ALBERT

Description: The overall global-scale consequences of climate change are dependent on the distribution of impacts across regions, and there are multiple dimensions to these impacts. This paper presents a global assessment of the potential impacts of climate change across several sectors, using a harmonised set of impacts models forced by the same climate and socio-economic scenarios. Indicators of impact cover the water resources, river and coastal flooding, agriculture, natural environment and built environment sectors. Impacts are assessed under four SRES socio-economic and emissions scenarios, and the effects of uncertainty in the projected pattern of climate change are incorporated by constructing climate scenarios from 21 global climate models. There is considerable uncertainty in projected regional impacts across the climate model scenarios, and coherent assessments of impacts across sectors and regions therefore must be based on each model pattern separately; using ensemble means, for example, reduces variability between sectors and indicators. An example narrative assessment is presented in the paper. Under this narrative approximately 1 billion people would be exposed to increased water resources stress, around 450 million people exposed to increased river flooding, and 1.3 million extra people would be flooded in coastal floods each year. Crop productivity would fall in most regions, and residential energy demands would be reduced in most regions because reduced heating demands would offset higher cooling demands. Most of the global impacts on water stress and flooding would be in Asia, but the proportional impacts in the Middle East North Africa region would be larger. By 2050 there are emerging differences in impact between different emissions and socio-economic scenarios even though the changes in temperature and sea level are similar, and these differences are greater in 2080. However, for all the indicators, the range in projected impacts between different climate models is considerably greater than the range between emissions and socio-economic scenarios.

Description: Climate stabilization efforts must integrate the actions of many socio-economic sectors to be successful in meeting climate stabilization goals, such as limiting atmospheric carbon dioxide (CO 2 ) concentration to be less than double the pre-industrial levels. Estimates of the costs and benefits of stabilization policies are often informed by Integrated Assessment Models (IAMs) of the climate and the economy. These IAMs are highly non-linear with many parameters that abstract globally integrated characteristics of environmental and socio-economic systems. Diagnostic analyses of IAMs can aid in identifying the interdependencies and parametric controls of modeled stabilization policies. Here we report a comprehensive variance-based sensitivity analysis of a doubled-CO 2 stabilization policy scenario generated by the globally-aggregated Dynamic Integrated model of Climate and the Economy (DICE). We find that neglecting uncertainties considerably underestimates damage and mitigation costs associated with a doubled-CO 2 stabilization goal. More than ninety percent of the states-of-the-world (SOWs) sampled in our analysis exceed the damages and abatement costs calculated for the reference case neglecting uncertainties (1.2 trillion 2005 USD, with worst case costs exceeding $60 trillion). We attribute the variance in these costs to uncertainties in the model parameters relating to climate sensitivity, global participation in abatement, and the cost of lower emission energy sources.

Description: In the 9th century BC, Assyrians based in northern Iraq started a relentless process of expansion that within two centuries would see them controlling most of the ancient Near East. Traditional explanations for the decline of the Neo-Assyrian Empire in the 7th century BC have emphasized the role of military conflict, and especially the destruction of the Assyrian capital, Nineveh, by a coalition of Babylonian and Median forces in 612 BC. However, it remains unclear how the Assyrian state, the most powerful military machine of its age and the largest empire the Old World had ever seen up to that time, declined so quickly. In this paper, we highlight two potential factors which may have had some influence upon the Assyrian decline that have not been previously explored. The first is a major increase in the population of the Assyrian heartland area at the dawn of the 7th century BC, which substantially reduced the drought resilience of the region. The second factor is an episode of severe drought affecting large portions of the Near East during the mid-7th century BC. We propose a series of testable hypotheses which detail how the combination of these two factors may have contributed to the development of considerable economic and political instability within the Assyrian Empire, and argue that these demographic and climatic factors played a significant role in its demise.

Description: Cap-and-trade, a regulatory instrument widely used to constrain greenhouse gas and other pollution, has recently been criticized for producing only small amounts of intended emission reductions. This paper looks at the empirical record of cap-and-trade since the beginning in 1995, and shows that emission targets have almost always been easier and cheaper to reach than expected. The five main reasons are generous targets, changes in economic output, fuel price movements, innovation, and complementary emission reduction policies. Overall, this failure to predict mitigation potentials may relate to a psychological “end of history bias,” whereby policymakers, industry, and analysts think that less change will happen in the future than has demonstrably happened in the past. Consequently, more abatement is possible and at lower costs than generally thought, rendering the prices of emission permits hard to predict. For climate research, the findings imply that emission scenarios assuming ever-increasing pollution prices may benefit from integrating recent experience with cap-and-trade regulations. In policy terms, mechanisms such as floor prices need to be considered to guarantee emission reductions under uncertainty.

Description: Existing studies in the context of assessing vulnerability to climate variability and change delineate, rather inadequately, interconnected interactions occurring within the climate-human-environment interaction space. Besides, studies documenting stakeholders’ perceptions regarding climate change induced vulnerabilities are limited in terms of providing indicators for decision-making. This paper aims at constructing a livelihood vulnerability index for climate variability and change capturing interconnected interactions based on peoples’ perceptions while providing indicators for evidence based decision-making. A semi-quantitative fuzzy cognitive mapping (FCM) approach has been deployed to capture peoples’ perceptions of climate induced perturbations and adaptations. This approach helps quantify stakeholders’ perspectives while capturing interconnected interactions in order to estimate livelihood vulnerability to climate variability and change of poor agro-pastoralists in the Bhilwara, a district in Western India. Combining the FCM approach with a sustainable livelihood framework warrants an understanding of assets sensitive to climate variability and change along with those serving as adaptive capacities. The findings of this study confirm that financial and natural assets are most susceptible to harm while organisational and financial assets provide resilience against climate variability and change. The results suggest that livelihood vulnerability of agro-pastoralists lie in the range of being ‘vulnerable’ to climate variability and change while varying across three seasons summer, winter, and rainfall.

Description: Recent literature, the US Global Change Research Program’s National Climate Assessment, and recent events, such as Hurricane Sandy, highlight the need to take better account of both storm surge and sea-level rise (SLR) in assessing coastal risks of climate change. This study combines three models—a tropical cyclone simulation model; a storm surge model; and a model for economic impact and adaptation—to estimate the joint effects of storm surge and SLR for the US coast through 2100. The model is tested using multiple SLR scenarios, including those incorporating estimates of dynamic ice-sheet melting, two global greenhouse gas (GHG) mitigation policy scenarios, and multiple general circulation model climate sensitivities. The results illustrate that a large area of coastal land and property is at risk of damage from storm surge today; that land area and economic value at risk expands over time as seas rise and as storms become more intense; that adaptation is a cost-effective response to this risk, but residual impacts remain after adaptation measures are in place; that incorporating site-specific episodic storm surge increases national damage estimates by a factor of two relative to SLR-only estimates, with greater impact on the East and Gulf coasts; and that mitigation of GHGs contributes to significant lessening of damages. For a mid-range climate-sensitivity scenario that incorporates dynamic ice sheet melting, the approach yields national estimates of the impacts of storm surge and SLR of $990 billion through 2100 (net of adaptation, cumulative undiscounted 2005$); GHG mitigation policy reduces the impacts of the mid-range climate-sensitivity estimates by $84 to $100 billion.

Description: Climate change impacts on water resources in the United States are likely to be far-reaching and substantial because the water is integral to climate, and the water sector spans many parts of the economy. This paper estimates impacts and damages from five water resource-related models addressing runoff, drought risk, economics of water supply/demand, water stress, and flooding damages. The models differ in the water system assessed, spatial scale, and unit of assessment, but together provide a quantitative and descriptive richness in characterizing water sector effects that no single model can capture. The results, driven by a consistent set of greenhouse gas (GHG) emission and climate scenarios, examine uncertainty from emissions, climate sensitivity, and climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, broad conclusions can be drawn regarding patterns of change and benefits of GHG mitigation. Four key findings emerge: 1) GHG mitigation substantially reduces hydro-climatic impacts on the water sector; 2) GHG mitigation provides substantial national economic benefits in water resources related sectors; 3) the models show a strong signal of wetting for the Eastern US and a strong signal of drying in the Southwest; and 4) unmanaged hydrologic systems impacts show strong correlation with the change in magnitude and direction of precipitation and temperature from climate models, but managed water resource systems and regional economic systems show lower correlation with changes in climate variables due to non-linearities created by water infrastructure and the socio-economic changes in non-climate driven water demand.

Description: Local communities across the Pacific Island region have long prepared for and managed extreme weather events. Strategies to cope with extreme weather, particularly cyclones and droughts, have involved using particular planting techniques, initiating innovative water storage practices, and employing food preservation tactics to survive. These local experiences and knowledge have been passed on between generations through stories and sharing practical know-how; however, very little formal documentation has transpired to date. This research attempts to document and synthesis these experiences and knowledge to safeguard them through written accounts but also demonstrate how Pacific communities can provide valuable, appropriate and effective strategies to prepare for and respond to extreme weather events. In-depth interviews ( n  = 40) were conducted with community members from three villages in Fiji (Naselesele, Qeleni and Yanuca) and three villages in Vanuatu (Piliura, Tassiriki and Lonamilo). While typically missing from community vulnerability and risk assessments in the Pacific, local experiences and knowledge are a core strength in enhancing adaptive capacity and planning community-based activities.

Description: There is now a growing literature emphasizing the critical importance of social variables in the formulation of coastal management policies seeking to tackle climate change impacts. This paper focuses on the role of social capital, which is increasingly identified as having a significant role in climate change adaptation and mitigation strategies. We focus on public perceptions of the social costs and benefits arising from two management options (managed retreat/realignment and hold-the-line), the resulting level of policy acceptability, and how this acceptability is mediated by social capital parameters within coastal communities. These issues are examined by means of a quantitative social survey implemented in Romney Marsh (east Sussex/Kent, UK), an area facing significant impacts from climate change. We tested two models through path analysis with latent structures. The first correlates respondents’ perceived costs and benefits with the level of public acceptability of the two policy options. In the second model, we introduce social capital variables, investigating the impacts on perceived social costs and benefits of the policy options, and the overall effect on the level of public acceptability. Our findings demonstrate: (1) perceived social costs and benefits of proposed policy options influence the level of public acceptability of these policies; (2) these social costs and benefits are connected with the level of public acceptability; and (3) specific social capital parameters (i.e. social trust, institutional trust, social networks and social reciprocity) influence perceived policy costs and benefits, and also have a significant impact on the level of public acceptability of proposed policy options.

Description: A high world demand for crude palm oil has caused a reduction in the area of Indonesia’s tropical rainforests over the past several decades. Our hypothesis is that the expansion of the area devoted to oil palm plantations at the expense of primary and secondary tropical rainforests will increase the local surface temperature. While similar studies of other crops have been reported, this is the first time this particular hypothesis has been investigated and reported using the remote sensing methods described in this paper. In this study, we used remotely sensed data to quantify land use changes from tropical rainforests to oil palm plantations, calculated the surface temperature from thermal infrared data supplied by band 6 of the Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+), examined the correlations of surface temperature to foliage cover, and conducted field work to verify the results obtained using the remotely sensed data. For this study, we used a new spectral index, Principal Polar Spectral Greenness (PPSG), that is potentially more sensitive than other index to small changes in foliage cover at high cover levels. The outcome of satellite image processing is only 0.2 °C different from direct temperature measurement in the field. Our study indicated that less density of the closed-canopy composition of oil palm trees resulted in higher surface temperature.

Description: Using an ensemble of four high resolution (~25 km) regional climate models, this study analyses the future (2021–2050) spatial distribution of seasonal temperature and precipitation extremes in the Ganges river basin based on the SRES A1B emissions scenario. The model validation results (1989–2008) show that the models simulate seasonality and spatial distribution of extreme temperature events better than precipitation. The models are able to capture fine topographical detail in the spatial distribution of indices based on their ability to resolve processes at a higher regional resolution. Future simulations of extreme temperature indices generally agree with expected warming in the Ganges basin, with considerable seasonal and spatial variation. Significantly warmer summers in the central part of the basin along with basin-wide increase in night temperature are expected during the summer and monsoon months. An increase in heavy precipitation indices during monsoon, coupled with extended periods without precipitation during the winter months; indicates an increase in the incidence of extreme events.

