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Carbon dioxide (CO2) emissions affect local temperature; quantifying that local response is important for learning about the earth system, the impacts of mitigation, and adaptation needs. We assume the climate system can be represented as a time‐dependent linear system, diagnosing Green's Functions for the spatial temperature response to CO2 emissions based on CMIP6 earth system models. This allows us to emulate the linear component of the temperature response to CO2. This approach is sufficient to capture the spatial temperature response of CMIP6 experiments within one standard deviation of the multimodel spread across most regions, though accuracy is lower in the Southern Ocean and the Arctic. Our approach reveals where nonlinear feedbacks are important in current CMIP6 models, and where the local system response is well represented by a time‐dependent linear differential operator. It incorporates emissions path dependency and may be useful for evaluating large ensembles of emission scenarios. Plain Language Summary: Carbon dioxide (CO2) emissions impact surface temperature. It is well established that the global mean temperature change is proportional to the cumulative emissions of CO2. This has led to the creation of carbon budgets to reach temperature goals. We test this relationship at the spatio‐temporal scale, quantifying a simple approach that estimates the local temperature response to CO2 emissions alone. We use an approach built from the Climate Model Intercomparison Project Phase 6 (CMIP6) Earth System Models, based on the concept that an additional unit of CO2 can be scaled for larger emissions and summed over time to estimate cumulative impacts. We evaluate this with additional CMIP6 experiments, showing that this approach captures the temperature response in most locations with lower accuracy in the Arctic and Southern Ocean. This type of approach may be useful to evaluate many policy scenarios and to better understand earth system processes that are represented in the models, as it takes around one second to quantify 90 years' worth of temperature change on a local computer, while Earth System Models can require weeks of runtime on supercomputers. Key Points: With a Green's Function approach, we emulate the linear component of the spatially resolved temperature response to CO2 emissionsWe reproduce the temperature response well within multi‐model uncertainty except in the Arctic and Southern OceanThis approach allows expedient quantification of the spatial and temporal temperature response to varying CO2 emissions pathways [ABSTRACT FROM AUTHOR]

Abstract Carbon dioxide (CO2) emissions affect local temperature; quantifying that local response is important for learning about the earth system, the impacts of mitigation, and adaptation needs. We assume the climate system can be represented as a time‐dependent linear system, diagnosing Green's Functions for the spatial temperature response to CO2 emissions based on CMIP6 earth system models. This allows us to emulate the linear component of the temperature response to CO2. This approach is sufficient to capture the spatial temperature response of CMIP6 experiments within one standard deviation of the multimodel spread across most regions, though accuracy is lower in the Southern Ocean and the Arctic. Our approach reveals where nonlinear feedbacks are important in current CMIP6 models, and where the local system response is well represented by a time‐dependent linear differential operator. It incorporates emissions path dependency and may be useful for evaluating large ensembles of emission scenarios.

Scenarios are often used to depict the possible outcomes of alternative future developments as part of the evaluation of climate and energy policy measures. In Finland, scenarios have become a standard practice in climate-related policy planning. However, scenario planning often results in a single cohesive narrative, which lacks transparency in why certain developments and solutions are included and others left out. This article focuses on how scenarios created during the planning of Finland's Medium-term Plan for Climate Change Policy (KAISU) were built, and how the actors involved assessed the characteristics and quality of these scenarios. We interviewed a total of 18 participants from research, administration, and policymaking domains involved in the creation of the plan and the scenarios it contains. Semi-structured interviews provided an insight into the creation and use of scenarios as part of policy formulation, as well as points of further improvement for the process. The KAISU plan was constructed as a cross-sectoral collaborative effort between policymakers, public officials, and researchers. Despite the variety of actors involved in the process, the resulting scenarios were perceived as well-executed by the participants. However, national scenario foresight could be improved in three dimensions: 1) the process where actors collaborate to build scenarios, 2) the scenario methodology, where solutions and developments are included or excluded, and 3) use of the scenarios after their construction. The scenario approach used in Finland corresponds with needs at the political level. However, the approach could be improved without compromising this goal. The underlying scenario assumptions and the compatibility of the models used lack transparency. Many actors involved in the scenario process have a limited understanding of the models used and measures proposed outside their respective sector. Construction of more than one policy scenario would allow a larger variety of possible future trajectories to be evaluated in national policymaking. In this case, the aim and role of the scenario process would have to be adjusted and clarified accordingly. Communication regarding the role and applicability of foresight methods should be improved for citizens and politicians alike. [ABSTRACT FROM AUTHOR]

