Demonstrating the use of UNSEEN climate data for hydrological applications: case studies for extreme floods and droughts in England

Abstract. Meteorological and hydrological hazards present challenges to people and ecosystems worldwide, but the limited length of observational data means that the possible extreme range is not fully understood. Here, a large ensemble of climate model data is combined with a simple grid-based hydrological model, to assess unprecedented but plausible hydrological extremes in the current climate across England. Two case studies are selected—dry (Summer 2022) and wet (Autumn 2023)—with the hydrological model initialised from known conditions then run forward for several months using the large climate ensemble. The modelling chain provides a large set of plausible events including extremes outside the range from use of observed data, with the lowest flows around 28 % lower on average for the Summer 2022 drought study and the highest flows around 42 % higher on average for the Autumn 2023 flood study. The temporal evolution and spatial dependence of extremes is investigated, including the potential time-scale of recovery of flows to normal and the chance of persistent extremes. Being able to plan for such events could help improve the resilience of water supply systems to drought, and improve flood risk management and incident response.