Table of contents

The rise of global surface temperature waned during the last decade, despite increasing greenhouse gas concentrations. The temperature changes were most pronounced over northern hemisphere land masses during winter (Cohen et al2012). They were largely associated with weakening of the mid-latitude westerly flow. To some, these temperature changes may seem paradoxical in the light of anthropogenic global warming, and thus there is much interest in explaining them. Peings and Magnusdottir (2014Environ. Res. Lett.9 034018) provide evidence that recent warming of the North Atlantic sea surface temperature (SST) may be part of the explanation.

Siebert et al (2014Environ. Res. Lett.9 044012) suggest that crop models do not represent the effect of heat stress on crop yield adequately unless they apply such effect to sensitive phases in a crop's growth cycle. Siebert et al focus particularly on the phase considered most sensitive for wheat yield in Germany, the time of anthesis. Siebert et al find that observed canopy rather than 2 m or ground temperature better quantifies the effect of heat stress during anthesis on wheat yield in Germany when evaluated against data from pot experiments under controlled conditions.

Black carbon in snow (BCS) simulated in the Community Atmosphere Model (CAM5) is evaluated against measurements over Northern China and the Arctic, and its sensitivity to atmospheric deposition and two parameters that affect post-depositional enrichment is explored. Improvements in atmospheric BC transport and deposition significantly reduce the biases (by a factor of two) in the estimation of BCS concentration over both Northern China and the Arctic. Further sensitivity simulations using the improved CAM5 indicate that the melt-water scavenging efficiency (MSE) parameter plays an important role in regulating BC concentrations in the Arctic through the post-depositional enrichment, which not only drastically changes the amplitude but also shifts the seasonal cycle of the BCS concentration and its radiative forcing in the Arctic. The impact of the snow aging scaling factor (SAF) on BCS shows more complex latitudinal and seasonal dependence, and overall impact of SAF is much smaller than that of MSE. The improvements of BC transport and deposition in CAM5 have a stronger influence on BCS than perturbations of the two snow model parameters in Northern China.

Climate extremes have and will continue to cause severe damages to buildings and natural environments around the world. A full knowledge of the probability of the climate extremes is important for the management and mitigation of natural hazards. Based on Mann–Kendall trend test and copulas, this study investigated the characteristics of precipitation extremes as well as their implications in southwestern China (Yunnan, Guangxi and Guizhou Province), through analyzing the changing trends and probabilistic characteristics of six indices, including the consecutive dry days, consecutive wet days, annual total wet day precipitation, heavy precipitation days (R25), max 5 day precipitation amount (Rx5) and the rainy days (RDs). Results showed that the study area had generally become drier (regional mean annual precipitation decreased by 11.4 mm per decade) and experienced enhanced precipitation extremes in the past 60 years. Relatively higher risk of drought in Yuanan and flood in Guangxi was observed, respectively. However, the changing trends of the precipitation extremes were not spatially uniform: increasing risk of extreme wet events for Guangxi and Guizhou, and increasing probability of concurrent extreme wet and dry events for Yunnan. Meanwhile, trend analyses of the 10 year return levels of the selected indices implied that the severity of droughts decreased in Yunnan but increased significantly in Guangxi and Guizhou, and the severity of floods increased in Yunnan and Guangxi in the past decades. Hence, the policy-makers need to be aware of the different characterizations and the spatial heterogeneity of the precipitation extremes.

Increased photosynthetic activity and enhanced seasonal CO₂ exchange of northern ecosystems have been observed from a variety of sources including satellite vegetation indices (such as the normalized difference vegetation index; NDVI) and atmospheric CO₂ measurements. Most of these changes have been attributed to strong warming trends in the northern high latitudes (⩾50° N). Here we analyze the interannual variation of summer net carbon uptake derived from atmospheric CO₂ measurements and satellite NDVI in relation to surface meteorology from regional observational records. We find that increases in spring precipitation and snow pack promote summer net carbon uptake of northern ecosystems independent of air temperature effects. However, satellite NDVI measurements still show an overall benefit of summer photosynthetic activity from regional warming and limited impact of spring precipitation. This discrepancy is attributed to a similar response of photosynthesis and respiration to warming and thus reduced sensitivity of net ecosystem carbon uptake to temperature. Further analysis of boreal tower eddy covariance CO₂ flux measurements indicates that summer net carbon uptake is positively correlated with early growing-season surface soil moisture, which is also strongly affected by spring precipitation and snow pack based on analysis of satellite soil moisture retrievals. This is attributed to strong regulation of spring hydrology on soil respiration in relatively wet boreal and arctic ecosystems. These results document the important role of spring hydrology in determining summer net carbon uptake and contrast with prevailing assumptions of dominant cold temperature limitations to high-latitude ecosystems. Our results indicate potentially stronger coupling of boreal/arctic water and carbon cycles with continued regional warming trends.

