Investigating Extreme Precipitation and Associated Cloud-Top Temperatures in Flash Flood Events over West Africa

Abstract

Flash floods, driven by short-duration, high-intensity rainfall, are among the most destructive hydrometeorological hazards in West Africa, causing significant loss of life and damage to homes, infrastructure, and agricultural land. Reliable forecasting remains challenging due to the scarcity of ground-based observations and the limited skill of numerical weather prediction models in accurately simulating convective systems in this region. This study aims to assess the extent to which floods and flash floods are caused by extreme precipitation events and to examine the temporal and spatial variations in cloud-top temperatures (CTTs) before and during such events. Daily precipitation associated with flood and flash flood events is analyzed using the Integrated Multi-satellitE Retrievals for GPM (IMERG) Early Run product. Extreme precipitation is classified into three categories: (i) daily rainfall exceeding the 99th percentile of wet days based on a 25-year IMERG record (extremely wet days), (ii) daily rainfall between the 95th and 99th percentiles (very wet days), and (iii) consecutive wet days within five to ten days prior to the event, where at least one day exceeded the 95th or 99th percentile threshold. The cloud-top temperatures are derived from the 10.8 µm channel of the High Rate SEVIRI Level 1.5 Image Data - MSG - 0 degree provided by EUMETSAT. Preliminary results indicate that all flash flood events are associated with extreme precipitation, which is accompanied by colder CTTs. The majority of flood events also meet the defined extreme categories. The findings underscore the potential of combining near-real-time precipitation estimates with geostationary infrared observations to enhance flash flood forecasting capabilities in West Africa.

Georgios C. Anagnostopoulos

Associate Professor of Electrical & Computer Engineering

I lead the Machine Learning Research Group at FIT.