Validation of Mountain Precipitation Forecasts from the Convection-Permitting NCAR Ensemble and Operational Forecast Systems over the Western United States

Convection-permitting ensembles can capture the large spatial variability and quantify the inherent uncertainty of precipitation in areas of complex terrain; however, such systems remain largely untested over the western U.S. In this study, we assess the capabilities of deterministic and probabilistic cool-season quantitative precipitation forecasts (QPFs) produced by the 10-member, convection-permitting (3-km horizontal grid spacing) NCAR Ensemble using observations collected by SNOTEL stations at mountain locations across the western U.S. and precipitation analyses from PRISM. We also examine the performance of operational forecast systems run by NCEP including the HRRR, NAM 3-km CONUS nest, GFS, and SREF. Overall, we find that higher resolution models, such as the HRRR, NAM-3km CONUS nest, and an individual member of the NCAR Ensemble, are more deterministically skillful than coarser models, especially over the narrow interior ranges of the western U.S., likely because they better resolve topography and thus better simulate orographic precipitation. The 10-member NCAR Ensemble also is more probabilistically skillful than 13-member sub-ensembles comprised of each SREF dynamical core, but less probabilistically skillful than the full 26-member SREF, due to insufficient spread. These results should help guide future short-range model development and inform forecasters about the capabilities and limitations of several widely used deterministic and probabilistic modeling systems over the western U.S.