Projections of land cover change generated from integrated assessment models (IAM) and other economic-based models can be applied for analyses of environmental impacts at sub-regional and landscape scales. For those IAM and economic models that project land cover change at the continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30 m) and at the global extent with relatively coarse spatial resolution (0.5°). We revised existing methods to downscale global land cover change projections for the US to 0.05° resolution using MODIS land cover data as the initial proxy for land class distribution. Land cover change realizations generated here represent a reference scenario and two emissions mitigation pathways (MPs) generated by the global change assessment model (GCAM). Future gridded land cover realizations are constructed for each MODIS plant functional type (PFT) from 2005 to 2095, commensurate with the community land model PFT land classes, and archived for public use. The GCAM land cover realizations provide spatially explicit estimates of potential shifts in croplands, grasslands, shrublands, and forest lands. Downscaling of the MPs indicate a net replacement of grassland by cropland in the western US and by forest in the eastern US. An evaluation of the downscaling method indicates that it is able to reproduce recent changes in cropland and grassland distributions in respective areas in the US, suggesting it could provide relevant insights into the potential impacts of socio-economic and environmental drivers on future changes in land cover.

Due to increasing atmospheric CO₂ concentrations and associated climate change, the global ocean is undergoing substantial physical and biogeochemical changes. Among these, changes in ocean oxygen and carbonate chemistry have great implication for marine biota. There is considerable uncertainty in the projections of future climate change, and it is unclear how the uncertainty in climate change would also affect the projection of oxygen and carbonate chemistry. To investigate this issue, we use an Earth system model of intermediate complexity to perform a set of simulations, including that which involves no radiative effect of atmospheric CO₂ and those which involve CO₂-induced climate change with climate sensitivity varying from 0.5 °C to 4.5 °C. Atmospheric CO₂ concentration is prescribed to follow RCP 8.5 pathway and its extensions. Climate change affects carbonate chemistry and oxygen mainly through its impact on ocean temperature, ocean ventilation, and concentration of dissolved inorganic carbon and alkalinity. It is found that climate change mitigates the decrease of carbonate ions at the ocean surface but has negligible effect on surface ocean pH. Averaged over the whole ocean, climate change acts to decrease oxygen concentration but mitigates the CO₂-induced reduction of carbonate ion and pH. In our simulations, by year 2500, every degree increase of climate sensitivity warms the ocean by 0.8 °C and reduces ocean-mean dissolved oxygen concentration by 5.0%. Meanwhile, every degree increase of climate sensitivity buffers CO₂-induced reduction in ocean-mean carbonate ion concentration and pH by 3.4% and 0.02 units, respectively. Our study demonstrates different sensitivities of ocean temperature, carbonate chemistry, and oxygen, in terms of both the sign and magnitude to the amount of climate change, which have great implications for understanding the response of ocean biota to climate change.

Much as humans suffer from heat-stress during periods of high temperature and humidity, so do dairy cattle. Using a temperature-humidity index (THI), we investigate the effect of past heatwaves in the UK on heat-stress in dairy herds. Daily THI data derived from routine meteorological observations show that during the summer, there has been an average of typically 1 day per year per station over the past 40 years when the THI has exceeded the threshold for the onset of mild heat-stress in dairy cattle. However, during the heatwaves of 2003 and 2006, this threshold was exceeded on typically 5 days on average in the Midlands, south and east of England. Most dairy cattle are in the west and north of the country and so did not experience the severest heat. Milk yield data in the south-west of England show that a few herds experienced decreases in yields during 2003 and 2006. We used the 11-member regional climate model ensemble with the A1B scenario from UKCP09 to investigate the possible future change in days exceeding the THI threshold for the onset of mild heat-stress. The number of days where the THI exceeds this threshold could increase to over 20 days yr⁻¹ in southern parts of England by the end of the century.

This work quantifies the agricultural water footprint (WF) of production (WF_{prod, agr}) and consumption (WF_{cons, agr}) and the resulting net virtual water import (netVW_{i, agr}) of 365 European river basins for a reference period (REF, 1996–2005) and two diet scenarios (a healthy diet based upon food-based dietary guidelines (HEALTHY) and a vegetarian (VEG) diet). In addition to total (tot) amounts, a differentiation is also made between the green (gn), blue (bl) and grey (gy) components. River basins where the REF WF_{cons, agr, tot} exceeds the WF_{prod, agr, tot} (resulting in positive netVW_{i, agr, tot} values), are found along the London–Milan axis. These include the Thames, Scheldt, Meuse, Seine, Rhine and Po basins. River basins where the WF_{prod, agr, tot} exceeds the WF_{cons, agr, tot} are found in Western France, the Iberian Peninsula and the Baltic region. These include the Loire, Ebro and Nemunas basins. Under the HEALTHY diet scenario, the WF_{cons, agr, tot} of most river basins decreases (max −32%), although it was found to increase in some basins in northern and eastern Europe. This results in 22 river basins, including the Danube, shifting from being net VW importers to being net VW exporters. A reduction (max −46%) in WF_{cons, agr, tot} is observed for all but one river basin under the VEG diet scenario. In total, 50 river basins shift from being net VW importers to being net exporters, including the Danube, Seine, Rhone and Elbe basins. Similar observations are made when only the gn + bl and gn components are assessed. When analysing only the bl component, a different river basin pattern is observed.

