SEED-FD
Financiado
Strenghtening Extreme Events Detection for Flood and Drought
“Today, one third of the world’s people, mainly in least developed countries and small island developing states, are still not covered by early warning systems... This is unacceptable, particularly with climate impacts sure to get...
“Today, one third of the world’s people, mainly in least developed countries and small island developing states, are still not covered by early warning systems... This is unacceptable, particularly with climate impacts sure to get even worse. Early warnings and action save lives. To that end, today I announce the United Nations will spearhead new action to ensure every person on Earth is protected by early warning systems within five years.”- UN Secretary-General António Guterres on World Meteorological Day 2022/03/23The ambition of the Strengthening Extreme Events Detection for Floods and Droughts (SEED-FD) project proposal is to give Europe, with the Copernicus Emergency Management Service, a leading position with this regard by breaking the current limitations of hydrological simulation accuracy and reliability and providing skillful floods and droughts forecasts available anywhere in the world, including in the global south for lower and middle-income countries, typically the most impacted by extreme hydrological events but also where the current knowledge gap in hydrological simulation and forecasting is highest.Combining state-of-the-art science with crucial advances in EO and non-EO technologies, the project's global objective is to enhance the quality and portfolio of the CEMS EWS for floods and droughts and improve the reliability of predictions all over the world. SEED-FD will target every critical part of the CEMS Hydrological Forecasting Modelling chain by applying state-of-the-art science to transform new observational information into high-quality hydrometeo extreme event forecast products. It will invest in better representing hydrological processes and parameterisation techniques of the CEMS core hydrological engine (LISFLOOD) and combine the model enhancements with innovative techniques to integrate EO and non-EO data with the near real-time hydrological processing chain for reducing hydrological forecasting errors.
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Duración del proyecto: 35 meses
Fecha Inicio: 2024-01-01
Fecha Fin: 2026-12-31
Fecha Fin: 2026-12-31
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-01-01
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Líder del proyecto
MAGELLIUM SAS
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5