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Register now for the EGU26 Peer Support programme!
  • 28 October 2025

Applications are now open for experienced attendees to apply to be a part of the EGU26 Peer Support programme. The Peer Support programme, formerly called the mentoring scheme, helps experienced attendees of the General Assembly to facilitate novice attendees in getting the most out of their experience during the week of the meeting. Submit your application by 31 March 2026.


Latest posts from EGU blogs

Living with a restless giant: The challenge of multi-risk management and communication at Campi Flegrei Volcano

Nestled within one of Europe’s most densely populated regions, the Campi Flegrei caldera is a volcanic system whose secular unrest shapes the daily life of its inhabitants. Here, during the last decade and still ongoing crisis, ground uplift, frequent earthquakes, and persistent gas emissions interact to create a complex, evolving multi-risk environment. These natural hazards rarely follow simple patterns: they overlap, cascade, or unfold independently, challenging scientists, authorities, and communities alike. As the ongoing unrest intensifies, long-standing questions about forecasting, …


Türkiye’s Climate at a Crossroads

Climate change is often described as a challenge of the future. Yet through our latest work, we’ve realized the future is already unfolding across Türkiye’s landscapes and climates. The signs are visible in the shifting seasons, intensifying heatwaves, and changes in rainfall… As one of the authors of the study “High-Resolution Projections of Bioclimatic Variables in Türkiye: Emerging Patterns and Temporal Shifts” led by Prof. Ünal, I would like to share with you what we found and why it matters. …


Harnessing Machine Learning to Advance Tropospheric Ozone Science

Machine learning (ML) and Artificial Intelligence (AI) offer powerful tools to address long-standing scientific challenges. At the molecular scale, we’ve seen projects like AlphaFold discover unknown protein structures and how they might interact with other molecules. At the planetary scale, ML-driven models like GraphCast (Google), AIFS (ECMWF) and ACE (Allen Institute for AI) are revolutionizing weather forecasting with predictive skill and lead times outperforming our leading numerical weather prediction systems. The recent development of AI foundational models, such as Aurora …