In this study, the effect of mean precipitation bias over the Pacific Intertropical Convergence Zone (ITCZ) on the El Niño southern oscillation (ENSO) transition is examined using CMIP3 and CMIP5 archives. It is found that the climate models with excessive mean precipitation over the central/eastern Pacific ITCZ tend to simulate slower phase transition of the ENSO. This is because a wetter climatology provides a favorable condition for anomalously strong convective activity; the El Niño-related convection anomaly tends to be increased over the central/eastern Pacific ITCZ with a local wet bias. This induces additional low-level westerlies over the central/eastern equatorial Pacific. As a result, the ENSO-related zonal wind stress anomaly over the central Pacific, which is south of the equator without the wet ITCZ bias during boreal winter, is shifted to the east, and its meridional width is expanded northward. It is found that both the eastward shift and northward expansion of ENSO-related wind stress can lead to slower ENSO phase transition as it takes longer time for the reflected Rossby waves to suppress the ENSO growth. This implies that the off-equatorial mean precipitation plays an important role in ENSO phase transition.

New demands for water can be satisfied through a variety of source options. In some basins surface and/or groundwater may be available through permitting with the state water management agency (termed unappropriated water), alternatively water might be purchased and transferred out of its current use to another (termed appropriated water), or non-traditional water sources can be captured and treated (e.g., wastewater). The relative availability and cost of each source are key factors in the development decision. Unfortunately, these measures are location dependent with no consistent or comparable set of data available for evaluating competing water sources. With the help of western water managers, water availability was mapped for over 1200 watersheds throughout the western US. Five water sources were individually examined, including unappropriated surface water, unappropriated groundwater, appropriated water, municipal wastewater and brackish groundwater. Also mapped was projected change in consumptive water use from 2010 to 2030. Associated costs to acquire, convey and treat the water, as necessary, for each of the five sources were estimated. These metrics were developed to support regional water planning and policy analysis with initial application to electric transmission planning in the western US.

This letter uses satellite remote sensing to examine patterns of cropland expansion, cropland abandonment, and changing cropping frequency in Mato Grosso, Brazil from 2001 to 2011. During this period, Mato Grosso emerged as a globally important center of agricultural production. In 2001, 3.3 million hectares of mechanized agriculture were cultivated in Mato Grosso, of which 500 000 hectares had two commercial crops per growing season (double cropping). By 2011, Mato Grosso had 5.8 million hectares of mechanized agriculture, of which 2.9 million hectares were double cropped. We found these agricultural changes to be selective with respect to land attributes—significant differences (p < 0.001) existed between the land attributes of agriculture versus non-agriculture, single cropping versus double cropping, and expansion versus abandonment. Many of the land attributes (elevation, slope, maximum temperature, minimum temperature, initial soy transport costs, and soil) that were associated with an increased likelihood of expansion were associated with a decreased likelihood of abandonment (p < 0.001). While land similar to agriculture and double cropping in 2001 was much more likely to be developed for agriculture than all other land, new cropland shifted to hotter, drier, lower locations that were more isolated from agricultural infrastructure (p < 0.001). The scarcity of high quality remaining agricultural land available for agricultural expansion in Mato Grosso could be contributing to the slowdown in agricultural expansion observed there over 2006 to 2011. Land use policy analyses should control for land scarcity constraints on agricultural expansion.

The ecological effects of forest fires burning with high severity are long-lived and have the greatest impact on vegetation successional trajectories, as compared to low-to-moderate severity fires. The primary drivers of high severity fire are unclear, but it has been hypothesized that wind-driven, large fire-growth days play a significant role, particularly on large fires in forested ecosystems. Here, we examined the relative proportion of classified burn severity for individual daily areas burned that occurred during 42 large forest fires in central Idaho and western Montana from 2005 to 2007 and 2011. Using infrared perimeter data for wildfires with five or more consecutive days of mapped perimeters, we delineated 2697 individual daily areas burned from which we calculated the proportions of each of three burn severity classes (high, moderate, and low) using the differenced normalized burn ratio as mapped for large fires by the Monitoring Trends in Burn Severity project. We found that the proportion of high burn severity was weakly correlated (Kendall τ = 0.299) with size of daily area burned (DAB). Burn severity was highly variable, even for the largest (95th percentile) in DAB, suggesting that other variables than fire extent influence the ecological effects of fires. We suggest that these results do not support the prioritization of large runs during fire rehabilitation efforts, since the underlying assumption in this prioritization is a positive relationship between severity and area burned in a day.

