AI / ML for Carbon Cycle Science -- CfA EGU 2026

[Vitus Benson]

Dear colleagues,

we want to highlight a session for this years EGU and invite you to submit an abstract:

Call for Abstracts: Machine Learning for Carbon Cycle Science at EGU 2026

💭 How can machine learning help us better understand and monitor the carbon cycle? Session ITS1.10/BG10.6 — "Machine learning and hybrid modelling for carbon cycle science, monitoring and carbon market policy" — at EGU 2026 (Vienna, 3–8 May) brings together researchers working on this question, from greenhouse gas estimation and ecosystem monitoring to carbon market verification and climate policy.

We welcome contributions on:
- Hybrid approaches combining ML with process-based understanding
- Uncertainty quantification and trustworthy ML for Earth systems
- Biomass, forest, and wetland monitoring
- Carbon markets, crediting, and verification
- Earth observation and multi-scale data integration

🧠 Whether you're developing new methods or applying ML to real-world carbon challenges, we'd love to see your work. We're particularly keen to foster exchange between climate scientists, remote sensing specialists, ecologists, industry, policymakers, and the AI community.
🗓️Abstract deadline: 15 January 2026, 13:00 CET
➡️Session link: https://meetingorganizer.copernicus.org/EGU26/session/52889
Conveners: Carlos Rodriguez-Pardo, Kasia Tokarska, Amirpasha Mozaffari, Vitus Benson, Kai-Hendrik Cohrs

We look forward to receiving your contributions!

Best wishes,

Vitus