A method to select general circulation models for pavement performance evaluation

Studies to understand the role of future climate on transportation infrastructure may use climate multiple models and interpret the results based on the statistical variation in simulated outcomes. Unfortunately, specific guidance on the models to choose that ensure results span the breadth of possible outcomes is limited, and the solution involves running simulations using as many models as possible. The objective of this study is to provide guidance on which models from the Coupled Intercomparison Project 5 (CMIP5) dataset to use for pavement studies in the United States and in so doing provide a framework for selecting models from other datasets and locations. Effective temperature functions are derived and used to select individual models from the CMIP5 dataset that represent the maximum, median, and minimum outcomes of the whole ensemble. The results are clustered based on region and represent relatively hot, cold, and median future assumptions. The model selection process is verified using detailed pavement analyses with all models at individual pavement sites in four states. The models chosen using the effective temperature approach are found to align with the extremes and the median, with further improvements to median estimates obtained by averaging all three (maximum, minimum, and median) models.