Biogenic lipids and polymers are surveyed for their ability to adsorb at the water–air interfaces associated with bubbles, marine microlayers and particles in the overlying boundary layer. Representative ocean biogeochemical regimes are defined in order to estimate local concentrations for the major macromolecular classes. Surfactant equilibria and maximum excess are then derived based on a network of model compounds. Relative local coverage and upward mass transport follow directly, and specific chemical structures can be placed into regional rank order. Lipids and denatured protein-like polymers dominate at the selected locations. The assigned monolayer phase states are variable, whether assessed along bubbles or at the atmospheric spray droplet perimeter. Since oceanic film compositions prove to be irregular, effects on gas and organic transfer are expected to exhibit geographic dependence as well. Moreover, the core arguments extend across the sea–air interface into aerosol–cloud systems. Fundamental nascent chemical properties including mass to carbon ratio and density depend strongly on the geochemical state of source waters. High surface pressures may suppress the Kelvin effect, and marine organic hygroscopicities are almost entirely unconstrained. While bubble adsorption provides a well-known means for transporting lipidic or proteinaceous material into sea spray, the same cannot be said of polysaccharides. Carbohydrates tend to be strongly hydrophilic so that their excess carbon mass is low despite stacked polymeric geometries. Since sugars are abundant in the marine aerosol, gel-based mechanisms may be required to achieve uplift. Uncertainties distill to a global scale dearth of information regarding two dimensional kinetics and equilibria. Nonetheless simulations are recommended, to initiate the process of systems level quantification.

Soil microbes play a key role in nutrient cycling and carbon sequestration. Global change can alter soil microbial population composition and behavior. Biochar addition has been explored in the last years as a way to mitigate global warming. However, responses of microbial communities to biochar addition in particular in relation to abiotic disturbances are seldom documented. An example of these disturbances, which is predicted to be exacerbated with global warming, is regional drought. It has been known that fungal-based food webs are more resistant to drought than their bacterial counterparts. Our study found that biochar addition can increase the resistance of both the bacterial and fungal networks to drought. Contrary to expected, this result was not related to a change in the dominance of fungal or bacteria. In general, soil amended with biochar was characterized by a faster recovery of soil microbial properties to its basal values. Biochar addition to the soil also suppressed the Birch effect, a result that has not been previously reported.

This study assessed the health burden attributable to childhood underweight through 2050 focusing on disability-adjusted life years (DALYs), by considering the latest scenarios for climate change studies (representative concentration pathways and shared socioeconomic pathways (SSPs)) and conducting sensitivity analysis. A regression model for estimating DALYs attributable to childhood underweight (DAtU) was developed using the relationship between DAtU and childhood stunting. We combined a global computable general equilibrium model, a crop model, and two regression models to assess the future health burden. We found that (i) world total DAtU decreases from 2005 by 28 ∼ 63% in 2050 depending on the socioeconomic scenarios. Per capita DAtU also decreases in all regions under either scenario in 2050, but the decreases vary significantly by regions and scenarios. (ii) The impact of climate change is relatively small in the framework of this study but, on the other hand, socioeconomic conditions have a great impact on the future health burden. (iii) Parameter uncertainty of the regression models is the second largest factor on uncertainty of the result following the changes in socioeconomic condition, and uncertainty derived from the difference in global circulation models is the smallest in the framework of this study.

Global urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities' fundamental characteristics and processes, and of the impact of changing land-cover on potential carbon storage. We present a grid square approach using multi-temporal Landsat data from around 1985–2010 to monitor the spatio-temporal land-cover dynamics of 50 global cities. The maximum-likelihood classification method is applied to Landsat data to define the cities' urbanized areas at different points in time. Subsequently, 1 km² grid squares with unique cell IDs are designed to link among land-cover maps for spatio-temporal land-cover change analysis. Then, we calculate land-cover category proportions for each map in 1 km² grid cells. Statistical comparison of the land-cover changes in grid square cells shows that urban area expansion in 50 global cities was strongly negatively correlated with forest, cropland and grassland changes. The generated land-cover proportions in 1 km² grid cells and the spatial relationships between the changes of land-cover classes are critical for understanding past patterns and the consequences of urban development so as to inform future urban planning, risk management and conservation strategies.

The responses of tree growth to recent climate warming may signal changes in the susceptibility of forest communities to compositional change and consequently impact a wide range of ecosystem processes and services. Previous research in the boreal forest has largely documented negative growth responses to climate in forest species and habitats characteristic of drier conditions, emphasizing the sensitivity of drier or warmer landscape positions to climate warming. In this study, we explored relationships between climate and tree-ring growth of black spruce, a dominant tree species typical of cool and moist habitats in the boreal forests of North America. We assessed how these responses varied with stand characteristics and landscape position across four different regions in Alaska and Yukon Territory. Approximately half of the trees measured across regions and topographic gradients exhibited reduced radial growth in response to warm temperatures in the previous growing season and current spring, which we interpret as a signal of drought stress. Although we found considerable variation in the growth responses of individual trees within sites, landscape position and stand characteristics were weak predictors of this variability, explaining ≦̸12% of the variation in any region. Our results indicate that future warming, particularly in spring, is likely to result in drought stress and a reduction of black spruce radial growth independent of region, landscape position, or stand characteristics. The occurrence of negative growth responses to temperature, even in cool and moist habitats, suggests that drought stress limitations may be more widespread in the northern boreal forest than previously anticipated, indicating broad sensitivity of ecosystem processes and services to climate change across a diverse range of habitat types.