There is substantial evidence that climate change is affecting ecosystems worldwide.California is no exception. With insights from historic climate change and subsequentspecies’ responses, scientists are developing refined tools to evaluate how species changemay continue in the future and what impact this may have on biodiversity andconservation. Bioclimatic envelope modeling is one approach to modeling speciesdistribution. However, it has many shortcomings by neglecting to account forindividualistic species response or inter specific competition. Furthermore, bioclimaticenvelope models do not account for species dispersal constraints or those imposed bydisturbances such as land use change or fire. BioMove is a novel spatially explicit,dynamic species modeling approach developed to address these issues. It simulates atarget species in a dynamic landscape, competing with a target species in competitionwith one or many PFTs. It combines various sub-models to integrate competition,dispersal and disturbance. It has important application potential for threatened speciesassessment, management coordination and decision support, invasive species modelingand other advanced climate change research.

From charting out climate change mitigation pathways to estimating price risks associated with the social cost of carbon, as environmentally concerned citizens of the twenty-first century, we live in a culture of foresight. Because of a growing integration of an ever-wider sample space of possible climate futures into the present, historical experience has become seemingly irrelevant for effectively predicting where our climate transitions are headed, in effect restricting our sense of futurity to its performativity in the present. What has been surprisingly absent as a theoretical and methodological approach among sociologists, however, are treatments of the performativity of the future as the expression of a historical praxis for prognosis, with its own mode of disclosure. By interrogating the temporal structure of anticipation that characterizes computer-based simulations of emissions scenarios, the paper illustrates how this praxis discloses the future in accordance with the grammatical tense of the future perfect. It then argues that this relationship between past and future is the cultural product of a historically particular set of prognostic techniques and technologies, namely, model-based scenario analysis. Against this background, the paper seeks to contribute to the rehabilitation of the relevance of historical experience by historicizing the social ontological status of the future that theories of performativity take as their starting point. • When it comes to climate mitigation, our sense of futurity has become restricted to its performativity in the present. • This paper historicizes the ontological status of the future that theories of performativity take as their starting point. • It interrogates the temporal structure of anticipation that characterizes computer-based simulations of emissions scenarios. [ABSTRACT FROM AUTHOR]

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia. © 2013 IOP Publishing Ltd.

Climate change is not only caused the rise in temperature but also changes in the global precipitation cycle, which leads to variation in spatial and temporal precipitation patterns. In this study, climate change impacts were investigated on temperature, precipitation, and evapotranspiration of Neyshabour plane with the uncertainty of AOGCM models and emissions scenarios in the future period (2080-2099). First, the minimum and maximum temperature and precipitation for ten models of AOGCM under scenarios A2 and B1 in the future period and the baseline period of 1992-2011 were prepared and then downscaled by using of LARS_WG model. The reference evapotranspiration was calculated by FAO-Penman-Monteith method for all models and emission scenarios. The result showed that the value of evapotranspiration and temperature during the warm months were increased and the value of precipitation was decreased during the cold months. Also, monthly uncertainty was investigated for minimum and maximum temperature, precipitation, and evapotranspiration. The temperature and evapotranspiration in the warm months and precipitation in the cold months have less uncertainty than the other months. Also, the results of uncertainty analysis for models and emission scenarios are showed that NCARPCM and HADCM3 models in the estimation of minimum and maximum temperature, CGCM3T47as well as GFDLCM2 models in the estimation of precipitation have the best uncertainty results based on the two scenarios, respectively. The uncertainty analysis of AOGCM models determined that the best of uncertainty in the estimation of reference evapotranspiration for two scenarios is observed in the result of GISS-ER model. Also, the A2 scenario has the better function than the B1 scenario in the estimation of evapotranspiration parameter.

Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2 ˚C or 1.5 ˚C. However, with substantial variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University's Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research. [ABSTRACT FROM AUTHOR]

Previous studies have projected the Central Plains low‐level jet (LLJ) to form more frequently over the South‐Central Plains region in the future, with limited projected changes in its speed and height. This work's objective was to assess future LLJ characteristics with wind speed outputs obtained from the Phase 5 of the Coupled Model Intercomparison Project (CMIP5) suite of models. Improvements in model resolution and simulation of climate dynamics relevant to LLJs were made in CMIP5, and a multi‐model study that focuses specifically on the LLJ's future state using these models is yet to be done. Occurrences of LLJs were identified by applying an LLJ definition based on wind shear to six‐hourly vertical wind profiles derived from the model outputs. Changes in future LLJ speed, frequency, and height versus a historical control were subsequently calculated on seasonal and diurnal temporal scales. As seen in previous work, the largest expected changes in LLJ characteristics are those of its frequency, especially in summer, autumn, and at night. Evidence was also found for large increases in frequency in the northern half of the study region, consistent with previous expectations. CMIP5 models with finer horizontal and vertical resolutions tended to project greater increases in LLJ frequency than those with coarse resolutions. Projected changes in LLJ speed and height were by contrast largely insignificant, also consistent with previous findings. However, these characteristics, along with frequency, exhibited notable diurnal variability in historical and future simulations, especially in winter. An increase in cold‐season LLJ variability could have implications for the consistency of synoptically driven LLJs. This finding, along with the projected warm‐season poleward shift in the LLJ's frequency maximum over the study region, elucidates the LLJ's future state as projected by a selection of CMIP5 models, and the consequences for processes that depend upon the LLJ's consistency. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the potential impacts of an international initiative designed to support and promote the development and implementation of appliances standards and labelling programs throughout the world. As part of previous research efforts, LBNL developed the Bottom Up Energy Analysis System (BUENAS), an analysis framework that estimates impact potentials of energy efficiency policies on a global scale. In this paper, we apply this framework to an initiative that would result in the successful implementation of programs focused on high priority regions and product types, thus evaluating the potential impacts of such an initiative in terms of electricity savings and carbon mitigation in 2030. In order to model the likely parameters of such a program, we limit impacts to a five year period starting in 2009, but assume that the first 5 years of a program will result in implementation of 'best practice' minimum efficiency performance standards by 2014. The 'high priority' regions considered are: Brazil, China, the European Union, India, Mexico and the United States. The products considered are: refrigerators, air conditioners, lighting (both fluorescent and incandescent), standby power (for consumer electronics) and televisions in the residential sector, and air conditioning and lighting in commercial buildings. In 2020, these regions and enduses account for about 37percent of global residential electricity and 29percent of electricity in commercial buildings. We find that 850Mt of CO2 could be saved in buildings by 2030 compared to the baseline forecast.

This paper presents efforts to date and prospective goals towards development of a modelling and analysis framework which is comprehensive enough to address the global climate crisis, and detailed enough to provide policymakers with concrete targets and achievable outcomes. In terms of energy efficiency policy, this requires coverage of the entire world, with emphasis on countries and regions with large and/or rapidly growing energy-related emissions, and analysis at the 'technology' level-building end use, transport mode or industrial process. These elements have not been fully addressed by existing modelling efforts, which usually take either a top-down approach, or concentrate on a few fully industrialized countries where energy demand is well-understood. Inclusion of details such as appliance ownership rates, use patterns and efficiency levels throughout the world allows for a deeper understanding of the demand for energy today and, more importantly, over the coming decades. This is a necessary next step for energy analysts and policy makers in assessment of mitigation potentials. The modelling system developed at LBNL over the past 3 years takes advantage of experience in end use demand and in forecasting markets for energy-consuming equipment, in combination with known technology-based efficiency opportunities and policy types. A particular emphasis has been placed on modelling energy growth in developing countries. Experiences to date include analyses covering individual countries (China and India), end uses (refrigerators and air conditioners) and policy types (standards and labelling). Each of these studies required a particular effort in data collection and model refinement--they share, however, a consistent approach and framework which allows comparison, and forms the foundation of a comprehensive analysis system leading to a roadmap to address the greenhouse gas mitigation targets likely to be set in the coming years.

