Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a sub-daily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.