Description: Large trees (〉76 cm breast-height diameter) are vital components of Sierra Nevada/Cascades mixed-conifer ecosystems because of their fire resistance, ability to sequester large amounts of carbon, and role as preferred habitat for sensitive species such as the California spotted owl. To investigate the likely performance of large trees in a rapidly changing climate, we analyzed growth rings of five conifer species against 20th century climate trends from local weather stations. Over the local station period of record, there were no temporal trends in precipitation, but maximum temperatures increased by 0.10 to 0.13 °C/decade (summer and autumn), and minimum temperatures increased by 0.11 to 0.19 °C/decade in all seasons. All species responded positively to precipitation, but more variation was explained by a significant positive response to minimum winter temperatures. High maximum summer temperature adversely affected growth of two species, and maximum spring temperatures in the year prior to ring formation were negatively associated with growth of one species. The strong coherent response to increasing minimum temperatures bodes well for growth of large trees in Sierra/Cascades region mixed conifer forest under continued climatic warming, but these trees will still be under threat by the increased fire intensity that is a indirect effect of warming.

Description: We test for the existence of long-term trends in 25- to 50-year long series of monthly rainfall, average river discharges, and minimum air temperatures in Colombia. The Empirical Mode Decomposition method is used as a mathematical filter to decompose a given time series into a finite number of intrinsic mode functions, assuming the coexistence of different frequency oscillatory modes in the series, and that the residual captures the likely existing long-term trends. The Mann-Kendall test for autocorrelated data is used to assess the statistical significance of the identified trends, and the Sen test is used to quantify their magnitudes. Results show that 62 % of river discharge series exhibit significant decreasing trends between 0.01-1.92 m 3 s −1 per year, which are highly consistent downstream albeit with different ratios between the trend magnitudes and mean discharges. Most minimum temperature series (87 %) exhibit increasing trends (0.01-0.08 ° Cyr −1 ). Results for precipitation series are inconclusive owing to the mixing between increasing trends (41 %, between 0.1-7.0 mm yr −1 ) and decreasing trends (44 %, between 0.1-7.4 mm yr −1 ), with no clear-cut geographical pattern, except for the increasing trend identified along the Pacific region, consistent with the increasing trend identified in the strength of the Chocó low-level wind jet off the Pacific coast of Colombia, an important moisture source of continental precipitation. Our results contribute to discerning between signals of climate change and climate variability in tropical South America.

Description: As global warming is scientifically and widely accepted, its impacts at regional scales are raising many questions for wine producers. In particular, climate parameters, especially temperature, play a decisive role in vine growth and grape ripening. An overview of expected climate change in terms of bioclimatic indexes (Winkler and Huglin) and thermal extremes in the wine-producing region of Champagne is presented. A variable-grid atmospheric general circulation model, ARPEGE-Climate, with a local zoom at 50 km over the area of interest, is used to investigate potential future changes in thermal extremes and bioclimatic indexes. Changes in daily maximum and minimum temperatures at key stages are discussed for three emission scenarios (B1, A1B, A2) that are currently used in studies of impacts of climate change. Model outputs are analyzed and critically assessed for a control period (1971–2000) and for changes in extreme events in relation to future scenarios, such as a decrease in extreme low temperatures in spring (April) during bud break and an increase in extreme high temperatures in summer, associated with more frequent heat waves during ripening.

Description: The International Panel on Climate Change (IPCC) has called for a new balance between reducing the risks from climate extremes and transferring them (for example, through insurance) as means for effectively preparing for and managing disaster impacts in a changing climate. This paper elaborates on this balance with an overview of disaster risk financing mechanisms and how they contribute to disaster risk reduction and climate change adaptation in developing countries. We suggest a risk management approach that targets risk reduction and risk financing to different layers of risk, including a layer that represents a possible limit to adaptation. By reviewing traditional post-disaster financial arrangements, such as government compensation, and non-traditional pre-disaster instruments, such as index-based insurance, we show how risk financing can complement and stimulate risk reduction. We discuss the benefits of financial instruments, including the provision of post-disaster finances for recovery and pre-disaster security necessary for climate adaptation and poverty reduction. These benefits come at a cost, and we discuss the risks, challenges, and future prospects of risk financing in developing countries.

Description: Food security in India is tightly linked to rainfall variability. Trends in Indian rainfall records have been extensively studied but the subject remains complicated by the high spatiotemporal variability of rainfall arising from complex atmospheric dynamics. For various reasons past studies have often produced inconsistent results. This paper presents an analysis of recent trends in monthly and seasonal cumulative rainfall depth, number of rainy days and maximum daily rainfall, and in the monsoon occurrence (onset, peak and retreat). A modified version of the Mann-Kendall test, accounting for the scaling effect, was applied to 29 variables derived from square-degree-resolution daily gridded rainfall (1951–2007). The mapping of gridded trend slopes and the regional average Kendall test were used concurrently to assess the field significance of regional trends in areas exhibiting spatial homogeneity in trend directions. The statistics we used account for temporal and spatial correlations, and thus reduce the risk of overestimating the significance of local and regional trends. Our results i/ improve available knowledge (e.g. 5 %-field-significant delay of the monsoon onset in Northern India); ii/ provide a solid statistical basis to previous qualitative observations (e.g. 1 %-field-significant increase/decrease in pre-monsoon rainfall depth in northeast/southwest India); and, iii/ when compared to recent studies, show that the field significance level of regional trends (e.g. in rainfall extremes) is test-dependent. General trend patterns were found to align well with the geography of anthropogenic atmospheric disturbances and their effect on rainfall, confirming the paramount role of global warming in recent rainfall changes.

Description: The Tibetan Plateau has experienced rapid warming like most other alpine regions. Regional assessments show rates of warming comparable with the arctic region and decreasing Asian summer monsoons. We used meteorological station daily precipitation and daily maximum and minimum temperature data from 80 stations in the eastern Tibetan Plateau of southwest China to calculate local variation in the rates and seasonality of change over the last half century (1960–2008). Daily low temperatures during the growing season have increased greatly over the last 24 years (1984–2008). In sites of markedly increased warming (e.g., Deqin, Yunnan and Mangya, Qinghai), daily and growing season daily high temperatures have increased at a rate above 5 °C/100 years. In Deqin, precipitation prior to the 1980s fell as snow whereas in recent decades it has shifted to rain during March and April. These shifts to early spring rains are likely to affect plant communities. Animals like yaks adapted to cold climates are also expected to show impacts with these rising temperatures. This region deserves further investigation to determine how these shifts in climate are affecting local biodiversity and livelihoods.

Description: Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.

Description: Changes in temperature, precipitation, sea level, and coastal storms will likely increase the vulnerability of infrastructure across the United States. Using four models that analyze vulnerability, impacts, and adaptation, this paper estimates impacts to roads, bridges, coastal properties, and urban drainage infrastructure and investigates sensitivity to varying greenhouse gas emission scenarios, climate sensitivities, and global climate models. The results suggest that the impacts of climate change in this sector could be large, especially in the second half of the 21st century as sea-level rises, temperature increases, and precipitation patterns become more extreme and affect the sustainability of long-lived infrastructure. Further, when considering sea-level rise, scenarios which incorporate dynamic ice sheet melting yield impact model results in coastal areas that are roughly 70 to 80 % higher than results that do not incorporate dynamic ice sheet melting. The potential for substantial economic impacts across all infrastructure sectors modeled, however, can be reduced by cost-effective adaptation measures. Mitigation policies also show potential to reduce impacts in the infrastructure sector – a more aggressive mitigation policy reduces impacts by 25 to 35 %, and a somewhat less aggressive policy reduces impacts by 19 to 30 %. The existing suite of models suitable for estimating these damages nonetheless covers only a small portion of expected infrastructure sector effects from climate change, so much work remains to better understand impacts on electric and telecommunications networks, rail, and air transportation systems. In addition, the effects of climate-induced extreme events are likely to be important, but are incompletely understood and remain an emerging area for research.

Description: Developing countries like India are under international pressure to sign a legally binding emissions treaty to avert catastrophic climatic change. Developing countries, however, have argued that any international agreement must be based on historic and per capita carbon emissions, with developed countries responsible for reducing their emissions first and funding mitigation and adaptation in other countries. Recently, however, several scholars have argued that Indian government climate change discourses are shifting, primarily by recognizing the “co-benefits” of an alignment between its development and climate change objectives, and by displaying increasing “flexibility” on mitigation targets. This study investigates the factors driving shifting Indian discourses of climate change by conducting and analyzing 25 interviews of Indian climate policy elites, including scientists, energy policy experts, leading government officials, journalists, business leaders, and advocates, in addition to analysis of articles published in Economic and Political Weekly (a prominent Indian policy journal), and reports published by the government and other agencies. Our analysis suggests that India’s concerns about increasing energy access and security, along with newer concerns about vulnerability to climate change and the international leadership aspirations of the Indian government, along with emergence of new actors and institutions, has led to plurality of discourses, with potential implications for India’s climate change policies.

Description: Effects of climate change are frequently claimed to be responsible for widespread civil violence. Yet, scientists remain divided on this issue, and recent studies suggest that conflict risk increases with higher rainfall, loss of rainfall, higher temperatures or none of the above. Lack of scientific consensus is driven by differences in data, methods, and samples, but may also reflect a fragile and inconsistent correlation for the habitual spatiotemporal domain, Sub-Saharan Africa post-1980. This study presents a comprehensive, multi-scale empirical evaluation of climate-conflict connections across Asia, the continent with the highest conflict rate per country. We find little evidence that interannual climate variability and anomalies are linked to historical conflict risk in the simple and general manner proposed by some earlier research. Although a significant parameter coefficient can be obtained under certain specifications, the direction and magnitude of the climate effects are inconsistent and sensitive to research design. Instead, Asian civil wars share central features with violent events elsewhere, proving the main correlates of contemporary armed conflict to be economic and socio-political rather than climatological.

Description: West Cornwall is the most south westerly part of mainland United Kingdom with a strong maritime climate. This paper analyses the earliest archived instrumental meteorological records collected in West Cornwall (SW England). Observations were obtained from the Met Office archive (Camborne 1957–2010; Culdrose 1985–2011), Trengwainton Garden (1940–2010), and from the Royal Cornwall Polytechnic Society, (data for Falmouth (1880–1952) and Helston (1843–1888)). Homogeneity tests were used (Levene and Brown-Forsythe tests) to exclude any trends not related to climate variability. The data exhibit trends in annual mean and maximum temperatures over the timescales analysed, and show a general temperature increase in the 20th and 21st century. Annual and seasonal temperature change was found to vary locally with strongly positive trends in autumn, spring and summer seasons. Trends in precipitation are positive only for the 19th century and only for one station. Correlation with the North Atlantic Oscillation (NAO) index gives negative results for precipitation data. However correlation with the NAO index is positive with temperature, especially in the winter season. Return period analysis shows a decrease in intensity and frequency of extreme precipitation events in the post-1975 period (Camborne and Trengwainton Garden stations). Climate change in the 20th century and future continued warming is likely to have major implications on biodiversity in this region.

Description: The terrestrial ecosystems of North America have been identified as a sink of atmospheric CO 2 though there is no consensus on the magnitude. However, the emissions of non-CO 2 greenhouse gases (CH 4 and N 2 O) may offset or even overturn the climate cooling effect induced by the CO 2 sink. Using a coupled biogeochemical model, in this study, we have estimated the combined global warming potentials (GWP) of CO 2 , CH 4 and N 2 O fluxes in North American terrestrial ecosystems and quantified the relative contributions of environmental factors to the GWP changes during 1979–2010. The uncertainty range for contemporary global warming potential has been quantified by synthesizing the existing estimates from inventory, forward modeling, and inverse modeling approaches. Our “best estimate” of net GWP for CO 2 , CH 4 and N 2 O fluxes was −0.50 ± 0.27 Pg CO 2 eq/year (1 Pg = 10 15  g) in North American terrestrial ecosystems during 2001–2010. The emissions of CH 4 and N 2 O from terrestrial ecosystems had offset about two thirds (73 %±14 %) of the land CO 2 sink in the North American continent, showing large differences across the three countries, with offset ratios of 57 % ± 8 % in US, 83 % ± 17 % in Canada and 329 % ± 119 % in Mexico. Climate change and elevated tropospheric ozone concentration have contributed the most to GWP increase, while elevated atmospheric CO 2 concentration have contributed the most to GWP reduction. Extreme drought events over certain periods could result in a positive GWP. By integrating the existing estimates, we have found a wide range of uncertainty for the combined GWP. From both climate change science and policy perspectives, it is necessary to integrate ground and satellite observations with models for a more accurate accounting of these three greenhouse gases in North America.

