A successful prediction of the record CO₂ rise associated with the 2015/2016 El Niño

In early 2016, we predicted that the annual rise in carbon dioxide concentration at Mauna Loa would be the largest on record. Our forecast used a statistical relationship between observed and forecast sea surface temperatures in the Niño 3.4 region and the annual CO₂ rise. Here, we provide a formal...

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Published in:Philosophical transactions of the Royal Society of London. Series B. Biological sciences 2018-10, Vol.373 (1760), p.1-11
Main Authors: Betts, Richard A., Jones, Chris D., Knight, Jeff. R., Keeling, Ralph. F., Kennedy, John. J., Wiltshire, Andrew J., Andrew, Robbie M., Aragão, Luiz E. O. C.
Format: Article
Language:eng
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Summary:In early 2016, we predicted that the annual rise in carbon dioxide concentration at Mauna Loa would be the largest on record. Our forecast used a statistical relationship between observed and forecast sea surface temperatures in the Niño 3.4 region and the annual CO₂ rise. Here, we provide a formal verification of that forecast. The observed rise of 3.4 ppm relative to 2015 was within the forecast range of 3.15±0.53 ppm, so the prediction was successful. A global terrestrial biosphere model supports the expectation that the El Niño weakened the tropical land carbon sink. We estimate that the El Niño contributed approximately 25% to the record rise in CO₂, with 75% due to anthropogenic emissions. The 2015/2016 CO₂ rise was greater than that following the previous large El Niño in 1997/1998, because anthropogenic emissions had increased. We had also correctly predicted that 2016 would be the first year with monthly mean CO₂ above 400 ppm all year round. We now estimate that atmospheric CO₂ at Mauna Loa would have remained above 400 ppm all year round in 2016 even if the El Niño had not occurred, contrary to our previous expectations based on a simple extrapolation of previous trends. This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.
ISSN:0962-8436
1471-2970