Convection-permitting Simulations of Historical and Possible Future Climate over the Contiguous United States

This study presents a novel, high-resolution, dynamically downscaled dataset that will help inform regional and local stakeholders regarding potential impacts of climate change at the scales necessary to examine extreme mesoscale conditions. WRF-ARW version 4.1.2 was used in a convection-permitting configuration (horizontal grid spacing of 3.75 km; 51 vertical levels; data output interval of 15-min) as a regional climate model for a domain covering the contiguous US Initial and lateral boundary forcing for the regional climate model originates from a global climate model simulation by NCAR (Community Earth System Model) that participated in phase 5 of the Coupled Model Inter comparison Project. Herein, we use a version of these data that are regridded and bias corrected. Two 15-year downscaled simulation epochs were examined comprising of historical (HIST; 1990–2005) and potential future (FUTR; 2085–2100) climate using Representative Concentration Pathway (RCP) 8.5. HIST verification against independent observational data revealed that annual/seasonal/monthly temperature and precipitation (and their extremes) are replicated admirably in the downscaled HIST epoch, with the largest biases in temperature noted with daily maximum temperatures (too cold) and the largest biases in precipitation (too dry) across the southeast US during the boreal warm season. The simulations herein are improved compared to previous work, which is significant considering the differences in previous modeling approaches. Future projections of temperature under the RCP 8.5 scenario are consistent with previous works using various methods. Future precipitation projections suggest statistically significant decreases of precipitation across large segments of the southern Great Plains and Intermountain West, whereas significant increases were noted in the Tennessee/Ohio Valleys and across portions of the Pacific Northwest. Overall, these simulations serve as an additional datapoint/method to detect potential future changes in extreme meso-γ weather phenomena.