Highlights of 2015

The US Environmental Protection Agency (EPA) has alleged that Volkswagen Group of America (VW) violated the Clean Air Act (CAA) by developing and installing emissions control system 'defeat devices' (software) in model year 2009–2015 vehicles with 2.0 litre diesel engines. VW has admitted the inclusion of defeat devices. On-road emissions testing suggests that in-use NO_x emissions for these vehicles are a factor of 10 to 40 above the EPA standard. In this paper we quantify the human health impacts and associated costs of the excess emissions. We propagate uncertainties throughout the analysis. A distribution function for excess emissions is estimated based on available in-use NO_x emissions measurements. We then use vehicle sales data and the STEP vehicle fleet model to estimate vehicle distance traveled per year for the fleet. The excess NO_x emissions are allocated on a 50 km grid using an EPA estimate of the light duty diesel vehicle NO_x emissions distribution. We apply a GEOS-Chem adjoint-based rapid air pollution exposure model to produce estimates of particulate matter and ozone exposure due to the spatially resolved excess NO_x emissions. A set of concentration-response functions is applied to estimate mortality and morbidity outcomes. Integrated over the sales period (2008–2015) we estimate that the excess emissions will cause 59 (95% CI: 10 to 150) early deaths in the US. When monetizing premature mortality using EPA-recommended data, we find a social cost of ∼$450m over the sales period. For the current fleet, we estimate that a return to compliance for all affected vehicles by the end of 2016 will avert ∼130 early deaths and avoid ∼$840m in social costs compared to a counterfactual case without recall.

Fires associated with agricultural and plantation development in Indonesia impact ecosystem services and release emissions into the atmosphere that degrade regional air quality and contribute to greenhouse gas concentrations. In this study, we estimate the relative contributions of the oil palm, timber (for wood pulp and paper), and logging industries in Sumatra and Kalimantan to land cover change, fire activity, and regional population exposure to smoke concentrations. Concessions for these three industries cover 21% and 49% of the land area in Sumatra and Kalimantan respectively, with the highest overall area in lowlands on mineral soils instead of more carbon-rich peatlands. In 2012, most remaining forest area was located in logging concessions for both islands, and for all combined concessions, there was higher remaining lowland and peatland forest area in Kalimantan (45% and 46%, respectively) versus Sumatra (20% and 27%, respectively). Emissions from all combined concessions comprised 41% of total fire emissions (within and outside of concession boundaries) in Sumatra and 27% in Kalimantan for the 2006 burning season, which had high fire activity relative to decadal emissions. Most fire emissions were observed in concessions located on peatlands and non-forested lowlands, the latter of which could include concessions that are currently under production, cleared in preparation for production, or abandoned lands. For the 2006 burning season, timber concessions from Sumatra (47% of area and 88% of emissions) and oil palm concessions from Kalimantan (33% of area and 67% of emissions) contributed the most to concession-related fire emissions from each island. Although fire emissions from concessions were higher in Kalimantan, emissions from Sumatra contributed 63% of concession-related smoke concentrations for the population-weighted region because fire sources were located closer to population centers. In order to protect regional public health, our results highlight the importance of limiting the use of fire by the timber and oil palm industries, particularly on concessions that contain peatlands and non-forest, by such methods as improving monitoring systems, local-level management, and enforcement of existing fire bans.

Earlier research that reports a correlational pattern between climate anomalies and violent conflict routinely refers to drought-induced agricultural shocks and adverse economic spillover effects as a key causal mechanism linking the two phenomena. Comparing half a century of statistics on climate variability, food production, and political violence across Sub-Saharan Africa, this study offers the most precise and theoretically consistent empirical assessment to date of the purported indirect relationship. The analysis reveals a robust link between weather patterns and food production where more rainfall generally is associated with higher yields. However, the second step in the causal model is not supported; agricultural output and violent conflict are only weakly and inconsistently connected, even in the specific contexts where production shocks are believed to have particularly devastating social consequences. Although this null result could, in theory, be fully compatible with recent reports of food price-related riots, it suggests that the wider socioeconomic and political context is much more important than drought and crop failures in explaining violent conflict in contemporary Africa.

