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Publication Number:  FHWA-HRT-15-019    Date:  May 2015
Publication Number: FHWA-HRT-15-019
Date: May 2015


Evaluation of Long-Term Pavement Performance (LTPP) Climatic Data for Use in Mechanistic-Empirical Pavement Design Guide (MEPDG) Calibration and Other Pavement Analysis



The importance of climate to the performance of pavements and many other transportation infrastructure assets is beyond debate. The Long-Term Pavement Performance (LTPP) Program has performed pioneering work to characterize and summarize site-specific climatic data for its General Pavement Studies (GPS) and Specific Pavement Studies (SPS) test sections. However, improvements in climatic data collection are needed to support current and future research on climate effects pertaining to pavement materials, design, and performance. The calibration and enhancement of the Mechanistic-Empirical Pavement Design Guide (MEPDG) is just one example of these emerging needs.(3)

To address these needs, the study had the following original objectives:

  • Examine current and emerging needs in climate data collection and engineering indices for use in MEPDG calibration, changes in Superpave binder performance grading, and development of future mechanistic-based infrastructure management applications, including pavement, bridge, and other types of asset management models.
  • Develop a methodology for characterizing location-specific historical climate indices that includes temporal changes in the position and measurement characteristics of the operating weather stations (OWS) used for the computation. This new methodology will include an estimate of the variability or uncertainty caused by the spatial averaging process used to develop the baseline indices.
  • Provide recommendations to update the climate statistics in the LTPP database.
  • Examine the need to add a climate-soils parameter such as the Thornthwaite Moisture Index (TMI) to the LTPP database. Examine the applicability of TMI to other transportation infrastructure applications.
  • Examine the need for continued location-specific solar radiation measurements to capture the effect of climate change on pavement and other infrastructure performance. Determine whether existing data sources can be used to fulfill this need.


Some clarification of terminology is appropriate here. The National Oceanic and Atmospheric Administration (NOAA) provides the following definitions:

Weather refers to [atmospheric] conditions at a given point in time (e.g., today’s high temperature), whereas Climate refers to the “average” weather conditions for an area over a long period of time (e.g., the average high temperature for today’s date).”(4)

The Intergovernmental Panel on Climate Change provides the following even more specific definition:

“Climate in a narrow sense is usually defined as the “average weather,” or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period ranging from months to thousands or millions of years. The classical period is 30years, as defined by the World Meteorological Organization (WMO). These quantities are most often surface variables such as temperature, precipitation, and wind. Climate in a wider sense is the state, including a statistical description, of the climate system.”(5)

The atmospheric data stored in the LTPP database are a combination of “weather,” which is currently the daily extremes, and “climate” statistics summarized at the monthly and annual level. To minimize potential confusion, this report uses the general term “climate” to represent the larger subject area, but may also use weather data to describe specific short-term observations or measurements.


During the execution of Phase 2 of the project, the study team discovered a newly emerging source of weather data that resulted in a change of direction in the project work plan. This discovery is credited to the University of Maryland (UMD) members of the research project team. A UMD Civil Engineering faculty member advised the study team of the existence of a new source of weather and climate data based on his recent work at the Goddard Space Flight Center in Greenbelt, MD. The name of the data source is Modern-Era Retrospective Analysis for Research and Applications (MERRA). The primary attribute of this data source that motivated the project direction change is the availability of continuous hourly weather data starting in 1979 on a relatively fine-grained uniform grid. MERRA also contains more fundamental scientific data elements than are available from any of the other data sources identified in phase1 of this project. If MERRA data proved to be a viable alternative, then all of the project objectives could be satisfied. Chapter 4 of this report provides more details and information on MERRA data.

The significant change in the phase 2 work plan was to evaluate MERRA data against available ground-based observations, both in statistical terms and using the MEPDG. The MEPDG, developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A and recently officially adopted by the American Association of State Highway and Transportation Officials (AASHTO), was selected because it contains the most advanced models on pavement-climate interaction that have ever been officially adopted by AASHTO.(6,3) The MEPDG is also a major focus of the objectives of the present study. Chapter 5 documents the findings of the comparisons between MERRA and best available ground-based weather data sources with significant time coverage.

More Extensive Analysis of MERRA Data

Initial evaluations of the MERRA data suggested that it is as good as, and in many ways superior to, weather data time series from conventional surface-based OWSs. The recommendations from these initial evaluations were that LTPP adopt MERRA as the data source for its next update to the Climate (CLM) module and develop a tool to extract and use this data for engineering applications.

After review of the initial evaluations by the Transportation Research Board’s Expert Task Group (ETG) on LTPP Special Activities, Federal Highway Administration (FHWA) experts, and LTPP staff, two primary comments necessitate additional analysis with the following primary objectives:

  1. More extensive analysis of MERRA data.
  2. Development of a tool to disseminate MERRA data.

The more extensive analysis of MERRA included the following specific study activities:

  • If possible, establish an appropriate ground truth for climate data.
  • Perform statistical comparisons of ground truth, OWS, and MERRA.
  • Evaluate the correctness of MEPDG surface shortwave radiation (SSR) calculations.
  • Compare MEPDG pavement performance predictions using ground truth, OWS, and MERRA climate data.


To provide a complete overview of the status of climate data in the LTPP program, chapter 2 contains a summary of the legacy LTPP approach to climate data in current use. While some of this information is available in other LTPP documents, some new information is presented here that provides a context to evaluate MERRA data against the legacy approach, not only as used by LTPP, but also for other infrastructure applications.

Chapter 3 provides a summary of infrastructure climate data needs and candidate data sources reviewed by the study team. While most of this information was contained in the phase 1 report, it is being repeated in this document for reviewer convenience.

Chapter 4 contains a description of the MERRA product. This includes a conceptual description of the modeling approach, the data used and produced by MERRA, and comments on quality control (QC) procedures.

Chapter 5 presents the findings of the evaluation of MERRA data against existing ground-based observations both statistically and using the MEPDG models. The analyses include a systematic quantitative evaluation of the sensitivity of MEPDG predicted pavement distresses to climate inputs, a statistical comparison of MERRA versus ground-based weather history inputs, and a critical comparison of MEPDG predicted pavement distresses using MERRA versus ground-based weather history data.

Chapter 6 presents the findings of the more extensive analysis of MERRA data, including additional statistical analysis comparing OWS and MERRA data, evaluation of the correctness of MEPDG SSR calculations, and comparison of MEPDG pavement performance predictions using OWS and MERRA climate data for more sections.

Chapter 7 presents the recommendations and findings of this research effort. These include the benefits of MERRA data, recommendations on inclusion of legacy climate indices, and initial concepts for implementation of MERRA data into the LTPP database.



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