Learn about sources of error in NWP, how they are quantified, and how ensembles are evaluated.
Learn how EFI, SOT and Model Climate are built and provide forecast guidance for extreme, or severe weather events.
Six modules introducing the main topics in machine learning in the context of weather and climate.
Five modules covering decision trees, deep learning, uncertainty and generative models, and physics-guided approaches.
Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.
Learn about sources of predictability, seasonal forecast skill and the ECMWF sub-seasonal forecasting system.
Learn about seasonal predictability, how numerical seasonal forecast models work and their outputs.
