Outline
ECMWF will host a live panel on 8 July 2026, under the Destination Earth (#DestinE) initiative of DG-CNECT at the European Commission. The session will explore how machine learning (ML) can support weather and climate prediction beyond the medium range, as part of the online training course Machine Learning for Earth Systems Modelling: Architectures, Data, and Prediction.
This second course in ECMWF’s three-course ML learning pathway focuses on the technical foundations of machine learning for weather prediction. It explores how modern AI-based prediction systems are designed, trained, and evaluated using real-world Earth system data and workflows.
The panel will bring together experts working on AI-based forecasting, climate prediction and Earth-system modelling to examine the opportunities and challenges of extending forecast skill beyond the medium range. Topics will include sub-seasonal and seasonal prediction, long-horizon stability, memory and representation challenges, and how emerging AI architectures may help address some of these forecasting challenges.
The panel will be recorded and made available as part of Module 8 of the online training course.
Speakers
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Jonathan Weyn (Microsoft Start Weather)
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Bo Lu (China Meteorological Administration)
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Masilin Gudoshava (IGAD Climate Prediction & Applications Centre)
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Lorenzo Zampieri (ECMWF)
Who should attend?
This event is aimed at researchers, practitioners, technical specialists, operational forecasters, climate service professionals, and industry experts interested in the use of ML for sub-seasonal, seasonal and long-range prediction.
The event is open to the public and to learners of the course Machine Learning for Earth Systems Modelling: Architectures, Data, and Prediction. If you are following the course, you will still need to register here to attend the live panel.
Registration
Participation is free of charge. To register for the event, click the "Registration" link on the left side of this page.
More information
To find out more about our ML training under Destination Earth, take a look at our ML training page.
If you are interested, join the free online course Machine Learning for Earth Systems Modelling: Architectures, Data, and Prediction.
The panel will be recorded and made available shortly after the event on our YouTube channel, and accessible through our eLearning platform as part of the course.