Evaluating Climate Models with the CLIVAR 2020 ENSO Metrics Package

Yann Y. Planton LOCEAN-IPSL, CNRS-IRD-MNHN-Sorbonne Université, Paris, France

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Eric Guilyardi LOCEAN-IPSL, CNRS-IRD-MNHN-Sorbonne Université, Paris, France, and National Centre for Atmospheric Science—Climate, University of Reading, Reading, United Kingdom

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

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Jiwoo Lee Lawrence Livermore National Laboratory, Livermore, California

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Peter J. Gleckler Lawrence Livermore National Laboratory, Livermore, California

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Tobias Bayr GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany

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Shayne McGregor School of Earth, Atmosphere and Environment, Monash University, Clayton, Victoria, Australia

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Michael J. McPhaden NOAA/Pacific Marine Environmental Laboratory, Seattle, Washington

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Scott Power School of Earth, Atmosphere and Environment, Monash University, Clayton, and Australian Bureau of Meteorology, Melbourne, Victoria, Australia

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Romain Roehrig CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Jérôme Vialard LOCEAN-IPSL, CNRS-IRD-MNHN-Sorbonne Université, Paris, France

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Aurore Voldoire CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Abstract

El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.

CURRENT AFFILIATION: NOAA/Pacific Marine Environmental Laboratory, Seattle, Washington

Supplemental material: https://doi.org/10.1175/BAMS-D-19-0337.2

© 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: Yann Y. Planton, yann.planton@noaa.gov

Abstract

El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.

CURRENT AFFILIATION: NOAA/Pacific Marine Environmental Laboratory, Seattle, Washington

Supplemental material: https://doi.org/10.1175/BAMS-D-19-0337.2

© 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: Yann Y. Planton, yann.planton@noaa.gov

Supplementary Materials

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