Seamless seasonal to sub-seasonal forecasts of flood risk

This project will assess the potential for seamless prediction of flood risk at the river basin scale. We expect a focus on Africa and have identified the river Tana in Kenya as one possibility, although this is to be decided, depending on candidate’s interest. This project will utilise the global Flood Awareness system (GLOFAS, Alfieri et al., 2013) which links a global hydrological model (Lisflood) to state-of-the-art weather/climate forecasts from the ECMWF ensemble forecast system. The GLOFAS model system produces forecasts of river discharge at 10km resolution from which probabilities of exceeding various critical thresholds (selected flow return periods) are derived. Forecasts lead times for the standard system extend to out to 45 days (including 15 days driven directly from the weather forecast) and for out to a number of months in new ‘GLOFAS-seasonal’ (Emerton et al., 2017).
The project will have 2 main aims
1. Evaluation of the predictability of flood events at seamless lead times of days to months. (i) Sub-seasonal lead times. Evaluate the skill of flood forecasts at the lead times of up to 45 days from the GLOFAS system. (ii) seasonal lead times.
2. Explore the potential application of this scientific information in potential Forecast based Action (FbA) for flood preparedness initiatives. The research will be conducted in the context of, and will be cognizant of operation flood risk management and preparedness action in the study basin
The project team
The project will complement the ForPAc project (www.forPAc) and FATHUM (led by University of Reading) projects funded under the NERC-DfID SHEAR programme. This will bring close links to the Red Cross Climate Centre and forecast centres in the UK. A supervisory panel will include representatives from FATHUM and other agencies in addition to the formal supervisors at Sussex. We envisage placements of 1-3 months at relevant meteorological forecast agencies.

The student will undertake their fundamental science research in the context of operational flood forecasting by national and international agencies with a direct link to flood response agencies. As such the student will experience the full end-to-end system of science into operations.
Skills and experience:
This project would be suitable for students with a degree in physical sciences, meteorology, physical geography or environmental science. Students will be required to work in a unix programming environment with scientific programming using e.g. IDL, R, python or similar, previous experience is desirable but not essential as training will be provided

For informal discussion about this studentship please contact: [Email Address Removed]
To be considered for the studentship, please submit a CV, a cover letter highlighting your relevant background and experience, and two references, to [Email Address Removed]