Cultivation of corn and soybeans in the United States reached record high levels following the biofuels boom of the late 2000s. Debate exists about whether the expansion of these crops caused conversion of grasslands and other carbon-rich ecosystems to cropland or instead replaced other crops on existing agricultural land. We tracked crop-specific expansion pathways across the conterminous US and identified the types, amount, and locations of all land converted to and from cropland, 2008–2012. We found that crop expansion resulted in substantial transformation of the landscape, including conversion of long-term unimproved grasslands and land that had not been previously used for agriculture (cropland or pasture) dating back to at least the early 1970s. Corn was the most common crop planted directly on new land, as well as the largest indirect contributor to change through its displacement of other crops. Cropland expansion occurred most rapidly on land that is less suitable for cultivation, raising concerns about adverse environmental and economic costs of conversion. Our results reveal opportunities to increase the efficacy of current federal policy conservation measures by modifying coverage of the 2014 US Farm Bill Sodsaver provision and improving enforcement of the US Renewable Fuels Standard.

Extreme heat events are associated with spikes in mortality, yet death rates are on average highest during the coldest months of the year. Under the assumption that most winter excess mortality is due to cold temperature, many previous studies have concluded that winter mortality will substantially decline in a warming climate. We analyzed whether and to what extent cold temperatures are associated with excess winter mortality across multiple cities and over multiple years within individual cities, using daily temperature and mortality data from 36 US cities (1985–2006) and 3 French cities (1971–2007). Comparing across cities, we found that excess winter mortality did not depend on seasonal temperature range, and was no lower in warmer vs. colder cities, suggesting that temperature is not a key driver of winter excess mortality. Using regression models within monthly strata, we found that variability in daily mortality within cities was not strongly influenced by winter temperature. Finally we found that inadequate control for seasonality in analyses of the effects of cold temperatures led to spuriously large assumed cold effects, and erroneous attribution of winter mortality to cold temperatures. Our findings suggest that reductions in cold-related mortality under warming climate may be much smaller than some have assumed. This should be of interest to researchers and policy makers concerned with projecting future health effects of climate change and developing relevant adaptation strategies.

New metrics and evidence are presented that support a linkage between rapid Arctic warming, relative to Northern hemisphere mid-latitudes, and more frequent high-amplitude (wavy) jet-stream configurations that favor persistent weather patterns. We find robust relationships among seasonal and regional patterns of weaker poleward thickness gradients, weaker zonal upper-level winds, and a more meridional flow direction. These results suggest that as the Arctic continues to warm faster than elsewhere in response to rising greenhouse-gas concentrations, the frequency of extreme weather events caused by persistent jet-stream patterns will increase.

Although a large body of quantitative environmental justice research exists, only a handful of studies have examined the processes by which racial and socioeconomic disparities in the location of polluting industrial facilities can occur. These studies have had mixed results, we contend, principally because of methodological differences, that is, the use of the unit-hazard coincidence method as compared to distance-based methods. This study is the first national-level environmental justice study to conduct longitudinal analyses using distance-based methods. Our purposes are to: (1) determine whether disparate siting, post-siting demographic change, or a combination of the two created present-day disparities; (2) test related explanations; and (3) determine whether the application of distance-based methods helps resolve the inconsistent findings of previous research. We used a national database of commercial hazardous waste facilities sited from 1966 to 1995 and examined the demographic composition of host neighborhoods around the time of siting and demographic changes that occurred after siting. We found strong evidence of disparate siting for facilities sited in all time periods. Although we found some evidence of post-siting demographic changes, they were mostly a continuation of changes that occurred in the decade or two prior to siting, suggesting that neighborhood transition serves to attract noxious facilities rather than the facilities themselves attracting people of color and low income populations. Our findings help resolve inconsistencies among the longitudinal studies and builds on the evidence from other subnational studies that used distance-based methods. We conclude that racial discrimination and sociopolitical explanations (i.e., the proposition that siting decisions follow the 'path of least resistance') best explain present-day inequities.