Climate change is accompanied by shifts in species distributions, as portions of current ranges become less suitable. Maintaining or improving landscape connectivity to facilitate species movements is a primary approach to mitigate the effects of climate change on biodiversity. However, it is not clear how ongoing changes in land use and climate may affect the existing connectivity of landscapes. We evaluated shifts in habitat suitability and connectivity for the imperiled Blanding's turtle ( Emydoidea blandingii ) in Wisconsin using species distribution modeling in combination with different future scenarios of both land use change and climate change for the 2050s. We found that climate change had significant effects on both habitat suitability and connectivity, however, there was little difference in the magnitude of effects among different economic scenarios. Under both our low- and high-CO 2 emissions scenarios, suitable habitat for the Blanding's turtle shifted northward. In the high-emissions scenario, almost no suitable habitat remained for Blanding's turtle in Wisconsin by the 2050s and there was up to a 100,000-fold increase in landscape resistance to turtle movement, suggesting the landscape essentially becomes impassable. Habitat loss and landscape resistance were exponentially greater in southern versus northern Wisconsin, indicating a strong trailing edge effect. Thus, populations at the southern edge of the range are likely to “fall behind” shifts in suitable habitat faster than northern populations. Given its limited dispersal capability, loss of suitable habitat may occur at a rate far faster than the Blanding's turtle can adjust to changing conditions via shifts in range. [ABSTRACT FROM AUTHOR]

ABSTRACT Precipitation, temperature, and evaporative demand are the most dominant factors affecting water availability in a region. This study examines projected changes in these hydro-climatic variables over western Canada under two greenhouse gas emissions scenarios using statistically downscaled, high resolution climate data generated by six Global Climate Models ( GCMs) from the latest Coupled Model Intercomparison Project ( CMIP5). Potential changes in the spatial and seasonal distributions of water availability over nine major western Canadian river basins are examined by computing the 3- and 12-month standardized precipitation and evapotranspiration indices ( SPEI-3 and SPEI-12). While individual GCM projections vary on the rate and seasonality of changes, they all indicate similar spatial and temporal patterns. The highest projected increases in precipitation and temperature are primarily in the northern basins, with some decreases in summer precipitation in the southern basins. The evolution of the SPEI-12 values for the southern basins such as Columbia, Saskatchewan, Fraser and Athabasca indicate a gradual increase in the magnitude and duration of water deficit, while the reverse was found for most of the northern basins such as Peel/Lower Mackenzie, Liard, and Northern Pacific that show a gradual increase in water surplus on an annual basis. The SPEI-3, however, shows that almost all river basins in western Canada, with the exception of Peel/Lower Mackenzie that are located in the extreme north of the study region, are projected to experience decreasing water availability in summer. In general, the study highlights the potential changes in the spatial and seasonal distribution of western Canadian water resources and sets the stage for a more detailed and process based hydro-climate modelling study to be conducted in the region. [ABSTRACT FROM AUTHOR]

In Algeria, energy consumption is growing rapidly. Due to the high demand and declining conventional energy resources, the country developed a new energy policy based on the promotion of renewable energies and CO2mitigation. For this purpose, the authorities have taken new steps to reinforce the legislative and institutional framework and put in place a favorable financial support. In addition, an ambitious program to develop solar energy and energy efficiency was adopted recently. The objective of this strategy is to achieve by 2030 a 40% share of solar electricity and to contribute, voluntarily, to reducing greenhouse gas (GHG) emissions. In this work, we present an analysis of the current situation and its projection to 2030 and we examine the available opportunities to reduce significantly GHG emissions. The study presents the magnitude of emissions in 2008 and 2012, the temporal evolution of CO2and particularly what will be the impact on GHG emissions of the new strategy. The results show that, in 2012, GHG emissions totaled 153 MT CO2eq. and growing at a rate of over 3%. However, there is a high potential for mitigation, especially in energy sectors, in building, transportation, as well as waste management and gas flaring. Two scenarios are developed: with implementation of solar energy and without. This analysis shows that the overall potential of CO2mitigation will rise in 2030 to about 300 MT CO2 eq. [ABSTRACT FROM PUBLISHER]

