Table of contents

Lark et al (2015 Environ. Res. Lett.10 044003), analyze recent shifts in US agricultural land use (2008–2012) using newly-available, high-resolution geospatial information, the Cropland Data Layer. Cropland expansion documented by Lark et al suggests the need to reform national agricultural policies in the wake of an emerging, new era of US agriculture characterized by rapid land cover/land use change.

Previous studies have offered strong evidence that grazers alter the vegetation composition and ecosystem carbon (C) balance in ecosystems. In Arctic peatlands, however, the role of grazing has remained largely uninvestigated. Falk et al (2015 Environ. Res. Lett.10 045001) showed that grazing by muskoxen in a high Arctic mire significantly affected both the vegetation and release of greenhouse gases. This finding highlights the potential of grazers to alter ecosystem processes in Arctic peatlands and, thus, to act as a major player in the global C budget.

Cities are hotspots of socio-economic activities and greenhouse gas emissions. The aim of this study was to extend the research range of the urban carbon footprint (CF) to cover emissions embodied in products traded among regions and intra-city sectors. Using Xiamen City as a study case, the total urban-related emissions were evaluated, and the carbon flows among regions and intra-city sectors were tracked. Then five urban CF accountings were evaluated, including purely geographic accounting (PGA), community-wide infrastructure footprint (CIF), and consumption-based footprint (CBF) methods, as well as the newly defined production-based footprint (PBF) and purely production footprint (PPF). Research results show that the total urban-related emissions of Xiamen City in 2010 were 55.2 Mt CO₂e/y, of which total carbon flow among regions or intra-city sectors accounted for 53.7 Mt CO₂e/y. Within the total carbon flow, import and export respectively accounted for 59 and 65%, highlighting the importance of emissions embodied in trade. By regional trade balance, North America and Europe were the largest net carbon exported-to regions, and Mainland China and Taiwan the largest net carbon imported-from regions. Among intra-sector carbon flows, manufacturing was the largest emission-consuming sector of the total urban carbon flow, accounting for 77.4, and 98% of carbon export was through industrial products trade. By the PBF, PPF, CIF, PGA and CBF methods, the urban CFs were respectively 53.7 Mt CO₂e/y, 44.8 Mt CO₂e/y, 28.4 Mt CO₂e/y, 23.7 Mt CO₂e/y, and 19.0 Mt CO₂e/y, so all of the other four CFs were higher than the CBF. All of these results indicate that urban carbon mitigation must consider the supply chain management of imported goods, the production efficiency within the city, the consumption patterns of urban consumers, and the responsibility of the ultimate consumers outside the city.

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.

On average, three tropical cyclones (TCs) affect the Republic of Korea each year, causing extensive damage. To alleviate the TC-induced disasters, the Korean government has invested nearly 4% of its annual budget in recent decades in prevention efforts; however, the effectiveness of this costly program has not been evaluated. This study determined whether any evidence shows a reduced vulnerability to TCs in Korea over 1979–2010 by utilizing multi-linear regression. Homelessness, casualties, and property losses were individually examined. These explained variables were normalized into the socio-economic circumstances of 2005 before the regression to eliminate the effect of changing exposure by dealing with population and wealth at provincial levels. Three potential explanatory variables based on nationwide weather-station data were considered, including the maximum wind, maximum rainfall, and number of affected stations over each TC's damaging period. In addition, the annual per capita income, showing a quasi-linear increasing tendency, was used as an additional explanatory variable to examine how vulnerability is altered. The results revealed that each empirical model of homelessness, casualties, and property losses can account for 47%, 57%, and 57% of each variance, respectively, which is highest when considering all four explanatory variables. Consistently negative coefficients of the per capita income terms for all damage types suggest that the vulnerability to TCs has been significantly reduced. This finding appears to be partly the result of the national prevention effort, although it also can be attributed to other unintended adaptation factors, such as building codes, industrial structures, and land use.

