The presence of a mesoscale convective vortex (MCV) and prolonged storm presence within a warm-frontal zone likely contributed to the storms’ anomalous efficiency in producing tornadoes. This study will examine machine learning and NWS outlooks leading up to the event to improve forecasters’ ability to communicate conditional probabilities. A better understanding of how to convey different types of probabilistic forecasts will equip NWS core partners with more information, enabling them to make informed decisions when weather impacts people’s lives and livelihoods. Additionally, this study focuses on the meteorological factors undergirding this rare event, highlighting the vital importance of accurate and consistent mesoanalysis in warning operations.
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