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High-albedo materials reflect more solar radiation and, thereby, alter the earth's radiative balance. Increasing pavement albedo, therefore, has been considered as a technological strategy to mitigate global warming. Previous studies have evaluated this strategy using global average models. To factor this effect into life cycle assessments, location-specific models of the albedo effect for pavements are required. A parametric analytical model is developed to estimate the radiative forcing (RF) using a novel model form and an iterative solution approach. The new model is extended to estimate the corresponding global warming potential (GWP) over an analysis period of 50 years for an albedo change in a pavement surface. This was applied to quantify the GWP impacts of increasing pavement albedo in 14 cities across various climate zones in the US. For the United States, the GWP in kg CO2 equivalent per square meter of altered surface ranges from 0.8 to 1.6 per 0.01 change in albedo, a range of more than 40%. Analysis of a hypothetical albedo change to all darker pavements in the US would produce a negative RF of a magnitude equivalent to that associated with a reduction in CO2 emissions of more than 17 Mton per year.

We consider the interplay of climate change impacts, global mitigation policies, and the economic interests of developing countries to 2050. Focusing on Malawi, Mozambique, and Zambia, we employ a structural approach to biophysical and economic modeling that incorporates climate uncertainty and allows for rigorous comparison of climate, biophysical, and economic outcomes across global mitigation regimes. We find that effective global mitigation policies generate two sources of benefit. First, less distorted climate outcomes result in typically more favorable and less variable economic outcomes. Second, successful global mitigation policies reduce global fossil fuel producer prices, relative to unconstrained emissions, providing a substantial terms of trade boost of structural fuel importers. Combined, these gains are on the order of or greater than estimates of mitigation costs. These results highlight the interests of most developing countries in effective global mitigation policies, even in the relatively near term, with much larger benefits post-2050.

Regional climate models (RCMs) can simulate heavy precipitation more accurately than general circulation models (GCMs) through more realistic representation of topography and mesoscale processes. Analogue methods of downscaling, which identify the large-scale atmospheric conditions associated with heavy precipitation, can also produce more accurate and precise heavy precipitation frequency in GCMs than the simulated precipitation. In this study, we examine the performances of the analogue method versus direct simulation, when applied to RCM and GCM simulations, in detecting present-day and future changes in summer (JJA) heavy precipitation over the Midwestern United States. We find analogue methods are comparable to MERRA-2 and its bias-corrected precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events, all significantly improving upon MERRA precipitation. For the late twentieth-century heavy precipitation frequency, RCM precipitation improves upon the corresponding driving GCM with greater accuracy yet comparable inter-model discrepancies, while both RCM- and GCM-based analogue results outperform their model-simulated precipitation counterparts in terms of accuracy and model consensus. For the projected trends in heavy precipitation frequency through the mid twenty-first century, analogue method also manifests its superiority to direct simulation with reduced intermodel disparities, while the RCM-based analogue and simulated precipitation do not demonstrate a salient improvement (in model consensus) over the GCM-based assessment. However, a number of caveats preclude any overall judgement, and further work—over any region of interest—should include a larger sample of GCMs and RCMs as well as ensemble simulations to comprehensively account for internal variability.

Large power transformers (LPTs) are critical yet vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and increase the risk of premature failure. Without adequate preparedness, a widespread situation could ultimately lead to prolonged grid disruption and incur excessive economic costs. Here, we investigate the potential impact of climate warming and corresponding shifts in summertime “hot days” on a selected LPT located in the Northeast United States. We apply an analogue method, which detects the occurrence of hot days based on the salient, associated large-scale atmospheric conditions, to assess the risk of future change in their occurrence. Compared with the more conventional approach that relies on climate model-simulated daily maximum temperature, the analogue method produces model medians of late twentieth century hot day frequency that are more consistent with observation and have stronger inter-model consensus. Under the climate warming scenarios, multi-model medians of both model daily maximum temperature and the analogue method indicate strong decadal increases in hot day frequency by the late twenty-first century, but the analogue method improves model consensus considerably. The decrease of transformer lifetime with temperature increase is further assessed. The improved inter-model consensus of the analogue method is viewed as a promising step toward providing actionable information for a more stable, reliable, and environmentally responsible national grid.