Runoff outputs from 11 atmosphere–ocean general circulation models (AOGCMs) participating in the fifth phase of Coupled Model Intercomparison Project were used to evaluate the changes in streamflow and agreement among AOGCMs at the end of 21st century. Under the highest emission scenario (Representative Concentration Pathways (RCP) 8.5), high flow is projected to increase in northern high latitudes of Eurasia and North America, Asia, and eastern Africa, while mean and low flows are both projected to decrease in Europe, Middle East, southwestern United States, and Central America. Projected changes under RCP4.5 show similar spatial distribution but with lower magnitude. The model spread of projected changes, however, is found to be large under both scenarios. Bootstrapped Mann–Whitney–Wilcoxon U test revealed that projected changes of streamflow regimes are statistically not significant in 8–32% (19–59%) of the world under RCP8.5 (RCP4.5). The model agreement on projected increase or decrease in mean and high flows is stronger under RCP8.5 than that under RCP4.5. On the other hand, the projected changes in low flow are robust in both scenarios with strong model agreement. In ∼7% (4%) of the world, high flow is projected to increase and low flow is projected to decrease, whereas in ∼29% (13%) all mean, high, and low flows are projected to increase under RCP8.5 (RCP4.5).

Ethanol produced from cellulosic feedstocks has garnered significant interest for greenhouse gas abatement and energy security promotion. One outstanding question in the development of a mature cellulosic ethanol industry is the optimal scale of biorefining activities. This question is important for companies and entrepreneurs seeking to construct and operate cellulosic ethanol biorefineries as it determines the size of investment needed and the amount of feedstock for which they must contract. The question also has important implications for the nature and location of lifecycle environmental impacts from cellulosic ethanol. We use an optimization framework similar to previous studies, but add richer details by treating many of these critical parameters as random variables and incorporating a stochastic sub-model for land conversion. We then use Monte Carlo simulation to obtain a probability distribution for the optimal scale of a biorefinery using a fermentation process and miscanthus feedstock. We find a bimodal distribution with a high peak at around 10–30 MMgal yr⁻¹ (representing circumstances where a relatively low percentage of farmers elect to participate in miscanthus cultivation) and a lower and flatter peak between 150 and 250 MMgal yr⁻¹ (representing more typically assumed land-conversion conditions). This distribution leads to useful insights; in particular, the asymmetry of the distribution—with significantly more mass on the low side—indicates that developers of cellulosic ethanol biorefineries may wish to exercise caution in scale-up.

Many empirical hurricane economic loss models consider only wind speed and neglect storm size. These models may be inadequate in accurately predicting the losses of super-sized storms, such as Hurricane Sandy in 2012. In this study, we examined the dependences of normalized US hurricane loss on both wind speed and storm size for 73 tropical cyclones that made landfall in the US from 1988 through 2012. A multi-variate least squares regression is used to construct a hurricane loss model using both wind speed and size as predictors. Using maximum wind speed and size together captures more variance of losses than using wind speed or size alone. It is found that normalized hurricane loss (L) approximately follows a power law relation with maximum wind speed (V_max) and size (R), L = 10^cV_max^aR^b, with c determining an overall scaling factor and the exponents a and b generally ranging between 4–12 and 2–4 respectively. Both a and b tend to increase with stronger wind speed. Hurricane Sandy's size was about three times of the average size of all hurricanes analyzed. Based on the bi-variate regression model that explains the most variance for hurricanes, Hurricane Sandy's loss would be approximately 20 times smaller if its size were of the average size with maximum wind speed unchanged. It is important to revise conventional empirical hurricane loss models that are only dependent on maximum wind speed to include both maximum wind speed and size as predictors.

Some studies showed that since the 1980s Modoki activity—a different sea surface temperature anomaly pattern from canonical El Niño–Southern Oscillation (ENSO) in the tropics—has been increasing in frequency. In the light of an analysis of the observations and simulations, we found that Modoki, as a new driver of global climate change, can modulate the tropical upwelling that significantly affects mid-lower stratospheric ozone. As a result, it has an important impact on the variations of tropical total column ozone (TCO), alongside quasi-biennial oscillation or canonical ENSO. Our results suggest that, in the context of future global warming, Modoki activity may continue to be a primary driver of tropical TCO changes. Besides, it is possible can serve as a predictor of tropical TCO variations since Modoki events precede tropical ozone changes.

Persistent contrails are an important climate impact of aviation which could potentially be reduced by re-routing aircraft to avoid contrailing; however this generally increases both the flight length and its corresponding CO$_{2}$ emissions. Here, we provide a simple framework to assess the trade-off between the climate impact of CO$_{2}$ emissions and contrails for a single flight, in terms of the absolute global warming potential and absolute global temperature potential metrics for time horizons of 20, 50 and 100 years. We use the framework to illustrate the maximum extra distance (with no altitude changes) that can be added to a flight and still reduce its overall climate impact. Small aircraft can fly up to four times further to avoid contrailing than large aircraft. The results have a strong dependence on the applied metric and time horizon. Applying a conservative estimate of the uncertainty in the contrail radiative forcing and climate efficacy leads to a factor of 20 difference in the maximum extra distance that could be flown to avoid a contrail. The impact of re-routing on other climatically-important aviation emissions could also be considered in this framework.

