Workshop : 03/11/2025 - 07/11/2025

Institut d’Études scientifiques de Cargèse , Corsica, France

Numerical Wildfire and AI Weather2025

Numerical Wildfire and AI Weather is a small, high-level scientific workshop bringing together leading experts in weather AI, numerical wildfire forecasting, and fire-atmosphere interactions. The workshop is designed as an intensive, on-site event. Unlike large conferences, this small-group format allows for extended scientific exchanges, joint project work, and a strong interdisciplinary approach. The goal is to bridge the gap between cutting-edge research and operational needs by focusing on real-world applications of AI, numerical modeling, and risk assessment.

The first two days will focus on wildfire science, exploring fire-atmosphere interactions, numerical fire spread models, and operational forecasting challenges. Experts will discuss the latest advancements in fire behavior prediction, risk assessment, and real-time monitoring.

The next two days will shift towards AI-driven forecasting of extreme weather events, with sessions on machine learning methods and applications for high-impact meteorological phenomena. Topics include AI-enhanced numerical weather prediction, uncertainty quantification, and applications for emergency response.
The final day (morning) will synthesize findings and make contact with practitioners in France and Corsica.

🔥 Key Topics:

• Coupling fire dynamics with high-resolution weather models
• AI-driven forecasting for wildfire behavior and extreme weather events
• Physics-based and data-driven fire propagation models
• Risk analysis and hazard mapping for fire-prone regions
• Uncertainty quantification and ensemble forecasting for wildfires
• Real-time fire monitoring and prediction systems
• Machine learning approaches for wildfire data assimilation
• Wildfire resilience strategies for urban and peri-urban environments
• Operational decision support systems for emergency response
• Impact of climate change on wildfire behavior and frequency
• Integration of AI with traditional numerical weather prediction models