Open AccessA European precipitation index for extreme rain‐storm and flash flood early warning
Author(s) -
Alfieri L.,
Thielen J.
Publication year - 2015
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1328
Subject(s) - flash flood , environmental science , precipitation , flooding (psychology) , climatology , meteorology , storm , warning system , quantitative precipitation forecast , extreme weather , flood myth , snow , index (typography) , climate change , geography , computer science , geology , psychology , telecommunications , oceanography , archaeology , world wide web , psychotherapist
Extreme rain storms are known for triggering devastating flash floods in various regions of Europe and particularly along the Mediterranean coasts. Despite recent notable advances in weather forecasting, most operational early warning systems for extreme rainstorms and flash floods are still based on rainfall measurements from rain gauges and weather radars, rather than on forecasts. As a result, warning lead times are bounded to a few hours and warnings are usually issued when the event is already taking place. This work proposes a novel early warning system for heavy precipitation events in Europe, aimed at identifying forecasts of extreme rainfall accumulations over short durations and within small‐size catchments prone to flash flooding. The system is based on the recently developed European Precipitation Index based on simulated Climatology (EPIC), which is calculated using COSMO‐LEPS ensemble weather forecasts and subsequently fitted with gamma distributions at each time step of the forecast horizon. Probabilistic exceedence of warning thresholds is calculated and alert points are generated where potentially extreme events are detected. Comparison of daily runs over 22 months with observed rainstorm events and flash floods in Europe denotes a probability of detection up to 90%, corresponding to 45 events correctly predicted, with average lead time of 32 h. Copyright © 2012 Royal Meteorological Society