Publications des scientifiques de l'IRD

Planton Y. Y., Guilyardi E., Wittenberg A. T., Lee J., Gleckler P. J., Bayr T., McGregor S., McPhaden M. J., Power S., Roehrig R., Vialard Jérôme, Voldoire A. (2021). Evaluating climate models with the CLIVAR 2020 ENSO metrics package. Bulletin of the American Meteorological Society, 102 (2), p. E193-E217. ISSN 0003-0007.

Titre du document
Evaluating climate models with the CLIVAR 2020 ENSO metrics package
Année de publication
2021
Type de document
Article référencé dans le Web of Science WOS:000646826000001
Auteurs
Planton Y. Y., Guilyardi E., Wittenberg A. T., Lee J., Gleckler P. J., Bayr T., McGregor S., McPhaden M. J., Power S., Roehrig R., Vialard Jérôme, Voldoire A.
Source
Bulletin of the American Meteorological Society, 2021, 102 (2), p. E193-E217 ISSN 0003-0007
El Nino-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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Limnologie physique / Océanographie physique [032]
Localisation
Fonds IRD [F B010081458]
Identifiant IRD
fdi:010081458
Contact