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

ABSTRACT: 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'.

SUBMITTER: Betts RA

PROVIDER: S-EPMC6178439 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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A successful prediction of the record CO<sub>2</sub> rise associated with the 2015/2016 El Niño.

Betts Richard A RA Jones Chris D CD Knight Jeff R JR Keeling Ralph F RF Kennedy John J JJ Wiltshire Andrew J AJ Andrew Robbie M RM Aragão Luiz E O C LEOC

Philosophical transactions of the Royal Society of London. Series B, Biological sciences 20181008 1760

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 CO<sub>2</sub> 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 biosphe ...[more]

PMID: 30297462

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Project description:A substantial body of work supports a teleconnection between the El Niño-Southern Oscillation (ENSO) and cholera incidence in Bangladesh. In particular, high positive anomalies during the winter (Dec-Feb) in sea surface temperatures (SST) in the tropical Pacific have been shown to exacerbate the seasonal outbreak of cholera following the monsoons from August to November. Climate studies have indicated a role of regional precipitation over Bangladesh in mediating this long-distance effect. Motivated by this previous evidence, we took advantage of the strong 2015-2016 El Niño event to evaluate the predictability of cholera dynamics for the city in recent times based on two transmission models that incorporate SST anomalies and are fitted to the earlier surveillance records starting in 1995. We implemented a mechanistic temporal model that incorporates both epidemiological processes and the effect of ENSO, as well as a previously published statistical model that resolves space at the level of districts (thanas). Prediction accuracy was evaluated with "out-of-fit" data from the same surveillance efforts (post 2008 and 2010 for the two models respectively), by comparing the total number of cholera cases observed for the season to those predicted by model simulations eight to twelve months ahead, starting in January each year. Although forecasts were accurate for the low cholera risk observed for the years preceding the 2015-2016 El Niño, the models also predicted a high probability of observing a large outbreak in fall 2016. Observed cholera cases up to Oct 2016 did not show evidence of an anomalous season. We discuss these predictions in the context of regional and local climate conditions, which show that despite positive regional rainfall anomalies, rainfall and inundation in Dhaka remained low. Possible explanations for these patterns are given together with future implications for cholera dynamics and directions to improve their prediction for the city.

Project description:The El Niño-Southern Oscillation exerts a large influence on global climate regimes and on the global carbon cycle. Although El Niño is known to be associated with a reduction of the global total land carbon sink, results based on prognostic models or measurements disagree over the relative contribution of photosynthesis to the reduced sink. Here, we provide an independent remote sensing-based analysis on the impact of the 2015-2016 El Niño on global photosynthesis using six global satellite-based photosynthesis products and a global solar-induced fluorescence (SIF) dataset. An ensemble of satellite-based photosynthesis products showed a negative anomaly of -0.7 ± 1.2 PgC in 2015, but a slight positive anomaly of 0.05 ± 0.89 PgC in 2016, which when combined with observations of the growth rate of atmospheric carbon dioxide concentrations suggests that the reduction of the land residual sink was likely dominated by photosynthesis in 2015 but by respiration in 2016. The six satellite-based products unanimously identified a major photosynthesis reduction of -1.1 ± 0.52 PgC from savannahs in 2015 and 2016, followed by a highly uncertain reduction of -0.22 ± 0.98 PgC from rainforests. Vegetation in the Northern Hemisphere enhanced photosynthesis before and after the peak El Niño, especially in grasslands (0.33 ± 0.13 PgC). The patterns of satellite-based photosynthesis ensemble mean were corroborated by SIF, except in rainforests and South America, where the anomalies of satellite-based photosynthesis products also diverged the most. We found the inter-model variation of photosynthesis estimates was strongly related to the discrepancy between moisture forcings for models. These results highlight the importance of considering multiple photosynthesis proxies when assessing responses to climatic anomalies.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'.

Dataset Information

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

Publications

A successful prediction of the record CO<sub>2</sub> rise associated with the 2015/2016 El Niño.

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