An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O₃) and fine particulate matter (PM_2.5) levels as a result of large changes in biogenic emissions. Using the Community Earth System Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O₃ increases of 5–27 ppb in India, 1–9 ppb in China, and 1–6 ppb in the United States, with peak PM_2.5 increases of up to 2 μg m⁻³. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10–100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.

In this study, we examine a supply-chain approach to more effectively mitigate primary PM_2.5 emissions in China from the perspectives of production, consumption and their linkages using structural path analysis. We identify the pattern of all supply chain paths using principal component analysis. To address the severe haze problems in China, it is important to understand how final demand purchase initiates production processes and ultimately leads to primary PM_2.5 emission. We found that consumers' demands on power and transportation mainly induce direct emissions, quite different from the demands on construction, industry and service products which largely drive emissions in upstream activities. We also found that nearly 80% of the economic sectors in China follow a similar pattern in generating primary PM_2.5 emissions in electricity, cement and the ferrous metal industries; but only the construction sector increases the release of PM_2.5 due to the production of non-metallic mineral products. These findings indicate that further reduction of end-of-pipe emissions in the power and transportation sectors will facilitate cleaner production in almost all the economic sectors. However, for urbanization induced emissions, China should mitigate PM_2.5 emissions through the supply chain of construction, either severely reducing its life-cycle intensity or carefully planning to avoid extensive, unnecessary building activity.

The Indian summer monsoon rainfall (ISMR) contributes nearly 80% of the annual rainfall over India and has a significant influence on the country's gross domestic product through the agricultural sector. Onset of the ISMR displays substantial interannual variability and controls the crop calendar and hence the agricultural output. This variability is traditionally linked to sea surface temperature (SST) anomalies over the tropical Pacific Ocean. The tropical Pacific SST underwent a regime shift during 1976/77. We report a prominent delay in the Indian summer monsoon (ISM) onset following the regime shift. The onset dates are computed with the Hydrologic Onset and Withdrawal Index, based on vertically integrated moisture transport over the Arabian Sea (AS). The shift in onset is found to be due to the change in moisture availability over the AS. A delay in the development of easterly vertical shear reduces northward-propagating intraseasonal variability during May–June, limiting the moisture supply from the equatorial Indian Ocean (IO) to the AS. This, along with enhanced precipitation over the IO during the pre-monsoon, drives a reduction in moisture availability over the AS region from pre- to post-1976/77, delaying the ISM onset in recent decades. Our findings highlight the need for the re-assessment of the crop calendar in India, which is now based on the mean onset date computed from long-term data, without considering the regime shift or trends in onset.

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.

Rivers of the world discharge about 36000 km³ of freshwater into the ocean every year. To investigate the impact of river discharge on climate, we have carried out two 100 year simulations using the Community Climate System Model (CCSM3), one including the river runoff into the ocean and the other excluding it. When the river discharge is shut off, global average sea surface temperature (SST) rises by about 0.5°C and the Indian Summer Monsoon Rainfall (ISMR) increases by about 10% of the seasonal total with large increase in the eastern Bay of Bengal and along the west coast of India. In addition, the frequency of occurrence of La Niña-like cooling events in the equatorial Pacific increases and the correlation between ISMR and Pacific SST anomalies become stronger. The teleconnection between the SST anomalies in the Pacific and monsoon is effected via upper tropospheric meridional temperature gradient and the North African–Asian Jet axis.

