The High Resolution Rapid Refresh (hrrr): Recent and Future Enhancements, Time-lagged Ensembling, and 2010 Forecast Evaluation Activities

Abstract

The first hourly-updated, 3-km storm-resolving model, the HRRR (High-Resolution Rapid Refresh), is being run at NOAA/ESRL/GSD and is nested within the Rapid Update Cycle (RUC) and future replacement, the Rapid Refresh (RR). The breakthrough with the HRRR is the development of an effective technique for assimilating 3-d radar reflectivity data in the 13-km RUC and 13-km Rapid Refresh. Both the RR and the HRRR use a version of the Weather Research and Forecasting (WRF) model. The HRRR relies on the RUC/RR data assimilation, which includes radar reflectivity assimilation based on a digital filter initialization (DFI) technique. Use of the forward (diabatic) DFI inside the RUC/RR is shown to dramatically improve reflectivity forecasts from the HRRR. The HRRR has considerable promise for short-range thunderstorm prediction with current applications in severe weather forecasting, tactical and strategic flight planning for the aviation sector, renewable-energy forecasts and planning, and case studies for warn-on-forecast research efforts. The HRRR has shown particular skill at accurately depicting storm mode (structure) and location. Also, the hourly output and hourly update frequency of the HRRR provide a large number of predictors for the creation of a HRRR-based convective probability guidance product known as the HRRR convective probabilistic forecast (HCPF). A description of the HRRR configuration will be provided along with a few case studies that include 15-hour forecasts generated hourly during the spring, summer and fall of 2010 over a CONUS domain that demonstrate the predictive skill of HRRR individual (deterministic) and time-lagged ensemble (probabilistic) forecasts. Future enhancements including radar assimilation at 3-km within the HRRR will be discussed as they relate to current challenges with HRRR forecasts on the convective-scale. See