EGU2020-17754
https://doi.org/10.5194/egusphere-egu2020-17754
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Exploring the links between hydrological forecast skill and multiple flood hazard drivers in southern Africa

Andrea Ficchi1, Hannah Cloke1,2,3, Ervin Zsoter4, Christel Prudhomme4, and Liz Stephens1
Andrea Ficchi et al.
  • 1Department of Geography and Environmental Science, University of Reading, Reading, UK
  • 2Department of Meteorology, University of Reading, Reading, UK
  • 3Department of Earth Sciences, Uppsala University, Uppsala, Sweden
  • 4European Centre for Medium-Range Weather Forecasts, ECMWF, Reading, UK

Severe flooding in southern Africa is caused by a variety of meteorological hazards including intense tropical cyclones and depressions, mesoscale convective complexes and persistent lows which bring extreme rainfall and flood events with different characteristics. Little is known about the relative predictability of flooding associated to these different drivers, especially in operational forecasting systems. Understanding the limits of predictability for the different drivers of flooding is important to provide evidence of forecast capabilities to end-users and decision-makers and build trust in the use of the forecasting systems.

Here we explore the skill of probabilistic flood forecasts from the operational Copernicus Emergency Management Service Global Flood Awareness System (GloFAS v2) over southern Africa. GloFAS provides real-time hydrological forecasts up to 30 days ahead by coupling ensemble weather forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) with hydrological modelling. The GloFAS flood forecasts are openly available and can support humanitarians and other international organisations to trigger action before a devastating flood occurs.

Using hydrological records of past flood events over the last 20 years, the GloFAS forecast skill is assessed by analysing the probability of detection of the events over different lead-times from 1 to 30 days, as well as the consistency and accuracy of predictions of event-based characteristics such as the flood timing and duration. We stratify the analysis by the multi hazard drivers of flooding with a focus on the distinction between tropical cyclones and other types of meteorological events. We suggest that such a stratified analysis of forecast skill can help modellers better understand the sources of predictability in flood forecasts and can support humanitarians to define specific trigger levels for forecast-based action for different types of flood events.

How to cite: Ficchi, A., Cloke, H., Zsoter, E., Prudhomme, C., and Stephens, L.: Exploring the links between hydrological forecast skill and multiple flood hazard drivers in southern Africa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17754, https://doi.org/10.5194/egusphere-egu2020-17754, 2020

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