Understanding Diverse Model Projections of Future Extreme El Niño

Samantha Stevenson Bren School of Environmental Sciences and Management, University of California at Santa Barbara, Santa Barbara, California

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Andrew T. Wittenberg NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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John Fasullo Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado

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Sloan Coats Department of Earth Sciences, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Bette Otto-Bliesner Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado

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Abstract

The majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day−1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. These competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.

© 2020 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: Samantha Stevenson, stevenson@bren.ucsb.edu

Abstract

The majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day−1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. These competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.

© 2020 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: Samantha Stevenson, stevenson@bren.ucsb.edu
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  • Ainsworth, T. D., S. F. Heron, J. C. Ortiz, P. J. Mumby, A. Grech, D. Ogawa, C. M. Eakin, and M. Leggat, 2016: Climate change disables coral bleaching protection on the Great Barrier Reef. Science, 352, 338342, https://doi.org/10.1126/science.aac7125.

    • 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
  • Bonfils, C. J. W., B. D. Santer, T. J. Phillips, K. Marvel, L. R. Leung, C. Doutriaux, and A. Capotondi, 2015: Relative contributions of mean-state shifts and ENSO-driven variability to precipitation changes in a warming climate. J. Climate, 28, 999710 013, https://doi.org/10.1175/JCLI-D-15-0341.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cai, W., and Coauthors, 2014: Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Climate Change, 4, 111116, https://doi.org/10.1038/nclimate2100.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cai, W., and Coauthors, 2015: Increased frequency of extreme La Niña events due to greenhouse warming. Nat. Climate Change, 5, 132137, https://doi.org/10.1038/nclimate2492.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cai, W., G. Wang, A. Santoso, X. Lin, and L. Wu, 2017: Definition of extreme El Niño and its impact on projected increase in extreme El Niño frequency. Geophys. Res. Lett., 44, 11 18411 190, https://doi.org/10.1002/2017GL075635.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Capotondi, A., and Coauthors, 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
  • Ceppi, P., F. Brient, M. D. Zelinka, and D. L. Hartmann, 2017: Cloud feedback mechanisms and their representation in global climate models. Wiley Interdiscip. Rev.: Climate Change, 8, e465, https://doi.org/10.1002/wcc.465.

    • 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
  • 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
  • Chung, E.-S., A. Timmermann, B. J. Soden, K.-J. Ha, L. Shi, and V. O. John, 2019: Reconciling opposing Walker circulation trends in observations and model projections. Nat. Climate Change, 9, 405412, https://doi.org/10.1038/s41558-019-0446-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, M., and Coauthors, 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
  • Deser, C., L. Terray, and A. S. Phillips, 2016: Forced and internal components of winter air temperature trends over North American during the past 50 years: Mechanisms and implications. J. Climate, 29, 22372258, https://doi.org/10.1175/JCLI-D-15-0304.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., and Coauthors, 2020: Insights from Earth system model initial-condition large ensembles and future prospects. Nat. Climate Change, 10, 277286, https://doi.org/10.1038/s41558-020-0731-2

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Di Lorenzo, E., and N. Mantua, 2016: Multi-year persistence of the 2014/15 North Pacific marine heatwave. Nat. Climate Change, 6, 10421047, https://doi.org/10.1038/nclimate3082.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DiNezio, P., B. Kirtman, A. Clement, S.-K. Lee, G. 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
  • Dunne, J. P., and Coauthors, 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
  • Fasullo, J. T., B. L. Otto-Bliesner, and S. Stevenson, 2018: ENSO’s changing influence on temperature, precipitation, and wildfire in a warming climate. Geophys. Res. Lett., 45, 92169225, https://doi.org/10.1029/2018GL079022.

    • 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
  • Guilyardi, E., P. Braconnot, F.-F. Jin, S.-T. Kim, M. Kolaskinski, T. Li, and A. Musat, 2009a: Atmosphere feedbacks during ENSO in a coupled GCM with a modified atmospheric convection scheme. J. Climate, 22, 56985718, https://doi.org/10.1175/2009JCLI2815.1.

    • 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, 2009b: 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., W. Cai, M. Collins, A. Fedorov, F.-F. Jin, A. Kumar, D.-Z. Sun, and A. Wittenberg, 2012: New strategies for evaluating ENSO processes in climate models. Bull. Amer. Meteor. Soc., 93, 235238, https://doi.org/10.1175/BAMS-D-11-00106.1.

    • 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., and B. 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
  • Hoegh-Guldberg, O., 1999: Climate change, coral bleaching and the future of the world’s coral reefs. Mar. Freshwater Res., 50, 839866, https://doi.org/10.1071/MF99078.

