To advance the state-of–the-art in operational hydro-meteorological forecasting, a newly funded project called IMPREX has recently been launched.
IMPREX stands for: IMproving PRedictions and management of hydrological EXtremes. The project, awarded €7.9 million over 4 years by the European Commission, aims to improve society’s ability to anticipate and respond to future hydrological extreme events in Europe.
IMPREX works across time-scales by focusing on both the quality of short-to-medium term predictions as well as the reliability of future climate projections. It does this by improving the representation of key processes in the current state-of-the-art forecasting systems. The application-oriented approach of the project hopes to improve the uptake of climate information in strategic economic sectors and contribute to risk management strategies across Europe. As a key outreach product, a periodic hydrological risk outlook for Europe will be produced.
IMPREX is built upon a strong team of experts from public and private sectors as well as universities and research institutes with complementary skills and experiences. The direct involvement of a broad range of users from key economic sectors will ensure the relevance of the project outputs. Water Footprint Network is leading one of the work packages which assesses impacts of hydrological extremes on the European economy and examines the risks related to the global supply and production of goods under hydrological extremes and climate change.
Water Footprint Network Project Manager, Dr, Ertug Ercin, joined the launch of the project at the premises of the coordinating organisation, the Royal Netherlands Meteorological Institute (KNMI), in De Bilt, Netherlands on 30th November 2015. The 3-day kick-off meeting allowed representatives from the 23 consortium members to build a strong team spirit and set the foundations for the work ahead.
You can stay informed on the latest project developments through twitter @imprex_eu and on www.imprex.eu.
IMPREX has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641811.