The new scenario framework developed by the climate change research community rests on the fundamental logic that a diversity of socio-economic pathways can lead to the same radiative forcing, and therefore that a given level of radiative forcing can have very different socio-economic impacts. We propose a methodology that implements a “scenario discovery” cluster analysis and systematically identifies diverse groups of scenarios that share common outcomes among a database of socio-economic scenarios. We demonstrate the methodology with two examples using the Shared Socio-economic Pathways framework. We find that high emissions scenarios can be associated with either high or low per capita GDP growth, and that high productivity growth and catch-up are not necessarily associated with high per capita GDP and high emissions. [ABSTRACT FROM AUTHOR]

Four policies might close the gap between the global GHG emissions expected for 2020 on the basis of current (2013) policies and the reduced emissions that will be needed if the long-term global temperature increase can be kept below the 2 °C internationally agreed limit. The four policies are (1) specific energy efficiency measures, (2) closure of the least-efficient coal-fired power plants, (3) minimizing methane emissions from upstream oil and gas production, and (4) accelerating the (partial) phase-out of subsidies to fossil-fuel consumption. In this article we test the hypothesis of the International Energy Agency (IEA) that these policies will not result in a loss of gross domestic product (GDP) and we estimate their employment effects using the E3MG global macro-econometric model. Using a set of scenarios we assess each policy individually and then consider the outcomes if all four policies were implemented simultaneously. We find that the policies are insufficient to close the emissions gap, with an overall emission reduction that is 30% less than that found by the IEA. World GDP is 0.5% higher in 2020, with about 6 million net jobs created by 2020 and unemployment reduced. Policy relevance The gap between GHG emissions expected under the Copenhagen and Cancun Agreements and that needed for emissions trajectories to have a reasonable chance of reaching the 2 °C target requires additional policies if it is to be closed. This article uses a global simulation model E3MG to analyse a set of policies proposed by the IEA to close the gap and assesses their macroeconomic effects as well as their feasibility in closing the gap. It complements the IEA assessment by estimating the GDP and employment implications separately by the different policies year by year to 2020, by major industries, and by 21 world regions. [ABSTRACT FROM AUTHOR]

This article illustrates the main difficulties encountered in the preparation of GHG emission projections and climate change mitigation policies and measures (P&M) for Kazakhstan. Difficulties in representing the system with an economic model have been overcome by representing the energy system with a technical-economic growth model (MARKAL-TIMES) based on the stock of existing plants, transformation processes, and end-use devices. GHG emission scenarios depend mainly on the pace of transition in Kazakhstan from a planned economy to a market economy. Three scenarios are portrayed: an incomplete transition, a fast and successful one, and even more advanced participation in global climate change mitigation, including participation in some emission trading schemes. If the transition to a market economy is completed by 2020, P&M already adopted may reduce emissions of CO2from combustion by about 85 MtCO2by 2030 – 17% of the emissions in the baseline (WOM) scenario. One-third of these reductions are likely to be obtained from the demand sectors, and two-thirds from the supply sectors. If every tonne of CO2not emitted is valued up to US$10 in 2020 and $20 in 2030, additional P&M may further reduce emissions by 110 MtCO2by 2030. This article analyses Kazakhstan's climate change and energy efficiency policies by making use of a modelling platform that provides a consistent framework for testing dynamic hypotheses. The effects of different P&M have been evaluated as the differences between two scenarios according to the United Nations Framework Convention on Climate Change (UNFCCC) reporting guidelines. It concludes that domestic climate mitigation objectives are synergistic with energy efficiency goals, and the set of policies adopted to achieve both objectives should be planned, implemented, and enforced jointly. It also quantifies the GHG emissions reduction if the transition to a market economy proceeds quickly and successfully (∼ −100 MtCO2e in 2030), and if a mitigation-specific policy is implemented (∼ −200 MtCO2e in 2030) compared to a baseline projection, and it highlights the need to prepare more robust and detailed energy balances and inventory of emissions in order to develop and monitor the progress of the policies. [ABSTRACT FROM AUTHOR]

