A Features-Based Assessment of the Evolution of Warm Season Precipitation Forecasts from the HRRR Model over Three Years of Development

Abstract

Abstract The High Resolution Rapid Refresh (HRRR) model has been the National Weather Service’s (NWS) operational rapid update model since 2014. The HRRR has undergone continual development, including updates to the Weather Research and Forecasting (WRF) Model core, the data assimilation system, and the various physics packages in order to better represent atmospheric processes, with updated operational versions of the model being implemented approximately every spring. Given the model’s intent for use in convective precipitation forecasting, it is of interest to examine how forecasts of warm season precipitation have changed as a result of the continued model upgrades. A features-based assessment is performed on the first 6 h of HRRR quantitative precipitation forecasts (QPFs) from the 2013, 2014, and 2015 versions of the model over the U.S. central plains in an effort to understand how specific aspects of QPF performance have evolved as a result of continued model development. Significant bias changes were found with respect to precipitation intensity. Model upgrades that increased boundary layer stability and reduced the strength of the latent heating perturbations in the data assimilation were found to reduce southward biases in convective initiation, reduce the tendency for the model to overestimate heavy rainfall, and improve the representation of convective initiation.