Effective climate policy will consist of mitigation and adaptation implemented simultaneously in a policy portfolio to reduce the risks of climate change. Previous studies of the tradeoffs between mitigation and adaptation have implicitly framed the problem deterministically, choosing the optimal paths for all time. Because climate change is a long-term problem with significant uncertainties and opportunities to learn and revise, critical tradeoffs between mitigation and adaptation in the near-term have not been considered. We propose a new framework for considering the portfolio of mitigation and adaptation that explicitly treats the problem as a multi-stage decision under uncertainty. In this context, there are additional benefits to near-term investments if they reduce uncertainty and lead to improved future decisions. Two particular features are fundamental to understanding the relevant tradeoffs between mitigation and adaptation: (1) strategy dynamics over time in reducing climate damages, and (2) strategy dynamics under uncertainty and potential for learning. Our framework strengthens the argument for disaggregating adaption as has been proposed by others. We present three stylized classes of adaptation investment types as a conceptual framework: short-lived “flow” spending, committed “stock” investment, and lower capacity “option” stock with the capability of future upgrading. In the context of sequential decision under uncertainty, these subtypes of adaptation have important tradeoffs among them and with mitigation. We argue that given the large policy uncertainty that we face currently, explicitly considering adaptation “option” investments is a valuable component of a near-term policy response that can balance between the flexible flow and committed stock approaches, as it allows for the delay of costly stock investments while at the same time allowing for lower-cost risk management of future damages.

Through the integration of a Water Resource System (WRS) component, the MIT Integrated Global System Model (IGSM) framework has been enhanced to study the effects of climate change on managed water-resource systems. Development of the WRS involves the downscaling of temperature and precipitation from the zonal representation of the IGSM to regional (latitude-longitude) scale, and the translation of the resulting surface hydrology to runoff at the scale of river basins, referred to as Assessment Sub-Regions (ASRs). The model of water supply is combined with analysis of water use in agricultural and non-agricultural sectors and with a model of water system management that allocates water among uses and over time and routes water among ASRs. Results of the IGSM-WRS framework include measures of water adequacy and ways it is influenced by climate change. Here we document the design of WRS and its linkage to other components of the IGSM, and present tests of consistency of model simulations with the historical record.

Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select “wet” and “dry” patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

Climate and energy policy in China will have important and uneven impacts on the country’s regionally heterogeneous transport system. In order to simulate these impacts, transport sector detail is added to a multi-sector, static, global computable general equilibrium (CGE) model which resolves China’s provinces as distinct regions. This framework is used to perform an analysis of national-level greenhouse gas (GHG) policies. Freight, commercial passenger and household (private vehicle) transport are separately represented, with the former two categories further disaggregated into road and non-road modes. The preparation of model inputs is described, including assembly of a provincial transport data set from publicly-available statistics. Two policies are analyzed: the first represents China’s target of a 17% reduction in GHG emissions intensity of GDP during the Twelfth Five Year Plan (12FYP), and the second China’s Copenhagen target of a 40–45% reduction in the same metric during the period 2005–2020.

We find significant heterogeneity in regional transport impacts. We find that both freight and passenger transportation in some of the poorest provinces are most adversely affected, as their energy-intensive resource and industrial sectors offer many of the least-cost abatement opportunities, and the transformation of their energy systems strongly affects transport demand. At the national level, we find that road freight is the transport sector affected most by policy, likely due to its high energy intensity and limited low-cost opportunities for improving efficiency.

The type and degree of regional disparity in impacts is relevant to central and provincial government decisions which set and allocate climate, energy and transport policy targets. We describe how this research establishes a basis for regional CGE analysis of the economic, energy and environmental impacts of transport-focused policies including vehicle ownership restrictions, taxation of driving activity or fuels, and the supply of public transit.