Description: We present an analysis of the inter-annual variability of hydrography—temperature and salinity – and ice conditions at the coastal site of Tvärminne, Gulf of Finland, Baltic Sea during the period 1927–2012. The aim is to analyze the natural variability and trends of the hydrographic characteristics, freezing and breakup dates, ice thickness, and the heat content during the last century. The study also includes the inter-connections between the ice season and the surface temperature and salinity in the open water season. The results showed a significant decrease of the ice season length, by almost 30 days. The maximum annual ice thickness decreased by 8 cm in the last 40 years. The surface water temperature increased by almost 1 °C and there was also an increasing trend in the heat content. The thermal memory of the system was 2–2.5 months. The surface salinity increased by 0.5 psu in the last 85 years. The results are discussed and compared to related studies.

Description: Using case study analysis across three sectors in China (cement, electric vehicles and coal fired electricity generation) and theoretical insights from the innovation studies literature, this paper analyses the development of China’s technological capabilities in low carbon technologies and the ways in which public policies have contributed to developing these capabilities. It finds that China has developed significant capabilities via a strategic approach. The paper’s findings have significant implications for international policies designed to support low carbon technology transfer to developing countries and broader processes of low carbon technological change and development. Such policies should go beyond the traditional focus on the transfer of technology hardware to focus on the development of low carbon technological capabilities in developing country firms.

Description: Our analyses partition the relative influence of progressive climate change and large-scale climate drivers that can be associated with the Quasi-Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), solar sunspot cycle, and multi-decadal oscillations on lake ice breakup dates for thirteen Northern Hemisphere lakes. Oscillatory dynamics explain 26 % of the total variance in the time series compared with 15 % for linear trends, leaving 60 % unexplained and likely attributable, in part, to local weather. Significant oscillatory dynamics include frequencies in 2–3 year periods (9.4 % of the total variance), 3–6 year periods (8.2 %), 10–12 year periods (1.6 %) and various multidecadal periods (0.4–1.3 %). All 13 study lakes, although widely scattered in the Northern Hemisphere, had similar oscillatory dynamics and linear trends, emphasizing that global processes influence lake ice breakup locally. We illustrate that while quasi-periodic dynamics associated with large-scale climate drivers are important, they do not mask the clear evidence for progressive climate change.

Description: This paper develops and applies methods to quantify and monetize projected impacts on terrestrial ecosystem carbon storage and areas burned by wildfires in the contiguous United States under scenarios with and without global greenhouse gas mitigation. The MC1 dynamic global vegetation model is used to develop physical impact projections using three climate models that project a range of future conditions. We also investigate the sensitivity of future climates to different initial conditions of the climate model. Our analysis reveals that mitigation, where global radiative forcing is stabilized at 3.7 W/m 2 in 2100, would consistently reduce areas burned from 2001 to 2100 by tens of millions of hectares. Monetized, these impacts are equivalent to potentially avoiding billions of dollars (discounted) in wildfire response costs. Impacts to terrestrial ecosystem carbon storage are less uniform, but changes are on the order of billions of tons over this time period. The equivalent social value of these changes in carbon storage ranges from hundreds of billions to trillions of dollars (discounted). The magnitude of these results highlights their importance when evaluating climate policy options. However, our results also show national outcomes are driven by a few regions and results are not uniform across regions, time periods, or models. Differences in the results based on the modeling approach and across initializing conditions also raise important questions about how variability in projected climates is accounted for, especially when considering impacts where extreme or threshold conditions are important.

Description: Many models have been developed to explore the likely consequences of climate change. These models tend to focus on single physical or socio-economic sectors and their processes, and neglect the many feedbacks that occur between the different components of the real world. To overcome this problem, models are increasingly being combined in integrated assessment platforms (IAPs), of which the CLIMSAVE IAP is an example, modelling cross-sectoral impacts, adaptation and vulnerability to climate change in Europe by combining 10 different meta-models that focus on specific sectors. Where models are combined in this way, however, attention must be given to the potential errors and uncertainties that integration might introduce. We present a quantitative uncertainty analysis of selected outputs of the CLIMSAVE IAP based on creating and sampling from probability density functions (PDFs) of each of the IAP’s input variables to take account of model and scenario uncertainty. We find limited uncertainties in aggregate outputs of the IAP, which allow specific impacts to be predicted with definable levels of confidence. However, we also find substantial overlap between different socio-economic scenarios at the European scale, suggesting that changes to socio-economic conditions cannot reliably overcome climate-related uncertainty. Nevertheless, there is evidence that particular adaptation actions may significantly alter the impacts of climate change, especially at local or national scales.

Description: Interannual variability over South America (SA) is mainly controlled by the El Niño-Southern Oscillation (ENSO) phenomenon. This study investigates the ENSO precipitation signal during austral spring (September–October–November-SON) over SA. Three global circulation models-GCMs-(MPI, GFDL and HadGEM2) are used for RegCM4 (Regional Climate Model version 4) downscaling of the present (1975–2005) near-future (2020–2050) and far-future (2070–2098) climates using two greenhouse gas stabilization scenarios (RCP4.5 and RCP8.5). For the present climate, only HadGEM2 simulates a frequency of El Niño (EN) and La Niña (LN) years similar to the observations. In terms of ENSO frequency changes, only in the far-future RCP8.5 climate there is greater agreement among GCMs, indicating an increase (decrease) of EN (LN) years. In the present climate, validation indicates that only the RegCM4 ensemble mean provides acceptable precipitation biases (smaller than ±20 %) in the two investigated regions. In this period, the GCMs and RegCM4 agree on the relationship between ENSO and precipitation in SA, i.e., both are able to capture the observed regions of positive/negative rainfall anomalies during EN years, with RegCM4 improving on the GCMs’ signal over southeastern SA. For the near and far future climates, in general, the projections indicate an increase (decrease) of precipitation over southeastern SA (northern-northeastern SA). However, the relationship between ENSO and rainfall in most of RegCM4 and GCM members is weaker in the near and far future climates than in the present day climate. This is likely connected with the GCMs’ projection of the more intense ENSO signal displaced to the central basin of Pacific Ocean in the far future compared to present climate.

Description: Climate change will cause large numbers of casualties, perhaps extending over thousands of years. Casualties have a clear moral significance that economic and other technical measures of harm tend to mask. They are, moreover, universally understood, whereas other measures of harm are not. Therefore, the harms of climate change should regularly be expressed in terms of casualties by such agencies such as IPCC’s Working Group III, in addition to whatever other measures are used. Casualty estimates should, furthermore, be used to derive estimates of casualties per emission source up to a given date. Such estimates would have wide margins of error, but they would add substantially to humanity’s grasp of the moral costs of particular greenhouse gas emissions.

Description: We provide an overview of an interdisciplinary special issue that examines the influence of climate change on people and fish in the Yakima River Basin, USA. Jenni et al. ( 2013 ) addresses stakeholder-relevant climate change issues, such as water availability and uncertainty, with decision analysis tools. Montag et al. ( 2014 ) explores Yakama Tribal cultural values and well-being and their incorporation into the decision-making process. Graves and Maule ( 2012 ) simulates effects of climate change on stream temperatures under baseline conditions (1981–2005) and two future climate scenarios (increased air temperature of 1 °C and 2 °C). Hardiman and Mesa ( 2013 ) looks at the effects of increased stream temperatures on juvenile steelhead growth with a bioenergetics model. Finally, Hatten et al. ( 2013 ) examines how changes in stream flow will affect salmonids with a rule-based fish habitat model. Our simulations indicate that future summer will be a very challenging season for salmonids when low flows and high water temperatures can restrict movement, inhibit or alter growth, and decrease habitat. While some of our simulations indicate salmonids may benefit from warmer water temperatures and increased winter flows, the majority of simulations produced less habitat. The floodplain and tributary habitats we sampled are representative of the larger landscape, so it is likely that climate change will reduce salmonid habitat potential throughout particular areas of the basin. Management strategies are needed to minimize potential salmonid habitat bottlenecks that may result from climate change, such as keeping streams cool through riparian protection, stream restoration, and the reduction of water diversions. An investment in decision analysis and support technologies can help managers understand tradeoffs under different climate scenarios and possibly improve water and fish conservation over the next century.

Description: As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and “usability” of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.

Description: There is an on-going debate about climate-induced migration but little empirical evidence. We examine how climate-induced migration has impacted vulnerability and adaptation of a coastal fishing community in Bangladesh. We used household surveys, interviews and focus group discussions to compare fishery dependent households who migrated from Kutubdia Island to mainland with those who stayed behind. Our results suggest that the resettled households are less exposed to floods, sea-level-rise and land erosion than those who stayed behind. They also have more livelihood assets, higher incomes and better access to water supply, health and educational services, technology and markets. In our case study migration has thus been a viable strategy to respond to climate variability and change.

Description: Glaciers around the world retreated as the climate warmed substantially. For the majority of alpine and arctic areas, however, the lack of meteorological data over a long period makes it difficult to build long-term climate and glacial fluctuation relationships, emphasizing the importance of natural proxy archives. Here we use the 230-year record of stem radial growth of birch trees ( Betula ermanii ) from the treeline forests above the receding glaciers in eastern maritime Kamchatka to analyse temporal variations of climate as well as glacial advance and retreat. Glaciers in Kamchatka Peninsula represent the southern limit of glaciation in far eastern Eurasia, which makes them prone to global warming. Using instrumental climate data (1930–1996) from local meteorological stations, we find that the July temperature had most prominent positive impact on birch growth. On the contrary, smaller ring increments are associated with the positive summer and net annual ice mass balance of Koryto Glacier. The prevailing trend of higher summer temperatures and lower snowfall over the past 70 years has enhanced tree growth while causing the glacier’s surface to lower by about 35 m and its front to retreat by about 490 m. Assuming these same relationships between climate, tree growth, and glacier mass balance also existed in the past, we use tree rings as a proxy record of climatically induced temporary halts in the glacier’s retreat over the past two centuries, which in total was over 1,000 m. Both direct observations and tree ring proxies indicate several prolonged warm periods (1990s, 1960s, 1930–1940s, 1880–1900s) interspersed with cooler periods (1984–1985, 1970–1976, 1953–1957, 1912–1926, 1855–1875, 1830–1845, 1805–1820 and 1770–1780) when the glacier re-advanced, creating several consecutive terminal moraine ridges. We conclude that birch tree-rings are suitable for assessing tree growth/climate/glacial relationships over a longer timescale in maritime Kamchatka.

Description: This paper analyzes the impact of climate, crop production technology, and atmospheric carbon dioxide (CO 2 ) on current and future crop yields. The analysis of crop yields endeavors to advance the literature by estimating the effect of atmospheric CO 2 on observed crop yields. This is done using an econometric model estimated over pooled historical data for 1950–2009 and data from the free air CO 2 enrichment experiments. The main econometric findings are: 1) Yields of C3 crops (soybeans, cotton, and wheat) directly respond to the elevated CO 2 , while yields of C4 crops (corn and sorghum) do not, but they are found to indirectly benefit from elevated CO 2 in times and places of drought stress; 2) The effect of technological progress on mean yields is non-linear; 3) Ignoring atmospheric CO 2 in an econometric model of crop yield likely leads to overestimates of the pure effects of technological progress on crop yields of about 51, 15, 17, 9, and 1 % of observed yield gain for cotton, soybeans, wheat, corn and sorghum, respectively; 4) Average climate conditions and climate variability contribute in a statistically significant way to average crop yields and their variability; and 5) The effect of CO 2 fertilization generally outweighs the effect of climate change on mean crop yields in many regions resulting in an increase of 7–22, 4–47, 5–26, 65–96, and 3–35 % for yields of corn, sorghum, soybeans, cotton, and wheat, respectively.

Description: The work attempts to assess the effects of global warming on the efficacy of current greenhouse cooling methods following a methodology previously proved for other agricultural buildings. The cooling potential of four greenhouse cooling techniques (natural ventilation, forced ventilation, fogging and shading) were simulated by computer modelling for five European locations, calculating the greenhouse internal air temperature from measured external climate data. Four 2080s scenarios were analysed in these five locations. They were constructed as a combination of General Circulation Models (Had CM3 and ECHAM4) downscaled for Europe with the HIRHAM and RCA3 regional models and driven by the A2 and B2 socio-economic scenarios. The crop considered as reference was tomato. The results showed that, in locations in southern Europe, adding evaporative cooling methods to ventilation and/or shading will be indispensable. In some areas of northern Europe, natural ventilation will no longer be sufficient, and shading or fogging will also be necessary. The economic consequences will be important, over all in the southern locations where water consumption, investment and working costs will be higher and necessary to ensure the crop production.