Heat waves (HWs) are projected to become more frequent and last longer over most land areas in the late 21st century, which raises serious public health concerns. Urban residents face higher health risks due to synergies between HWs and urban heat islands (UHIs) (i.e., UHIs are higher under HW conditions). However, the responses of urban and rural surface energy budgets to HWs are still largely unknown. This study analyzes observations from two flux towers in Beijing, China and reveals significant differences between the responses of urban and rural (cropland) ecosystems to HWs. It is found that UHIs increase significantly during HWs, especially during the nighttime, implying synergies between HWs and UHIs. Results indicate that the urban site receives more incoming shortwave radiation and longwave radiation due to HWs as compared to the rural site, resulting in a larger radiative energy input into the urban surface energy budget. Changes in turbulent heat fluxes also diverge strongly for the urban site and the rural site: latent heat fluxes increase more significantly at the rural site due to abundant available water, while sensible heat fluxes and possibly heat storage increase more at the urban site. These comparisons suggest that the contrasting responses of urban and rural surface energy budgets to HWs are responsible for the synergies between HWs and UHIs. As a result, urban mitigation and adaption strategies such as the use of green roofs and white roofs are needed in order to mitigate the impact of these synergies.

Fire emissions associated with land cover change and land management contribute to the concentrations of atmospheric pollutants, which can affect regional air quality and climate. Mitigating these impacts requires a comprehensive understanding of the relationship between fires and different land cover change trajectories and land management strategies. We develop future fire emissions inventories from 2010–2030 for Sumatra and Kalimantan (Indonesian Borneo) to assess the impact of varying levels of forest and peatland conservation on air quality in Equatorial Asia. To compile these inventories, we combine detailed land cover information from published maps of forest extent, satellite fire radiative power observations, fire emissions from the Global Fire Emissions Database, and spatially explicit future land cover projections using a land cover change model. We apply the sensitivities of mean smoke concentrations to Indonesian fire emissions, calculated by the GEOS-Chem adjoint model, to our scenario-based future fire emissions inventories to quantify the different impacts of fires on surface air quality across Equatorial Asia. We find that public health impacts are highly sensitive to the location of fires, with emissions from Sumatra contributing more to smoke concentrations at population centers across the region than Kalimantan, which had higher emissions by more than a factor of two. Compared to business-as-usual projections, protecting peatlands from fires reduces smoke concentrations in the cities of Singapore and Palembang by 70% and 40%, and by 60% for the Equatorial Asian region, weighted by the population in each grid cell. Our results indicate the importance of focusing conservation priorities on protecting both forested (intact or logged) peatlands and non-forested peatlands from fire, even after considering potential leakage of deforestation pressure to other areas, in order to limit the impact of fire emissions on atmospheric smoke concentrations and subsequent health effects.

Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering not just water and carbon cycling, biodiversity, and climate, but also demography, public health, and economy. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. We developed a method to map the urban extent from the defense meteorological satellite program/operational linescan system nighttime stable-light data at the global level and created a new global 1 km urban extent map for the year 2000. Our map shows that globally, urban is about 0.5% of total land area but ranges widely at the regional level, from 0.1% in Oceania to 2.3% in Europe. At the country level, urbanized land varies from about 0.01 to 10%, but is lower than 1% for most (70%) countries. Urbanization follows land mass distribution, as anticipated, with the highest concentration between 30° N and 45° N latitude and the largest longitudinal peak around 80° W. Based on a sensitivity analysis and comparison with other global urban area products, we found that our global product of urban areas provides a reliable estimate of global urban areas and offers the potential for producing a time-series of urban area maps for temporal dynamics analyses.

