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ARTificial Intelligence for Seasonal forecast of Temperature extremes

Project description

Artificial intelligence for advanced seasonal forecasts

Seasonal forecasts are instruments for climate prediction that help risk prevention related to extreme weather. While recent progress in statistical methods and numerical modelling has improved seasonal forecasts’ performance, their usefulness often remains limited, especially in the mid-latitudes. The EU-funded ARTIST project will improve insights into climate predictability at the seasonal timescale, aiming to increase the performance of existing prediction systems. The project will design a statistical and dynamical hybrid model, synthesising a state-of-the-art dynamical seasonal prediction system and a statistical model relying on advanced machine learning techniques, focusing on the seasonal prediction of temperature extremes in Europe. This hybrid model will combine the theoretical foundation and interpretability of physical modelling with the spatio-temporal predictive relationships identified by artificial intelligence.

Coordinator

BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION
Net EU contribution
€ 172 932,48
Address
Calle Jordi Girona 31
08034 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
Other funding
€ 0,00