Inter-basin sources for two-year predictability of the multi-year La Niña event in 2010–2012

Multi-year La Niña events often induce persistent cool and wet climate over global lands, altering and in some case mitigating regional climate warming impacts. The latest event lingered from mid-2010 to early 2012 and brought about intensive precipitation over many land regions of the world, partic...

Full description

Saved in:
Bibliographic Details
Published inScientific reports Vol. 7; no. 1; pp. 2276 - 7
Main Authors Luo, Jing-Jia, Liu, Guoqiang, Hendon, Harry, Alves, Oscar, Yamagata, Toshio
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 23.05.2017
Nature Publishing Group
Nature Portfolio
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Multi-year La Niña events often induce persistent cool and wet climate over global lands, altering and in some case mitigating regional climate warming impacts. The latest event lingered from mid-2010 to early 2012 and brought about intensive precipitation over many land regions of the world, particularly Australia. This resulted in a significant drop in global mean sea level despite the background upwards trend. This La Niña event is surprisingly predicted out to two years ahead in a few coupled models, even though the predictability of El Niño-Southern Oscillation during 2002–2014 has declined owing to weakened ocean-atmosphere interactions. However, the underlying mechanism for high predictability of this multi-year La Niña episode is still unclear. Experiments based on a climate model that demonstrates a successful two-year forecast of the La Niña support the hypothesis that warm sea surface temperature (SST) anomalies in the Atlantic and Indian Oceans act to intensify the easterly winds in the central equatorial Pacific and largely contribute to the occurrence and two-year predictability of the 2010–2012 La Niña. The results highlight the importance of increased Atlantic-Indian Ocean SSTs for the multi-year La Niña’s predictability under global warming.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-01479-9