Comparison of Lightning Forecasts from the High-Resolution Rapid Refresh Model to Geostationary Lightning Mapper Observations

Abstract

Abstract The ability of the High-Resolution Rapid Refresh (HRRR) model to forecast the location of convective storms is of interest for a variety of applications. Since lightning is often present with intense convection, lightning observations from the Geostationary Lightning Mapper (GLM) on GOES-East are used to evaluate the performance of the HRRR lightning forecasts from May through September during 2018 and 2019. Model skill is presented in terms of the fractions skill score (FSS) evaluated within circular neighborhoods with radial distances from 30 to 240 km. Case studies of individual events illustrate that the HRRR lightning forecasts FSS varies from storm to storm. Mean FSS is summarized for the months with peak lightning activity (June–August) for the west, central, and east United States. Our results suggest that forecasters should use HRRR lightning forecasts to indicate general tendencies for the occurrence, region, and timing of thunderstorms in a broad region rather than expect high forecast accuracy for lightning locally. For example, when FSS is evaluated within small neighborhoods (30-km radius), mean FSS drops sharply after the first two hours of model integration in all regions and during all hours of the day. However, when evaluated within larger neighborhoods (60-km radius and larger), FSS in the western United States and northern Mexico remains high for all lead times in the late afternoon and early evening. This result is likely due to the model capturing the tendency for convection to break out over higher terrain during those hours.