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A metric for quantifying El Niño pattern diversity with implications for ENSO–mean state interaction

  • Danielle E. Lemmon
  • Kristopher B. Karnauskas
Article

Abstract

Recent research on the El Niño–Southern Oscillation (ENSO) phenomenon increasingly reveals the highly complex and diverse nature of ENSO variability. A method of quantifying ENSO spatial pattern uniqueness and diversity is presented, which enables (1) formally distinguishing between unique and “canonical” El Niño events, (2) testing whether historical model simulations aptly capture ENSO diversity by comparing with instrumental observations, (3) projecting future ENSO diversity using future model simulations, (4) understanding the dynamics that give rise to ENSO diversity, and (5) analyzing the associated diversity of ENSO-related atmospheric teleconnection patterns. Here we develop a framework for measuring El Niño spatial SST pattern uniqueness and diversity for a given set of El Niño events using two indices, the El Niño Pattern Uniqueness (EPU) index and El Niño Pattern Diversity (EPD) index, respectively. By applying this framework to instrumental records, we independently confirm a recent regime shift in El Niño pattern diversity with an increase in unique El Niño event sea surface temperature patterns. However, the same regime shift is not observed in historical CMIP5 model simulations; moreover, a comparison between historical and future CMIP5 model scenarios shows no robust change in future ENSO diversity. Finally, we support recent work that asserts a link between the background cooling of the eastern tropical Pacific and changes in ENSO diversity. This robust link between an eastern Pacific cooling mode and ENSO diversity is observed not only in instrumental reconstructions and reanalysis, but also in historical and future CMIP5 model simulations.

Notes

Acknowledgements

We acknowledge the WCRP Working Group on Coupled Modelling and U.S. DOE/PCMDI for CMIP, and thank the climate modeling groups for producing and making available their model output (http://cmip-pcmdi.llnl.gov/cmip5/). D.L. acknowledges support from the National Science Foundation Graduate Research Fellowship Program (GRFP). The authors are grateful for helpful conversations with Drs. Antonietta Capotondi, Balaji Rajagopalan and Jeffrey Weiss.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Danielle E. Lemmon
    • 1
    • 2
  • Kristopher B. Karnauskas
    • 1
    • 2
  1. 1.Department of Atmospheric and Oceanic SciencesUniversity of ColoradoBoulderUSA
  2. 2.Cooperative Institute for Research in Environmental SciencesUniversity of ColoradoBoulderUSA

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