Description: An integrated process involving participatory and modelling approaches for prioritizing and evaluating climate change adaptation options for the Kangsabati reservoir catchment is presented here. We assess the potential effects of climate change on water resources and evaluate the ability of stakeholder prioritized adaptation options to address adaptation requirements using the Water Evaluation And Planning (WEAP) model. Two adaptation options, check dams and increasing forest cover, are prioritized using pair-wise comparison and scenario analysis. Future streamflow projections are generated for the mid-21 st century period (2021–2050) using four high resolution (~25 km) Regional Climate Models and their ensemble mean for SRES A1B scenario. WEAP simulations indicate that, compared to a base scenario without adaptation, both adaptation options reduce streamflow. In comparison to check dams, increasing forest cover shows greater ability to address adaptation requirements as demonstrated by the temporal pattern and magnitude of streamflow reduction. Additionally, over the 30 year period, effectiveness of check dams in reducing streamflow decreases by up to 40 %, while that of forest cover increases by up to 47 %. Our study highlights the merits of a comparative assessment of adaptation options and we conclude that a combined approach involving stakeholders, scenario analysis, modelling techniques and multi-model projections may support climate change adaptation decision-making in the face of uncertainty.

Description: The new scenario framework facilitates the coupling of multiple socioeconomic reference pathways with climate model products using the representative concentration pathways. This will allow for improved assessment of climate impacts, adaptation and mitigation. Assumptions about climate policy play a major role in linking socioeconomic futures with forcing and climate outcomes. The paper presents the concept of shared climate policy assumptions as an important element of the new scenario framework. Shared climate policy assumptions capture key policy attributes such as the goals, instruments and obstacles of mitigation and adaptation measures, and introduce an important additional dimension to the scenario matrix architecture. They can be used to improve the comparability of scenarios in the scenario matrix. Shared climate policy assumptions should be designed to be policy relevant, and as a set to be broad enough to allow a comprehensive exploration of the climate change scenario space.

Description: This paper presents a novel approach to allocation of spatially correlated data, such as emission inventories, to finer spatial scales, conditional on covariate information observable in a fine grid. Spatial dependence is modelled with the conditional autoregressive structure introduced into a linear model as a random effect. The maximum likelihood approach to inference is employed, and the optimal predictors are developed to assess missing values in a fine grid. An example of ammonia emission inventory is used to illustrate the potential usefulness of the proposed technique. The results indicate that inclusion of a spatial dependence structure can compensate for less adequate covariate information. For the considered ammonia inventory, the fourfold allocation benefited greatly from incorporation of the spatial component, while for the ninefold allocation this advantage was limited, but still evident. In addition, the proposed method allows correction of the prediction bias encountered for the upper range emissions in the linear regression models.

Description: Several recent papers have suggested that high temperatures are associated with reduced maize yields. To better understand the conditions under which this association may occur, we conduct two analyses on maize yields from 1981 to 2011 for 100 U.S. counties with large areas planted to maize in the mid-West and Great Plains. First, we compare statistical yield models in non-irrigated and extensively irrigated counties, after carefully evaluating the degree of crop irrigation in a county and selecting only counties with no irrigation or extensive irrigation. We find that yields in extensively irrigated counties have minimal dependency on temperature factors in the regression model. Second, we compare statistical yield models across non-irrigated counties using data sets with and without years with known extreme moisture anomalies. We find that for Minnesota, Central Iowa, and Northern Illinois, the sufficiency of yield models based only on temperature factors are highly leveraged by the few years with extreme moisture anomalies. In western Iowa and much of Illinois, temperature factors consistently explain a moderate amount of yield variability, even when extreme moisture anomalies are removed. In general, these findings suggest that in many regions maize yields are not solely dependent on temperature and that other factors (e.g. humidity, soil moisture, flooding) likely need to be accounted for to improve statistical yield models and to make accurate projections of maize yield in a changing climate.

Description: The framework for the new scenarios being developed for climate research calls for the development of a set of Shared Socioeconomic Pathways (SSPs), which are meant to differ in terms of their challenges to mitigation and challenges to adaptation . In order for the scenario process to fulfill its goals, the research and policy communities need to develop a shared understanding of these concepts. This paper focuses on challenges to adaptation . We begin by situating this new concept in the context of the rich literatures related to inter alia adaptation, vulnerability, and resilience. We argue that a proper characterization of challenges to adaptation requires a rich, exploration of the concept, which goes beyond mere description. This has a number of implications for the operationalization of the concept in the basic and extended versions of the SSPs. First, the elements comprising challenges to adaptation must include a wide range of socioeconomic and even some (non-climatic) biophysical factors. Second, careful consideration must be given to differences in these factors across scales, as well as cross-scale interactions. Third, any representation of the concept will require both quantitative and qualitative elements. The scenario framework offers the opportunity for the SSPs and full scenarios to be of greater value than has been the case in past exercises to both Integrated Assessment Modeling (IAM) and Impacts, Adaptation, and Vulnerability (IAV) researchers, but this will require a renegotiation of the traditional, primarily unidirectional relationship between the two communities.

Description: The La Plata Basin (LPB) is one of the most important regions for agriculture and livestock production in South America, playing a central role in the world food production and food security. Within its borders is also located the whole Brazilian Pantanal region. Identifying the most important land use sectors in LPB as well as the changes observed in the past years is fundamental to recognize which areas of the basin might be more vulnerable to climate change in order to design adaptation strategies. A general characterization of land use and livestock production of Brazilian LPB was done by using the System of Automatic Retrieving (SIDRA) of Brazilian Institute of Geography and Statistics (IBGE) platform as the major source of data. It was observed expressive increases in land areas used for temporary crops, such as soybean, sugarcane, and maize, as well as increases in poultry and swine production. These important changes in agricultural land use and livestock production are currently associated to non-climatic drivers, but this dynamic might be strongly affected by the consequences of climate change and variability, with negative socio-economic impacts for the whole region.

Description: The Yakima River Basin (Basin) in south-central Washington is a prime example of a place where competing water uses, coupled with over-allocation of water resources, have presented water managers with the challenge of meeting current demand, anticipating future demand, and preparing for potential impacts of climate change. We took a decision analysis approach that gathered diverse stakeholders to discuss their concerns pertaining to climate change effects on the Basin and future goals that were collectively important. One main focus was centered on how climate change may influence future salmon populations. Salmon have played a prominent role in the cultures of Basin communities, especially for tribal communities that have social, cultural, spiritual, subsistence, and economic ties to them. Stakeholders identified the need for a better understanding on how the cultural, spiritual, subsistence, and economic aspects of the Confederated Tribes and Bands of the Yakama Nation could be affected by changes in salmon populations. In an attempt to understand the complexities of these potential effects, this paper proposes a conceptual model which 1) identifies cultural values and components and the interactions between those components that could influence tribal well-being, and 2) shows how federal natural resource managers could incorporate intangible tribal cultural components into decision-making processes by understanding important components of tribal well-being. Future work includes defining the parameterization of the cultural components in order for the conceptual model to be incorporated with biophysical resource models for scenario simulations.

Description: The paper presents the problem of a simulation of the greenhouse gases emission permits market where only low accuracy emission amounts are known. An organization of the market with uncertain emissions is proposed and trading rules for individual market participants are discussed. Simulation of the market is based on a multi-agent system. Negotiation of purchase/sale prices between the parties are introduced, where the trading parties adopt one of two options: (i) bilateral negotiations, and (ii) sealed bid reverse auctions. Results of simulation runs show trajectories of transaction prices, as well as probability distributions of learning agents’ bidding prices.

Description: Stephen Gardiner argues that geoengineering does not meet the “canonical technical definition” of a global public good, and that it is misleading to frame geoengineering as a public good. A public good is something that is nonrival and nonexcludable. Contrary to Gardiner’s claims, geoengineering meets both of these criteria. Framing geoengineering as a public good is useful because it allows commentators to draw on the existing economic, philosophical, and social scientific literature on the governance of public goods.

Description: There are diverse linkages between climate change and security including risks of conflict, national security concerns, critical national infrastructure, geo-political rivalries and threats to human security. We review analysis of these domains from primary research and from policy prescriptive and advocacy sources. We conclude that much analysis over-emphasises deterministic mechanisms between climate change and security. Yet the climate-security nexus is more complex than it appears and requires attention from across the social sciences. We review the robustness of present social sciences analysis in assessing the causes and consequences of climate change on human security, and identify new areas of research. These new areas include the need to analyse the absence of conflict in the face of climate risks and the need to expand the range of issues accounted for in analysis of climate and security including the impacts of mitigation response on domains of security. We argue for the necessity of robust theories that explain causality and associations, and the need to include theories of asymmetric power relations in explaining security dimensions. We also highlight the dilemmas of how observations and historical analysis of climate and security dimensions may be limited as the climate changes in ways that present regions with unprecedented climate risks.

Description: Large-scale climatic variability exerts a strong influence on local-scale environmental patterns and processes. However, disentangling the effects of global climate forcing from observed patterns in local processes requires robust understanding of the underlying patterns of temporal variability and consideration of the specific setting in which these processes take place. Here, we examine the influence of intermediate-scale environmental factors in modulating the effects of the North Atlantic Oscillation (NAO) on long-term water level dynamics in natural lakes. Lakes are ideal systems to study these relationships because of their acute sensitivity to environmental change and their linkages with multi-scale processes through the hydrological cycle. Using a novel combination of analytical tools, we show that the coupling between the NAO and water level dynamics is markedly nonstationary (i.e., time-frequency variant) and strongly lake-specific, filtered through the particular weather and environmental settings of lakes and their catchments. We conclude that to fully understand the nonstationary interplay between climate and ecology, we need first to disentangle the intermediate links between climate and different embedded environmental factors related to the process of interest. This knowledge should enhance significantly our ability to produce adequate long-term water resource management strategies, to preserve biological diversity and to achieve sustainable development under a globally changing climate.

Description: Using a 25-year record of monitoring data, we show that recent climate change has affected the thermal properties and oxygen content of seven lakes in south-central Ontario, Canada, and five lakes in north-central Wisconsin, USA. Coherent patterns in autumnal lake warming were driven by increased autumn air temperature in both lake districts. Temperature increases were restricted to the epilimnion and metalimnion of the lakes, resulting in increased thermal stability of the water column. Mixing depths also decreased over the study period. Shallower mixing depths in the Ontario lakes were due to climate-driven increases in lake-water dissolved organic carbon concentrations. Collectively, changes in the thermal regime of the lakes suggest autumn mixing of the water column may be delayed. Metalimnetic oxygen also increased in the Wisconsin lakes, perhaps in response to increased algal production as lake thermal regimes changed. The response of individual lakes to climate change was modified by lake chemistry in the Ontario lake district and by lake chemistry and morphometry in the Wisconsin lake district. Our results demonstrate coherent lake response to climate change and highlight the importance of both regional and local factors in regulating individual lake response to global climate change.

Description: Tree mortality in response to climate change induced drought has emerged as a global concern. Small changes of tree mortality rates can profoundly affect forest structure, composition, dynamics and ecosystem services such as carbon sequestration. Our analyses of longitudinal data from natural stands (82 plots) in Beijing showed that tree mortality rates have increased significantly over the two decades from 1986 to 2006. In contrast, recruitment rates decreased significantly over this period. The increase in overall mortality rates resulted from an increase in tree deaths dominantly attributed to changes in temperature and precipitation resulting in drier conditions across latitudes, elevations, tree species, and tree sizes. In addition, the results showed that mortality rates of Chinese pine ( Pinus tabuliformis ) ( β 1  = 0.0874) as a result of climate change induce drought were much smaller than oak ( Quercus ) ( β 1  = 0.1583).