Drought-induced tree mortality has recently received considerable attention. Questions have arisen over the necessary intensity and duration thresholds of droughts that are sufficient to trigger rapid forest declines. The values of such tipping points leading to forest declines due to drought are presently unknown. In this study, we have evaluated the potential relationship between the level of tree growth and concurrent drought conditions with data of the tree growth-related ring width index (RWI) of the two dominant conifer species (Pinus edulis and Pinus ponderosa) in the Southwestern United States (SWUS) and the meteorological drought-related standardized precipitation evapotranspiration index (SPEI). In this effort, we determined the binned averages of RWI and the 11 month SPEI within the month of July within each bin of 30 of RWI in the range of 0–3000. We found a significant correlation between the binned averages of RWI and SPEI at the regional-scale under dryer conditions. The tipping point of forest declines to drought is predicted by the regression model as SPEI_tp = −1.64 and RWI_tp = 0, that is, persistence of the water deficit (11 month) with intensity of −1.64 leading to negligible growth for the conifer species. When climate conditions are wetter, the correlation between the binned averages of RWI and SPEI is weaker which we believe is most likely due to soil water and atmospheric moisture levels no longer being the dominant factor limiting tree growth. We also illustrate a potential application of the derived tipping point (SPEI_tp = −1.64) through an examination of the 2002 extreme drought event in the SWUS conifer forest regions. Distinguished differences in remote-sensing based NDVI anomalies were found between the two regions partitioned by the derived tipping point.

Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins—which together have a present population of ∼2 billion people—are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of >300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

This paper presents an overview of the state of measurement and monitoring capabilities for forests in the context of REDD+ needs, with a focus on what is currently possible, where improvements are needed, and what capabilities will be advanced in the near-term with new technologies already under development. We summarize the role of remote sensing (both satellite and aircraft) for observational monitoring of forests, including measuring changes in their current and past extent for setting baselines, their carbon stock density for estimating emissions in areas that are deforested or degraded, and their regrowth dynamics following disturbance. We emphasize the synergistic role of integrating field inventory measurements with remote sensing for best practices in monitoring, reporting and verification. We also address the potential of remote sensing for enforcing safeguards on conservation of natural forests and biodiversity. We argue that capabilities exist now to meet operational needs for REDD+ measurement, reporting, and verification and reference levels. For some other areas of importance for REDD+, such as safeguards for natural forests and biodiversity, monitoring capabilities are approaching operational in the near term. For all REDD+ needs, measurement capabilities will rapidly advance in the next few years as a result of new technology as well as advances in capacity building both within and outside of the tropical forest nations on which REDD+ is primarily focused.

In 2014, Central England experienced its warmest year in a record extending back to 1659. Using both state-of-the-art climate models and empirical techniques, our analysis shows a substantial and significant increase in the likelihood of record-breaking warm years, such as 2014, due to human influences on climate. With 90% confidence we find that anthropogenic forcings on the climate have increased the chances of record warm years in Central England by at least 13-fold. This study points to a large influence of human activities on extreme warm years despite the small region of study and the variable climate of Central England. Our analysis shows that climate change is clearly visible on the local-scale in this case.

Air quality in Great Britain has improved in recent years, but not enough to prevent the European Commission (EC) taking legal action for non-compliance with limit values. Air quality is a national public health concern, with disease burden associated with current air quality estimated at 29 000 premature deaths per year due to fine particulates, with a further burden due to NO₂. National small-area analyses showed that in 2001 poor air quality was much more prevalent in socio-economically deprived areas. We extend this social distribution of air quality analysis to consider how the distribution changed over the following decade (2001–2011), a period when significant efforts to meet EC air quality directive limits have been made, and air quality has improved. We find air quality improvement is greatest in the least deprived areas, whilst the most deprived areas bear a disproportionate and rising share of declining air quality including non-compliance with air quality standards. We discuss the implications for health inequalities, progress towards environmental justice, and compatibility of social justice and environmental sustainability objectives.

