CHAPTER 1

Background and Research Approach

1.1 Background

Environmental conditions can have a significant effect on flexible and rigid pavement performance, both in actuality and in terms of what is modeled. Factors such as temperature, precipitation, cloud cover, and freezing index are important in identifying the impact of the environment on a pavement section. These factors not only affect how the pavement layer materials behave when subjected to environmental loadings, but they also affect pavement layer responses to traffic loadings. The responses of a particular pavement section are dependent on a number of material properties, particularly the susceptibility of the materials to moisture and freeze thaw, how well the pavements expel water, and how water infiltrates the pavement system. When this research project began, the AASHTOWare Pavement ME software (henceforth referred to as Pavement ME or PMED) used climate data obtained using the North American Regional Reanalysis (NARR) dataset, which is an assimilation of weather data across the entirety of North America (1). The NARR data, or any assimilated climate dataset, are a more complete representation of the climate for a particular location compared to individual weather stations, which were available in Pavement ME versions prior to 2016. The NARR data required minimal quality control checks within Pavement ME since the quality control occurred before it was incorporated into Pavement ME. In addition, no hourly climate values were missing within the NARR dataset; the opposite frequently occurred when the ground-based weather stations were used.

In addition to NARR, NASA’s Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) utilized data from the Earth Observing System (EOS) satellites to improve precipitation and water vapor climatology beginning in 1979 (2). FHWA and AASHTO have adopted use of the MERRA-2 data and translated the variables into civil engineering applications, specifically pavement analysis and design. FHWA’s Long Term Pavement Performance (LTPP) Climate Tool provides limited access to the MERRA-2 database by generating site-specific climate data, based on the nearest available grid point, in a format compatible with Pavement ME. The available climate inputs in the Climate Tool include temperature, precipitation, wind speed, percent sunshine, and relative humidity. AASHTOWare is currently using the MERRA-2 climatic data from the LTPP Climate Tool to recalibrate the flexible pavement performance prediction models in Pavement ME. The full MERRA-2 datasets available directly through NASA also include hourly solar radiation values based on measured cloud-cover fractions, which is not currently included in the Climate Tool. Including these values can vastly improve the accuracy and reliability of predicted pavement temperatures. Studies reveal challenges in matching the predictions from the Enhanced Integrated Climatic Model (EICM), the climatic model used in Pavement ME, with field observations and pavement performance. Variations in measurement of climatic attributes have also been reported to Operating Weather Stations (OWS).

Using an assimilated dataset, such as MERRA-2, which spans the globe, can have significant benefits compared to individual weather stations across the United States. MERRA-2 data provide opportunities for enhancements to the climatic parameters and module calculations for pavement design using Pavement ME. They also provide improved climatology; higher frequency outputs, including hourly data; and additional locations beyond the United States. Available data categories include temperature, precipitation, surface pressure, cloud cover, humidity, wind speed, and solar radiation.

1.2 Research Objectives

The objectives of this project are to (1) evaluate the impact of using NASA’s MERRA-2 through the FHWA LTPP Climate Tool to improve the climatic inputs and related models for Pavement ME, (2) enhance and simplify climate input parameters for Pavement ME that can be implemented by transportation agencies, and (3) develop climate-related models based on identified parameter enhancements.

1.3 Organization of the Report

This report is organized into four chapters:

• Chapter 1: Background and Research Approach
• Chapter 2: Findings
• Chapter 3: Interpretations and Applications
• Chapter 4: Conclusions and Suggested Research

1.4 Research Approach

The research approach to complete this research project included identifying potential limitations with respect to the climate data, models, and methods currently included in the EICM and PMED. These limitations can have a significant effect on the predicted pavement temperature and, subsequently, pavement performance. The limitations found throughout this research project were divided into multiple categories: (1) climate data source limitations, (2) EICM model limitations, and (3) limited documentation of the models and overall access to the hourly climate data. To address the identified limitations, several enhancements were developed. The identified limitations are documented in Chapter 2 while the enhancements to address the limitations are reported in Chapter 3.