Description: Total uncertainty in greenhouse gas (GHG) emissions changes over time due to “learning” and structural changes in GHG emissions. Understanding the uncertainty in GHG emissions over time is very important to better communicate uncertainty and to improve the setting of emission targets in the future. This is a diagnostic study divided into two parts. The first part analyses the historical change in the total uncertainty of CO 2 emissions from stationary sources that the member states estimate annually in their national inventory reports. The second part presents examples of changes in total uncertainty due to structural changes in GHG emissions considering the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) emissions scenarios that are consistent with the EU’s “20-20-20” targets. The estimates of total uncertainty for the year 2020 are made under assumptions that relative uncertainties of GHG emissions by sector do not change in time, and with possible future uncertainty reductions for non-CO 2 emissions, which are characterized by high relative uncertainty. This diagnostic exercise shows that a driving factor of change in total uncertainty is increased knowledge of inventory processes in the past and prospective future. However, for individual countries and longer periods, structural changes in emissions could significantly influence the total uncertainty in relative terms.

Description: Carbon Capture and Storage (CCS) can be a valuable CO 2 mitigation option, but what role CCS will play in the future is uncertain. In this paper we analyze the results of different integrated assessment models (IAMs) taking part in the 27th round of the Energy Modeling Forum (EMF) with respect to the role of CCS in long term mitigation scenarios. Specifically we look into the use of CCS as a function of time, mitigation targets, availability of renewables and its use with different fuels. Furthermore, we explore the possibility to relate model results to general and CCS specific model assumptions. The results show a wide range of cumulative capture in the 2010–2100 period (600–3050 GtCO 2 ), but the fact that no model projects less than 600 GtCO 2 indicates that CCS is considered to be important by all these models. Interestingly, CCS storage rates are often projected to be still increasing in the second half of this century. Depending on the scenario, at least six out of eight, up to all models show higher storage rates in 2100 than in 2050. CCS shares in cumulative primary energy use are in most models increasing with the stringency of the target or under conservative availability of renewables. The strong variations of CCS deployment projection rates could not be related to the reported differences in the assumptions of the models by means of a cross-model comparison in this sample.

Description: That the climate is changing and societies will have to adapt is now unequivocal, with adaptation becoming a core focus of climate policy. Our understanding of the challenges, needs, and opportunities for climate change adaptation has advanced significantly in recent years yet remains limited. Research has identified and theorized key determinants of adaptive capacity and barriers to adaptation, and more recently begun to track adaptation in practice. Despite this, there is negligible research investigating whether and indeed if adaptive capacity is translating into actual adaptation action. Here we test whether theorized determinants of adaptive capacity are associated with adaptation policy outcomes at the national level for 117 nations. We show that institutional capacity, in particular measures of good governance, are the strongest predictors of national adaptation policy. Adaptation at the national level is limited in countries with poor governance, and in the absence of good governance other presumed determinants of adaptive capacity show limited effect on adaptation. Our results highlight the critical importance of institutional good governance as a prerequisite for national adaptation. Other elements of theorized adaptive capacity are unlikely to be sufficient, effective, or present at the national level where national institutions and governance are poor.

Description: Eutrophication is a process resulting from an increase in anthropogenic nutrient inputs from rivers and other sources, the consequences of which can include enhanced algal biomass, changes in plankton community composition and oxygen depletion near the seabed. Within the context of the Marine Strategy Framework Directive, indicators (and associated threshold) have been identified to assess the eutrophication status of an ecosystem. Large databases of observations ( in situ ) are required to properly assess the eutrophication status. Marine hydrodynamic/ecosystem models provide continuous fields of a wide range of ecosystem characteristics. Using such models in this context could help to overcome the lack of in situ data, and provide a powerful tool for ecosystem-based management and policy makers. Here we demonstrate a methodology that uses a combination of model outputs and in situ data to assess the risk of eutrophication in the coastal domain of the North Sea. The risk of eutrophication is computed for the past and present time as well as for different future scenarios. This allows us to assess both the current risk and its sensitivity to anthropogenic pressure and climate change. Model sensitivity studies suggest that the coastal waters of the North Sea may be more sensitive to anthropogenic rivers loads than climate change in the near future (to 2040).

Description: The prairie pothole region (PPR) in the north-central United States and south-central Canada constitutes the most important waterfowl breeding area in North America. Projected long-term changes in precipitation and temperature may alter the drivers of waterfowl abundance: wetland availability and emergent vegetation cover. Previous studies have focused on isolated wetland dynamics, but the implications of changing precipitation on managed, river-fed wetlands have not been addressed. Using a structured decision making (SDM) approach, we derived optimal water management actions for 20 years at four river-fed National Wildlife Refuges (NWRs) in North and South Dakota under contrasting increasing/decreasing (+/−0.4 %/year) inflow scenarios derived from empirical trends. Refuge pool depth is manipulated by control structures. Optimal management involves setting control structure heights that have the highest probability of providing a desired mix of waterfowl habitat, given refuge capacities and inflows. We found optimal seasonal control structure heights for each refuge were essentially the same under increasing and decreasing inflow trends of 0.4 %/year over the next 20 years. Results suggest managed pools in the NWRs receive large inflows relative to their capacities. Hence, water availability does not constrain management; pool bathymetry and management tactics can be greater constraints on attaining management objectives than climate-mediated inflow. We present time-dependent optimal seasonal control structure heights for each refuge, which are resilient to the non-stationary precipitation scenarios we examined. Managers can use this information to provide a desired mixture of wildlife habitats, and to re-assess management objectives in reserves where pool bathymetry prevents attaining the currently stated objectives.

Description: For agriculture, there are three major options for mitigating greenhouse gas (GHG) emissions: 1) productivity improvements, particularly in the livestock sector; 2) dedicated technical mitigation measures; and 3) human dietary changes. The aim of the paper is to estimate long-term agricultural GHG emissions, under different mitigation scenarios, and to relate them to the emissions space compatible with the 2 °C temperature target. Our estimates include emissions up to 2070 from agricultural soils, manure management, enteric fermentation and paddy rice fields, and are based on IPCC Tier 2 methodology. We find that baseline agricultural CO 2 -equivalent emissions (using Global Warming Potentials with a 100 year time horizon) will be approximately 13 Gton CO 2 eq/year in 2070, compared to 7.1 Gton CO 2 eq/year 2000. However, if faster growth in livestock productivity is combined with dedicated technical mitigation measures, emissions may be kept to 7.7 Gton CO 2 eq/year in 2070. If structural changes in human diets are included, emissions may be reduced further, to 3–5 Gton CO 2 eq/year in 2070. The total annual emissions for meeting the 2 °C target with a chance above 50 % is in the order of 13 Gton CO 2 eq/year or less in 2070, for all sectors combined. We conclude that reduced ruminant meat and dairy consumption will be indispensable for reaching the 2 °C target with a high probability, unless unprecedented advances in technology take place.

Description: As sea level rises, coastal communities will face increased risks of flooding, storm surge, and inundation. In some areas, structural protective measures will be built, and for some properties, accommodation to sea level rise may be possible. For other areas, however, some form of retreat will be either preferred on economic or sociopolitical grounds or required given fiscal constraints. This paper considers how society can proactively manage shoreline retreat in those locations where it is deemed the preferable policy. A three-part strategy is proposed: (1) reduce new development in the highest-risk areas; (2) adopt policies that allow for expected and orderly removal or modification of development as inundation occurs; and (3) take advantage of disasters to implement managed retreat approaches. Specific policies are recommended and the challenges of institutional change discussed.

Description: Our study focuses on uncertainty in greenhouse gas (GHG) emissions from anthropogenic sources, including land use and land-use change activities. We aim to understand the relevance of diagnostic (retrospective) and prognostic (prospective) uncertainty in an emissions-temperature setting that seeks to constrain global warming and to link uncertainty consistently across temporal scales. We discuss diagnostic and prognostic uncertainty in a systems setting that allows any country to understand its national and near-term mitigation and adaptation efforts in a globally consistent and long-term context. Cumulative emissions are not only constrained and globally binding but exhibit quantitative uncertainty; and whether or not compliance with an agreed temperature target will be achieved is also uncertain. To facilitate discussions, we focus on two countries, the USA and China. While our study addresses whether or not future increase in global temperature can be kept below 2, 3, or 4 °C targets, its primary aim is to use those targets to demonstrate the relevance of both diagnostic and prognostic uncertainty. We show how to combine diagnostic and prognostic uncertainty to take more educated (precautionary) decisions for reducing emissions toward an agreed temperature target; and how to perceive combined diagnostic and prognostic uncertainty-related risk. Diagnostic uncertainty is the uncertainty contained in inventoried emission estimates and relates to the risk that true GHG emissions are greater than inventoried emission estimates reported in a specified year; prognostic uncertainty refers to cumulative emissions between a start year and a future target year, and relates to the risk that an agreed temperature target is exceeded.

Description: We assess the future of coal under alternative climate stabilization regimes, investigating how the quantity and location of future coal production, trade and use depends upon five factors: the supply-side constraint of resource depletion, diversification and deepening of international trade, economic growth, trends in energy intensity, and the availability of coal-fired carbon-free electric generation technology (IGCC-CCS). Using the Phoenix computable general equilibrium model of the world economy, we find that coal is sensitive to demand-side assumptions about economic growth and energy-saving structural or technological change. In a 550 ppm stabilization emission tax scenario, the gobal coal industry initially declines sharply and then rebounds, in 2050 reaching roughly the same size as it is today—but only if IGCC-CCS is available by 2020. Under alternative stabilization regimes, IGCC-CCS penetration is a key influence on production and imports in major coal regions, where it interacts with extraction costs driven by the rate of depletion relative to trade partners.

Description: Landuse in East Asia has changed substantially during the last three decades, featured with expansion of urban built-up at unprecedented scale and speed. The fast expansion of urban areas could contribute to local and even regional climate change. However, current spatial datasets of urban fractions do not well represent the extent and expansion of urban areas in the regions, and that best available satellite data and remote sensing techniques have not been well applied to serve regional modeling of urbanization impacts on near surface temperature and other climate variables. Better estimates of localized urban fractions are badly needed. Here we use high and mid resolution satellite data to estimate urban fractions and road width at local and regional scales. With our fractional cover, data fusion, and differentiated threshold approaches, more spatial details of urban cover are demonstrated than previously reported in many global datasets. Many city clusters were merging into each other, with gradual blurring of boundaries and disappearance of gaps among member cities. Cities and towns were more connected with roads and commercial corridors, while wildland and urban green areas have become more isolated as patches among built-up areas. Average road width in commercial areas was 37.2 m in Beijing (north, temperate) and 24.2 m in Guangzhou (south, tropical), which are greater than these listed in model default values. Those new estimates could effectively improve climate simulation at local and regional scales in East Asia.

Description: In public debate surrounding climate change, scientific uncertainty is often cited in connection with arguments against mitigative action. This article examines the role of uncertainty about future climate change in determining the likely success or failure of mitigative action. We show by Monte Carlo simulation that greater uncertainty translates into a greater likelihood that mitigation efforts will fail to limit global warming to a target (e.g., 2 °C). The effect of uncertainty can be reduced by limiting greenhouse gas emissions. Taken together with the fact that greater uncertainty also increases the potential damages arising from unabated emissions (Lewandowsky et al. 2014 ), any appeal to uncertainty implies a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.

Description: Uncertainty forms an integral part of climate science, and it is often used to argue against mitigative action. This article presents an analysis of uncertainty in climate sensitivity that is robust to a range of assumptions. We show that increasing uncertainty is necessarily associated with greater expected damages from warming, provided the function relating warming to damages is convex. This constraint is unaffected by subjective or cultural risk-perception factors, it is unlikely to be overcome by the discount rate, and it is independent of the presumed magnitude of climate sensitivity. The analysis also extends to “second-order” uncertainty; that is, situations in which experts disagree. Greater disagreement among experts increases the likelihood that the risk of exceeding a global temperature threshold is greater. Likewise, increasing uncertainty requires increasingly greater protective measures against sea level rise. This constraint derives directly from the statistical properties of extreme values. We conclude that any appeal to uncertainty compels a stronger, rather than weaker, concern about unabated warming than in the absence of uncertainty.