The link between subsurface fluid injection and induced seismicity has gained recent significance with an increase in earthquakes associated with the disposal of oilfield waste fluids. There are obvious similarities between wastewater reinjection and proposed CO₂ storage (CCS) operations. However, as well as the seismic hazard, induced seismicity during CCS operations poses additional risks, because an induced event located above the target reservoir could compromise the hydraulic integrity of the caprock. In this paper we re-examine case examples where earthquakes have been induced by wastewater injection into deep aquifers in the light of proposed future CCS operations. In particular we consider possible controls on event magnitudes, and look at the spatial distributions of events. We find that the majority of events are located below the target reservoirs. This is an encouraging observation from the perspective of caprock integrity, although it presents a challenge in terms of pre-injection characterization of deep-lying faults several kilometres below the target zone. We observe that 99% of events are found within 20 km of injection wells, suggesting a minimum radius for geomechanical characterization and monitoring. We conclude by making recommendations for modelling and monitoring strategies to be followed prior to and during commercial-scale deployment of CO₂ storage projects.

The discrepancy between recent observed and simulated trends in global mean surface temperature has provoked a debate about possible causes and implications for future climate change projections. However, little has been said in this discussion about observed and simulated trends in global temperature extremes. Here we assess trend patterns in temperature extremes and evaluate the consistency between observed and simulated temperature extremes over the past four decades (1971–2010) in comparison to the recent 15 years (1996–2010). We consider the coldest night and warmest day in a year in the observational dataset HadEX2 and in the current generation of global climate models (CMIP5). In general, the observed trends fall within the simulated range of trends, with better consistency for the longer period. Spatial trend patterns differ for the warm and cold extremes, with the warm extremes showing continuous positive trends across the globe and the cold extremes exhibiting a coherent cooling pattern across the Northern Hemisphere mid-latitudes that has emerged in the recent 15 years and is not reproduced by the models. This regional inconsistency between models and observations might be a key to understanding the recent hiatus in global mean temperature warming.

Historical and 21st century global precipitation changes are investigated using data from the fifth Coupled Model Intercomparison Project (CMIP5) Atmosphere-Ocean-General-Circulation-Models (AOGCMs) and a simple energy-balance model. In the simple model, precipitation change in response to a given top-of-atmosphere radiative forcing is calculated as the sum of a response to the surface warming and a direct 'adjustment' response to the atmospheric radiative forcing. This simple model allows the adjustment in global mean precipitation to atmospheric radiative forcing from different forcing agents to be examined separately and emulates the AOGCMs well. During the historical period the AOGCMs simulate little global precipitation change despite an increase in global temperature—at the end of the historical period, global multi-model mean precipitation has increased by about 0.03 mm day⁻¹, while the global multi-model mean surface temperature has warmed by about 1 K, both relative to the pre-industrial control means. This is because there is a large direct effect from CO₂ and black carbon atmospheric forcing that opposes the increase in precipitation from surface warming. In the 21st century scenarios, the opposing effect from black carbon declines and the increase in global precipitation due to surface warming dominates. The cause of the spread between models in the global precipitation projections (which can be up to 0.25 mm day⁻¹) is examined and found to come mainly from uncertainty in the climate sensitivity. The spatial distribution of precipitation change is found to be dominated by the response to surface warming. It is concluded that AOGCM global precipitation projections are in line with expectations based on our understanding of how the energy and water cycles are physically linked.

Urban agriculture (UA) has been drawing a lot of attention recently for several reasons: the majority of the world population has shifted from living in rural to urban areas; the environmental impact of agriculture is a matter of rising concern; and food insecurity, especially the accessibility of food, remains a major challenge. UA has often been proposed as a solution to some of these issues, for example by producing food in places where population density is highest, reducing transportation costs, connecting people directly to food systems and using urban areas efficiently. However, to date no study has examined how much food could actually be produced in urban areas at the global scale. Here we use a simple approach, based on different global-scale datasets, to assess to what extent UA is constrained by the existing amount of urban space. Our results suggest that UA would require roughly one third of the total global urban area to meet the global vegetable consumption of urban dwellers. This estimate does not consider how much urban area may actually be suitable and available for UA, which likely varies substantially around the world and according to the type of UA performed. Further, this global average value masks variations of more than two orders of magnitude among individual countries. The variations in the space required across countries derive mostly from variations in urban population density, and much less from variations in yields or per capita consumption. Overall, the space required is regrettably the highest where UA is most needed, i.e., in more food insecure countries. We also show that smaller urban clusters (i.e., <100 km² each) together represent about two thirds of the global urban extent; thus UA discourse and policies should not focus on large cities exclusively, but should also target smaller urban areas that offer the greatest potential in terms of physical space.

This study assessed trends in the variability of soil temperature (T_SOIL) using spatially averaged observation records from Russian meteorological land stations. The contributions of surface air temperature (SAT) and snow depth (SND) to T_SOIL variation were quantitatively evaluated. Composite time series of these data revealed positive trends during the period of 1921–2011, with accelerated increases since the 1970s. The T_SOIL warming rate over the entire period was faster than the SAT warming rate in both permafrost and non-permafrost regions, suggesting that SND contributes to T_SOIL warming. Statistical analysis revealed that the highest correlation between SND and T_SOIL was in eastern Siberia, which is underlain by permafrost. SND in this region accounted for 50% or more of the observed variation in T_SOIL. T_SOIL in the non-permafrost region of western Siberia was significantly correlated with changes in SAT. Thus, the main factors associated with T_SOIL variation differed between permafrost and non-permafrost regions. This finding underscores the importance of including SND data when assessing historical and future variations and trends of permafrost in the Northern Hemisphere.