Microplastic debris floating at the ocean surface can harm marine life. Understanding the severity of this harm requires knowledge of plastic abundance and distributions. Dozens of expeditions measuring microplastics have been carried out since the 1970s, but they have primarily focused on the North Atlantic and North Pacific accumulation zones, with much sparser coverage elsewhere. Here, we use the largest dataset of microplastic measurements assembled to date to assess the confidence we can have in global estimates of microplastic abundance and mass. We use a rigorous statistical framework to standardize a global dataset of plastic marine debris measured using surface-trawling plankton nets and coupled this with three different ocean circulation models to spatially interpolate the observations. Our estimates show that the accumulated number of microplastic particles in 2014 ranges from 15 to 51 trillion particles, weighing between 93 and 236 thousand metric tons, which is only approximately 1% of global plastic waste estimated to enter the ocean in the year 2010. These estimates are larger than previous global estimates, but vary widely because the scarcity of data in most of the world ocean, differences in model formulations, and fundamental knowledge gaps in the sources, transformations and fates of microplastics in the ocean.

The European Parliament recently called for urgent measures to halve food waste in the EU, where consumers are responsible for a major part of total waste along the food supply chain. Due to a lack of data on national food waste statistics, uncertainty in (consumer) waste quantities (and the resulting associated quantities of natural resources) is very high, but has never been previously assessed in studies for the EU. Here we quantify: (1) EU consumer food waste, and (2) associated natural resources required for its production, in term of water and nitrogen, as well as estimating the uncertainty of these values. Total EU consumer food waste averages 123 (min 55–max 190) kg/capita annually (kg/cap/yr), i.e. 16% (min 7–max 24%) of all food reaching consumers. Almost 80%, i.e. 97 (min 45–max 153) kg/cap/yr is avoidable food waste, which is edible food not consumed. We have calculated the water and nitrogen (N) resources associated with avoidable food waste. The associated blue water footprint (WF) (the consumption of surface and groundwater resources) averages 27 litre per capita per day (min 13–max 40 l/cap/d), which slightly exceeds the total blue consumptive EU municipal water use. The associated green WF (consumptive rainwater use) is 294 (min 127–max 449) l/cap/d, equivalent to the total green consumptive water use for crop production in Spain. The nitrogen (N) contained in avoidable food waste averages 0.68 (min 0.29–max 1.08) kg/cap/yr. The food production N footprint (any remaining N used in the food production process) averages 2.74 (min 1.02–max 4.65) kg/cap/yr, equivalent to the use of mineral fertiliser by the UK and Germany combined. Among all the food product groups wasted, meat accounts for the highest amounts of water and N resources, followed by wasted cereals. The results of this study provide essential insights and information on sustainable consumption and resource efficiency for both EU policies and EU consumers.

The global number of dam constructions has increased dramatically over the past six decades and is forecast to continue to rise, particularly in less industrialized regions. Identifying development pathways that can deliver the benefits of new infrastructure while also maintaining healthy and productive river systems is a great challenge that requires understanding the multifaceted impacts of dams at a range of scales. New approaches and advanced methodologies are needed to improve predictions of how future dam construction will affect biodiversity, ecosystem functioning, and fluvial geomorphology worldwide, helping to frame a global strategy to achieve sustainable dam development. Here, we respond to this need by applying a graph-based river routing model to simultaneously assess flow regulation and fragmentation by dams at multiple scales using data at high spatial resolution. We calculated the cumulative impact of a set of 6374 large existing dams and 3377 planned or proposed dams on river connectivity and river flow at basin and subbasin scales by fusing two novel indicators to create a holistic dam impact matrix for the period 1930–2030. Static network descriptors such as basin area or channel length are of limited use in hierarchically nested and dynamic river systems, so we developed the river fragmentation index and the river regulation index, which are based on river volume. These indicators are less sensitive to the effects of network configuration, offering increased comparability among studies with disparate hydrographies as well as across scales. Our results indicate that, on a global basis, 48% of river volume is moderately to severely impacted by either flow regulation, fragmentation, or both. Assuming completion of all dams planned and under construction in our future scenario, this number would nearly double to 93%, largely due to major dam construction in the Amazon Basin. We provide evidence for the importance of considering small to medium sized dams and for the need to include waterfalls to establish a baseline of natural fragmentation. Our versatile framework can serve as a component of river fragmentation and connectivity assessments; as a standardized, easily replicable monitoring framework at global and basin scales; and as part of regional dam planning and management strategies.