    • Search Google Scholar
    • Export Citation
  • Huang, B., and Coauthors, 2016: Further exploring and quantifying uncertainties for Extended Reconstructed Sea Surface Temperature (ERSST) version 4 (v4). J. Climate, 29, 31193142, https://doi.org/10.1175/JCLI-D-15-0430.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, P., 2016: Time-varying response of ENSO-induced tropical Pacific rainfall to global warming in CMIP5 models. Part I: Multimodel ensemble results. J. Climate, 29, 57635778, https://doi.org/10.1175/JCLI-D-16-0058.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, P., 2017: Time-varying response of ENSO-induced tropical Pacific rainfall to global warming in CMIP5 models. Part II: Intermodel uncertainty. J. Climate, 30, 595608, https://doi.org/10.1175/JCLI-D-16-0373.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, P., and S. Xie, 2015: Mechanisms of change in ENSO-induced tropical Pacific rainfall variability in a warming climate. Nature Geosci., 8, 922926, https://doi.org/10.1038/ngeo2571.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kay, J. E., and Coauthors, 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. Amer. Meteor. Soc., 96, 13331349, https://doi.org/10.1175/BAMS-D-13-00255.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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
  • Power, S., F. Delage, C. Chung, G. Kociuba, and K. Keay, 2013: Robust twenty-first-century projections of El Niño and related precipitation variability. Nature, 502, 541545, https://doi.org/10.1038/nature12580.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., and W. Collins, 1991: Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351, 2732, https://doi.org/10.1038/351027a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodgers, K. B., J. Lin, and T. L. Frolicher, 2015: Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model. Biogeosciences, 12, 33013320, https://doi.org/10.5194/bg-12-3301-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ropelewski, C. F., and M. S. Halpert, 1986: North American Precipitation and Temperature patterns associated with the El Niño/Southern Oscillation (ENSO). Mon. Wea. Rev., 114, 23522362, https://doi.org/10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2.

    • 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
  • Stevenson, S., 2012: Significant changes to ENSO strength and impacts in the twenty-first century: Results from CMIP5. Geophys. Res. Lett., 39, L17703, https://doi.org/10.1029/2012GL052759

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevenson, S., B. Fox-Kemper, M. Jochum, B. Rajagopalan, and S. Yeager, 2010: ENSO model validation using wavelet probability analysis. J. Climate, 23, 55405547, https://doi.org/10.1175/2010JCLI3609.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevenson, S., B. Fox-Kemper, M. Jochum, R. Neale, C. Deser, and G. Meehl, 2012: Will there be a significant change to El Niño in the twenty-first century? J. Climate, 25, 21292145, https://doi.org/10.1175/JCLI-D-11-00252.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevenson, S., J. T. Fasullo, B. L. Otto-Bliesner, R. A. Tomas, and C. Gao, 2017: Role of eruption season in reconciling model and proxy responses to tropical volcanism. Proc. Natl. Acad. Sci. USA, 114, 18221826, https://doi.org/10.1073/pnas.1612505114.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stuecker, M. F., and Coauthors, 2020: Strong remote control of future equatorial warming by off-equatorial forcing. Nat. Climate Change, 10, 124129, https://doi.org/10.1038/s41558-019-0667-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2009: A summary of the CMIP5 experimental design. CLIVAR Rep., 32 pp., www.clivar.org/organization/wgcm/references/Taylor_CMIP5.pdf.

  • 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
  • Vecchi, G., and B. Soden, 2007: Global warming and the weakening of the tropical circulation. J. Climate, 20, 43164340, https://doi.org/10.1175/JCLI4258.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G., and A. Wittenberg, 2010: El Niño and our future climate: Where do we stand? Wiley Interdiscip. Rev.: Climate Change, 1, 260270, https://doi.org/10.1002/wcc.33.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and A. T. Wittenberg, 2012: A method for disentangling El Niño–mean state interaction. Geophys. Res. Lett., 39, L14702, https://doi.org/10.1029/2012GL052013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, M., J.-S. Kug, F.-F. Jin, M. Collins, M. Ohba, and A. T. Wittenberg, 2012: Uncertainty in the ENSO amplitude change from the past to the future. Geophys. Res. Lett., 39, L20703, https://doi.org/10.1029/2012GL053305.

    • 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, T. L. Delworth, G. A. Vecchi, and F. Zeng, 2014: ENSO modulation: Is it decadally predictable? J. Climate, 27, 26672681, https://doi.org/10.1175/JCLI-D-13-00577.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., C. Deser, G. Vecchi, J. Ma, H. Teng, and A. Wittenberg, 2010: Global warming pattern formation: Sea surface temperature and rainfall. J. Climate, 23, 966986, https://doi.org/10.1175/2009JCLI3329.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ying, J., and P. Huang, 2016: Cloud–radiation feedback as a leading source of uncertainty in the tropical Pacific SST warming pattern in CMIP5 models. J. Climate, 29, 38673881, https://doi.org/10.1175/JCLI-D-15-0796.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zheng, X.-T., S.-P. Xie, L.-H. Lv, and Z.-Q. Zhou, 2016: Intermodel uncertainty in ENSO amplitude change tied to Pacific Ocean warming pattern. J. Climate, 29, 72657279, https://doi.org/10.1175/JCLI-D-16-0039.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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