Background Ozone and PM 2.5 are current risk factors for premature death all over the globe. In coming decades, substantial improvements in public health may be achieved by reducing air pollution. To better understand the potential of emissions policies, studies are needed that assess possible future health impacts under alternative assumptions about future emissions and climate across multiple spatial scales. Method We used consistent climate–air-quality–health modeling framework across three geographical scales (World, Europe and Ile-de-France) to assess future (2030–2050) health impacts of ozone and PM 2.5 under two emissions scenarios (Current Legislation Emissions, CLE, and Maximum Feasible Reductions, MFR). Results Consistently across the scales, we found more reductions in deaths under MFR scenario compared to CLE. 1.5 [95% CI: 0.4, 2.4] million CV deaths could be delayed each year in 2030 compared to 2010 under MFR scenario, 84% of which would occur in Asia, especially in China. In Europe, the benefits under MFR scenario (219 000 CV deaths) are noticeably larger than those under CLE (109 000 CV deaths). In Ile-de-France, under MFR more than 2830 annual CV deaths associated with PM 2.5 changes could be delayed in 2050 compared to 2010. In Paris, ozone-related respiratory mortality should increase under both scenarios. Conclusion Multi-scale HIAs can illustrate the difference in direct consequences of costly mitigation policies and provide results that may help decision-makers choose between different policy alternatives at different scales. [ABSTRACT FROM AUTHOR]

This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5° × 0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001-2010, 2041-2050, and 2091-2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer ( p < 0.01) adjusted means into letter comparisons. The study found that for most of the next 100 years in Louisiana, monthly mean temperature under all three emissions projections will increase; and monthly precipitation will, however, decrease. Under three emission scenarios, A1FI, A2, and B2, the mean SOC in the upper 30-cm depth of Louisiana forest soils will decrease from 33.0 t/ha in 2001 to 26.9, 28.4, and 29.2 t/ha in 2100, respectively; the mean SOC of Louisiana cropland soils will decrease from 44.4 t/ha in 2001 to 36.3, 38.4, and 39.6 t/ha in 2100, respectively; the mean SOC of Louisiana grassland soils will change from 30.7 t/ha in 2001 to 25.4, 26.6, and 27.0 t/ha in 2100, respectively. Annual SOC changes will be significantly different among the land cover classes including evergreen forest, mixed forest, deciduous forest, small grains, row crops, and pasture/hay ( p < 0.0001), emissions scenarios ( p < 0.0001), and their interactions ( p < 0.0001). [ABSTRACT FROM AUTHOR]

Climate change is the latest in a dismaying series of challenges that industrialism and modernity have gifted to humanity. To date, anthropological and archaeological responses have focused largely on the culturally particular--that is, on the interactions of climate, environment, cultural schema, and social systems in specific locales and eras. In this article, I urge a complementary response that capitalizes on archaeology and anthropology's holistic and universalistic investigative aspirations and expertise. For two decades, the Intergovernmental Panel on Climate Change (IPCC) has overseen major efforts to model human social dynamics and their implications for future climate change. These models are technically sophisticated but economically reductionist and substantively crude. Here, I review these efforts and provide three examples of how established and future archaeological and anthropological research could improve them. Recent changes to the IPCC's modeling regime make this an opportune moment for such a project. [ABSTRACT FROM AUTHOR]

