A framework for generating catalogues of high-impact UNSEEN flood events
Year: 2026
Type: article
Abstract: In recent years, Europe has experienced several episodes of catastrophic flooding that were unprecedented in the historical record. Estimating the impact of rare flood events is crucial for improving risk preparedness and emergency management, but this effort is hampered by the limited availability of historical data. We describe a modular framework for generating a catalogue of physically plausible high-impact flood events using ensemble prediction systems. The framework builds on existing methodologies for the analysis, validation, and pooling of seasonal reforecasts from the European Flood Awareness System (EFAS) with the UNSEEN (UNprecedented Simulated Extremes using ENsembles) approach. We employ the probabilistic impact model CLImate ADAptation (CLIMADA, Aznar-Siguan and Bresch (2019)) to identify a subset of events with severe impact potential. Synoptic patterns are reconstructed using the ECMWF SEASonal forecasts version 5 (SEAS5) reforecasts to form a catalogue of plausible extremes. We illustrate the case study of the Panaro watershed in Emilia-Romagna, Italy, a region affected by multiple record-breaking floods in recent years. The analysis illustrates the added value of combining ensemble pooling with impact modelling, to anticipate high-impact extreme events before they occur. Our framework can be leveraged to explore risk storylines for stress-testing, and to support adaptation decision making for disaster management.
Source: Climate Services
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,290
Funder: Università di Bologna
OpenAlex ID: W7125475569