Impact of Climate Data Sources on Pavement Mechanistic-Empirical Design Pavement Distress Predictions

In the Pavement Mechanistic-Empirical Design (PMED) approach, several climatic factors such as air temperature, precipitation, percentage sunshine, and humidity are considered for analyzing and predicting pavement distresses. Current version of AASHTOWare (version 2.6.22) is integrated with Modern Era Retrospective Analysis for Research and Application (MERRAv2.0) database to retrieve these climatic data inputs for prediction of distresses in flexible pavements. This paper compared the predicted distresses of flexible pavements designed for different locations in the state of New Jersey using three climate data sources: (1) MERRA database from the National Aeronautical and Space Administration (NASA); (2) MERRAv2.0, an improved version of MERRA; and (3) North American Regional Reanalysis (NARR) data supplied with the AASHTOWare version 2.3.1. Predictions on permanent deformation in asphalt layer and bottom-up cracking in asphalt layer were found to be the most affected distresses due to change in climatic data source. NARR climatic data set had a lower prediction on permanent deformation in asphalt layer and bottom-up cracking compared to MERRA and MERRAv2.0. Permanent deformations in asphalt layer using MERRA and MERRAv2 were found sensitive to the bias in windspeed data that was specific to certain locations. MERRAv2 had a higher prediction value (up to 40%) for bottom-up cracking compared to that of MERRA climatic data. International Roughness Index (IRI), top-down cracking, and thermal cracking were found to be least affected due to change in climatic data source. Consequently, this could lead to assessing the requirement for recalibration of the performance prediction models for the state of New Jersey.