Policy makers have called for a 'fair and ambitious' global climate agreement. Scientific constraints, such as the allowable carbon emissions to avoid exceeding a 2 °C global warming limit with 66% probability, can help define ambitious approaches to climate targets. However, fairly sharing the mitigation challenge to meet a global target involves human values rather than just scientific facts. We develop a framework based on cumulative emissions of carbon dioxide to compare the consistency of countries' current emission pledges to the ambition of keeping global temperatures below 2 °C, and, further, compare two alternative methods of sharing the remaining emission allowance. We focus on the recent pledges and other official statements of the EU, USA, and China. The EU and US pledges are close to a 2 °C level of ambition only if the remaining emission allowance is distributed based on current emission shares, which is unlikely to be viewed as 'fair and ambitious' by others who presently emit less. China's stated emissions target also differs from measures of global fairness, owing to emissions that continue to grow into the 2020s. We find that, combined, the EU, US, and Chinese pledges leave little room for other countries to emit CO₂ if a 2 °C limit is the objective, essentially requiring all other countries to move towards per capita emissions 7 to 14 times lower than the EU, USA, or China by 2030. We argue that a fair and ambitious agreement for a 2 °C limit that would be globally inclusive and effective in the long term will require stronger mitigation than the goals currently proposed. Given such necessary and unprecedented mitigation and the current lack of availability of some key technologies, we suggest a new diplomatic effort directed at ensuring that the necessary technologies become available in the near future.

Brazil plans to meet the majority of its growing electricity demand with new hydropower plants located in the Amazon basin. However, large hydropower plants located in tropical forested regions may lead to significant carbon dioxide and methane emission. Currently, no predictive models exist to estimate the greenhouse gas emissions before the reservoir is built. This paper presents two different approaches to investigate the future carbon balance of eighteen new reservoirs in the Amazon. The first approach is based on a degradation model of flooded carbon stock, while the second approach is based on flux data measured in Amazonian rivers and reservoirs. The models rely on a Monte Carlo simulation framework to represent the balance of the greenhouse gases into the atmosphere that results when land and river are converted into a reservoir. Further, we investigate the role of the residence time/stratification in the carbon emissions estimate. Our results imply that two factors contribute to reducing overall emissions from these reservoirs: high energy densities reservoirs, i.e., the ratio between the installed capacity and flooded area, and vegetation clearing. While the models' uncertainties are high, we show that a robust treatment of uncertainty can effectively indicate whether a reservoir in the Amazon will result in larger greenhouse gas emissions when compared to other electricity sources.

The onset of spring plant growth has shifted earlier in the year over the past several decades due to rising global temperatures. Earlier spring onset may cause phenological mismatches between the availability of plant resources and dependent animals, and potentially lead to more false springs, when subsequent freezing temperatures damage new plant growth. We used the extended spring indices to project changes in spring onset, defined by leaf out and by first bloom, and predicted false springs until 2100 in the conterminous United States (US) using statistically-downscaled climate projections from the Coupled Model Intercomparison Project 5 ensemble. Averaged over our study region, the median shift in spring onset was 23 days earlier in the Representative Concentration Pathway 8.5 scenario with particularly large shifts in the Western US and the Great Plains. Spatial variation in phenology was due to the influence of short-term temperature changes around the time of spring onset versus season-long accumulation of warm temperatures. False spring risk increased in the Great Plains and portions of the Midwest, but remained constant or decreased elsewhere. We conclude that global climate change may have complex and spatially variable effects on spring onset and false springs, making local predictions of change difficult.

