This session connects scientists from multiple disciplines to advance our understanding of atmospheric and oceanographic processes in coastal and open-ocean environments, across different time and space scales. We encourage contributions that integrate diverse approaches like numerical models (including coupled systems and Digital Twins), observational strategies (in situ, remote sensing), and data-driven methods (e.g., machine learning) to tackle complex phenomena such as extreme weather events, air-sea interactions, and coastal-to-global circulation (both in the atmospheric and marine environments). We also explicitly encourage contributions addressing climate-scale variability and change, including long-term trends, variability modes, and their representation in coupled atmosphere–ocean modelling frameworks. Topics may include, but not limited to, extreme weather events, heatwaves, sea-level changes, coastal circulation, and cross-disciplinary methods for operational forecasting and climate impact assessments. Special attention will be given to applications bridging weather and climate timescales, including prediction systems, climate services, and decision-support tools for mitigation and adaptation strategies. By fostering a collaborative framework, we aim to explore innovative solutions for early warning systems, operational applications, and long-term environmental strategies.

Potential topics include, but are not limited to:
• Extreme weather events (including tropical cyclones, severe wind and wave storms)
• Heatwaves (marine and atmospheric) and their interactions
• Sea-level changes, storm surges, and coastal flooding
• Coastal circulation and sediment dynamics
• Cross-disciplinary methods for operational forecasting and climate impact assessments
• Climate variability and change in atmosphere–ocean systems (e.g. teleconnections, long-term trends, extremes attribution)
• Coupled modelling and climate services applications (e.g. seasonal-to-decadal prediction, digital twins, adaptation and mitigation tools)