European Union FP7, Royal Society, and National Science Foundation.

Background Europe has emerged as a major climate change hotspot, both in terms of an increase in seasonal averages and climate extremes. Projections of temperature-attributable mortality, however, have not been comprehensively reported for an extensive part of the continent. Therefore, we aim to estimate the future effect of climate change on temperature-attributable mortality across Europe. MethodsWe did a time series analysis study. We derived temperature-mortality associations by collecting daily temperature and all-cause mortality records of both urban and rural areas for the observational period between 1998 and 2012 from 147 regions in 16 European countries. We estimated the location-specific temperature-mortality relationships by using standard time series quasi-Poisson regression in conjunction with a distributed lag non-linear model. These associations were used to transform the daily temperature simulations from the climate models in the historical period and scenario period (2006-2099) into projections of temperature-attributable mortality. We combined the resulting risk functions with daily time series of future temperatures simulated by four climate models (ie, GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) under three greenhouse gas emission scenarios (ie, Representative Concentration Pathway [RCP]2.6, RCP6.0, and RCP8.5), providing projections of future mortality attributable fraction due to moderate and extreme cold and heat temperatures.Findings Overall, 7•17% (95% CI 5•81-8•50) of deaths registered in the observational period were attributed to nonoptimal temperatures, cold being more harmful than heat by a factor of ten (6•51% [95% CI 5•14-7•80] vs 0•65% [0•40-0•89]), and with large regional differences across countries-eg, ranging from 4•85% (95% CI 3•75-6•00) in Germany to 9•87% (8•53-11•19) in Italy. The projection of temperature anomalies by RCP scenario depicts a progressive increase in temperatures, more exacerbated in the high-emission scenario RCP8.5 (4•54°C by 2070-2099) than in RCP6.0 (2•89°C) and RCP2.6 (1•67°C). This increase in temperatures was transformed into attributable fraction. Projections consistently indicated that the increase in heat attributable fraction will start to exceed the reduction of cold attributable fraction in the second half of the 21st century, especially in the Mediterranean and in the higher emission scenarios. The comparison between scenarios highlighted the important role of mitigation, given that the total attributable fraction will only remain stable in RCP2.6, whereas the total attributable fraction will rapidly start to increase in RCP6.0 by the end of the century and in RCP8.5 already by the middle of the century. InterpretationThe increase in heat attributable fraction will start to exceed the reduction of cold attributable fraction in the second half of the 21st century. This finding highlights the importance of implementing mitigation policies. These measures would be especially beneficial in the Mediterranean, where the high vulnerability to...

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Despite steady progress in the understanding of El Niño–Southern Oscillation (ENSO) in the past decades, questions remain on the exact mechanisms explaining the heat buildup leading to the onset of El Niño (EN) events. Here we use an ensemble of ocean and atmosphere assimilation products to identify mechanisms that are consistently identified by all the data sets and that contribute to the heat buildup in the western Pacific 18 to 24 months before the onset of EN events. Meridional and eastward heat advection due to equatorward subsurface mass convergence and transport along the equatorial undercurrent are found to contribute to the subsurface warming at 170°E–150°W. In the warm pool, instead, surface horizontal convergence and downwelling motion have a leading role in subsurface warming. The picture emerging from our results highlights a sharp dynamical transition at 170°E near the level of the thermocline.

Despite extensive ongoing efforts on improving the long-term prediction of El Niño-Southern Oscillation, the predictability in state-of-the-art operational schemes remains limited by factors such as the spring barrier and the influence of atmospheric winds. Recent research suggests that the 2014/15 El Niño (EN) event was stalled as a result of an unusually strong basin-wide easterly wind burst in June, which led to the discharge of a large fraction of the subsurface ocean heat. Here we use observational records and numerical experiments to explore the sensitivity of EN to the magnitude of the heat buildup occurring in the ocean subsurface 21 months in advance. Our simulations suggest that a large increase in heat content during this phase can lead to basin-wide uniform warm conditions in the equatorial Pacific the winter before the occurrence of a very strong EN event. In our model configuration, the system compensates any initial decrease in heat content and naturally evolves towards a new recharge, resulting in a delay of up to one year in the occurrence of an EN event. Both scenarios substantiate the non-linear dependency between the intensity of the subsurface heat buildup and the magnitude and timing of subsequent EN episodes.

The oscillatory nature of El Niño‐Southern Oscillation results from an intricate superposition of near‐equilibrium balances and out‐of‐phase disequilibrium processes between the ocean and the atmosphere. The main objective of the present work is to perform an exhaustive spatiotemporal analysis of the upper ocean heat budget in an ensemble of state‐of‐the‐art ocean assimilation products. We put specific emphasis on the ocean heat advection mechanisms, and their representation in individual ensemble members and in the different stages of the ENSO oscillation leading to EN events. Our analyses consistently show that the initial subsurface warming in the western equatorial Pacific is advected to the central Pacific by the equatorial undercurrent, which, together with the equatorward advection associated with anomalies in both the meridional temperature gradient and circulation at the level of the thermocline, explains the heat buildup in the central Pacific during the recharge phase. We also find that the recharge phase is characterized by an increase of meridional tilting of the thermocline, as well as a southward upper‐ocean cross‐equatorial mass transport resulting from Ekman‐induced anomalous vertical motion in the off‐equatorial regions. Although differences between data sets are generally small, and anomalies tend to have the same sign, the differences in the magnitude of the meridional term are seen to be key for explaining the different propagation speed of the subsurface warming tendency along the thermocline. The only exception is GECCO, which does not produce the patterns of meridional surface Ekman divergence (subsurface Sverdrup convergence) in the western and central equatorial Pacific.

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The theoretical predictability limit of El Niño–Southern Oscillation has been shown to be on the order of years, but long-lead predictions of El Niño (EN) and La Niña (LN) are still lacking. State-of-the-art forecasting schemes traditionally do not predict beyond the spring barrier. Recent efforts have been dedicated to the improvement of dynamical models, while statistical schemes still need to take full advantage of the availability of ocean subsurface variables, provided regularly for the last few decades as a result of the Tropical Ocean–Global Atmosphere Program (TOGA). Here we use a number of predictor variables, including temperature at different depths and regions of the equatorial ocean, in a flexible statistical dynamic components model to make skillful long-lead retrospective predictions (hindcasts) of the Niño-3.4 index in the period 1970–2016. The model hindcasts the major EN episodes up to 2.5 years in advance, including the recent extreme 2015/16 EN. The analysis demonstrates that events are predicted more accurately after the completion of the observational array in the tropical Pacific in 1994, as a result of the improved data quality and coverage achieved by TOGA. Therefore, there is potential to issue long-lead predictions of this climatic phenomenon at a low computational cost.