Description: Paleo-reconstructed hydrologic records offer the potential to evaluate water resources system performance under conditions that may be more extreme than seen in the historical record. This study uses a stochastic simulation framework consisting of a non-homogeneous Markov chain model (NHMM) to simulate the climate state using Palmer Drought Severity Index (PDSI)-reconstructed data, and K-nearest neighbor (K-NN) to resample observational net basin supply magnitudes for the Great Lakes of North America. The method was applied to generate 500 plausible simulations, each with 100 years of monthly net basin supply for the Upper Great Lakes, to place the observed data into a longer temporal context. The range of net basin supply sequences represents what may have occurred in the past 1,000 years and which can occur in future. The approach was used in evaluation of operational plans for regulation of Lake Superior outflows with implications for lake levels of Superior, Michigan, Huron and Erie, and their interconnecting rivers. The simulations generally preserved the statistics of the observed record while providing new variability statistics. The framework produced a variety of high and low net basin supply sequences that provide a broader estimate of the likelihood of extreme lake levels and their persistence than with the historical record. The method does not rely on parametrically generated net basin supply values unlike parametric stochastic simulation techniques, yet still generates new variability through the incorporation of the paleo-record. The process described here generated new scenarios that are plausible based on the paleo and historic record. The evaluation of Upper Great Lakes regulation plans, subject to these scenarios, was used to evaluate robustness of the regulation plans. While the uncertain future climate cannot be predicted, one can evaluate system performance on a wide range of plausible climate scenarios.

Description: The UK Government’s first National Adaptation Programme seeks to create a ‘climate-ready society’ capable of making well-informed and far-sighted decisions to address risks and opportunities posed by a changing climate, where individual households are expected to adapt when it is in their interest to do so. How, and to what extent, households are able to do this remains unclear. Like other developed countries, research on UK adaptation has focused predominately on public and private organisations. To fill that gap, a systematic literature review was conducted to understand what actions UK households have taken in response to, or in anticipation of, a changing climate; what drives or impedes these actions; and whether households will act autonomously. We found that UK households struggle to build long-term adaptive capacity and are reliant upon traditional reactive coping responses. Of concern is that these coping responses are less effective for some climate risks (e.g. flooding); cost more over the long-term; and fail to create household capacity to adapt to other stresses. While low-cost, low-skill coping responses were already being implemented, the adoption of more permanent physical measures, behavioural changes, and acceptance of new responsibilities are unlikely to happen autonomously without further financial or government support. If public policy on household adaptation to climate change is to be better informed than more high-quality empirical research is urgently needed.

Description: The effects of future temperature and hence evapotranspiration increases on drought risk over North America, based on ten current (1970–1999) and ten corresponding future (2040–2069) Regional Climate Model (RCM) simulations from the North American Regional Climate Change Assessment Program, are presented in this study. The ten pairs of simulations considered in this study are based on six RCMs and four driving Atmosphere Ocean Coupled Global Climate Models. The effects of temperature and evapotranspiration on drought risks are assessed by comparing characteristics of drought events identified on the basis of Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspration Index (SPEI). The former index uses only precipitation, while the latter uses the difference (DIF) between precipitation and potential evapotranspiration (PET) as input variables. As short- and long-term droughts impact various sectors differently, multi-scale (ranging from 1- to 12-month) drought events are considered. The projected increase in mean temperature by more than 2 °C in the future period compared to the current period for most parts of North America results in large increases in PET and decreases in DIF for the future period, especially for low latitude regions of North America. These changes result in large increases in future drought risks for most parts of the USA and southern Canada. Though similar results are obtained with SPI, the projected increases in the drought characteristics such as severity and duration and the spatial extent of regions susceptible to drought risks in the future are considerably larger in the case of SPEI-based analysis. Both approaches suggest that long-term and extreme drought events are affected more by the future increases in temperature and PET than short-term and moderate drought events, particularly over the high drought risk regions of North America.

Description: There is a growing focus on the economics of adaptation as policy moves from theory to practice. However, the techniques commonly used in economic appraisal have limitations in coping with climate change uncertainty. While decision making under uncertainty has gained prominence, economic appraisal of adaptation still uses approaches such as deterministic cost-benefit analysis. Against this background, this paper provides a critical review and assessment of existing economic decision support tools (cost-benefit analysis and cost-effectiveness analysis) an uncertainty framework (iterative risk management) and alternative tools that more fully incorporate uncertainty (real options analysis, robust decision making and portfolio analysis). The paper summarises each method, provides examples, and assesses their strengths and weaknesses for adaptation. The tools are then compared to identify key differences, and to identify when these approaches might be appropriate for specific applications in adaptation decision making.

Description: This paper analyzes the meteorological drought events in Paraguay in the period of 1964 to 2011, using the Standardized Precipitation Index (SPI). The objective is to determine if the frequency and/or severity of droughts has increased or decreased in the last years, in response of climate change. They The southernmost parts of the country are affected by severe droughts producing damage to soybean and corn crop during the rainy season (October–March) especially during the summer of 2008–2009. The years of 1967, 1968, 1978, 1979, 2000 and 2008 was identified as severe to extreme drought events and coincides with La Niña event. However, the relationship between all drought events, especially those agricultural droughts and La Niña is not clear, suggesting the necessity of new research, focusing on new drivers to explain the cause of the droughts. The economy of Paraguay, based for good part on agriculture, is clearly vulnerable to droughts. Even though no undeniable increasing trend in drought frequency/severity was detected, contingency plans to diminish drought impacts ought to be elaborated.

Description: Based on the reconstructed temperatures, precipitation changes, and occurrences of extreme climate events, together with historical records on fiscal deterioration, food crises, and the frequencies of popular unrest, rebellions and wars, we identified three principal ways in which climate change contributed to the collapse in the Ming dynasty. Firstly, cooling, aridification, and desertification during a cold period destroyed the military farm system, which was the main supply system for the provisioning of government troops on the northern frontiers; these impacts increased the military expenditure from 64 % of total government expenditure in 1548–1569 to 76 % in 1570–1589 and thus aggravated the national fiscal crisis that occurred during the late Ming dynasty. Secondly, climate deterioration (e.g., cooling, aridification, and an increase in the frequencies of frost- and drought-related disasters, etc.) led to a 20–50 % reduction in the per capita production of raw grain in most areas of China, which resulted in widespread food crises and exacerbated the vulnerability of social structures during the last several decades of the Ming dynasty. Thirdly, the severe droughts occurring in 1627–1643 were a key trigger to the peasantry uprising. These droughts also played a significant role to promote the peasantry uprising, especially reviving the peasantry troops by recruitment of famine victims when they nearly perished in 1633 and 1638, and severely disrupting the food supply for the government troops, resulting in the final defeat of the government troops by the peasantry troops. This study contributes to an understanding of the climate-related mechanisms behind the collapse of the Ming dynasty, and provides a historical case study that enhances our understanding of the nature of interactions between climate change and social vulnerability.

Description: Studies of climate change impacts on agricultural land use generally consider sets of climates combined with fixed socio-economic scenarios, making it impossible to compare the impact of specific factors within these scenario sets. Analysis of the impact of specific scenario factors is extremely difficult due to prohibitively long run-times of the complex models. This study produces and combines metamodels of crop and forest yields and farm profit, derived from previously developed very complex models, to enable prediction of European land use under any set of climate and socio-economic data. Land use is predicted based on the profitability of the alternatives on every soil within every 10’ grid across the EU. A clustering procedure reduces 23,871 grids with 20+ soils per grid to 6,714 clusters of common soil and climate. Combined these reduce runtime 100 thousand-fold. Profit thresholds define land as intensive agriculture (arable or grassland), extensive agriculture or managed forest, or finally unmanaged forest or abandoned land. The demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available. An iteration adjusts prices to meet these constraints. A range of measures are derived at 10’ grid-level such as diversity as well as overall EU production. There are many ways to utilise this ability to do rapid What-If analysis of both impact and adaptations. The paper illustrates using two of the 5 different GCMs (CSMK3, HADGEM with contrasting precipitation and temperature) and two of the 4 different socio-economic scenarios (“We are the world”, “Should I stay or should I go” which have contrasting demands for land), exploring these using two of the 13 scenario parameters (crop breeding for yield and population) . In the first scenario, population can be increased by a large amount showing that food security is far from vulnerable. In the second scenario increasing crop yield shows that it improves the food security problem.

Description: Future changes of terrestrial ecosystems due to changes in atmospheric CO 2 concentration and climate are subject to a large degree of uncertainty, especially for vegetation in the Tropics. Here, we evaluate the natural vegetation response to projected future changes using an improved version of a dynamic vegetation model (CLM-CN-DV) driven with climate change projections from 19 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The simulated equilibrium vegetation distribution under historical climate (1981–2000) has been compared with that under the projected future climate (2081–2100) scenario for Representative Concentration Pathway 8.5 (RCP8.5) to qualitatively assess how natural potential vegetation might change in the future. With one outlier excluded, the ensemble average of vegetation changes corresponding to climates of 18 GCMs shows a poleward shift of forests in northern Eurasia and North America, which is consistent with findings from previous studies. It also shows a general “upgrade” of vegetation type in the Tropics and most of the temperate zones, in the form of deciduous trees and shrubs taking over C3 grass in Europe and broadleaf deciduous trees taking over C4 grasses in Central Africa and the Amazon. LAI and NPP are projected to increase in the high latitudes, southeastern Asia, southeastern North America, and Central Africa. This results from CO 2 fertilization, enhanced water use efficiency, and in the extra-tropics warming. However, both LAI and NPP are projected to decrease in the Amazon due to drought. The competing impacts of climate change and CO 2 fertilization lead to large uncertainties in the projection of future vegetation changes in the Tropics.

Description: While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM 2.5 ) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO 2 ) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM 2.5 would yield economic benefits in the range of $6 to $30 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $198 per metric ton of CO 2 in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.

Description: Climate change will increase the frequency and/or intensity of certain extreme weather events, and perceived experience with extreme weather may influence climate change beliefs, attitudes, and behaviors. However, the aspects of extreme events that influence whether or not people perceive that they have personally experienced them remain unclear. We investigate (1) the correspondence of reported experience of extreme weather events with documented events, and (2) how characteristics of different extreme events shape the geographic area within which people are likely to report they have experienced it—the event’s perceived “shadow of experience.” We overlay geocoded survey responses indicating personal experience with hurricanes, tornadoes, and drought—from a 2012 nationally representative survey ( N  = 1,008) of U.S. residents—on maps of recorded event impacts. We find that reported experiences correspond well with recorded event impacts, particularly for hurricanes and tornadoes. Reported experiences were related to event type, proximity, magnitude and duration. The results suggest locations where disaster preparedness efforts and climate change education campaigns could be most effective after an extreme weather event.

Description: This paper addresses the problem of meeting a predetermined temperature target cost-effectively under uncertainty and gradual learning on climate sensitivity. The firstorder optimality conditions to a stochastic cost-minimization problem with a temperature constraint are first provided, portraying how marginal costs evolve with an optimal hedging strategy. Then, numerical stochastic scenarios with cost curves fitted to recent climate changemitigation scenarios are presented, illustrating both the range of possible future pathways and the effect of uncertainty to the solution. Last, the effect of several different sets of assumptions on the optimal hedging strategy are analyzed. The results highlight that the hedging of climate sensitivity risk calls for deeper early reductions, although the possibility of different assumptions prevents providing accurate policy guidance.

Description: A recent Climatic Change review article reports a remarkable convergence of scientific evidence for a link between climatic events and violent intergroup conflict, thus departing markedly from other contemporary assessments of the empirical literature. This commentary revisits the review in order to understand the discrepancy. We believe the origins of the disagreement can be traced back to the review article’s underlying quantitative meta-analysis, which suffers from shortcomings with respect to sample selection and analytical coherence. A modified assessment that addresses some of these problems suggests that scientific research on climate and conflict to date has produced mixed and inconclusive results.

Description: A comment by Buhaug et al. attributes disagreement between our recent analyses and their review articles to biased decisions in our meta-analysis and a difference of opinion regarding statistical approaches. The claim is false. Buhaug et al.’s alteration of our meta-analysis misrepresents findings in the literature, makes statistical errors, misclassifies multiple studies, makes coding errors, and suppresses the display of results that are consistent with our original analysis. We correct these mistakes and obtain findings in line with our original results, even when we use the study selection criteria proposed by Buhaug et al. We conclude that there is no evidence in the data supporting the claims raised in Buhaug et al.

