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Long Term Pavement Performance (LTPP) climatic database revision and expansion

Filetype[PDF-461.74 KB]


  • English

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    • TRIS Online Accession Number:
      00805902
    • NTL Classification:
      NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION;NTL-HIGHWAY/ROAD TRANSPORTATION-Pavement Management and Performance;
    • Abstract:
      Although the effects of climatic factors on pavement performance have long been recognized as important, those effects remain largely unquantified because individual pavement research projects to date generally have been restricted to limited geographical areas with more or less uniform climatic conditions and relatively short time spans, making it difficult to separate the effects of climatic factors from those of loading. By virtues of the relatively broad geographic and climatic distribution of the test sections involved and the long-term nature of the study, the Long Term Pavement Performance (LTPP) program will rectify that situation. The LTPP climatic database is intended to provide the weather and climatic information needed to characterize the environment in which each LTPP test section has existed from the time of construction through the LTPP monitoring period. The LTPP database was originally established in 1992, and its development is documented in the following report: "Development of the LTPP Climatic Database," SHRP-P-621, Strategic Highway Research Program, National Research Council, Washington, D.C., 1992. Between 1997 and 1998, the LTPP climatic database was revised and updated to (1) include test sections that had not been constructed when the original database was established, (2) improve accuracy of data for the small number of test sections for which accurate location (longitude and latitude) information was not available in 1992, and (3) improve the usefulness of the database. This document summarizes the revisions to and update of the LTPP climatic database, including the identification and sources of data, selection and verification of weather stations, actual data retrieval from available sources, and data quality assurance.
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