The EGU 2026 General Assembly will host Session AS1.4 – “Subseasonal prediction, processes and warning capabilities (EDI)”.
This session welcomes contributions on all aspects of subseasonal-to-seasonal (S2S) prediction, from physical drivers and prediction systems to extreme events and societal applications. In particular, contributions related to the AI Weather Quest are of special interest, recognising the competition’s key role in benchmarking AI-based subseasonal forecasts in real time.
If you have been developing or testing an AI model within the Quest, this is an excellent opportunity to:
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Share lessons learned from model development and evaluation,
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Showcase your results and insights to the wider S2S and AI communities,
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Discuss how AI approaches can advance predictability and early warning capabilities,
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Present examples of how your work supports applications or is integrated into decision-making contexts.
Abstract submission deadline: Thursday, 15 January 2026, 13:00 CET
Session link: Session AS1.4
The session is convened by Pauline Rivoire (University of Lausanne, Switzerland), with co-conveners Daniela Domeisen (University of Lausanne / ETH Zürich, Switzerland), Marisol Osman (Universidad de Buenos Aires, CONICET, CNRS, IRD – CIMA, Argentina), Steffen Tietsche (European Centre for Medium-Range Weather Forecasts, Germany), and Christopher White (University of Strathclyde, United Kingdom).
We strongly encourage all teams to submit an abstract, whether your results are already public on the leaderboard or you are still gearing up for participation.