Meteorological Satellite Conference '26: Advancing Contrail Detection with Meteosat-12/FCI and GEO Satellite Constellations
Updated: 10 minutes ago
Darmstadt, Germany - September 2026
At the Meteorological Satellite Conference 2026, Hugues Brenot from the Royal Belgian Institute for Space Aeronomy presented groundbreaking work on satellite-based observation algorithms titled "An early warning algorithm for aviation hazard monitoring using MTG-I1/FCI within a multi-sensor GEO–LEO web interface". Developed with support from the E-CONTRAIL 2 project, this research marks a significant step forward in monitoring non-CO2 aviation climate forcing, specifically persistent ice contrails.
While aviation's climate impact is driven in part by CO2, non-CO2 effects such as contrail formation and radiative forcing represent a major environmental factor. Effective mitigation requires accurate, real-time detection of regions susceptible to persistent contrails.
Key Takeaways for E-CONTRAIL 2:
Geostationary High Temporal Resolution: Historically, high-selectivity detection relied on Low Earth Orbit (LEO) hyperspectral sensors (such as IASI and TROPOMI), which suffer from long revisit times. By extending retrieval techniques to Geostationary (GEO) sensors like MTG-I1 (now Meteosat-12) /FCI (as well as MSG/SEVIRI and Himawari-9/AHI), the algorithm delivers continuous, high-frequency observations over full disk coverage.
COBRA & Ice Index RGB Composites: The Covariance-Based Retrieval Algorithm (COBRA) utilizes 8 thermal infrared channels to separate spectral signatures of ice particles from underlying atmospheric background. This enables the creation of new RGB composites combining mineral dust, SO2, and an ice index specifically tuned to capture contrail evolution and thin ice clouds.
Machine Learning & Tracking: Satellite retrievals are integrated with Machine Learning (ML) models for automated contrail detection and tracking.
Operational Monitoring Interface: These products feed directly into the SACS / NAMSAT web-based interface (sacs.aeronomie.be), providing near-real-time (NRT) satellite data to assess aviation climate impacts dynamically across global flight corridors.
By bridging cutting-edge geostationary satellite imagery with advanced ML algorithms, E-CONTRAIL 2 continues to advance the scientific foundation for climate-optimized flight planning.
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