Determining the time of emergence of climates altered from their natural state by anthropogenic influences can help inform the development of adaptation and mitigation strategies to climate change. Previous studies have examined the time of emergence of climate averages. However, at the global scale, the emergence of changes in extreme events, which have the greatest societal impacts, has not been investigated before. Based on state-of-the-art climate models, we show that temperature extremes generally emerge slightly later from their quasi-natural climate state than seasonal means, due to greater variability in extremes. Nevertheless, according to model evidence, both hot and cold extremes have already emerged across many areas. Remarkably, even precipitation extremes that have very large variability are projected to emerge in the coming decades in Northern Hemisphere winters associated with a wettening trend. Based on our findings we expect local temperature and precipitation extremes to already differ significantly from their previous quasi-natural state at many locations or to do so in the near future. Our findings have implications for climate impacts and detection and attribution studies assessing observed changes in regional climate extremes by showing whether they will likely find a fingerprint of anthropogenic climate change.

Aviation emissions impact surface air quality at multiple scales—from near-airport pollution peaks associated with airport landing and take off (LTO) emissions, to intercontinental pollution attributable to aircraft cruise emissions. Previous studies have quantified aviation's air quality impacts around a specific airport, in a specific region, or at the global scale. However, no study has assessed the air quality and human health impacts of aviation, capturing effects on all aforementioned scales. This study uses a multi-scale modeling approach to quantify and monetize the air quality impact of civil aviation emissions, approximating effects of aircraft plume dynamics-related local dispersion (∼1 km), near-airport dispersion (∼10 km), regional (∼1000 km) and global (∼10 000 km) scale chemistry and transport. We use concentration-response functions to estimate premature deaths due to population exposure to aviation-attributable PM_2.5 and ozone, finding that aviation emissions cause ∼16 000 (90% CI: 8300–24 000) premature deaths per year. Of these, LTO emissions contribute a quarter. Our estimate shows that premature deaths due to long-term exposure to aviation-attributable PM_2.5 and O₃ lead to costs of ∼$21 bn per year. We compare these costs to other societal costs of aviation and find that they are on the same order of magnitude as global aviation-attributable climate costs, and one order of magnitude larger than aviation-attributable accident and noise costs.

The current global gold rush, driven by increasing consumption in developing countries and uncertainty in financial markets, is an increasing threat for tropical ecosystems. Gold mining causes significant alteration to the environment, yet mining is often overlooked in deforestation analyses because it occupies relatively small areas. As a result, we lack a comprehensive assessment of the spatial extent of gold mining impacts on tropical forests. In this study, we provide a regional assessment of gold mining deforestation in the tropical moist forest biome of South America. Specifically, we analyzed the patterns of forest change in gold mining sites between 2001 and 2013, and evaluated the proximity of gold mining deforestation to protected areas (PAs). The forest cover maps were produced using the Land Mapper web application and images from the MODIS satellite MOD13Q1 vegetation indices 250 m product. Annual maps of forest cover were used to model the incremental change in forest in ∼1600 potential gold mining sites between 2001–2006 and 2007–2013. Approximately 1680 km² of tropical moist forest was lost in these mining sites between 2001 and 2013. Deforestation was significantly higher during the 2007–2013 period, and this was associated with the increase in global demand for gold after the international financial crisis. More than 90% of the deforestation occurred in four major hotspots: Guianan moist forest ecoregion (41%), Southwest Amazon moist forest ecoregion (28%), Tapajós–Xingú moist forest ecoregion (11%), and Magdalena Valley montane forest and Magdalena–Urabá moist forest ecoregions (9%). In addition, some of the more active zones of gold mining deforestation occurred inside or within 10 km of ∼32 PAs. There is an urgent need to understand the ecological and social impacts of gold mining because it is an important cause of deforestation in the most remote forests in South America, and the impacts, particularly in aquatic systems, spread well beyond the actual mining sites.

