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The Mechanistic-Empirical Pavement Design Guide (MEPDG; AASHTO 2015) and its implementation in the AASHTOWare Pavement ME Design software (PMED) represents a major improvement over its predecessors, particularly in its comprehensive coverage of climate impacts on pavement performance. This paper compares the predicted distresses of asphalt concrete (AC) and jointed plain concrete pavement (JPCP) using four different climate data sources: ground based weather station (GBWS) data supplied with early versions of the (PMED), the North American Regional Reanalysis (NARR) data supplied with the July 2016 version of the PMED (version 2.3.1), and the Modern Era Retrospective Analysis for Research and Application (MERRA) Versions 1.0 and 2.0 (MERRA-1 and MERRA-2) data from the National Aeronautical and Space Administration (NASA). Pavement performance predictions generated using these data showed disagreement among some of the climate data sources, especially for MERRA-2.Comprehensive diurnal and other time series analyses of the raw climate data found significant 9 disagreements in the percent sunshine estimates. Percent sunshine is used in the PMED environmental effects model to semi-empirically estimate the downwelling shortwave radiation reaching the pavement surface. The MERRA-1 and MERRA-2 data independently provide direct predictions of downwelling surface shortwave radiation (SSR); these values were found to agree with ground-based observations 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 PMED. 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 that SSR rather than percent sunshine be used as a direct input to the PMED.