Global Disease Outbreaks Associated with the 2015-2016 El Nino Event.
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ABSTRACT:
SUBMITTER: Anyamba A
PROVIDER: S-EPMC6374399 | biostudies-literature | 2019 Feb
REPOSITORIES: biostudies-literature
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Project description:Wetlands are thought to be the major contributor to interannual variability in the growth rate of atmospheric methane (CH4) with anomalies driven by the influence of the El Niño-Southern Oscillation (ENSO). Yet it remains unclear whether (i) the increase in total global CH4 emissions during El Niño versus La Niña events is from wetlands and (ii) how large the contribution of wetland CH4 emissions is to the interannual variability of atmospheric CH4. We used a terrestrial ecosystem model that includes permafrost and wetland dynamics to estimate CH4 emissions, forced by three separate meteorological reanalyses and one gridded observational climate dataset, to simulate the spatio-temporal dynamics of wetland CH4 emissions from 1980-2016. The simulations show that while wetland CH4 responds with negative annual anomalies during the El Niño events, the instantaneous growth rate of wetland CH4 emissions exhibits complex phase dynamics. We find that wetland CH4 instantaneous growth rates were declined at the onset of the 2015-2016 El Niño event but then increased to a record-high at later stages of the El Niño event (January through May 2016). We also find evidence for a step increase of CH4 emissions by 7.8±1.6 Tg CH4 yr-1 during 2007-2014 compared to the average of 2000-2006 from simulations using meteorological reanalyses, which is equivalent to a ~3.5 ppb yr-1 rise in CH4 concentrations. The step increase is mainly caused by the expansion of wetland area in the tropics (30°S-30°N) due to an enhancement of tropical precipitation as indicated by the suite of the meteorological reanalyses. Our study highlights the role of wetlands, and the complex temporal phasing with ENSO, in driving the variability and trends of atmospheric CH4 concentrations. In addition, the need to account for uncertainty in meteorological forcings is highlighted in addressing the interannual variability and decadal-scale trends of wetland CH4 fluxes.
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Project description:Severe drought and extreme heat associated with the 2015-2016 El Niño event have led to large carbon emissions from the tropical vegetation to the atmosphere. With the return to normal climatic conditions in 2017, tropical forest aboveground carbon (AGC) stocks are expected to partly recover due to increased productivity, but the intensity and spatial distribution of this recovery are unknown. We used low-frequency microwave satellite data (L-VOD) to feature precise monitoring of AGC changes and show that the AGC recovery of tropical ecosystems was slow and that by the end of 2017, AGC had not reached predrought levels of 2014. From 2014 to 2017, tropical AGC stocks decreased by 1.31.21.5 Pg C due to persistent AGC losses in Africa ( -0.9-1.1-0.8 Pg C) and America ( -0.5-0.6-0.4 Pg C). Pantropically, drylands recovered their carbon stocks to pre-El Niño levels, but African and American humid forests did not, suggesting carryover effects from enhanced forest mortality.
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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'.
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Project description:In this paper, we report the triggering effect of extratropical perturbation on the onset of an atypical Madden-Julian Oscillation (MJO) and onset of the 2015-16 El Niño in March 2015. The MJO exhibited several unique characteristics: the effect of extratropical forcing, atypical genesis location and timing in the equatorial western Pacific, and the extremity of amplitudes in many aspects. The southward-penetrating northerly associated with the extratropical disturbances in the extratropical western North Pacific contributed to triggering the deep convection and westerly wind burst (WWB) and onset of the MJO over the anomalously warm tropical western Pacific in early March. The persisting strong WWB forced downwelling Kelvin wave-like oceanic perturbation that propagated eastward and led to the onset of the 2015-16 El Niño. The proposed novel extratropical forcing mechanism explaining the unique extratropics-MJO-El Niño association, based on both data diagnostics and numerical experiments, warrants further attention for a more detailed understanding of the onset of the MJO and its potential effect on El Niño.
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Project description: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'.
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Project description:The 2015-2016 El Niño had large impacts globally. The effects were not as great as anticipated in Kenya, however, leading some commentators to call it a 'non-event'. Our study uses a novel combination of participatory Climate Vulnerability and Capacity Analysis tools, and new and existing social and biophysical data, to analyse vulnerability to, and the multidimensional impacts of, the 2015-2016 El Niño episode in southern coastal Kenya. Using a social-ecological systems lens and a unique dataset, our study reveals impacts overlooked by conventional analysis. We show how El Niño stressors interact with and amplify existing vulnerabilities to differentially impact local ecosystems and people. The policy significance of this finding is that the development of specific national capacities to deal with El Niño events is insufficient; it will be necessary to also address local vulnerabilities to everyday and recurrent stressors and shocks to build resilience to the effects of El Niño and other extremes in climate and weather.
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Project description:During the winter of 2015, there was a strong El Nino (ENSO) event, resulting in significant anomalies for meteorological conditions in China. Analysis shows that the meteorological conditions in December 2015 (compared to December 2014) had several important anomalies, including the following: (1) the surface southeasterly winds were significantly enhanced in the North China Plain (NCP); (2) the precipitation was increased in the south of eastern China; and (3) the wind speeds were decreased in the middle-north of eastern China, while slightly increased in the south of eastern China. These meteorological anomalies produced important impacts on the aerosol pollution in eastern China. In the NCP region, the PM2.5 concentrations were significantly increased, with a maximum increase of 80-100??g m(-3). A global chemical/transport model (MOZART-4) was applied to study the individual contribution of the changes in winds and precipitation to PM2.5 concentrations. This study suggests that the 2015El Nino event had significant effects on air pollution in eastern China, especially in the NCP region, including the capital city of Beijing, in which aerosol pollution was significantly enhanced in the already heavily polluted capital city of China.
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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.
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