Efficient method for revealing key uncertainties proves viable in regional integrated assessment analysis
In a direct evaluation of the uncertainty characterization process being applied as part of the Platform for Regional Integrated Modeling and Analysis (PRIMA) framework, Pacific Northwest National Laboratory scientists examined building energy policy under multiple energy-efficiency settings and several distinct uncertainty scenarios using a sub-regional version of the Global Change Assessment Model known as GCAM-USA. Their goal was to develop a decision-focused (i.e., relevant to a particular stakeholder) sensitivity analysis that identified factors that most influence stakeholder decisions. In an effort to generate an option that falls between ad hoc one-variable-at-a-time sensitivity assessments (for large models) or Monte Carlo analysis of all potential uncertainties (for small models), PNNL scientists used a middle-course, fractional-factorial analysis method to test the building energy policies. Their work showed that the number of factors required for modeling a given GCAM outcome actually was small, greatly reducing the modeling and computational burden in the presence of...