During the Soviet Virgin Lands Campaign, approximately 23 million hectares (Mha) of Eurasian steppe grassland were converted into cropland in Northern Kazakhstan from 1954 to 1963. As a result Kazakhstan became an important breadbasket of the former Soviet Union. However, the collapse of the Soviet Union in 1991 triggered widespread agricultural abandonment, and much cropland reverted to grasslands. Our goal in this study was to reconstruct and analyze agricultural land-cover change since the eve of the Virgin Lands Campaign, from 1953 to 2010 in Kostanay Province, a region that is representative of Northern Kazakhstan. Further, we assessed the potential of currently idle cropland for re-cultivation. We reconstructed the cropland extent before and after the Virgin Lands Campaign using archival maps, and we mapped the agricultural land cover in the late Soviet and post-Soviet period using multi-seasonal Landsat TM/ETM+ images from circa 1990, 2000 and 2010. Cropland extent peaked at approximately 3.1 Mha in our study area in 1990, 38% of which had been converted from grasslands from 1954 to 1961. After the collapse of the Soviet Union, 45% of the Soviet cropland was abandoned and had reverted to grassland by 2000. After 2000, cropland contraction and re-cultivation were balanced. Using spatial logistic regressions we found that cropland expansion during the Virgin Lands Campaign was significantly associated with favorable agro-environmental conditions. In contrast, cropland expansion after the Campaign until 1990, as well as cropland contraction after 1990, occurred mainly in areas that were less favorable for agriculture. Cropland re-cultivation after 2000 was occurring on lands with relatively favorable agro-environmental conditions in comparison to remaining idle croplands, albeit with much lower agro-environmental endowment compared to stable croplands from 1990 to 2010. In sum, we found that cropland production potentials of the currently uncultivated areas are much lower than commonly believed, and further cropland expansion is only possible at the expense of marginal lands. Our results suggest if increasing production is a goal, improving crop yields in currently cultivated lands should be a focus, whereas extensive livestock grazing as well as the conservation of non-provisioning ecosystem services and biodiversity should be priority on more marginal lands.

Climate variability and extremes are expected to increase due to climate change; this may have significant negative impacts for agricultural production. Previous work has primarily focused on the impact of mean growing season temperature and precipitation on rainfed crop yields with little work on irrigated crop yields or climate extremes and their timing. County-level crop yields and daily precipitation and temperature data are pooled to quantify the impact of climate variability and extremes on four major staple crops in the United States. Conditional density plots are used to graphically explore the relationship between climate extremes and crop yields, thereby avoiding assumptions about linearity or underlying probability distributions. Non-linear and threshold-type relationships exist between yields and both precipitation and temperature climate indices; irrigation significantly reduces the impact of all climate indices. In some cases, this occurs by shifting the threshold, such that a more extreme weather event is necessary to negatively impact yields. In other cases, irrigation essentially decouples the crop yields from climate. This work demonstrates that irrigation may be a beneficial adaptation mechanism to changes in climate extremes in coming decades.

Climate change in Ethiopia is occurring against a backdrop of rapid population growth and urbanization, entrenched poverty and a heavy burden of disease, and there is little information on specific health risks with which to approach adaptation planning and strengthen adaptive capacity. Using detailed household surveys (400 households, 1660 individuals, 100% participation) and focus groups in two informal urban communities in the Southern city of Shashemene, we identified locally relevant hazards and found that climate change is likely to intensify existing problems associated with poverty. We also showed that despite their proximity (situated only 1 km apart) the two communities differ in key characteristics that may affect climate change vulnerability and require nuanced approaches to adaptation. Detailed, community-level research is therefore necessary, especially where other sources of data are lacking, to ensure that adaptation activities in the world's poorest communities address relevant risks.

Eurasian fall snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea-ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea-ice decline in autumn is still under debate. Our analysis is based on snow observations from 820 Russian land stations, moisture transport using a Lagrangian approach derived from meteorological re-analyses. We show that declining sea-ice in the Barents and Kara Seas (BKS) acts as moisture source for the enhanced Western Siberian snow depth as a result of changed tropospheric moisture transport. Transient disturbances enter the continent from the BKS region related to anomalies in the planetary wave pattern and move southward along the Ural mountains where they merge into the extension of the Mediterranean storm track.