We assess the ability of global water systems, resolved at 282 large river basins or Assessment Sub Regions (ASRs), to the meet water requirements over the coming decades under integrated projections of socioeconomic growth and climate change. We employ a Water Resource System (WRS) component embedded within the MIT Integrated Global System Model (IGSM) framework in a suite of simulations that consider a range of climate policies and regional hydroclimatic changes through the middle of this century. We find that for many developing nations water-demand increases due to population growth and economic activity have a much stronger effect on water stress than climate change. By 2050, economic growth and population change alone can lead to an additional 1.8 billion people living in regions with at least moderate water stress. Of this additional 1.8 billion people, 80% are found in developing countries. Uncertain regional climate change can play a secondary role to either exacerbate or dampen the increase in water stress due to socioeconomic growth. The strongest climate impacts on relative changes in water stress are seen over many areas in Africa, but strong impacts also occur over Europe, Southeast Asia and North America. The combined effects of socioeconomic growth and uncertain climate change lead to a 1.0 to 1.3 billion increase of the world's 2050 projected population living in regions with overly exploited water conditions— where total potential water requirements will consistently exceed surface-water supply. Under the context of the WRS model framework, this would imply that adaptive measures would be taken to meet these surface-water shortfalls and would include: water-use efficiency, reduced and/or redirected consumption, recurrent periods of water emergencies or curtailments, groundwater depletion, additional inter-basin transfers, and overdraw from flow intended to maintain environmental requirements.

The growing need for risk-based assessments of impacts and adaptation to climate change calls for increased capability in climate projections: specifically, the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Herein, the authors present a technique that extends the latitudinal projections of the 2D atmospheric model of the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate model projections archived from exercises carried out for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a set of transformation coefficients, and this approach is demonstrated in application to near-surface air temperature and precipitation, for which high-quality observational datasets and model simulations of climate change are available. The current climatology of the transformation coefficients is observationally based. To estimate how these coefficients may alter with climate, the authors characterize the climate models’ spatial responses, relative to their zonal mean, from transient increases in trace-gas concentrations and then normalize these responses against their corresponding transient global temperature responses. This procedure allows for the construction of metaensembles of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with regionally resolved patterns from the archived IPCC climate model projections. This hybridization of the climate model longitudinal projections with the global and latitudinal patterns projected by the IGSM can, in principle, be applied to any given state or flux variable that has the sufficient observational and model-based information.

[1] A global biofuels program will potentially lead to intense pressures on land supply and cause widespread transformations in land use. These transformations can alter the Earth climate system by increasing greenhouse gas (GHG) emissions from land use changes and by changing the reflective and energy exchange characteristics of land ecosystems. Using an integrated assessment model that links an economic model with climate, terrestrial biogeochemistry, and biogeophysics models, we examined the biogeochemical and biogeophysical effects of possible land use changes from an expanded global second-generation bioenergy program on surface temperatures over the first half of the 21st century. Our integrated assessment model shows that land clearing, especially forest clearing, has two concurrent effects—increased GHG emissions, resulting in surface air warming; and large changes in the land's reflective and energy exchange characteristics, resulting in surface air warming in the tropics but cooling in temperate and polar regions. Overall, these biogeochemical and biogeophysical effects will only have a small impact on global mean surface temperature. However, the model projects regional patterns of enhanced surface air warming in the Amazon Basin and the eastern part of the Congo Basin. Therefore, global land use strategies that protect tropical forests could dramatically reduce air warming projected in these regions.

