Evaluating climate models with the CLIVAR 2020 ENSO Metrics Package
Article
Article Title | Evaluating climate models with the CLIVAR 2020 ENSO Metrics Package |
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ERA Journal ID | 1961 |
Article Category | Article |
Authors | Planton, Yann Y. (Author), Guilyardi, Eric (Author), Wittenberg, Andrew T. (Author), Lee, Jiwoo (Author), Gleckler, Peter J. (Author), Bayr, Tobias (Author), McGregor, Shayne (Author), McPhaden, Michael J. (Author), Power, Scott (Author), Roehrig, Romain (Author), Vialard, Jerome (Author) and Voldoire, Aurore (Author) |
Journal Title | Bulletin of the American Meteorological Society |
Journal Citation | 102 (2), pp. E193-E217 |
Number of Pages | 25 |
Year | 2021 |
Publisher | American Meteorological Society |
Place of Publication | Boston, MA, United States |
ISSN | 0003-0007 |
1520-0477 | |
Digital Object Identifier (DOI) | https://doi.org/10.1175/bams-d-19-0337.1 |
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. |
ANZSRC Field of Research 2020 | 370201. Climate change processes |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Sorbonne University, France |
National Oceanic and Atmospheric Administration, United States | |
Lawrence Livermore National Laboratory, United States | |
GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany | |
Monash University | |
University of Toulouse, France | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q66wv/evaluating-climate-models-with-the-clivar-2020-enso-metrics-package
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