Description: A rationale is a reasoned narrative used to justify a norm or set of norms; in turn, it determines the expectations that one holds from the law and provides a framework in which complementary norms are bargained. This article proposes a reflection on the elusive rationale for international climate law. Its first, analytical claim is that there is currently no consensus on such a rationale—an absence likely to impede climate negotiations. References to “equity,” “common but differentiated responsibilities” and “respective capabilities” in existing climate law provide insufficient guidance to ongoing negotiations, reflecting an agreement to disagree rather than a common vision. The construction of a rationale is prevented by protracted disputes regarding the ethical grounds relevant to climate law and by the ambivalence of national interests, which are essentially social constructs. A second, normative claim of this article is that the rationale for climate law should be construed as a hybrid narrative reconciling moral aspirations with pragmatic constraints. Thus, it is submitted that the concept of complex interdependence could be applied to climate change to emphasize existing national interests in fostering global sustainable development. Although important debates remain, complex interdependence provides essential guidance by calling states to take moral arguments into account, in their own interest—when such arguments are widely accepted by civil societies—in order to avoid human destitution and resentment and to preclude the possibility of disastrous consequences on international peace and security.

Description: Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts to stakeholders. Typically, CIIs comprise into a single index several weather variables —such as temperature, wind speed, precipitation and humidity— which are relevant for a particular problem of interest. Moreover, most of the CIIs require daily (or monthly) physical coherence among these variables for their proper calculation. This constraints the number of statistical downscaling techniques suitable for a component-wise approach to this problem. We test the suitability of the alternative “direct” downscaling approach in which the downscaling method is applied directly to the CII, thus circumventing the multi-variable problem and allowing the use of a wider range of downscaling methods. For illustrative purposes, we consider two popular CIIs —the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), used in the wildfire and tourism sectors, respectively— and compare the performance of the two approaches using the analog method, a simple and popular method providing inter-variable dependence. The results obtained with ‘perfect’ reanalysis predictors are comparable for both approaches, although smaller accuracy is obtained in general with the direct approach. Moreover, similar climate change ‘deltas’ are obtained with both approaches when applied to an illustrative future global projection using the ECHAM5 model. Overall, there is a trade-off between performance and simplicity which needs to be balanced for each particular application.

Description: Changes in the Atlantic overturning circulation have a strong influence on European temperatures, North American sea level and other climate phenomena worldwide. A meaningful assessment of associated societal impacts needs to be based on the full range of its possible future evolution. This requires capturing both the uncertainty in future warming pathways and the inherently long-term response of the ocean circulation. While probabilistic projections of the global mean and regional temperatures exist, process-based probabilistic assessments of large-scale dynamical systems such as the Atlantic overturning are still missing. Here we present such an assessment and find that a reduction of more than 50 % in Atlantic overturning strength by the end of the 21 s t century is within the likely range under an unmitigated climate change scenario (RCP8.5). By combining linear response functions derived from comprehensive climate simulations with the full range of possible future warming pathways, we provide probability estimates of overturning changes by the year 2100. A weakening of more than 25 % is found to be very unlikely under a climate protection scenario (RCP2.6), but likely for unmitigated climate change. The method is able to reproduce the modelled recovery caused by climatic equilibration under climate protection scenarios which provides confidence in the approach. Within this century, a reduction of the Atlantic overturning is a robust climatic phenomena that intensifies with global warming and needs to be accounted for in global adaptation strategies.

Description: Decision-makers have confirmed the long term objective of preventing a temperature increase greater than 2 °C. This paper aims at appraising by means of a cost-benefit analysis whether decision makers’ commitment to meet the 2 °C objective is credible or not. Within the framework of a cost-benefit type integrated assessment model, we consider that the economy faces climate damages with a threshold at 2 °C. We run the model for a broad set of scenarios accounting for the diversity of “worldviews” in the climate debate. For a significant share of scenarios we observe that it is considered optimal to exceed the threshold. Among those “non-compliers” we discriminate ”involuntary non-compliers” who cannot avoid the exceedance due to physical constraint from ”deliberate compliers” for whom the exceedance results from a deliberate costs-benefit analysis. A second result is that the later mitigation efforts begin, the more difficult it becomes to prevent the exceedance. In particular, the number of ”deliberate non-compliers” dramatically increases if mitigation efforts do not start by 2020, and the influx of involuntary non-compliers become overwhelming f efforts are delayed to 2040. In light of these results we argue that the window of opportunity for reaching the 2 °C objective with a credible chance of success is rapidly closing during the present decade. Further delay in finding a climate agreement critically undermines the credibility of the objective.

Description: The potential effects of climate change on net primary productivity (NPP) of U.S. rangelands were evaluated using estimated climate regimes from the A1B, A2 and B2 global change scenarios imposed on the biogeochemical cycling model, Biome-BGC from 2001 to 2100. Temperature, precipitation, vapor pressure deficit, day length, solar radiation, CO 2 enrichment and nitrogen deposition were evaluated as drivers of NPP. Across all three scenarios, rangeland NPP increased by 0.26 % year −1 (7 kg C ha −1  year −1 ) but increases were not apparent until after 2030 and significant regional variation in NPP was revealed. The Desert Southwest and Southwest assessment regions exhibited declines in NPP of about 7 % by 2100, while the Northern and Southern Great Plains, Interior West and Eastern Prairies all experienced increases over 25 %. Grasslands dominated by warm season (C4 photosynthetic pathway) species showed the greatest response to temperature while cool season (C3 photosynthetic pathway) dominated regions responded most strongly to CO 2 enrichment. Modeled NPP responses compared favorably with experimental results from CO 2 manipulation experiments and to NPP estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS). Collectively, these results indicate significant and asymmetric changes in NPP for U.S. rangelands may be expected.

Description: This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone damages under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 478 estimates of the temperature-damage relationship from nineteen studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5 °C increase in global surface air temperature would cause hurricane damages to increase by 63 %. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are +28 % and +23 %, respectively. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.

Description: Bolivia is located at the crossroad of the major climatic influences of Northern and Southern-South America, which turns this country into a natural laboratory to investigate the interactions between ocean-climate and fire variability. We chose two oceanic indices: MEI (multivariate ENSO Index) and AMO (Atlantic Multidecadal Oscillation) to select the three most representative years for four oceanic conditions: El Niño, La Niña, AMO, and standard years (understood as years with little ocean influences), for the period 1992–2012. We investigated how i) rainfall (dry vs wet seasons) and ii) fire responded in five Bolivian biomes (Tropical Moist Forests, Tropical Dry Forests, Tropical Grasslands, Tropical Montane, and Seasonally Flooded ecosystems) under these oceanic conditions. Bolivia showed a strong rainfall increase in El Niño years in both seasons (wet/dry), while AMO showed the strongest droughts in both seasons. La Niña showed a bipolar response with rainfall increases in the wet season and a very marked rainfall decrease in the dry season. Drought significantly increased fire numbers in AMO years, being the most significant fire condition and suggesting a larger fire influence of the Atlantic than the Pacific at the national level. Surprisingly, the amount of fire was very large under normal years (STD) and similar to fire levels under La Niña, suggesting generalized fire conditions in the country, except for El Niño years that bring rainfall excess and little fire. The most fire-affected biomes were the seasonally flooded and dry forests, followed by the grassland/savannah biome. Montane areas showed the least fire, but satellite fire omission is well known in the Andean region.

Description: Projections of regional changes in surface-air temperature and precipitation, in response to unconstrained emissions as well as a climate mitigation policy, for the Zambezi River Basin (ZRB) are presented. These projections are cast in a probabilistic context through a hybrid technique that combines the projections of the MIT Integrated Global System Model (IGSM) to pattern-change kernels from climate-model results of the Coupled Model Intercomparison Project (CMIP). Distributional changes of precipitation and surface-air temperature averaged over the western and eastern ZRB are considered. Overall, the most significant response to climate policy is seen in the spring. Frequency distributions of precipitation change for the unconstrained emission scenario indicate a majority of the outcomes to be drier by 2050, although the distribution spans both increased and decreased precipitation. Through climate policy, the distributions’ total range of outcomes collapses considerably, and perhaps more importantly, the mode of the distribution aligns with zero precipitation change. For surface-air temperature, climate policy consistently reduces the modal value of warming, and this reduction is strongest for the western ZRB. Climate policy also considerably abates the occurrence of the most extreme temperature increases, but the minimum warming in the distributions is less affected.

Description: Climate extremes indices are evaluated for the northeast United States and adjacent Canada (Northeast) using gridded observations and twenty-three CMIP5 coupled models. Previous results have demonstrated observed increases in warm and wet extremes and decreases in cold extremes, consistent with changes expected in a warming world. Here, a significant shift is found in the distribution of observed total annual precipitation over 1981-2010. In addition, significant positive trends are seen in all observed wet precipitation indices over 1951-2010. For the Northeast region, CMIP5 models project significant shifts in the distributions of most temperature and precipitation indices by 2041-2070. By the late century, the coldest (driest) future extremes are projected to be warmer (wetter) than the warmest (wettest) extremes at present. The multimodel interquartile range compares well with observations, providing a measure of confidence in the projections in this region. Spatial analysis suggests that the largest increases in heavy precipitation extremes are projected for northern, coastal, and mountainous areas. Results suggest that the projected increase in total annual precipitation is strongly influenced by increases in winter wet extremes. The largest decreases in cold extremes are projected for northern and interior portions of the Northeast, while the largest increases in summer warm extremes are projected for densely populated southern, central, and coastal areas. This study provides a regional analysis and verification of the latest generation of CMIP global models specifically for the Northeast, useful to stakeholders focused on understanding and adapting to climate change and its impacts in the region.

Description: Here we present two new metrics used for comparing climate impacts of emissions of different climate forcers: the Global Sea level rise Potential (GSP) and the Integrated Global Sea level rise Potential (IGSP). The GSP represents the Sea Level Rise (SLR) at a given time horizon due to an emission pulse of a forcer; the IGSP is similar but represents the time integrated SLR up to a given point in time. The GSP and IGSP are presented relative to the SLR caused by a comparable emission pulse of carbon dioxide. The metrics are assessed using an Upwelling-Diffusion Energy Balance Model (UDEBM). We focus primarily on the thermosteric part of SLR, denoted GSP th . All of the examined climate forcers – even black carbon, a very Short-Lived Climate Forcer (SLCF) – have considerable influence on the thermosteric SLR on the century time scale. For a given time horizon and forcer, GSP th lies in between the corresponding metric values obtained using Global Warming Potential (GWP) and Global Temperature change Potential (GTP), whereas IGSP th ends up in the opposite end to GTP in the spectrum of compared metrics. GSP th and IGSP th are more sensitive for SLCFs than for the long-lived Greenhouse Gases (GHGs) to changes in the parameterization of the model (under the time horizons considered here). We also use a Semi-Empirical (SE) model to estimate the full SLR, and corresponding GSP SE and IGSP SE , as alternatives to the thermosteric approach. For SLCFs, GSP SE is greater than GSP th for all time horizons considered, while the opposite holds for long-lived GHGs such as SF 6 .

Description: Conventional forecast driven approaches to climate change adaptation create a cascade of uncertainties that can overwhelm decision makers and delay proactive adaptation responses. Robust Decision Making inverts the analytical steps associated with forecast-led methodologies, reframing adaptation in the context of a specific decision maker’s capacities and vulnerabilities. In adopting this bottom-up approach, the aim is to determine adaptation solutions which are insensitive to uncertainty. Yet despite the increased use of the approach in large-scale adaptation projects in developed countries, there is little empirical evidence to test whether or not it can be successfully applied in developing countries. The complex realities of decision making processes, the need to combine quantitative data with qualitative understanding and competing environmental, socio-economic and political factors all pose significant obstacles to adaptation. In developing countries, these considerations are particularly relevant and additional pressures exist which may limit the uptake and utility of the Robust Decision Making approach. In this paper, we investigate the claim that the approach can be deemed valuable in developing countries. Challenges and opportunities associated with Robust Decision Making, as a heuristic decision framework, are discussed with insights from a case study of adapting coastal infrastructure to changing environmental risks in South Africa. Lessons are extracted about the ability of this framework to improve the handling of uncertainty in adaptation decisions in developing countries.

Description: This paper applies an ontological politics approach for studying how complexity, uncertainty, and ignorance are being dealt with in the Netherlands by looking at how knowledges are produced and incorporated in decision-making on uncertain climate change. On the basis of work done in the Netherlands, this paper shows two things in particular. First, how decision making responses historically have been subject to change under the influence of floods and how the emergence of climate change has significantly changed these floods. Second, based on the analysis of processes dealing with a blue-green algae problem in a lake, climate change not only changed decision making responses but also changed the very reality that is being enacted. Consequently, this brings an ethical dimension to the fore, related to the intrinsic tension between the growing awareness that “all is interconnected” on the one hand and the realization we cannot take all into account.