Government organizations are responsible for strategic decisions regarding the economic development of individual countries and regional areas. This decision-making process is influenced by the certainty of the information presented to government officials. One area where this decision-making influence is challenging government officials is in climate-based events. The past decade has witnessed a significant rise in the number of climate events, as well as the number of people affected by climate events. Far from being under control, evidence and long-term projections suggest that these events are climate-based rather than weather-based. In these projections, climate change is a global issue with potential impacts for every country. However, the relative impact of these events will be far different in the developed and developing worlds. As detailed in this paper, the authors examined this disparity through an analysis of 10 countries with varying income levels to determine the relative impact of climate ...

The adequacy of freshwater resources remains a critical challenge for a sustainable and growing society. We present a self-consistent risk-based assessment of water availability and use under future climate change and socioeconomic growth by midcentury across southern and eastern Asia (SEA). We employ large ensemble scenarios from an integrated modeling framework that are consistent across the spectrum of regional climate, population, and economic projections. We find socioeconomic growth contributes to an increase in water stress across the entire ensemble. However, climate change drives the ensemble central tendency toward an increase in water stress in China but a reduction in India, with a considerable spread across the ensemble. Nevertheless, the most deleterious unabated climate-change impact is a low probability but salient extreme increase in water stress over China and India. In these outcomes, annual withdrawals will routinely exceed water-storage capacity. A modest greenhouse gas mitigation pathway eliminates the likelihood of these extreme outcomes and also benefits hundreds of millions of people at risk to various levels of water stress increase. Over SEA we estimate an additional 200 million people under threat of facing at least heavily water-stressed conditions from climate change and socioeconomic growth, but the mitigation scenario reduces the additional population-under-threat by 30% (60 million). Nevertheless, there remains a 1-in-2 chance that 100 million people across SEA experience a 50% increase in water stress and a 1-in-10 chance they experience a doubling of water stress. Therefore, widespread adaptive measures may be required over the coming decades to meet these unavoidable risks in water shortfalls.

This paper is an empirical investigation of the effects of climate on the use of electricity by consumers and producers in urban and rural areas within China. It takes advantage of an unusual combination of temporal and regional data sets in order to estimate temperature, as well as price and income elasticities of electricity demand. The estimated positive temperature/electric power feedback implies a continually increasing use of energy to produce electric power which, in China, is primarily based on coal. In the absence of countervailing measures, this will contribute to increased emissions, increased atmospheric concentrations of greenhouse gases, and increases in greenhouse warming.

This study represents the first attempt at an integrated approach to assessing the potential impacts of climate change on the national economy of South Africa via a number of (but not necessarily all) impact channels. The study focuses on outcomes by abou

We consider the interplay of climate change impacts, global mitigation policies, and the interests of developing countries to 2050. Focusing on Malawi, Mozambique, and Zambia, we employ a structural approach to biophysical and economic modeling that incorporates climate uncertainty and allows for rigorous comparison of climate, biophysical, and economic outcomes across global mitigation regimes. We find that effective global mitigation policies generate two sources of benefit. First, less distorted climate outcomes result in typically more favourable economic outcomes. Second, successful global mitigation policies reduce global fossil fuel producer prices, relative to unconstrained emissions, providing a substantial terms of trade boost to structural fuel importers. Combined, these gains are on the order of or greater than estimates of mitigation costs. These results highlight the interests of most developing countries in effective global mitigation policies, even in the relatively near term, with the likelihood of much larger benefits post 2050.

Projections of regional changes in surface air temperature and precipitation for the greater Nile River basin and northern Africa are presented. The probabilistic projections are obtained through a technique that combines projections of the MIT Integrated Global System Model with climate-change patterns of the Intergovernmental Panel on Climate Change. Overall, the most consistent response to climate policy is seen in the distributions of temperature change. For precipitation, the predominant climate stabilization response is to reduce the likelihood of modal change.

