Regional Analysis

A Contemporary Carbon Balance for the Northeast Region of the United States

Development of regional policies to reduce net emissions of carbon dioxide (CO2) would benefit from the quantification of the major components of the region’s carbon balance fossil fuel CO2 emissions and net fluxes between land ecosystems and the atmosphere. Through spatially detailed inventories of fossil fuel CO2 emissions and a terrestrial biogeochemistry model, we produce the first estimate of regional carbon balance for the Northeast United States between 2001 and 2005. Our analysis reveals that the region was a net carbon source of 259 Tg C/yr over this period. Carbon sequestration by land ecosystems across the region, mainly forests, compensated for about 6% of the region’s fossil fuel emissions. Actions that reduce fossil fuel CO2 emissions are key to improving the region’s carbon balance. Careful management of forested lands will be required to protect their role as a net carbon sink and a provider of important ecosystem services such as water purification, erosion control, wildlife habitat and diversity, and scenic landscapes.

© 2013 American Chemical Society

A Dynamic General Equilibrium Analysis of Adaptation to Climate Change in Ethiopia

This study links a multisectoral, regionalized, dynamic, computable general equilibrium (CGE) model of Ethiopia with a system country-specific hydrology, crop, road, and hydropower engineering models to simulate the economic impacts of climate change scenarios from global circulation models (GCMs) to 2050. In the absence of externally funded, policy-driven adaptation investments, Ethiopia's GDP in 2050 will be up to 10% below the counterfactual no climate change (historical climate) baseline. Suitably designed adaptation investments could restore aggregate welfare to baseline levels at a cost that is substantially lower than the welfare losses as a result of climate change. Such investments, even if funded from domestic resources, have benefits that greatly exceed their costs, and are largely consistent with Ethiopia's long-run development strategy.

© 2012 Blackwell Publishing Ltd.

A Framework for Analysis of the Uncertainty of Socioeconomic Growth and Climate Change on the Risk of Water Stress: a Case Study in Asia

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in how these factors change in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. If socio-economic growth is unconstrained by global actions to limit greenhouse gas concentrations, water-stressed populations may increase from about 800 million to 1.7 billion in this region.

A framework for modeling uncertainty in regional climate change

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 IGSMCAM 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.

© 2014 Springer Science+Business Media

A Framework for Modeling Uncertainty in Regional Climate Change

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 US associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections (using different climate policies), climate system parameters (represented by different values of climate sensitivity and net aerosol forcing), natural variability (by perturbing initial conditions) and structural uncertainty (using different climate models). The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an intermediate complexity earth system model (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). Secondly, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that uncertainty in 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 precipitation changes, with natural variability having a large impact in the first part of the 21st century. Overall, the choice of policy is the largest driver of uncertainty in future projections of climate change over the US.

Pages

Subscribe to Regional Analysis