Ammonia (NH₃) is the primary alkaline gas in the atmosphere that contributes to formation of secondary particles. Emission of NH₃ from vehicles, particularly gasoline powered light duty vehicles equipped with three-way catalysts, is regarded as an important source apart from emissions from animal wastes and soils, yet measured emission factors for motor vehicles are still not available in China, where traffic-related emission has become an increasingly important source of air pollutants in urban areas. Here we present our tunnel tests for NH₃ from motor vehicles under 'real world conditions' in an urban roadway tunnel in Guangzhou, a central city in the Pearl River Delta (PRD) region in south China. By attributing all NH₃ emissions in the tunnel to light-duty gasoline vehicles, we obtained a fuel-based emission rate of 2.92 ± 0.18 g L⁻¹ and a mileage-based emission factor of 229.5 ± 14.1 mg km⁻¹. These emission factors were much higher than those measured in the United States while measured NO_x emission factors (7.17 ± 0.60 g L⁻¹ or 0.56 ± 0.05 g km⁻¹) were contrastingly near or lower than those previously estimated by MOBILE/PART5 or COPERT IV models. Based on the NH₃ emission factors from this study, on-road vehicles accounted for 8.1% of NH₃ emissions in the PRD region in 2006 instead of 2.5% as estimated in a previous study using emission factors taken from the Emission Inventory Improvement Program (EIIP) in the United States.

Agriculture is closely affected by climate. Over the past decade, biofuels have emerged as another important factor shaping the agricultural sector. We ask whether the presence of the US ethanol sector can play a role in moderating increases in US corn price variability, projected to occur in response to near-term global warming. Our findings suggest that the answer to this question depends heavily on the underlying forces shaping the ethanol industry. If mandate-driven, there is little doubt that the presence of the corn-ethanol sector will exacerbate price volatility. However, if market-driven, then the emergence of the corn-ethanol sector can be a double-edged sword for corn price volatility, possibly cushioning the impact of increased climate driven supply volatility, but also inheriting volatility from the newly integrated energy markets via crude oil price fluctuations. We find that empirically the former effect dominates, reducing price volatility by 27%. In contrast, mandates on ethanol production increase future price volatility by 54% in under future climate after 2020. We also consider the potential for liberalized international corn trade to cushion corn price volatility in the US. Our results suggest that allowing corn to move freely internationally serves to reduce the impact of near-term climate change on US corn price volatility by 8%.

The land-use sector can contribute to climate change mitigation not only by reducing greenhouse gas (GHG) emissions, but also by increasing carbon uptake from the atmosphere and thereby creating negative CO₂ emissions. In this paper, we investigate two land-based climate change mitigation strategies for carbon removal: (1) afforestation and (2) bioenergy in combination with carbon capture and storage technology (bioenergy CCS). In our approach, a global tax on GHG emissions aimed at ambitious climate change mitigation incentivizes land-based mitigation by penalizing positive and rewarding negative CO₂ emissions from the land-use system. We analyze afforestation and bioenergy CCS as standalone and combined mitigation strategies. We find that afforestation is a cost-efficient strategy for carbon removal at relatively low carbon prices, while bioenergy CCS becomes competitive only at higher prices. According to our results, cumulative carbon removal due to afforestation and bioenergy CCS is similar at the end of 21st century (600–700 GtCO₂), while land-demand for afforestation is much higher compared to bioenergy CCS. In the combined setting, we identify competition for land, but the impact on the mitigation potential (1000 GtCO₂) is partially alleviated by productivity increases in the agricultural sector. Moreover, our results indicate that early-century afforestation presumably will not negatively impact carbon removal due to bioenergy CCS in the second half of the 21st century. A sensitivity analysis shows that land-based mitigation is very sensitive to different levels of GHG taxes. Besides that, the mitigation potential of bioenergy CCS highly depends on the development of future bioenergy yields and the availability of geological carbon storage, while for afforestation projects the length of the crediting period is crucial.

The increasing demand for agricultural products and the uncertainty of international food markets has recently drawn the attention of governments and agribusiness firms toward investments in productive agricultural land, mostly in the developing world. The targeted countries are typically located in regions that have remained only marginally utilized because of lack of modern technology. It is expected that in the long run large scale land acquisitions (LSLAs) for commercial farming will bring the technology required to close the existing crops yield gaps. While the extent of the acquired land and the associated appropriation of freshwater resources have been investigated in detail, the amount of food this land can produce and the number of people it could feed still need to be quantified. Here we use a unique dataset of land deals to provide a global quantitative assessment of the rates of crop and food appropriation potentially associated with LSLAs. We show how up to 300–550 million people could be fed by crops grown in the acquired land, should these investments in agriculture improve crop production and close the yield gap. In contrast, about 190–370 million people could be supported by this land without closing of the yield gap. These numbers raise some concern because the food produced in the acquired land is typically exported to other regions, while the target countries exhibit high levels of malnourishment. Conversely, if used for domestic consumption, the crops harvested in the acquired land could ensure food security to the local populations.

