Can rainfall forecasts from global NWP model ensembles be used to detect areas at flash flood risk? Developing a rainfall-based flash flood forecasting system over a continuous global domain and up to medium range lead time.

Flash floods are one of the most devastating natural hazards. They can occur in large or small rural or urban areas, with little to no warning. Extreme (localized) rainfall plays a crucial role. This presentation compares the rainfall forecast performance, for the raw ECMWF ensemble (ENS) and post-processed point-scale output derived from that (ecPoint), in pinpointing areas at risk of flash floods. Long-term objective verification and case studies are used to compare. Although ENS effectively identifies areas at flash flood risk in instances of large-scale rainfall, its performance falters when confronted with localized extreme convective systems. We show that ecPoint yields superior results up to medium-range timescales for both scenarios, pinpointing well the areas at flash flood risk and the value of the triggering rainfall events. This outcome will enable decision-makers to extend their preparedness and action time window. This presentation will also demonstrate forecast system strengths and weaknesses, and how forecasters can leverage these to produce better predictions of areas at flash flood risk up to medium-range lead times over a continuous global domain.