Investigating the forecast predictability for fluvial flooding from tropical cyclones
- 1Met Office, Exeter, Exeter, Devon, United Kingdom (firstname.lastname@example.org)
- 2University of Reading, Reading, Berkshire, United Kingdom
- 3Uppsala University, Uppsala, Sweden
- 4Centre for Natural hazards and Disaster Science, Uppsala, Sweden
- 5ECMWF, Reading, Berkshire, United Kingdom
- 6University of Loughborough, Loughborough, United Kingdom
- 7Centre for Ecology and Hydrology, Wallingford, United Kingdom
Global ensemble forecast models have been shown to have good skill in forecasting the track probabilities of tropical cyclones worldwide, but less well-studied is their ability to predict the hazards resulting from tropical cyclones, which in the case of fluvial flooding can extend far from the landfall location traditionally focussed on in operational tropical cyclone warnings. This work aims to investigate the key factors that influence the predictability of fluvial flood severity from tropical cyclones, using forecasts from the Global Flood Awareness System (GloFAS). GloFAS is jointly developed by the European Commission and the European Centre for Medium-Range Weather Forecasts (ECMWF) and is designed to provide a global overview of upcoming flood events to decision makers as part of the Copernicus Emergency Management Service, producing probabilistic river discharge forecasts driven by global ECMWF ensemble forecasts coupled to a hydrological model. This presentation will explore the chain of uncertainty through the forecasting process for several recent tropical cyclone flood events including Hurricane Iota and Cyclone Nivar. It investigates the influence on the overall predictability and uncertainty of the fluvial flood forecasts of various components of the forecasting chain, including the track, intensity, and precipitation forecasts for the tropical cyclone, and the hydrological catchment conditions and modelling.
How to cite: Titley, H., Cloke, H., Harrigan, S., Pappenberger, F., Prudhomme, C., Robbins, J., Stephens, E., and Zsoter, E.: Investigating the forecast predictability for fluvial flooding from tropical cyclones, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8888, https://doi.org/10.5194/egusphere-egu21-8888, 2021.
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