Extreme El Niño and La Niña events more common under future climate scenarios

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The frequency of extreme El Niño and La Niña events is expected to increase under future greenhouse warming, according to Australian scientists who have reviewed the latest data. They say extreme El Niño and La Niña events are both projected to increase from 5.6 events per century in the present day to 8.9 and 8.3 events per century in the future climate, respectively. 

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conference:
Nature Reviews Earth & Environment
Research:Paper
Organisation/s: CSIRO, The University of New South Wales, The University of Melbourne, Monash University
Funder: This work is supported by the Strategic Priority Research Program of the Chinese Academy of Sciences, grant no. XDB40000000. W.C., A.S., B.N. and G.W. are supported by the Centre for Southern Hemisphere Oceans Research (CSHOR), a joint research facility between Qingdao National Laboratory for Marine Science and Technology (QNLM) and Commonwealth Scientific and Industrial Research Organisation (CSIRO), and the Earth System and Climate Change Hub of the Australian Government’s National Environment Science Program. M.F.S. was supported by the NOAA’s Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) Program grant NA20OAR4310445 and participates in the MAPP Marine Ecosystem Task Force. This is Pacific Marine Environmental Laboratory (PMEL) contribution number 5213. M.L. is supported by the ARISE ANR (Agence Nationale pour la Recherche) project (ANR-18-CE01-0012). X. Lin is supported by the National Natural Science Foundation of China (41925025 and 92058203). B.G. was supported by the National Natural Science Foundation of China (41922039). A.C. is supported by the NOAA’s Climate Program Office Climate Variability and Predictability (CVP) and MAPP programs. M.C. was supported by NERC grant NE/S004645/1. This is IPRC publication 1525 and SOEST contribution 11356. A.S.T. is supported by the Australian Research Council (ARC FT160100495). S.-W.Y. is funded by the Korean Meteorological Administration Research and Development Program under grant (KMI2020-01213). Y.Y. is supported by the National Natural Science Foundation of China (NSFC) project (grant no. 41976005). X. Li is supported by National Key R&D Program of China (2018YFA0605703) and the National Natural Science Foundation of China (grant 41976193). M.C. is supported by NERC grant NE/S004645/1. T.B. is funded by Deutsche Forschungsgemeinschaft (DFG) project “Influence of Model Bias on ENSO Projections of the 21st Century” through grant 429334714. C.K. is supported by US NSF award AGS- 1902970. J.R.B. acknowledges support from the ARC Centre of Excellence for Climate Extremes (CE170100023). J.Y. is supported by the National Natural Science Foundation of China (grants 41690121 and 41690120). A.T. was supported by the Institute for Basic Science (IBS-R028-D1). S.M. acknowledges support from the Australian Research Council through grant number Ft160100162. J.-S.K. is supported by the National Research Foundation of Korea (NRF- 2018R1A5A1024958). X.-T.Z. is funded by the National Natural Science Foundation of China (41975092). B.D. acknowledges support from Fondecyt (grant 1190276) and ANR (grant ANR-18-CE01-0012). We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. PMIP is endorsed by both WCRP/WGCM and Future Earth/PAGES.
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