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To improve the climate resiliency of existing and new pavements, it is important to carry out pavement designs using continuous climate records at high temporal frequencies. Over the years, significant research efforts have been dedicated to obtain high-quality climatic data for pavement design including the latest adoption of the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The purpose of this study is to assess how MERRA-2 performs when compared to the Canadian Weather Energy and Engineering Datasets (CWEEDS), which provides hourly meteorological data for many parts of the country from various periods. In the first part, climate parameters at nine locations were directly compared to determine the correlation between two data sets. In the second part, long-term performances were simulated for typical flexible pavement to assess the relative impact of each climate scenario. As detailed in this paper, observed differences between MERRA-2 and CWEEDS indicate the need for further improvement of climate data quality and availability for designing resilient pavements in Canada. [ABSTRACT FROM AUTHOR]

Climate change is expected to impact both the operational and structural performance of infrastructures such as roads, bridges, and buildings. However, most past life cycle assessment (LCA) studies do not consider how the operational/structural performance of infrastructure will be affected by a changing climate. The goal of this research was to develop a framework for integrating climate change impacts into LCA of infrastructure systems. To illustrate this framework, a flexible pavement case study was considered where life‐cycle environmental impacts were compared across a climate change scenario and several time horizons. The Mechanistic‐Empirical Pavement Design Guide (MEPDG) was utilized to capture the structural performance of each pavement performance scenario and performance distresses were used as inputs into a pavement LCA model that considered construction and maintenance/rehabilitation materials and activities, change in relative surface albedo, and impacts due to traffic. The results from the case study suggest that climate change will likely call for adaptive design requirements in the latter half of this century but in the near‐to‐mid term, the international roughness index (IRI) and total rutting degradation profile was very close to the historical climate run. While the inclusion of mechanistic performance models with climate change data as input introduces new uncertainties to infrastructure‐based LCA, sensitivity analyses runs were performed to better understand a comprehensive range of result outcomes. Through further infrastructure cases the framework could be streamlined to better suit specific infrastructures where only the infrastructure components with the greatest sensitivity to climate change are explicitly modeled using mechanistic‐empirical modeling routines. [ABSTRACT FROM AUTHOR]

The mechanistic–empirical (ME) design guide developed under the National Cooperative Highway Research Program represents a true change in the approach to engineering road structures. Changes in material properties with seasonal variations in moisture and temperature condition, which influence the mechanical response of the materials and hence the structural response of road layers, forced reliance on empirical measures to predict performance. These empirical functions will require calibration to ensure the prediction model is responsive to local conditions including adopted construction practice. The performance of pavements in cold regions clearly reveal the need to properly measure the distribution of stresses, strains, moisture, and thermal regimes, within road layers over a period of time. This paper presents the design, implementation, and use of a practical road instrumentation monitoring system capable of capturing all structural and environmental data for roadways. This proposed road installation scheme is simple yet effective in generating data that could be used to calibrate a host of design M-E and visco-elastic models including the new AASHTO design guide. Details include selection of sensors, data acquisition systems, data processing techniques, and some actual data. [ABSTRACT FROM AUTHOR]