Characteristics and Predictability of Extreme Precipitation Related to Atmospheric Rivers, Mesoscale Convective Systems, and Tropical Cyclones in the U.S. Southeast

Abstract

The Southeastern United States (SEUS) region has lower extreme quantitative precipitation forecast (QPF) skill compared to the northeastern or western United States. Previous studies have reported that the extreme precipitation events (EPEs) with high integrated vapor transport (IVT) have higher QPF skill than those with low IVT in the SEUS. We hypothesize that this extreme QPF skill is influenced by different storm types, such as atmospheric rivers (ARs), mesoscale convective systems (MCSs), and tropical cyclones (TCs), occurring within various synoptic patterns. This study investigates pattern-wise QPF skill and the contribution of storm types to EPEs in the SEUS. Six synoptic patterns associated with EPEs were identified from 2001 to 2019. These patterns exhibited a distinct seasonality: three occurred in the cool season, two in the warm season, and one in the transition season. Approximately 35% of the EPEs in the cool season, 24% in the transition season, and 29% in the warm season are associated with coincident ARs and MCSs. Pattern-wise QPF skill derived from the GEFS reforecast dataset illustrated that the cool season pattern, characterized by high IVT and frequency of ARs, has higher QPF skill. In contrast, the warm season pattern with high convective available potential energy and integrated water vapor has lower QPF skill across multiple lead times. In addition, patterns with higher frequency of ARs or coincident ARs and MCSs have better predictability than those with isolated MCSs. These results provide insight into the contribution of storm types to EPEs and their predictability in the SEUS.