Biofuel Backfire For compelling economical, geopolitical, and environmental reasons, biofuels are considered an attractive alternative to fossil fuels for meeting future global energy demands. Melillo et al. (p. 1397 , published online 22 October), however, suggest that a few serious drawbacks related to land use need to be considered. Based on a combined biogeochemistry and economic model, indirect land use (for example, clearing forested land for food crops to compensate for increased biofuel crop production on current farmlands) is predicted to generate more soil carbon loss than directly harvesting biofuel crops. Furthermore, increased fertilizer use for biofuels will add large amounts of nitrous oxide—a more effective heat-trapping molecule than carbon dioxide—to the atmosphere. Policy decisions regarding land and crop management thus need to consider the long-term implications of increased biofuel production.

Traditional `delta-change´ approach of scenario generation for climate change impact assessment to water resources strongly depends on the selected base-case observed historical climate conditions that the climate shocks are to be super-imposed. This met

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., United Nations University. World Institute for Development Economics Research, Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change

Climate change and permafrost thaw have been suggested to increase high latitude methane emissions that could potentially represent a strong feedback to the climate system. Using an integrated earth-system model framework, we examine the degradation of near-surface permafrost, temporal dynamics of inundation (lakes and wetlands) induced by hydro-climatic change, subsequent methane emission, and potential climate feedback. We find that increases in atmospheric CH[subscript 4] and its radiative forcing, which result from the thawed, inundated emission sources, are small, particularly when weighed against human emissions. The additional warming, across the range of climate policy and uncertainties in the climate-system response, would be no greater than 0.1 ° C by 2100. Further, for this temperature feedback to be doubled (to approximately 0.2 ° C) by 2100, at least a 25-fold increase in the methane emission that results from the estimated permafrost degradation would be required. Overall, this biogeochemical global climate-warming feedback is relatively small whether or not humans choose to constrain global emissions., United States. Dept. of Energy (Climate Change Prediction Program Grant DE-PS02-08ER08-05), United States. Dept. of Energy. Office of Science (Biological and Environmental Research)

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States (US) associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections, global climate system parameters, natural variability and model structural uncertainty. The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an Earth System Model of Intermediate Complexity (EMIC) (with a two-dimensional zonal-mean atmosphere). Regional climate change over the US is obtained through a two-pronged approach. First, we use the IGSM-CAM framework, which links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Second, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that the range of annual mean temperature changes are mainly driven by policy choices and the range of climate sensitivity considered. Meanwhile, the four sources of uncertainty contribute more equally to end-of-century precipitation changes, with natural variability dominating until 2050. For the set of scenarios used in this study, the choice of policy is the largest driver of uncertainty, defined as the range of warming and changes in precipitation, in future projections of climate change over the US., United States. Environmental Protection Agency. Climate Change Division (Cooperative Agreement #XA-83600001)

The mitigation of potential climate change while sustaining energy resources requires global attention and cooperation. Among the numerous strategies to reduce Green House Gas (GHG) emissions is to decommission carbon intensive electricity production while increase the deployment of renewable energy technologies – such as wind and solar power generation. Yet the generation capacity, availability, and intermittency of these renewable energy sources are strongly climate dependent – and may also shift due to unavoidable human-induced change. In this study, we present a method, based on previous studies, that estimates the risk of climate-change on wind and solar resource potential. The assessment combines the risk-based climate projections from the Integrated Global Systems Model (IGSM), which considers emissions and global climate sensitivity uncertainty, with more regionally detailed climate information from 8 GCMs available from the Coupled Model Intercomparison Project phase 3 (CMIP-3). Southern Africa, specifically those in the Southern African Development Countries (SADC), is used as a case study. We find a median change close to zero by 2050 in the long-term mean of both wind speed and Global Horizontal Irradiance (GHI), both used as indicators of changes in electricity production potential. Although the extreme possibilities range from about −15% to +15% change, these are associated with low probability. The most prominent effect of a modest climate mitigation policy is seen in the doubled likelihood of the mode of the distribution of wind power change. This increased likelihood is made at the expense of decreased likelihood in the large changes of the distribution, but these trade-offs with the more extreme likelihoods are not symmetric with respect to the modal change.