ABSTRACT To account for CO2 impacts on the vegetation leaf area index ( LAI) and the different responses of stomatal conductance in various vegetation species, the modified Soil and Water Assessment Tool ( SWAT) model is calibrated in the Xinjiang Basin with the measured daily streamflow from 1961 to 1970, showing that SWAT accurately reproduces monthly and annual streamflow from 1971 to 2005 and actual evapotranspiration ( AET) from 1983 to 2005. AET and streamflow in the basin for the 21st century are assessed using a multi-model ensemble approach in which downscaled and bias corrected outputs are compared to the baseline (1971-1999) and used to drive the SWAT model. The ensemble average annual precipitation decreases in the three scenarios, with maximum decreases of 7.61% during 2011-2050 and 4.80% during 2051-2090 in scenario A2. In contrast, the ensemble average annual and monthly temperature (minimum and maximum) increase by different amounts during the two periods in each scenario. For each emissions scenario, the ensemble average annual AET will increase, while the average annual streamflow will decrease. Under the A2 scenario, the maximum changes of average annual AET (streamflow) are +18.31% (−20.93%) and +20.93% (−23.43%) during 2011-2050 and 2051-2090, respectively. Compared to the baseline, the ensemble average annual minimum streamflow during 2011-2050 will decrease by approximately 20% under the A1B and A2 scenarios and by 7% in the B1 scenario. Thus, the ensemble average annual maximum streamflow will decrease under each scenario during the two periods, except for a 6.42% increase in the A1B scenario during 2051-2090. A Generalized Extreme Value ( GEV) analysis, simultaneously, suggests that the maximum annual streamflow will decrease during the two periods under each scenario, with exception during 2051-2090 in the scenario A1B, and the magnitudes will decrease for 2-, 5-, 10-, 20- and 50-year return periods. [ABSTRACT FROM AUTHOR]

In the recent climate change negotiations it was declared that the increase in global temperature should be kept below 2°C by 2100, relative to pre-industrial levels. China's CO2emissions from energy and cement processes already account for nearly 24% of global emissions, a trend that is expected to keep increasing. Thus the role of China in global GHG mitigation is crucial. A scenario analysis of China's CO2emissions is presented here and the feasibility of China reaching a low-carbon scenario is discussed. The results suggest that recent and continued technological progress will make it possible for China to limit its CO2emissions and for these emissions to peak before 2025 and therefore that the global 2°C target can be achieved. Policy relevance In signing the Copenhagen Accord, China agreed to the global 2°C target. Results from this article could be used to justify low-carbon development policies and negotiations. While many still doubt the feasibility of a low-carbon pathway to support the global 2°C target, the results suggest that such a pathway can be realistically achieved. This conclusion should increase confidence and guide the policy framework further to make possible China's low-carbon development. Related policies and measures, such as renewable energy development, energy efficiency, economic structure optimization, technology innovation, low-carbon investment, and carbon capture and storage (CCS) development, should be further enhanced. Furthermore, China can play a larger role in the international negotiations process. In the global context, the 2°C target could be reaffirmed and a global regime on an emissions mitigation protocol could be framed with countries’ emissions target up to 2050. [ABSTRACT FROM PUBLISHER]

In the recent climate change negotiations it was declared that the increase in global temperature should be kept below 2°C by 2100, relative to pre-industrial levels. China's CO2 emissions from energy and cement processes already account for nearly 24% of global emissions, a trend that is expected to keep increasing. Thus the role of China in global GHG mitigation is crucial. A scenario analysis of China's CO2 emissions is presented here and the feasibility of China reaching a low-carbon scenario is discussed. The results suggest that recent and continued technological progress will make it possible for China to limit its CO2 emissions and for these emissions to peak before 2025 and therefore that the global 2°C target can be achieved. Policy relevance In signing the Copenhagen Accord, China agreed to the global 2°C target. Results from this article could be used to justify low-carbon development policies and negotiations. While many still doubt the feasibility of a low-carbon pathway to support the global 2°C target, the results suggest that such a pathway can be realistically achieved. This conclusion should increase confidence and guide the policy framework further to make possible China's low-carbon development. Related policies and measures, such as renewable energy development, energy efficiency, economic structure optimization, technology innovation, low-carbon investment, and carbon capture and storage (CCS) development, should be further enhanced. Furthermore, China can play a larger role in the international negotiations process. In the global context, the 2°C target could be reaffirmed and a global regime on an emissions mitigation protocol could be framed with countries' emissions target up to 2050. [ABSTRACT FROM AUTHOR]