Methane is the second most powerful carbon-based greenhouse gas in the atmosphere and its production in the natural environment through methanogenesis is positively correlated with temperature. Recent field studies showed that methane emissions from Arctic thermokarst lakes are significant and could increase by two- to four-fold due to global warming. But the estimates of this source are still poorly constrained. By using a process-based climate-sensitive lake biogeochemical model, we estimated that the total amount of methane emissions from Arctic lakes is 11.86 Tg yr⁻¹, which is in the range of recent estimates of 7.1–17.3 Tg yr⁻¹ and is on the same order of methane emissions from northern high-latitude wetlands. The methane emission rate varies spatially over high latitudes from 110.8 mg CH₄ m⁻² day⁻¹ in Alaska to 12.7 mg CH₄ m⁻² day⁻¹ in northern Europe. Under Representative Concentration Pathways (RCP) 2.6 and 8.5 future climate scenarios, methane emissions from Arctic lakes will increase by 10.3 and 16.2 Tg CH₄ yr⁻¹, respectively, by the end of the 21st century.

The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state.

Understanding the changing nature of the intraseasonal oscillatory (ISO) modes of Indian summer monsoon manifested by active and break phase, and their association with extreme rainfall events are necessary for probabilistic estimation of flood-related risks in a warming climate. Here, using ground-based observed rainfall, we define an index to measure the strength of monsoon ISOs and show that the relative strength of the northward-propagating low-frequency ISO (20–60 days) modes have had a significant decreasing trend during the past six decades, possibly attributed to the weakening of large-scale circulation in the region during monsoon season. This reduction is compensated by a gain in synoptic-scale (3–9 days) variability. The decrease in low-frequency ISO variability is associated with a significant decreasing trend in the percentage of extreme events during the active phase of the monsoon. However, this decrease is balanced by significant increasing trends in the percentage of extreme events in the break and transition phases. We also find a significant rise in the occurrence of extremes during early and late monsoon months, mainly over eastern coastal regions. Our study highlights the redistribution of rainfall intensity among periodic (low-frequency) and non-periodic (extreme) modes in a changing climate scenario.

Terrestrial ecosystems currently sequester about one third of anthropogenic CO₂ emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO₂ by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

The early 21st century was marked by several severe winters over Central Eurasia linked to a blocking anti-cyclone centered south of the Barents Sea. Severe winters in Central Eurasia were frequent in the 1960s when Arctic sea ice cover was anomalously large, and rare in the 1990s featuring considerably less sea ice cover; the 1960s being characterized by a low, the 1990s by a high phase of the North Atlantic Oscillation, the major driver of surface climate variability in Central Eurasia. We performed ensemble simulations with an atmospheric general circulation model using a set of multi-year Arctic sea ice climatologies corresponding to different periods during 1966–2012. The atmospheric response to the strongly reduced sea ice cover of 2005–2012 exhibits a statistically significant anti-cyclonic surface pressure anomaly which is similar to that observed. A similar response is found when the strongly positive sea ice cover anomaly of 1966–1969 drives the model. Basically no significant atmospheric circulation response was simulated when the model was forced by the sea ice cover anomaly of 1990–1995. The results suggest that sea ice cover reduction, through a changed atmospheric circulation, considerably contributed to the recent anomalously cold winters in Central Eurasia. Further, a nonlinear atmospheric circulation response to shrinking sea ice cover is suggested that depends on the background sea ice cover.

Short periods of intense rainfall may be associated with significant impacts on society, particularly urban flooding. Climate model projections have suggested an intensification of precipitation under scenarios of climate change. This is in accordance with the hypothesis that precipitation intensities will increase with temperature according to the thermodynamic Clausius–Clapyeron (CC) relation (a rate of ∼6–7% °C⁻¹)—a warmer atmosphere being capable of holding more moisture. Consequently, CC scaling between temperature and extreme precipitation has been demonstrated in numerous studies and in different locations, with higher than CC scaling (so-called super CC scaling) observed for sub-daily extremes. Here we use a new dataset of UK hourly precipitation to identify seasonal scaling relationships between mean daily temperature and 99th percentile hourly precipitation intensities. Pooling the data for the whole UK indicates only slightly higher than CC scaling in spring and summer at higher temperatures, notably less than the 2xCC scaling observed in other regions. Both the highest hourly intensities and the highest scaling in the UK occur in summer and so for this season the dependency of the scaling relationship on large scale circulation conditions is examined using a set of air flow indices. A shear vorticity index (indicative of large-scale flow cyclonicity) is noted to have the greatest influence on the relationship, approaching 2xCC at higher temperatures when shear vorticity is negative (anticyclonic rotation). An examination of the occurrence of intense events indicates that these can occur under cyclonic and anticyclonic conditions but that in the south-east of England the latter conditions disproportionately favour their occurrence. These results suggest that changes in circulation regimes could modify the expected changes in precipitation intensities prescribed by CC scaling and arising as a consequence of future warming.

