Improvement of Climate Data for Use in MEPDG Calibration and Other Pavement Analysis
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2019-01-01
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Edition:Final; September 2016-January 2019
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Abstract:This study compares the predicted distresses of asphalt concrete (AC) and jointed plain concrete pavement (JPCP) using four different climate data sources: (1) ground-based weather station (GBWS) data, (2) the North American Regional Reanalysis (NARR) data, and (3 and 4) the Modern-Era Retrospective Analysis for Research and Applications (MERRA) versions 1 and 2 (MERRA-1 and MERRA-2) data. The results indicate that pavement performance predictions generated using these data showed disagreement among some of the climate data sources, especially for MERRA-2. Comprehensive diurnal and time-series analyses of the raw climate data found significant disagreements in the percent sunshine data. Percent sunshine is used in the Pavement ME Design environmental effects model to semi-empirically estimate the shortwave radiation reaching the pavement surface, the major driver for pavement heating and cooling. The MERRA-1 and MERRA-2 data independently provide direct predictions of surface shortwave radiation (SSR); these values were found to agree with “ground truth” measurements of SSR from the U.S. Climate Reference Network (USCRN). The direct model predictions of SSR were used to back calculate “synthetic” percent sunshine for input into the Pavement ME Design software. Use of the synthetic percent sunshine derived from predicted SSR eliminated nearly all discrepancies in predicted pavement performance using MERRA-1 vs. MERRA-2 data. Based on these results, the authors recommend SSR rather than percent sunshine to be used as input into the Pavement ME Design software.
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