This collaborative research group will undertake research aimed at improving the models needed to evaluate environmental and energy policy and to make robust decisions based on outcomes. Addressing the consequences of a changing environment for the economy, food and water security, and energy supply is an increasingly urgent challenge. New understanding and analysis tools are needed that can allow decision makers to act in the presence of uncertainty. The models to be developed will provide deeper understanding and actionable information about the potential future of Earth and human society, improve capabilities to forecast future conditions, and quantify the uncertainty around projections so that decision makers can balance risk and reward. This collaborative group includes experts in economics, physical sciences, energy technologies, law, computational mathematics, statistics, and computer science to improve and connect the methods and models needed to evaluate energy, economics, agriculture, and other sectors. The collaborative group will engage high school students, undergraduates, graduate students, and postdoctoral scholars in its work, contributing to the education of a diverse population. All models, data, and tools developed by the collaborative group will be openly available to the research, policy, and citizen communities to encourage use and participation.
This collaborative group will work to realize opportunities inherent in new data sources, computational capabilities, participants, and collaborations. The collaborative group will conduct research in five key areas: (1) Improved characterizations of future climate. The collaborative group will develop new understanding of what state-of-the-art models have to say about likely changes in climate extremes and variability. (2) Characterization of environmental impacts. The collaborative group will develop more powerful computational tools to forecast the influence of environmental change upon economics, agriculture, land use, demographics, and other sectors. Experts from multiple disciplines will collaborate on building new computational models, conducting comparisons of existing models, distributing historical data for model evaluation and validation, and using multiple models for impact assessments. (3) Integrating uncertain information. The best policies for preventing environmental damage are likely to be those that best balance return and risk in the face of many uncertainties. The collaborative group will develop models to identify robust strategies that perform well over a wide range of scenarios. (4) Evaluation of models. The collaborative group will develop methods for evaluating the confidence that can be placed in different projections of future climate and impacts. (5) Computational technologies. The collaborative group will develop new web tools, numerical solution methods, and large-scale models that make full use of modern supercomputers. These tools will allow researchers to add additional detail to models, explore uncertainty, and deliver previously impossible results. This collaborative group project is supported by the NSF Directorate for Social, Behavioral, and Economic Sciences through its Decision Making Under Uncertainty (DMUU) funding opportunity.