Description: Monthly mean air temperature (AT) at 85 sites and instantaneous stream-water temperature (WT) at 129 sites for 1960–2010 are examined for the mid-Atlantic region, USA. Temperature anomalies for two periods, 1961–1985 and 1985–2010, relative to the climate normal period of 1971–2000, indicate that the latter period was statistically significantly warmer than the former for both mean AT and WT. Statistically significant temporal trends across the region of 0.023 °C per year for AT and 0.028 °C per year for WT are detected using simple linear regression. Sensitivity analyses show that the irregularly sampled WT data are appropriate for trend analyses, resulting in conservative estimates of trend magnitude. Relations between 190 landscape factors and significant trends in AT-WT relations are examined using principal components analysis. Measures of major dams and deciduous forest are correlated with WT increasing slower than AT, whereas agriculture in the absence of major dams is correlated with WT increasing faster than AT. Increasing WT trends are detected despite increasing trends in streamflow in the northern part of the study area. Continued warming of contributing streams to Chesapeake Bay likely will result in shifts in distributions of aquatic biota and contribute to worsened eutrophic conditions in the bay and its estuaries.

Description: The lowlands of eastern and northeastern Bolivia are characterized by a transition between the humid evergreen forests of the Amazon Basin and the deciduous thorn-scrub vegetation of the Gran Chaco. Within this landscape lies one of the world’s best preserved areas: the ecoregion known as the Chiquitano dry forest, where deforestation patterns over a 30 year period were analyzed. Results indicate that the area of the natural cover was reduced from 97.21 % before 1976 to 82.10 % in 2008, causing significant change in the landscape, especially in the spatial configuration of forest cover. The density of forest fragments increased from 0.073 patches per 100 ha before 1976 to 0.509 in 2008, with a mean distance between patches of 151 and 210 m over the same period, leading to a considerable reduction in the fragment sizes, from 1,204 ha before 1976 to a mere 54 in 2008. This pattern, observed in forests, does not occur in the savannas because, on one hand the savanna area is much lower compared to that of forests, and on the other because the deforestation process tended to be concentrated within forested areas. Based on the observed patterns, it is possible that in the future the natural landscapes will be substituted principally by anthropic landscapes, if there is no change in the economic and land distribution policies. If this process continues, it will stimulate the expansion of mechanized agriculture and the colonization of new areas, which will lead to further deforestation and landscape fragmentation.

Description: We present an assessment of climate change impacts on the hydrologic regime of the 600,000 km 2 Upper Paraguay River basin, located in central South America based on predictions of 20 Atmospheric/Ocean General Circulation Models (AOGCMs). We considered two climate change scenarios from the Intergovernmental Panel on Climate Change (IPCC) and two 30-years time intervals centered at 2030 and 2070. Projected temperature and precipitation anomalies estimated by the AOGCMs for the study site are spatially downscaled. Time series of projected temperature and precipitation were estimated using the delta change approach. These time series were used as input to a detailed coupled hydrologic-hydraulic model aiming to estimate projected streamflow in climate change scenarios at several control points in the basin. Results show that impacts on streamflow are highly dependent on the AOGCM used to obtain the climate predictions. Patterns of temperature increase persist over the entire year for almost all AOGCMs resulting in an increase in the evapotranspiration rate of the hydrological model. The precipitation anomalies show large dispersion, being projected as either an increase or decrease in precipitation rates. Based on these inputs, results from the coupled hydrologic-hydraulic model show nearly one half of projections as increasing river discharge, and other half as decreasing river discharge. If the mean or median of the predictions is considered, no discernible change in river discharge should be expected, despite the dispersion among results of the AOGCMs that reached +/−10 % in the short horizon and +/− 20 % in the long horizon, at several control points.

Description: Warmer, drier summer weather brought by global climate change should encourage use of outdoor leisure facilities. Yet few studies assess the effect of current weather and climate conditions upon visits to leisure attractions. Statistical time series models are used to analyse the short-run impact of weather and the long-run impact of climate upon visits to Chester Zoo, England. Temperature has a non-linear effect on visit levels. Daily visits rise with temperature up to a threshold around 21 °C. Thereafter visitor numbers drop on hot days. Visits are redistributed over time in accordance with the weather. Visitors discouraged by rainy weather one day turn up later when the weather improves. Otherwise, visitor behaviour is mainly influenced by the annual rhythm of the year and the pattern of public and school holidays. Out-of-sample tests suggest almost 70 % of the variation in visit levels can be explained by the combination of weather and time of year. Climate change is likely to redistribute visitors across the year. But it does not follow that “summer” visitor behaviour will transfer to spring and autumn. Day length, existing patterns of human activity and availability of leisure time constrain visit levels regardless of better weather. The main implication of potential climate change is the need for physical adaptation of the tourist environment as temperatures rise and rainfall diminishes in summer.

Description: Ever-increasing global warming has created a societal imperative to reach and engage youth, whose futures are at risk. In this paper, we evaluate the climate science knowledge, beliefs, attitudes, behavior and communication impact of an entertainment-education high school assembly program in a random sample of 49 schools (from population of 779 that received the intervention) and a panel of 1,241 students. Pre- and post-assembly surveys composed of questions from the Global Warming’s Six Americas segmentation and intervention-specific measures were administered in classrooms. We demonstrate that exposure to climate science in an engaging edutainment format changes youths’ knowledge, beliefs, involvement, and behavior positively and moves them to audience segments that are more engaged in the issue. The net impact of scaled, multi-sensory, captivating programs for youth could be a population shift in science-informed engagement in the issue of climate change. In addition, such programs can inspire youth for deeper engagement in school programs, personal action, and political and consumer advocacy.

Description: The Upper Brahmaputra River Basin is prone to natural disasters and environmental stresses (floods, droughts and bank erosion, delayed rainfall, among others) creating an environment of uncertainty and setting the basin back in terms of socio-economic development. The climate change literature shows that agriculture and ecosystems and their services are highly climate sensitive, yet they are the main sources of livelihood that supports a large proportion of residents of the tributaries of the Brahmaputra River Basin. The continuous depletion of ecosystems and loss of agricultural outputs resulting from environmental stressors has a substantial impact on the socio-economic wellbeing of the basins residents, particularly the vulnerable rural poor. This paper uses spatially explicit data from Census, Household Surveys and Earth Observation to develop a transferable methodological approach which investigates the extent of dependence on agriculture and ecosystems as a source of livelihood in the contrasting sub-basins of the Brahmaputra River in the State of Assam, India and Bhutan, and the risk to these livelihood dependencies in these sub-basins due to potential environmental impacts of climate change. The results from this study constitute a case study in the development of a systematic and spatially explicit set of tools that inform and assist policy makers in the appropriate interventions to secure the livelihood benefits of sustainably managed agriculture in the face of environmental change.

Description: We investigate the potentially changing effect of urbanization on per capita and per unit of GDP carbon dioxide emissions for 69 nations from 1960 to 2010. We examine the effect of urbanization, measured as the percent of nation’s population residing in urban areas, for the overall sample as well as for smaller regionally-defined samples of nations. The results of two-way fixed effects longitudinal models for both outcomes highlight that the changing effects of urbanization on national carbon emissions throughout the world regions are far from monolithic, and these differences are hidden by the analyses of emissions for the overall sample. We provide tentative explanations for our regionally-specific findings, and conclude by emphasizing the need for more nuanced urban data and future research to increase our collective understanding of the carbon emissions / urbanization relationship.

Description: We apply a probabilistic approach to the evaluation of climate change impacts in Mozambique. We pass a distribution of climate shocks through a series of structural biophysical models. The resulting joint distributions of biophysical outcomes are then imposed on a dynamic economywide model. This framework produces distributions of economic impacts of climate change thus identifying an explicit range of potential economic outcomes and associating probability levels with given sets of outcomes. For example, we find that the economy of Mozambique may be up to 13 % smaller in 2050 compared with a fictional no climate change scenario (and assuming global policy fails to constrain emissions growth). The probability of gross domestic product (GDP) declines of greater than 10 % is relatively small at 2.5 %. These large declines are principally the result of dramatic reductions in flood return periods. To 2050, about 70 % of future climates result in GDP losses of between zero and five percent. In about 9 % of cases, climate change shocks result in higher GDP outcomes. We conclude that, relative to current practice, this structural probabilistic approach provides (i) significantly more information to decision-makers, (ii) more detailed insight into the importance of various impact channels, and (iii) a more holistic and comprehensive approach for evaluating adaptation options.

Description: Five stakeholder-relevant indices of agro-meteorological change were analysed for the UK, over past (1961–1990) and future (2061–2090) periods. Accumulated Frosts, Dry Days, Growing Season Length, Plant Heat Stress and Start of Field Operations were calculated from the E-Obs (European Observational) and HadRM3 (Hadley Regional Climate Model) PPE (perturbed physics ensemble) data sets. Indices were compared directly and examined for current and future uncertainty. Biases are quantified in terms of ensemble member climate sensitivity and regional aggregation. Maps of spatial change then provide an appropriate metric for end-users both in terms of their requirements and statistical robustness. A future UK is described with fewer frosts, fewer years with a large number of frosts, an earlier start to field operations (e.g., tillage), fewer occurrences of sporadic rainfall, more instances of high temperatures (in both the mean and upper range), and a much longer growing season.

Description: This paper uses the RoSE transportation sector scenarios of the GCAM and REMIND energy-economy-models for the U.S. region to derive and compare these models’ intrinsic elasticities with those resulting from historical trends, estimates from the literature, and across each other. To estimate the model-intrinsic elasticities, we explore the use of dynamic linear panel data models. On the basis of 26 scenarios (panels) between 2010 and 2050, our analysis suggests that nearly all model-intrinsic elasticities with respect to final energy use are roughly comparable to each other, to those observed historically, and to those from other studies. The key difference is these models’ comparatively low intrinsic income elasticity of final energy use. This and other minor differences are interpreted through key assumptions underlying both energy-economy-models.

Description: Irrigation water requirements (IWR) are expected to be influenced by changes in the climate variables driving water availability in the soil-plant system. Most of the agricultural surface areas of the heterogeneous Swiss Rhone catchment are already exposed to drought. Aiming at investigating future pressures on the water resources to fill the growing gap between rain-fed and optimum water supply for cultivation, we downscaled and bias corrected 16 regional climate scenarios from the ENSEMBLES dataset for the period 1951–2050 using a Quantile Mapping methodology calibrated with daily observations from 5 contrasting weather stations. The data reveal an increased evaporative demand over the growing season for almost all stations and scenarios (2021–2049 vs. 1981–2009). The picture is less clear for precipitation, with a projected decrease or increase depending on the scenario, station and month. The main results indicate that bias correction of climate scenarios not only reduces the remaining error between baseline and observations but also enhances the change signal in seasonal IWR estimates. This is due to a higher and more realistic sensitivity of IWR to the atmospheric water budget, the slope of this relationship being steeper in the observations than in the uncorrected data. The seasonal cycle of the IWR change signal shows different sensitivities and climate drivers across crops (grassland and maize) and stations, but a consistent trend towards an increase despite uncertainty. This increased water demand will have to be reconciled with possibly decreased or shifted future water availability from glacier and snow melt.

Description: The C oastal F luvial Flood ( CFFlood ) model for assessing coastal and fluvial flood impacts under current and future climate and socio-economic conditions is presented and applied at the European scale. Flood frequency is estimated as a function of river flows, extreme sea levels and estimated defence standards to determine the flood extent and depth. Flood consequences are estimated by combining the latter with information on urban areas, population density and Gross Domestic Product (GDP). Climate and socio-economic scenarios and possible adaptation choices are included to analyse future conditions. In 2010, almost 6 % of the European population is estimated to live in the 100 year flood area. The corresponding economic loss is €236 billion, assuming no defences. Estimated flood protection reduces economic damage substantially by 67 to 99 % and the number of people flooded is reduced by 37 to 99 % for the 100 year event. Impact simulations show that future climate and socio-economic conditions may increase flood impacts, especially in coastal areas due to sea-level rise. In contrast, impacts caused by fluvial flooding sometimes decrease, especially in southern and western regions of Europe due to decreases in precipitation and consequent run-off. Under high-end scenarios, flood impacts increase substantially unless there are corresponding adaptation efforts.