Numerous studies have suggested an impact of the 11 year solar cycle on the winter North Atlantic Oscillation (NAO), with an increased tendency for positive (negative) NAO signals to occur at maxima (minima) of the solar cycle. Climate models have successfully reproduced this solar cycle modulation of the NAO, although the magnitude of the effect is often considerably weaker than implied by observations. A leading candidate for the mechanism of solar influence is via the impact of ultraviolet radiation variability on heating rates in the tropical upper stratosphere, and consequently on the meridional temperature gradient and zonal winds. Model simulations show a zonal mean wind anomaly that migrates polewards and downwards through wave–mean flow interaction. On reaching the troposphere this produces a response similar to the winter NAO. Recent analyses of observations have shown that solar cycle–NAO link becomes clearer approximately three years after solar maximum and minimum. Previous modelling studies have been unable to reproduce a lagged response of the observed magnitude. In this study, the impact of solar cycle on the NAO is investigated using an atmosphere–ocean coupled climate model. Simulations that include climate forcings are performed over the period 1960–2009 for two solar forcing scenarios: constant solar irradiance, and time-varying solar irradiance. We show that the model produces significant NAO responses peaking several years after extrema of the solar cycle, persisting even when the solar forcing becomes neutral. This confirms suggestions of a further component to the solar influence on the NAO beyond direct atmospheric heating and its dynamical response. Analysis of simulated upper ocean temperature anomalies confirms that the North Atlantic Ocean provides the memory of the solar forcing required to produce the lagged NAO response. These results have implications for improving skill in decadal predictions of the European and North American winter climate.

Australian air pollution standards are set at national and state levels for a number of chemicals harmful to human health. However, these standards do not need to be met when ad hoc pollution licences are issued by state environment agencies. This situation results in a highly unequal distribution of air pollution between towns and cities, and across the country. This paper examines these pollution regulations through two case studies, specifically considering the ability of the regulatory regime to protect human health from lead and sulphur dioxide pollution in the communities located around smelters. It also considers how the proposed National Clean Air Agreement, once enacted, might serve to reduce this pollution equity problem. Through the case studies we show that there are at least three discrete concerns relating to the current licencing system. They are: non-onerous emission thresholds for polluting industry; temporal averaging thresholds masking emission spikes; and ineffective penalties for breaching licence agreements. In conclusion, we propose a set of new, legally-binding national minimum standards for industrial air pollutants must be developed and enforced, which can only be modified by more (not less) stringent state licence arrangements.

Climate model based projections suggest a drying of the central European summer climate toward the end of the century. In this study we investigate the influence of the spatial resolution of an atmosphere-only climate model (EC-Earth at two resolutions, ∼25 and ∼112 km horizontal) on the simulated summer drying in this area. High resolution models have a more realistic representation of circulation in the current climate and could provide more confidence on future projections of circulation forced drying. We find that the high resolution model is characterized by a stronger drying in spring and summer, mainly forced by circulation changes. The initial spring drying intensifies the summer drying by a positive soil moisture feedback. The results are confirmed by finding analogs of the difference between the high and medium-resolution model circulation in the natural variability in another ensemble of climate model simulations. In the current climate, these show the same precipitation difference pattern resulting from the summer circulation difference. In the future climate the spring circulation also plays a key role. We conclude that the reduction of circulation biases due to increased resolution gives higher confidence in the strong drying trend projected for central Europe by the high-resolution version of the model.