Kim, 2010: Relationships between extratropical sea level pressure variations and the central Pacific and eastern Pacific types of ENSO. J. Climate, 24, 708720, https://doi.org/10.1175/2010JCLI3688.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, L., R. A. Weller, and W. T. Liu, 2003: Case analysis of a role of ENSO in regulating the generation of westerly wind bursts in the western equatorial Pacific. J. Geophys. Res., 108, 3128, https://doi.org/10.1029/2002JC001498.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, Z. J., J. P. McCreary, and J. A. Proehl, 1995: Meridional asymmetry and energetics of tropical instability waves. J. Phys. Oceanogr., 25, 29973007, https://doi.org/10.1175/1520-0485(1995)025<2997:MAAEOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zavala-Garay, J., C. Zhang, A. M. Moore, A. T. Wittenberg, M. J. Harrison, A. Rosati, J. Vialard, and R. Kleeman, 2008: Sensitivity of hybrid ENSO models to unresolved atmospheric variability. J. Climate, 21, 37043721, https://doi.org/10.1175/2007JCLI1188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, C., and J. Gottschalck, 2002: SST anomalies of ENSO and the Madden–Julian oscillation in the equatorial Pacific. J. Climate, 15, 24292445, https://doi.org/10.1175/1520-0442(2002)015<2429:SAOEAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, T., and D. Z. Sun, 2014: ENSO asymmetry in CMIP5 models. J. Climate, 27, 40704093, https://doi.org/10.1175/JCLI-D-13-00454.1.

  • Zuo, H., M. A. Balmaseda, S. Tietsche, K. Mogensen, and M. Mayer, 2019: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: A description of the system and assessment. Ocean Sci., 15, 779808, https://doi.org/10.5194/os-15-779-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
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ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models

Han-Ching ChenaDepartment of Atmospheric Sciences, University of Hawaiʻi at Mānoa, Honolulu, Hawaii

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Fei-Fei-JinaDepartment of Atmospheric Sciences, University of Hawaiʻi at Mānoa, Honolulu, Hawaii

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Sen ZhaoaDepartment of Atmospheric Sciences, University of Hawaiʻi at Mānoa, Honolulu, Hawaii
bCIC-FEMD/ILCEC, Key Laboratory of Meteorological Disaster of Ministry of Education, and College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China

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Andrew T. WittenbergcNOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Shaocheng XiedLawrence Livermore National Laboratory, Livermore, California

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Abstract

This study examines historical simulations of ENSO in the E3SM-1-0, CESM2, and GFDL-CM4 climate models, provided by three leading U.S. modeling centers as part of the Coupled Model Intercomparison Project phase 6 (CMIP6). These new models have made substantial progress in simulating ENSO’s key features, including amplitude, time scale, spatial patterns, phase-locking, the spring persistence barrier, and recharge oscillator dynamics. However, some important features of ENSO are still a challenge to simulate. In the central and eastern equatorial Pacific, the models’ weaker-than-observed subsurface zonal current anomalies and zonal temperature gradient anomalies serve to weaken the nonlinear zonal advection of subsurface temperatures, leading to insufficient warm/cold asymmetry of ENSO’s sea surface temperature anomalies (SSTA). In the western equatorial Pacific, the models’ excessive simulated zonal SST gradients amplify their zonal temperature advection, causing their SSTA to extend farther west than observed. The models underestimate both ENSO’s positive dynamic feedbacks (due to insufficient zonal wind stress responses to SSTA) and its thermodynamic damping (due to insufficient convective cloud shading of eastern Pacific SSTA during warm events); compensation between these biases leads to realistic linear growth rates for ENSO, but for somewhat unrealistic reasons. The models also exhibit stronger-than-observed feedbacks onto eastern equatorial Pacific SSTAs from thermocline depth anomalies, which accelerates the transitions between events and shortens the simulated ENSO period relative to observations. Implications for diagnosing and simulating ENSO in climate models are discussed.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fei-Fei Jin, jff@hawaii.edu

Abstract

This study examines historical simulations of ENSO in the E3SM-1-0, CESM2, and GFDL-CM4 climate models, provided by three leading U.S. modeling centers as part of the Coupled Model Intercomparison Project phase 6 (CMIP6). These new models have made substantial progress in simulating ENSO’s key features, including amplitude, time scale, spatial patterns, phase-locking, the spring persistence barrier, and recharge oscillator dynamics. However, some important features of ENSO are still a challenge to simulate. In the central and eastern equatorial Pacific, the models’ weaker-than-observed subsurface zonal current anomalies and zonal temperature gradient anomalies serve to weaken the nonlinear zonal advection of subsurface temperatures, leading to insufficient warm/cold asymmetry of ENSO’s sea surface temperature anomalies (SSTA). In the western equatorial Pacific, the models’ excessive simulated zonal SST gradients amplify their zonal temperature advection, causing their SSTA to extend farther west than observed. The models underestimate both ENSO’s positive dynamic feedbacks (due to insufficient zonal wind stress responses to SSTA) and its thermodynamic damping (due to insufficient convective cloud shading of eastern Pacific SSTA during warm events); compensation between these biases leads to realistic linear growth rates for ENSO, but for somewhat unrealistic reasons. The models also exhibit stronger-than-observed feedbacks onto eastern equatorial Pacific SSTAs from thermocline depth anomalies, which accelerates the transitions between events and shortens the simulated ENSO period relative to observations. Implications for diagnosing and simulating ENSO in climate models are discussed.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fei-Fei Jin, jff@hawaii.edu

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