The High Resolution Rapid Refresh (HRRR): Recent and future enhancements, time-lagged ensembling, and 2010 forecast evaluation activities
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.