Recent Performances of the High-Resolution Rapid Refresh (HRRR) model in Southern California

Major improvements in the warning/forecast process through the use of numerical weather modeling are ongoing and will continue well into the future. One such vehicle, a beneficiary of recent technology that will help facilitate these improvements, is the High-Resolution Rapid Refresh (HRRR) model. NOAA's real-time 3-km resolution, hourly updated, cloud-resolving atmospheric model, (initialized by 3-km grids with 3-km radar assimilation over a 1-h period) has been incorporated into the National Weather Service San Diego warning/forecast process and shows promise for significant improvements. It is likely that the HRRR is the only hourly convective resolving model running operationally and distributed to field forecasters. The output from this model has shown to be very useful, especially since it can provide rapidly updated guidance to the forecasters, and should be able to resolve smaller scale phenomena than is currently seen in other national operational models. The model has had some recent remarkable performances in Southern California, even on events with a relatively large deviation from climatology. Case studies, including the 12 December 2014 cold frontal event in Southern California will be examined in this paper as examples that will be used to help prove the point that such high resolution mesoscale models can make very valuable contributions to the forecast process and can catch unusual events as well.