Dependence upon groundwater to meet rising agricultural and domestic water needs is expected to increase substantially across the tropics where, by 2050, over half of the world's population is projected to live. Rare, long-term groundwater-level records in the tropics indicate that groundwater recharge occurs disproportionately from heavy rainfalls exceeding a threshold. The ubiquity of this bias in tropical groundwater recharge to intensive precipitation is, however, unknown. By relating available long-term records of stable-isotope ratios of O and H in tropical precipitation (15 sites) to those of local groundwater, we reveal that groundwater recharge in the tropics is near-uniformly (14/15 sites) biased to intensive monthly rainfall, commonly exceeding the ∼70th intensity decile. Our results suggest that the intensification of precipitation brought about by global warming favours groundwater replenishment in the tropics. Nevertheless, the processes that transmit intensive rainfall to groundwater systems and enhance the resilience of tropical groundwater storage in a warming world, remain unclear.

Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (p-value <0.05) in the number of heat waves during the period 1973–2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2/3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations.

The western Amazon is one of the world's last high-biodiversity wilderness areas, characterized by extraordinary species richness and large tracts of roadless humid tropical forest. It is also home to an active hydrocarbon (oil and gas) sector, characterized by operations in extremely remote areas that require new access routes. Here, we present the first integrated analysis of the hydrocarbon sector and its associated road-building in the western Amazon. Specifically, we document the (a) current panorama, including location and development status of all oil and gas discoveries, of the sector, and (b) current and future scenario of access (i.e. access road versus roadless access) to discoveries. We present an updated 2014 western Amazon hydrocarbon map illustrating that oil and gas blocks now cover 733 414 km², an area much larger than the US state of Texas, and have been expanding since the last assessment in 2008. In terms of access, we documented 11 examples of the access road model and six examples of roadless access across the region. Finally, we documented 35 confirmed and/or suspected untapped hydrocarbon discoveries across the western Amazon. In the Discussion, we argue that if these reserves must be developed, use of the offshore inland model—a method that strategically avoids the construction of access roads—is crucial to minimizing ecological impacts in one of the most globally important conservation regions.

We present an updated version of the radiosonde dataset homogenized by Iterative Universal Kriging (IUKv2), now extended through February 2013, following the method used in the original version (Sherwood et al 2008 Robust tropospheric warming revealed by iteratively homogenized radiosonde data J. Clim. 21 5336–52). This method, in effect, performs a multiple linear regression of the data onto a structural model that includes both natural variability, trends, and time-changing instrument biases, thereby avoiding estimation biases inherent in traditional homogenization methods. One modification now enables homogenized winds to be provided for the first time. This, and several other small modifications made to the original method sometimes affect results at individual stations, but do not strongly affect broad-scale temperature trends. Temperature trends in the updated data show three noteworthy features. First, tropical warming is equally strong over both the 1959–2012 and 1979–2012 periods, increasing smoothly and almost moist-adiabatically from the surface (where it is roughly 0.14 K/decade) to 300 hPa (where it is about 0.25 K/decade over both periods), a pattern very close to that in climate model predictions. This contradicts suggestions that atmospheric warming has slowed in recent decades or that it has not kept up with that at the surface. Second, as shown in previous studies, tropospheric warming does not reach quite as high in the tropics and subtropics as predicted in typical models. Third, cooling has slackened in the stratosphere such that linear trends since 1979 are about half as strong as reported earlier for shorter periods. Wind trends over the period 1979–2012 confirm a strengthening, lifting and poleward shift of both subtropical westerly jets; the Northern one shows more displacement and the southern more intensification, but these details appear sensitive to the time period analysed. There is also a trend toward more easterly winds in the middle and upper troposphere of the deep tropics.