Understanding the vulnerability and response of human society to climate change is necessary for sound decisionmaking in climate policy, but progress is made difficult by the fact that science and information products must be integrated across at least three fields: geosciences for the physical effects of climate change, environmental science for the biosphere responses, and economics for the impacts to human welfare and subsequent adaptations. The research agenda described here leverages high-performance computing to address key challenges at this interface and incorporate climate change vulnerabilities, impacts, and adaptations (VIA) consistently into an economic modeling and analysis framework using biophysical and statistical models. The overall goal is an improved understanding of the interactions of climate and socio-economic changes on: 1) the supply and demand of agricultural commodities, 2) local land-use and land-cover, and 3) regional and global food sustainability. This is accomplished through the development of a number of research products and technologies including a new framework for massively parallel simulations of impact models, a methodology and software suite for scaling the resulting measures to arbitrary spatial scales, a set of validation experiments and skill-based multi-model ensemble averaging techniques, and a set of scenario based adaptation experiments to evaluate “sociotechnical and environmental pathways to sustainable food and climate futures.” The program outlined also includes developing new tools for delivering information directly to decision-makers operating at a variety of scales from international policy-makers to local watershed managers and agricultural development authorities.
Many collaborative initiatives and institutions around the world have undertaken large-scale projects to address underlying scientific questions about productivity and environmental sustainability, as well as gather, produce, and distribute the technology, data, and information products required by stakeholders and policy-makers. To be credible, these assessments must account simultaneously for the socio-economic drivers of demand, the environmental limitations and changes from a warming climate, and the potential and limitations for sociotechnical adaptations to vulnerabilities and impacts. To be maximally useful, they must additionally be able to address the major underlying uncertainties in the system and deliver information products and impact measures across a wide range of spatial and temporal scales that communicate these uncertainties. We are partnering with many such institutions in our research efforts, providing a wide variety of learning and collaboration opportunities for students in socio-economic, policy, climate, VIA, and computational sciences. To address top-down large scale policy-making and planning needs (primarily at the national and international level), the center for Robust Decision-making in Climate and Energy Policy (RDCEP), an international collaboration of researchers founded in 2010 and centered at the University of Chicago Computation Institute, is creating a new high-performance open source socio-economic and integrated assessment modeling framework called the Community Integrated Model of Economic and Resource Trajectories for Humankind (CIM-EARTH). At the opposite extremes of scale, the Agricultural Modeling Intercomparison and Improvement Project (AgMIP), an international collaboration also founded in 2010, seeks to produce the next generation of agricultural climate vulnerability and impact measures through a distributed simulation exercise that uses multi-model (of both climate and impacts) ensemble information to characterize impacts and uncertainties at the field scale, along with a variety of aggregation and scaling methodologies to translate these distributions to decision relevant environmental and political scales (e.g. county, watershed, or national boundaries). To help integrate different parts of the VIA puzzle into a more consistent view of the overall impact picture, the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP) was recently initiated and covers agriculture, water, health, and biomes models.
The basic high-level methodological elements of the research agenda are 1) simulate, at high resolution and continental/global extent, the impacts of a changing climate on primary production (agriculture, livestock/pasture, and forestry) around the world, 2) produce tools that can aggregate these measures consistently to arbitrary boundaries for use in economic models and analysis at decision-relevant scales, and 3) characterize uncertainties inherent in the estimates, develop methods to track uncertainty through scaling and aggregation, and determine regimes in which estimates can be considered more or less robust.