Abstract Manager

Performance predictions produced using AASHTOWare Pavement Mechanistic–Empirical Design (PMED) are highly sensitive to climatic inputs. Although PMED is calibrated using MERRA-2 reanalysis data to support realistic project-level performance prediction, the transient variability and sequencing inherent in reanalysis climate data can obscure interpretation of pavement response mechanisms and confound assessment of the relative influence of traffic, materials, and structural design parameters. Furthermore, projected climate change introduces additional uncertainty, as shifts in temperature, precipitation, and freeze–thaw cycles can alter pavement performance over its service life. This study evaluates the sensitivity of flexible pavement performance predictions to key design variables, including traffic volume and pavement structural configuration, while accounting for climatic influences by employing Typical Meteorological Year (TMY) climate data as a controlled and repeatable baseline. The objective is to isolate and benchmark sensitivities within the PMED framework, while providing a basis for assessing potential climate change impacts on pavement durability. A multi-regional Canadian case study conducted across ten cities demonstrates that the proposed framework enables more transparent comparison of design alternatives, reduces uncertainty in PMED outputs, and facilitates preliminary evaluation of climate-driven performance shifts. The results show that the TMY-based approach is effective for exploring performance trends, comparing alternative structural configurations, and assessing the influence of design variables such as material selection, traffic loading, and evolving climate conditions.