Is it possible to identify flash flood risk areas with global model rainfall forecasts? A comparative study for the ECMWF ensemble - raw model versus a point-scale post-processed version.

Flash floods are one of the most devastating natural hazards. They can occur in very 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. Performance evaluation is based on location and timing accuracy for the 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 how ecPoint yields superior results for both scenarios, pinpointing well areas at flash flood risk up to medium-range timescales. This enables 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.