A Climatology of Qualitative Precipitation Forecast Errors for Mesoscale Convective Systems in the High Resolution Ensemble Forecast

The majority of warm season rainfall in the central United States comes from mesoscale convective systems (MCSs). Accurate MCS forecasting is important because small errors in aspects such as location and intensity can have large impacts on predictions of local hydrology and flooding. To better understand MCS forecasting errors, 40 MCSs from June 2019 to September 2021 were examined. MCS rainfall during 30-hour periods (from 12 UTC day 1 through 18 UTC day 2) from each of the eight HREF ensemble members that ran during this period were compared to Multi-Radar Multi-Sensor (MRMS) precipitation fields for the same 30 hours. The HREF ensemble makes use of time lagging, so that four members (HRRR, NAM 3km nested, HRW ARW, and HRW NSSL) were initialized at 12 UTC, three (NAM 3km nested, HRW ARW, and HRW NSSL) at 00 UTC, and one (HRRR) at 06 UTC. MODE was used to identify 18 rainfall object parameters mostly pertaining to rainfall location and intensity for the observations and each HREF member. The 18 parameters will be used to create a climatology for systemic biases of each HREF member. This information will be used in complementary work to explore methods for QPF adjustment.