Globally, urban areas are expanding, and their regional, spatially cumulative, environmental impacts from transportation projects are not typically assessed. However, incorporation of a Regional Advance Mitigation Planning (RAMP) framework can promote more effective, ecologically sound, and less expensive environmental mitigation. As a demonstration of the first phase of the RAMP framework, we assessed environmental impacts from 181 planned transportation projects in the 19 368 km² San Francisco Bay Area. We found that 107 road and railroad projects will impact 2411–3490 ha of habitat supporting 30–43 threatened or endangered species. In addition, 1175 ha of impacts to agriculture and native vegetation are expected, as well as 125 crossings of waterways supporting anadromous fish species. The extent of these spatially cumulative impacts shows the need for a regional approach to associated environmental offsets. Many of the impacts were comprised of numerous small projects, where project-by-project mitigation would result in increased transaction costs, land costs, and lost project time. Ecological gains can be made if a regional approach is taken through the avoidance of small-sized reserves and the ability to target parcels for acquisition that fit within conservation planning designs. The methods are straightforward, and can be used in other metropolitan areas.

Several lines of evidence suggest that the warming climate plays a vital role in driving certain types of extreme weather. The impact of warming and of extreme weather on forest carbon assimilation capacity is poorly known. Filling this knowledge gap is critical towards understanding the amount of carbon that forests can hold. Here, we used a perfect-deficit approach to identify forest canopy photosynthetic capacity (CPC) deficits and analyze how they correlate to climate extremes, based on observational data measured by the eddy covariance method at 27 forest sites over 146 site-years. We found that droughts severely affect the carbon assimilation capacities of evergreen broadleaf forest (EBF) and deciduous broadleaf forest. The carbon assimilation capacities of Mediterranean forests were highly sensitive to climate extremes, while marine forest climates tended to be insensitive to climate extremes. Our estimates suggest an average global reduction of forest CPC due to unfavorable climate extremes of 6.3 Pg C (∼5.2% of global gross primary production) per growing season over 2001–2010, with EBFs contributing 52% of the total reduction.

Northern sub-Saharan Africa (NSSA) has a wide variety of climate zones or biomes, where albedo dynamics are highly coupled with vegetation dynamics and fire disturbances. Quantifying surface albedo variations due to fire disturbances on time scales of several months to several years is complex and is made worse by lack of accurate and spatially consistent surface albedo data. Here, we estimate the surface albedo effect from wildfires in different land cover types in the NSSA region using Moderate Resolution Imaging Spectroradiometer (MODIS) multi-year observational data (2003–11). The average decrease in albedo after fires at the scale of 1 km MODIS footprint is −0.002 02 ± 0.000 03 for woody savanna and −0.002 22 ± 0.000 03 for savanna. These two land cover types together account for >86% of the total MODIS fire count between 2003 and 2011. We found that only a small fraction of the pixels (≦̸10%) burn in two successive years and about 47% had any fire recurrence in 9 years. The study also derived the trajectories of post-fire albedo dynamics from the percentages of pixels that recover to pre-fire albedo values each year. We found that the persistence of surface albedo darkening in most land cover types in the NSSA region is limited to about 6–7 years, after which at least 99% of the burnt pixels recover to their pre-fire albedo. Our results provide critical information for deriving necessary input to various models used in determining the effects of albedo change due to wild fires in the NSSA region.

Prehistoric and early historic human cultures are known to be closely connected to and dependent on their natural environments. We test the hypothesis that climate change influenced the means of subsistence of ancient tribes and favored agricultural or cattle herding economic strategies. Our study area is the Khakass–Minusinsk Hollow, located in the foothills of the Sayan Mountains, south-central Siberia, which was, for a few millennia, a buffer zone for human migrations across the Great Eurasian Steppe. Three different methods (the Montane BioClimatic Model, MontBCliM; the biomization method; and the actualizm method) are employed to reconstruct vegetation taken from the fossil pollen of sediment cores in two mountain lakes at eleven time slices related to successive human cultures back to the mid-Holocene. MontBCliM model is used inversely to convert site paleo-vegetation into site paleo-climates. Climate-based regression models are developed and applied to reconstructed climates to evaluate possible pasture and grain crops for these time slices. Pollen-based reconstructions of the climate fluctuations uncovered several dry periods with steppe and forest-steppe and wetter periods with forests since 6000 BP. Grasslands increased by an order of magnitude during the dry periods and provided extensive open space suitable for pastoralism; however, both grain and pasture yields decreased during these dry periods. During wetter climates, both grain and pasture yields increased twofold and supported more fixed human settlements centered around farming and cattle herding. Thus, the dry periods favored pastoralist rather than farming activities. Conversely, tribes that practiced agriculture had some advantage in the wet periods.

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