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Response of El Niño sea surface temperature variability to greenhouse warming

Kim, S. T., Cai, W., Jin, F.-F., Santoso, A., Wu, L., Guilyardi, E. ORCID: https://orcid.org/0000-0002-2255-8625 and An, S.-I. (2014) Response of El Niño sea surface temperature variability to greenhouse warming. Nature Climate Change, 4 (9). pp. 786-790. ISSN 1758-6798

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To link to this item DOI: 10.1038/nclimate2326

Abstract/Summary

The destructive environmental and socio-economic impacts of the El Niño/Southern Oscillation1, 2 (ENSO) demand an improved understanding of how ENSO will change under future greenhouse warming. Robust projected changes in certain aspects of ENSO have been recently established3, 4, 5. However, there is as yet no consensus on the change in the magnitude of the associated sea surface temperature (SST) variability6, 7, 8, commonly used to represent ENSO amplitude1, 6, despite its strong effects on marine ecosystems and rainfall worldwide1, 2, 3, 4, 9. Here we show that the response of ENSO SST amplitude is time-varying, with an increasing trend in ENSO amplitude before 2040, followed by a decreasing trend thereafter. We attribute the previous lack of consensus to an expectation that the trend in ENSO amplitude over the entire twenty-first century is unidirectional, and to unrealistic model dynamics of tropical Pacific SST variability. We examine these complex processes across 22 models in the Coupled Model Intercomparison Project phase 5 (CMIP5) database10, forced under historical and greenhouse warming conditions. The nine most realistic models identified show a strong consensus on the time-varying response and reveal that the non-unidirectional behaviour is linked to a longitudinal difference in the surface warming rate across the Indo-Pacific basin. Our results carry important implications for climate projections and climate adaptation pathways.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:51597
Publisher:Nature Publishing Group

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