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.
Fields of science
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EF
Coordinator
08034 Barcelona
Spain
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