Evaluation of wintertime precipitation estimates and forecasts in the mountains of Colorado

Abstract

Wintertime precipitation poses many observational and forecasting challenges, especially in the complex topography of the western US where radar beam blockage and difficulty siting in situ observations yields more sparse observations than in the eastern US. Uncertainty in western US winter precipitation is known to be high, so much so that some studies have found model simulated precipitation to produce similar or better large-scale estimates of annual precipitation than gridded observational products during climatologically anomalous years. This study evaluates high-resolution gridded precipitation estimates from Multi-Radar Multi-Sensor (MRMS) and Stage IV as well as forecasts from NOAA’s High-Resolution Rapid Refresh (HRRR) model in the Colorado Rocky Mountains. Gridded precipitation estimates and forecasts are compared to in situ SNOTEL measurements for two seasons of wintertime precipitation. The influence of forecast length, lead time, and model elevation on seasonal precipitation predictions from the HRRR are investigated. Additional comparisons are made to the relatively dense network of observations deployed in Colorado’s East River Watershed during the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign. Gridded products and forecasts are found to underestimate cold season precipitation by 25–65% compared to in situ and aircraft measurements, with longer forecast periods and lead times (6–24 h) having smaller biases (25–30%) than shorter forecast periods and lead times (55–65%). The assessment of multiple years of observations indicates that these biases are related more to the data and methods used to create the gridded products and forecasts than to precipitation characteristics.